A Guide to the Psychology of Eating 9781350125100, 9781350125117, 9781350125148, 9781350125124

Table of contents :
Cover
Half Title
Series
Title
Copyright
Contents
Figures
Tables
About the Authors
Preface
Acknowledgments
Chapter 1 Your Appetizer: An Introduction to the Psychology of Eating
Chapter 2 Recipe for Success: Research Methods and Food Studies
Chapter 3 Top Chef Paleolithic: Evolutionary Psychology and Eating
Chapter 4 This Is Your Brain on Food: The Biopsychology of Eating
Chapter 5 Savor the Flavor: Gustation and Olfaction
Chapter 6 Variety Is the Spice of Life: Cognitive Psychology and Eating
Chapter 7 L’appétit vient en mangeant: Learning Processes in Consumption
Chapter 8 The Apple of My Eye: Child Development and Eating
Chapter 9 “When in Rome …”: Social Influences on Eating
Chapter 10 Overnutrition and Public Health
Chapter 11 Beyond the Golden Cage: Eating Disorders
Chapter 12 Eating Is Necessary, and Cooking Is an Art: The Origin of Cuisine
Bibliography
Index

Citation preview

A Guide to the Psychology of Eating

Also Available from Bloomsbury Food Studies, Willa Zhen The Psychology of Overeating, Kima Cargill Why Food Matters, Edited by Melissa L. Caldwell

A Guide to the Psychology of Eating Leighann Chaffee and Stephanie da Silva

BLOOMSBURY ACADEMIC Bloomsbury Publishing Plc 50 Bedford Square, London, WC1B 3DP, UK 1385 Broadway, New York, NY 10018, USA 29 Earlsfort Terrace, Dublin 2, Ireland BLOOMSBURY, BLOOMSBURY ACADEMIC and the Diana logo are trademarks of Bloomsbury Publishing Plc First published in Great Britain 2022 Copyright © Leighann Chaffee and Stephanie da Silva, 2022 Leighann Chaffee and Stephanie da Silva have asserted their rights under the Copyright, Designs and Patents Act, 1988, to be identified as Authors of this work. For legal purposes the Acknowledgments on p. xi constitute an extension of this copyright page. Cover image © Renate Vanaga, Unsplash Cover design: Graham Robert Ward All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage or retrieval system, without prior permission in writing from the publishers. Bloomsbury Publishing Plc does not have any control over, or responsibility for, any third-party websites referred to or in this book. All internet addresses given in this book were correct at the time of going to press. The author and publisher regret any inconvenience caused if addresses have changed or sites have ceased to exist, but can accept no responsibility for any such changes. A catalogue record for this book is available from the British Library. A catalog record for this book is available from the Library of Congress. ISBN: HB: 978-1-3501-2510-0 PB: 978-1-3501-2511-7 ePDF: 978-1-3501-2512-4 eBook: 978-1-3501-2513-1 Typeset by Newgen KnowledgeWorks Pvt. Ltd., Chennai, India Printed and bound in Great Britain To find out more about our authors and books visit www.bloomsbury.com and sign up for our newsletters.

Contents

List of Figures List of Tables About the Authors Preface Acknowledgments

vi vii viii ix xi

1

Your Appetizer: An Introduction to the Psychology of Eating

1

2

Recipe for Success: Research Methods and Food Studies

20

3

Top Chef Paleolithic: Evolutionary Psychology and Eating

47

4

This Is Your Brain on Food: The Biopsychology of Eating

71

5

Savor the Flavor: Gustation and Olfaction

98

6

Variety Is the Spice of Life: Cognitive Psychology and Eating

7

L’appétit vient en mangeant: Learning Processes in Consumption 142

8

The Apple of My Eye: Child Development and Eating

166

9

“When in Rome …”: Social Influences on Eating

190

10

Overnutrition and Public Health

212

11

Beyond the Golden Cage: Eating Disorders

236

12

Eating Is Necessary, and Cooking Is an Art: The Origin of Cuisine 259 Bibliography Index

120

279 353

Figures

1.1 1.2 2.1 2.2 3.1 3.2 4.1 4.2 4.3 4.4 5.1 5.2 5.3 6.1 6.2 7.1 7.2 8.1 8.2 9.1 9.2 9.3 10.1 11.1 12.1 12.2

The psychology of eating The biopsychosocial approach The scientific method Diagram of research design Hominin evolution timeline Image of foraging bee Metabolism and energy reservoirs Image of the ob knockout mouse model for obesity Brain structures and anatomy for regulating eating Communication between hypothalamus and brain networks Image of the tongue and papillae The gustatory pathway The olfactory pathway Image of citrus fruits Memory model diagram Diagram of flavor-flavor and flavor-nutrient associations Four components of observational learning Graph of breastfeeding benefits on motor development Structural model of behavioral tendencies based on negative affect Social influences diagram Routes of persuasion diagram Nutritional quality and nutritional messaging of kid foods in Canada Biopsychosocial explanation for overnutrition Diagram of the biopsychological etiology of eating disorders Image of spices Degrees of food insecurity

6 10 22 29 50 56 76 79 81 82 100 101 107 122 134 147 157 174 186 191 198 205 224 249 261 268

Tables

1.1 Subdisciplines of psychology and example questions relevant for the study of eating 1.2 Macronutrients, their energy yield, and description 2.1 Pasteur’s quadrant of scientific inquiry 2.2 Key considerations in research design 3.1 Emotions and their potential functions in consumption 4.1 Principles of nervous system function 4.2 Hypothalamus functions for regulation of feeding 4.3 Neuropeptide signals, functions, and actions 8.1 Developmental stages and typical patterns of eating

7 12 25 26 64 73 82 83 172

About the Authors

Leighann R. Chaffee is an associate teaching professor in psychology at the University of Washington Tacoma, in Tacoma, Washington, United States. As an educator, she employs perspectives from psychology and neuroscience to promote student persistence and success from the classroom, to the research lab, and in study abroad programs. Stephanie P. da Silva, PhD, BCBA-D is a professor in the Department of Psychology, Columbus State University, in Columbus, Georgia, United States. Dr. da Silva teaches undergraduate courses in research methods, behavior analysis, and the psychology of eating. She enjoys spending time with her family, playing tennis with friends, and jogging to podcasts … and she loves food. Authorship order is presented alphabetically and does not reflect relative contributions.

Preface

Eating and drinking are necessary, everyday components of our life, yet undergraduate coursework in psychology largely omits coverage of these topics. Elective classes about sex, drugs, and film are common while the university curriculum rarely dedicates coursework to the psychology of eating. In line with Virginia Woolf’s words, “One cannot think well, love well, sleep well, if one has not dined well,” recognition of the central role of food and drink in human experience is on the rise. Psychology of eating research has thrived in the past three decades with an awareness of eating in the study of motivation, emotion, and health. Increased knowledge of the cognitions and behaviors around food and consumption confirms the base upon which the psychology of eating is built. Our motivation for writing this book is to support the scholarly investigation and teaching of eating in psychological science. As the psychology of eating rarely functions as an independent area of study, we pull together information from several related disciplines to summarize and advance current understanding of consumption and provide rationale for greater investment in the psychology of eating. This text complements existing resources on eating that emphasize clinical manifestations of disordered eating or advice for health and nutrition. Though clinical and dietary topics are important, they provide a small window into the larger roles of foods and drinks in our lives. A broader purview through the lens of psychology and its traditional subdisciplines is provided by this text, resulting in a comprehensive treatment of consumption and its bidirectional influences in human life. Finally, the authors Leighann R. Chaffee and Stephanie P. da Silva are dedicated to the art and craft of teaching and thus have incorporated student-focused and evidencebased approaches to the presentation of material in the book and ancillary resources. Just as home cooks rely on their go-to recipes and restaurant chefs rely on their star dishes, this text adheres to our strengths in providing an academic, in contrast with a self-improvement, perspective. The goal is to synthesize evidence on typical patterns of eating and relations with our food world rather than a focus on disordered eating. While we hope this material is personally relevant for you and is illustrated by examples in your life, we take a scholarly and scientific approach to best serve the students and scholars who we hope will read this text. As you read, you will recognize each chapter is structured as a meal. The major topics of the meal comprise its “courses,” similar to a salad or pasta course at a restaurant. As meals are more than the entrée, so is each of our chapters. A chapter begins with “whet your appetite” questions to sharpen your interest in the chapter themes, along with the

x

P r ef a c e

chapter menu that lists content comprising the meal. The first section of each chapter is the “amuse-bouche,” which translates literally to mouth amuser. In a restaurant, an amuse-bouche is a bite-sized taste of food, an hors d’oeuvre, that is offered by the chef rather than ordered by the patron. The amuse-bouche provides the chef the chance to demonstrate their craft, and this section of each chapter is an opportunity to exhibit important content that is further explained within the courses of the chapter. There are three or four main courses of each chapter, similar to the content sections of a traditional textbook. Then, to conclude the meal proper, we hope you can sink your teeth into an enriching dessert that provides application of the material. After the dessert, you will find a dining review to narrow your focus to the key features of the chapter. Finally, each chapter concludes with the gochisousama, from the Japanese phrase Gochisousamadeshita, used to thank the chef for the meal. The literal translation is “it was a great deal of work (preparing the meal)” and it serves to thank all contributors to the meal, from the chef to the server and even the food itself. In these thankful conclusions of each chapter, we share a few additional resources for subsequent reading in appreciation of the scientific chefs who masterfully study the chapter topic. Ancillary materials are available through the publisher, Bloomsbury, to include supplemental content and pedagogical resources. Bon Appétit Leighann and Stephanie

Acknowledgments

From Author Leighann R. Chaffee: My appreciation in three squares—deepest gratitude to my students’ strength and curiosity to fuel me like a hearty breakfast to be a better person (and academic). Appreciation to my colleagues at UWT and the mentorship of Dr. Kima Cargill—your warmth and wisdom the nourishing lunch. Cheers to my family for the encouragement and my pals for encouraging the fun, you are the merriment of a dinner party. And to Dan, my clever companion and bottomless pit, all my love and thanks. From Author Stephanie P. da Silva: To my family

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Chapter 1 Your Appetizer: An Introduction to the Psychology of Eating Whet Your Appetite: Food Science What is the psychology of eating and for whom is it relevant? Brainstorm the topics that are encompassed by the psychology of eating and how these topics may be similar or different than those studied in nutrition. What is the service of applying a scientific approach to the psychology of eating? In this chapter, the scope of the psychology of eating is defined to better understand the goals of the field and this text.

Menu Amuse-Bouche: Are Bugs Food? Course 1: Essential Roles of Food and Eating Focus on Food Food Studies as an Interdisciplinary Field Course 2: Contributions of Psychology Course 3: The Study of Nutrition Dessert: What Does “Healthy” Mean? Dining Review Gochisousama Glossary

1 2 2 4 5 11 15 17 18 18

Amuse-Bouche: Are Bugs Food? Do you consider bugs to be food for yourself and for others? Historically, insects have been classified as nonfoods among European and North American countries, yet entomophagy is common in regions of Asia, Africa, Latin America, and Australia. In fact,

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over 3,000 ethnic groups, or over 2 billion people, worldwide consume insects (Akhtar & Isman, 2018; Ramos-Elorduy, 2009). Attempts to popularize entomophagy in areas where it is not practiced face barriers rooted in insect-driven disgust, fear of disease, and social norms (Jensen & Lieberoth, 2019). This rejection of a new food demonstrates a psychological barrier, rather than a logical or health concern (Belluco et al., 2013). But the 21st century has brought newfound openness to entomophagy, and consumption of crickets has gained particular traction around the world (Halloran et al., 2016). The present efforts to encourage insect consumption are based on sustainability of protein sources given global population growth. Imathiu (2020) argues that insects can address the first three of the United Nations (2015) Sustainable Development Goals: No Poverty, Zero Hunger, and Good Health and Well-being given their benefits for food accessibility (Gahukar, 2011) and favorable nutrition profile (Dobermann, Swift, & Field, 2017). Different resources are required to produce various animal proteins, and insects require less water, feed, and land than cattle, swine, and poultry (Dobermann, Swift, & Field, 2017). Crickets are easy to grow, transport, and consume. Roasted and salted, they are reminiscent of sunflower seeds, or they can be ground into a powder to fortify other foods (e.g., adding protein to flours). Although negative connotations remain for some potential consumers, specific education and communication about personal and societal benefits can soften resistance to entomophagy.

Course 1: Essential Roles of Food and Eating This chapter began with questions about the relevance of studying eating from the perspective of psychological science. It is hoped that by the end of this chapter, and certainly by the end of this text, you agree investigating and understanding eating is a worthy endeavor. In our image-conscience world, a great deal of focus is placed on the weight-related implications of eating habits. Though the topic of weight appears occasionally in this text (e.g., in Chapter 10), the focus is more broadly on experiences with food and eating, and resulting bidirectional relations between consumption and physical and mental well-being. Nearly all humans consume foods and drinks daily, making the experience an essential and core part of being. To understand human nature, we need to understand eating.

Focus on Food What did you eat for your last meal? And why did you choose that instead of something else? The question of food choice is an overarching theme in the psychology of eating and this text. How many food decisions do you make each day and what drives these

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choices? Food choices provide a window into our identity and have significant bearing on our health and well-being. Researchers, such as Ogden (2003), describe the meaning of food across dimensions addressed in this text: Food Classifications. The question of whether or not we eat insects (and other arthropods) demonstrates the most basic classification of an item as a food or nonfood. Insect eating occurs in 130 of the world’s nations, though classification of insects as a nonfood still holds firm among many North Americans and Europeans. A diet, by definition, identifies acceptable and unacceptable foods, and cultural expectations are established regardless of whether we are consciously following a specific diet with rules explicitly stated or implied. The role of emotion and culture in eating is studied extensively by Paul Rozin, who identified four bases for food rejection as distaste, danger, disgust, and ideation (Rozin & Fallon, 1980). In some cuisines, specific food items are classified by the meals or occasions when consumed. Author Stephanie da Silva, referred to as SS throughout the text, sometimes makes traditional breakfast foods, such as eggs and pancakes, in the evening for her family. The “breakfast for dinner!” announcement is met with enthusiasm when, in reality, it is just dinner. The fundamental aspect of these classifications is in defining food or drinks as appropriate for the occasion. Food as a Feature of the Self. You have likely heard the common phrase “you are what you eat,” but you may not be familiar with “Good food is the foundation to genuine happiness.” This is a famous quote by Auguste Escoffier (1846–1935), French restauranteur, chef, and writer, credited with elevating both French cuisine and cooking as a career path. This approach demonstrates the pleasure and enjoyment in eating, observable through conflicts around self-control and morality (Ogden, 2003). For example, the understanding that “most people both eat and care about animals” is often observed in guidance around the consumption of animal proteins (Loughnan et al., 2014). Individualized meanings of food are grounded in personal and social identity and influenced by the psychological processes described throughout the text. Further goals of this text are to explore food as social interaction and food as cultural identity, and this discussion of communication through food is apparent in the later chapters. In psychology, culture is defined as the shared attitudes, behaviors, values, and traditions within a group of people or a community that are passed to subsequent generations. Food can serve as a social marker, as cuisine is a clue to our cultural group and an opportunity for social exchange. Groups often identify themselves by the food they offer; this role of food is noteworthy for immigrant groups, as sharing of food provides an avenue to demonstrate solidarity and simultaneously preserving ethnic identity (Rozin, 1996). Food and drinks are a core aspect of celebrations as well as religious practice and rituals. Culture influences both our context and our food choice, and inclusion of cultural perspectives benefits all types of research in psychology.

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Food Studies as an Interdisciplinary Field The psychology of eating is complemented by evidence from food studies and from the study of consumption. Food Studies as an academic field is interdisciplinary in nature, with the goal to understand the relationships between food and the human experience (Miller & Deutsch, 2009), including perspectives from anthropology, history, economics, social sciences like psychology and sociology, plus nutrition. Multidisciplinary theories and methods are synthesized in food studies scholarship. Food studies scholars investigate not only to learn about the topic of food but also to apply food as a methodological tool, as the foods we eat, produce, and prepare for consumption provide insight into the human experience (Miller & Deutsch). Food provides a window into identity—interrogation of personal sentiments around entomophagy highlights the advantages of a multidisciplinary approach. Food studies considers forces that influence food choice beyond the individual from the following perspectives: ●

●

●

●

●

Anthropology, the study of humanity and diversity, as well as our evolutionary origins, may inquire about the nature of our current diet, the ways it diverged from our ancestors, and the practice of entomophagy. History studies and interprets past events in the present context, noting the records and time course of eating and harvest practices, such as the consumption of insects. Economics examines the way people use resources and respond to incentives, providing insight to the costs and benefits of consuming insects for energy. Sociology investigates the structure and function of human societies, and the potential for social organizational structures like politics, religion, and education to influence our behavior, such as the consumption of insects. Nutrition, the study of how diet impacts human health, helps us understand the potential benefits or consequences of consuming a specific food item like insects.

Chew on This: Agreeable to Arthropods? Author Leighann Chaffee, referred to as LC throughout this text, grew up in Alaska and lives and teaches in Washington State, where she employs the example of Dungeness crab to illustrate aspects of food choice and entomophagy. Despite the fact that these odd-looking arthropods are a bit like giant bugs from the sea, we readily devour them as a delicacy. The disciplinary perspectives of food studies provide insight into the consumption patterns of these tasty crustaceans. The bounty of Dungeness crab sustains both diet and culture of Indigenous groups of the Pacific Northwest, especially since salmon fishing was limited by habitat destruction. Today, tribal economies and nontribal fishermen depend on Dungeness as the most valuable seafood harvest on the West Coast (NOAA, 2020). Dungeness crab is a

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notable example of an unlikely food source—they are bottom dwellers with big claws, thus harvesting them requires special knowledge and tools. Once obtained, their meat is difficult to access due to the hard shell. But inside is a source of protein and omega-3 essential fatty acids. The harvest and preparation typically involve ritual by Indigenous people and non-Indigenous folks alike, and they are commonly consumed as a special occasion or holiday feast. The psychology of eating complements this evidence by providing additional understanding of food choice.

Course 2: Contributions of Psychology Psychology aims to advance our understanding of mental processes and behavior, through research and application, to help people and communities thrive. Professional psychologists work in diverse settings, from academic psychologists and researchers like the authors of the text, to clinical and counseling settings, schools, nonprofits, and the private sector. Despite the centrality of food and eating in our life, only recently has academic psychology approached the study of eating as a distinct area of interest—especially beyond the clinical approaches to disordered eating. Prior to the 1990s, ingestive behavior was studied from other, more specific viewpoints. Biological and physiological research emphasized experimental approaches to the study of nutrition and chemical senses in the 1940s and 1950s (Kissileff & Ladenheim, 2013). Simultaneous scholarship in gastronomy and anthropology called attention to the cultural implications of food and eating while industry-focused research explored topics relevant to the culinary arts and food production. Literature fully dedicated to the psychology of eating was rare at that point, one example being the first edition of Alexandra Logue’s text, Psychology of Eating and Drinking, in 1986. An edited volume on the topic was published by Elizabeth Capaldi in 1996, the same year Paul Rozin published an article, “Towards a Psychology of Food and Eating …,” in Current Directions of Psychological Science arguing that psychology had virtually ignored the integral role of consumption in understanding behavior. In the decade that followed, Jane Ogden (2003) published her book, The Psychology of Eating: From Healthy to Disordered Behavior, that included information and analysis from several subdisciplines in psychology, further solidifying the topic of food and eating as a legitimate area of study for psychologists. This specialty has blossomed since thanks to the leadership of (these and other) early pioneers and contemporary researchers who forged scholarship and a literature base dedicated to understanding food and eating as part of the human experience. Yet, as compared to other topics explored in psychology, the psychology of eating still is not unified by an umbrella organization, like a professional

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association or dominant journal (Figure 1.1). However, two key organizations that frame psychology of eating, with their related publication outlets, are: 1. Association for the Study of Food and Society (ASFS; food-culture.org): Founded in 1985, ASFS exemplifies the interdisciplinary contributions to our understanding of the psychology of eating, particularly the humanities and social sciences. This organization produces the journal Food, Culture, & Society to disseminate work related to its mission. Also see Food Quality and Preference, International Journal of Gastronomy and Food Science, and Food and Foodways. 2. Society for the Study of Ingestive Behaviors (SSIB; ssib.org): Founded in 1987, SSIB combines behavioral and biological approaches to eating, advancing basic scientific research and expertise. Journals that publish work in this area include Appetite, Eating Behaviors, Frontiers in Eating Behavior, Physiology and Behavior, Journal of Nutrition, and Chemical Senses. Professionals from these prominent organizations operate in niches that differ in purpose and scope, with ASFS emphasizing systemic application of food science (e.g., to communities) and SSIB emphasizing fundamental understanding of consumption (e.g., neurobiological processes). The gap between these biological and cultural approaches to eating is a nexus point for the psychology of eating. The psychology of eating, in line with the broader discipline of psychology, considers impact of individual psychological processes in the context of social interactions and the community (Figure 1.1). In 2013, Frontiers in Psychology began publishing its special section on Eating Behavior as an

Figure 1.1  The psychology of eating. The nexus of the psychology of eating with related disciplines and topics explored. Image created by Leighann Chaffee and Stephanie da Silva.

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outlet for psychology of eating research. Much like the present text, the Eating Behavior section addresses psychological, physiological, neurocognitive, and social aspects of human consumption, including nonclinical and clinical aspects of eating behavior (Frontiers in Psychology: Eating Behavior, 2021). In launching the special section, Meule and Vögele (2013) state its purpose is “to build knowledge for the understanding of eating behavior by bringing together academics with different expertise,” such as basic researchers and practitioners, and increase “awareness of a more comprehensive view on eating behavior.” The purpose and scope of these previously established sources on psychology of eating are consistent with the content and goals of this text. Table 1.1 defines the major subdisciplines of psychology, their goals, and questions about eating that represent each perspective. The sample questions are actual questions addressed by experts in the field and in this text.

Table 1.1  Subdisciplines of psychology and example questions relevant for the study of eating Area of psychology Goal (chapter)

Questions addressed

Evolutionary psychology (3)

Apply principles of natural selection to understanding psychological processes

Why do humans, but not our primate relatives, cook food over fire? Why can only some adults tolerate dairy products?

Biopsychology (4)

Understand the biological How come some foods are more satisfying basis of behavior and mental than others? Why does hunger make some processes people grumpy, or hangry?

Sensation and

Explain neural processing How does the brain make sense of the and interpretation of sensory chemicals in food that we taste and smell? information Does the presentation of food influence its acceptance and flavor?

perception (5)

Cognition (6)

Understand processes such Does food packaging, such as nutrition as thinking, language, and labels or health claims, influence our food decision making decisions? Is breakfast really the most important meal of the day?

Behavioral

Identify principles of learning Why do we experience hunger around to explain responses to the the same time each day? Do we foster environment consumption by reward and/or example?

psychology (7) Developmental psychology (8)

Describe biological and environmental factors that influence lifespan changes

How does prenatal nutrition impact food preferences and development? Does marketing impact children’s eating habits?

Social psychology (9, Recognize and demonstrate Do social norms influence our consumption how behavior is influenced patterns? Can we use the power of 10, and 12) by others persuasion to influence eating habits?

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Table 1.1  Subdisciplines of psychology and examples of questions relevant for the study of eating (continued) Area of psychology Goal (chapter) Health psychology (10 and 11)

Cultural psychology (9, and 12)

Explore processes contributing to illness and wellness of individuals and societies

Questions addressed What are the adverse consequences of weight stigma? How can we decrease the prevalence of disordered eating?

Describe influence of How does the food we eat reflect our cultural practices on identity, cultural knowledge and values? In what meaning, and ways of being ways do contemporary policies support cultural values related to eating?

The contributions of specific psychological disciplines to our understanding of eating is apparent through the example of entomophagy in the amuse-bouche. Consumption of insects is energy efficient, explored at the levels of individuals and societies in Chapters 3 and 12, yet food rejection—even disgust—occurs in response to the idea or offering. Aversion to certain foods, such as insects, is a product of beliefs about insects (Chapter 6), personal experience and development (Chapters 7 and 8), social norms (Chapter 9), and systemic access (Chapter 12). Viewing a topic, like entomophagy, from these multiple perspectives generates a more comprehensive understanding and informs potential interventions or policies. As an example, experimental methods of behavioral psychology can increase acceptance of insect-fortified food products to promote food security, and consumer perception of label claims and attitudes, studied within cognitive psychology, can optimize the cost and composition of these foods (Alemu et al., 2017).

Morsel: Plurality of Perspectives Academic pursuits have at best ignored Traditional and Indigenous Knowledge systems and at worst pirated this information without credit to the source. Traditional Knowledge emerges from generations of Indigenous experience and is observed in local customs and traditions. It originates and exists outside of the realm of modern academia and Western ways of knowing. As an example, the uses of plants, herbs, and other foods from a region to treat illness or promote wellness may be ignored or eschewed by the academic establishment, despite the fact that Traditional Knowledge and its medicines are the majority source for healthcare in developing countries (per the WHO; Poorna, Moghul & Arunachalam, 2014). Although not rigorously tested in a laboratory setting, many of the treatments derive from observations accumulated over generations and have effects that are later validated in academic laboratories. In 2015, the Nobel Prize in Physiology

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or Medicine was awarded to Tu Youyou, a Chinese scientist who determined the active antimalarial compound in the traditional herbal remedy of wormwood after consulting a 1,600-year-old historical text (Lasker Foundation, 2011). Her work resulted in the development of the modern prescription drug, artemisinin, that saved millions of lives (nobelprize.org). Regardless of their known benefits, Traditional and Indigenous Knowledge systems face significant risks in (1) extinction if not properly preserved and (2) exploitation when not managed via intellectual property protection. Thus, Traditional Knowledge archives, libraries, and databases seek to guard Traditional Knowledge from these pressures. The potential for food sources such as insects and crab to provide essential nutrients and sustainability is one illustration of the power of Traditional Knowledge. Groups who engage in entomophagy possess expertise including which species are safe for consumption, sustainable harvesting protocols, and preparation methods (Yen, 2009). Indigenous Knowledge provides critical strategies to support conservation of species and has demonstrated utility in the case of Dungeness crab and other harvests (e.g., Ban et al., 2017). Incorporating Traditional Knowledge in our understanding of eating promotes favorable attitudes toward sustainable practices, yet great care is requisite to preserve and safeguard these groups from exploitation.

Psychological explanations of a specific phenomenon, like eating, commonly are described as a biopsychosocial approach (Figure 1.2). Rather than applying a narrow theoretical perspective, a biopsychosocial explanation synthesizes: ●

●

●

Evidence on the biological basis of behavior, including evolutionary psychology and neuroscience. Behavioral, cognitive, and developmental research at the level of individuals across the lifespan. Social and cultural influences on psychological and biological processes and outcomes.

For a case in point, we will consider the biopsychosocial approach to pica, a type of eating disorder characterized by the consumption of nonnutritive substances, or eating things that are not food. A person with pica may consume large amounts of chalk, hair, or other materials. It becomes concerning when the consumption of nonnutritives competes with adequate intake of food/nutrients and/or when digestive problems (e.g., blockages) surface. To understand pica and treat it effectively, it helps to view it: Biologically: Previous explanations for pica focused on treating malnutrition, such as iron-deficient anemia, in folks who consume clay (Delaney et al., 2015), and pica can be induced by poisoning in a rodent model (Mitchell et al., 1976). However, the

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Figure 1.2  The biopsychosocial approach. The biopsychosocial influences on eating. Image created by Leighann Chaffee.

majority of patients with pica do not have anemia. Rather, the overlapping presentation of pica in children with developmental deficits, geriatric patients, and those with other psychiatric comorbidities (Delaney et al., 2015) highlights the potential for a brainbased explanation. Case studies in humans and animals confirm the potential for selective brain damage and neurotransmitter dysfunction to induce pica (Ali, 2001), though the evidence is rather incomplete. Psychologically: Traditional psychological views regard pica as a learned behavior, supported by the efficacy of behavioral interventions to reduce symptoms in those with developmental disabilities (McAdam et al., 2004). Stress tends to precede or exacerbate symptoms of pica (Rose, Porcerelli, & Neale, 2000), similar to other obsessive-compulsive behaviors and disorders. Socially: In addition to the presentation described above, pica is documented in the context of culturally appropriate ritualistic behavior (Ali, 2001), specifically in pregnant women first described in a Western medical text in 1563 (Rose, Porcerelli, & Neale, 2000). Alone, each explanation is weaker and fails to account for origins and variability in presentations of pica. But together, the biopsychosocial approach demonstrates the complexity of this disorder and aids in understanding the multiple mechanisms of its occurrence.

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Course 3: The Study of Nutrition The psychology of eating largely does not attempt to address the question of “What should we eat?” nor seek to provide dietary advice. Although the potential impacts of consumption on health are of interest within both the psychology of eating and the field of nutritional science, the approaches are largely distinct. Nutritional science emphasizes the study of the components of food, and their impact on health and disease, with an eye toward dietary strategies and recommendations. These goals of nutrition and related dietary sciences are not shared with the psychology of eating or this text. Although some foods and drinks likely will be highlighted implicitly in a more or less positive light (e.g., in relating sugar to diabetes), readers are encouraged to consider and make consumption decisions in collaboration with healthcare providers. Further, the research reviewed herein is based on populations studied and may not fit individual readers’ needs. Even if the goals of this text and nutritional science differ, readers will benefit from a working knowledge of digestion and other basic principles of nutrition science. To that end, the remainder of this section is devoted to identifying key terms and processes integrated in conversations of this text to maximize learning. Eating (appetitive and consummatory) behavior provides energy and nutrition through the food we eat, via processes of digestion and metabolism. Digestion is breaking down food, mechanically through chewing and via enzymatic actions in our alimentary, or digestive, system, into substances that can be used by the body. This system starts in the mouth, through the esophagus, stomach, and intestines. It also includes the associated glands: salivary, pancreas, gallbladder, and liver. After being chewed in the mouth, food is swallowed through the throat into the esophagus and forced ahead via peristalsis (muscle contractions). In the stomach, enzymes and hydrochloric acid break down the food with the help of even stronger peristalsis. The presence of food in the stomach makes it feel physically full (distended) and cues of satiety are further signaled by the presence of nutrients (e.g., fat, protein; Halford & Boyland, 2013). When food leaves the stomach for the small intestine, it is reduced to a thick liquid called chyme to pass through the pyloric sphincter into the small intestine. The breakdown of food in the small intestine continues via enzymes from the pancreas. The small intestine is lined with fingers called villi to increase surface area for absorption of nutrients. This means that few substances are absorbed in the stomach (besides alcohol) and, instead, in the small intestine food and nutrients, plus water and electrolytes, are absorbed into blood circulation through specialized epithelial cells (Johnson, 2013). The waste, or unusable, parts of food pass into the large intestine, or colon. The liquid part of waste is reabsorbed through the intestinal walls, the solid waste is sent along and evacuates as feces. We use the energy from foods in metabolism, the chemical processes that occur in living organisms to maintain life, providing building blocks for the cells of our body and the energy for life. The nutritional components of food used by the body are called

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Table 1.2  Macronutrients, their energy yield, and description Macronutrient

Energy yield

Types

Carbohydrate (simple and complex sugars)

4 kcal/g

Monosaccharides: glucose, fructose, galactose Disaccharides: e.g., sucrose = glucose + fructose Complex carbohydrates: starches

Protein (amino acids)

4 kcal/g

Peptides (short chains) and proteins (long chains of amino acids) Essential amino acids cannot be made in the body and must be acquired through diet

Fat (lipids)

9 kcal/g

Saturated fat: chains of all single bonds, solid at room temp. (lard) Unsaturated fat: contains double bonds, liquid at room temp. (olive oil) Essential fatty acids: obtained via diet (e.g., omega-3s and omega-6s)

macronutrients and micronutrients. The macronutrients carbohydrate, protein, and fat yield energy, commonly expressed in units known as kilocalories (kcal), though these are commonly referred to as “calories” in food. Table 1.2 shows that the energy density of foods varies based on their composition of macronutrients. Several factors impact the digestion and metabolism of food such as the composition of the foods themselves, notably the presence of fiber. After nutrients are absorbed from the alimentary canal into the blood circulatory system, they pass to the liver via the hepatic portal vein (Carlson & Birkett, 2017). One function of the liver is to detect nutrients (glucose and lipids) and coordinate with the brain to regulate hunger and metabolism. The liver makes all the cholesterol needed to help cells build hormones. Cholesterol also comes from diet when consuming foods from other animals (e.g., dairy and meat). We need sufficient cholesterol, specifically “good” high-density lipoprotein (HDL) cholesterol for body functions, without an excess of “bad” low-density lipoprotein (LDL) cholesterol. Excess cholesterol in conjunction with other risk factors (like excess body fat) contributes to hyperlipidemia, though the current epidemiological data provides little benefit to restricting dietary cholesterol to the 300 mg/day recommendation unique to the United States (Fernandez, 2012). Digestion is not possible without the function of the pancreas to produce the enzymes used by the small intestines to break down food and unlock the nutrients (the digestive enzyme known as bile is concentrated in the gallbladder). The pancreas also performs endocrine functions to produce and secrete insulin and glucagon into the bloodstream, both important for glucose metabolism (Carlson & Birkett, 2017). As you have likely observed, the energy density of a food is but one impact on our satisfaction and satiety, or fullness, after a meal. Additional discussion of the biopsychology and metabolism of consumption occurs in Chapter 4.

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Compared to macronutrients covered earlier, micronutrients refer to individual vitamins and minerals extracted from foods, drinks, and supplements consumed. Like macros, micronutrients are essential for the function of the body and obtained from different foods and food groups; for example, both milk and broccoli contain calcium. Most of the vitamins and minerals are achieved through varied diets, but some—such as vitamin D—are difficult to obtain through diet alone. Calcium and vitamin D are required early in life to support bone growth, and sustained intake offsets osteoporosis late in life (National Institutes of Health, 2018). We create or extract vitamin D via sun exposure; consumption of foods with naturally occurring vitamin D such as fish, eggs, mushrooms, and meats; and through foods and drinks fortified with vitamin D. Fortification efforts in industrialized nations occur because vitamin D deficiency is unique to places where energy-dense foods are abundant, partly as a result of increased sun safety protocols. Micronutrient deficiencies can cause severe health issues and are associated with childhood and adult malnutrition. Malnutrition causes nearly half of all global deaths in children under 5 (WHO, 2020). Specific deficiencies in iron, vitamin A, and iodine are common around the world, particularly in children, pregnant women, and those in low- and middle-income regions. In the rich and developed world, nutrition problems are more likely to present in the form of overweight and obesity, also referred to as overnutrition and discussed in Chapter 10. While 462 million adults worldwide were underweight in 2014, nearly 2 billion were overweight or obese (WHO, 2020). Paradoxically, countries with the highest rates of obesity also have a booming health and wellness industry. In the United States, the vitamin and supplement industry is worth over $100 billion (Molvar, 2018) and that number is expected to grow each year. Supplements are clearly indicated in certain cases, such as prenatal vitamins and supplements for those at risk of osteoporosis, but the majority of the folks who buy and take supplements receive little benefit. Concerns around poor regulation and lack of efficacy of these products are abundant (Nestle, 2013), and although vitamin toxicity is relatively rare (about 60,000 cases per year in the United States), more is not always better in the case of vitamins. The psychology of eating provides insight into the appeal of these products (see Chapter 2).

Morsel: Can Food Cure Disease? When foods have positive impacts beyond nutrition itself, they sometimes are called functional foods (Nelson, 2017). There is little doubt regarding benefits of eating plenty of fruits and vegetables; however, the line between behaviors that are favorable to health and medical interventions is sometimes less than clear. The goals of medicine and nutrition overlap in their desire to improve health and combat illness, although most Western medical doctors prescribe pharmaceutical products

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while many nutritional experts recommend dietary prescriptions over drugs. These distinct avenues to wellness prevent conflation of nutrition and medical practices, yet also leaves the diet and nutrition industries less regulated and consumers in more vulnerable positions. To combat malnutrition and disease, there is a push to create crop varieties with maximum nutrients and vitamins (Schaal, 2018) and food fortification addresses micronutrient shortfalls through infusion of folic acid, iron, and vitamins A and D (Berner et al., 2014; Keats et al., 2019). But there is care in keeping distinct the downsides of deficits and upsides of excess. Not only are chronic deficiencies of particular vitamins, except vitamin D, unlikely in societies with energy-dense foods (e.g., fortified cereals, juices), there is little evidence of benefits from excess vitamins and minerals. And, though rare, some vitamins can have negative effects when consumed in excess (Baker et al., 1990; Hayes, 2008). Further, many vitamins and supplements are manufactured without regulation, leaving quality control a real concern. Trends in food prescriptions can come and go as new evidence indicates a promising ailment fix. Many arise from legitimate initial laboratory evidence but exaggerated outcomes develop over time. Grand claims surround consumables, from fish oils and apple cider vinegar to specific vitamins and minerals (e.g., Goggins, 2016). To a large extent, these dietary changes are attempts to prevent or thwart disease or medical conditions. Vitamin C is an example of a popularly touted supplement for benefits like combating the common cold, but its powers are largely unsubstantiated when tested carefully (Hemilä & Chalker, 2013). Food and supplement fixes were especially appealing during the COVID-19 epidemic when consumers sought methods of protection against the virus and resulting illness. Vitamin D, zinc, and elderberry were esteemed with abilities to minimize susceptibility to COVID-19, while research illustrated these substances fall short of their functional reputations (Adams, Baker, & Sobieraj, 2020). In Chapter 2, critical evaluation of such claims is addressed to strengthen your immunity to them.

The study of nutrition and diet is challenging for several reasons. Few scientific disciplines face the same cultural, religious, political, and business implications as nutrition, and these influence the ethics of studying what we eat and providing recommendations (Rucker & Rucker, 2016). The study of nutrition is limited by practical obstacles such as recording precisely what and how much people eat; specific challenges are identified in Chapters 2 and 6. Even the act of recording what you eat can alter your normal habits, perhaps this is a phenomenon you have experienced when trying out a nutrition app. There is no doubt that diet quality is associated with positive outcomes for physical and mental health, but the lack of consensus around

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the definition of a healthy diet is evident when appraising convoluted nutrition advice we hear throughout our lifetimes. One important differentiation is that between energy density and nutrient density; an energy-dense diet is likely to be high in refined grains, added sugars, and added fats, whereas a diet of whole grains, lean protein, and fresh fruits and vegetables has lower energy density (Darmon & Drewnowski, 2008). Which diet is of better quality? Note the lower energy diet described is likely to have more nutrient density, including micronutrients and a more optimal balance of macronutrient building blocks. The challenge of defining a healthy diet is further explored—perhaps ironically—in the Dessert section of this chapter. An essential take-home message from our explanation of the psychology of eating is its distinction from the study of nutritional science. Like any good science, the psychology of eating explains what is known or understood, tentatively at this time, about the reasons why we eat and drink. Nutrition and psychology complement each other, but the psychology of eating does not provide advice on what should be eaten for health, moral, financial, or other reasons. Remember the question of “Are bugs food?” posed at the start of this chapter? Answering this question from the perspective of nutritional sciences alone is relatively simple, as the insects consumed in some areas of the world, such as crickets and mealworms, meet standards for food safety, provide protein on par with other sources of meat, and supply various micronutrients (Dobermann, Swift, & Field, 2017). This answer to the question fails to capture the psychological processes of food classification, acceptance and rejection, as well as the complex cultural determinants and implications of entomophagy.

Dessert: What Does “Healthy” Mean? If you were asked to define a healthy diet, what would your focus be? Would you identify foods consumed or those avoided? Would you include macronutrient and micronutrient recommendations, or amounts of certain foods or groups for consumption? “Health” and “healthy” are difficult to define through the lens of psychology. Health relates to well-being, physical and psychological, as holistic approaches to health promotion integrate the mind and the body (CDC, 2018). Physical well-being is associated with longevity, self-perceived health or absence of illness, social connectedness, and productivity. The overlapping construct of psychological well-being encompasses positive emotion (happiness), engagement, relationships, meaning and purpose, plus accomplishment (Seligman, 2011). Unfortunately, the term healthy is applied far too broadly in our modern world, and the indiscriminate use of this term has stripped its meaning. Defining certain foods as healthy or unhealthy is one example of the food classifications described above, embedded in cultural values and personal food ideals. Many folks are dedicated to consuming a “healthy” diet, and our ideals about proper meals influence food selection (Devine et al., 1999). Food choice is largely defined by the

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taste of a food (sensory properties), health of the food (utility), and the resources (time, money, knowledge) required to obtain that food (Connors et al., 2001). Attention to the health outcomes associated with diet began with attention to the overweight epidemic in the 1990s (Rozin et al., 1999). At present, suboptimal diet is the leading cause of death globally, so the stakes are high to consume a proper diet. Dietary guidelines are provided by governmental organizations such as the Centers for Disease Control and Prevention (CDC) and the World Health Organization (WHO), based on systematic reviews of current scientific evidence. These reviews result in recommendations such as the following from the WHO (2020) for a healthy diet: ● ●

●

●

●

Fruit, vegetables, legumes, nuts, and whole grains At least 400 g (5 portions) of fruit and vegetables per day (excluding potatoes, cassava, other starchy roots) Less than 10% of total energy intake from free sugars, equivalent to 50 g per person per day Less than 30% of total energy intake from fats, though unsaturated fats are preferable to saturated fats Less than 5 g of salt per day (should be iodized)

These recommendations are further tailored for children and pregnant women, and additional information is available from healthcare providers for people with specific nutritional needs. Are these recommendations straightforward? How do they align with your own definition of “healthy”? It is actually easier for most people to define a nutritionally poor-quality diet, characterized by low intakes of fresh fruit, vegetables, nuts, and whole grains with higher intakes of processed foods and added sugars and fats (de Ridder et al., 2017), than a high-quality diet. Knowledge of nutrition is one predictor of consistent healthy diet, but this knowledge does not prevent people from eating unhealthy foods, and the majority of people in industrialized countries do not meet nutritional standards (de Ridder et al. 2017). We learn about foods from family and friends, the media, health professionals, and health education in schools. Despite the complex nutritional information presented to the public over time, research studies show fairly accurate knowledge base and understanding of recent guidelines in the general public (de Ridder et al.). However, many consumers find it difficult to discern between evidence-based dietary advice and misinformation (Evers & Carol, 2007) and do not readily apply these guidelines to their own diet (de Ridder et al.). Confusion over dietary advice is demonstrated by transitions and flip-flops in dietary advice and prevailing attitudes around food items, exemplified by eggs, wheat, and fats (Mozaffarian & Forouhi, 2018). Increases in the average person’s attention to the nutrient composition of their food, for instance by reading the labels, can promote the attitude of nutritionism, as the value of a food is judged solely by the specific macronutrients and micronutrients it contains. Yet a single nutrient within a food is unlikely to have significant health protective

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effects, especially when compared to the detrimental effects of overeating. Views of the healthfulness of an individual food are influenced by social factors and culture— the categorization of individual foods as healthy or unhealthy is a perspective rather unique to the United States (Rozin, 1999). You can likely easily classify dessert within this dichotomy. Unfortunately, research on the health effects of individual food items is often reported in a misleading, incomplete, or sensationalized manner. Reliance on nutritionism is problematic because it emphasizes individual choices yet fails to consider the full impacts of our eating habits and diet on health. A psychological consequence of nutritionism is the propensity to reach false conclusions about the effects of food items or ingredients, such as inaccurate prevailing notions that eating turkey causes drowsiness due to tryptophan and that superfoods can detoxify the body. A major goal of the next chapter is to develop skills in evaluating the research and claims around food and eating. Then the psychological predictors, such as knowledge, motivation, emotions, attitudes, and habits, of a high-quality diet are explored (de Ridder et al., 2017). By the end of the text, you will be well versed in the cognition and motivations that drive food choice, as well as the associated outcomes of those choices.

Dining Review Key Elements

Recommended Reviews

Whet your appetite: Food science

Now that we have concluded the chapter, what is the benefit of applying a scientific approach to the psychology of eating?

The amuse-bouche

Do you practice entomophagy? Does your diet include any other arthropods? Identify types of appeals to encourage your acceptance of consuming insects as food.

Course 1: An introduction

How do the various interdisciplinary perspectives of food studies supplement psychology in the study of food and eating?

Course 2: Psychology

Define the field of psychology and the biopsychosocial approach to the study of eating. Apply the four dimensions (food classifications, food as a feature of the self, food as social interaction, and cultural identity) to your own experiences with food and eating.

Morsel: Plurality of perspectives Find an additional example of Traditional Knowledge that is overlooked by contemporary academic perspectives. Course 3: Nutrition

What are the goals of the study of nutrition? Why is it so challenging to accurately measure dietary intake and associated impacts on health?

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Key Elements

Recommended Reviews

Morsel: Can food cure

Explore a functional food claim you have heard (maybe through a friend or family member). What does evidence state about it?

disease? Dessert: Healthy

Can you identify examples of terms in addition to the word “healthy” that are poorly defined in our food system? Find an additional example of nutrition guidelines and contrast with the WHO recommendations that are shared.

Gochisousama Thanks to the chef! Recommended reading: ●

●

●

An introductory psychology textbook, such as Laura King’s The Science of Psychology: An Appreciative View. McGraw Hill. Paul Rozin’s rationale for the study of the Psychology of Eating: Rozin, P. (1996), “Toward a psychology of food and eating: From motivation to module to model to marker, morality, meaning, and metaphor.” Current Directions in Psychological Science, 5(1): 18–24. For an engaging tour of the alimentary canal: Mary Roach’s (2013) Gulp. W. W. Norton.

Glossary Biopsychosocial approach:

a psychological perspective embracing the biological, psychological, and social contributions to the phenomenon of interest

Culture:

the shared attitudes, behaviors, values, and traditions within a group of people or a community that are passed to subsequent generations

Digestion:

the process of breaking down food, using mechanical and enzymatic action in the alimentary system, into substances the body can use

Energy density:

in foods, the amount of kcal per weight of a food item

Entomophagy:

the practice of eating insects

Food studies:

an interdisciplinary academic field with the goal to understand the relationships between food and the human experience

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Functional foods:

foods, substances consumed, with medicinal properties or benefits; also known as nutraceuticals

Macronutrients:

the nutrients we use in the largest amounts, including carbohydrates, fat, and protein

Metabolism:

chemical processes that occur within a living organism to maintain life

Micronutrients:

essential vitamins and minerals required in various quantities for our body to function

Nutritionism:

a paradigm of understanding food in which the value of a food item is determined by the individual nutrients it contains

Pica:

type of disordered eating marked by consistent and developmentally inappropriate ingestion of nonnutritive substances

Psychology:

the scientific study of behavior and mental processes

Psychology of eating:

the academic study of the relationship between psychological processes and eating, including the impact of individual psychological and brain processes in the context of social interactions and the community

Satiety:

the feeling of fullness (and absence of hunger)

Traditional Knowledge:

beliefs, skills, and practices developed and maintained across generations of local and Indigenous populations

Chapter 2 Recipe for Success: Research Methods and Food Studies Whet Your Appetite: Clickbait Conundrums Think of a social media post touting benefits or harms of a certain food. Do claims around food, nutrition, and health catch your eye? Blueberries improve your memory! Stress eating causes tummy fat! And coffee (or tea or red wine) is either good for longevity or bad for your health depending on the day of the week. How do you evaluate the veracity of these food-related claims? Are they worth your time and energy to read further? In this chapter, scientific techniques and critical thinking are emphasized for evaluating such claims about eating and drinking. These skills are essential whether you have a future as a researcher, academic, or an informed citizen and eater.

Menu Amuse-Bouche: Why We Need the Flavor of Science Course 1: Methods of Inquiry—There’s More Than One Way to Cook an Egg The Process of Science Research Design—Developing Your Recipe Repertoire Course 2: Evaluating Research and Scientific Claims Evaluating Scientific Claims: Be Your Own Recipe Critic Research Ethics Course 3: The Spirit of Science—Essential Features of a Researcher Curiosity Collaboration Skepticism Humility Dessert: Mouth-Watering Pseudoscience

21 22 22 24 33 33 35 40 40 41 41 42 43

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Dining Review Gochisousama Glossary

44 44 45

Amuse-Bouche: Why We Need the Flavor of Science Each of us arrives to the psychology of eating with previously held conceptions—opinions of foods that boost brain function, judgments about certain cuisines, or beliefs around monosodium glutamate, commonly known as MSG, causing headaches. We eat and drink multiple times each day, so these topics are especially prone to personal biases. It can be difficult to accept evidence contrary to our own subjective observations and judgments. Headlines are one source of information, where reporters or media outlets are authoritative sources of knowledge. Parents, doctors, or esteemed community members also serve as authorities of information. Other times, reason and logic offer solutions, for instance consulting nutrition labels to make a deduction regarding the food’s impacts. Personal experiences, too, provide direct access to information about eating and drinking. Most people avoid food eaten shortly before getting sick. These nonscientific ways of knowing have strengths and limitations. Experts make errors, logical arguments can hide or rely on fallacies, and personal experiences are valuable but biased. Such limitations are overcome by thinking critically and embracing the scientific attitude, both topics of this chapter. In science, empirical ways of knowing are preferred over authorities and logic. This means information is obtained through direct interactions with the world, or gathered via senses (e.g., sight, taste). What further separates science from nonscientific empirical knowledge is its systematic nature. Instead of personal and/or casual observation, science uses objective and planned recording techniques to produce more reliable observations and repeatedly tests them over time. Contemporary tension between science and other belief systems can obscure critical thinking. In times of uncertainty, feelings sway risk estimations and thwart rationality so that outlandish claims become more appealing (Tannert, Elvers, & Jandrig, 2007). Still, uncertainty is central to science because true empiricism does not aim to prove dogma but rather to verify (or, in practice, falsify) theory with evidence. Laypeople and experts often view eating and nutrition differently (Bisogni et al., 2012), and conflicting information from these sources illustrates the impact and persistence of nonscientific information. Even in the face of contradictory information, existing lore is retained, a phenomenon known as belief perseverance (Goodwin & Goodwin, 2013). Sometimes—like beliefs—the food we eat stays, leaving a lingering taste that is neutralized with a palate cleanser like pickled ginger when eating sushi, sorbet between fine dining courses, or plain crackers with wine tasting. Imagine how you might now cleanse your palate from preexisting beliefs about food and consumption to approach the psychology of eating with an open mind.

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Course 1: Methods of Inquiry—There’s More Than One Way to Cook an Egg Health claims in the news may trigger questions of their veracity and source. Research involves systematic investigation into questions about why, when, and what we eat to elevate confidence in the findings. While your opinion about the best cup of coffee in town is relevant for you, research provides the necessary objectivity to determine the biological and social mechanisms that draw us to the experience of coffee, a highly influential global food commodity (Topik, 2000). Many researchers share some variant of the maxim feelings are not facts and opinions are not evidence. We encourage this tenet as a point for reflection throughout your studies of the psychology of eating. This chapter serves as a primer or refresher to the research process and to familiarize methods referenced throughout the text, including their strengths and limitations.

The Process of Science Science is the body of knowledge obtained through application of the scientific method. The scientific method is an outline, as a set of principles, for the steps of acquiring knowledge rather than a strict recipe. There are many ways to cook an egg, and choosing how to cook that egg is determined by the research question, expertise, resources, and preferences. As multiple studies are conducted and analyzed about a specific research question or area of interest, evidence builds gradually to illuminate and galvanize our understanding of consumption (Figure 2.1).

Figure 2.1  Steps in the scientific method. An outline of the scientific method. Image created by Leighann Chaffee.

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The research process begins with a question, which can arise from observations (“I wonder why I crave ice cream every night?”), curiosities (“Do some foods improve learning?”), or out of existing theory. A theory is a unified explanation that organizes our knowledge about some phenomenon and serves as the basis for making predictions. For example, the theory of planned behavior (Ajzen, 1991) asserts that our behavior in specific contexts is predictable based on our attitude toward the behavior, the norms for the behavior, and our perceived behavioral control (our perception that we can actually perform the behavior of interest). The theory of planned behavior is applied to a variety of eating intentions and behaviors, such as ability to follow a specific diet. Theories relevant to the study of eating appear throughout this text. A good theory has the below attributes (Goodwin & Goodwin, 2013): ●

● ●

Falsification: specific enough to be tested, and the limits of its explanatory power can be identified Parsimony: the simpler the explanation the better Productivity: inspires new research questions and findings

Deductive thinking can generate novel questions from theory. From the theory of planned behavior, we might ask, “Can we predict how many slices of pizza a person will eat based on their attitudes and the situation?” The research question is stated as a hypothesis, a statement of prediction about the variables of interest in the study. We might hypothesize “College students who like pizza will consume more pizza when socially encouraged to eat the pizza provided.” Unfortunately, the term theory is misused frequently in conversation when a person is in fact referring to a prediction or hypothesis they have formed. The research question and hypothesis identify the construct of interest, studied as a research variable. A construct is a hypothetical factor, like food cravings, that cannot be measured directly. Sadly, there is no meter available to objectively and flawlessly measure the intensity of food cravings in research participants, as this would be convenient. Rather, the construct is measured indirectly, for instance, by asking the participant about their cravings. For most constructs, a variety of measurements are possible. The specific procedure used to measure the construct for the sake of the study is an operational definition. Researchers opt for measures supported by research in the field and use the measures systematically and consistently throughout a study. Measures used in psychological research may be overt behavior, self-report on surveys, or physiological activity, and measurements are never exact. The body weight scale in Author LC’s lab, as an example of physiological measure, has an error range of ±1 kg according to the owner’s manual. Measures are evaluated by their validity (accuracy) and reliability (consistency), where reliability of the scale is indicated by similarity of readings for the same person over time. As additional information is collected, our knowledge improves, and theory is revised accordingly. To fulfill the scientific process, findings must be shared publicly with members

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of the discourse community. Imagine the limited impact of scientific work—no matter its merit—that is not shared. Dissemination is a critical aspect of research so others can access methods, findings, and applications. It is imperative to describe research methods with enough detail they can be understood and replicated by others. Sharing data, in raw form via repositories, and summary analyses are critical for findings to be known and further tested. Research can impact practice only when research is publicly accepted and used for betterment of daily living. Several mechanisms exist for sharing research, such as presentations at professional conferences, original research articles submitted to journals, or popular media blurbs. Effectively communicating research to a range of audiences is a key skill of scientists.

Chew on This: Peer Review In most areas of expertise, researchers publish their work in academic (scholarly) journals that follow a peer-review process. The editor of the journal serves as a gatekeeper, first sending the article to several researchers to examine and review the work in great detail (Suls & Martin, 2009). These reviewers, often anonymously, evaluate the scientific value and quality of the work, including the methods and data analysis, appropriateness of conclusions drawn, and any ethical concerns. The reviewers determine if the work is ready to be published as is, if additional work is required before publication, or if the research does not meet the publication standards (e.g., in rigor or subject matter) of the journal. By their own assessment and recommendations from reviewers, journal editors make final decisions about the inclusion of research in a journal. Critics of traditional peer review cite problems with unqualified or unmotivated reviewers, bias against lesser established researchers in favor of established researchers, and mean-spirited anonymous reviews. To uphold the purpose of peer review in promoting scientific integrity while minimizing its limitations, some researchers recommend new or blended approaches that include pre-registration of research methods to professional websites, public (Internet) posting of raw data with public review of submitted papers, and transparent sharing of reviewer concerns with publication of research papers (Suls & Martin, 2009). Some of these adjustments to peer review are already practiced in natural sciences and may be adopted by psychology journals in the near future.

Research Design—Developing Your Recipe Repertoire Your selected research question, whether you are asking a question for information sake or aiming to fix a problem, dictates the nature of your research. Basic, or fundamental,

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research is conducted to investigate underlying principles of behavior and mental processes. In contrast, applied research has the goal of solving immediate, real-world problems. In this textbook, we synthesis basic research in biopsychology, sensation, learning, and memory to inform our understanding of the psychology of eating. A study on the potential for the sensory properties, like appearance of a food, to influence our emotional state is classified as basic research, and these findings may inform applied research aiming to improve food choice. Sometimes applied research is viewed as more valuable than basic research because its relevance can be more apparent for the layperson (Goodwin & Goodwin, 2013). Relatedly, government investment in basic science has decreased in recent decades (Casassus, 2014). Criticisms of basic research fail to acknowledge that the generation of knowledge is valuable in itself. Instead, appreciation for knowledge is justified by its translation into applied settings where work that is seemingly unrelated contributes to improvements in quality of life (Spralding, 2016). Basic and applied research complement each other and are both essential for scientific progress, as illustrated by Pasteur’s quadrant of scientific inquiry provided in Table 2.1.

Quest for fundamental knowledge

Table 2.1  Pasteur’s quadrant of scientific inquiry (Stokes, 1997) Pure basic research Use-inspired basic research How does sugar consumption disrupt Under what conditions is student recall memory processes? related to dietary sugar? (this quadrant is blank as any question by nature is either interested in knowledge or application)

Applied research Is risk of dementia reduced by restricting sugar intake?

Concern with application

Although the psychology of eating is a relatively new discipline, it has experienced its share of controversy. In 1992, Herbert Meiselman, a renowned research psychologist for the US government, published an article in the journal Appetite on the state of the discipline, outlining limitations of laboratory settings and criticizing overreliance on selfreport and physiological evidence. To remedy these limitations and enhance ecological validity, he proposed real meals served to real people in real eating situations, emphasizing the importance of field research to enhance generalizability of findings (Meiselman, 1992). Although these recommendations may seem relatively benign, Meiselman’s article ignited intellectual debate over the rigor of the field. Well-known researchers responded to argue the merits of basic research and the need for rigorously controlled studies (Rolls & Shide, 1992), assert that humans and animals eat in all settings and thus a “naturalistic environment” is prone to the same bias of the researcher as the laboratory setting (Kissileff, 1992), and claim Meiselman is overly optimistic about researcher’s access to “real” eating settings and downplaying the limitations of observational research (Tuorila & Lähteenmäki,

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1992). The challenges of design described in this chapter have troubled researchers in the psychology of eating since the field’s inception and are not easy to address. A topic explored with multiple, complementary methods supplies deeper understanding than a single technique (Warde, 2014), and the psychology of eating is a discipline of mixed methodology. Given the diffuse origins of the field, consumption research did not develop an established paradigm, or way of knowing. We view this as a strength of the psychology of eating as it benefits from varied expertise, perspectives, and operations. The ways researchers arrange and design their investigations are described in Table 2.2. Table 2.2  Key considerations in research design Design Question

Spectrum of design answers falls between these endpoints

What type of information do I seek?

Basic, Fundamental Knowledge (Understanding)

Application (Problem Solving)

Where will the research take

Laboratory (Artificial Setting)

Field (Natural Setting)

measured?

Quantitatively (Numerically)

Qualitatively (Narratively)

How will variables be treated/ arranged?

Manipulation with Control (Experimental)

Observed without Intervention (Nonexperimental)

place? How will variables be

Research Location. Research varies from controlled laboratory settings to naturalistic field research. It is commonly assumed that laboratory research provides greater control over conditions of the study and field research more closely approximates everyday life, but the level of control is determined by the study design and care in its implementation, and can vary across locations. Internal validity is determined to a large degree by the level of control in research and refers to confidence in the identified relations between variables. Because human consumption varies day-to-day, a seminaturalistic setting can be created in a laboratory to simulate environments like a shared meal table (Pesch & Lumeng, 2017). Though many psychology research findings from the laboratory are consistent with field research findings, there is significant variability in the sizes of the effects (Mitchell, 2012). The social environment is equally important to the physical research setting, and design of laboratory and field studies can account for social influences on eating (Higgs & Thomas, 2016). The term external validity is used to describe the potential for research findings to generalize to other environments, populations, and times (Goodwin & Goodwin, 2013).

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Measurement of Variables. Transforming a construct into a variable involves determining how it will be operationalized (using operational definitions discussed previously) or empirically assessed. This refers to your measurement plan. Three common measures of events in psychological science are physiological events, behavior, and selfreports that can be collected anew or gathered via archives. Physiological measures are common in the psychology of eating, as they may include blood glucose levels, heart rate, brain imaging, for instance, with fMRI, and neurobiological methods to more directly measure brain activity. Behavior measures are observed by researchers. For example, mealtimes can be recorded to measure feeding behaviors with behavior coding, a rigorous and systematic process to identify and record target behaviors—see Pesch and Lumeng (2016) and Bakeman and Quera (2011). Though time-intensive, it can yield valuable information missed by self-report (Pesch & Lumeng, 2016). In a laboratory designed to look like a dining room, hidden cameras can capture caregiver–toddler interaction and behaviors when a toddler encounters a novel food. Recording provides opportunities for researchers to rewatch the encounter and capture behaviors (e.g., facial expressions, number of bites) relevant to the hypothesis. One disadvantage is potential technical difficulties in recording. Self-report methods, like interviews, questionnaires, and personal technology (apps), are common in the psychology of eating and are advantageous for variables that are not readily observable. However, there are limitations in that self-report is notoriously imprecise for tracking eating habits (Schoeller, 1995). Participants may not disclose information about sensitive topics, like craving taboo food items or overeating, or be able to accurately report behaviors, like amount of popcorn consumed while watching television. Information is limited further by recall errors, age, or communication abilities. Findings are more credible when self-report data are complemented with direct study of actions (Baumeister, Vohs, & Funder, 2007; Meiselman, 1992). Online data collection is increasing in popularity; we have only begun evaluating the quality of online data, yet initial analyses indicate it is at least as reliable as traditional methods (Buhrmeister, Kwang, & Gosling, 2011). And online participants may be more attentive to instructions, particularly if experienced in online research (Hauser & Schwartz, 2015). Archival research involves any preexisting data that can be used alone or in combination with newly taken physiological measure, behavior observation, or selfreports. Though the archival information is not new, it is often analyzed in a new way by the researcher. Examples may include grocery or cafeteria sales, obesity rates in the World Health Organization (WHO) database, nutritional profile of food on packaging, a backlog of cooking shows, news reports of E. coli outbreaks, restaurant openings and closings available in city records, and others. Content analysis is common as part of archival research, which requires systematic evaluation and summary of narrative. As an example, a researcher could analyze the content of menus across cultures or time.

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Morsel: Measurement and Body Composition Characteristics of body composition, the percentages of fat, muscle, and bone in the body, are often used as an indicator of health. Body composition is a common variable in studies of obesity and eating disorders, and throughout health sciences and the psychology of eating, from food choice to emotions and development. Body composition is operationalized in a variety of ways, from the sometimes painful skin calipers (error prone in untrained hands) previously used in schools, to more contemporary technology that is expensive and inaccessible. For feasible estimates of body composition, practitioners often use crude measurements of waist-to-hip ratio and body mass index (BMI). Especially for child and adolescent wellness checks, BMI is a standard indicator of growth patterns. BMI is calculated as the proportion of body weight per body height, and can be computed by hand (weight in kilograms / [height in m]2) or with an online calculator. BMI has the benefit of being easy to calculate, but the limitations are clear when comparing BMI with other indicators of body composition. The relationship between BMI and other measures of body composition, particularly adiposity, varies drastically. BMI is not an equally valid index of adiposity across age, sex, and ethnicity (Camhi et al., 2011; Vanderwall et al., 2017). BMI is elevated in people with a high proportion of lean muscle mass, like athletes (Nevill et al., 2006). Remember that BMI is not a direct measure of adiposity but rather body proportions. These limitations of BMI are exacerbated by the use of categories with rather arbitrary cutoffs. At present, the categories defined by the World Health Organization and the Centers for Disease Control and Prevention are as follows: ● ● ● ● ● ●

Underweight: BMI below 18.5 kg/m2 Normal weight: 18.5–24.9 kg/m2 Pre-obesity/overweight: 25.0–29.9 kg/m2 Obesity class I: 30–34.9 kg/m2 Obesity class II: 35.0–39.9 kg/m2 Obesity class III: BMI above 40.0 kg/m2

These cutoffs overestimate the prevalence of obesity in some cases and underestimate in others—for example, they failed to identify nearly half the cases of obesity in a study of reproductive age women (Rahman & Berenson, 2010). This is especially problematic given that BMI overestimates adiposity and health risks for Black people (Burkhauser & Cawley, 2008). The uncritical use of BMI as an imprecise operational definition of adiposity causes misclassification of individuals into these categories and can reduce the efficacy of efforts to curb the obesity epidemic.

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Figure 2.2  Diagram of research design. Image created by Stephanie da Silva.

Variables are captured best through multiple measures, sometimes including quantitative (numerical) and qualitative (narrative) elements. Converging operations is the application of multiple measures to assess a construct. Multidisciplinary approaches often use converging operations as an attempt to unify explanations about some phenomenon across perspectives and methods (Sternberg & Grigorenko, 2001). You can think of converging operations as the “whole is better than the sum of the parts” approach to gauging a construct. Qualitative and quantitative inquiry provide complementary depth, examples, and richness to our understanding of the research question. Many contemporary researchers use multiple measures, such as quantitative physiological rhythms with qualitative self-reports, in a single program of research (Figure 2.2). Treatment of Factors. There are two broad categories of design, experiments and nonexperiments, that differ in their treatment (or lack thereof) of research variables. Experiments involve manipulation of at least one variable, or in other words, experiments require researchers to intervene. Nonexperiments, by comparison, measure aspects of the world as they exist without research manipulation. Sometimes there is a third category of research, quasi-experimental, identified when no variable is manipulated but there is some level of control in the research. A test of mindless eating in a laboratory may draw conclusions regarding the contributions of food attitudes, gender, and body weight in prediction of consumption during distraction. Even in such a quasi-experiment—no matter how controlled—the resulting relations are, fundamentally, correlations because food attitudes, gender, and body weight are measured as they occur without researcher manipulation or assignment. As we will discuss, care is required in interpreting research findings appropriately. Let us now describe experimental and nonexperimental design.

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In order to draw conclusions about cause and effect, an experiment is necessary. An experiment is a systematic study in which independent variable(s) are manipulated or controlled by the researcher to measure their effects on dependent variable(s) while other extraneous variables are held constant. Randomized controlled trials (RCTs) are the gold standard for causal conclusions because their design limits bias in several ways. Participants are randomized into experimental and control groups with the goal of distributing their attributes between conditions of the study. Randomization is essential for true experimental design as it protects against unknown sources of variability, to safeguard against the possibility that the researchers or the participants are influencing the outcome (Rosenthal & Rosnow, 2008). RCTs should be double-blind, so that neither the participant nor the researcher recording the data are aware of the condition each participant is assigned. This control feature limits expectation effects in participants and researchers that may influence the outcome. Use of a placebo, another control feature, also curbs expectations because it prevents participants, and sometimes researchers, from discerning presence or absence of the experimental variable and ensures that participants are treated equally in all ways except the critically important feature of the manipulation. It is easier to keep participants and researchers blind when effective placebos (e.g., nonalcoholic beer that tastes like it contains alcohol) are used. In case you are wondering about this researcher “trickery,” participants are informed about conditions of the study, including their assigned condition, after a study in a process called debriefing. Let’s walk through the steps of designing a study to answer a research question: How do stress levels influence eating habits? First, to formulate the question as a hypothesis, maybe you state, “The experience of stress significantly increases consumption of junk food.” To conduct an experiment, first identify and operationalize the variables: ●

●

The manipulated independent variable (IV) is stress. Participants in the experimental group will experience a stressor in the laboratory and participants in the control group experience a placebo. Instruct the experimental group to anticipate a public speaking performance and provide them 10 minutes to prepare a 5-minute speech on a controversial topic (similar to the methods of Oliver and colleagues, 2000) to be reviewed and rated by public speaking experts from the communications department. The experimental condition is actually the stressful preparation period—unknown to the participants, there is no speech. Participants in the control condition will not be told of any speech, but rather spend 10 minutes listening to emotionally neutral text while they sit and relax. The dependent variable (DV) is junk food consumption. During the 10-minute period, all participants will have access to a (consistent) variety of packaged junk foods. Video recordings will be used to identify the snacks they select, a qualitative measure. The trash will be collected after each participant so researchers can record the volume of junk food consumed minus any discarded, a quantitative measure.

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Half of the participants are randomly assigned to the stress condition and the other half to a control condition while keeping other aspects of the study constant to limit the influence of confounding variables. After the completion of the study, the participants experience debriefing, in which they are informed of the purpose of the study and are provided an opportunity to ask questions (Goodwin & Goodwin, 2013). At the conclusion of the study, any differences in junk food consumption between the groups are assumed to indicate the effect of stress as long as all other variables are held constant. Not all research aims to determine causal relationships, and sometimes it is not feasible or ethical to manipulate a variable. It is possible to manipulate a brief stressor in the laboratory (with proper approval, described in Course 2), but it is not ethical to manipulate or assign significant life stressors, such as enduring a natural disaster in childhood. When the independent variable is not randomly assigned, the study is quasi-experimental or correlational in nature—two descriptors we use for research that fundamentally is nonexperimental. Nonexperimental research helps understand relationships between variables, but does not allow causal conclusions. For instance, a child’s vegetable consumption may be similar to parental vegetable intake (true in children, this relationship seems to diminish by adolescence; Pearson, Biddle, & Gorely, 2008). This is a positive correlation (more parental vegetable consumption means more child vegetable consumption), in contrast to an inverse (negative) correlation, in which greater parental vegetable consumption would mean less in the offspring. There are two important caveats of correlational research to remember. First, the direction of the relationship is unknown—it could be that parental vegetable intake causes their kids to eat more, or that the children eating more vegetables leads the parents to eat more too. And second, there may be a third variable that drives this relationship—perhaps families residing near markets with affordable produce are more likely to eat a vegetable-rich diet, making vegetables more accessible for the parents and children alike. Resources and socioeconomic status are common third variables to consider in the relationship between what we eat and our health. Frequently, researchers in food studies have questions about consumption over geographical location, time, or age, which—by nature—cannot be manipulated. When investigating such variables, two designs are commonly used. ●

Cross-sectional studies involve a between-groups comparison of a specific variable at the same time. Consider the third variable of convenient access to produce as a potential contributor to vegetable intake. A cross-sectional study comparing adults residing in rural areas and nonrural areas of the United States found that in 37 states, adults residing in rural areas were less likely to get at least five daily servings of fruit and vegetables (Lutfiyya, Chang, & Lipsky, 2012). Cross-sectional designs also are used to compare people of various age groups on some measure. Tiggemann and Lynch (2001), for instance, surveyed women 20–84 years in age, finding that body

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dissatisfaction was similar for all age groups, but body monitoring, anxiety about one’s body, and disordered eating were relatively lower in older age groups. Longitudinal studies involve a within-subjects comparison of a specific variable across time, usually years, by tracking the same people and conducting repeated measurements. A 5-year longitudinal study of vegetable consumption in adolescence revealed that adequate skills and resources for preparing food were associated with better diet quality (Larson et al., 2006).

Nonexperimental research does not allow causal conclusions, but these studies have particular value in allowing exploration of variables that cannot be manipulated, allow for some control, and often produce results with applied significance to benefit people’s lives (Goodwin & Goodwin, 2013). Additional nonexperimental approaches that provide valuable information are case studies and ethnographies, which typically provide the most narrative or depth in their analyses of all methods. ●

●

In case studies, researchers listen, record, and report in-depth analysis of a single person, situation, or community. For example, Ford (2009) explored the relationship between climate change, food security, and adaptability of the Inuit community Igloolik in the Canadian territory Nunavut. Extreme weather and conditions of the ice impact subsistence hunting and food delivery to nearby stores, highlighting the dual threat of climate change in this area. Ford interviewed community members to gather data on food procurement, perceived impact of weather, changes in eating patterns, and adaptability of the community. These findings contribute to the development of a model for assessing food system vulnerability and the response to extreme climate conditions in Inuit communities, to inform future policy or public health efforts to support community health. In ethnographies, researchers become immersed in a setting to study social interactions, behaviors, or perspectives as a member of the group (Reeves, Kuper, & Hodges, 2008). In essence, ethnographers join the group while they collect data and insights as a member of the community. Ethnographies allow access to traditional food and nutrition practices, including belief systems around diet and nutrition that contrast with contemporary academic viewpoints and may be hidden from direct study. Such understanding of diverse groups enhances the appropriateness of health policies.

These examples illustrate the advantages of trusting relationships between researchers and participants. Limitations of qualitative methods include the time commitment to develop relationships, the potential for the researchers’ own perspectives to bias the inquiry and thus the findings, and the careful attention to standards of research ethics (Reeves, Kuper, & Hodges, 2008).

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Course 2: Evaluating Research and Scientific Claims Imagine you read the headline “Stress have you snacking? Try this simple solution!” You click on the article and are drawn into a compassionate narrative about the stresses of modern life, an encouraging statement about food providing comfort in uncertain times, and eating advice from “the experts.” How do we evaluate this source?

Evaluating Scientific Claims: Be Your Own Recipe Critic The ease of evaluating the source of this advice varies across websites and articles. If the source is unnamed and uncited, it should be an easy decision to close the article and seek information elsewhere. Alternately, the source and their credentials may be identified—articles about food, eating, and health frequently cite registered dietitians, nutritionists, medical doctors, or psychologists. But the mere presence of credentials does not validate the recommendation. Individuals may tout fake or outdated certification or may speak beyond their expertise, an unfortunately common issue in popular media portrayals of medical practice and celebrity doctors. It is best to take time to verify the credentials of the source of information, whether that be a medical specialist, article, or web advice. Information should be grounded in empirical evidence, presented objectively, and void of emotional appeals (e.g., fear-mongering). Many news media outlets directly link to a research study of interest, a remarkable convenience compared to the amount of detective work required to evaluate these claims even 10 years ago. Each study is a piece in a bigger research puzzle, so it is important to evaluate the merits and contributions of a single study in the context of the broader body of research. The features of research design from this chapter are an excellent place to begin your evaluation. After accessing the article, first determine the aims and the scope of the study. Use this information to identify the key variables and the design necessary to address that research question. Next, focus on the methodological integrity of the study and the fidelity of the data (Levitt et al., 2017). A specific consideration is the steps used by the researchers to limit bias, for instance, use of grounded theory, randomization, blinding, and accounting for extraneous variables (Sutherland, Spiegelhalter, & Burgman, 2013). Many reports may provide the outcomes of inferential statistical tests, to quantify the likelihood that the results were due to the factor of interest or a result of random chance. A significant finding indicates that researchers have sufficient confidence in their sample outcomes to conclude those findings exist in reality (not due to error) for a larger population. But the absence of significant differences, called null findings, also provides useful information. There is variability and unpredictability in the real world, and variation observed in the research setting is either a product or chance or real differences. Return to the example from above—if there is no significant difference in junk food consumption between

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the participants engaging in the stressful task and the control group, this is valuable information. You may want to reexamine the manipulation of the independent variable to ensure it is properly stressful. Alternately, it may be that the relationship between acute social stress and junk food consumption is questionable, and other forms of stress merit consideration. For years, research in psychology has been plagued by the “file drawer problem” as null results were not published (Rosenthal & Rosnow, 2008). This results in a publication bias: if a study is conducted 10 times, with 9 null results and 1 significant finding, yet only that significant finding is published, the scientific public has a rather skewed view of the phenomenon (Francis, 2012). Limitations of null hypothesis significance testing are addressed by additional methodological and publication practices. The design of the study determines the statistical power, the ability to detect any effect that occurs. Given the investment of time and resources in conducting research, we want to avoid false negatives. The power to detect differences is determined not just by sampling but also by effect size, the magnitude of the difference between groups (Funder & Ozer, 2019). If we find a significant effect in our example, it is valuable to know how much junk food consumption increased in the stressor condition compared to the control condition. And it is not just about size—a complex variable like junk food consumption is determined by many factors in addition to the experience of a stressor, so an effect size that is small by traditional benchmarks may be meaningful, especially if the small effect is demonstrated consistently through a larger body of research (Funder & Ozer). Effect sizes are used in meta-analysis of research, a quantitative technique for summarizing a research domain (Rosenthal, 1994), which estimates the overall magnitude of the effect of the relationship as reported across research studies. The goals of a systematic review and meta-analysis are to summarize collective outcomes of several studies and protect against overarching claims from limited assessments. Replication is a cornerstone of science. Results are trustworthy only when they are repeatable— across researchers, populations, and even time. In the past 20 years, psychology has faced what some call a “replication crisis,” with failures to replicate seminal findings in the field compounded by instances of scientific fraud (Shrout & Rodgers, 2018). Deliberate scientific fraud is considered rather unforgivable, and this pivotal moment in psychology has produced positive outcomes including calls for transparency and open science, more attention to training in research methods and statistical analysis, and collaboration in replication efforts. A threat to the external validity and repeatability of psychology research findings is the unique characteristics of the research samples. One source of research participants is the “pool” of student volunteers available at the university where research is being conducted. Imagine the demographics of that pool of participants over the last 100 years, sometimes described with the acronym WEIRD for White, educated, industrialized, rich, and democratic (Heinrich, Heine, & Norenzayan, 2010). In examining the findings published in the top psychology research journals, 96% rely on samples from Western

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industrialized countries (e.g., North America, Europe, Australia), predominantly White participants, yet these countries only represent 12% of the world’s population (Rad, Martingano, & Ginges, 2018). What are the problems with this unique sample? First, WEIRD samples represent neither our diverse global community nor the population of the multiethnic nations listed above. Second, there is documented variability in the psychological functions that we assume to be universal. For example, relevant to the study of food and eating, people from small-scale nations show enhanced social cooperation than those from industrialized nations, Westerners value freedom of personal choice to a greater extent than non-Westerners, and those of us from the United States, in particular, value personal choice to an even greater extent (Heinrich et al.). College student participants in the United States are unique further still, and while they may be less embedded in the community, they are more supportive of diversity and hold crosscultural worldviews (Heinrich et al.). It is clear that a large enough convenience sample does not guarantee generalizability of the findings. The aim of psychological research is to understand both human universals and variability, and the study of the food-eating domain within psychology merits attention to the role of culture and context. There are no simple solutions to enhancing inclusivity of research, yet useful theoretical frameworks are accepted for explanation of cultural variability (see Matsumoto & Yoo, 2006). Many researchers now describe their findings in the context of the sample when publishing their work in scholarly journals—but unfortunately these caveats may be omitted by media outlets that spin the research findings into a catchy headline. Critical thinking by audiences is imperative to remain an informed consumer. A final consideration in evaluating the quality of a research study is the ethics of that research.

Research Ethics Strict guidelines for ethical research are essential to ensure the research is methodologically sound and that safeguards are in place to protect the welfare of human participants and animal subjects. The information given here provides the foundation for evaluating the studies you encounter, but comprehensive training is required for those who will be conducting research. The famous psychologist Robert Rosenthal, dedicated to meticulous research methods, argued that the scientific quality of research is closely interrelated with the ethics of that work. In other words, high-quality research design justifies the investment of time and resources in that work (Rosenthal, 1994): participants volunteer time and effort, resources are allocated by the university or funding agency, findings may be published by an academic journal, and society makes an investment in translating and using science. Throughout this chapter, you have learned a bit more about evaluating research design including characteristics of a study that allow causal conclusions. However, research participants and nonexperts may not possess the same skills, so it is important

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to avoid exaggerating and misrepresenting research findings, specifically around causal relationships where they are not established (Rosenthal, 1994). Findings can be exaggerated, misrepresented, or fabricated through inappropriate data analysis. The term “scientific fraud” is used to broadly describe failures of honesty, including data falsification.

Morsel: Fraud in a Famous Food Lab Have you ever come across articles indicating that the endless presentation of a food item such as soup or popcorn would lead to mindlessly eating that item? What about research suggesting that we eat more pizza in the presence of others? These findings are the work of Brian Wansink, a former Cornell University professor who directed research in Cornell University’s well-known Food and Brand lab and is widely cited by textbooks and the media. Wansink worked for years on studying the environmental cues and cognitive associations linked to human food consumption and practices. Wansink’s work, from his prize-winning “bottomless bowl” study showing people overconsume soup when unaware the bowl is being replenished, to his book Mindless Eating: Why We Eat More Than We Think, has shaped our beliefs about food over the last 20 years (Hamblin, 2018). In recent years, inconsistencies in Wansink’s work led to scrutiny and investigation. In one day, the renowned Journal of the American Medical Association (JAMA, 2018) issued a press release to announce the retractions of six of his papers, signifying grave concerns with the standards of his research. More retractions followed (18 at present), calling his entire body of work, and the work of his collaborators, into question (Bartlett, 2017). Wansink was investigated and resigned from Cornell University. Wansink’s scientific practices violated research ethics in a series of ways. One problem was uncovered by Jordan Anaya, who developed a mathematical model known as Granularity Related Inconsistency of Means (GRIM), designed to detect numerical inconsistencies. GRIM can be used to analyze published research— using information available such as sample size, the technique is able to verify whether the solutions and conclusions presented in the paper are plausible (Bartlett, 2017). Using the GRIM program, Anaya and colleagues found four papers coauthored by Wansink were riddled with impossible mathematical calculations (van der Zee, Anaya, & Brown, 2017). Their work sparked a larger conversation regarding the trustworthiness of Wansink’s publications. Anaya and colleagues’ work now identifies 26 of Wansink’s publications with suspected problems (Bartlett, 2017), including statistical discrepancies, and more blatant signs of scientific fraud, including data duplication and falsification. Articles coauthored by Wansink were also retracted due to evidence of p-hacking, after Wansink’s own blog post

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spurned this criticism when he admitted to encouraging this practice in his graduate students (Resnick & Belluz, 2018). Earlier in this chapter, statistical significance was discussed as one criterion for evaluating research claims. The practice of p-hacking involves manipulating analyses to reach a critical alpha level required for statistical significance and, often, publication in a scholarly journal (Aschwanden, 2015). How common is scientific fraud? Is it possible to discourage p-hacking and data falsification? Most educators, including the authors of this text, argue that a solid foundational training in research methods, statistical analysis, and ethics is key to prevention of scientific fraud. This training is lacking in Wansink’s case—despite publishing in journals for research in psychology and economics, Wansink’s background is in marketing (Hamblin, 2018). According to Bartlett (2017), he was unaware of the term p-hacking to describe his practices. Proposed changes to the process of research and publishing aim to systematically reduce scientific fraud. Preregistration of study plans makes practices like p-hacking more difficult, open data sharing allows third-party analysis of findings, and emphasis on more rigorous statistical analysis thwarts exaggeration of findings. These steps are essential as each case of scientific fraud, whether deliberate or the consequence of poor training, prompts questions of the trustworthiness of the larger body of published research.

Human Participants. The ethical guidelines for working with human participants in research are outlined and enforced by both the governing body, such as the American Psychological Association (APA), and the appropriate Institutional Review Board (IRB), an ethics board that reviews applications for research projects and monitors ongoing research to ensure only ethical research is conducted. The IRB is typically affiliated with the university or hospital where the research is being conducted. In plain terms, the ethical guidelines for research with human participants are: 1. First, do no harm. Benefits of the research outweigh any potential costs, including temporary discomfort or stress. In biomedical research, the parallel principles are beneficence (to do good) and nonmaleficence (do no harm). 2. Voluntary participation. Participants are informed of the purpose and nature of the research via a detailed Informed Consent document before the research begins. Participants (over age 18) read and sign the document to indicate their willingness to voluntarily participate. 3. Confidentiality. Participant privacy is to be protected and participant information is kept confidential, similar to medical information. These guidelines are articulated in great detail by the review board that oversees the ethical administration of research (typically an Institutional Review Board at a

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university), providing recommendations to protect the research participants and the transparency of the research process. Standards are further elaborated for working with children and minors, interacting with vulnerable populations, clinical trials research, and best practices for cross-cultural research. A majority of our current regulations were developed in response to egregious human rights violations perpetrated in the name of science. The consequence of these past injustices is distrust in the scientific and medical community (Levine et al., 2012). Researchers have a professional and moral obligation to demonstrate integrity and honesty and to ensure the respect and dignity of participants. Animal Subjects. The psychology of eating necessitates review of behavioral, biomedical, and neuroscience research fields, which use nonhuman animal (hereafter, animal) subjects. Many of us dream of a world where comprehensive research is possible without animal subjects and advances in technology have increased the potential for nonanimal (e.g., in vitro) tests to reduce the number of animals required (Festing & Wilkinson, 2007). However, animal research remains a critical avenue to scientific insight for both human and animal quality of life. It helps, too, to realize the numbers of animals—mostly rodents along with birds and fish—used for research relative to their involvement in other endeavors, such as being hunted for sport and recreation, farmed and processed for food, and labored for human benefit. In the United States, over 9 billion chickens were raised for food in 2020 (US Poultry & Egg Association, 2021), which alone—without considering other animal food sources—far surpasses the number of animals (estimated roughly as less than 120 million in the United States and 200 million worldwide) used in all types of research (Carbone, 2021; Taylor & Alvarez, 2020). Finally, researchers are committed to ethical and humane care of research animals for reasons beyond their own benefit, but also to preserve integrity of their research in having healthy subjects. Given that animals cannot provide voluntary consent for participation, guidelines are in place to ensure their humane care before, during, and after the research. In the United States, three particular layers of ethical guidance exist for psychological research with animals. First, The Ethical Principles of Psychologists and Code of Conduct (American Psychological Association, 2017) contains a brief section (8.09) about animal research in which it recommends maintaining the welfare and comfort of the animals generally and especially during procedures related to the research to include the proper training of animal researchers, use of anesthesia when necessary, and humane care before, during, and after research. Secondary assurances are provided by the US government through enforcement of the Animal Welfare Act (United States Department of Agriculture; 1966) and the Public Health Service Policy on Humane Care and Use of Laboratory Animals (National Institutes of Health, 2015). It is these legally binding regulations that specify conditions of acquisition, housing, and treatment of animals in various capacities, including research. A final mechanism for protecting

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animal subjects is by a local ethics committee typically called the Institutional Animal Care and Use Committee (IACUC). This committee operates at the level of individual schools or research facilities and approves any research affiliated with the institution that involves animals. Committee members, to include scientists, nonscientists, and a veterinarian, review research proposals to scrutinize the purpose, procedures, and husbandry (i.e., caretaking). Some questions they consider are whether the use of animals is justified, the research has scientific or applied value, and if alternative procedures are available. Researchers generally share public concern for laboratory research animals and play active roles in not only adhering to guidelines but also promoting and revising them. Conflicts of Interest. The guidelines for conducting ethically sound research mandate disclosure of conflicts of interest. A conflict of interest is a situation in which a person, like a researcher, can potentially derive personal or financial benefits from actions made in their official capacity. Conflicts of interest are quite common in pharmaceutical research, and this information is disclosed when research is published (in reputable journals). You can imagine that similar conflicts can occur for foods and drinks. Disclosing of conflicts of interest is essential because systematic evaluation of research findings demonstrates that authors with ties to the corporations invested in products are more likely to find outcomes favorable for said corporations (Perlis et al., 2005). The global food market is dominated by large multinational corporations, with resources to exert influence over regulatory organizations, researchers, politicians, practitioners, and consumers. Imagine a corporation developing a new fat substitute with potential health benefits for reducing blood pressure and cholesterol. The corporation produces research by their own scientists and cherry-picks the data to demonstrate superiority of the fat substitute. Given the revolving door between government regulatory committees and the private industry, the corporation uses established connections, arranges meetings with the regulatory body and patent office, petitions for approval, and the product enters the market. Then, unfortunately, the product shows adverse or even dangerous side effects, discovered by independent researchers. Upon regulatory review, the corporation brings its own experts to counter the adverse incidents and negative research, eventually receiving extended patents and having warning labels removed (Nestle, 2013). This is not a hypothetical case but rather an abridged telling of the tale of Olestra, the fat substitute that causes loose stools, cramping, and inhibits the absorption of micronutrients. Nutrition research is unfortunately dwarfed by the relative investment into drugs and technology (Mozaffarian, 2017). The food industry has drawn comparisons to the tobacco industry and in fact uses the same playbook and even hired away big tobacco executives upon the decline of that industry (Brownell & Warner, 2009). Alarming similarities include the marketing of harmful products like sugar-sweetened beverages, specifically targeting children and susceptible groups, and corporate lobbying to sway political interests, for instance, opposition to the proposed soda

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tax in Mexico (Mozaffarian). Throughout this text, you will become informed on the nutritional and health challenges posed by our contemporary food environment, thus the imperative for methodologically sound and unbiased research. One potential solution is to improve the funding environment for academic researchers, thus reducing the appeal of industry-sponsored grants and partnerships (Soares et al., 2019). The National Academies of Sciences (and other groups) have critiqued the process for developing the US dietary guidelines for lack of transparency and conflicts of interest (Bero, 2017). Similar conflicts of interest are suspected among creators of European dietary guidelines (Robinson et al., 2013) as well as those in Latin America (Barnoya & Nestle, 2016). From these examples and in closing this section, it is hoped that you see the relevance for understanding and using a scientific eye in your approach to eating and drinking.

Course 3: The Spirit of Science—Essential Features of a Researcher Embracing the mindset of a researcher and scientist, characterized by curiosity, collaboration, skepticism, and humility, facilitates our ability to interact with research in the psychology of eating. These characteristics are similar to those used by an eater trying a new cuisine or a chef developing a new recipe, as they facilitate an open mind for learning and asking questions.

Curiosity Curiosity and enthusiasm—asking questions about people and how the world works— are essential for the first step of conducting science. Research questions come from many sources (Miller & Deutsch, 2009): our observations of the world around us may lead us to wonder why some people say cilantro tastes like soap, travel may spurn more observations and inquiries about the ubiquity of ice cream, social media could lead to questions about emotional and cognitive effects of viewing alluring images of food, and news outlets regularly report on food with stories that leave lingering questions. And research generates more research, as each study is a sliver of evidence and follow-up questions are expected to remain. Exposure to different points of view, through formal opportunities such as collaborations and attending academic conferences, or informally via travel, art, and literature, is valuable in generating creative ideas. Creativity is defined in a variety of ways, and here the meaning can be distilled into generating novel ideas or solutions, as innovation facilitates the movement from an idea to an outcome (Goodwin & Goodwin, 2013). Open-mindedness and collaboration are encouraged as we advance in our academic training to ensure we maintain flexible and creative thinking.

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Collaboration Given the inherent interdisciplinarity of the psychology of eating, adjacent research methods merit discussion. There is a bidirectional relationship between our health and our eating, so collaboration with biopsychology, neuroscience, and biomedical research is relevant. Biopsychology and neuroscience employ methods to measure physiological function (blood pressure, blood glucose) and brain activation, with neuroimaging plus neurobiological techniques typically conducted with animal subjects to identify brain areas and signals corresponding to particular processes or behavior. Health and biomedical research overlaps with the field of epidemiology, the study of the patterns and distribution of health and disease conditions, as well as their determinants and associations in certain populations (CDC, 2016). Epidemiology contextualizes the risks associated with certain health behaviors and conditions, and applied research aims to provide solutions for health problems. The techniques of epidemiology can be applied to nutrition, monitoring the nutritional status in a population, and the role of nutrition in health and medical conditions. The measurement of eating patterns is challenging and unreliable; this leads to unreliable health claims, linking superfoods to health benefits or certain diets to scary diseases without context. Remember the distinction in experimental and nonexperimental evidence? Correlational studies using thousands of variables from memory-based dietary assessment methods (described more in Chapter 6) result in many correlations with expected false positives, meaningless correlations, and those with a small effect size (see Aschwanden, 2016). Schoenfeld and Ioannidis (2013) identified common cooking ingredients from recipes then searched for published studies to link the ingredients and cancer risk. Of the 50 identified ingredients, 40 of them were claimed to increase or decrease the risk of cancer, though the causal evidence was weak or absent from these claims.

Skepticism Early in this chapter, the maxim feelings are not facts and opinions are not evidence was shared to encourage insight into the biases and perspectives we bring to the table. Skepticism and critical thinking enable objectivity in the process of conducting and evaluating science—skeptics require evidence before accepting claims. Each of us has experience with food and eating that shape our perspectives and interests in the psychology of eating. It is especially important to use critical thinking in evaluating claims that are too good to be true, and these emerge all too frequently when it comes to questions of food, eating, and health (Aschwanden, 2016). Proper critical thinking and skepticism require care for detail, evaluation of the evidence, and assessment of the conclusions rather than merely accepting claims at face value. Remember, each study is a sliver of evidence, and our burning questions are not answered by conducting a single study, much less by reading one headline.

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Morsel: Sugar Hype Foundational knowledge on the process of science is useful for evaluating claims like the widespread belief that sugar consumption leads to hyperactivity, especially in children. In festive situations, it is not uncommon for someone to comment about the children being “hyped up” from sugar consumed. The belief that sugar drives children’s movement and inattention began in the 1970s with the Feingold Diet, which advocated removing sugar and other additives from children’s diets to alleviate symptoms of ADHD. In truth, however, there is no evidence that sugar consumption leads to hyperkinetic behavior. Researchers of the past 50 years have failed to find a relation between sugar consumption and hyperactivity. In these studies, parents or other evaluators are blind to whether or not foods and drinks contain sugar, sugar substitutes (e.g., aspartame or saccharin), or no additives. Most studies, especially those conducted using controlled experiments, report no difference in perceived hyperactivity as a function of sugar consumption (Krummel et al., 1996; Milich, Wolraich, & Lindgren, 1986). So, why does the sugar–hyperactivity connection continue? First, it is difficult— psychologically—to change beliefs, especially when beliefs coincide with casual observations. We hold fast to initial conclusions, showing belief perseverance even in the face of counterevidence, and we seek and attend to agreeable information illustrating our confirmation bias. Second, perceived correlations between sugar consumption and hyperactivity are maintained by a third factor, often in the context of a birthday or other celebrations. These events provide increased access to sugary foods and drinks and are reason for children to be excited and active. Counter to this myth, classic symptoms of hyperglycemia (i.e., elevated blood sugar levels) in most people include excessive thirst and fatigue. Further, blood sugar would be elevated only temporarily in most children, as insulin production begins early in response to the smell and taste of sweet foods to facilitate the glucose uptake, leading to feelings of fatigue. Any “sugar high” would be relatively temporary, much shorter than hours. The skeptical, tentative, and cumulative traits of science are on display (or demonstrated) in this line of research assessing the sugar hype.

Humility To display intellectual humility is to recognize that our beliefs and knowledge might, in fact, be wrong. Humility allows us to engage in open-mindedness, which requires we monitor our confidence in our beliefs (Resnick, 2019). Intellectual humility is a skill essential to design a study with appropriate controls and to evaluate the generalizability of research findings. This requisite humility was described as “productive stupidity” by Martin Schwartz (2008), occurring when we confront the limitations of our knowledge to

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embark in the depth of inquiry that can lead to big discoveries. The best studies, and the best scientists, openly discuss the limitations of the evidence and acknowledge that additional research is needed to support their claims. The controversies reviewed from the psychology of eating demonstrate why it is essential to endorse the scientific attitude when reading, conducting, and evaluating research findings. These controversies spurned advances: Meiselman’s concern of research setting and the replies enhanced evaluation of ecological validity, the use of WEIRD samples and arbitrary BMI cutoffs brought attention to issues of generalizability, and Wansink’s controversies led to broad calls for open science. Learning from these earlier controversies is facilitated with the scientific attitude, as curiosity, collaboration, skepticism, and humility make us more skillful researchers and thinkers.

Dessert: Mouth-Watering Pseudoscience The examples of catchy headlines brainstormed early in this chapter may be linked to articles or products that tout the miraculous power of superfoods or fad diets. Claims like “antioxidant powers” or “boost your brain” are especially catchy and pervasive. But are these claims valid? Is the research reliable? For most people, there is no clear distinction between true scientific and pseudoscientific claims, especially outside of our area of expertise. The term pseudoscience defines the fake or bogus nature of these claims, which achieve credibility by appearing similar to actual science. Take, for example, the antioxidant craze: it certainly seems sciency, with claims these superfoods neutralize free radicals to prevent disease. Yet all fruits and vegetables contain antioxidants, as additives they assist in food preservation (Finley et al., 2011), and the current evidence does not support the use of antioxidant supplements for preventing disease or promoting longevity (Bjelakovic et al., 2012). Fad diets similarly masquerade as sciency—proponents of the fasting trend appeal to our ancestral past when nourishment was not readily available. But fasting, like many fad diets, fails rigorous empirical evaluation and is prone to high rates of dropout given its extreme nature (e.g., Stockman et al., 2018). The rise of the wellness industrial movement further highlights the appeal of pseudoscientific claims from well-known figures and the need for larger societal conversations around the appeal of this industry (Jolly, 2020). How do we distinguish pseudoscientific claims from facts in the study of eating? Pseudoscience is discerned from true science in that it deliberately misleads, influences with anecdotes, relies on vague generalizations, and most importantly lacks falsifiability (Goodwin & Goodwin, 2013). Each of the examples above is touted by celebrities or celebrity doctors influencing with vivid anecdotes. People who use pseudoscience to sell products or promote diets appeal to gut-level heuristics over critical thinking, even providing an avenue for acceptance and belonging via social networks (Chaffee & Cook, 2017). Red flags including making extraordinary claims, promising a quick fix, and articles lacking credentialed authors and peer review alert the presence of pseudoscience

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(Zaborski & Therriault, 2019). The lessons from this chapter, verifying the source of information, using skepticism when evaluating simplified explanations, and recognizing the characteristics of pseudoscience described above, rely on critical thinking to protect ourselves from wasting our time, our money, or more importantly compromising our health when confronting pseudoscience.

Dining Review Key Elements

Recommended Reviews

Whet your appetite: Clickbait

Reexamine this question now that you have finished the meal proper—brainstorm examples of clickbait with nutritional claims and the ways to evaluate the veracity of those claims based on the information in this chapter.

The amuse-bouche: Flavor of

Contrast science and empirical knowledge with other ways of knowing. What are the strengths and limitations of our sources of knowledge?

science Course 1: Methods of inquiry

Brainstorm a research question and follow this question through the scientific method. How might you answer this question with various research designs?

Morsel: Body composition and

Identify three measures of body composition and their relationship with adiposity and health risks.

BMI Course 2: Evaluating research

Use the concepts described in this section to evaluate a research paper on the psychology of eating.

Morsel: Scientific fraud

How was this case of scientific fraud detected? Apply principles from Course 2.

Course 3: The spirit of science

Find examples of researchers in the psychology of eating that exemplify these characteristics.

Morsel: Sugar hype

For what reasons do people believe that sugar leads to hyperactive behavior? What evidence to the contrary is most compelling for you?

Dessert: Pseudoscience

Find an example of pseudoscientific claims around food and nutrition. Note the aspects of pseudoscience displayed and share with a peer.

Gochisousama Thanks to the chef! Recommended reading: ●

Cross cultural research methods: Matsumoto & Hee Yoo (2006), “Toward a new generation of cross-cultural research,” Perspectives on Psychological Sciences, 1(3): 234–50.

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●

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Comprehensive research methods text for psychology: Goodwin, K. A. & C. J. Goodwin (2013). Research in Psychology: Methods and Design (7th ed.). Hoboken, NJ: Wiley. Design and Analysis ○ WEIRD participants https://slate.com/technology/2013/05/weird-psychologysocial-science-researchers-rely-too-much-on-western-college-students.html ○ Evaluating qualitative research: Evidence-based mental health notebook (1999) https://ebmh.bmj.com/content/ebmental/2/4/99.full.pdf Human Participants ○ APA guidelines for human participants https://www.apa.org/research/responsible/ human?tab=5 ○ US Department of Health and Human Services Office of Research Integrity ○ https://ori.hhs.gov/human-subject-research Animal Subjects ○ NIH Office of Animal Welfare https://olaw.nih.gov ○ National Association for Biomedical Research https://www.nabr.org

Glossary Applied research:

goal of solving immediate, real-world problem

Basic (fundamental) research: conducted to investigate underlying principles of behavior and mental processes; goal of the advancement of knowledge Belief perseverance:

inability to change one’s beliefs when presented with new or contradictory evidence

Case study:

a method of inquiry involving detailed analysis of a particular case, person, or community

Confirmation bias:

common tendency to seek, attend to, and remember information that agrees with preexisting beliefs or conclusions

Construct:

a hypothetical factor that cannot be observed directly

Converging operations:

related investigations on the same phenomenon, even using slightly different operationalization and measurement, nevertheless support a common conclusion

Dissemination:

spreading of information; in science, the act of making scientific methods and findings available to the public

Effect size:

quantifies the magnitude of the difference between two variables or groups

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Ethnography:

a method of inquiry where researchers become immersed in a setting or culture and study social interactions, behaviors, or perspectives as a member of the group

Experiment:

a systematic study to determine causal relationships, in which independent variable(s) are manipulated or controlled by the researcher to measure its effects on dependent variable(s) and other extraneous variables are held constant

External validity:

describe the potential for research findings to generalize to other environments, populations, and times

Hyperglycemia:

abnormally high sugar concentration in the blood

Hyperkinetic behavior:

high levels of movement and exhibited behavior, which sometimes is impulsive; also known as hyperactivity

Hypothesis:

a statement of prediction about the relationship between research variables

Internal validity:

confidence in the identified relations between variables, determined to a large degree by the level of control in conducted research

Operational definition:

a statement to describe the specific measurement process for variables in the present study

Paradigm:

a mode or standard exemplifying the methods and/or theories of a science; a way of doing a science

Pseudoscience:

discerned from true science in that it deliberately misleads, influences with vague anecdotes, relies on vague generalizations, and most importantly lacks falsifiability

Theory:

a unified explanation that organizes our knowledge about some phenomenon and serves as the basis for making predictions

Third factor:

an event or variable that can explain an existing relation between two other variables, often through its causation of other events; sometimes called a common-causal variable

Chapter 3 Top Chef Paleolithic: Evolutionary Psychology and Eating Whet Your Appetite: Raw Foods Have you heard of contemporary diets that restrict eating to raw food? What advantages are purported by raw food advocates and what are the downsides? From an evolutionary perspective, why do humans eat raw or cooked foods? When did cooking become a common part of food preparation in human history? The perspective of evolutionary psychology helps answer questions regarding diet and food preparation from our ancestral past to our modern world.

Menu Amuse-Bouche: The Appeal of (Mythical) Ancestral Past Course 1: Evolutionary Psychology Comparative Anatomy Harnessing Fire and the Cooking Hypothesis Course 2: Food Procurement and Foraging Innate Behavior Systems Models of Food Selection Foraging in Contrived Settings Comparisons and Individual Differences Course 3: Mechanisms of Survival The Thrifty Phenotype Basic Emotions in Consumption Dessert: Choosing the Cheesecake? Lactase Persistence Dining Review Gochisousama Glossary

48 49 49 50 52 52 54 58 60 60 61 63 66 67 68 68

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Amuse-Bouche: The Appeal of (Mythical) Ancestral Past Popularity of Paleolithic diets—as evidenced by “paleo” as the most googled diet term in 2013—raises questions regarding an optimal human diet. Purveyors of Paleo diets argue that humans are genetically predisposed to eat foods people ate in periods long ago— from 10,000 to 2.5 million years ago (mya) when hunting and gathering (Pontzer, Wood, & Raichlen, 2018). A top-rated Paleo diet book (Cordain, 2011) promotes greater health “by eating the foods you were designed to eat.” Paleo diets tend to be high in protein and fiber and low in sugar and refined carbohydrates. Coffee, legumes, grains, and dairy products are generally prohibited, and many versions of the Paleo diet emphasize consuming animal-based proteins like beef. On the surface, Paleo consumption seems logical. Diet-related health markers for Indigenous groups—like the Tsimane people living near the Amazon in Bolivia—are superior to people living in industrialized societies. Diabetes, heart disease, high blood pressure, and obesity are much rarer among Tsimane compared to people inhabiting nearby cities (Kaplan et al., 2017). Members of Indigenous societies engage in more movement, with some walking as much as 6–9 hours per day (Leonard & Robertson, 1997), and do not eat processed foods containing combinations of simple sugars, fats, and high sodium content. Indigenous diets are generally favorable to industrialized diets, as indicated by marked increase in chronic illnesses when Indigenous people transition to consumption of packaged foods (Bolivian tribe transitions; Kraft et al., 2018; Manimunda et al., 2011), and the illnesses can persist for generations, as noted in places like Australia. A gap exists, however, between the observed Indigenous diets and Paleo prescriptions (Pontzer, Wood, & Raichlen, 2018), which is where pro-Paleo arguments fall flat. Johnson (2015) describes paleo diets as “myths … of a lost golden age” (p. 101). Analyses relying on evidence from nondecaying isotopes (carbon and nitrogen) indicated that over 50% of calories consumed were from meat, including large and small game. It seemed diets were rather narrow during the Paleolithic period (Richards & Trinkaus, 2009; Stiner, 2006) until more recent research relying on microremains of grains and plant matter in tooth tarter showed that plant-based foods were a Paleolithic staple (Henry, Brooks, & Piperno, 2014). Instead of the meat-heavy, low-carb version portrayed in the Paleo diet, some hunter-gatherers consume(d) as many as 80% of their calories from carbohydrates (O’Conner, 2018). For the Hazda hunter-gatherer society of Tanzania, as much as 15% of their calories come from honey (Marlowe et al., 2014). Honey consumption is particularly important as it was omitted in early ethnographies of over 1000 Indigenous societies comprising the oft-cited research to justify Paleo trends (Eaton & Konner, 1985). Opposed to its mythical portrayals, Paleolithic diets varied by necessity among and across peoples as available nutrients varied. Henry, Brooks, and Piperno (2014) argue that Paleolithic consumption was as wide ranging as the diets of modern humans and further questioned the existence of any major dietary shift in human ancestors since the Paleolithic period. More critical than meat consumption for Indigenous health were

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the nonexistence of processed foods and sedentary lifestyle. A focus on consistent movement and flexible, diverse diet more authentically represents the adaptive Neolithic lifestyle of modern humans (Turner & Thompson, 2013).

Course 1: Evolutionary Psychology Evolution, through the process of natural selection, is not intentional or goal-oriented. Instead, through the process of natural selection, the best-adapted individuals survive and pass on their adaptive traits to the next generation. Individuals that are less welladapted do not survive or reproduce. As the environment changes, adaptive traits in populations change as well. This means that evolution does not create “better” or “superior” organisms over time; instead, shifts in characteristics of populations occur from nonintentional, nondesigned environmental changes. As a basic primer, three mechanisms are necessary for natural selection: variation, selection, and retention. A population must contain members who are different in some way, such as physical features or behavior (i.e., variation exists). Environmental pressure then limits survival for all members of the population, meaning some traits will not be as suited for survival as others (i.e., selection occurs). Finally, there must be a mechanism (i.e., genes) for passing selected traits to subsequent generations (i.e., retention occurs). With an understanding of these key features, we now discuss human ancestry.

Comparative Anatomy Modern humans differ physically from their hominin ancestors, and anatomical variations across our 6-million-year history provide evidence of consumption changes throughout that time (Walker, 1981). The mandible, or jaw, of Australopithecus (circa 3 mya) is noticeably different from that of Homo sapiens. Striations created by the teeth indicate Australopithecines had stronger bites with larger teeth and greater molar surface area (Demes & Creel, 1988), allowing early hominins to chew through hard outer layers of fruits to access inner sustenance (Walker, 1981). As canine teeth (and roots) shortened and incisors shrunk, bite strength weakened. Tool development and dietary changes quickly made the job of cutting food obsolete for the teeth. In fact, Raia (2018) cites the jaw changes of hominins as the most rapid evolutionary change recorded among any primates. The small intestine and large intestine shortened from Homo habilis to Homo sapiens (a transition between 1.5 and 0.5 mya), indicating that the gut had less work to do in later hominins. Either food required less processing by containing less roughage or food was less intact, mechanically or chemically, when it reached the gut. Microbes inhabiting the stomach also changed in this time. When primary diets were fruits, microorganisms in the stomach could help break down food and even pass

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Figure 3.1  Timeline of hominin evolution. Source: Luca, Perry, & Di Rienzo (2010); Verendeev & Sherwood (2017). Image created by Stephanie da Silva based on Luca et al. (2010) and Verendeev & Sherwood (2017).

into the small intestine with food. However, a stomach that provides a cozy home for microorganisms is not advantageous when foodborne pathogens become probable. As hominins who traveled consumed more variety in meat and food, the stomach grew more acidic, and, thus, decreased adverse effects from micro-threats in foods (Dunn et al., 2020). Taste buds also grew more sensitive (Breslin, 2013) as our huntergatherer ancestors capitalized on smells and tastes to find and identify safe foods (Figure 3.1). Further physical changes in hominins of the past 2 million years include a reduction in muscle mass, increased brain and head size, and reduced size discrepancy between males and females (i.e., sexual size dimorphism). To understand these corollaries of dietary changes, we turn to a “striking” discovery—fire, its use in consumption, and its blazing impact on human evolution.

Harnessing Fire and the Cooking Hypothesis This chapter opened with questions regarding raw food and its central role in contemporary dieting trends. Raw food diets are described by several variations of the name raw food like “raw vegan” or “100% raw” and advocates usually require that between 70% and 100% of foods consumed must be raw (Walker, 2005). Food is considered raw if it has

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never been heated to 40–48°C. In contemporary forms, a raw food diet further designates that food should be nonprocessed by modern conveniences, such as pesticides and pasteurization, and alcohol is prohibited. Most of the food comes from plants, although raw animal products (e.g., eggs, fish, meat, and milk) are technically included. The outcomes of raw food diets vary with the rigidity of raw food prescriptions and adherence. Reported health benefits of raw foods include increased weight control, digestion, and energy, but these also occur with greater exercise, lower incident of smoking, and alcohol abstinence that are common among raw food enthusiasts. One of the bestknown studies of raw food consumption, the Giessen Raw Food Study, reported weight loss of about 10 kg for men and 12 kg for women among all participants who followed any variation of a raw food diet (Koebnick et al., 1999; Watson, 2001). Greater adherence to raw food lifestyle increases likelihood of being underweight and missing nutrients (e.g., vitamin B12). Worrisome outcomes include below-normal BMI among nearly 15% of men and 25% of women who follow raw food diets, with nearly 30% of women under age 45 experiencing amenorrhea. Amenorrhea is a loss of menstruation that can be created by a lack of bodily fat stores brought about by insufficient energy consumption or over expenditure. Further, bone mineral content and bone density can be lower among those who consume raw foods compared to control participants of similar ages (Fontana et al., 2005). To sustain body weights on long-term raw food diets, at least 15% of calories consumed should come from non-raw food sources including processed and cooked foods. Cooking foods improves several of their properties for consumption. Physical features are altered to make the food more accessible and chewable. Potatoes and cassava are examples of plant tubers that are difficult to consume without heating them. Cooking also allows safe consumption of some foods; green beans, lima beans, and kidney beans all can be toxic if consumed raw because cyanide is created when they are broken down by the human digestive system. Cooking foods eliminates many foodborne pathogens, such as Salmonella and the Trichinella worm in pork and E. coli in raw chicken (Carmody & Wrangham, 2009). Finally, cooking improves vitamin and nutrient absorption during digestion. Tomatoes and broccoli, among other vegetables, offer more nutrients once cooked, and cooking cabbage elevates vitamins C and K, magnesium, and folate garnered through its consumption. Cooking represents a major shift that impacted nearly every aspect of the human experience, from nutrition to family structures. The increase in cooked foods, as long ago as two million years through harnessing of fire (Luca, Perry, & Di Rienzo, 2010), is intimately connected with physical changes in humans, including changes to the brain. The adult human brain uses as much as 20% of kcal consumed in a day, which is a much greater proportion of daily intake allocated to the brain compared to other animals (Herculano-Houzel, 2012). For children and adolescents, 50–80% of resting metabolic rate can be accounted for by the brain (Kuzawa et al., 2014). Human brain size and body fatness are much greater than that of other animals, and the fat stores are thought to support the brain in times of food scarcity. By comparison, humans have less skeletal

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muscle mass than other animals, allowing energy allocation to the brain rather than muscles (Leonard et al., 2003). Evidence of fire harnessing during a time of explosion in brain growth among humans provided the basis for the cooking hypothesis. Dr. Richard Wrangham and colleagues offered the cooking hypothesis to explain several correlated changes in our evolutionary history: smaller jaws and teeth, smaller male bodies especially in the chest/shoulder regions, larger body size of females, greater affiliation/socialization in multimale and multifemale tribes, increased time walking on two feet, expansion of hominin populations beyond warm latitudes like Africa and Indonesia, and, finally, bigger brains. With reduced muscle mass and less work required by the gut, something afforded through the advent of cooking, physiological processes and energy use by the brain could expand. A larger brain requires more energy, provided by food preparations that yielded more calories. Cooking allowed for greater energy intake, such that evolutionary processes—like brain growth—were not “constrained” by an energy budget. In fact, as we will discuss many times, modern humans excel at food preparation to the point that many of us have an excess of energy sources available to us. To revisit the earlier raw food discussion, Wrangham believes humans now have adapted to eat cooked foods to the point that raw foods alone are unlikely to meet modern human energy needs (Adler, 2013). Cooked food can provide energy from the time we consume it, whereas raw food reaches the colon mostly intact. When mice are fed cooked foods, compared to raw foods, they gain more energy and body weight (Groopman, Carmody, & Wrangham, 2015) and show subsequent preference for cooked foods once they have experienced them. When foods such as vegetables, eggs, and meats are heated during preparation, they provide more calories during digestion (Carmody, Weintraub, & Wrangham, 2011). Other preparation changes, like chopping or blending foods, do not impact energy obtained from them or preferences for them, although mechanical breakdown allows for reallocation of time and energy away from chewing to other activities. Imagine the efficiency gained by grinding foods with a tool, like a mortar and pestle, in place of teeth.

Course 2: Food Procurement and Foraging One of the first and primary purposes of interacting with the world is to procure food by engaging in a range of behaviors along a continuum from innate to learned. We now explore these.

Innate Behavior Systems There are three categories or types of innate behavior systems in animals: reflexes, fixed action patterns (FAPs), and temperament. They are ordered by complexity and flexibility,

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where reflexes are the most simple and rigid of behaviors and temperament is the most complex and amenable to influence. Reflexes. A reflex is a simple response of a part or parts of the body in reaction to specific stimuli. In this sense, reflexes are simple relations between stimuli and responses. Reflexes usually occur quickly, lasting only a brief moment, and most known reflexes serve adaptive purposes like aiding consumption. Mosquitos innately approach the smell of carbon dioxide, which helps them find warm-blooded organisms. Likewise, human infants are born with a host of reflexes that support consumption. Examples are the rooting reflex—turning head toward an object that touches the cheek, sucking reflex—a sucking motion of the mouth in response to something touching the roof of the mouth, and swallowing reflex—closure of the glottis with cessation of breathing and a rise in the larynx when a food source touches the back of the throat (Colson, Meek, & Hawdon, 2008; Nishino, 2013). Abnormal delays or abnormal persistence of these neonatal reflexes, which typically wane with maturation, are signs of neurological problems (Tsai, Chen, & Lin, 2010). Fixed Action Patterns. Fixed action patterns (FAPs) are similar to reflexes in that they are innate responses to particular stimuli or stimulus elements. FAPs differ from reflexes in that: (1) they involve a sequence of actions rather than the single movement most often characteristic of reflexes; (2) they usually involve movement of an entire organism rather than only part of an organism; and (3) their structure is more likely to change across occurrences and with experience compared to reflexes that look very similar each time they occur. Stimuli that trigger or lead to the onset of an FAP are called sign stimuli or releasers, and research often aims to isolate or determine critical features of sign stimuli for initiating the FAP. For instance, squirrels may hoard any type of nut with equal vigor, or they may vary behaviors, such as interest, latency to approach, and protective acts, based on certain nut qualities (e.g., size or color). Nut caching in squirrels is but one case of a consumption-related FAP, with web weaving in spiders and bone burying in domestic dogs as other examples (Vollrath & Seldon, 2007). A pig may toss a piece of food in the air and a raccoon may make “dipping” motions with food as if dousing it in water (Lyall-Watson, 1963). You may recognize FAPs in your pet as when your dog treats the sofa like a wooded burial location. In any case, the animal is carrying out what it was hardwired to do: a series of actions that serve adaptive functions to secure and preserve a (valued) food item. Temperament. This third category of innate behavior is the most flexible, varying the most across conditions and time. Temperament refers to biologically based differences in how people react (emotionally, physically, and cognitively) to stimuli and events (Rothbart & Bates, 2007) and can further include our abilities to control those reactions. Infants often are classified with temperaments that are easy, difficult, or slow-to-warm-up, often through caregiver survey responses (Gartstein & Rothbart, 2003). Temperament can be measured using self-report surveys or, more reliably, by direct observation of behavior, such as how quickly we react, whether we approach or avoid stimuli, how long we interact with stimuli, and emotions displayed like anger or joy.

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Inasmuch as temperament describes interactions with any stimuli, temperament can predict our behavior around food and food-related stimuli. Infants are more likely to accept novel foods if they are more likely to approach (i.e., not avoid or show fear) novel stimuli generally (Moding, Birch, & Stifter, 2014). This means that an underlying tendency to be wary of unknown stimuli (Moding & Stifter, 2016) extends to food and may underlie food neophobia. In turn, mothers of infants with difficult temperaments are more likely to use food as a means of comforting the child, creating a situation where individuals learn to “turn to food” when feeling anxious about unknowns (McMeekin et al., 2013). These tendencies extend to adults, with trait arousability being most strongly connected to eating. Arousal, a state of alert and attention, is positively correlated with dieting, preoccupation with gaining weight, and food as a constant temptation. Arousal is negatively associated with voracious eating, but positively related to secret binging, food phobia, and inabilities to eat (Mehrabian & Riccioni, 1986). The impact of arousal on eating varies across people; high levels of arousal coupled with anxiety suppress intake in some but induce eating in others (Macht, 2008). The role of temperament and personality in eating behavior, including disordered eating and obesity, emphasizes the role of emotionality and self-regulation (e.g., Burt, Boddy, & Bridgett, 2015; Mehrabian, 2012; Stifter & Moding, 2019). Impact of Experience on Innate Tendencies. Reflexes, FAPs, and temperament are considered innate because they appear in an organism’s repertoire without experience like parental modeling or training. But, as discussed in Chapter 7, these innate tendencies can be altered by experiences. Our environments can support their occurrences, leaving them mostly intact, or alter the timing and structure of them. As an example, mosquitoes can be trained to engage in sugar-feeding—an innate tendency—based on odor cues previously associated with successful feedings (Sanford & Tomerlin, 2011). If a squirrel has endless access to nuts and other food sources, its innate FAP to bury them will wane. Finally, in the case of temperament, an aroused child who naturally reacts joyfully and with high alert to environmental signals, such as a birthday cake, may learn to suppress reactions in the face of punitive caregivers.

Models of Food Selection Biologists and psychologists, along with others who study animal behavior, have observed and attempted to describe the ways that animals find, keep, and return to food sources in the wild. To forage is to search for food, and animals’ search strategies are not entirely random but generally are orderly and predictable. In this section, we explore two models of food procurement. As with most behavior models, these were developed to describe existing data/observations and then tested for their ability to predict new observations. When a model adequately predicts and describes food-directed behavior, we can say it has good explanatory power.

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Optimal Foraging Theory. Developed from observing animals in their natural habitats, optimal foraging theory (OFT) argues that animals maximize food gains while minimizing energy expenditures (MacArthur & Pianka, 1966). If all other factors, such as predation risk and the quality of a food resource, remain constant, animals will return to a food source that is easy to access, cache, and consume. When foods of greater quality become available, animals may choose them so long as the energy expense of attaining the richer food is not so great as to offset the increased energy supplied by the food. The factor “energy expenditure” includes variables such as search time, search distance, difficulty of predatory actions (e.g., difficulty of the kill), and ease of consumption (e.g., complexity of access to edible components). When access to food caches is risky, either from nearby predators or conspecific competition over resources, choice of that food resource should decline. In humans, the social and monetary price of the food is included in its expense. The “profitability” of prey, or a food resource, is a ratio of energy gained divided by energy expended. In short, OFT states that food choices will favor options that are most profitable. Foods like insects provide a high profitability ratio because risk and cost of attaining them is low, while the energy they provide, protein and other nutrients, is high. OFT successfully describes food selections, measured by “exploitation”—visits and consumption of food resources—among birds, invertebrates, and mammals (Bence & Murdoch, 1986; MacCracken & Hansen, 1987; Sayers, Norconk, & Conklin-Brittain, 2010; Pyke, 1984). A more contemporary version of OFT is optimal diet theory, and our discussion refers to these models interchangeably. Together, these theories can account for roughly 75–85% of outcomes in studies testing them. This explanatory power is not too bad considering the model has been around for over 50 years and has been tested with varied methods, experimental and nonexperimental, and in myriad species and contexts. The model was created for situations where animals access foods from patches, or caches, such as nuts, seeds, and honey. In patch foraging, the difficulty and probability of attaining energy remains fairly constant, resting on assumptions that food replenishment and threats remain similar over time. OFT is less reliable in its predictions of food selections when prey are mobile or less certain (Sih & Christensen, 2001). One exception is foraging for mobile prey in a stationary manner; the crab spider, for example, forages by setting traps at flower sites, and OFT accurately predicts site selection based on potential food capture and weather threats (Romero & Vaconcellos-Neto, 2004). Weaker predictions are made when the predator also moves to capture prey, though there are efforts to extend the model to account for mobile food capture (Bartumeus & Catalan, 2009). It is believed that OFT tendencies are inherited, meaning natural selection has produced animals that forage economically. The idea of evolved foraging strategies has been criticized (Pierce & Ollason, 1987) because we cannot observe past foraging strategies or their changes across time and generations. Other controversial elements

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Figure 3.2  A foraging bee. Image from Pixabay.

of optimal foraging include assumed abilities to ascertain energy expenses and payoffs, even if unconscious, and—moreover—for behavior to be sensitive to the differential energy expended. For example, current versions of OFT cannot explain observed suboptimal foraging (see reviews by Pyke, 1984; Sih & Christensen, 2001), which is not necessarily detrimental to the theory (Sayers, Norconk, & Conklin-Brittain, 2010). Understanding potential OFT prediction failures, or cases when animals do not behave according to the model, can highlight variables that may impact foraging decisions (Figure 3.2). Such variables include capture success rates based on prey’s ability to hide or evade the foraging predator; the impact of consumption risks, such as parasites, on food selections (Lozano, 1991); and deprivation levels of predators (Bence & Murdoch, 1986). The Matching Law. A second model of food choice is the matching law (TML). In its earliest and simplest form (Herrnstein, 1961), TML states that the allocation of behavior across various food resources will equate, or “match,” the relative richness of concurrently available food resources. This means that, if all else is equal, food choice will be determined by proportions of food availability where preference (indicated by greater percent of choices or time expended) for the richer food source will be demonstrated. TML makes more sense if we apply it to a situation. Imagine that a deer is foraging among rose and lily patches in a neighborhood. Let’s say the flowers at one house,

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House A, replenish twice per month and flowers at another house, House B, replenish once per month. Because there are twice as many roses and lilies provided at House A relative to House B, TML predicts that the deer will allocate twice as much time and effort (i.e., behavior) foraging at House A than House B. Mathematically, it is calculated as a proportion of food available from one house of the total food availability from all resources. In the case of House A and House B, we would predict that two-thirds (67%) of foraging time and effort will be spent at House A since House A provides replenishes twice per month and the only other food resource is House B that replenishes once per 2 month: . Should a third garden, House C, become available that replenishes three 2+1 2 times per month, foraging at House A would change to 2 + 1+ 3 , or one-third (33%). Of course, the wild is not so simple as yards with equally valued plants and equally risky environments. Many other variables influence choice, like personal preference and response effort. Extensions of TML, mostly as variations of the generalized matching law (Baum, 1974, 1979), aim to account for these factors. To test predictions of TML, rates of responding and time allocation are measured based on experimental manipulation of reward probability, magnitude and quality, and schedule of availability. Although TML is a model of choice for any resource, most studies have assessed it using food outcomes. In rats, for example, choice is tested among response options that produce food pellets, access to sweetened condensed milk, or rat chow. In pigeons or other birds, choices among response options that lead to seed and grain (varying in quality and timing of access) options are measured. TML describes fairly well laboratory assessments of choice and has been extended to natural environments (e.g., foraging situations) with similar success (Poling et al., 2011). Keep in mind that TML aims to describe inclinations of choice fundamental to all organisms. This is a tall order for any scientific model. Although TML describes choice among options that pay off variably, with some unpredictability, there are cases when TML does not closely predict or describe choices. Challenging scenarios for TML include cases when food is delayed and varies in magnitude and situations when choice is tested in discrete trials rather than free/open behavior markets. Delays to food access and size of food caches are important limitations because in nature there are many situations when food resources vary in these ways (e.g., in harvesting a crop). Biological preparedness wields greater influence by frequency of food encounters over size or amount of food obtained in a single encounter, along with a predisposed insensitivity to delayed outcomes. When a small amount of food (such as 1 g) is provided immediately and a larger amount of food (such as 3 g) is provided 10 seconds later, rats and pigeons will choose the smaller amount. Animals prefer getting a sure thing right away, even if it leads to less food earned in the long run. Though our bias toward immediate payoffs poses challenges for TML, it makes perfect sense evolutionarily. In the wild, an effective strategy is to consume immediately available resources rather than taking chances on potential resources in the future. All this is to say that we are affected by frequency and

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immediacy of food to such an extent that larger, delayed food resources garner much less of our effort and attention than would be predicted by traditional economic models. This hypersensitivity to subtle but quick rewards may have served humans millions of years ago but provides conundrums in modern living. Another difficulty for TML is accounting for choices influenced by language, like information or rules (Pierce & Epling, 1983; Poling et al., 2011). A choice of frozen yogurt over ice cream, for instance, cannot be accounted for by TML because the decision is driven by future-oriented information such as calorie or fat content. For the most part, sensitivity to information, such as nutrients and long-term impacts, is advantageous in contemporary environments. A student of Author SS, for example, developed a self-rule to drink a 300 mL glass of water each morning before beginning her cup of coffee. Her morning water consumption was driven by language-mediated information, specifically the importance of hydration, rather than immediately available and tempting variables (e.g., aroma, taste, and calories of drink options). Situations like these expose other environmental variables that come to the fore in decision making.

Foraging in Contrived Settings Based on OFT predictions and contemporary observations, humans will behave in lessthan-optimal ways in their current industrialized worlds of food abundance. Imagine if we minimized energy expense while maximizing energy consumption. It would not take long for detrimental health effects to result. Some experts advocate designing everyday settings to make healthier food selections occur per the OFT and TML models (Brunstrom & Cheon, 2018). Approaches include making the desirable food choices more viscerally appealing, conveniently available, and attainable—even set as the default item, and selected ahead of time (through precommitment when deprivation levels are low; Liu et al., 2014). These strategies minimize conflict between genetic tendencies and modern temptations. Though food procurement can be a source of stress, the activity has cognitive and physical benefits. Compare the task of finding and securing food in the wild compared to situations in captivity, where food is provided in limited offerings each day. Animals raised with scheduled feedings offered freely tend to gain weight, engage in less activity, and even develop signs of boredom and agitation (e.g., pacing). A trend toward requiring animals to find and catch foods is part of enrichment programs for animals housed in captivity, such as at zoos or preservation centers. Increased play and body care, along with fewer signs of boredom, are observed when animals are provided food choices and their growth patterns remain similar to situations of scheduled feeding regimens (Boga et al., 2009; Keskin et al., 2004). The freedom to choose what we eat, even if attainment of the food source is more effortful and the options are similarly nutritious, seems to have health benefits in and of itself.

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Morsel: Foraging in the Cafeteria Cafeterias are eating establishments where food is ready and displayed for customer selection. They were popularized in the United States, especially in schools and workplaces, and are characterized by customer self-service. Because cafeterias involve an environment of many food options, they can be viewed as human foraging scenarios where OFT and TML can be applied. Based on the quality, quantity, and availability of food in the cafeteria, patrons’ choices can be predicted in the same way that we predict animals’ selections among food caches. Even more, cafeterias provide excellent testing grounds for determining whether food selections can be altered by changing the availability and arrangements of food options. In one test of response effort, teenagers in a school cafeteria were more likely to choose and eat precut oranges compared to whole oranges. That is, simply making oranges easier to eat, or less effortful, enhanced their selection (Swanson, Branscum, & Nakayima, 2009). In general, 89% of studies in which healthier options were made more convenient, marked by faster attainment with less effort, showed increased choice for the healthier food options (Gordon, Dynan, & Siegel, 2018). Specific successful strategies were keeping fruits and vegetables in sight lines and as first available options, making healthier options accessible through “express lanes,” rebranding desirable food choices with appealing messages and social norms (e.g., indicating that most students eat at least one vegetable at lunch), and providing incentives for choosing fruits and vegetables. A final strategy that swayed selection in favor of vegetables was the offering of vegetable samples to customers while they waited in line. Reducing the price of healthy options, as done for carrots and fresh fruit in a cafeteria and low-fat options in vending machines (Hannan et al., 2002), also increases consumption of these items by as much as four times their baseline consumption. As discussed in Chapter 6, a more controversial but equally effective approach would be increasing price of less desirable food choices, as observed with soda and cigarette taxes (Kansagra et al., 2015). An important consideration in interpreting these cafeteria findings is that choice/ selection does not always correspond with consumption. Although there are several documented cases where short-term selection of food in the cafeteria changed after environmental manipulations, it is less certain (1) whether consumption per se is altered and (2) whether behavior changes lasted over time. In one study, for example, positive messaging and convenience bundling led to increased selection of fruits and low-fat milk at schools relative to their selection at comparable schools without the intervention, but researchers did not observe increased consumption of the items (Quinn et al., 2018). Though OFT accounts for consumption difficulties, neither OFT nor TML measures the amounts of food consumed after behavior/ choice is allocated toward particular resources. To ensure that human interventions produce real benefits, consumption tracking is critical.

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Comparisons and Individual Differences TML and OFT provide promising abilities to predict food search and choice strategies. You may be wondering at this point which theory of food selection is superior. Of the two theories, OFT is the more well-known and studied, with 19,500 hits in Google Scholar compared to 5,560 hits for TML. Both models provide useful starting points with some challenges. Animals’ strategies are admittedly bound by sensory abilities, memory, and deprivation levels (Laughlin & Mendl, 2000). Some animals, for instance, rely more on olfactory cues whereas others rely on visual search strategies. Based on genetic history and experience, animals may use win–win strategies, where they return to food caches that once paid off, or win–shift strategies, such that they move on after depleting a food source (Guitar et al., 2017). Animals may also differ in which exergy expenditures influence their behavior most. In marmosets, for instance, food selection was impacted more by distance to food cache than by the quality of food—even if overall ratio of expense/ gain was similar (Ahlborn & Rothe, 1999). Animals have different diet preferences, based on taste or other factors of palatability, which can challenge OFT predictions made according to energy alone (Sih & Christensen, 2001). A final variable not yet discussed is group foraging, as when members compete and cooperate for resources shared with others. The Ideal Free Distribution model, a TML and OFT derivative, predicts that richer food resources will attract more behavior and members of the group than leaner options, via analysis at the level of individuals and the group, respectively. These predications have been tested and supported in free-range pigeons and college students as they distributed behavior among seed patches or money prizes (Kraft & Baum, 2001; MorandFerron, Lalande, & Giraldeau, 2009). If there is a single message to be taken from this section it is that food procurement and choice result from an interaction of genetic propensity and experience, or two selection processes. Phylogenetic selection—at the level of the gene—prepares organisms with innate tendencies (e.g., maximizing energy gains) via natural selection over many generations. Ontogenetic selection—at the level of behavior—represents adaptation within the lifetime. As maladaptive or unsuccessful behaviors occur, their likelihood should dissipate and fall out of the repertoire. This combined approach helps explain why humans can be swayed by verbal information, like nutrients, even without biological propensity to select nutritious foods. Shared impacts of selection processes are discussed further in the next section about survival.

Course 3: Mechanisms of Survival A cry of hunger is one of our first behaviors of life, a fundamental survival technique. Through evolutionary processes, babies who cry when hungry are more likely to survive and caregivers who recognize those cries are more likely to ensure the survival of their genes. If either action is absent, the crying or responsiveness to it, survival probability plummets.

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In this section we explore two other ways humans are equipped to survive: physical adaptations in times of limited nutrients and emotions related to (potential) consumption.

The Thrifty Phenotype Phenotype refers to observable characteristics that result from the expression of genes. Genotype, by comparison, refers to genes located in pairs of chromosomes. Genes have variants known as alleles that are inherited from parents to the offspring. As an example, consider phenylketonuria (PKU), an inherited disorder of metabolism and also the first specific cause identified for intellectual disability (Blau, 2016). PKU is caused by variants of the gene that code for the enzyme phenylalanine hydroxylase (PAH) located on chromosome 12. PAH is an important enzyme that converts the amino acid phenylalanine to tyrosine, a vital step for our body to function. Without sufficient PAH, phenylalanine accumulates in the blood, with neurotoxic effects causing intellectual disability. PKU is inherited in a recessive pattern, thus both biological parents of the offspring must carry an altered variant of the PAH gene and pass that PAH variant to the offspring for PKU to occur. However, both parents may also have a normally functioning copy of that gene, and since PKU is recessive, the parent would not have signs or symptoms of the disorder (Blau, 2016). This genotypic blueprint is not a fated story, however, as preand postnatal environments can affect development and phenotypic presentation. When phenotypes are more amenable to environmental influence, we say their phenotypic plasticity is high. In the case of PKU, treatment with a special diet low in phenylalanine greatly reduces neuropsychological deficits, though routine evaluation is necessary (Blau, 2016). On the other hand, untreated patients show phenotype intellectual disability (Ramus et al., 1999). Fortunately, all newborns are screened for PKU in much of the world. Obviously, not all phenotypic alterations from diet are intentionally implemented or have positive outcomes, as in the case of PKU corrections. Malnourished environments can alter phenotypes, especially in early life. Even if a genotypic code prescribes particular size and weight based on chromosomes of the parents, a child can grow less—that is, be phenotypically smaller—given a lack of resources to sustain what was prescribed by their genes. Reasons for malnutrition in utero vary and can include placental malfunction, underconsumption by the mother, or toxins impacting absorption or processing of nutrients. The ability to slow down growth in dire times is adaptive, or even “thrifty,” and is preferable to an inflexible phenotype (Lindsay & Bennett, 2001). Survival could be at risk during persistent pursuit of an impossible size in a malnourished context. Hales and Barker (1992) are credited with coining the phrase thrifty phenotype to describe relations between prenatal and infant growth restriction with subsequent metabolic diseases (see also Barker, 1990). Low birth weight is connected to type 2 diabetes, including negative effects on organs involved, and comorbid conditions such as hypertension and cardiovascular disease (Barker et al., 1993). This revelation, now generally accepted, was quite remarkable because prior evidence of shared diabetes

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risks among twins supported genetic attributions. Instead, deficits in insulin production and response can be attributed to fetal experience in utero more than genes (Poulson et al., 2002). Restricted infant growth and thinness at birth are associated with subsequent decreased glucose tolerance. Two specific effects explain this thrifty phenotype. First, a fetus that grows with limited resources develops cells that function suboptimally for processing sugar—creating a case of sugar sensitivity. Second, internal organs, such as the pancreas, do not grow and develop as many cells as they would in times of nutritional abundance. The impoverished organism is served well in the short term by fewer cells and hypersensitivity to sugar because diminished processing of sugar allows greater energy utilization and less energy expenditure (Hales & Barker, 2001). It is only when environmental conditions become rich that this prior frugal development becomes a problem. When energy-dense foods are introduced, cells can become taxed or overwhelmed— unable to tolerate glucose—with accelerated intake. The inability to process newfound energy/sugar levels leads to weight gain and metabolic disease (Hales & Barker, 2001). Thus, the combination of early life undernourishment with subsequent overnourishment breeds type 2 diabetes. Identifying risk level in early life can be difficult since low birth weight (under 3000 g) is uncommon in many nations where diabetes is prevalent. Instead, childhood growth patterns can be monitored for diabetes risk. Low weight and/or BMI as a baby, with accelerated growth and weight gain beginning between ages 2 and 7 is a notably risky trend. The limited or reasonable sustenance in early life followed by abundance and overconsumption in childhood are a “one-two punch” to the endocrine system that develops under one set of conditions and is later overwhelmed by available sugar. Negative effects of these lifestyle transitions have been observed among Indigenous groups that transition from traditional lifestyles (e.g., hunting and gathering) to contemporary diets of processed foods. In Canada, where diabetes prevalence has skyrocketed in the last 30 years, comparisons among Inuit and Oji-Cree support the idea of a thrifty phenotype. Many Inuit prescribe to traditional lifestyles characterized by limited foods from their proximal environment, whereas Oji-Cree follow a more modern lifestyle. If the thrifty phenotype remains in environments of limited resources, as is the case with Inuit, there is no increased risk for metabolic disease. Inuit, for example, though genetically harboring similar risks for diabetes, have low prevalence of diabetes. Oji-Cree, however, experience high rates of diabetes. It appears that, although malnutrition is low in current times, past periods of malnourishment among certain populations created a thrifty genotype (Neel, 1962) where a tendency to conserve energy expenditure (e.g., by thwarting cell growth and insulin production) is genetically endowed and not just a result of direct experience with malnourishment. This thrifty genotype is more likely to exist among populations that more recently lived Indigenous lifestyles, such as native tribes of Canada, United States, Brazil, and Australia. In all cases, Indigenous populations experienced higher prevalence of diabetes than other subgroups when the populations transitioned to situations of food abundancy. Working together, nature and nurture provide efficient ways to use energy resources to support survival in times of scarcity. Some humans have developed a

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thrifty genotype such that their genetic code prescribes less insulin production and response, especially in the face of limited resources, and can create a thrifty phenotype when needed. These combined histories—phylogenetic and ontogenetic—set up the body for regulation failures when the individual is faced with plentiful processed foods and drinks. The impact of environmental factors on the expression of genes is called epigenetics, relevant to understanding diabetes as heritable changes in gene function caused by lifestyle help explain the increased incidence of diabetes in the developed world. Thusly exists a complex interplay between evolutionary adaptation and modern lifestyle.

Basic Emotions in Consumption Emotions involve expressive, behavioral, and physiological features and are influenced by cognitive, evolutionary, and sociocultural processes (Scarantino, 2016). Charles Darwin (1872) may have been the first to recognize, report, and provide evidence of universally experienced and expressed emotions in his book The Expression of the Emotions in Man and Animals. Darwin saw similarities in emotional expression across species and concluded that emotions result from natural selection. That is, animals failing to experience, express, or perceive emotions to or by others were less likely to survive. Imagine how perceiving anger or fear can facilitate safe interactions or hierarchies. Since Darwin, evolutionary and motivational psychologists have explored the idea of basic emotions, with most identifying between 6 and 10 universal emotions that play roles in “fundamental life tasks” (Ekman, 1999, p. 46) across cultures. Across nearly all taxonomies, joy, sadness, fear, anger, surprise, and disgust are cited. The concept of basic, or primary, emotions forms one theoretical perspective to explore the relationship between feelings and eating. This evolutionary perspective points to emotions surrounding consumption, as described in Table 3.1. Potential dangers of consumption, like exposure to predators, foodborne pathogens or toxins, and postingestion lethargy, are more likely to be encoded and recalled with the help of emotions attached to them. That is, acute activation of emotions adds meaning to information (e.g., location, tastes), influencing subsequent consumption accordingly. If fear-inducing events happen in pursuit of prey, probability of again pursuing that prey may be reduced. Consumption is more likely to be repeated when it is correlated with positive emotions. Gutjar et al. (2014) asked men and women to rate their emotions in a computer program after trying a breakfast drink. Participants were given six positive emotions and six negative emotions to describe their experience: desire, satisfaction, pride, hope, joy, fascination, disgust, dissatisfaction, shame, fear, sadness, and boredom. Subsequent choice of the breakfast drink was more likely if pleasant emotions occurred with its initial consumption. Even when emotional states are caused by events unrelated to food, they can impact consumption. For instance, foods are more accepted when experiencing positive affect and less accepted when experiencing negative affect, regardless of the events that triggered the affect (Edwards, Hartwell, & Brown, 2013).

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Table 3.1  Emotions and their potential functions in consumption Emotion

Preconsumption/ Potential Function Example

Postconsumption/ Potential Function Example

Joy/Happiness

Positive reaction to a sweet smell predicting tasty, energy-dense food

Positive emotion to satiety, energy intake

Surprise

Surprise to finding an unexpected food cache or finding that a food cache is unexpectedly depleted

Surprise to a taste that does not match expectations (based on appearance or smell)

Anger

Strong negative affect, sometimes accompanied by aggression; can trigger eating in those with low emotion regulation

Increased agitation from caffeine consumption and alcohol withdrawal

Sadness

Sadness to loss of resources, food Sadness increases or decreases after or otherwise; can be a precursor to binge eating, feelings of satiety consumption, especially if combined with sense of helplessness

Disgust

Disgust at sight, smell, or texture of potential food source

Disgust at taste or nausea produced by a food source

Fear

Withdrawal and avoidance to smell signaling toxicity; fear induced by nonfood threats can lead to consumption (i.e., “comfort” eating)

Fear to potential outcomes from vomiting, fever, and other symptoms of poison; anxiety symptoms from reactive hypoglycemia

Differentiated neural correlates of the basic emotions are generally acknowledged (see Lindquist et al., 2012, for a review) and functions of these brain areas are further described in Chapter 4. For instance, joy and surprise are associated with reward pathways rich in dopamine, and underactivity in serotonin pathways is correlated with reported sadness (Panksepp, 2007). We may collectively understand the label and expression of disgust or joy, yet the common experience of emotions do not necessitate their innate status. Emotions and their expressions are at least partially acquired through social mechanisms, like contagion (Rozin, 1996). And we do not have to experience emotions directly for them to impact our eating and drinking. Since we are born with strong tendencies to be sensitive to others’ emotional expressions, we are less likely to consume foods when we perceive disgust in others as they consume those foods (Phillips et al., 1997). Both disgust from tasting substances and observed disgust in others activate the anterior insula, the “gustatory cortex” (more in Chapter 5), which indicates the close connection between experienced and perceived emotions. A primary way we view others’ disgust is in their facial expressions, but other cues—like disgust odors shared via body sweat— also indicate disgust (Zheng et al., 2018). Our food choices can literally be affected by an odor emitted from others who are consuming a food!

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Evolutionary accounts of emotions traditionally are at odds with socio-cognitive accounts, like two-factor theory (Schacter & Singer, 1962), that focus on a psychological appraisals of physiological states and environmental cues in creating a perceived emotion. Even though emotions are biologically evident, modern neuroscientific evidence demonstrates far more nuance than discrete centers for emotional primaries. A more recent approach to emotions, theory of constructed emotion (Barrett, 2006), integrates biological and socio-cognitive perspectives. According to this perspective, the vivid experience of emotion is a central feature of the human mind, constructed by a mosaic of brain activity to provide meaning to experiences, with similar patterns of activity when an emotion is experienced, imagined, or observed (Bastiaanen, Thioux, & Keysers, 2009). Just as Darwin advanced the principle of variation within a species and environment, the biological basis of emotional experience varies across individuals (Barrett, 2013). Our brain embodies multiple predictions of upcoming events to ensure we respond optimally. Brain regions and their neurons are multipurpose, and emotional experiences are created by multiple patterns of neuronal activity (Barrett, 2017). Given that our brain functions to ensure we have sufficient resources to survive, grow, and reproduce, it is not surprising that the mosaic of brain activation during emotional experience overlaps with the brain networks responsible for seeking and securing energy resources. By this explanation, we do not gag because we are disgusted, but experience disgust as we make active predictions from internal sensations to avoid a potentially harmful food (LeDoux & Brown, 2017). A biopsychosocial approach to emotions, as compared to an evolutionary approach alone, helps account for individual differences in emotionality. More reactive temperaments acquire aversions, marked by disgust and avoidance, more easily (i.e., in fewer trials). Disgust sensitivity, usually measured by survey (e.g., Food Disgust Scale; Hartmann & Siegrist, 2018), varies across individuals. People with higher food disgust sensitivity scores are more likely to reject new foods, especially based on texture, eat fewer varieties of foods, and waste food (Egolf, Siegrist, & Hartmann, 2018). Women are more likely than men to have higher disgust sensitivities, which fits with their greater sensitivity to smells generally, though this does not result in differences in perception or consumption (Spence, 2019). Other individual differences include proneness to mood dysregulation, like bipolar disorder and major depression, such that more intense and prolonged periods of negative affect—sadness and fear—are experienced. Propensity for negative affect, particularly in obese individuals or chronic dieters, is correlated with increased consumption. As indicated thus far, disgust is a particularly powerful emotion in the context of consumption. We are more disgusted by food signals of real—not just perceived— threats, like pathogens from souring and waste products (Oaten, Stevenson, & Case, 2009), which validates the use of emotions in aiding survival. Rozin and Fallon (1980, 1987) notably identified four types of food rejections, one of which is the emotional experience of disgust. The most memorable aspects of consumption are those critical for staying safe, and disgust serves a critical role of blocking consumption when risk is present. Fecal matter is the only universal substance of disgust but does not elicit disgust

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until the toddler years or later (Rozin et al., 1986), further supporting socialized origins of emotion. Our aversive reaction to the idea of consuming feces is so strong that, even when told it is chocolate, most people refused to eat a brown nugget provided to them on a table after being shown a virtual scenario where a dog walked across the table and “pooped” the nugget (Ammann et al., 2020). A final aspect of emotions related to consumption is whether the emotions are oriented to the past, present, or future. When experiencing future-oriented emotions, individuals are more likely to make choices that benefit their future selves—for example, choosing nutrient-rich vegetables and fruits rather than processed foods (Winterich & Haws, 2011). When sadness generates self-focused beliefs with less hope about the future, rewardseeking becomes more likely, illustrating the negative-state relief model of consumption (Cialdini, 1973). Consumption becomes more likely as food is a major source of reward (Dorison et al., 2020) sought to “numb, distract, and soothe, emotions” (Kemp, Bui, & Greer, 2011, para 5). Distracting tasks can alleviate ruminations—in-the-moment recurring focus on negative affect—and, resultingly, the use of consumption to alleviate negative affect (Kemp, Bui, & Greer, 2013). The greater number and variety of reward outlets available, the more a person can move beyond negative affect to seek nonfood rewards. Evolutionary psychology provides a useful framework to comprehend interactions with food in humans and our animal relatives alike. From evaluating foraging patterns to interrogating the appeal of ancestral diets, eating is best understood through comprehension of evolutionary principles. The thrifty phenotype and theories of emotion provide examples of the interplay between genes and environment and the importance of the biopsychosocial model taken by this text as consumption is explored further in these frameworks.

Dessert: Choosing the Cheesecake? Lactase Persistence You likely are familiar with the term lactose intolerance as it is experienced in a majority of adult humans. A 2017 estimate found the global prevalence is 68%, where the highest prevalence was 70% in the Middle East and the lowest prevalence was 28% in areas of Europe. Its prevalence is actually higher, between 69% and 80%, when genotyping measures (i.e., assessment of genetic structures) are used instead of self-reported symptoms of intolerance (Storhaug, Fosse, & Fadness, 2017). This discrepancy indicates that some adults are intolerant but function with symptoms and do not realize or report problems with lactose. Particularly in Euro-American regions, lactose intolerance—sometimes classified as a subtype of lactose maldigestion—is discussed as a medical condition because it often requires dietary changes or pharmaceutical treatment. Lactose intolerance, or lactose malabsorption, can reveal itself as quickly as 15 minutes after consuming foods containing lactose, a sugar found in milk and many products made from milk (i.e.,

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“dairy products”). Symptoms differ across individuals in type and severity, ranging from discomfort with gas to cramping with diarrhea (Carroccio et al., 1998). The cause of lactose maldigestion is an absence or depletion of lactase, the enzyme responsible for breaking down lactose, in the gut. Three categories of lactose intolerance include primary, the most common, due to a reduction in lactase production as we mature from babies to adults; secondary, due to trauma or disease to the small intestine that prevents lactase production; and congenital, due to a recessive genetic mutation marked by the absence of lactase production from birth (Harrington & Mayberry, 2008). The interesting twist is that, at least in its primary form, lactose intolerance is the norm in the animal kingdom. In fact, humans are the only animals who process lactose as adults. All others lose their lactase production—and, thus, the ability to digest milk—as part of postweaning maturation. Viewing this topic through an evolutionary lens, focus shifts from lactose intolerance to lactase persistence, the continued production of lactase into adulthood that peculiarly evolved among 25–75% of humans across various subpopulations. Lactase persistence results from a dominant genetic allele that is especially likely among Northern Europeans (Swallow, 2003). Humans who continued lactase production were more likely to survive from milk sources in dire times while those without lactase were more likely to suffer when meat and plant material were unavailable. Genetic testing indicates that lactase persistence evolved separately among subgroups of Europeans and Africans, illustrating the strong environmental pressure for phenotypic processing of milk products based on cultural practices (Tishkoff et al., 2007). In cultures that do not practice dairy farming, such as many areas of Asia, lactase persistence is low (Itan et al., 2009). The next time you ponder that cheesecake dessert, consider yourself lucky if your lactase persistence allows you to process it without side effects. If you are lactose intolerant, or lactase nonpersistent (Swagerty, Walling, & Klein, 2002), you can (1) indulge in the cheesecake knowing that you may later pay a price, (2) opt for the cheesecake with a dose of prescription lactase (taken orally) to ward off maldigestion symptoms, or (3) skip the cheesecake altogether.

Dining Review Key Elements

Recommended Reviews

Whet your appetite: Raw foods

Have you heard of a raw food diet? Think of your typical daily intake. What percent of the foods you eat are raw?

The amuse-bouche: Appeal of Describe diets of hunters and gatherers. What aspects of their diets seem critical for health benefits observed among (mythical) ancestral past indigenous groups? Course 1: Evolutionary psychology

What benefits, historically and in your life, were/are provided by cooking foods?

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Key Elements

Recommended Reviews

Course 2: Food procurement

Apply OFT and TML to food shopping decisions or food choices in a cafeteria. What similar and different predictions would they make?

and foraging

Morsel: Foraging in the cafeteriaWhich strategies for nudging better choices in cafeterias do you think would work for you? Is it possible to apply them to your home or other eating situations? Explain. Course 3: Mechanisms of Survival Dessert: Lactase Persistence

Imagine you are at dinner with family and explain to them the thrifty phenotype account of the connection between low birth weight and risk of diabetes. From an evolutionary perspective, why would lactase continue to be produced in people who farm cattle?

Gochisousama Thanks to the chefs! ●

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Rozin, P., & A. E. Fallon (1987), “A perspective on disgust,” Psychological Review, 94(1): 23–41. Tracy, J. L., & D. Randles (2011), “Four models of basic emotions: A review of Ekman and Cordaro, Izard, Levenson, and Panksepp and Watt,” Emotion Review, 3: 397–405. Turner, B. L., & A. L. Thompson (2013), “Beyond Paleolithic prescription: Incorporating diversity and flexibility in the study of human diet evolution,” Nutrition Review, 71(8): 501–10. Ulijaszek, S. K. (2002), “Human eating behaviour in an evolutionary ecological context,” Proceedings of the Nutrition Society, 61: 517–26. Check out National Geographic’s interactive map of Stone Age menus: https://www. nationalgeographic.com/foodfeatures/evolution-of-diet/

Glossary Adaptation:

a change or the process of change by which an organism or species becomes better suited to its environment

Amenorrhea:

the loss of menstruation or menstrual cycles

Arousal:

state of being physiologically activated, as indicated by vigor, energy, and tension

Biological preparedness:

inherent predispositions, usually in reference to behavior or learning abilities

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Cafeteria:

a restaurant or dining room where customers serve, or are served, an arrangement of precooked option; often seen in schools and some businesses

Choice:

the act of selecting a decision when there is more than one option

Cooking Hypothesis:

an explanation for several changes in evolutionary history from incorporating cooked foods into our diet

Corollaries:

a direct or natural consequence or result

Epigenetics:

the study of heritable changes in an organism caused by modification of gene expression not attributed to alterations of the DNA sequence.

Evolution:

the gradual development and adaptation of organisms

Fixed Action Patterns (FAP): innate sequence of responses to specific stimuli or stimulus elements Food neophobia:

an intense fear of new or unfamiliar foods

Forage:

to search for food

Genotype:

genetic code where the alleles comprise the paired chromosomes from both parents

Hominin:

a primate of a taxonomic group that comprises those species regarded as human (ancestral to humans)

Homo sapiens:

the primate species to which modern humans belong

Lactase:

the enzyme responsible for processing lactose

Lactase persistence:

continued production of the enzyme, lactase, into adulthood; only occurs in humans

Lactose:

a sugar found in milk

Lactose intolerance:

a digestive disorder, or form of maldigestion, occurring from too little production of lactase for digesting lactose

Matching Law, the:

a mathematical model that predicts relative responding across options based on relative rates of reinforcement available from those options

Natural selection:

the process by which organisms that better adapt to their environment tend to survive longer and produce more offspring

Nature–nurture debate:

traditional dichotomous approach to explaining behavior by appealing to either innate predispositions (nature) or lifetime experiences (nurture)

Neophobia:

fear of the unfamiliar or something newly introduced

Ontogenetic selection:

refers to behaviors adapted within lifetime

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Optimal foraging theory:

a theory that expresses animals maximize their food gains while minimizing energy consumption

Pathogens:

virus, bacteria, or disease that can cause illness

Phenotype:

observable characteristics that occur due to our genes and environment

Phenotypic plasticity:

ability for various phenotypes to result from a single genotype based on environmental conditions

Phylogenetic selection:

refers to genes that prepare organisms with innate tendencies that happen due to natural selection over many generations

Reflex:

the relation between a specific stimulus and a response it elicits; usually involves movement of only one or more parts of an animal

Releaser:

see sign stimulus

Retention:

maintenance of traits or features across generations, as when chromosomes retain genetic code from parents to offspring

Roughage:

indigestible materials within food that assist with passage of waste through the gut; also known as dietary fibers

Selection:

relatively greater success, or survival rates, of some traits based on environmental pressures or demands

Sign stimulus:

a stimulus that triggers the onset of a FAP; also known as releaser

Temperament:

biologically based individual propensity in reactions to stimuli and events, especially novel ones

Theory of constructed emotion: an explanation of emotions that rest on mental appraisal of neurophysiological states and context Thrifty genotype:

genetic predisposition for organisms to survive in times of low energy intake through maximum sensitivity to sugar and minimum sensitivity to insulin

Thrifty phenotype:

trait expression, marked by less cell development and organismic growth, resulting from early life exposure to limited nourishment

Variation:

differences among members of a population

Chapter 4 This Is Your Brain on Food: The Biopsychology of Eating Whet Your Appetite: What Is Your Comfort Food? What is your personal comfort meal? Think of the meal you want after a stressful day, one that provides solace when you are sad or coziness on a cold rainy night. For many of us, comfort meals share certain characteristics, often warm and palatable, containing both carbohydrates and fats. How does your brain interpret and experience your comfort food to provide those warm, fuzzy feelings? These questions can be answered by examining the brain on food, a central focus of this chapter.

Menu Amuse-Bouche: Beyond Hunger Pangs Course 1: The Bread and Butter—Fundamental Principles of Biopsychology Like Peanut Butter and Jelly: The Nervous System and Endocrine System Motivation Course 2: The Balancing Act—Metabolism and Homeostasis Course 3: Time to Eat! Hunger and Satiety Signals Course 4: The Brain—Head Chef and Chief Executive Officer It’s All Gravy: Neurotransmitter Signaling Integration Dessert: Pleasure, Appetite, and Endocannabinoids Dining Review Gochisousama Glossary

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Amuse-Bouche: Beyond Hunger Pangs Think back to the last time you were hungry, perhaps after you woke up this morning. What did that hunger feel like? Does hunger mean powerful grumblings of your stomach, motivating your first meal? Or it is more cerebral, a message from your brain reminding you to fuel up for the day? Early researchers Cannon and Washburn (1912) “felt” the sensation of hunger occurred from stomach contractions, so Washburn swallowed a balloon designed to measure pressure in his stomach. Washburn’s reported hunger pangs coincided with registered constriction of the balloon, and the stomach contraction theory of hunger was born. As researchers learned more about the signals in the body, attribution of hunger to stomach contractions alone seemed too simple. Janowitz and Grossman (1949) aimed to disentangle gastric factors and oral factors in feeding, differentiating the role of stomach contractions and the presence of food in the gastrointestinal tract from chewing and swallowing. To isolate these factors, they used sham feeding procedures (interrupting the esophagus so food consumed does not reach the stomach) and intragastric feeding (depositing food directly into the stomach through the abdominal wall) in rats. They discovered an inconsistent relationship between gastric factors and satiety: the actions of chewing and swallowing food inhibited hunger even in the absence of food reaching the stomach. Gastric factors and oral factors cooperate to produce satiety and to regulate food intake. Similarly, infusion of nutrients and glucose directly into the rat digestive system does not reduce oral food intake proportionately to the energy received. This led to the hypothesis that regulation may involve more complex mechanisms than simple nutrient detection (Nicolaidis & Rowland, 1976).

Course 1: The Bread and Butter—Fundamental Principles of Biopsychology When Authors LC and SS teach their courses on the psychology of eating, an organization similar to this text is used, dedicating time to research methods, evolutionary theory, and the physiology of eating. Students may ask, “Is this a psychology course or a biology class?” to which we answer Everything psychological is simultaneously biological (Myers, 2011). It is impossible to fully appreciate eating and drinking without an understanding of fundamental biopsychological principles, the physiological building blocks of subsequent chapters. As such, the biopsychology of eating demands significant discussion of the brain. To engage with the biopsychological evidence in this chapter, it is helpful to understand a few key features of the nervous system (Table 4.1).

Like Peanut Butter and Jelly: The Nervous System and Endocrine System Cooperation between the body’s two communication systems, the nervous system and endocrine system, is essential to the biopsychology of eating. In the nervous system, cells

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Table 4.1  Principles of Nervous System Function Principle

Example

Complexity: We use our mind to study the brain and nervous system, yet as we learn new questions emerge. Biopsychology aims to explain the biological basis of psychological processes. Functions necessary for survival require more than a single brain region or pathway, but rather elaborate, mosaic-like networks. Redundancy in this system allows for complexity of function.

Complexity of the brain mirrors the pattern of its development, from back to front and inside out. Consider the hypothalamus, a region in the brain crucial for eating plus many other bodily functions. Though it is quite small, sophisticated research techniques reveal a collection of even smaller areas within it, each with complex functions—some regulating hunger, satiety, and energy balance.

Adaptability: Our experiences can change our brain—we survive by learning about the world and adapting to the challenges and opportunities we face. The brain’s gift for change is called neuroplasticity, and the discovery of the brain’s ability to adapt and change is a significant influence in the field of neuroscience.

The potential for our experiences to alter the function of our brain is a function of neuroplasticity. Exposure to hyperpalatable foods may cause neuroplastic changes in learning and reward (Volkow, Wise, & Baler, 2017), and exercise enhances neuroplasticity and protects against cognitive impairment as the brain changes to accommodate new experiences (e.g., Kim, Choi, & Chung, 2016).

Integration: Each neuron must combine information from multiple sources to control the function of the body. The sensory, motor, cognitive, and emotional processes of the brain are integrated to guide our thoughts, feelings, and behaviors.

Consider the experience of eating food—sensory information includes taste, smell, temperature, and texture, which you perceive while chewing, moving the food around with your tongue, and swallowing. Your sensory, motor, cognitive, and emotional reactions to the food are integrated to create the experience.

called neurons send messages with neurotransmitter molecules. Neurotransmitters cross the space between neurons, called the synapse, to continue the message in the next neuron. Signals in the nervous system are electrochemical; an impulse traveling down the axon is an electrical signal called an action potential. When the action potential arrives at the terminal button of the axon, the electrical signal drives the release of chemicals— neurotransmitter molecules—to communicate with other neurons. There are a variety of neurotransmitters, each with multiple receptor subtypes and diverse functions throughout the brain. The human brain contains approximately 85 billion neurons, and a similar number of glial cells (von Bartheld, Bahney, & Herculano-Houzel, 2016). Glial cells were traditionally considered as support cells, but more recent evidence shows they play an active role in physiological function, including in the networks governing eating (e.g., Yang, Qi, & Yang, 2015). Our brain is an integrated system of pathways, tracts, and networks that collaborate for processes such as taste, smell, disgust, and pleasure.

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The nervous system has two subdivisions: the central nervous system including the brain and spinal cord and the peripheral nervous system containing all the nerves in the body. These systems communicate extensively; for example, the vagus nerve (see Figure 4.3) carries signals between the digestive system and the brain, coordinating functions like swallowing, contracting smooth muscle of the intestines, and sensing nutrients (Berthoud & Neuhuber, 2000). The vagus nerve relays those stomach contractions measured by Cannon and Washburn’s balloons. There is renewed interest in the gut– brain axis, a communication seat between our nervous system and three other systems— the digestive, endocrine, and immune. There is special fascination in the composition of the gut microbiome; communication between the gut and the brain relies on the products of metabolism from the gut microorganisms can signal the nervous system (Bray, 2019). This axis links the peripheral function of the intestines with the psychological, emotional, and cognitive functions of the brain. The function of the nervous system is complemented by the endocrine system. The nervous system and the endocrine system convene at a structure called the hypothalamus, which governs the endocrine system via the pituitary gland. The hypothalamus also manages maintenance activities required for survival, including eating and drinking (Figure 4.4). In the endocrine system, glands release messengers called hormones into the bloodstream. Feedback is a key feature of the endocrine system: hormones circulating in the bloodstream reach the brain, which monitors and modifies ongoing endocrine function. For example, the endocrine system responds to circulating levels of thyroid hormones synthesized and secreted by thyroid glands to affect metabolism. The brain evaluates thyroid hormone levels and provides feedback to regulate this system. Although thyroid hormone levels fluctuate over the course of the day, chronically low levels in hypothyroidism, or high levels in hyperthyroidism, impact health and are treated by medical doctors. Many signals of hunger and satiety discussed in this chapter are in fact hormones.

Motivation Eating is a motivated behavior, like drinking fluids, sleeping, and sharing romantic bonds. Motivated behaviors are goal-directed, essential for survival, and make us feel good. Hunger and satiety are psychological states that define motivation for food; that is, they initiate, guide, and maintain consumption (or not). Redundancy, which refers to multiple— often repetitive—physiological cues, is a key feature of the complexity in the biological explanation of consumption. Organisms with more signals to consume have elevated chances of survival. Physiological needs, like food and water, create drives like hunger and thirst to activate behavior and ensure the need is met. A drive is an internal state that encourages action, like appetitive behaviors to seek food and consummatory behaviors to eat food. Ancel Keys and colleagues (1950) noted that food deprivation causes a motivational hot state in

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their observation that extreme hunger leads to disregarding other fundamental needs like social connection. We are pushed by drives and pulled by incentives in the environment to encourage us to meet our needs with specific behaviors, with some options more pleasant and rewarding than others. Author LC once taught courses at a community college with a culinary program where the incentive of freshly baked goodies from the bakery near her classroom served as an external tug on her approach and consumption. You may be recognizing how drives and incentives work together in this example. LC is more likely to visit the bakery for cookies when her internal drive, hunger—created by a state of food deprivation—also pushes her toward something of sustenance. Should LC smell cookies mid-morning after consuming a robust breakfast an hour earlier, the cookie incentive would be a less powerful lure. Influences beyond survival can motivate our ingestive behavior, as the pastries from the culinary program are likely a less ideal source of energy than the lunch LC packed for the day. The positive-incentive perspective explains why LC is drawn more to the pastries than the carrot sticks she had (optimistically) packed—eating is vital and also fun. Eating stimulates feelings of pleasure by activating the reward system of the brain (Berridge & Robinson, 1998). After all, eating is about more than reducing the physiological drive of hunger; it is about satisfying appetite (Berridge, 2004). The reward, in this case food, stimulates liking, the hedonic impact, and promotes future wanting, the motivational incentive value (Berridge & Robinson, 2003). The positive-incentive perspective is vital to comprehending biopsychology and eating.

Course 2: The Balancing Act—Metabolism and Homeostasis Brainstorm how you feel when you first wake up in the morning. What is going on in your stomach and your brain? Our digestive system is typically empty when first waking in the morning; many hours have passed since dinner the night before. Blood glucose levels are probably low, while muscles, organs, and the brain need energy to function. Blood glucose levels are important physiological signals for metabolism and are monitored by cells in the brain and liver. Here, we take a brief tour of metabolism, the chemical processes occurring in living organisms to maintain life, providing building blocks for cells and the energy for life. Humans eat in short spurts of meals and snacks rather than continuously, so energy must be stored for later use. Fortunately, redundant mechanisms have evolved to accumulate fat in times of abundance to survive periods of famine (for review, see Havel, 2001). Between meals, the short-term energy reservoir is used, made of glycogen (a complex carbohydrate) in our liver and muscles. But you will not see glycogen on a nutrition label or ingredient list. The body makes glycogen from the simple carbohydrate glucose in the presence of insulin, a peptide hormone produced by the pancreas. When

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Figure 4.1  Metabolism. Metabolism and energy reservoirs. Created by Leighann Chaffee using BioRender.

the short-term reservoir is insufficient, the long-term reservoir of adipose (fat) tissue is relied on. This long-term reservoir is used during longer breaks between meals, like the overnight sleep. In response to the decrease in blood glucose, called hypoglycemia, the pancreas secrets glucagon, which converts the glycogen stored in the short-term reservoir back into glucose for energy (Figure 4.1). Though the brain is a needy organ, requiring 20% of all daily energy (see Chapter 3), it can only consume glucose for energy and cannot use fatty acids from the long-term reservoir. Unlike cells in the body that require insulin to use glucose, the cells of the central nervous system have unique glucose transporters so they can absorb glucose even without insulin. The brain has glucose detectors that activate pathways for energy homeostasis to ensure there is adequate glucose for survival. Homeostasis refers to a tendency for our bodies to regulate and maintain physiological stability for functioning in varied environments. Examples include adjustments to not only body temperature and sex drive but also—more importantly for the present conversation—hunger and thirst. Feedback allows for detection of errors to initiate corrections, but the idea of a homeostatic set point around weight or energy is quite controversial. Cannon (1932) himself referred not to set points but rather to the balance of opposing processes like hunger and satiety. By the end of this chapter, you will be equipped to address this debate on the homeostatic set-point assumption of weight regulation. In addition to glucose and fat, the third important class of macronutrient is proteins, which are long chains of amino acids (see Chapter 1). Amino acids provide the building blocks for the body to make proteins and peptides, and amino acids can also be converted into fat

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for storage in the long-term reservoir. Unlike the brain, skeletal muscle and other tissues can use either glucose or fats for energy. The cells of our body require insulin to use glucose for energy, and specialized liver cells detect glucose levels and availability of fat, signaling this information to the brain (for review, see Woods et al., 2000). Energy homeostasis includes the collective processes to regulate energy intake and expenditures over time. To summarize, when first waking in the morning the digestive system is empty, but we can rely on the adipose in our long-term energy reservoir to support our energy needs. Breakfast delivers macronutrients to provide immediate energy for the brain and body from glucose and protein and also triggers satiety. Energy is also stored for later—insulin allows glycogen storage in the short-term energy reservoir, and all macronutrients (the glucose, protein, and fats) from the meal can be stored as adipose in the long-term energy reservoir.

Chew on This: Quenching Thirst—Fluids and Homeostasis The study of homeostasis and metabolism includes drinking behavior, as water is required to sustain life. The volume of fluid within cells, called intracellular fluid, as well as intravascular fluid (blood plasma) is carefully regulated and monitored by receptors. When the receptors detect insufficient volume of blood plasma, volumetric thirst motivates drinking water. Additionally, specialized neurons called osmoreceptors regulate drinking in response to changes in concentration of solutes in the intracellular fluids, to initiate osmometric thirst. These specialized neurons are located in the subfornical organ, conveniently adjacent to and critically connected with the hypothalamus (Hindmarch & Ferguson, 2016). Thirst provides an interesting case in homeostasis, as thirst can trigger drinking before a deficit occurs, for instance, at mealtime in anticipation of salty foods that cause osmometric thirst (Berridge, 2004). In this case, the thirst is not explained by a standard homeostatic model, but rather a result of learned and anticipatory signals dynamically integrated with the foods consumed (Zimmerman et al., 2016) via the hunger and satiety signals discussed in the next section.

Course 3: Time to Eat! Hunger and Satiety Signals Remember the guiding principles of biopsychology—to improve the odds of survival, redundant cues and signals communicate hunger and satiety between the body and the brain. These signals, known as peptides (small chains of amino acids), are called appetite hormones and gut–brain neuropeptides. The distinction between appetite hormones and gut-brain neuropeptides is their source: neuropeptides are synthesized by

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and secreted from neurons, whereas hormones are produced by endocrine cells. Appetite hormones are orexigenic if they increase appetite and feeding and anorexigenic if they decrease appetite and feeding. Ghrelin is one such hunger signal. As a circulating appetite hormone released from the stomach and gastrointestinal system when empty, ghrelin levels rise before each meal and bind to receptors in the hypothalamus to stimulate eating (Kojima et al., 1999; Cummings et al., 2001). As compared to rodents fed ad libitum (with access to food throughout the day), rodents fed in short bursts to mimic meals have a sharper increase in ghrelin before the meal independent of their state of hunger (Drazen et al., 2006). And administration of ghrelin to lab rodents produces dosedependent weight gain from increased food intake and reduced fat utilization (Tschöp et al., 2000). Similarly, an infusion of ghrelin in humans stimulates appetite and intensifies imagination about favorite meals (Schmid et al., 2005). In anticipation of breakfast after an overnight fast, ghrelin levels are likely high and help motivate food seeking. Because ghrelin is a potent stimulator of hunger, it seems logical that a pharmaceutical used to limit ghrelin could combat overeating and/or obesity. In particular, a receptor antagonist—a drug that binds to and blocks a receptor site rather than activating it—seems a potential candidate for treatment. But, alas, as you probably guessed from the lack of effective pharmacological interventions for obesity, such antagonists do not work. Though ghrelin antagonists decrease appetite and body weight in mice (Asakawa et al., 2003), unwanted side effects in cardiovascular and gastrointestinal systems limit therapeutic potential in humans (Horvath et al., 2003). Strains of mice born without ghrelin have normal appetites, normal patterns of development, and normal sizes (Sun, Ahmed, & Smith, 2003). The tendency for these mice to eat and drink and maintain body weight, despite their lack of ghrelin, is evidence—once again—of the multiple biological mechanisms of consumption in our redundant and complex system. Now let us turn to the topic of satiation and consider how we recognize our consumption limits. Think back to the early research of Cannon and Washburn—was a full stomach sufficient to stop eating? Hunger signals to start a meal are essential for survival, but regulation is also required to stop eating. Satiety signals either function in the short term, to stop a single meal, or in the long term to maintain energy stores (adipose). And some meals are more satisfying than others—a piece of pizza may fill you up more than a pile of carrots. In addition to psychological factors like expectation, physiological factors in the form of gut–brain neuropeptides account for feelings of fullness: ●

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When food is processed in the stomach, it passes through the duodenum at the beginning of the small intestine. Here, the peptide cholecystokinin (CCK) is secreted in response to the presence of fats (Moran, Robinson, & McHugh, 1985). CCK then communicates satiety to the brain via the vagus nerve (Figure 4.3). The small intestine releases peptide YY (PYY) proportional to the calories consumed (Pedersen-Bjergaard et al., 1996). PYY is not responsive to water consumption and

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is correlated with self-reported suppression of hunger and augmentation of satiety (Stoeckel et al., 2008). The gut–brain neuropeptides described thus far regulate appetite in a short-term fashion, during a single day. What happens when a person overeats or undereats during the course of several weeks or months? Is there feedback to ensure the overage or deficit is detected? Animals in the wild have relatively consistent body weight and fat stores despite irregular food supply. In 1950, researchers at the Jackson Laboratory, an independent biomedical research institute, noticed a strange mouse in their population. This mouse was three times the expected body weight, had five times the body fat, and had an insatiable appetite (Ingalls, Dickie, & Shell, 1950). What caused this unique phenotype, called the ob mouse pictured on the left in Figure 4.2, is a recessive mutation of the ob gene on chromosome 6. This mutation was hypothesized to encode a circulating feedback signal to regulate body weight, released in proportion to body fat (Zhang et al., 1994). This feedback signal regulates body weight in normal rodents and was identified as the OB protein named leptin from the Greek word leptós for thin (Halaas et al., 1995). The anorectic effects of leptin are dose-dependent and due to reduction in fat (not lean) body mass (Friedman & Halaas, 1998). Leptin is produced in proportion to adipose (fat) stores in the body, decreasing food intake and body weight through feedback to the hypothalamus (Baskin, Hahn, & Schwartz, 1999).

Figure 4.2  OB mouse. The ob knockout mouse model for obesity. Remi BENALI/Getty Images.

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Did the discovery of leptin lead to a cure for obesity? Again, unfortunately, no, as is quite obvious from the unabated obesity rates around the globe (see Chapter 10). Jeffrey Halaas and colleagues (1997) found the infusion of leptin into the brain had stronger anorexigenic effects than its infusion into the peripheral blood stream, and obese strains of mice are resistant to the effects of peripherally administered leptin. This leptin resistance holds true in both genetically-based obesity and in diet-induced obesity. In these cases, leptin levels are quite high in the peripheral blood stream, but it is unable to exert its effects in the central nervous system. Similar to ghrelin, the functions of leptin are more nuanced than originally understood. The ob mouse not only eats more but is also less active and has decreased immune and reproductive function (Friedman & Halaas, 1998). The broader role of leptin begins in infancy, when leptin signals maturation of hypothalamic feeding circuits (Bouret et al., 2012). Leptin receptors are located throughout the brain, with function in reproduction, immunity (Friedman & Halaas, 1998), and the reward system (Figlewicz, Naleid, & Sipols, 2003) in addition to guarding against weight gain. Diabetes. When adipose tissue changes during weight gain, leptin levels in the periphery increase, and neuroendocrine activity is altered such as insulin resistance (Burger & Berner, 2014). Insulin, serving as a satiety signal, is secreted by the pancreas to regulate blood glucose levels. Neurons in the hypothalamus and reward network are responsive to insulin and leptin levels (Abizaid, Gao, & Horvath, 2006). Insulin dysregulation is the mechanism of diabetes—type 1 diabetes is characterized by a childhood-onset deficiency of insulin, but only 5–10% of all cases of diabetes are type 1 (CDC.gov, 2020). The disruption of insulin sensitivity is the key feature of the far more prevalent type 2 diabetes, as both peripheral tissues and the neurons of the brain become resistant to the effects of insulin even when exposed to elevated insulin levels (Schwartz & Porte, 2005). The roles of these individual signals are pieces of a big and challenging puzzle and it is only partially complete at this point in the chapter. The hypothalamus not only integrates the signals but also communicates with the many brain regions involved in eating. To further explore the role of the brain, think ahead to lunch.

Course 4: The Brain—Head Chef and Chief Executive Officer How does the brain balance the need for nourishment with daily responsibilities, motivating us to eat lunch against competing demands for time and attention? The brain is the star of energy regulation, integrating sensory input from the body, while balancing sophisticated cognitive and emotional processes and environmental cues. To appreciate the principles of integration and complexity, first consider the pattern of brain development: from back to front and from the inside to the outside. This pattern is echoed in complexity of function—at the back of the head, the brainstem matures early and controls automatic

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Figure 4.3  Brain structures. Brain structures and anatomy for regulating eating. Created by Leighann Chaffee using BioRender.

functions for survival like respiration and coordination. The brainstem is considered an “older” structure, present in animals like salamanders that have lived on earth far longer than humans. As ingestive behavior is phylogenetically old, the brainstem mediates the core functions of consuming food like swallowing. In the brainstem, the nucleus of the solitary tract (NTS for the Latin nucleus tractus solitarius) receives taste information from the tongue plus inputs from the vagus nerve, then projects to higher brain regions like the hypothalamus (Figure 4.3). The hypothalamus, which governs the endocrine system via the pituitary gland and manages maintenance activities required for survival, also communicates with the limbic system, a network of subcortical structures essential for the regulation of motivated behaviors, memory, and emotion. In physiology, studying the abnormal helps to understand the normal. Our knowledge of the hypothalamic functions comes from early case studies of patients with tumors of the hypothalamus (Brobeck, Tepperman, & Long, 1943), plus experimental manipulation of these regions in animal subjects (Hoebel & Teitelbaum, 1962) to demonstrate regional hypothalamic functions important for feeding (Table 4.2 and Figure 4.4). Subsequent research found stimulation or lesion of other brain regions also impacts consumption (e.g., the amygdala; Anand & Brobeck, 1951), thus demonstrating the basic model of the LH as a hunger center and the VMH as a satiety center to be insufficient.

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Table 4.2  Hypothalamus functions for regulation of feeding Stimulation

Lesion

Lateral Hypothalamus (LH)

Increase feeding

Decrease feeding

Ventromedial Hypothalamus (VMH)

Decrease feeding

Increase feeding

Figure 4.4  Hypothalamus. Communication between hypothalamus and brain networks. Created by Leighann Chaffee using BioRender.

The hypothalamus is a small area of the brain forming a collection of communicating nuclei performing many functions. The nearby arcuate nucleus of the hypothalamus is responsible for coordinating the functions of the LH and VMH (for review, see Abizaid, Gao, & Horvath, 2006). The arcuate nucleus (Figure 4.4) is adjacent to the capillaries at the base of the hypothalamus for strategic access to the signals circulating in the bloodstream. The arcuate nucleus is innervated by and contains receptors for major neurotransmitters and metabolic hormone signals, allowing it to respond to fluctuations in nutrients. Neurons in the arcuate nucleus express additional peptides important for regulating intake (Table 4.3).

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Table 4.3  Neuropeptide signals, functions, and actions Neurons

Signals released

Function

Response to leptin in the arcuate nucleus

NPY/AgRP (orexigenic)

Neuropeptide Y and Agouti-related peptide

Increase eating, weight, and fat accumulation. Integrate effects of leptin, insulin, and ghrelin

Stimulated by leptin levels when energy reserves are low, increases the motivational drive for food and energy storage

POMC/CART

Pro-Opiomelanocortin, Satiety, appetite α-Melanocyte Stimulating suppression, and Hormone, Cocaine- and reduced feeding Amphetamine-Related Transcript

(anorexigenic)

Responsive to leptin to exert their anorectic effects

Source: Morton & Schwartz (2001), Abizaid (2006), Baskin, Hahn, & Schwartz (1999).

The redundancy and complexity of the network of brain areas regulating appetite should be apparent at this point and is about to become more so. This specialized network balances the orexigenic effects of NPY and anorexigenic effects of POMC through projections from the arcuate nucleus to other hypothalamic regions essential for regulating intake, such as the LH and VMH, the periventricular hypothalamus (PVH), and other brain regions. The idea of brain “centers” was useful at first, but decades of research demonstrate a more intricate pattern of energy homeostasis. Indeed, a network of specialized metabolic sensing neurons works together to integrate numerous signals of energy regulation (Levin, 2006). Derivatives of POMC, called melanocortins, integrate neural pathways governing energy balance with metabolic signals of energy state to govern neuroendocrine body weight regulation (Gao & Horvath, 2007). Melanocortin receptors (MC3R and MC4R) are expressed in the hypothalamus and limbic system, and melanocortin pathways decrease food intake and energy expenditure plus modulate food reward (Pandit et al., 2016). Subsequent control of eating is also managed by lateral hypothalamic orexin (aka hypocretin) neurons by which orexin promotes both arousal and feeding (Broberger et al., 1998). Similar to melanocortins, orexin projects to higher brain regions for emotion and motivation (Peyron et al., 1998), and orexin neurotransmission maintains the wake cycle. Disruption of orexin neurotransmission is one cause of narcolepsy when associated with increased body mass (Messina et al., 2014). Our body certainly learns from the signals associated with energy balance to adjust behavior: we respond to interoceptive cues to initiate eating when hungry, and food deprivation clearly increases food-seeking behavior in animals. Likewise, we respond to positive energy balance or satiety signals to stop

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eating when full. This integration of internal signals and experience to anticipate future outcomes demonstrates the role of learning in the control of food intake (Benoit, Davis, & Davidson, 2010). Does this system enable anticipation of energy needs during a long day, to motivate food-seeking behavior? Remember, the control of energy homeostasis is redundant and complex, requiring a distributed network of neurons in the brain and periphery to govern eating behavior. The hypothalamus cooperates within the limbic system and cortex to guide complex ingestive behaviors. The cortex is the last area of the brain to fully develop, not reaching maturity until adulthood. The cortex is the ultimate area for information processing and is more complex in primates than other mammals (see Chapter 3). Interoceptive cues are detected not only by the hypothalamus but also by the hippocampus, a key structure for memory allowing associations between stimuli and consolidation of signals for energy balance (Benoit, Davis, & Davidson, 2010). Rats with lesion of the hippocampus eat more, direct more behavior toward signals of food, and increase conditioned appetitive behavior (Davidson et al., 2009). Adjacent to the hippocampus is the amygdala, an important structure in processing the significance of stimuli and events. Evidence from neuroimaging studies shows a more robust response of the amygdala to food cues when we are hungry than when we are full (Malik, McGlone, & Dagher, 2011; Chen, Papies, & Barsalou, 2016). A significant body of research implicates the amygdala as an essential structure for learned food cues, particularly cue-potentiated feeding, a paradigm in which animals overeat in certain situations, similar to a human overdoing it at a restaurant or holiday meal (for review, see Johnson, 2013). Moving forward through the pattern of brain development, next consider the cingulate cortex, a band of cortical fibers on the medial surface of the hemispheres (Figure 4.2). The cingulate cortex is an important liaison between emotional, motivational, and cognitive functions. The anterior cingulate cortex (ACC) is especially relevant to our studies as it helps link our motivation with behavioral outcomes and is adjacent to areas of the prefrontal cortex (PFC) that project to the limbic system. The frontal cortex serves the more complex role to initiate behavior and regulate decision making around food. The ACC allocates attention, detects errors to evaluate performance (Carter, Botvinick, & Cohen, 1999), and synthesizes experiences to guide decision making (Rushworth & Behrens, 2008). The ACC also codes hedonic response to taste in conjunction with the anterior insula and orbitofrontal cortex (OFC; Rolls, 2008), lights up with oral delivery of fat and sucrose (de Araujo & Rolls, 2004), and responds robustly to the taste of a milkshake (Gearhardt et al., 2011). Dysfunction in this pathway is commonly associated with patterns of overuse, including substance addiction or overeating (Volkow, Wise, & Baler, 2017). The ACC and PFC collaborate to balance moderation versus impulsivity. As the wise Robert Sapolsky (2017) would say, the “frontal cortex makes you do the harder thing when it’s the right thing to do.” On the way to work, one might anticipate a future need for fuel even if not yet hungry or experiencing an energy deficit. The PFC is essential for planning ahead and is responsible

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for complex cognitive and executive functions like decision-making and problem-solving. The PFC is located at the very front of the brain and is thus the last area of the brain to reach maturity. There are several distinct regions of the PFC, and our focus is on the two circuits crucial for the study of eating: the OFC and the ventral medial prefrontal cortex (mPFC), both characterized by significant development during primate evolution (Öngür & Price, 2000). A great deal of evidence supports the collaboration of frontal brain regions for food-related decisions. How do these brain regions contribute to our choice between a healthy or tasty lunch? Humans commonly evaluate different stimuli to compare options and make decisions, to anticipate the experience of selecting, say, salad versus fast food. The OFC receives input from all five sensory systems plus visceral afferents, serves as the secondary olfactory area, and communicates with the limbic and reward systems (Rolls, 2000). Thus, OFC activation correlates with subjective pleasantness ratings of food stimuli and decreases with satiety (Kringelbach et al., 2003), represents the affective value of reinforcers (Kringelbach, 2005), and is more active when hungry (Siep et al., 2009). Think of the OFC as a neuroeconomist for food reward. Nearby, the mPFC signals bodily (visceromotor) responses via the hypothalamus and striatum (Öngür & Price, 2000). Fortunately, behavior is influenced by more than reward value—the nearby dorsolateral PFC modulates these processes to consider aversive outcomes and factors beyond pleasure, like health (Plassman, O’Doherty, & Rangel, 2010; Hare, Camerer, & Rangel, 2009). Together, the PFC regions represent an interconnected network essential for consumption, integrating cognitive processes, experience, and sensory cues to weigh risks and benefits of food choices. The hypothalamus coordinates eating within the brain. It balances orexigenic and anorexigenic signals from the body with signals from the amygdala and hippocampus. It further integrates the role of the anterior cingulate to link motivation and behavioral outcomes, participating in more sophisticated collaboration with the frontal cortex for food-related decisions.

Morsel: Blood Glucose and Willpower Have you ever noticed yourself snap at someone when hungry, or fail to pay attention in class when you have not had enough to eat? We all have felt the effects of low blood glucose on our energy and willpower, or even noticed bouts of hanger or negative emotions when hungry. Blood glucose is the main energy currency of the body and serves as one signal of the many variables that motivate eating. In psychology, willpower is thought of as self-control, the self-regulation required to fulfill individual long-term goals and follow shared rules. Proper selfcontrol can be seen in a range of personal health and social behaviors, such as using moderation when eating dessert, waiting in line to check out groceries, and keeping a study and assignment calendar for academic achievement (Logue,

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1988; Gaillot & Baumeister, 2007; Duckworth, 2011). How do we explain lapses in self-control, like procrastinating instead of studying, impulsively spending money, or snapping at a loved one when hungry? Consider the energy model for self-control, in which energy resources are required for cognitive function and executive processes like exerting self-control (Baumeister, Vohs, & Tice, 2007). In this model, self-control is thought to be a finite resource—similar to a tired muscle, evidence from laboratory settings and the real world shows that after exerting self-control on one task, energy is “depleted,” and performance worsens on a subsequent self-control task. Further support links metabolic cues with decision making, as low blood glucose levels predict preferences for immediate versus future rewards. This delay discounting is the common tendency to choose immediate but smaller rewards over larger prizes in the future. After consuming a sugary drink, participants’ blood glucose levels increased and were inversely correlated with delayed discounting—these participants declined a small immediate reward and opted instead for a larger delayed reward (Wang and Dvorak, 2010). In other words, they demonstrated self-control. When blood glucose levels are low, an increased desire for resources is experienced, and people are more likely to act greedy and impulsive, demonstrating a failure in selfcontrol (Orquin & Kurzban, 2016). At one time, the general conclusion was that low blood glucose levels decrease the ability to make deliberate and wise decisions. But wait—we are capable of working long days, even skipping meals when too busy, and make it through without impulsivity, bad behavior, or poor decisions. The relationship between blood glucose and behavior is actually quite disputed, and there is a body of evidence contradicting the evidence outlined so far. What explains the opposing findings? First, the relationship between brain glucose utilization, peripheral blood glucose levels, and self-regulatory capacity is actually quite complex, and it is too simplistic to assume a direct association between ingesting carbohydrates and the availability of glucose to reach specific brain regions for task performance (Gibson, 2007). Thus, some of the empirical findings draw invalid conclusions on the basis of blunt measurements of glucose levels (Kurzban, 2010). It is especially notable that changes in peripheral glucose levels, typically measured in these studies, are unlikely to reflect real-time glucose usage in relevant brain areas (Gibson). Attempts at replication have failed to show the depletion of self-control (Xu et al., 2014) and a meta-analysis shows an unreliable relationship between glucose levels and self-control, potentially due to publication bias (Vadillo et al., 2016). So where does this leave us on the issue of hanger? An alternate to the energy model is a motivational model—consumption of sugary substances activates the reward system (Kringelbach, 2004) and thus increases motivation to persevere. Molden et al. (2012) failed to find any change in blood glucose levels with mental effort or self-control tasks. However, these researchers found that merely tasting a sugary solution by rinsing one’s mouth

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(not ingesting) bolstered self-control even though it does not increase the amount of glucose available. This demonstrates a placebo effect, where completion of a challenging task requiring attention and regulation primes the belief that sugar augments self-control stores. In fact, beliefs about willpower, and sensitivity to the idea that self-control can be depleted, influence self-regulatory capacity (Job et al., 2013). Glucose is crucial to human functioning but take comfort to know self-regulatory capacity is not so fragile to depend on immediate energy availability. Perhaps most importantly, we should feel empowered to know our beliefs about self-control can influence success in situations that demand willpower.

Mood and affect influence eating—in human neuroimaging studies, mood influences regional brain activity in the PFC when viewing food cues. Negative affect was associated with greater activation of the medial OFC and ACC to high-calorie foods, while positive affect increased lateral OFC activation to high-calorie food cues (Killgore & YurgulunTodd, 2006). When synthesizing information about eating and mood, consider more than appetite signals and brain regions; also examine the role of classical neurotransmitters and their communication between the hypothalamus, limbic system, and cortical networks to regulate eating.

It’s All Gravy: Neurotransmitter Signaling The relationship between food and mood is well-studied and addressed at several points in this text; here, we focus on the role of serotonin and dopamine. Serotonin, chemical name 5-hydroxytryptamine (5-HT), is a classic neurotransmitter, synthesized from the dietary precursor tryptophan, yet early research on mood and food focused on carbohydrate craving in response to negative mood. The link between eating and mood is well understood, as negative emotional states like depression and anxiety are known to impact appetite, either increasing or decreasing eating. While it is sometimes tempting to distill distinct functions to individual neurotransmitters, appreciate the principles of complexity and integration within nervous system as the human experience depends on interaction across brain networks. The serotonin network in the brain originates in the raphe nuclei of the brainstem and moves throughout the brain, connecting many brain areas and signals related to mood, arousal, and appetite. But the majority of serotonin in the body is located in the gut, specifically in the enterochromaffin cells of the gastrointestinal tract, and both peripheral and brain serotonin signals are important components of satiety (Voigt & Fink, 2015). There is a well-documented inverse relationship between level of brain serotonin and food intake, supported by research using pharmacological manipulation and

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genetic models (for review, see Lam et al., 2010). More specifically, serotonin decreases eating by decreasing meal size and duration through negative feedback in response to macronutrient consumption (Leibowitz & Alexander, 1998). As expected, mice lacking functional serotonin receptors have deficits in satiety and consume larger meals. The gut–brain neuropeptides regulating hunger and satiety are reciprocally regulated by neurotransmitters. In the hypothalamus, serotonin receptors are expressed in neurons of the arcuate nucleus, and the lateral hypothalamus sends neural projections to the raphe nuclei. Serotonin counteracts a variety of hunger signals (NPY/AgRP and orexin) and influences satiety signals (melanocortins, CCK, and potentially leptin) to curb intake (Lam et al., 2010; Voigt & Fink, 2015). The role of serotonin is recognized in many forms of disordered eating, in overeating and obesity, and in eating disorders and dietary restraint. The redundant and complex nature of the physiological regulation of eating indicates why a treatment that manipulates a single neuropeptide or neurotransmitter is unlikely to be effective. Serotonin and orexin are key signals for arousal and wakefulness, and circadian dysregulation is a notable risk for metabolic disease (Versteeg et al., 2015) and also mood disorders (Walker et al., 2020). Discussion of obesity is reserved for Chapter 10, but, keep in mind, the modulatory effects of serotonin on appetite demonstrate its crucial role in the motivational aspects of eating (also see Chapter 7), thus implicating interaction with the neurotransmitter dopamine. The brain networks for ingestive behavior have evolved to motivate eating and reinforce food seeking to ensure survival. The influence of food on mood can be explained by the hedonic qualities of food that elicit feelings of pleasure. This requires neurotransmitter signaling within and between brain networks for eating, with serotonin regulating emotional and behavioral responses to the dopamine motive system that responds to enticing food cues in the environment. The neurotransmitters acetylcholine, glutamate, and GABA provide additional signaling within this system, forming bridges between the structures and signals described. Many types of consumption, from alcohol and drugs to sex and palatable foods, activate the reward system. The warm fuzzy feelings of pleasure are better known as the reward value, and—for our purposes—this is operationalized as how hard we will work for food. Brainstorm some foods expected to have higher reward values and those with less rewarding properties. Why does the food reward value matter? Survival is dependent on this willingness to work for food, whether we are hunter-gatherers trekking across the landscape to forage for the next meal or showing up at work to earn a paycheck for groceries. The reward network projects widely in the brain to form several pathways; the current focus is on the projections from the ventral tegmental area (VTA) of the midbrain to the nucleus accumbens (NAcc) for appetitive motivation, essential for the positive-incentive perspective. The powerful reinforcement of reward accompanying stimulation of certain brain areas was first described by Olds and Milner (1954) who examined the septal area

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and later the NAcc and lateral hypothalamus. Rats press a lever diligently to receive stimulation of the pleasure centers such as the NAcc. The NAcc, located in the forebrain (Figure 4.2), is of special interest due to its coordination of inputs from the senses and the dopamine, opioid, and serotonin systems (Berthoud, 2002) with feeding-related information from the NTS, gustatory cortex, and hypothalamus (Kelley, 2004) in order to code the incentive salience of rewarding stimuli like food (Berridge, 2004). Dopamine release is linked to eating and food reward in human participants (Small et al., 2003), and brain reward circuits are responsive to calorie-rich stimuli even in the absence of taste signaling (de Araujo et al., 2008). The hypothalamus (LH and ARC) projects to the VTA of the dopamine network, while the dopamine neurons of the VTA are inhibited by peripheral satiety signals like leptin and insulin, and stimulated by hunger signals like ghrelin (Volkow Wise, & Baler, 2017). This system is especially sensitive to the novelty of food cues (Bassareo & Di Chiara, 1997), and dopaminergic activity in the mPFC can drive food intake in sated animals (Land et al., 2014). In the brain, plasticity in the form of neuroadaptations occurs in this network in drug addiction, and to a lesser extent in overeating and obesity. To summarize, the neurotransmitters serotonin and dopamine interact to influence meal size and frequency (Meguid et al., 2000), integrating signals of hunger and satiety through an elaborate network of brain structures while making decisions, for instance, of what and how much to eat for lunch. Recall the earlier discussion about hanger, eating, and self-control. One key to solving the riddle of hanger is serotonin. We have long known that serotonin pathways are crucial for effectively delaying reinforcement (Wogar, Bradshaw, & Szabadi, 1993), the key dependent measure for self-control described earlier in this chapter. In animal models, depleting serotonin enhances impulsive action (Winstanley et al., 2004), and tryptophan depletion impairs the ability to make decisions based on the value of rewards (Seymour et al., 2012). In humans, serotonin is implicated in value-based decision making and its activity in the PFC and OFC is crucial for inhibitory control (Cools, Roberts & Robbins, 2008; Hare, Camerer, & Rangel, 2009). Pharmacological manipulation of serotonin levels in human participants enhances attention to health over taste in a food choice task (Vlaev et al., 2017). These findings do not explicitly address the question of hanger, rather they provide a mechanism to link diet, brain signaling, and self-control via serotonin. Beliefs about willpower and depletion can influence the capacity for self-regulation, demonstrating the principle of adaptability of the nervous system. The brain constructs emotions and interpretation of events based on past experiences and knowledge (Barrett, 2017). When hungry, the regions responsible for both emotion and eating light up, such as the ACC, insula, and amygdala (Chen, Papies, & Barsalou, 2016). We may misattribute hunger signals as negative emotions, and this is dependent on context and focus of attention. MacCormack and Lindquist (2019) found hungry participants experienced negative emotions in a negative (but not neutral or positive) context, but only when participants were not directly focused on their emotion. These researchers found no depletion in self-regulation and rather emphasized that both the context and

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bodily processes like hunger can serve as “ingredients” for emotions. Remember, preconceived ideas about hunger and willpower influence experience. This constructivist explanation is supported by contemporary neuroscientific evidence for emotion and helps to further understand why we sometimes mistake our emotional experiences for physiological needs. As we compose this chapter, the Muslim holy month of Ramadan has just begun. The vast majority of the 1.6 billion Muslims living around the globe will fast from dawn to sunset during this month of faithful intention. In addition to fasting, this is a time of spirituality, extra prayer, and increased generosity to others, leading up to the three-day Eid al-Fitr holiday and celebration. Each morning, there is a meal before sunrise, then no eating, drinking, chewing gum, or smoking until after sunset when fast is broken— typically with dates and water (though this varies) and a large dinner called iftar (CrawfordOppenheimer, 2011). The study of religious devotion through fasting provides insight to several important concepts. First, consider self-regulation: both males and females report a good mood throughout the day during the fast, though one study found females report more consistent and more positive mood than males (Finch et al., 1998). Prosocial behavior is augmented during Ramadan. Research has revealed greater generosity during the fast than after dinner (Haruvy, Ionnou, & Golshirazi, 2018) and less volatile investing (Bialkowski, Etebari, & Wisniewski, 2012), perhaps reflecting greater optimism and solidarity. This evidence indicates that low blood glucose does not necessitate a loss of self-regulation.

Integration The integration of signals from the central and peripheral nervous system, endocrine system, and gastrointestinal system is a key feature of the biopsychology of eating. To review, the nervous system and endocrine system cooperate for the regulation of eating. In fact, the term neuroendocrine is sometimes used to describe systems from this chapter, as the hypothalamus governs the endocrine system via the pituitary, and many hunger and satiety signals are in fact peptide hormones that circulate in the blood and signal to the brain or target tissues. Case in point: Leptin is a hormone derived from adipose that circulates signals of energy balance to the brain at the hypothalamus (Bates & Myers, 2003) and is commonly referred to as an appetite hormone. Here consider three additional illustrations of integration for the biopsychology of eating: Gonadal Hormones. Gonadal hormones, those secreted by gonads, include the estrogens and androgens. These hormones have reciprocal influences on eating and body weight, though their effects are more observable in female rats given fluctuations in meal size and frequency throughout the estrous (female reproductive) cycle, while food intake in male rats is quite stable (Meguid et al., 2000). Gonadal hormones provide feedback to the hypothalamus (ventromedial area) and interact with dopamine and serotonin signaling (Meguid et al.) to influence meal size and frequency. Sufficient estrogen signaling may be

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partially protective against the health consequences of obesity as estrogen specifically impacts energy homeostasis and adipose distribution (for review, see Brown & Clegg, 2010). In a study of mice with obesity induced by a high-fat diet, female mice gained less weight than male mice and the females showed reduced deficits in learning (Hwang et al., 2010). Estrogen further influences energy homeostasis because the benefits of exercise are dependent on estrogen signaling (Cotman & Berchtold, 2002). Given that gonadal hormone levels fluctuate in development and aging, these concepts inform later discussions of obesity and health (Chapter 10). Microbiome. Signals such as insulin, ghrelin, CCK, and others allow communication between the gut and the brain. This bidirectional communication, sometimes called the “gut-brain axis,” includes neural messages between the central and enteric nervous system, immune signals, endocrine hormones, plus interacting microbial factors (Holzer & Farzi, 2015). Microbial factors are a product of microbial metabolism colonizing the gut to form part of the body’s microbiome. Diet and lifestyle influence our microbiome, which in turn influences physiology and behavior (Liang et al., 2018). The microbiome can rapidly accommodate diet changes, like transitions between animalbased and plant-based diets (David et al., 2014). This flexibility is advantageous given the diversity of human consumption. The mechanism linking red meat consumption and accelerated atherosclerosis of cardiovascular disease is now at least partially explained by the microbiome. Red meat is particularly rich in L-carnitine, which produces a proatherosclerotic signal, trimethylamine-N-oxide (TMAO) when metabolized by the microbiota (Koeth et al., 2014). Rats consuming a Western diet (high in fat and sugar) have altered microbiome that influences their metabolism and further contributes to their obesity (Turnbaugh et al., 2008). As we know, diet and mood have a bidirectional relationship. In a rodent model, high-fat diet alters behaviors indicative of depression, with decreased socializing, increased fatigue, and changes in eating patterns. This dietinduced depression is accompanied by changes in expression of appetite hormones and disturbance in intestinal microbiota composition (Hassan et al., 2018). Stress and illness impact composition of the microbiome (Cryan & Dinan, 2002), where dysfunction of the gut–brain axis results in stress-induced and stress-exacerbated disorders (Kelly et al., 2015). Pathologies related to gut health are physiological (e.g., irritable bowel syndrome), psychological (e.g., depression, anxiety), and behavioral (e.g., disordered eating). You may have noticed products touting probiotic properties, claiming they can enhance physical and mental health, often associated with fermented foods like yogurt, kefir, and miso in addition to supplements targeting the microbiota. Before running away with appealing claims, consider challenges to diet-based engineering of the microbiome. First, a supplement is unlikely to establish itself in the existing community of the gut, and it is an oversimplification to expect benefits from a single strain (Johnson & Foster, 2018). Rather, the benefits we receive from our microbiota are likely from collaborative functional properties of the community. The bidirectional communication between the brain and the gut is expected to be an area of significant research in the coming decades to enhance

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our understanding of physical and mental health and wellness. Our accumulating knowledge of the microbiome highlights the principles of complexity and integration, as our signals of hunger and satiety also interact with the microbiome. Reward. The dopamine system alone does not explain the power of food rewards. The redundant and complex system for regulating ingestive behavior overlaps with the reward network to ensure we are motivated to eat enough for survival. ●

●

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Merely viewing photos of food activates ghrelin in humans (Schüsser et al., 2012) to augment the hedonic, or pleasure, value of a food. Leptin resistance, a metabolic dysfunction commonly seen in overweight and obese individuals, alters the hedonic processes in the brain to regulate feeding behavior (for a review, Murray et al., 2014). Orexin stimulates reward seeking and mediates context-conditioned responses to meals and chocolate (Choi et al., 2010). Orexin neurons project from the hypothalamus to the ventral tegmental reward area to regulate dopamine response to rewarding stimuli (for review, see Kenny, 2011).

The terms “liking” and “wanting” are used to describe the hedonic impact and incentive salience, respectively, of dissociable components of reward (Berridge, 2004). Within this framework, craving is an aspect of motivational wanting, and hedonic liking encompasses the pleasure of consumption. Based on the evidence reviewed thus far, do you believe the dopamine reward system is more strongly associated with liking or wanting of food rewards? Interestingly, the wanting of a reward is not always correlated with the hedonic liking of the reward. Wanting is the drive to obtain food rewards; this process promotes our associations, approach, and consumption of rewards rather than our cognitive, explicit desires. One might think or say they want to follow a balanced diet and avoid junk foods while buying and eating a large bag of chips in a single afternoon. Thus, wanting does not require (and may even undermine) the sophisticated cognitive capabilities of the cortex, relying more on subcortical networks (Berridge & Kringelbach, 2013). As you may have deduced, the dopamine reward system is essential for the process of wanting and can function independently of food liking (Berridge et al., 2010). Though possible to isolate these elements of reward, liking and wanting are complementary. The neurobiological substrates of pleasure are localized and referred to as “hedonic hotspots” (Berridge, Robinson, & Aldridge, 2009). Reward hotspots include neurotransmitter systems of endogenous opioids (including endorphins), endocannabinoids, and GABA systems. One important opioid hotspot is located in the NAcc, where opioid stimulation enhances liking within the hedonic hotspots (Berridge & Kringelbach, 2013). Injection of an opioid agonist into the NAcc increases liking reactions to sucrose taste (Pecina & Berridge, 2000) and opioid antagonists such as naloxone suppress the hedonic reaction to palatable foods (sugar and fat) in both normal participants and those with binge-eating symptoms (Drewnowski et al., 1995).

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Endocannabinoid infusion has a similar effect in these same brain regions (Berridge et al., 2010) and is described in the dessert. Insight into the distinct processes of liking and wanting informs future discussion of temptation, restriction, and disordered eating. Throughout this chapter, we tracked eating during the course of a day, from first waking up in the morning through anticipation of energy needs to make it through classes and work. We started with an empty stomach in the morning, noted immediate or short-term signals of hunger that motivate eating, and learned the low-blood-glucose explanation for eating is insufficient, as peripheral signals interact with neuropeptides in the brain to signal hunger and satiety. As we fill our stomachs and finish our plate, short-term signals of satiety take over to communicate fullness. The material grew more complex with integration of the evolutionary perspective; focusing on survival of our ancestors depended on times of food shortage. The biological complexity of the neurobiological system for eating is clearly illustrated by the network of brain signals and structures, clued-in to environmental cues for hunger to promote energy intake. Thus, eating is influenced not only by energy needs but also by extra-homeostatic factors like motivation and pleasure. Thus, eating occurs in the absence of hunger, in anticipation of future deficits, when bored or sad, and even when tempted with yummy treats (see Chapter 7). The biopsychological perspective is in sharp contrast to a simple set-point assumption for regulation of body weight. Earlier homeostatic explanations argued that energy balance was regulated around maintaining some internal signal at optimal levels. Glucostatic and lipostatic theories with a thermostat-like criterion dominated research in eating during the 20th century. If ingestive behavior was truly governed by homeostatic motivation, this would require some sort of set-point range for a specific physiological variable or set of variables, plus error detectors to sense deficits and an error corrector to respond (Berridge, 2004). Yet eating is far more complicated, and humans and animals experience fluctuations in their own weight compared to the average adult of their species. In physiology, studying the abnormal gives many clues about normal function. Cases of dysregulated eating, in the form of eating disorders and obesity described in Chapters 10 and 11, call homeostatic feedback into question. To appreciate the complex and redundant system regulating our eating, acknowledge the integration of brain signals and network of parallel processes (Berthoud, 2002). As everything psychological is simultaneously biological, the psychological influences on eating, like memory and reward, are represented in this network governing ingestive behavior. These parallel loops distribute functions to efficiently manage energy balance and integrate complex metabolic, sensory, endocrine, neural, and motivational demands. What does this mean for energy regulation in the course of a single day? Purely homeostatic regulation is not likely because the neurocircuitry that guides eating is convoluted and redundant, and the system is biased toward hunger and eating rather than satiation. Additionally, variability is expected in meal patterns between people

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and also within an individual because eating is not merely consistently habitual but also opportunistic and guided by pleasure. Experience shapes this complex network, and the mechanisms that protected human ancestors from scarcity now predispose overconsumption as physiological safeguards against positive energy balance are vulnerable in the modern environment.

Dessert: Pleasure, Appetite, and Endocannabinoids Remember the comfort food imagined at the beginning of the chapter? Imagine a long day at work, after which you are yearning for a favorite comfort meal. How does the information in this chapter explain the purpose and characteristics of comfort food? First, consider the macronutrients profile of the food. Comfort food preferences vary by person from experience and culture, but it is likely to be a warm and palatable meal rich in carbohydrates and perhaps fats. The positive-incentive value of the comfort food depends on dopamine signaling, as well as endogenous opioid signals and the endocannabinoid system that are triggered by palatable foods (Parsons & Hurd, 2015). Endocannabinoids are substances produced within the body that bind the same receptors in the brain as the psychoactive substance in marijuana. In fact, the study of marijuana led to the discovery of this endogenous cannabinoid system. Many brain areas essential for eating contain cannabinoid receptors, including the amygdala, PFC, lateral hypothalamus, and of course the reward areas of the NAcc (Parsons & Hurd, 2015), and cannabinoid signaling in this circuit influences the hedonic effects of natural rewards, like comfort food. The endocannabinoids collaborate with the endogenous opioids to influence hypothalamic energy metabolism and dopamine reward signaling (Cota et al., 2006). But the impact of endocannabinoids on eating occurs beyond the reward network. The medical application of marijuana is in the treatment of chronic conditions to promote appetite. Administration of the endocannabinoid anandamide to the ventromedial hypothalamus increases eating in rats (Jamshidi & Taylor, 2009), even when they are sated (Williams & Kirkham, 1998). The ob mouse described earlier has increased endocannabinoid levels in the hypothalamus, and their weight gain can be attenuated with a drug that acts as an antagonist on cannabinoid (CB1) receptors (Cota & Woods, 2005). Endocannabinoids promote eating through interactions with NPY, melanocortins, and orexin (for review, see Cota & Woods, 2005). The endocannabinoid system also modulates energy homeostasis in the periphery via actions in the adipose tissues, the liver, and muscles (Silvestri, Ligresti, & Di Marzo, 2011). The role of endocannabinoids highlights the integration of biological and psychological factors in the regulation of eating. Endocannabinoid signaling enhances hedonic ratings and palatability of foods, plus the positive-incentive value of the food (Kirkham, 2009).

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Advances in the scientific understanding of the critical components governing consumption inspire drug development and the endocannabinoid system is another likely target for the treatment of eating disorders and obesity. Regulatory barriers on research involving controlled substances in the United States limit biomedical advances (National Academies of Science, 2017). In order to adequately follow up on therapeutic strategies, it is first necessary to integrate perspectives and evidence from the various specialties in psychology, like sensation, cognition, and learning, to elucidate the complex determinants of eating.

Dining Review Key Elements

Recommended Reviews

Whet your appetite: Comfort food

Now that you have reached the end of the chapter, can you describe the reasons why your comfort meal is so comforting? Consider how your brain responds to the foods and ingredients.

The amuse-bouche: Hunger

Why are stomach contractions insufficient to explain hunger and intake? Describe the biopsychological sources of hunger.

pangs Course 1: Fundamental principles of biopsychology Course 2: Metabolism and homeostasis Course 3: Hunger and satiety signals

Summarize three key approaches to motivational explanations of eating: drives, incentives, and positiveincentive theory. Outline the limitations of set-point assumptions for body weight regulation, identifying the forces on hunger and satiety beyond body weight and simple homeostasis. Create a table to organize the information you have collected on the signals of hunger and satiety. Be sure to indicate key structures, their locations, and their functions.

Course 4: The brain

Identify eating-related processes described in this chapter, and beyond, that require integration of multiple brain systems. Consider, for example, eating in the absence of hunger or changes in eating when under the influence of a substance.

Morsel: Blood glucose and willpower

Imagine you choose to modify (not limit) your diet—for example, to limit sugar or become a vegetarian. Identify the brain areas and signals involved in your change and those that are to blame when giving in to temptation.

Dessert: Pleasure and endocannabinoids

Why are there multiple signals to encode reward value of food and other positive incentives?

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Gochisousama Thanks to the chef! Recommended reading: ●

●

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A review of the classic research on the topic of homeostasis: Cooper, S. J. (2008), “From Claude Bernard to Walter Cannon. Emergence of the concept of homeostasis,” Appetite, 51: 419–27. For a comprehensive biopsychology textbook: Carlson, N. R. & M. A. Birkett (2017), Physiology of Behavior (12th ed.). Boston: Pearson. A comprehensive and engaging guide to behavior: Sapolsky, R. M. (2017), Behave, New York, NY: Penguin Press.

Glossary Anorexigenic:

a signal, hormone, or neuropeptide that decreases appetite and promotes satiety

Appetite hormones:

sequences of amino acids that signal hunger and nutrient levels between the brain and the body; also known as gut–brain neuropeptides

Enteric nervous system:

a division of the peripheral nervous system that is responsible for digestion

Gut–brain neuropeptides:

sequences of amino acids that signal hunger and nutrient levels between the brain and the body; also known as appetite hormones

Homeostasis:

the process of maintaining a stable internal state; energy homeostases are the collective processes that regulate our energy intake and energy expenditures over time

Hypothalamus:

brain region that directs motivated behaviors and governs the endocrine system via the pituitary gland; see Figure 4.3

Insulin:

peptide hormone produced by the pancreas that regulates use of glucose for energy

Metabolism:

chemical processes that occur in living organisms to maintain life; provide building blocks for cells and energy for life

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Microbiome:

sum of all microbiota inhabiting the human body

Motivation:

processes that initiate, guide, and maintain goaldirected behavior

Neurotransmitters:

chemicals that carry messages between neurons at the synapse

Orexigenic:

a signal, hormone, or neuropeptide that increases appetite and promotes hunger

Positive-incentive perspective: theoretical approach to motivation that behavior is directed in part by feelings of pleasure and reward Self-control:

capacity to regulate personal behavior, emotion, and desires, to override impulses and automatic responses

Chapter 5 Savor the Flavor: Gustation and Olfaction Whet Your Appetite: Is Flavor More Than Taste? Name the five senses. Was flavor one you identified? In the psychology of eating, we distinguish between the concepts of flavor and taste, or gustation. What are your initial impressions about this distinction? Try to create operational definitions for flavor and taste, and to update your definitions throughout this chapter as the role of our senses and perception in eating and drinking are explored.

Menu Amuse-Bouche: Why Is Food Bland When You Have a Stuffy Nose? Course 1: Gustation—Chase That Taste The Gustatory Pathway The Primary Tastants Taste Sensitivity: Is Your Tongue High Strung? Course 2: Olfaction—Decode the Odor The Olfactory Pathway: Following the Scent Souvenirs from Smells: Odor-Evoked Memory Individual Similarities and Differences Course 3: Flavor Perception Dessert: Eat First with Your Eyes—Plating and Presentation Dining Review Gochisousama Glossary

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Amuse-Bouche: Why Is Food Bland When You Have a Stuffy Nose? Why is it that a food that tastes so good in some circumstances can be so thoroughly dull and flat in others, such as when congested due to a cold or allergies? Frequently, a stuffy nose (“rhinorrhea”) is to blame. In 2020, as coronavirus pandemic circled the globe, anosmia or the loss of the sense of smell, was first reported anecdotally in some patients without obvious symptoms of the virus. Though olfactory problems are not uncommon during the simple cold, sinus infections, and even diseases associated with aging, patients with COVID-19 are unique in that anosmia presents without rhinorrhea. An early investigation showed anosmia in 85.6% of patients surveyed, commonly accompanied by a diminished sense of taste called ageusia (Lechien et al., 2020). Why does COVID-19 impair smell and taste? And how does it weaken the senses without causing a stuffy nose? The relationship between our physical health and our senses demonstrates the strong biological influence on perceptions of taste and smell. In this chapter, we will address the interconnectedness of the senses for the perception of flavor.

Course 1: Gustation—Chase That Taste Think of someone you know that consumes a relatively limited diet, relying on only a small selection of foods, perhaps the same lunch day in and day out. Now imagine an even narrower diet like those of koalas and pandas that subsist on eucalyptus leaves and leaves and stems of bamboo, respectively. Creatures with a limited diet face a simpler task when finding nourishment. By comparison, omnivores must trust their senses to seek out appropriately nutritious foods while avoiding harmful foods (Galef, 1981 as cited by Rousmans et al., 2000), all while competing with specialist herbivores and carnivores in the environment. When trying to understand an integrated process like sensation or perception, the use of simple and discrete categories facilitates thinking. For instance, we often identify the five senses: vision, audition (hearing), touch, gustation (taste), and olfaction (smell). Sensation and perception are collaborative aspects of human cognition. The purpose of these senses is to detect stimuli from the external world through light, sound, heat, and chemicals received by sensory receptors and sent to the nervous system (Carlson & Birkett, 2017). Once sensory information reaches the brain, the processes of perception take over. Perception allows us to organize and interpret the information from our senses, to recognize meaningful objects and events, as it tells a meaningful story based on the events around us. The five basic senses cooperate, and the distinctions between them can be rather murky. A quick web search yields various claims of a sixth sense, from the role of imaginative play to the properties of the immune system. Most relevant are visceral sensations from the internal environment communicated to the brain by the vagus nerve; this sense of the

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internal state of our body is termed interoception. Of the five primary senses, gustation and olfaction are most involved in eating. These are our chemical senses as they detect chemicals in the air and dissolved in the saliva (Carlson & Birkett, 2017).

The Gustatory Pathway To experience flavor, the brain must interpret the sensory experience received by gustatory receptors. The bumps on our tongue are actually not taste receptors—these are papillae, and along the side of each papilla is a trough where the taste buds are found. Each papilla has multiple taste buds, and each taste bud is a group of 50–100 taste receptor cells (Arvidson & Friberg, 1980; Scott, 2005). This means the tastes of cookies can activate receptors for sweet, salty, and umami in many taste buds across the tongue. Take a look at your tongue in a mirror to note the size difference in papillae, with larger ones toward the back and smaller ones at the front (Figure 5.1).

Figure 5.1  Tongue and papillae. A depiction of the tongue and shape of the papillae. Created by Tony Graham/Getty Images.

As we chew, food is broken down into molecules that enter an opening called a taste pore to interact with taste receptor cells for sweet, salty, sour, bitter, and umami. The sensations

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of taste then signal to the brain via cranial nerves that innervate the face, jaw, and tongue plus the vague nerve (discussed in Figure 4.3 in Chapter 4; Carlson & Birkett, 2017). These cranial nerves project to the brainstem area known as the nucleus of the solitary tract (NTS, referred to in Chapter 4) and then the thalamus, which is responsible for relaying sensory information. This pathway is similar across other senses, too. The thalamus relays incoming sensory information to the primary and then secondary sensory cortex. For taste, the pathway from the thalamus projects to the insula, the primary gustatory cortex, and the secondary gustatory region in the orbitofrontal cortex (OFC), depicted in Figure 5.2.

Figure 5.2  Gustatory pathway. The gustatory pathway. Created by Leighann Chaffee using BioRender.

The name insula points to the protected, or insulated, nature of this brain region due to its position tucked behind the temporal lobe at the intersection with the frontal cortex. The insula is responsible for the rapid interpretation of taste information, differentiating taste qualities like sweet and sour in about 175 milliseconds (Crouzet, Busch, & Ohla, 2015), and the cells in this region may respond to one or multiple basic tastes, acting as both specialists and generalists (Fletcher et al., 2017). The insula is broadly tuned, integrating somatosensory information from the mouth like temperature and viscosity (de Araujo & Simon, 2009) plus olfactory information (Samuelson & Fontanini, 2017). The gustatory cortex demonstrates plasticity as we learn about specific flavors—a topic we will explore more later.

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When gustatory signals travel from the insula to the OFC (Rolls & Grabenhorst, 2008), neurons of the OFC show multisensory responses (temperature and texture) plus converging olfactory information. In humans, the insula and OFC respond to taste stimuli more potently when hungry, thus coding the reward value (Rolls & Grabenhorst; Haase, Cerf-Ducastel, & Murphy, 2009; van Rijn, de Graaf, & Smeets, 2015). In essence, the OFC functions as a neuroeconomist, receiving input from all five senses to make computations about the reward value and pleasantness of potential foods.

The Primary Tastants Simple categories are used to describe complex taste perception. The idea of basic tastes originated in ancient philosophical texts from the Han dynasty of China (Unschuld, 2003). Known as the Su Wen collection, these texts from the 2nd century bce outline a doctrine to organize sensory experiences into collections of five categories, identifying the primary tastes: sweet, salty, sour, bitter, and acrid. This ancient idea of primary tastes provided the foundation for early research on gustation, as Hanig (1901) demonstrated areas of the tongue that are sensitive to sweet, salty, bitter, and sour, confirming basic tastants, but omitting the acrid primary (due to its overlap with bitter). This “tongue map” is not congruent with our contemporary understanding of gustatory receptors, but it further strengthened reference to the primary taste categories. These primaries each serve an adaptive purpose. Sweet. Glucose is the primary energy currency for the body and brain. Preference for sweet is crucial in mammals to encourage lactose consumption in milk for proper energy for growth. Fortunately, sweet preference is present from birth, occurs spontaneously without being learned, and is relatively stable through childhood (Desor, Maller, & Green, 1977). Variability in sweet preference is likely due to genes (Fushan et al., 2009), culture (Moskowitz et al., 1975), and experience (Liem & de Graaf, 2004). Sweet tastes activate type 1 taste receptors (TAS1R2 and TAS1R3; Li et al., 2002) and signal the reward system to reinforce consumption. Salty. The minerals in salt, required micronutrients for the function of cells in the body, are sensed by taste buds through sodium ion channels (Heck, Mierson, & DeSimone, 1984). Unlike other animals, humans consume salt beyond requirements for physiological function, problematic as excess salt intake contributes to hypertension in some people (Mattes, 1997). Both culture and context influence exposure to salt and subsequently preferences (Mattes, 1997), and the mutability of our salt preferences is good news if encouraged to limit salt intake for health reasons. Sour. The tart pucker caused by potent sour foods helps warn against consumption of acidic substances, like unripe or spoiled fruit, or inedible items. Similar to the other taste primaries, sour is detected by a unique receptor, in the form of an ion channel (PKD2L1; Huang et al., 2006). Mild sour taste may be perceived as pleasant, an adaptive

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preference for our hunter-gatherer ancestors since mild acids prevent the formation of harmful bacteria (Lindemann, 2001). Bitter. Similar to sour, bitter warns to avoid potentially harmful stimuli like poison and toxin, yet there is significant variability in perception of bitter by type 2 taste receptors (TAS2Rs; Chandrashekar et al., 2000). Both age and genetics account for this variability (Menella, Pepino, & Reed, 2005), and we will return to bitter sensitivity later in this chapter. Remember these primary tastants are rarely experienced in isolation—for instance, the bitterness of caffeine is easily masked by sugar and salt in our favorite beverages (Drewnowski, 2001). In addition to these four tastants, umami is now recognized as a primary, and fat may be as well, as both serve to signal crucial nutrients in edible food items. One hesitation in the classification of fat as a primary tastant is its overlap with other primaries, such as umami (Running, Craig, & Mattes, 2015). Umami. Named from the Japanese term for delicious, umami signifies the presence of the amino acid L-glutamate in proteins (Lindemann, 2001). Similar to sweet, we are drawn to rich and savory umami tastes that communicate nutritional significance like animal proteins, seafood, mushrooms, milk, tomatoes, soups, and broths. The validity of umami as a taste primary, described by chemist Kikunae Ikeda in 1908, was not widely recognized in Western textbooks and research until the 1990s and further confirmed by identification of glutamate receptors at the taste cells (Lindemann, 2000; Chaudhari, Landin, & Roper, 2000) and processed by taste areas of the cortex (de Araujo et al., 2003). Monosodium L-glutamate (MSG) is used commercially as a flavor enhancer and food preservative, though be wary of inappropriate assumptions about MSG in Asian cuisine. MSG is actually more prevalent in highly processed foods of the US food industry, such as chips and seasoning blends. And despite many anecdotal claims of MSG sensitivity, decades of research fail to support adverse events from glutamate (Jinap & Hajeb, 2010).

Morsel: Umami and the Maillard Reaction In laboratory research on gustation, droplets of specific chemicals are placed on the tongues of participants (or dissolved in water) to measure their experience of primary tastants in isolation. An example is the use of citric acid to gauge responses to sour. In the real world, alternatively, we experience complex fusions of taste primaries transformed through cooking. In Chapter 3, we reviewed the benefits of cooking such as anatomical changes to the body and brain. Now the conversation is extended to how cooked food benefits the tastes of foods, thanks to the synergism of temperature and ingredients in creating flavors. Think of cookies fresh out of the

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oven—the temperature heightens the aroma, changes the texture, and enhances the flavor (just don’t burn your tongue!). Cooking develops flavor through a series of chemical reactions. While cookies bake, the heat causes water in the dough to evaporate, leavening agents like baking soda release carbon dioxide gas to create airy pockets, and caramelizing sugars form the nutty or butterscotch flavors (Warren, n.d.). The same chemical reaction that produces the complex flavors of caramelization in desserts contributes to rich savory flavors in other foods—think of the malty and toasty flavor of bread, the depth of stock, miso paste, and soy sauce. The chemical reaction was named for French chemist Louis Camille Maillard after he described the process by which applying heat breaks down a carbohydrate and amino acid, allowing molecules to rearrange themselves, to form a greater variety of flavors (Allen, 2012). This tasty chemical rearrangement also occurs via fermentation when microbial metabolism changes the chemical composition of the food, creating more flavor. For instance, miso is a paste of soybeans inoculated with koji (Aspergillus oryzae) for an earthy and funky umami kick. Though Maillard explained how cooking creates flavor based on chemistry, unlocking the flavor in proteins to boost the deliciousness of umami was known from a variety of origins dating back to early humans. Escoffier’s early 20th-century cookbooks emphasized the pleasure revealed by browned meats, roasting coffee to develop flavor likely originated in Yemen before 1500, the Japanese broth dashi that exemplifies umami dates from the 8th century, and our hunter-gatherer ancestors cooked meat over fire (Lehrer, 2007; Topik, 2000). We are hardwired to enjoy the taste of umami unlocked by the Maillard reaction.

Taste Sensitivity: Is Your Tongue High Strung? We clearly do not all love broccoli, red wine, or even chocolate, illustrating the remarkable diversity in human preferences. As Linda Bartoshuk (1980) appropriately described, humans do not “all inhabit the same taste world.” You may prefer creamy milk chocolate, or intense dark chocolate, or no chocolate at all. Variability is observed in our liking of vegetables, rich foods, coffee, and even chocolate, but what explains these differences? Wide variability in the density of papillae distribution on the human tongue means differing amounts of taste pores, and thus gustatory receptors, correlated with enhanced taste intensity for sweet, salty, and bitter (Miller & Reedy, 1990). The study of taste sensitivity began in the 1930s, when a scientist named Arthur Fox was synthesizing a compound called phenylthiocarbamide (PTC) and some of it flew into the air. Another researcher in the lab described a strongly bitter taste, but Fox could taste nothing (Bartoshuk, Duffy, & Miller, 1994). Inspired by this discovery, Fox and others launched

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research to study this sensitivity to PTC in families, and their work caught the attention of geneticists studying Mendelian inheritance patterns. We now know that taste sensitivities are not determined by a single gene—rather, multifactorial interactions of genes and experience explain taste sensitivity status. In the 1970s, Linda Bartoshuk began a series of studies on taste sensitivity spanning her prolific career. Initially, Bartoshuk and colleagues used the adjectives “tasters” and “nontasters” to describe sensitivity to PTC and the related compound 6-n-propylthiouracil (PROP). Later, the subcategory of “supertasters” was added (Bartoshuk, 2000). In contrast with medium tasters who perceive the substance PROP as mildly bitter, supertasters find the substance to be so bitter it is nearly painful. Although the distribution varies slightly by gender and culture, about 25% of the population are nontasters, 25% are supertasters, and about half are somewhere in the middle, classified as tasters (Bartoshuk, Duffy, & Miller, 1994). The taste receptor 2 family (TAS2R), which includes twenty-five bitter taste genes plus other genes like gustin (CA6), contributes to the genetic basis of taste preferences (Hayes, Feeney, & Allen, 2013). But genes alone are not sufficient to explain the tremendous functional variety in taste. Taste sensitivity is determined by polygenetic influences plus experience, as factors like cigarette smoking and exposure to certain tastes shape perception. Understanding taste sensitivity provides insights into eating habits; supertasters are more likely to avoid bitter foods like leafy green vegetables, yet they also avoid intense tastes like alcohol, tobacco, and highly palatable foods rich in sugar and fat (for review, see Bartoshuk, 2000). Given that increased consumption of vegetables is a common dietary and health promotion strategy, sensitivity to bitter is potentially concerning. PROP/ PTC tasters are more likely to conceal bitter tastes with additional salt or seasonings (Drewnowski, Henderson, & Barratt-Fornell, 2001) and nontasters, particularly females, tend to prefer rich and highly palatable foods (Duffy & Bartoshuk, 2000). In adulthood, sensitivity to bitter and salty tastes declines with advancing age (Drewnowski, 2001). Though children are more sensitive to bitter than adults, PROP sensitivity does predict consumption of cruciferous vegetables and fats (Keller et al., 2002) because experiences also drive taste preferences.

Chew on This: Some Like It Hot Oftentimes, taste sensitivity is correlated with sensitivity to spicy food. We have not yet addressed perception of spice, aromatic plant material—including herbs, other parts of plants like the flower or roots, and extracted oils from plants—used to season foods to build flavor (Billing & Sherman, 1998). Imagine a food spiced with chili powder (capsaicin) lending a spicy heat. If sensitive to PROP/PTC, you may experience the heat as more intense than nontasters (Prescott & Swain-Campbell,

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2000) but plenty of nontasters find spicy food to be intolerable. Thus, the sensation of spice occurs at least in part through a different mechanism, made quite clear by the burning pain experienced when we pass the limits on our own subjective spice tolerance. Food that is too spicy for an individual is painful to consume, pointing to the role of nociception (pain perception) rather than taste. The spice receptor is identified as TRPV1, a heat-sensing channel that signals pain (Caterina et al., 1997). Similar prickly sensations come from ginger or radish, but sensitivity to spice does not necessarily map on to the construct of taste sensitivity described thus far. In Chapter 12, we further explore the function of spice in the context of cuisine.

Based on this information, do you predict yourself to be a nontaster, taster, or supertaster? How might you test your prediction? If using dye on your tongue and counting the papillae under a magnifying glass is not feasible, PROP/PTC test strips are readily available on the Internet.

Course 2: Olfaction—Decode the Odor Eating would be risky without our sense of smell, and our ancestors would likely have made themselves ill (or far worse) if they had to taste-test each food to determine its safety. The main function of the olfactory system for consumption is to identify appropriate foods and avoid harmful substances, an underappreciated role in the modern world of refrigeration and protection against food-borne pathogens. Olfaction is essential for well-being via its roles in eating and social interactions. Most humans go to great lengths to maintain a pleasant, or at least nonoffensive, odor, highlighting the role of the olfactory system in social interactions. The role of pheromones is typically relegated to animals, yet humans also possess the specialized aspect of the olfactory system that processes pheromones called the vomeronasal organ (Meredith, 2001). Humans are able to distinguish thousands of odors (Buck & Axel, 1991), but primary odors are difficult to specify and name compared to the five primary tastants. As learned in Chapter 4, abnormal functioning can provide insights into normal functioning. In this regard, specific anosmias, the inability to perceive a particular compound, offer understanding of odor primaries. Amoore (1977) studied anosmias, finding 80 different compounds that mapped onto 32 primary odors, isolating the chemicals that yield scents like musk, fishy, and malty. In the end, his research generated more questions than answers, as real-world scents are mixtures of many molecules, and some chemical compounds are perceived differently by different people. Isobutyl isobutyrate, found in apricot and other fruits, is a flavoring agent in alcoholic beverages, but was described

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Figure 5.3  Olfactory pathway. The olfactory pathway (created in BioRender). (Ob: olfactory bulb; Prfm: piriform cortex; AMG: amygdala; THAL: thalamus; OFC: orbitofrontal cortex). Created by Leighann Chaffee.

as either fruity or minty by participants. Decades of research on olfactory perception and coding yielded questions about the molecular “logic” of smell and why the pleasure of good food depends so heavily on the aroma.

The Olfactory Pathway: Following the Scent When inhaling a scent, odor molecules are swept up and in toward receptors on olfactory sensory neurons embedded in a layer of tissue in the back of the nasal passage called the olfactory neuroepithelium (epithelium means thin layer of tissue; Axel, 1995; Carlson & Birkett, 2017). Olfactory sensory neurons, support cells, and stem cells line the olfactory neuroepithelium. These stem cells replace the short-lived olfactory neurons every few weeks (Figure 5.3). The olfactory sensory neuron axons project through a thin portion of the skull at the top of the nasal passage to the olfactory bulb, then form a synapse on the neurons that travel to higher brain regions. These signals project to the primary olfactory cortex, called the piriform cortex (sometimes spelled pyriform, which means pear-shaped), located at the junction of the frontal and temporal lobe. Note the two olfactory pathways: Thalamic-OFC: Olfactory receptors → Olfactory bulb → Piriform cortex & Amygdala → Thalamus → OFC Limbic: Olfactory receptors → Olfactory bulb → Piriform cortex & Amygdala → Limbic system

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Unlike gustation and the other senses, olfactory signals reach the cortex without first passing through the thalamus. At the cortex, the multiple incoming sensory signals are integrated for conscious perception of odors via the thalamic-orbitofrontal pathway and emotional response via the limbic pathway (Mainland et al., 2014). The piriform cortex integrates multiple signals through reciprocal connection with multiple brain regions and is active during cognitive and motivational tasks (Gottfried, 2010). The primary olfactory cortex codes the types and intensity of odors, and the OFC represents the pleasantness and reward value of that odor (Rolls & Grabenhorst, 2008). In addition to the OFC, the piriform cortex sends simultaneous downstream messages to the amygdala, hippocampus, insula, and striatum to activate behavioral and emotional responses to odor, which are functions addressed in the next section. How does this pathway detect the 10,000+ chemicals to recognize odors? This question inspired Linda Buck and Richard Axel to embark on decades of groundbreaking research that led to their 2004 Nobel Prize in Physiology and Medicine (Mombaerts, 2004). They showed that a full 3% of human genes code for odor receptors, and the organization of the odor detection and coding system is the key to comprehending odor perception. Each olfactory receptor type can recognize multiple odors and individual odors activate a combination of olfactory receptors (Buck, 2004; Zou & Buck, 2006). These combinations allow 350 total olfactory receptor types in humans, whereas other mammals have more, to recognize thousands of odors on average. To think about this another way—imagine you have 10 ingredients in your pantry. These ingredients can be combined into many different mixtures, and even more if cooking with distinct methods, but just focus on mixtures for now. There are 10 possible mixtures with one item each, 45 ways to combine two items, and 120 ways to combine three ingredients. The calculations in combinatorial mathematics can get quite unwieldy. To follow through on this example, the 10 ingredients in your pantry can be combined into 1,023 possible mixtures. Now imagine your brain processing the combinatorial nature of 350 odor receptors activated by tens of thousands of individual odors, a process that occurs throughout the day without conscious effort. Herein lies the enigma of olfaction because we do not fully grasp how the brain decodes sensory signals from our olfactory system. We can unite the activity of many olfactory receptors into a distinct sensation, as the molecules that make up our meal are blended for a cohesive odor. We are simultaneously able to selectively attend to a single odor, to smell the aroma of a single food item, in a complex environment with many other odors. The organization of this system provides some clues in that olfactory receptors that respond to similar odors are grouped into regions of the olfactory neuroepithelium (Ressler, Sullivan & Buck, 1993). This topographic grouping of similar odors is preserved at the olfactory bulb (Rubin & Katz, 1999). These signals then project to the piriform cortex in a fashion that varies between individuals, meaning that Authors LC and SS could agree that a perfume smells like roses while the patterns of activation in their piriform cortex would be unique (Schaffer et al., 2018). And remember that odors in the real world are

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mixtures of dozens of molecules; these combined odors have distinct representations in the piriform cortex rather than being created from a combination of individual molecules (Gottlieb, 2010). Next investigated is the question of how the brain decodes the chemical signals from the environment to deliver the emotional and behavioral responses to specific smells.

Souvenirs from Smells: Odor-Evoked Memory When LC moved to Boston in her mid-20s, she was surprised by how frequently she thought of her Grandma Carol, experiencing warm fuzzy feelings from memories visiting her in the summer when she was young. What explains this experience? Grandma Carol lives in rural Pennsylvania, in a lovely home with a beautiful sun porch looking across the backyard. As with many 1950s homes in humid climates, the house has a particular scent that is pleasant but a bit damp. During LC’s childhood, this odor was very unique to her grandparent’s home, but when she moved to Boston she was bombarded by the warm fuzzy feelings and odor-evoked memories of Grandma Carol when she entered nearly every home, including the apartment LC rented, due to their shared damp scent. We have long known about these memories, sometimes called Proustian in reference to Marcel Proust’s writings of a madeleine biscuit evoking joyous memories of his youth (Herz & Schooler, 2002). Neurological understanding of such memories came more recently. Recall that the olfactory pathway is unique in its direct, one-synapse connection to the amygdala and thus easy access to the adjacent hippocampus. The characteristics of odor-evoked memories are sometimes explained with the acronym LOVER—limbic, old, vivid, emotional, and rare (Larsson et al., 2014). The limbic pathway for olfactory perception allows emotional response to odor in advance of conscious perception of the odor because activation of the amygdala provides the emotional significance prior to the activation of the cortex. In fact, the amygdala and hippocampus show more potent activation to odor-evoked memory than general odors and visual cues (Herz et al., 2004). Olfactory cues conjure a more intense emotional memory than verbal and visual cues (Herz & Schooler, 2002), and odors are effective cues of autobiographical memory (Chu & Downes, 2002). Odor-evoked memories are possible for aversive events—imagine smelling the cologne or perfume of a scorned ex-lover. The associations between odor and past experiences rely on memory (Cain, 1979). Remember that adaptability is a defining feature of the nervous system, and the olfactory bulb is one of only two regions in the adult brain that generates new neurons throughout life (Ming & Song, 2005). Olfactory sensory neuron outputs demonstrate plasticity when animals form predictive associations between specific odors and fear (Kass et al., 2013). Recent research highlights the benefits of cell turnover in the olfactory bulb to enable learning and association of meaning with smells (Lledo & Valley, 2016) as new cells fine-tune sensory information processing to adapt to the environment. The remarkable neurogenesis and plasticity of olfactory neurons explain the complexity of

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odor recognition. The adaptability of the olfactory system elucidates diversity in the individual experiences of smell.

Individual Similarities and Differences Given that we readily learn associations between experiences and odors, context and culture can influence odor perceptions. While folks tend to agree on the pleasantness or unpleasantness of certain odors, a few differences highlight cultural influences on these associations. Scents of cleaning products vary globally, as anise or wintergreen may be associated with appetizing food items or inedible chemicals for cleaning. Culturally specific odors are rated as more pleasant by the groups from which they originate, such as soy sauce and dried fish for Japanese participants (Ayabe-Kanamura et al., 1998). Though gender differences in sensory abilities are commonly assumed, the stereotypes of gendered differences in smell rely on heteronormative assumptions for social roles and the data do not conclusively support these presumptions. When studies find a difference in olfactory sensitivity or discrimination abilities between biological sexes, females demonstrate marginally superior olfactory acuity (Sorokowski et al., 2019). Given that experience guides olfactory perception, this gender difference may be explained by enhanced opportunities for olfactory learning for females. However, gender differences in olfactory abilities emerge developmentally early, which may indicate a biological basis, as the gender differences are more pronounced in female acuity to human biological odors (Brand & Millot, 2001). Smell is more than odor alone, also serving as crucial social and health functions. The most significant individual differences for olfaction are changes related to aging. During aging, both sensitivity to specific odors and discrimination between odors diminish, though the degree of olfactory acuity decline is variable (Kremer et al., 2007). Age-related decline in memory is also associated with a decline in odor recognition likely due to decreased responding in both memory and olfactory regions (Cerf-Ducastel & Murphy, 2009), impacting enjoyment of food, nutrition, and thus well-being (Doty & Kamath, 2014). Olfactory decline predicts several causes of inadequate energy intake and subsequent mortality, including neurodegenerative diseases (Pinto et al., 2014). The deterioration of sensory abilities during aging can also impact mental health; poor odor identification is associated with symptoms of loneliness and depression (Sivam et al., 2016) and early screening for olfactory decline is essential to maintain quality of life during aging. What explains the sensory loss caused by COVID-19? Early estimates from patients with COVID-19 show nearly an 80% decline in olfactory function and 70% decline in taste function (Parma et al., 2020). By one analysis, the loss of smell is the best predictor of COVID-19 infection (Gerkin et al., 2020) and thus useful when laboratory tests are not available. Unfortunately, it seems as though SARS-CoV-2 enters cells by binding to receptors that are abundant in the olfactory neuroepithelium described earlier, providing

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access to the central nervous system via the olfactory sensory receptors and supporting cells (Kay, 2020). At present, most patients who survive the virus recover their olfactory and gustatory function, though the time course and experience is variable and some patients indefinitely lose their full abilities.

Morsel: Cilantro Think back to the foods identified as key markers of taste sensitivity. These foods are nearly all bitter—vegetables like broccoli and cabbage from the Brassica family, coffee, and alcohol. Cilantro, also known as coriander leaf, is one highly divisive food item not yet discussed. Do you experience cilantro as pleasant and fresh? Or unpleasant, with a soapy or dirty flavor? Individual differences in preference for cilantro implicate culture, as it is featured in a subset of all global cuisines including those from Asia, Latin America, the Caribbean, and the Mediterranean regions. In one study conducted in Toronto, the proportion of participants who disliked cilantro varied by ethnocultural group, and dislike was least common among the participants identifying as South Asian, Hispanic, and Middle Eastern (Mauer & El-Sohemy, 2012). Erikkson and colleagues (2012) conducted a genome-wide association study to identify the specific inheritance pattern of cilantro preferences in a sample of 14,604 participants of European ancestry. They identified a candidate gene (a single-nucleotide polymorphism) to distinguish cilantro likers and dislikers. This gene is known to code for olfactory rather than taste receptors. The heritability estimate of this allele for soapy taste is quite low, meaning that only a small proportion of the variability in cilantro perception is due to inherited factors. This low heritability emphasizes the role of experience, from exposure to mother’s diet in utero to the prevalence of cilantro in home cuisine, in shaping our perceptions of cilantro flavor.

Course 3: Flavor Perception Our preferences for certain flavors, from coffee to cabbage to cilantro, are shaped by both biology and experience. The heritability of PROP sensitivity and cilantro preferences calls attention to the role of genes in individual experiences with foods. When interacting in the environment, the perception of flavor depends on both the bottom-up sensory processes of gustation and olfaction and the top-down processes of psychological influences. Gustation and olfaction themselves are dependent entities, though the role of olfaction in the perception of flavor is a bit underappreciated. While eating, odor molecules from food in the air move in through the nose (orthonasal transmission) and food in the mouth excites the olfactory receptors high up in the nasal cavity through retronasal transmission

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(see Figure 5.2). Yet perception of flavor is guided as much by psychological influences as by sensory processes. Additional sensory aspects of food items influence their palatability and our experiences of them; imagine a soggy loaf of bread or a warm beer, both rather unpleasant due to unexpected texture and temperature. Preferences for crunchy foods are likely adaptive as the texture of fruits and other foraged items can be a clue to their safety, and crunchiness indicates freshness (e.g., of an apple) and provides auditory stimulation for the multisensory experience of flavor (Zampini & Spence, 2004). Any novice home cook can attest to the challenges of timing dishes to be ready and still warm when they reach the dinner table, even though the role of temperature was underappreciated for a time. The first European celebrity chef, Marie-Antoine Carême, epitomized the style of service á la français, with extravagant food sculptures served cold and rather unpalatably (Lehrer, 2007). The more contemporary chef Escoffier, a genius of umami mentioned earlier, favored service in courses of individual dishes, each served fresh and hot from the kitchen. The warmth allows more molecules from the food to evaporate into the air, and these vapors enhance the resulting aroma and flavor. Again, Escoffier was guided by principles of pleasure in eating. Like many other chefs and restaurateurs, Escoffier recognized the importance of the context and experience in the perception of flavor. Thus far, our description of gustation and olfaction has focused on bottom-up processing, when the features of a stimulus are interpreted from the sensory receptors up the pathway to the cortex to interpret the experience. The appearance, aroma, and taste of a new food help determine whether or not to try it. But an individual’s perception and preferences are unique and are too complex to understand through bottom-up sensory processes alone. Knowledge, expectations, and the context drive perception in top-down processing (Reisberg, 2019), like when making a new dish from a favorite cookbook but have preexisting knowledge and expectations that guide expectations for the flavor of that food. Top-down processing helps explain the superiority of our favorite brand as compared to the competitor, the enjoyment of shared meals over dining alone, and preference for our grandmother’s preparation of the special family recipe even though we could make it ourselves. Gustation itself is not merely a bottom-up process, and some researchers argue that gustation is actually multisensory given the influence of temperature and texture on taste via additional sensory neurons in the mouth.

Chew on This: “I Scream, You Scream—We All Scream for Ice Cream” Gelato, sorbet, kulfi, chongos, dondurma, mochi, faloodeh, plombir, akutaq—many global cuisines possess a cold and delicious dessert similar to ice cream. The endless varieties of ice cream reveal its popularity, but the brilliance of ice cream lies in the multisensory nature of flavor. Taste alone does not solve the riddle; after all, before hardening in the freezer, the ice cream mixture is too sweet and soupy to be palatable. But temperature influences flavor, and considerable amounts of

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sweeteners are required for the ice cream to be perceived as sufficiently sweet when it is frozen. A family of receptors expressed in the taste buds (TRPM5), similar to those described for taste sensitivity, are responsible for signaling temperature information and the thermal sensitivity of sweet taste (Talavera et al., 2005). After the first bite of ice cream melts slightly in our mouth, we experience enhanced sweetness and creaminess (Hayes, Feeney, & Allen, 2013). This dynamic nature of ice cream enhances the multisensory experience and makes it so delightful.

Flavor perception depends on a distributed network of brain activation. Gustatory and somatosensory information, encoding taste plus temperature and texture from the mouth, converges at the NTS in the brainstem (see Figure 5.2) with visceral input from the gut. Descending projections from the gustatory cortex, amygdala, and hypothalamus also meet at the NTS, demonstrating top-down modulation of taste information (Simon et al., 2006). Similar top-down influences are documented for olfaction, such as the contextdependent nature of rodent sniffing behavior, enhanced by motivation to perform a task (Jordan et al., 2018). An important follow-up inquiry is why and how these top-down influences interact with sensory experiences. The flavor network, including the insula, plus the OFC and anterior cingulate, provides both bottom-up and top-down processing for flavor perception. The higher brain structures provide psychological inputs such as attention and expectation that guide experiences with a particular food. Given that taste and smell of food items are linked during each experience in the real world, it is difficult to estimate the boundary between the contribution of each sense to flavor perception.

Morsel: Why We Need Sommeliers Wine maintains an elevated status in many global culinary traditions, both past and present. The ubiquitous alcohol use around the globe, despite adverse consequences (to be discussed shortly), is owed to the activation of the reward system by alcoholic beverages boosted by the social norms around drinking. Wine is prevalent, but the process of judging and describing wine is a challenging task, requiring a knowledge base, multisensory processing, meticulous memory for past experiences, and illustrative communication abilities. Restaurants commonly employ or contract a sommelier, an expert, to work with the management and purchasers, building and maintaining the wine inventory, collaborating with the chef to complement the menu, and educating the staff on ideal pairing suggestions. Wine tasting itself is a rather ambiguous and subjective experience. Emphasis is placed on detecting sweetness from residual sugars after fermentation, sourness from acidity levels, and astringency from the tannins that is often confused with

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bitterness (Koone et al., 2014). In fact, perception of PROP bitterness does not directly predict alcohol intake. Nontasters experience liquor like scotch as less bitter and sweeter than tasters and are therefore more accepting of substances containing alcohol (Lanier, Hayes, & Duffy, 2005). The expectations forged from experiences and encouraged by sommeliers influence the perception of wines. You may even be familiar with the infamous study in which wine experts were unable to distinguish between red and white wine. Frédéric Bouchet at the University of Bordeaux further demonstrated the role of subjectivity, tricking students of oenology (the study of wine) to alter their description of a wine based on the price and the color (Morrot, Brochet, & Dubourdieu, 2001; Brochet & Morrot, 1999). The expensive label does more than influence subjective perception of flavor; it is also correlated with increased activity in the medial OFC (Plassman et al., 2008). You may realize verbal descriptions of food items can change perceptions of them, and the magnitude of this effect can be quite astounding. Top-down influences from the language used to describe foods or products alter brain activation in the flavor network and the appetitive value of that item (for review, see Piqueras-Fiszman & Spence, 2015). Contextual cues influence the layperson and expert alike. In a small study of experienced (male) sommeliers as compared to naïve participants, expertise was associated with a larger network of activation including the left insula and OFC, and bilateral dorsolateral PFC (CastriotaScanderbeg et al., 2005). You may recognize these structures as the flavor network, plus the additional region of the PFC that integrates executive function to form analytic judgments compared to naïve participants. Though progressive winemakers assert that we should drink what we like, more traditional approaches emphasize specific rules for pairing. Flavor pairing is not as straightforward as grouping similar tastes or chemical compounds (Ahn et al., 2011). Food and beverage pairings are guided by cultural guidelines for specific cuisines. Recommendations for pairing are articulated by experts in culinary schools and textbooks or are passed down through traditions of shared cultural knowledge. Pairings may emphasize balance and compatibility, or complementary components of the food and beverage items. Eaters prefer similarity in food and wine pairings, pairing sweet foods with sweet wines, and similar acidity levels also create a balanced and desirable pairing (Koone et al., 2014), as aromatic similarity between food and beverage can enhance perceptions of harmony and complexity (Eschevins et al., 2018). LC has an unrefined palate for wine and commonly relies on restaurant (or Internet) recommendations for food and beverage pairings, highlighting the take-home message of this section. Expectations influence perceptions, and a positive recommendation from a knowledgeable party, like a sommelier, enhances our experience with both food and beverage (Siegrist & Cousin, 2009).

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We can assume Louis Pasteur had good intentions when he said, “Wine is the most healthful and most hygienic of beverages,” but he was perhaps overlooking the potential dangers of excessive drinking. Alcohol (ethanol) is one of the most commonly used psychoactive substances, altering perceptions, thoughts, mood, and behavior. In the short term, drinking may have pleasurable effects such as relaxation and boosting confidence, but it also reduces coordination, hinders good judgment, and can lead to risky behavior. It depresses the central nervous system, enhancing the effects of the inhibitory neurotransmitters GABA and activating the dopamine reward system. The depressant effects of alcohol might sound fitting for the nightcap to induce a more relaxed and stress-free state for sleep. Yet, although alcohol may relax us initially, once alcohol is processed the opposite effects occur due to withdrawal. The initial inhibitory (depressant) effects are challenged by the compensatory efforts in the nervous system to restore homeostasis. Unless alcohol intake is sustained, psychological effects of alcohol 3–4 hours after consumption include dehydration, elevated pulse, agitation, nervousness, and insomnia. Yes, that is correct: insomnia (Bayard et al., 2004). As with any cycle of tolerance and withdrawal, repeated use of alcohol leads to increasingly smaller initial depressant effects and increasingly larger indirect compensatory excitation. Consuming alcohol also impacts the way we eat and process food. Alcohol supplies 7 kcal of energy per gram but fails to signal satiety, and alas there is no compensatory reduction in meal size (Yeomans, Caton, & Hetherington, 2003). Further, the psychoactive effect of alcohol—disinhibition—encourages food intake. This information may be useful for a restaurateur or host of a dinner party, but may be a disappointment for the occasional drinker who enjoys a glass of wine with dinner. At mealtime, beverage choices including alcohol can enhance the flavor of the meal. When ethanol is consumed with fatty foods, triglycerides rise, and several signals described thus far are upregulated. Alcohol promotes insulin resistance independent of energy intake or expenditure, and degree of insulin resistance is associated with severity of liver disease in chronic alcohol use (Carr et al., 2013). A positive feedback loop is hypothesized, in which circulating lipids and alcohol alike stimulate eating via dopamine, endogenous opioids, and orexins to promote alcohol intake or excessive eating (Leibowitz, 2007). Circulating leptin levels are associated with alcohol intake independent of obesity (Mantzoros et al., 1998). Given these interactions, appetite signals may be assistive for treating alcohol use disorder. For example, NPY levels in the mouse brain are inversely related to alcohol consumption and tolerance (Theile et al., 1998), and ghrelin levels positively correlated with duration of abstinence in patients with chronic alcoholism (Kim et al., 2005). Therefore, signals like ghrelin or NPY could be helpful for maintaining abstinence, though these approaches are not currently applied in treatment. Chronic alcohol use has adverse effects on the brain, cardiovascular system, liver, and gastrointestinal system (Meyer & Quenzer, 2019). Longer term effects include liver cirrhosis, kidney failure, gout, and obesity, as well as greater prevalence of vitamin deficiencies (e.g., hypocalcemia, hypokalemia) since absorption and processing of

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nutrients is debilitated. In lean women, incidence of type 2 diabetes increases with alcohol use. Globally, over 7% of male deaths can be attributed to alcohol use (WHO, 2018). Despite conventional wisdom and wishful thinking that small doses of alcohol promote health, a recent meta-analysis concluded “the safest level of drinking is none” (Griswald et al., 2016). Alcohol is the third leading cause of preventable death in the United States (NIH, 2020) and contributes to over 5% of the global burden of disease and injury (WHO, 2018). Given these dangers, why is alcohol use so ubiquitous? The biopsychosocial approach provides significant insight. In addition to enhancing the inhibitory effect of the neurotransmitter GABA, which leads to relaxation and disinhibition, alcohol activates the dopamine motive system and the endogenous opioids to deliver reinforcement and subsequent craving (Meyer & Quenzer, 2019). The biological effects of alcohol explain the psychological reasons for misuse, as alcohol both enhances pleasant feelings and provides self-medication for anxiety and negative mood due to serotonin system involvement (Swenden et al., 2000). And these psychological mechanisms for stress-induced drinking have a hereditable component (Spanagel, Noori, & Heilig, 2014). Such forces on addiction exist within cultural contexts and norms around drinking, and the low rates of alcoholism in cultures prohibiting alcohol illustrate the potent social forces at play. Multisensory integration of gustatory, olfactory, visual, and oral somatosensory stimuli occurs in the OFC (Rolls & Grabenhorst, 2008). In addition to integration, the OFC directs top-down efforts to process sensory information—for instance, in enhancing or suppressing taste responses at the gustatory cortex on the basis of present olfactory information (Shimemura, Fujita, & Kashimori, 2016). Other researchers demonstrate that the insula is an essential player in odor processing in the piriform cortex even when taste stimuli are not present (Maier et al., 2015). Return to the imagination exercise from Course 1 of a chocolate chip cookie hot from the oven. As the cookie warms, the molecules become volatile and the aroma vapors enter our nasal passage to excite the olfactory receptors in our olfactory neuroepithelium, projecting to the olfactory bulb and then the piriform cortex. From here, we may experience warm, pleasant emotions based upon past experiences with this same treat given the direct access to the amygdala. Odor signals are simultaneously transmitted on the limbic and thalamic orbitofrontal pathway where our brain encodes the pleasure of this aroma and activates other cortical regions for reward and motivation, encouraging us to take a bite of the cookie. As we take a bite, odors continue to activate the olfactory pathway through retronasal transmission. Our olfactory experience is complemented by the delicious taste; gustatory and somatosensory information is transduced from the tongue and mouth to the NTS in the brainstem via cranial nerves. The taste information is relayed through the thalamus. The next stop is the primary cortex—both the gustatory and somatosensory cortex are activated rapidly, as multisensory information converges to help us comprehend the

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complexity of the flavor. Finally, the OFC integrates signals of taste, smell, and texture to code the pleasure you experience while eating that favorite food. Simultaneous top-down influences guide flavor perception—our mood, expectations, and memories influence the flavor we experience and the subjective pleasure in that moment. Taste itself is a primary reinforcer; thus, it has value without additional rewards or punishment, and the insula and OFC project to the reward system to encode the value of specific tastes (Rolls & Grabenhorst, 2008). Flavor perception is also modulated by positive and negative experiences, by associating tastes with outcomes like pleasure or poisoning. Gina Rae La Cerva asserts: “Flavor is a map of our desires,” which is supported by evidence from neuroscience since the flavor network responds more robustly to food cues when hungry than when full. We cannot rely on singular and reductive explanations to comprehend flavor perception, but rather must consider the complex, experiential, and neural factors that guide our interactions with the world.

Dessert: Eat First with Your Eyes—Plating and Presentation How does the appearance of a cookie or wine influence perception of flavor? Throughout the chapter, taste and smell are discussed as dependent entities, highlighting the oft underappreciated role of olfaction and aroma in experiences with food. But flavor perception is more than taste and smell, it is a multisensory experience with top-down influences from sophisticated cortical regions. For humans, the act of foraging, whether finding food in the wild or in the grocery store, relies primarily on vision. Similar to the previously cited research on wine, the hue and appearance of foods influence perceptions, particularly when the color does not match expectations (Spence, 2015). It is important to note the appearance of food beyond the color matters. The early celebrity chef Carême acknowledged that “A well-displayed meal is improved one hundred percent in my eyes” and encouraged artful and architectural plating of his creations. In plating, the neatness and attractiveness influence liking of the meal (Zellner et al., 2011 and 2014). Spence and colleagues (2016) emphasize that adaptive reliance on vision to find sustenance makes us prone to “visual hunger” as the presence of food cues drives consumption. Visual cues of palatable and energy-dense foods grab attention, activate the flavor network, and promote overconsumption. These researchers and others postulate that attractive plating of “healthy” foods, for instance, arranging a salad in an appealing display on the plate, could improve liking and thus consumption of those foods. Pictures of beautiful food are abundant in advertisements and digital media, and viewing these images activates the reward network to motivate consumption, a topic we return to in Chapter 10.

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Dining Review Key Elements

Recommended Reviews

Whet your appetite: Flavor

Update your operational definition of flavor with evidence from this chapter.

The amuse-bouche:

How does olfaction influence flavor perception? And why might specific viruses impact our sensory abilities?

COVID-19 Course 1: Gustation

Diagram the gustatory pathway. Describe the sensation and perception of umami and spicy tastes.

Course 2: Olfaction

Diagram the representation of an odor-evoked memory in the olfactory pathway.

Course 3: Flavor perception

Describe an eating situation with differential top-down and bottom-up influences on flavor perception. Identify the brain areas responsible for aspects of sensation and perception in your example.

Morsel: Why we need

How does perception of flavor, for example, of wine, differ between novice and expert tasters? Describe influences on excess drinking.

sommeliers Dessert: Plating and presentation

Why do some researchers define gustation as multisensory? How might you apply principles from this chapter to enhance your experience with the meals you prepare?

Gochisousama Thanks to the chef! Recommended reading: ●

●

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An interdisciplinary text describing lessons on the brain from artists, including gustation and olfaction: Lehrer, J. (2007), Proust Was a Neuroscientist. New York: Mariner Books. An anthropological perspective on our relationship with wild food: La Cerva, G. R. (2020), Feasting Wild: In Search of the Last Untamed Food. British Columbia: Greystone Books. Dr. Maya Warren, the ice cream scientist, on the chemistry of ice cream deliciousness https://www.mayawarren.com.

Glossary Anosmia:

loss of the sense of smell

Bottom-up processing: processing sensory information as it is received that works up toward a representation and more advanced cognition about that stimulus

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Gustation:

the action of tasting, the sense associated with taste

Insula:

the primary gustatory cortex

Interoception:

the sense that allows for detection of what is going on inside of our body, for example, feeling full

Olfaction:

the action of smelling, the sense of smell

Perception:

the organization and interpretation of sensory information

Pheromones:

chemical scents that influence the behavior of members of our same species, signaling opportunities for mating or competition

Sensation:

the process of detecting sensory information via receptors

Taste sensitivity:

a construct of taste intensity based on the distribution and density of taste receptors on the tongue

Top-down processing: processing of information that starts with higher-level cognition, as the brain applies knowledge or expectations to the perception of information

Chapter 6 Variety Is the Spice of Life: Cognitive Psychology and Eating Whet Your Appetite: Don’t Judge a Food by Its Cover Imagine the following scenario: You are hungry and thirsty trying to grab a quick bite in a busy and crowded market. What information do you use to make your choice? The appearance, cost, convenience? Are you swayed by the healthiness of the items? Do statements like low fat, lean, or organic catch your eye? This chapter explores information processing and memory to describe the methodical and not-so-methodical decisions that contribute to consumption.

Menu Amuse-Bouche: Eating, Fast and Slow Course 1: At the Head of the Table—Cognition Categories Heuristics Food Choice: Procurement and Consumption Decisions Course 2: The Hungry Hippocampus—Memory and Eating Nutrition Research and Memory Course 3: On the Back Burner—Parallel Processing Dessert: Angel Food—The Health Halo Dining Review Gochisousama Glossary

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Amuse-Bouche: Eating, Fast and Slow The present chapter would be relatively brief if humans were perfectly rational, weighing pros and cons equally for effective decision making. Consider your recent food

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choices—can you identify a time you acted less than sensible, perhaps selecting a food known to cause a stomachache or eating out despite having leftovers in the fridge? Why do people make irrational decisions? Nobel Prize winners Daniel Kahneman and Richard Thaler have answers—these researchers, plus others, pioneered the field of behavioral economics (Thaler, 2016). Research in behavioral economics functions at the intersection of psychology, cognitive science, and economics, to explore the predictable irrationality of human beings. Delay discounting (Chapter 4) exemplifies the irrationality in the tendency to choose immediate rewards, even when they are less valuable than future rewards or outcomes. In contrast with more traditional perspectives that assume consumers are rational and deliberate, evidence from behavioral economics provides a more realistic understanding into processes of cognition that influence our food decision making, for better and for worse.

Course 1: At the Head of the Table—Cognition The field of cognitive psychology is the scientific study of the mind as an information processor, aiming to describe our thought processes to address theoretical issues such as rationality and practical considerations like our perception of food labels. Our goal in the present chapter is to recognize and apply cognitive processes in order to understand food decision making.

Categories Humans use concepts and categories to simplify the world—after all, it is easier to plan to meet your friends for pizza than to explain that you are hungry for flat dough with red sauce, topped with Italian meats and cheeses, and baked at a high temperature in a special oven. In this example, pizza serves as a category to facilitate communication and comprehension by providing cognitive economy. How are categories formed? According to prototype theory, categories are defined by the “ideal” example, or prototype; membership in the category is determined by comparison with the prototype (Rosch, 1973). The prototype is an average that represents the category, influenced by your experiences, for instance, with pizza. Similarly, exemplar-based reasoning uses a specific remembered instance, perhaps a New York-style slice, a Chicago deep-dish, or authentic wood-fired pizza from Naples. Both prototypes and exemplars rely on memory to determine category membership. Categorization is more consequential than ordering pizza: our ability to classify items as edible and inedible is crucial for survival. Keep in mind that omnivores face a “dilemma” to consume a balanced diet while avoiding toxins (see Chapter 3; Rozin, 1976). The classifications of foods and rejections of nonfoods depends, in part, on certain aspects of stimuli. The property of color is especially relevant when categorizing novel food objects (Spence & Piqueras-Fiszman, 2016), valued over shape for rhesus

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Figure 6.1  Citrus fruits. Can you identify and classify these objects despite their ambiguity? Image by PublicDomainImages for Pixabay.

monkeys and human children alike (Santos, Hauser, & Spelke, 2001). Categorization by color is domain-specific, and different properties are used to categorize objects in other domains (e.g., tools; Rosch, 1973). Interestingly, domain-specific representation of food items is not present in infants and emerges in early childhood around age 4 or 5 (Hauser & Spelke, 2004). It is generally accepted that humans and other primates have a specialized cognitive system for representing and recognizing edible items given the consequences of mistakes in food selection (Figure 6.1; Santos, Hauser, & Spelke, 2001). During infancy and early childhood, nourishment takes a central role in the daily life of our parents and caregivers. Eventually humans (and animals) must independently navigate the food environment, including the constant stream of complex nutritional information on the helpful and harmful aspects of certain foods. Unfortunately, with little training in nutrition, epidemiology, and risk analysis, humans are underprepared to respond to the abundance of health information (Rozin, Ashmore & Markwith, 1996). While our capacity for categorization is essential for survival, categorical thinking can get us into trouble by creating false dichotomies, for instance, between “sweet” and “nonsweet” foods. In one study, 45% of participants thought that 5 oz of bread had fewer calories than 1 oz of chocolate, demonstrating dose insensitivity and the categorical thinking of bread as relatively less rich than chocolate (Rozin, Ashmore,

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& Markwith, 1996). Categorical thinking is but one example of cognitive errors around nutrition information.

Heuristics Simple rules and strategies that guide food choice—for example, considering all salads as healthy food options—demonstrate use of heuristics. Heuristics are mental shortcuts that simplify judgment or decision making by reducing complex cognitive tasks such as calculating probability to simpler mental operations (Tversky & Kahneman, 1974). For instance, when trying to decide between two snacks, selecting the cheaper option is easier than a lengthy analysis of the perceived palatability, attractiveness, convenience, ingredients, health, and ethical concerns related to each product. The simple heuristic of making decisions based on a single attribute is called a lexicographic decision rule (Bettman, 1979), and employing this heuristic to rely on one or only a few attributes simplifies food choice decisions (e.g., Scheibehenne, Todd, & Miesler, 2007). As an example, a person may rely on the name or appearance of a dish more than other attributes such as price, calories, and nutritional information when selecting a lunch item at a cafeteria (Schulte-Mecklenbeck et al., 2013). If you currently are primed to attend to calories (let’s say, because you are on a diet), calorie content might be the one attribute driving your decisions; in a point or macro-based diet system, the points or macros become the focused attribute.

Chew on This: Tricked by Unit Bias Suggestions to decrease our portion sizes for weight loss are a part of many diets because portion control is an easily modifiable contributor to total energy intake. Now consider the heuristic of unit bias, or the idea that a single entity is the appropriate amount (Geier, Rozin, & Doros, 2006). If served a beverage at a restaurant, diners are likely to drink the beverage without looking up the recommended serving size for that beverage, or measuring the volume of the glass. People assume the amount served at a restaurant or purchased at the store is the correct amount to consume without doing additional research or measuring. In addition to the unit bias heuristic, heuristics such as “finish your plate” or “don’t waste food” increase eating (Hetherington & Blundell-Birtill, 2018). Encouraging appropriate portions through specific training can be helpful, but there is some evidence that awareness that portion sizes have increased over time and are often larger than in previous decades (called the portion size effect, see Chapter 9) is insufficient to prevent overeating (Zuraikat et al., 2018).

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Clearly, heuristics can yield poor outcomes, like selecting a product based on the label while neglecting the price or overeating due to unit bias. Heuristics are useful in navigating our numerous daily food decisions because they increase efficiency, capitalize on expertise, and guide attention to important attributes of food (Schulte-Mecklenbeck et al., 2013), generally (but not always) resulting in smart decisions. Schemas, or generalized collections of knowledge built from past experience and stored in memory, also guide behavior in familiar situations. Schemas include organized declarative and procedural information (Figure 6.2) and include stereotypes, social roles, and social scripts. In a wellknown context, like the evening meal, scripts simplify decisions by providing sequential information about the expected events. Analysis of scripts for the evening meal among adults reveals personal values frame the experience and the food choices made (Blake et al., 2008). Whether social connection, nutrition, or relaxation, the values endorsed by the participants illustrate the special status of the evening meal. Now apply these shortcuts of cognition and thinking to our decisions about eating and drinking.

Food Choice: Procurement and Consumption Decisions Judgment is the process of evaluating evidence to form conclusions, such as drawing on experiences to offer a restaurant recommendation. The complementary process of decision making involves selecting a choice among several possibilities, for instance, ordering at that restaurant. Basic cognitive processes such as the use of categories and heuristics help understand these choices. Information processing requires synthesis of input from our senses (Chapter 5). Prior to consumption, sensory experiences lead to anticipation and expectations about the food or drink, and whether it will be enjoyed. When a food tastes different than expected, the mismatch causes surprise and can produce a negative affective response. Yeomans and colleagues (2008) asked participants to taste a food labeled as “frozen savory mousse” or “ice cream”—the food was highly novel smoked salmon ice cream. Participants’ expectations affected their sensory and hedonic responses; the incongruent label (“ice cream”) resulted in stronger and saltier flavor ratings and less reported pleasantness than the more congruent mousse label, demonstrating that congruency with expectation affects subjective food experiences. As previously reviewed regarding heuristics, poverty of time or money can adversely impact decisions and the ability to obtain a nutritious diet (see Chapters 9 and 10) as these are instances when quick, short-sighted judgments will be made with less focus on long-term consequences like health or sustainability. In fact, humans rely on only one or a few attributes in making food choices. A person may aim for health and a balanced diet, but it is challenging to act according to these values when taste is the foremost influence of food choice, followed by cost, while nutritional concerns are less relevant (Glanz et al., 1998). On a positive note, people who endorse nutrition as a value in food choice selfreport more fruit and vegetable consumption and eat less fast food.

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Morsel: Microvariety In his best-selling book of the same name, Barry Schwartz provides evidence for the paradox of choice. The paradox is that although more options seem appealing and are desired by consumers, increased options are not always best (psychologically). In fact, he argues that the pervasive choices available in modern societies can work against happiness and even contribute to depression (Schwartz, 2000). The world of eating is no exception in the nearly unlimited food and drink choices at our disposal, and we tend to shop and eat at locations with many options available—like the options for 285 cookies, 165 juices, 230 soups, 175 salad dressings, and 275 cereals in American grocery stores (Schwartz & Ward, 2004)! Maybe you have experienced the stress of this paradox during meal selections at restaurants. The wait staff visit, and your friends are ready to order, but you are full of questions: What if the special of the night is exceptional, but what if it is not? You could be sacrificing your usual and sure-favorite selection for a letdown. What will go better with the drink you already ordered? Are you hungry enough to add a salad to your meal? Having options can create anxiety and increase the likelihood of dissatisfaction with our choices—or even regret them. So, although we might prefer to go to restaurants with larger menus, the multitude of options can reduce satisfaction in the end. If you find it difficult to relate to the paradox of choice, you are not alone. Not everyone experiences it, especially in low-stakes situations like ordering from a menu. The effect is stronger in certain types of people called “maximizers” (Schwartz et al., 2002). Maximizers desire the best possible result and, by comparison, “satisficers” are okay (or, satisfied) by any decision or outcome that is good enough to meet some standard. Using the restaurant example, these two types of people are likely to reflect differently about their menu decisions. Upon having a good meal, by criteria expected for the experience, the satisficer will leave pleased by their selection. A maximizer, however, may enjoy the meal yet continue to wonder whether another selection would have been better (i.e., would have maximized their experience). Too many choices also can prevent decisions altogether, an “I can’t decide so I won’t decide” effect (Kida, Moreno, & Smith, 2010). This means that the anxiety leading up to the menu selection may be followed by conformity to others’ selections in effort to alleviate the negative emotions surrounding the decision (Schwartz & Ward, 2004).

Judgments and decisions are sometimes based on food labels, entertained at the opening of the present chapter. Qualities of packaged foods are communicated by ingredient lists and nutrition labels in most areas of the world. A nutrition label displays the macro- and micronutrients found in the food and their amount, typically in a panel,

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as a list or graphic. The purpose is to make ingredients transparent and to guide food selection, providing a clear list of all aspects of the food, from the desirable, like vitamins, to those considered less desirable, like saturated fats (Hawkes, 2010). However, nutrition and ingredient labels on food items are not universal; they vary by location and type of food item. In the United States, regulations on food labeling were recommended in the early 1970s, when food producers were encouraged to voluntarily disclose all ingredients plus calories, grams of macronutrients, and select micronutrients (Institute of Medicine, 2010). Labels were then mandated with passage of the 1990 Nutrition Labeling and Education Act (NLEA). Many other countries followed, with nutrition labels mandated in Canada in 2003 (full compliance by 2007); early regulations in the European Union began in the 1990s though full compliance was not mandatory until 2016, Australia and New Zealand in 2002, and many countries following with required or voluntary labels, notably on foods with nutritional claims or special dietary uses (e.g., Chile in 2006, the Gulf States in 2007, China in 2010; Hawkes, 2010). Regulating nutrition labels is an evolving process and, as global obesity rates climb despite interventions to improve food choices, it is essential to evaluate the impact of strategies like nutrition labels. Do nutrition labels inform consumers and affect their food purchases? The self-reported use of nutrition labels is generally high but varies by subgroup; for example, individuals with specific dietary needs or allergies are likely to use labels consistently (Campos, Doxey, & Hammond., 2010). There is some evidence that many consumers look at nutrition panels but do not actually process the information (Cowburn & Stockley, 2004). And, unfortunately, from 1995 to 2006, US consumer use of nutrition labels significantly declined when making food decisions (Todd & Variyam, 2008). Barriers to label use include lack of time (Cowburn & Stockley, 2004; van Herpen & van Trijp, 2011), unfamiliarity with the label (Bialkova & van Trijp, 2010), and poor nutrition knowledge (Miller & Cassady, 2015). One proposal for improving consumer use of nutritional information is to place the label on the front of the package, which aims to make information visible and clear (e.g., Institute of Medicine, 2010). These front-of-package indicators work best if consistent in format and placement (Bialkova & van Trijp, 2010) and if they rely on simple logos or a traffic light system seen in the UK and EU (van Herpen & van Trijp, 2011). Compared to current labels of tabled nutrients that can be overwhelming, streamlined labels convey simple guidelines that build on our categorization tendencies. Interventions for empowering consumers with nutrition knowledge may further bolster the benefits of nutrition labels. From a public health perspective, the purpose of these labels is to guide nutritional choices, and they are particularly useful for choosing among ultra-processed packaged foods. Remember that junk foods are energy-dense and hyperpalatable and, despite best efforts at moderation, the palatability of a food drives consumption via the reward system (Chapter 4). Interactions between the reward network and brain areas of the prefrontal cortex (PFC) exert executive control for processes like careful judgment and decisions (Botvinick & Braver, 2015). Activity in the ventromedial PFC is correlated with

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goal-directed decisions, and modulated by the adjacent dorsolateral PFC when exerting self-control. In one study by Hare, Camerer, and Rangel (2009), self-control was based on whether participants selected a food they (previously) rated as healthy or tasty compared to a neutral item. Executive control is the mechanism that allows our mind to prioritize goals by managing thought processes and operations (Reisberg, 2019). Thus far, the labels discussed are on packaged foods, but how does this relate to purchases at restaurants? In the United States, a number of cities and localities require calorie information on the menus of restaurants, though typically only chain restaurants or fast-food establishments. Kiszko and colleagues (2014) found significant variability in the effects of calorie information: most consumers are aware of the calorie information, but the presence of calorie information did not significantly reduce calories purchased in the majority of the studies reviewed. Decision making is situated in a social context that aims to sell us products, and nutrition education fails when the environment remains the same. However, individuals who are motivated by dieting or nutrition are more likely to use calorie information. Remember that taste is critical in food decisions; and while health consciousness and perceptions of food healthfulness may impact eating (Paquette, 2005), the degree of their effects is unclear. Nutrition knowledge and beliefs positively impact diet quality (Beydoun & Wang, 2008), as does a positive attitude toward healthy eating (Aggarwal et al., 2014). Health literacy was predictive of a higher-quality diet and negatively correlated with sugar-sweetened beverage consumption in a cross-sectional study of participants living in the Mississippi delta in the US South (Zoellner et al., 2011). Analysis of data from the National Health and Nutrition Examination Survey (NHANES, to return like indigestion later in this chapter) shows participants that prioritize nutrition during grocery shopping had higher-quality diets when controlling for income and education (Aggarwal et al., 2016). But what compels the cookies, chips, or other nonessential items into the grocery basket? The bonus cookies in the grocery basket could be considered “irrational” as they require extra cost and effort to purchase and do not align with goals for a balanced diet, yet eating the cookies will generate a positive reward (e.g., Damasio, 2003, Jacquier et al., 2012). Observation of your own actions likely illuminates inconsistency and nuance. Perhaps you have noticed the ability to say no to some treats while failing to exert self-control for others (for Author LC, donuts). Thaler (1981) outlines the evidence for “dynamic inconsistency,” as the value of a reward is dependent on the size of the reward and the amount of time until the reward is received. Not surprisingly, the utility of a food is judged in part by to the expectation that it will bring satiety (Brunstrom & Rogers, 2009). Participants rate food generally, and high-fat foods in particular, more positively when hungry (Lozano, Crites, & Aikman, 1999). Hungry participants also choose energydense snacks (e.g., chocolate bars and salty crisps) over fresh fruit, especially when selecting a snack to eat immediately as compared to a snack to consume in the future (Read & van Leeuwan, 1998). Findings like these show our dynamic inconsistency is

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biased against low-calorie options, even if they are nutrient dense. Our susceptibility to dynamic inconsistency is partly driven by an intrapersonal empathy gap, characterized by our inability to imagine ourselves in a future state that is different than our present state. This empathy gap precludes our currently satiated selves from understanding challenges encountered and decisions made by our later hungry selves. Expecting our future selves to show restraint while indulging our current selves is the crux of self-control failures (Read & van Leeuwen). Additional errors in cognition and specifically decision making further complicate food choices. Remember that categorical thinking is used to (over)simplify nutritional information by classifying foods as entirely good and bad, or healthy and unhealthy (Rozin, Ashmore, & Markwith, 1996). Sometimes the false dichotomization of a food is determined by only one “healthy” or “unhealthy” ingredient, such as calcium or sodium, through a cognitive process called the law of contagion (or, simply contagion). Consider the example of popcorn—what differentiates trendy “healthy” popcorn with the variety in the movie theater? (The answer is butter!) Contagion refers to the evaluation of a whole object (i.e., the popcorn) based on its composition or association with something specific that is value laden (i.e., the butter). In one study illustrating combined effects of food dichotomies and contagion, Chernev and Gal (2010) measured calorie estimations in participants who were offered hamburger alone, hamburger with salad, or hamburger with a chocolate chip cookie. Not surprisingly, participants correctly estimated the hamburger with a cookie contained the highest number of calories. The more interesting finding involves the calorie estimates of a hamburger with salad, which was estimated to contain nearly 100 fewer calories than the hamburger alone. Yes, you read that correctly—adding a salad to a hamburger leads to lower calorie estimations for the meal. The classification of “salad” as healthy/good has a contagious effect on perceptions of the hamburger. Another cognitive fallacy, dose insensitivity, also was observed among participants studied by Rozin and colleagues. Dose insensitivity refers to our tendency to evaluate a food as equally healthy or harmful, regardless of how much was consumed. That is, if something is harmful in large amounts, it is often viewed as similarly harmful in small amounts. Dose insensitivity undermines moderation and encourages adoption of fad diets that rely on strict adherence to or elimination of foods or sometimes entire food groups . From these fallacies it is clear that consumption decisions are sometimes misled by misperceptions and faulty logic, even when we believe our choices are informed. Choices around health behaviors, including eating, require trade-offs: the balance of proximal outcomes like satisfying hunger and future outcomes related to health. Eating behavior is predicted by consideration of immediate consequences, whereas exercising behavior is related to consideration of future consequences (van Beek, Antonides, & Handgraaf, 2013). Compensatory health beliefs are the expectation that engaging in healthy behaviors can compensate for unhealthy actions (Rabiau, Knäuper, & Miquelon, 2006), and these beliefs can rationalize indulgences. For example, people with greater

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compensatory health beliefs, whether temporary or consistent, engage in more unhealthy snacking (e.g., Amrein, Scholz, & Inauen, 2021; Radtke et al., 2014). Further, when eating choices do not align with goals, a person naturally tries to understand and explain their behavior—even if it is unintentional—by adjusting their standards for eating. On some occasions, explanations are fabricated for the unhealthy behavior after the fact to justify it (Adriaanse et al., 2018).

Chew on This: Special Occasions and Small Exceptions Think of celebrations and special events attended throughout a year and the ways these may influence eating. If you attend 10 birthday dinners and elect to eat cake at each of them, a small 300–600 calorie “exception” to typical eating habits, the total accumulation is 3000–6000 calories for the year … from birthday dinners alone! As you can imagine, birthdays are not the only reasons justifying for momentary breaks in our long-term eating tendencies or goals. There are also times when folks say, “Gosh, I’ve worked hard” or “What a day!” followed by “I need ___” or “I deserve ___,” where the blanks are filled with indulgences, like a large margarita. Cognitively, in the moment, we are insensitive to the long-term implications of these exceptions. If, instead, “small exceptions” were things like going to bed early or taking an extra-long walk to combat stress or fatigue, small exceptions can move a person toward long-term goals and health (rather than undermining them). A smallchanges framework, aimed at supporting small but deliberate efforts in lifestyle for health choices, is endorsed by the American Society for Nutrition (Hill, 2009). The moral of the story is that the next time you want to make a “small exception,” (1) make the exception to the norm something with long-term benefits or (2) make the exception as small as possible.

Errors in judgment, such as contagion, the false dichotomy, and dose insensitivity demonstrate the predictable irrationality of human cognition described in the amusebouche. An assumption of research in behavioral economics is that people sometimes act in a way that is harmful to themselves, for instance, consuming too many sugarsweetened beverages. It is not possible to ban any and all foods or drinks that are harmful, but is it possible to apply these research findings on cognition, heuristics, and food choice to positively impact consumption? One now-common solution is taxing junk food and sugar-sweetened beverages and subsidizing (decreasing the cost) of healthy options like produce. The premise is that a “sin tax,” like those on sugar-sweetened

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beverages, helps consumers to maximize their welfare because they make poor consumption decisions (e.g., too much soda) less likely. Mexico implemented a tax of one peso per liter on all (nonalcoholic) beverages with added sugar in January of 2014, which successfully decreased purchase of these beverages by 8.2% over 2 years (Colchero et al., 2017). Additional experimental research explored a grocery purchasing tax, finding that taxation of high-calorie-for-nutrient foods reduced their intake and overall energy intake of consumers, but subsidies for low-calorie-for-nutrient foods did not effectively decrease energy intake among consumers (Epstein et al., 2010). These policies remain controversial and unpopular to some, but it is difficult to contest the success of the significant reduction in sugar-sweetened beverage purchases in cities like Philadelphia (38% decrease as reported by Roberto, Lawman & LeVasseur, 2019). Economic approaches such as a sin tax must be framed properly to capitalize on these tendencies in human cognition because humans do not rationally weigh all information when making choices (Tversky & Kahneman, 1981). Another approach is to limit contextual factors, some covered in the present chapter: portion sizes, microvariety, labels, aggressive marketing, and sales promotions (like, buy one get one free) all increase consumption through automatic, heuristic reasoning (Cohen & Babey, 2012). In an environment designed to promote consumption, heuristics can lead to poor food choices at restaurants and grocery stores. Even when cognizant of the subtle contextual influences, deliberate efforts to resist these cues are often unsuccessful due to the dual nature of human information processing, further explored in Course 3 of the present chapter. By drawing awareness to assumptions made around food and eating, such as in the case of breakfast described next, a person can create new automatic processes to mitigate overconsumption.

Morsel: The Most Important Meal of the Day? Perhaps you have a routine for breakfast, selecting a trusty option to fuel your day. For others, breakfast may be reserved for special occasions, a leisurely day off work or holiday. The transformational powers of breakfast to preserve physical and psychological well-being are touted in the popular media and scientific literature, asserting that skipping the morning meal contributes to obesity (for review of observational studies, see Timlin & Pereira, 2007) and increases health risks like type 2 diabetes (in men, Mekary et al., 2012; and women, Mekary et al., 2013). Apparently, breakfast is essential. Or is it? During this review of the rise of breakfast, please consider two cautions. First, there is a developmental distinction between children and adults, and school breakfast programs make vital contributions to combating hunger and food insecurity, and thus boost school performance (Pollitt, 1995). A balanced breakfast to fuel the day

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is essential for the development of kids, teens, and young adults and is associated with short-term improvements in attendance and psychosocial and academic functioning (Murphy et al., 1998). In the United States, the School Breakfast Program (established in 1966) was reformed into the Healthy, Hunger-Free Kids Act (implemented in 2012) for better meal quality in part due to the documented benefits of breakfast for schoolchildren (e.g., Rampersaud et al., 2005). Second, cultural norms may dictate breakfast patterns, and individual needs vary greatly, so “one-size-fits-all” advice for breakfast is both unrealistic and unethical. The breakfast imperative is a recent phenomenon; breakfast was not normalized in the Western world until the Industrial Revolution (Garber, 2016), as norms to avoid gluttony warned against eating too early in the day. Breakfast cereal was developed in the 19th century by religious men who believed bland foods could prevent moral weaknesses (such as masturbation according to Kellogg, guru of the cornflake; Mudry, 2018). Given the limitations of industry-funded research (Chapter 2), it is of no surprise that some early work supporting the link between breakfast and health was laden with conflicts of interest due to industry backing (e.g., Cho et al., 2003) and relied on correlational (not causal) evidence. Methodological limitations are clear when inspecting the hype around breakfast and school performance; while proper access to food is a fundamental need for all, the correlational evidence ignores confounding factors such as overall health, nutrition, parental involvement, and socioeconomic status (Adolphus, Lawton, & Dye, 2013). Evidence contradicting the breakfast imperative was ignored or dismissed until recently. A meta-analysis by Sievert and colleagues (2019) identifies key points of the breakfast imperative: international recommendations consistently encourage breakfast, recommendations are based on observational studies plagued by limitations such as the confound of socioeconomic status, and breakfast contributes to total daily energy intake, thus influencing weight and health. The final point is crucial— total daily energy intake is a factor in obesity. Contrary to popular opinion, skipping breakfast (for adults) does not unequivocally lead to increased hunger through the day or to weight gain. To fully evaluate breakfast, consider the shifting landscape of breakfast in the developed world where traditional food items have been replaced with those of convenience (Spence, 2017). The quality of the breakfast certainly matters for schoolchildren (Mahoney et al., 2005), but the effects are not clear in adults (Zilberter & Zilberter, 2013). A breakfast of foods high in calories with added sugar but low in fiber and nutritional value is problematic, and some evidence shows that highfat breakfast subsequently increases lunch intake as compared to a low-fat meal of equal energy content (Clegg & Shafat, 2010). Reconsideration of a standard breakfast imperative is based partly on tests of preloading—an experimental

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manipulation for participants to eat something in advance of an experiment where consumption of a target food is measured under the guise of a taste test. The participants consume a preliminary heap of calories, commonly a milkshake. Strict homeostatic predictions lead to the inaccurate assumption that calories, fats, and sugars from the milkshake would result in decreased intake during the meal. However, this is not the case, as drinking a milkshake before a meal does not necessarily mean a smaller meal to compensate. Any effects on appetite conclude in 2 hours (de Graaf & Hulshof, 1996), and participants overconsume with preload regardless of their body weights. Subsequent research suggests that the effects of food consumption on satiety are mediated by psychological mindset; the perceived nutritional content of the preload impacts physiological satiety response via the neuropeptide ghrelin (Crum et al., 2011). Beliefs about the composition of foods consumed have powerful influences on satiety and later consumption. To bring this back to breakfast: a universal recommendation is not evidencebased. First, breakfast has utility for the physical and mental development and performance of children and adolescents. Second, the transformational powers of breakfast for adults, particularly for weight loss, are doubtful at best and likely biased through conflicts of interest. Contemporary breakfast foods are less likely to be balanced than more traditional morning meals. Remember those compensatory health beliefs? Common claims around breakfast as healthy, or even necessary, may lead to a discounting of those morning calories and greater intake throughout the day. Attending to the nutritional content of foods consumed allows for more thoughtful food choices at all meals.

Course 2: The Hungry Hippocampus—Memory and Eating Cognitive processes rely on experiences and knowledge, and thus memory, as the good and bad events of our past guide our present actions and judgments. People remember the appearance of delicious and repulsive foods, the location of filling meals, and the skills needed to gather and prepare foods. Previous discussion of foraging strategies, the hippocampus, and odor-evoked memories highlight the essential role of memory in the psychology of eating. Memory and motivation guide goal-directed actions for survival through the evaluations of stimuli, like determining whether a food is safe and edible. Remember from earlier chapters the orbitofrontal cortex (OFC) integrates sensory cues, experiences, and higher cognitive processes (such as that value to eat healthy mentioned before), to weigh the risks and benefits in food decisions. The brain network for eating also includes the

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hippocampus (Chapter 4), which receives appetite signals such as leptin to modulate foodrelated memory processing (Kanoski et al., 2001). Research on information processing suggests that connections between the PFC (specifically the orbitofrontal region) and hippocampus synthesize motivational states and spatial information to provide a cognitive map of the path required to procure food (Wikenheiser & Schoenbaum, 2016). The OFC is a secondary gustatory cortex, encoding the reward value of tastes and odors (Rolls, 2004) and collaborating with the hippocampus for goal-directed decision making (Wikenheiser & Schoenbaum). The complicated interaction between higher mental processes, reward, and contextual cues demonstrates the sophistication of cognitive processes at work before, during, and after food consumption. Food memory is tied to appetite and satiety. The memory of intake outweighs physiological sensations of hunger and fullness (for review, see Higgs, 2005). For example, disruption of memory by anterograde amnesia interferes with satiety such that patients with amnesia will eat a second full meal (or even a third!) only 30 minutes after completing the first meal (Rozin et al., 1998). Interestingly, despite their inability to remember eating a meal or particular food, patients with amnesia still demonstrate sensory-specific satiety—waned subjective pleasantness for the taste, smell, and appearance of foods when and shortly after consuming them (Hetherington et al., 2006; Higgs et al., 2008; Stang, 1975). In classic studies, the prolific researcher Barbara Rolls and colleagues (1981) demonstrated complementary effects to sensory-specific satiety of increased intake when a variety of food options are available. Both tendencies— to eat more in the presence of multiple foods and satiate to single foods—serve to promote a diversified diet. The fact that people with memory loss still experience sensory-specific satiety and overeating in the face of various foods is evidence these tendencies are controlled implicitly and are fundamental to consumption. These examples demonstrate two components of memory. First, the working memory system is a limited capacity processing center that integrates one’s present thoughts and ideas. As attention to food cues is crucial for survival, it is logical that food stimuli hold special significance in working memory. Thinking about food draws even more attention to food cues (for review, see Higgs, 2016), attention to a meal improves memory for that meal and decreases later snack intake (Higgs & Donohoe, 2011), and working memory capacity is associated with successful dieting (Whitelock et al., 2018). Cues for tasty treats like cake and donuts induce craving and deplete working memory capacity (Meule et al., 2012), similar to the way advertisements hijack our best intentions. Second, episodic memory (long-term memory for specific events) is essential given the evidence from amnesic patients and the potential for remembered experiences to impact food liking (Higgs, 2016), as thinking about earlier meals or future meals, as compared to other activities, can suppress food intake (Vartanian et al., 2016). Consider the purposeful and thoughtful enjoyment of a meal—cultural norms for slow eating encourages satiety and enjoyment of food in the moment (Rozin, 2005) and focus on the current meal promotes carryover satiety due to the lingering memory of the food (Figure 6.2; Higgs & Donohoe, 2011).

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Figure 6.2  Memory diagram. Diagram representation of memory systems modeled from cognitive explanations. Created by Leighann Chaffee.

Chew on This: Burst Your Bubble Familiarity with processes of memory helps to review the assertion that chewing gum benefits cognitive performance. In response to claims that chewing gum promotes relaxation (Hollingworth, 1939), contemporary researchers further interrogated the potential benefits of chewing gum for cognitive and affective processes. The findings from controlled laboratory studies show that chewing gum selectively improves working memory (e.g., Wilkinson, Scholey, & Wesnes, 2002), due possible to context-dependent effects because memory is enhanced when participants chew gum both while memorizing a list of words and when later asked to recall the words (Baker et al., 2004). Some subsequent research supports this effect (Hirano et al., 2008), but other studies fail to find the facilitative effect of gum chewing for recall (e.g., Johnson & Miles, 2007) even when using highly similar procedures. One explanation for the contradictory findings is the effects are short-lived—and require that gum chewing begins before the cognitive task—with the assumption that mastication enhances arousal and attention but is reduced to certain domains

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(Onyper et al., 2011). Thus, the potential for chewing gum to significantly improve real-life outcomes (like scores on an exam) is limited, and other factors like sleep, health, and study strategies have stronger impacts on performance outcomes.

Memory is remarkable, yet it is imperfect and vulnerable to personal biases, errors, and omissions. Even the suggestion of bad experiences (a false memory) with certain foods decreases preferences for and consumption of them (Bernstein & Loftus, 2009). Memory is fragile both during initial acquisition and encoding (storing of the information) and when retrieving the memory to work with the information (Loftus, 1979). According to the renowned memory researcher Elizabeth Loftus (1993), memory is a constructive and “reconstructive” process as information may be integrated when originally encountered or later when the memory is recalled. Memory is more akin to a painting with touches added each time it is observed, rather than a photographic image that is fixed once taken. The malleability of human memory requires researchers to use savvy methods when measuring consumption since people cannot be trusted to fully recognize and remember eating and drinking (Figure 6.2).

Nutrition Research and Memory The use of a mobile app to track nutrition or exercise has surged in popularity in recent years (Smith, 2015). The process of logging food and exercise is similar to self-report data collection methods commonly employed in social science research (see Chapter 2). Practical considerations limit direct observation of behavior; after all, who would behave naturally if a food researcher followed their every move from rise to rest, recording every interaction with food? As it is not feasible to directly measure these constructs, researchers frequently rely on participants to report data via questionnaires, surveys, and interviews. Self-report methods are used in nutrition research, for instance, the National Health and Nutrition Examination Survey (NHANES) of the United States, other nation-specific efforts, plus international surveys like those administered by the World Health Organization. For the NHANES, dietary behavior is inquired during an in-home interview, participants complete a 24-hour dietary recall during a physical examination, and a food-frequency questionnaire (FFQ) is mailed to participants for follow-up (National Center for Health Statistics, 2010). The FFQ, a full 24 pages of multiple-choice questions, is a common method for collecting dietary intake data. Participants report how often they ate certain foods during a specified time period (days or months) based on a finite list, and food databases are used to calculate numeric energy (calorie) values from the self-reported foods eaten. In most instances, health surveys are integrated in the iteration of national nutritional recommendations. Memory-based dietary assessment methods have faced extensive criticism. In 1987, Basiotis and colleagues determined that 31 days of food intake recording was required for

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accurate estimates of energy intake. The most condemning evidence against the validity of memory-based dietary assessments compares self-reported data with a sophisticated technique to compute total energy intake, and the ubiquity of underreporting is evident (for review, see Hill & Davies, 2001). Archer and colleagues (2013) evaluated four decades of NHANES data and determined that most participants (67.3% of women and 58.7% of men) reported eating and drinking that was not physiologically sufficient to sustain life. Paradoxically, while population health has declined due to the consequences of obesity, self-reported consumption of fatty and carbohydrate-rich foods has decreased (Heitmann, Lissner, & Osler, 2000). Though the accuracy of self-report data varies, with average rates of energy underreporting of 28% with FFQ and 15% with 24-hour recall (Freedman et al., 2014), pervasive validity problems beg the question of why people inaccurately describe eating and drinking. Even if the research participant has no bad intentions, the potential for errors arises at several points. Imagine yourself as a participant, recording every food you ate, every snack, and each beverage, including the ingredients, portions (weight or volume), condiments, and seasonings, for the past day or even 7 days. A participant logging their foods throughout the day may commit an error due to omission or inaccurate portion size. However, many people enter their intake sporadically, even logging several days at once—now, dynamic constructive and reconstructive processes of memory influence the accuracy of self-report (Schacter, Norman, & Koustaal, 1998). Social desirability, or the tendency to present oneself in a favorable manner (Hebert et al., 1995), biases responses as well. Who is going to tell the nutrition researcher they ate an entire pizza by themselves? No one, that’s who. Traditional health and nutrition research, in the absence of psychology, inaccurately assumes that behaviors are logical and rational. Applying principles of cognitive psychology, illustrating the errors in judgment and inherent irrationality of human thinking is crucial for understanding food decision making and health.

Course 3: On the Back Burner—Parallel Processing Thus far, the review of thought processes, perception, and memory paints a rather harsh picture of human cognition, prone to miscalculation and inaccuracy. It would be ideal if thinking was deliberate and rational, yet these flaws emphasize the parallel automatic processes of cognition. Researchers of human cognition describe at least two modes of thinking, termed the dual-process model (Ferreira et al., 2006; Kahneman, 2011). The fast, Type 1 thinking system is efficient but prone to errors and is balanced by a slow and purposeful, and thus more accurate, mode of thinking (Type 2). Since Type 2 thinking is deliberate, it requires more mental energy and consequently is able to focus attention and less likely to be used under conditions of time pressure, divided attention, and cognitive load (Ferreira et al., 2006). Interestingly, cognitive processes like memory can influence behavior through the automatic, fast system (Higgs, 2016). Think back to those cookies

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that jumped into the shopping basket—in this example, the food choice relies more on automatic Type 1 thinking, bypassing the rational (Type 2) thinking system. Many cognitive processes are characterized by this dual structure. Memories that are consciously known and can be described, such as the episodic memory of yesterday’s breakfast, are called explicit memories. Additional memory processes are implicit in nature; they are memories that are unconsciously encoded and outside of conscious awareness, yet still influence cognitive processes (Reisberg, 2019). Examples of implicit memory include how to flip a pancake in the air without a spatula (procedural memory), preference for a specific restaurant chain based on experience (priming due to advertisements), and conditioned taste aversion (classical conditioning). The validity of the (often-inaccurate) memory-based dietary measures is compromised in part by reliance on solely explicit memory processes. Researchers may also be interested in attitudes toward particular foods, such as preferences for organic foods or positive thoughts about junk food. To a psychologist, an attitude encompasses evaluations of and feelings about a specific thing such as a food. Attitudes exist on conscious (explicit) as well as automatic (implicit) levels. Self-report measures of conscious attitudes only predict behavior when cognitive resources and working memory capacity are adequate to act in a thoughtful, deliberate manner (Friese, Hofman, & Wänke, 2008). When might implicit and self-reported attitudes be incongruent? Contrast Author LC’s nutrition knowledge (quite advanced) to LC’s actual eating behavior (typically overindulgent)—automatic attitudes and evaluations of yummy food are a better predictor than deliberate, Type 2 thinking. Thanks to some clever researchers, there exists tests for revealing implicit evaluations and thinking. Automatic attitudes are recorded through indirect measures, such as the Implicit Association Test (IAT; Greenwald, McGhee, & Schwartz, 1998), which quantifies the speed of categorization of stimuli as an insight to the automatic positive and negative associations. The IAT and its variations are used to study food preferences and consumer behavior and serve as a predictor of behavior beyond self-reported attitudes (Maison, Greenwald, & Bruin, 2004). When explicit attitudes for food products are incongruent with implicit preferences, participants select the implicitly preferred food brand when choices are made under time pressure (Friese, Hofman, & Wänke, 2008). Evidence supporting the role of implicit attitudes in eating is quite strong though nuanced by features of the participant: ●

●

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Hunger status: Participants rate food more positively when hungry, and the effect is greater toward high-fat foods than low-calorie foods (Lozano, Crites, & Aikman, 1999). Body composition: Female participants with a BMI over 30 rate high-calorie sweet foods (like chocolate cake) significantly less positively than participants with a lower BMI, and high-calorie nonsweet foods (pizza) significantly more positively (Czyzweska & Graham, 2008). Dietary restraint: Participants who are watching what they eat show stronger implicit liking for high-calorie foods than participants who score low on a dietary restraint scale (Houben, Roefs, & Jansen, 2010).

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Working memory capacity: Low working memory capacity undermines the consistency between health attitudes and health behaviors (for review, see Dohle, Diel, & Hofmann, 2018).

Despite these mixed findings, implicit attitudes are an essential consideration in comprehending the psychology of eating and contemporary researchers consider implicit processes when studying food choice.

Chew on This: Targeting Implicit Attitudes Marketing researchers exploit priming, the activation of associations in memory, to enhance positive evaluations and brand identification to encourage consumer spending. But implicit attitudes can be harnessed to promote healthier choices as well, as suggested by Marteau and colleagues (2012). A simple rehearsal of the enjoyable aspects of a nutritious meal increases remembered enjoyment and more subsequent consumption of that food (Robinson, Blissett, & Higgs, 2012). The effect of rehearsal capitalizes on the self-reference effect, a term for enhanced recollection of information that is relevant to one’s life. The power of self-referencing is clear to any student: when the material applies to one’s own life, it is easier to remember. Repeatedly describing previous experiences while engaging in preferred eating capitalizes on the self-referencing effect; by aligning our goals with desired practices, the actions are more relevant and memorable, and positive implicit evaluations of these behaviors are augmented. This potential is corroborated by evidence from neuroscience—targeting bottom-up, implicit processes through response-inhibition training programs shows promise to decrease intake and weight in individuals who are overweight (Stice et al., 2016). These interventions are quite different from typical weight loss treatments, as a computerized training program is used to practice the positive associations with nutritious foods (Hollands & Marteau, 2016), and making links between foods and the self through a brief associative self-referencing task enhances implicit preferences toward healthy foods (Dimartini et al., 2019). Similarly, evaluative conditioning, described in Chapter 7, demonstrates the promise of this approach.

Respecting the complexity of human cognition helps account for our shortcomings and potential for irrationality. Attention to principles of human cognition is particularly relevant when evaluating evidence to implement policy such as nutrition recommendations, product labels, or soda taxes, and much of the evidence relies on participant self-report. When new studies are encountered, remember to: ●

Evaluate each study critically, including the methods used, the limitations, and potential for bias

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● ●

Incorporate knowledge of cognition and dual processes Consider the fallibility of memory plus predictable irrationality in analysis of the evidence

Dessert: Angel Food—The Health Halo A halo effect occurs when an individual’s evaluation of an object or person is biased by only one attribute of that entity (Miller, 1970, or Nisbett & Wilson, 1977). In other words, one good quality emits a positive light that shines on the entire person, object, or even a food. The health halo effect is a specific avenue for the magical thinking called contagion described earlier. Where contagion implies that objects (or ingredients) in contact with each other can exert influence, here the halo from a single attribute results in a positive evaluation of the whole. The health halo effect can arise from claims on food packaging, swaying the consumer’s perceptions of those foods. Food packaging has the power to impact the consumer experience: when product images are attractive (even inflated), ratings of the food or drink tend to be more positive (Mizutani et al., 2010). Desirable labels of natural, low fat, and organic bias attitudes toward the food (Andrews, Netemeyer, & Burton, 1998; Kozup, Creyer & Burton, 2003; Chandon & Wansink, 2007). Think back to the scenario at the beginning of the chapter where you are hungry and looking to buy a snack: does a small statement on a package influence your perception of that food? Errors in cognition, such as the shortcut to categorize foods as simply good or bad to ease navigation of nutrition information, play a role in the health halo. Consumers generalize from a specific label claim to a general evaluation of the product as “healthy” (Andrews, Netemeyer, & Burton, 1998). Claims like “heart healthy” on a menu and food package enhance attitudes toward the product and purchase intentions (Kozup, Creyer, & Burton, 2003), and low-fat labels lead consumers to underestimate the calorie content of the food item (Ebneter, Latner, & Nigg, 2013). When the label makes a health claim, like low calories, it can have the unintended effect of increasing consumption (McCann et al., 2013). In fact, the front-of-package claim is given greater weight than the nutrition panel (Roe, Levy & Derby, 1999). An “organic” label also produces a halo; as an example, the organic designation on wine increases hedonic ratings, improves taste, and boosts perceived healthfulness (Apaoloza et al., 2017). This halo can extend from other attributes or associations, as seen when consumers with favorable attitudes toward a company known for social responsibility tend to underestimate the calories in their food products and thus consume more (Peloza, Ye, & Montford, 2015). Unfortunately, the health halo also operates in children: kids exposed to advertisements with healthy messages for nutrient-poor foods perceive those foods as healthier (Harris et al., 2018), yet the messages do not positively influence their general attitudes toward health and nutrition. The health halo demonstrates both the power and the liability of cognitive processes. Speedy mental shortcuts, like categorization and implicit attitudes, are less reliable than rational, Type 2 thinking. To overcome these challenges, consider slowing down and engaging in more thoughtful interactions with our complex modern food environment.

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Dining Review Key Elements

Recommended Reviews

Whet your appetite

What is the cognitive explanation for our propensity to fall prey to label claims on food products?

The amuse-bouche

Identify the concepts and terms from behavioral economics within this chapter and describe an application.

Course 1: Cognition

Find examples of categorical thinking, heuristics, and unit bias in your own life.

Morsel: Microvariety

Is microvariety a global phenomenon? Find cross-cultural evidence to support (or refute) whether these influences extend around the globe.

Morsel: Breakfast

Find popular news articles both in support and against the health benefits of breakfast. Evaluate the quality of the evidence provided.

Course 2: Memory

Diagram the memory system, and then add the gustatory and olfactory inputs you learned about in the previous chapter.

Course 3: Parallel processing

Identify an attitude you hold about food—is this explicit or implicit? Describe one way you might uncover additional implicit attitudes or preferences.

Dessert: The health halo

Are any regulations in place to limit or monitor the health claims made on foods? How are these enforced?

Gochisousama Thanks to the chef! Recommended reading: ●

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A text on the principles of behavioral economics: Kahneman, D. (2011). Thinking, Fast and Slow. New York: Farrar, Straus, & Giroux. A Hidden Brain podcast on the empathy gap: https://www.npr.org/2019/11/13/778933239/ the-ventilator-life-death-and-the-choices-we-make-at-the-end.

Glossary Attitude:

our evaluations for something, like a food (or a thing, person, or group), with affective, behavioral, and cognitive components

Categorical thinking:

the cognitive shortcut to reduce a continuum of

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possibilities to discrete categories, for instance, creating the false dichotomy of healthy and unhealthy Cognition:

mental processes, including thinking, language, memory, judgment, decision-making, and problem-solving

Compensatory health beliefs: the inaccurate belief or expectation that engaging in healthy behaviors can compensate for unhealthy actions Contagion:

for our purposes, the idea that food can be perceived as contaminated by “unhealthy” ingredients or bettered by “healthy” ingredients

Decision making:

in psychology, the cognitive process of selecting a choice (such as a course of action) among several possibilities

Dose insensitivity:

the faulty belief regarding the harmfulness, or healthfulness of substances, regardless of the amount consumed

Executive control:

the mechanism that allows our mind to prioritize our goals through control of thought processes and operations, via the prefrontal cortex

Halo effects:

occurs when an individual’s evaluation of an object or person is biased by one positive attribute of that individual; extends on the entire person, object, or even a food

Heuristic:

a mental shortcut that simplifies judgment or decisionmaking by reducing complex cognitive tasks like calculating probability to simpler mental operations

Judgment:

in psychology, process by which evidence, provided by our experiences, is incorporated in order to draw conclusions

Sensory specific satiety:

during and after consumption of a food, the subjective pleasantness of the taste, smell, and appearance of that food decreases relative to other foods

Unit bias:

the perception that a single entity, such as a package of chips, is the appropriate amount for consumption

Chapter 7 L’appétit vient en mangeant: Learning Processes in Consumption Whet Your Appetite: Acquired Tastes Imagine how you take your coffee, your selection of salad greens, or cheeses from the party tray. What determines whether you will return to a new restaurant for novel foods you tried for the first time? What foods or drinks do you avoid and why? Why is food from your childhood so tasty? Through questions like these, this chapter examines the role of acquired tastes in eating habits.

Menu Amuse-Bouche: Mere Exposure Course 1: Classical Conditioning Classical Conditioning Flavor-Flavor Associations Flavor-Nutrient Associations Conditioned Taste Aversion Applications of Conditioned Responses Course 2: Operant Conditioning Reinforcing and Punishing Effects of Eating Food Food as Reinforcers for Other (Nonconsumption) Behavior Nonfood Reinforcers and Punishers for Consumption Course 3: Observational Learning Attention Retention and Motoric Reproduction Motivation Combined Effects and Individual Differences

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Dessert: Collateral Consumption Dining Review Gochisousama Glossary

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Amuse-Bouche: Mere Exposure Upon first encounter with new foods, they are eaten tentatively and in smaller amounts as part of a protective neophobia previously discussed (Chapter 3). During consumption, we attend to the odor, taste, and source of the substance. Following consumption, we remain vigilant—even if subconsciously—for body cues indicating the safety and nutrients of what we ingested. If all goes well, this first “safe” experience makes it more likely we will consume the food or drink the next time it is available (Kalat & Rozin, 1973). Here described is one of the simplest examples of how experience affects consumption: the mere exposure effect. Mere exposure reduces uncertainty, playing on our natural tendencies to prefer and approach familiar stimuli (Lee, 2001). Beyond familiarity, repeated exposures to stimuli, such as the smells, textures, and tastes of substances, also produce simple forms of learning called habituation and sensitization. These learning processes are marked by changes in reflexive reactions to stimuli like food smells or tastes. An example might be the startle reaction many people experience upon a first encounter with hot pepper or spicy food. Over time, with repeated exposures to a food or drink, reactions to the stimuli change in intensity. Think back to your first encounter with new food, especially one different from your norms. Maybe it was fondue or your first foray into raw seafood. In a first exposure, we react to the sight or presentation of the food; it likely garners most of our attention as its appearance is deciphered. Physiological and emotional reactions take place in this first encounter, and—whether the experience is positive or negative—these reactions change in intensity, even if slightly, upon your second experience with the food. Increased reactions (e.g., exaggerated disgust, excitement) with exposures represent sensitization, and decreased reactions (e.g., less visual inspection/fascination, fear) represent habituation. Of the two processes, habituation is more common, and it makes sense that we pay less attention and react less to foods we have experienced repeatedly (see Epstein et al., 2009 for a review). It would be wasteful to exert energy toward foods and drinks that are a regular part of our lives or food repertoire. During individual meals, too, habituation to gustatory stimuli occurs as additional bites are taken. This waning responsiveness to the food and drinks (called sensory-specific satiety, Chapter 6) contributes to our decision to stop eating. These tidbits of learning via exposure illustrate the power of experience in consumption. The simple learning phenomena just described illustrate two major assumptions

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regarding learning: (1) behavior is amenable to events surrounding it and (2) all behavior serves a purpose. When organisms are responsive to changes in their environment (i.e., the world around them), they have learned. These environmental impacts on behavior hereafter are addressed in three general areas of learning: classical conditioning, operant conditioning, and observational learning.

Course 1: Classical Conditioning Classical Conditioning Ivan Pavlov generally is credited with demonstrating and disseminating classical conditioning. Pavlov, a Russian physiologist, was interested in the role of saliva in digestion. In testing the impact of meat powder varying in dryness, Pavlov noticed his dog subjects responded before food was physically present, salivating to the sound of approaching footsteps and other cues of upcoming food. Pavlov shifted his focus to studying how dogs respond to stimuli that predict food rather than responses to the food per se. He reported on “psychic secretions,” known today as conditioned responses (CR) or conditional responses. These CRs are elicited by cues or signals, conditioned stimuli (CS), for upcoming events, like food presentations. Likely unbeknownst to Pavlov, Alois Kreidl (1896) of Austria already had published a study of conditioned food procurement in fish (Logan, 2002). Kreidl was studying the hearing abilities of fish, aiming to demystify colloquial and prior research claims that fish would come for food when called by a bell. He determined that fish would arrive for food at the sight of a keeper and from vibrations of the footsteps, effectively demonstrating conditioned responding to visual and cutaneous stimuli that predict food. These two pioneers illustrated that signals for food, CSs, trigger digestive actions (salivation) and motor actions (orienting, moving to food locations), which are two forms of conditioned responding that prepare us for consumption.

Chew on This: You Rang? Though a parallel between Pavlov’s laboratory bell and a dinner bell would be charming in this chapter about conditioned eating, historians (Todes, 2014) now understand Pavlov did not use a bell to signal upcoming food in his lab tests. Likely a mistaken translation, the bell has become the “classic” way (pun intended) people describe Pavlov’s Nobel Prize winning research. Experts argue further that a bell would have been too uncontrolled for Pavlov, as its sound and rhythm would be more difficult to keep consistent across trials compared to that of the tuning forks and metronomes Pavlov used.

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CSs occur in various modes, from auditory, visual, and tactile, to more abstract forms like the passage of time. We are well equipped to respond based on temporal dimensions of cues, as you may notice with your morning stomach pangs or lack thereof in case you usually skip breakfast. Nonhuman animals respond similarly to such cues based on circadian rhythm or environmental signals of time, as when marmosets make more visits and stay longer in locations based on previously experienced food schedules (Monclaro et al., 2014) or when rats show differential food expectations based on time since their last meal (Benoit, Davis, & Davidson, 2010). When temporal cues are combined with other stimuli as predictors of food, time controls food-oriented behavior better than the other stimuli, like auditory signals (Kirkpatrick & Church, 2000). If you eat meals at roughly the same time each day, your body anticipates food before it arrives with lesser influence by people, sounds, and so on. These learned cues for eating, from external signals to peripheral feedback signals within the body, can be more powerful than homeostatic regulation of intake. Thus, signals for food can lead to consumption behaviors in the absence of hunger or physiological need. CRs also take on many structural forms, but they share universal function of preparing the organism for unconditioned stimuli (e.g., food, drink) and their corresponding unconditioned responses (e.g., salivation). In the context of consumption, CRs improve food procurement and digestion. Examples include movement towards food locations, increased attention towards food cues, and physiological preparation (e.g., insulin production). Some CRs, such as production of ghrelin, occur as much as 2 hours prior to food intake (Drazen et al., 2006), and stronger CRs are generated by more valuable foods and drinks. CRs that prepare the body for consumption may be the basis of food cravings, making food withdrawal effects aversive in ways similar to what is experienced in drug withdrawal (Havermans, 2013). One observed preparatory CR that might be rather enjoyable (as opposed to aversive) is the production of endorphins when cues (e.g., smell, sight, time) signal that you will be eating something containing chili pepper (Rozin & Schiller, 1980). CRs can explain why diets based on meal timing and portion size, such as fasting for long periods or eating small meals through the day, work initially with diminishing impact (or efficacy) over time. The body adapts to the timing of food intake and slows metabolism in the case of fasting or increases metabolism in the case of anticipated loading. A key to making calorie restriction effective for weight loss would be to “trick” the body into expecting calories and then preventing consumption of the calories. Such a strategy, called cue exposure with response prevention (CERP), has been demonstrated successfully in controlled studies for alcohol, cigarette, and food cues (e.g., Havermans et al., 2007). Frankort, Siep, and Roefs (2013) used CERP to test chocolate cravings, finding increased activity in areas of the brain known to be involved with reward, such as amygdala, somatosensory cortex, and posterior cingulate cortex, in response to the presence of chocolate and—lesser so—pictures of chocolate.

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Self-reported cravings coincided with neural activity and neither measure decreased over time when no chocolate was (allowed to be) eaten. This means that cravings from food cues persist for some time. If CERP is used to curb conditioned cravings (one type of CR), it will require many trials of repeated cue exposure as well as trials of long durations to ensure cravings are not sustained (from something like a person’s postsession snacking/intake). The main point thus far is that we adapt readily to respond to stimuli that predict (subsequent) availability of foods and drinks and, therefore, consumption. Besides these anticipatory and preparatory roles, classical conditioning also affects selection and enjoyment of foods. Capaldi (2004) and Touzani, Bodnar, and Sclafani (2010) describe these appetitive effects of classical conditioning in two categories, flavor-flavor associations and flavor-nutrient associations.

Flavor-Flavor Associations Flavor-flavor associations can have enduring impacts on food approach and food avoidance. When two flavors are paired closely together, preference for the unknown or neutral flavor will shift according to existing preferences for the flavor presented with it. Product manufacturers and chefs know this well; add sugars and tasty fats to most any dish for crowd-pleasing effects. In laboratory settings, associations are created by pairing particular flavors, such as wintergreen or cinnamon, with different concentrations of saccharin (a preferred flavor). In such tests, rats prefer whichever flavor is paired with a higher concentration of saccharin (Holman, 1975) and the associations can be learned in only one trial as when tested with Kool-Aid flavors sweetened with fructose (Ackroff et al., 2009). Flavor-flavor effects also occur in humans using various flavors like tea that are presented in sweetened or unsweetened forms (Zellner et al., 1983). These isolated demonstrations are microcosms of everyday acquired preferences for bitter flavors, like beer, coffee, wine, and cheese, and sour flavors, like sour candies and lemonade, due to their pairings with sugar and fat (Figure 7.1). If you are thinking flavor pairings would be a good strategy for getting kids (or yourself?) to eat broccoli, you are correct. But note that the paired flavors must be consumed proximally; for example, broccoli can be topped with sugar or fatty cheese or mixed with a preferred food. By comparison, successively spaced presentations of a new (especially bitter or sour) flavor prior to consumption of a preferred taste leads to decreased preference for the first/new flavor and increased preference for the second, already-preferred flavor. This phenomenon, observed when rats differentially eat potatoes and rice based on which food was eaten prior to sucrose (Capaldi et al., 1987), is called the dessert effect. As discussed in Chapter 8, these undesired changes in liking also occur when children eat dessert after their vegetables.

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Figure 7.1  Diagram of flavor-flavor and flavor-nutrient associations. Created by Stephanie da Silva.

Flavor-Nutrient Associations Flavor-nutrient associations involve learned relations between experienced flavors and post-ingestive events (see Rozin & Zellner, 1985). The nutrient density, or energy density, of the food is not detected until food reaches the gut but nevertheless influences flavor preferences. When rats are given two different flavors of saccharin, a calorie-free/nutrientfree substance, prior to a nutrient-loaded chow or prior to nonnutrients, rats preferred the flavor that preceded chow presentations. Conversely, when flavors are paired with nonnutrients (i.e., time periods of nutrient deprivation), rats avoid them (Boakes, Colagiuri, & Mahon, 2010). Flavor-nutrient associations might be better termed “flavorcalorie” associations to avoid the implication that organisms seek vitamins and minerals in their foods. In reality, it is satiation and calories that drive flavor-nutrient associations rather than well-balanced nutrient profiles. Flavor-nutrient associations, though necessarily delayed, are so strong that they can override flavor-flavor associations. Mehiel and Bolles (1988), in a series of experiments, reported two key findings. ●

●

When rats were provided pairings of an unpreferred flavor followed by calorie solutions (i.e., containing sucrose) or a preferred flavor followed by noncalorie solutions (i.e., containing saccharin), flavor preferences shifted so that the two flavors were equally valued. Rats developed preferences for solutions containing sucrose (a calorie-laden substance) compared to solutions containing saccharin (a calorie-free substance) when those solutions contained flavors that initially were liked similarly.

The finding that rats will prefer a particular flavor liquid if associated with intragastric infusions of nutrients further illustrates the robustness of flavor-nutrient effects (Sclefani, 1990).

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Flavor-flavor and flavor-nutrient associations involve reward-based processing in the brain. Rats given a dopamine receptor antagonist that decreases active impact of dopamine in synapses will not acquire typical preferences from flavor-flavor or flavornutrient associations (Touzani, Bodnar, & Sclefani, 2010). Comparatively, actions of the orbitofrontal cortex, amygdala, and opioid receptors do not affect flavor associations (Scarlet et al., 2012; Touzani et al.). So, how is dopamine involved in flavor associations? Dopamine is triggered by the gastrointestinal tract based on caloric load (see de Araujo et al., 2012), which allows dopamine to play a central role in modulating calorie intake and need. Once the rewarding effects of sweetened flavors or dense nutrients are eliminated, the acquired flavor preferences also go away (Touzani et al.). Take a moment to consider how flavor-nutrient associations play out in our everyday lives. Basic processes of flavor associations are the same in humans and nonhumans, though human research is complicated by lack of controls for hunger/satiety during sessions, various learning and genetic histories, and small differences in experimental design (Yeomans, 2012). One explanation of the dessert effect is that the dense nutrients experienced by the intestines after the meal, likely from dopamine and perhaps CCK (Mehiel & Bolles, 1988), are attributed to flavors of the most recently consumed item, the dessert. Evidence in rats supports this idea with one caveat. The flavors associated with post-ingestive nutrients depend on whether the nutrients are high in sugar or high in fat. Rats prefer flavors they consume near the end of a meal if fat is infused intragastrically, but prefer flavors they consume early in the meal if sugar is infused intragastrically because the feedback mechanisms from consumption of sugars and fats occur at different speeds, where the sugar is detected more quickly (Myers & Sclafani, 2001a, 2001b; Myers, 2013). So, imagine a child eats five bites of spinach and is told they cannot have any other snacks or foods for the evening. The vegetable flavor now is associated with lack of nutrients, such that now the vegetable flavor will be less preferred. Apply the same logic to a chronic dieter who eats fresh salads during times of calorie restriction and consumes desserts, alcohol, and high-sodium foods during bouts of carefree eating. Mind which flavors are being paired with nutrients and which flavors are being paired with temporary “starvation.” Not only will flavors associated with calorie loading gain preference, consumption of too-few nutrients, which is counterproductive for other reasons, can make associated low-calorie, nutrient-dense foods less preferable and less likely to be eaten over time.

Conditioned Taste Aversion Just as food preferences are adjusted from experiences over time, food aversions similarly are learned. Tastes, odors, or sights of food/drink paired with noxious stimuli are likely to elicit negative reactions, like nausea and avoidance. These reactions represent conditioned taste aversion (CTA), its original name, despite evidence that the aversion occurs to various aspects of the food beyond taste alone. Further, aversions

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are demonstrated more readily when multiple cues, like taste and odor, are available (Slotnick, Westbrook, & Darling, 1997). CTAs are acquired quite easily, often in one trial, which suggests that biological preparedness is involved in their acquisition (Rozin & Kalat, 1971). To illustrate selective, or prepared, associations in CTA, Garcia and Koelling (1966) conducted a study known as the “bright, noisy water study.” In phase 1, all rats were provided with the same flavored water. When the rats drank from the dispenser, a click sounded and a light flashed. For half the rats, the bright, noisy, and flavored water consumed in this first phase was followed by electric shock, which elicits a freeze response. For the remaining rats, the bright, noisy, and flavored water was followed by irradiation, which induces nausea. In phase 2, rats were provided with either bright, noisy water (without flavor) or flavored water (without the click and light) and researchers measured how much water the rats drank. Rats that were previously shocked after drinking water drank less of the bright, noisy water compared to the flavored water. Rats that were previously irradiated after drinking water drank less of the flavored water compared to the bright, noisy water. The fundamental result is that we do not associate all stimuli with similar ease/effort. Instead, rats more easily associated an event that made them nauseous (in this case, irradiation, but often an emetic drug is administered) with the taste of water instead of auditory or visual cues of nausea. You likely are familiar with an experience like that of Garcia and Koelling’s rats. Though doubtful irradiation was involved, exposure to bacterial or viral infections in foods or of the body creates similar effects. Food poisoning is a term commonly used to describe infection caused by microbial contamination of food since these are more likely to cause acute, intense symptoms. The most common culprits of such “poisoning” include norovirus, which is responsible for an estimated 36% of global infections, and E. coli, which accounts for another 17% of infections (Kirk et al., 2015). Though symptoms of food poisoning present similarly to other illnesses, like viral infection from another nonfood source, it is estimated that 2 billion global incidents of food poisoning occur each year. In case you were unlucky enough to be part of that statistic, think back to your symptoms. Like you and other humans, rats not only alter consumption (i.e., avoid the tastes that preceded onset of the illness), they show nauseous responses, like “lying on belly”—as measured by observation—if forced to consume a liquid to which CTA has been learned (Schafe & Bernstein, 1996). In humans, self-reported disgust and heightened facial muscular activity (measured by electromyography) are correlated with conventional signs of CTA, such as refusal to eat (Borg et al., 2016). Severe illness is not required for CTAs to develop. A time period without nutrients/ calories, without explicitly delivered aversive stimuli, also decreases flavor preferences (Boakes, Colagiuri, & Mahon, 2010). Painful gut sensations produce CTA, like that caused by nausea or malaise (Lin, Arthurs, & Reilly, 2017). In humans, visual portrayals of gastrointestinal illness can foster CTA, as generated when Borg et al. (2016) paired images of neutral foods (cheese and a bruschetta wrap) with a 40-second video clip of a vomiting woman. CTA to foods were not shown for food images paired with videoed

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glassmaking. In a final example of the power of CTAs, they can be acquired even when animals are anesthetized during the noxious effects of the radiation or drug (Rabin & Rabin, 1984). Once CTA develops, it can be difficult to eliminate. Through a procedure known as extinction, many CRs can be eliminated by simply presenting the CS—in this case, the taste—without the related unconditioned stimuli—in this case, the nausea-inducing irradiation, drug, or bacteria. One reason extinction does not work well for CTA is that exposure to the conditioned stimulus requires consumption of the food or drink, which needs to occur voluntarily. Instead, explicit counterconditioning where a food is paired with something appetitive, such as in flavor-sweet associations, may be necessary to eliminate disgust and reinstate consistent acceptance or consumption.

Chew on This: The Medicine Effect Another twist in the taste conditioning story is that, if a liquid or food taste is provided before an animal begins recovering from illness, the flavors predictive of recovery (or, “feeling better”) become preferred (i.e., consumed more often). Dubbed the medicine effect, these conditioned preferences might explain why we sometimes grow to love the foods we consume while sick but mending. Barker and Weaver (1991) provided a laboratory demonstration of the medicine effect. They first injected rats with lithium to cause illness. Rats then tasted saccharin flavor 30 minutes later (as illness was setting in) and tasted vinegar flavor 75 minutes later (as the effects of lithium were dissipating). During later testing, rats avoided saccharin flavor and preferred vinegar flavor. Although the medicine effect is not as robust a finding as flavor-flavor associations, flavor-nutrient associations, or CTAs, it might explain occasional learned preferences.

Applications of Conditioned Responses The role of classical conditioning in product branding and messaging began over a century ago. John Watson, best known for demonstrating classically conditioned fears in Little Albert, provided expertise to the advertising industry (e.g., J. Walter Thompson Agency) to change consumer reactions. One example is his Maxwell House campaign aimed to associate the coffee brand with images of high-class living and the phrase “slip into the dream” (Bartholomew, 2013). Connecting any food or drink, like a coffee product, with social status can change consumer emotional responses to the product and proclivities to purchase it. In social sciences, changes in value of one stimulus through its association with another stimulus is known as evaluative conditioning. Many experts still believe the

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processes involved in such learned valuations are the same as those that led Pavlov’s dogs to salivate (see McSweeney & Bierley, 1984, for a summary of classical conditioning relevance in marketing). Marketers of food know of these effects, just as Watson did. From catchy taglines, to smiling kids and cute cartoon characters, appealing events are placed proximally with foods and drinks. Such evaluative conditioning for products can have detrimental effects on eating for individuals and societies. First, advertisement of processed foods pushes products with lower nutritional value and higher long-term risks to a vulnerable population (Folkvord et al., 2016). Carrots, celery, and tomatoes are not sold with accompanying prizes, smiling faces, and warm-fuzzy characters. Second, food advertisements can increase quantity of consumption in viewers. Harris, Bargh, and Brownell (2009) showed in a series of experiments that children ate nearly 50% more goldfish when watching a TV show containing unhealthy food advertisements than when watching a show with nonfood advertisements. Remember that the sight of a food initiates a host of physiological preparations and psychological expectations of food. Third and finally, emotions elicited by the advertisements color attitudes toward the food products (Kim, Lim, & Bhargava, 1998). Although additional learning and social processes are at work besides classical conditioning (see Allen & Madden, 1985), the value of product name, brand, and image does seem dependent upon associative learning via media commercials and the programming surrounding the commercial (Goldberg & Gorn, 1987). A more uplifting application of advertising, per Birch (1987), is that you can do some evaluative conditioning yourself at home. If you are nicer to kids, displaying positive emotions, while offering them novel foods, their acceptance and consumption of the food becomes more likely.

Course 2: Operant Conditioning Despite traditional divides (Skinner, 1935), the line between classical and operant conditioning is blurred (Domjan, 2016) and there is considerable overlap in the two types of conditioning. An example is the reinforcing and punishing effects of unconditioned stimuli, like nutrients or toxins. Accordingly, discussion of operant conditioning merits a return to some previously discussed concepts. Ogden (2003) categorized the role of reinforcement in eating into three areas: (1) reinforcing effects of eating food (i.e., consummatory behavior), (2) use of food reinforcers to strengthen other behavior, (3) use of nonfood reinforcers to shift consumption. Using the same framework, each of these areas is explored.

Reinforcing and Punishing Effects of Eating Food It makes sense that consumption of food would be reinforcing. We might even say the act of consumption is “automatic” since it is maintained by its own reward mechanism. The

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most proximal and certain outcome of eating and drinking is gut stimulation, meaning consumption is followed by post-ingestinal events. These flavor-nutrient associations, earlier presented from a classical conditioning perspective, are studied as operant conditioning by some experts (e.g., Rozin & Zellner, 1985) who view flavor-nutrient effects in terms of anticipated consequences. That is, consumption of specific flavors is controlled to a large degree by its physiological consequences (Myers & Sclafani, 2003). Additional evidence regarding reinforcing effects of eating was provided by Kevin Myers. He and his colleagues showed that rats will continue to eat a particular flavor when consumption of it is shortly followed by intragastric infusions of glucose. In other words, the infusion of glucose in the gut did not lead to satiation, or “stop” signals for eating, but rather appetition, or “go” signals for eating. The glucose strengthened consumption. Furthermore, the reinforcing effects were specific to the flavor consumed. When a second bottle of differently flavored liquid replaced the initial flavor, drinking subsided. Flavornutrient associations, then, may be understood better as a reinforcement effect rather than a result of CR development (Myers, 2013; Myers, Taddeo, & Richards, 2013). Viewing flavor preferences as operant allows inclusion of motivation in the analysis. Operant selection of flavors based on post-ingestinal consequences will vary across situations and time depending on deprivation levels. We might choose to eat a lessnutrient, less-dense food, in times we are not deprived. For instance, carrying healthy snacks to keep hunger at bay works by devaluing the reinforcing consequences of eating and thereby suppressing consumption. In behavior-analytic terminology, this preloading strategy is called an abolishing operation because it decreases the value of the food and decreases the likelihood that food will be sought or consumed (Langthorne & McGill, 2009). Its opposite is an establishing operation, which is created by time without foods and drinks (i.e., deprivation). You may have noticed how the value of lunch was enhanced on a day when you skipped breakfast. High deprivation levels establish foods and drinks as more valuable or as more potent reinforcers for consumption. These same effects of abolishing and establishing operations work on specific flavors. Author SS, for instance, finds that 2 weeks without curry typically initiates cravings (i.e., signs of curry deprivation). By the same token, gustatory feedback from daily consumption of curry would not be as reinforcing; its value would decrease, partly through habituation processes we discussed earlier (McSweeney, 2004). One reinforcing aspect of consumption is described by self-medication, the consumption of certain foods (or drugs) to treat symptoms such as anxiety or depression. As an example, negative mood may be accompanied by carbohydrate craving, seeking, and consumption. Though controversial, this relation between mood and carbohydrate consumption has been demonstrated in double-blind studies and may be mediated by serotonin and its dietary precursor tryptophan (Wurtman & Wurtman, 1995). In one experimental demonstration, Corsica and Spring (2008) induced a negative mood in participants by prompting them to think about a sad memory while playing sad music. Thereafter, self-reported carbohydrate cravers reliably chose a carbohydrate-rich

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beverage over a protein-rich beverage. The carbohydrate-boosted beverage also outperformed the protein-rich beverage in its antidepressant effects for participants with mild-to-moderate dysphoric mood. Such effects are consistent with correlational data: carbohydrate cravings increase during luteal phases, or premenstruation, when serotonin levels are naturally lower (Dye & Blundell, 1997) and cravings increase during fall and winter in folks with Seasonal Affective Disorder (O’Rourke, Wurtman, & Wurtman, 1988). Drugs that increase serotonin levels in the brain curb cravings for the carbohydrates but do not reduce hedonic value of the foods reported by patients (Wurtman & Wurtman, 1995). The carbohydrates remain pleasurable and available, but are consumed at lower rates, suggesting that their (over)consumption might be linked to serotonin deficits.

Morsel: Chocolate It is perhaps of little surprise that chocolate is one of the most desired foods, with 39% of female and 14% of male college students indicating chocolate as their most commonly craved food item in a study by Weingarten and Elston (1991). In their sample, chocolate cravers reported there is no substitute for chocolate, except some other type of chocolate. Other studies report equally strong chocolate preferences, with high self-reported liking and regular consumption (Rozin, Levine, & Stoess, 1991). Many of us find chocolate to be absolutely delightful, but what is so special about chocolate? Is It Sugar Craving? Perhaps we eat chocolate to satisfy our sweet cravings? Chocolate preparation into cakes, candies, and cookies typically incorporates a great deal of sugar and fat, lending the smooth, pleasing texture. Though the palatability is essential, Rozin and colleagues (1991) demonstrated that the craving for chocolate is largely independent of sweet craving. Or Maybe the Caffeine? The average 1 oz piece of dark chocolate (about 28 g) has 12 mg of caffeine, while 1 oz of milk chocolate has only about 4 mg of caffeine (USDA.org). But most of us do not start our day with chocolate; an 8-oz cup of brewed coffee contains approximately 100 mg of caffeine. Some people may consume sufficiently high amounts of chocolate for a caffeinated buzz, but the caffeine levels in chocolate fail to explain its widespread allure. Psychoactive Properties. If not sugar and caffeine, why is chocolate so powerful? Chocolate contains a special ingredient, theobromine (3.7-dimethylxanthine), with psychoactive properties. The name alone is powerful—Theobroma cacao is derived from the Greek gods (theo) and food (brosi). A 1-oz portion of dark chocolate contains 130–450 mg of theobromine. The caffeine and theobromine together in a normal portion of chocolate have psychostimulant effects, improving cognitive function and increasing energy levels (Smit, Gaffan, & Rogers, 2004).

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The simultaneous anticipation of the delightful orosensory properties of chocolate activates brain regions for pleasure and reward, and association between the sensory gratification and positive mood further drives the desire for chocolate (Parker, Parker, & Brotchie, 2006).

Active substances in some foods provide them with unusual, drug-like potential as reinforcers or punishers. We say someone is “intoxicated” when they have ingested a toxic substance with psychotropic, or psychoactive, effects. Keep in mind that any substance has toxicity potential at certain doses, as was noted in one interesting case of licorice intoxication when a woman ate 1.8 g of licorice per day—such a large amount that she experienced loss of potassium and eventual cardiac arrest (Dolan, Matulka, & Burdock, 2010). Examples of more apparent psychoactive substances in foods include psilocybin found in fungi, opium alkaloids in poppy seeds, and myristicin in nutmeg (Carlin, Dean, & Ames, 2020; Sangalli, Sangalli, & Chiang, 2000). Far and away, caffeine is the most commonly consumed psychostimulant in the world. It is a defensive toxin produced by over 60 species of plants, such as tea, coffee, and cacao (Willson, 2018), and is absorbed by the small intestine and distributed to cells through the body. It clearly serves as a powerful reinforcer for consumption as over 80% of the world’s population consumes caffeine, with most having fairly safe reactions to it (e.g., increased alertness). If moderate intake (no more than 400 mg per day) is exceeded, punishing outcomes can occur. High doses of caffeine can produce heart palpitations and disrupted rhythms, as well as nervousness, restlessness, and anxiety. Caffeine-based pick-me-ups also have quickly dissipating effects that leave a person lulled and hungry, and withdrawal effects include lethargy, headache, and irritability (Childs & de Wit, 2006; Smith, 2002); but, as discussed in Chapter 6, the impact of these delayed (less appealing) consequences of caffeine (or any drug) is discounted and its immediate, direct boosts control our behavior to a much greater degree.

Food as Reinforcers for Other (Nonconsumption) Behavior By the 1920s and 1930s, Pavlov—in part through notice by Polish physiologists, Konorski and Miller (1937)—had observed voluntary actions in his dogs that led to food deliveries. The dogs would repeat an action of the skeletal muscles that resulted in access to food. These physiologists in Europe, along with B. F. Skinner in the United States, began differentiating between reflexive actions derived from stimulus–stimulus contingencies (e.g., flavor-flavor pairings) and voluntary actions (e.g., consumption) maintained by their outcomes (e.g., satiety). But E. L. Thorndike, an American comparative psychologist, had been studying complex forms of food procurement since the late 1800s. He was interested in animal

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intelligence and how animals solve problems, often raising his subjects from birth to observe their experience and determine if their abilities to find and earn food were innate or learned. In his most famous research, Thorndike placed hungry cats, dogs, and chicks in “puzzle boxes,” allowing them 10 minutes to figure out how to escape and gain access to a dish of food. In some cases, the behavior was one action, such as stepping on a foot treadle, and, in other cases, the behavior was a required chain, such as stepping on a platform, pulling a string, and pecking a wall tack (Chance, 1999). He found that the animals would repeat the behavior that allowed them access to food. Their latency (or, delay) to complete the action decreased across trials in which they were placed in the puzzle box. Thorndike concluded that action in a context that lead to pleasurable outcomes (i.e., food) will be repeated in that context. Thorndike, then, was one of the first people to demonstrate experimentally the impact of food reinforcers on nonconsumption behaviors that produced them. Since Thorndike, over 100 years of behavioral experimentation has involved food procurement. In the most straightforward way, eating involves operant conditioning because any action that results in obtainment of food is reinforced by access to the food or, by some interpretations, the consummatory behavior involved in eating the food. Palatable foods are considered unconditioned reinforcers because their value is natural for nearly all organisms. Sweet tastes fall into this category of reinforcer. Other tastes, like bitter and sour, are more likely conditioned reinforcers because their reinforcing properties are acquired through associations with existing reinforcers, such as sweet tastes (e.g., sweetened caramel creamer) and social interactions (e.g., having coffee with friends). When we engage in behavior to produce a food, whether it is dining at a fancy restaurant, grabbing a soda from our refrigerator, or making a pit stop for frites (or, “fries”), food reinforcement usually is at work.

Nonfood Reinforcers and Punishers for Consumption The consequences (i.e., the stimulus changes) that follow behavior are called reinforcers and punishers and their involved processes or effects that strengthen and weaken food choices and eating are called reinforcement and punishment, respectively. The impact of reinforcement and punishment depends on the context of the consequences, nature of the consequences, and other variables, such as immediacy and consistency. The matching law (Chapter 3) and its principles are relevant here for understanding choices among options. When faced with two equivalent vending machines with one offering snacks at half the price, the obvious choice is the more affordable option. Factor in the quality and size of the available foods in each machine and the decision grows more complex, but still is somewhat predictable. Given powerful enough reinforcers, people will eat all sorts of things. Think of the sometimes-aversive consequences people endure directly from eating and drinking to earn reinforcers, like attention or social approval. One bar in Las Vegas, Nevada, offers a

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“Scorpion Shot.” Patrons actually pay extra money for a scorpion to be placed in the bottom of their preferred liquor drink. Clearly, from this promotional gimmick, socially mediated reinforcers affect consumption. By the same token, consumption can be punished socially. In a gender-normed culture, a man who orders a salad and a fruity cocktail drink might be ridiculed by friends and may decrease such choices in their presence. Similarly, business opportunities, romantic relationships, and family belongingness may hinge on particular foods or drinks we partake. By the same processes, Taste Avoidant Learning (TAL), not to be confused with CTA in classical conditioning, involves avoiding particular flavors after their ingestion produces aversive outcomes. For instance, Garcia, Kovner, and Green (1970) showed that contingent presentations of foot shocks to rats when they consumed a liquid decreased their subsequent ingestion of that particular liquid while avoidance of the same foot shocks was possible by drinking a differently flavored liquid. Returning to themes from Chapters 3 and 6, reinforcers and punishers can be used strategically to alter eating and drinking, as when using nudges in cafeterias to encourage vegetable and fruit consumption or when government-imposed taxes discourage purchase and consumption of sweetened beverages. These techniques are revisited in Chapter 8 for the specific case of encouraging children to consume varied diets.

Course 3: Observational Learning Do as I say, not as I do

Albert Bandura discussed vicarious transmission of behavior inhibition and disinhibition (now called vicarious reinforcement and vicarious punishment) to refer to cases when we see outcomes of others’ actions and are subsequently influenced by them (Bandura, 1965). There are obvious survival benefits of seeing others find and secure food, and then following suit. Children learn how to procure food from watching behavior models of caregivers, other adults, and even competitors (e.g., Bugnyar & Kotrschal, 2002). Adults, too, can learn to gain food by watching experts. Observer pigeons, for example, solved a problem more quickly after watching demonstrator pigeon complete the problem to obtain food compared to observer pigeons that watched a demonstrator pigeon only eat (Palameta & Lefebvre, 1985). Bandura identified four requirements for observational learning: attention, retention, motoric reproduction, and motivation (Bandura, 1969). For socially based learning, he argued the learner needs to pay attention to the behavior model, remember the modeled behavior/sequence, be physically capable of producing the behavior model, and be motivated to engage in the behavior. Combined impact of these variables can be seen in many reactions to eating contests. As captivating (i.e., attention grabbing) as it was to watch Kobayashi water-soaking his buns to eat 50 hotdogs, doubling the previous record

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Figure 7.2  Four components contributing to observational learning. Created by Stephanie da Silva.

of 24, in the Coney Island Hotdog Eating Contest of 2001, few of us have the physical capability or motivation to repeat his modeled consumption. For different reasons (i.e., your lack of attention), you may be unable to imitate a friend’s dinner selection if distracted when she placed her order from the waiter (Figure 7.2).

Attention Observed behaviors cannot be separated from those who demonstrate them. Characteristics of the demonstrator affect likelihood of attending to the behavior, as indicated by decades of research on the impact of advertisements containing appealing characters. When child observers eat lunch next to peers who are eating vegetables that the observers do not prefer, observer preference for those vegetables increases in only a few days (Birch, 1980). Such preference changes are more likely with peer demonstrators, followed by parent and then teacher demonstrators. We tend to consume more when familiar folks, especially those with whom we share characteristics (as is the case in kinship), are eating with us. For example, children consumed more cookies in the presence of a sibling than in the presence of a peer or when alone (Salvy et al., 2008). Rosenthal and McSweeney (1979) showed that male demonstrators were more likely than female to affect the amount eaten (in numbers of crackers) by participants, but both types of demonstrator influenced the speed at which participants consumed food. Their research is further evidence of how demonstrator characteristics impact imitation and that specifics of the modeled eating, in terms of its pace and size, are noticed by others. Consumption intrinsically attracts us, as noted in the recent phenomenon—mukbang— where viewers watch others consume copious amounts of foods and drinks, sometimes noisily, via live-stream or Internet broadcast (Kircaburun et al., 2020). We are similarly

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captivated by anyone engaged in such an unusual bout of eating, such as gorging on hotdogs or eating an exotic dish, especially if the act is accompanied by instructions from others to “Look, check that out!” With modeled eating by children in commercials, there will be additional attention-grabbing aspects of the ads like music, bright colors, and attractive faces. Inadvertently, parents might draw too much attention to children who are engaged in food refusal (that could consequently be modeled by other children). The central point is that anything directing attention to the modeled consumption could increase the likelihood it is imitated, which was shown in research on mukbang reporting that viewers are more likely to eat or drink the substances consumed in the videos they watch (Kircaburun et al.).

Retention and Motoric Reproduction The ability to remember and repeat actions is critical for observational learning. We often struggle to note, remember, and recreate complex actions, like Danielle Kang’s golf swing, Graham Norton’s humor, or Paul Hollywood’s baking of rum babas. The actions of eating in themselves—from accessing foods, to placing them in the mouth and chewing—are fairly easy to imitate. There are occasions, however, when consumption acts might be harder to remember and repeat. One example is the use of certain eating utensils as observers may not remember particular fingers or positioning involved and may not be able to physically maneuver food with the utensil. Author SS remembers the difficulties of cracking walnuts like her father when she was a child with too little strength to do so. Further, SS does not consume crab legs because she has no recollection of how to open them and access their edible contents, despite dining with people who were eating crab legs hundreds of times.

Motivation Seeing another person enjoy a food is a case of vicarious reinforcement if it increases the likelihood we will eat the food. For this to occur, we must be motivated in some way by the observed experience with the food. Perhaps surprisingly, observer hunger does not appear to influence the effects of modeled eating, and modeling has less impact at breakfast and lunch than at dinner (Cruwys, Bevelander, & Hermans, 2015). Seeing or hearing others make expressions or sounds indicating they enjoy a food can serve as vicarious versions of reinforcers discussed previously, but direct personal history with a food is more powerful than these indirect experiences modeled by others. If you have a CTA to peach ice cream, for instance, it probably will not matter how many people you observe enjoying the food; your prior experience with the food is a relatively stronger predictor of what you will eat. Consider the power of personal experience as another reason why pushing bitter vegetables on young children can backfire in the long run. Provide them with multiple negative experiences with a food while their taste is acutely

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sensitive to bitter and a small miracle may be needed before they will try the food again. Just as reinforcement occurs vicariously, so does punishment. Birch and colleagues (1987) have discussed the unfortunate climate in which many healthy foods are provided to kids. Comments like “this is not bad for kale,” or nonverbal apprehension and bitter faces displayed by adults attempting to model appropriate consumption garner associations between the food and negatively valued stimuli (e.g., a bitter face) and serve as a case of vicarious punishment in which observers learn the consequences of eating the food for themselves could be uncomfortable or aversive. Unfortunately, it is as difficult to reverse observed negative experiences with foods as direct negative experience (Greenhalgh et al., 2009). Like CTA and TAL, seeing negative experiences and avoiding food accordingly provides protection/benefits. Vicariously experienced reinforcers and punishers are powerful motives, especially when in novel environments attempting to gain acceptance and membership. Approval from others is reinforcing and, when we see others gain approval from particular actions, we are more likely to repeat the action. Consider a binge drinking case since, unfortunately, this behavior is quite common among traditional college-age students. If Author LC watches SS consume large quantities of alcohol in a short time and receives social accolades from friends with romantic attention from a partner, LC may be inclined to binge drink if she feels competent to do so and values the observed consequences experienced by SS. Lest you think such imitation is a phenomenon of wasted youth, take note of one of Travel Channel’s most popular shows, Man v. Food, in which its host travels to various destinations to engorge on whatever giant stash of food the restaurant offers. According to the Travel Channel (Robinson, 2017), the TV show—in its 10 years on the air—has inspired development of over 1000 eating contests by restaurants. This is observational learning at its best (or worst?). Business owners and patrons see the demonstrated event on television and recreate it locally. As miserable as the host (i.e., consumption model) appears while eating the food, observed social reinforcers and media hype (e.g., cheers and notoriety) can be more powerful than the observed outcomes of the consumption itself.

Combined Effects and Individual Differences A combination of variables is involved in most studies of modeled and imitated eating. Frazier et al. (2012) reported that preschool children were more likely to select foods eaten by same-gender children with positive emotional expressions than foods eaten by children of a different gender with negative emotions. Attention to eating by others depends on factors like similarity, liking, and status of the demonstrator. Motivation to repeat the consumption rests in the vicariously experienced outcomes (e.g., positive or negative emotional expression) and their value to the observer. Interactions also were obtained by Jansen and Tenney (2001) who provided children access to a nonpreferred yogurt under conditions when the yogurt was nutrient dense or nutrient free while being

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eaten by someone else. Modeling had a greater effect when the food was nutrient dense, showing a potentiation of modeling by nutrients in the food. There also are individual differences in the extent to which a person is affected by socially mediated behavior models. Younger children often mimic behavior of others with less regard for the outcomes of the behavior for themselves (e.g., the palatability and nutrients of the food). Women tend to adjust eating to align with others more than men (Cruwys, Bevelander, & Hermans, 2015), but women are less likely to engage in high-profile (i.e., “showy,” contest-based) binge eating. To summarize what we know about observational learning, seeing others enjoy foods makes it more likely we will try the foods but the effects are attenuated if other—more familiar and preferred—food choices are available (Pliner & Mann, 2004). Our imitation of eating is more likely if we admire or feel similar to the person and if we are motivated to eat/drink by the value of food or the value of other stimuli provided for eating the food. If our experience and the modeled experience are inconsistent, our own direct experience with the food and its outcomes (such as flavor, nutrients, or later nausea) overrides the vicarious experiences (i.e., observed experiences in others). Burke and colleagues (2010) describe the impact of comparisons we make regarding outcome predictions for demonstrated behavior we observe and for our own behavior. The decision to repeat an observed action is based on predicted outcomes, which can be wrong, as in the case where a prior CTA keeps someone from enjoying a delicious, safe meal. For more information on this topic, see a review by Cruwys, Bevelander, & Hermans (2015).

Dessert: Collateral Consumption We have reviewed eating and drinking as related to the value of the consumed substance. But eating and drinking also can be induced indirectly by regular presentations of other, uncorrelated, stimulus events. Let’s say food becomes available at regular intervals (e.g., every 1 minute) for a food-deprived rat in an operant chamber while water is freely available. The intermittent availability of food—or, more specifically, the periods between the food deliveries—will lead to water consumption in the rat. Moreover, the induced behavior often occurs at extreme levels. Such induced drinking by a rat, for example, involves consuming more water than is needed per any homeostatic or water deprivation explanation. Ingestion of large amounts of fluid within a short time is called polydipsia. When the excessive drinking is created by scheduled events (sometimes called the “generator schedule”) it is called schedule-induced polydipsia (SIP; e.g., Falk, 1966). The induced fluid consumption is not related to deprivation of fluids but is linked to deprivation of the reinforcers (e.g., food). There are multiple explanations of polydipsia, probably the most accepted being that SIP is a displacement activity emitted during periods of nonreinforcement or no reward. Displacement acts distract organisms from desired

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goals when the goals are unavailable. In studies of SIP involving intermittent food delivery without availability of water, rats still emit a displacement activity, such as wheel running (Levitsky & Collier, 1968) or grooming, at times between food availability. There is a primary type of polydipsia, psychogenic polydipsia (PPD), characterized by chronic excessive drinking across situations. It usually occurs in individuals diagnosed with mental conditions, such as schizophrenia and depression, and can have detrimental outcomes such as water intoxication and incontinence (e.g., Kohli, Verma, & Sharma, 2011). Traditionally, discussions of PPD and SIP do not overlap since the former is a concern of personality theorists and clinicians focused on understanding a chronic symptom and the latter is a concern of behavioral psychologists focused on effects of environmental events. But perhaps the schedule-induced form of polydipsia is a milder case of a similar phenomenon, an idea supported by recent findings that drugs with the same mechanisms of action (e.g., inhibition of serotonin reuptake) can treat PPD and SIP. Further, medications that reduce either type of polydipsia do not affect regulatory drinking, providing more evidence that polydipsia is nonhomeostatic. SIP is used as a model of compulsive behavior (e.g., skin picking) in humans because displacement acts have compulsive characteristics, like the vigor with which they occur (Moreno & Flores, 2012). Real-world bouts of binge drinking and binge eating parallel polydipsia in structure and maybe function, even showing similar ranges in variability across individuals (Navarro et al., 2015). SIP has been used as a model of overconsumption of alcohol (Gilpin et al., 2008; Lester, 1961) because scheduled food rewards can induce ethanol consumption to levels of self-intoxication where the rats cannot stand or walk. If you are having a hard time applying excessive drinking among nonhumans to excessive eating in humans, heed three documented extensions: ●

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Senter and Sinclair (1967) showed again that excessive ethanol is consumed during wait times and similar overconsumption during nonreinforcement occurred for a sucrose solution. That is, they extended previous rat findings with ethanol to sugarbased solutions. Doyle and Samson (1985) tested schedule-induced consumption of water, nonalcoholic beer, and alcoholic beer in human participants who were playing a slot machine that paid off every 30 or 90 seconds. They replicated all previous reports in nonhumans regarding effects of schedule and type of fluid available. Muller, Crow, and Cheney (1979) measured walking, shifting of weight, and pacing in humans who earned tokens by pulling a plunger in a laboratory. Their participants engaged in “fidgeting”-type behaviors during periods between token availability, illustrating schedule-induced motor activity in humans.

It is not a stretch, in combining these findings, to imagine that eating readily available preferred foods could occur as a function of intermittent schedules controlling other reinforcers, like money (Rzeszutek, 2017).

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Consider your behavior in known wait times, such as traffic signals, long lines, television commercials, and computer processing time, when you have little control over timing of goals or events. These situations containing signals of nonreinforcement are often aversive and induce some displacement activity that helps you endure the wait time, especially if the wait is somehow stressful. Navarro et al. (2015) found evidence that SIP is “therapeutic” in the neurological sense as compulsive drinking is mediated by serotonin action and administration of a serotonin receptor agonist decreased compulsive drinking. When serotonin levels then were reversed by administration of a serotonin antagonist, compulsive SIP returned. In our current world, checking of cell phones is a commonly observed compulsive displacement act known to reduce anxiety. In situations where food or drink is available, eating and drinking could serve as a displacement act. It makes sense that, over time and with environmental support, these schedule-induced consumptions could become persistent, generalized habits. This process represents what many people report as “I eat when I’m bored.” Perhaps a more accurate descriptor is, “I eat when experiencing a compulsive need to do something during a period of minimal reinforcement.” Author SS is reminded of her mindless snacking habit while grading student papers or writing (maybe even this book!).

Dining Review Key Elements

Recommended Reviews

Whet your appetite: Acquired tastes

Think of familiar foods that you enjoy. How did you react to these foods when you first tried them? Can you describe your progression of liking across repeated exposure?

The amuse-bouche: Mere exposure

Recall a memorable first experience with food. What attention and emotions occurred? Describe how that reaction to the food dissipated, or habituated, as you experienced it again.

Course 1: Classical

Explain flavor-flavor and flavor-nutrient associations to a friend using everyday language.

conditioning Course 2: Operant conditioning Morsel: Chocolate

Review the idea of food as reward. What happens when children have energy-dense foods readily available, especially in times of emotional significance? Revisit the possible reasons people enjoy chocolate, which has many reinforcing properties. What other events or experiences become associated with chocolate through conditioning?

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Key Elements

Recommended Reviews

Course 3: Observational learning

Think of a time when you ate or drank something because you saw others do it. Using this example, describe how Bandura’s four components were present in your experience of observational learning.

Dessert: Collateral consumption

Do you engage in eating or drinking when bored? Draw parallels between your experience and SIP.

Gochisousama Thanks to the chefs! ●

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Capaldi, E. D. (1996). Why We Eat What We Eat: The Psychology of Eating. Washington, DC: American Psychological Association. Rozin, P., & Zellner, D. (1985). “The role of Pavlovian conditioning in the acquisition of food likes and dislikes,” Annals of the New York Academy of Sciences, 443: 189–202. Sclafani, A. (2018), “From appetite setpoint to appetition: 50 years of ingestive behavior research,” Physiology & Behavior, 192: 210–17. Zentall, T. R., & B. G. Galef (1987). Social Learning: Psychological and Biological Perspectives. Lawrence Erlbaum Associates.

Glossary Abolishing operation:

events that decrease the value of rewards and decrease probability of behavior that produces those rewards; as an example, prefeeding decreases the value of food rewards

Behavior models:

exhibited behavior, usually by a conspecific or caregiver

Biological preparedness:

innate tendencies toward particular behaviors or learned associations

Conditioned reinforcers:

reinforcers with acquired value; also called secondary reinforcers

Conditioned responses (CR):

learned reaction to events, called conditioned stimuli, that predict subsequent occurrence of other events, called unconditioned stimuli

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events that predict subsequent occurrent of other events, called unconditioned stimuli, and thereby elicit learned—preparatory—reactions

Conditioned Taste Aversion (CTA): special case of classical conditioning in which the CR is nausea, refusal, and/or avoidance of taste, smell, or other cues predictive of a food or drink Counterconditioning:

a classical conditioning technique used to produce conditioned responses that are contrary to behavior that previously was elicited by a conditioned stimulus

Dessert effect:

successively spaced presentations of a new (especially bitter or sour) flavor prior to consumption of the preferred taste lead to less preference for the first flavor and increased preference for the second, alreadypreferred flavor

Establishing operation:

events that increase the value of rewards and increase probability of behavior that produces those rewards; as an example, food deprivation increases the value of food rewards

Extinction:

reduced (strength in) responding due to the removal of reinforcers/rewards maintaining a behavior

Food poisoning:

illness, usually nausea with vomiting, caused by consuming food or drink contaminated with bacteria, viruses, or other toxins

Habituation:

decreased intensity of reflexive response to stimulation across repeated exposures to the same stimulus event

Medicine effect:

a taste provided before the organism recovers from a drug or illness is predictive of recovery (or, “feeling better”) and becomes preferred

Mere exposure effect:

our repeated experience with an ingested substance increases our consumption of it

Operant chamber:

experimental enclosure used to test animal behavior

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Polydipsia:

extreme thirst marked by excessive drinking, intake of fluids

Psychoactive:

containing properties that affect conscious experience; also known as psychotropic

Punishment:

process or procedure by which consequences of behavior weaken their occurrence

Reinforcement:

process or procedure by which consequences of behavior strengthen their occurrence

Schedule-induced polydipsia (SIP): ingestion of large amounts of fluid within a short time created by scheduled events Sensitization:

increased intensity of reflexive response to stimulation across repeated exposures to the same stimulus event

Unconditioned reinforcers:

reinforcers with innate value; also called primary reinforcers

Vicarious Punishment:

decrease in behavior probability produced by seeing a behavior model and its consequences

Vicarious Reinforcement:

increase in behavior probability produced by seeing a behavior model and its consequences

Chapter 8 The Apple of My Eye: Child Development and Eating Whet Your Appetite: Why Are Some Kids Such Picky Eaters? Are some children picky eaters regardless of their exposure to foods? What happens if caregivers require children to eat vegetables—does that increase acceptance and consumption of vegetables in the near and distant future? What is different among picky and nonpicky eaters? What does it mean to be a picky eater, and when does picky eating become a problem? Childhood experiences are a recurring theme of this chapter. Nurtured eating is revisited with focus on early life influences that shape relations with food as well as biological maturity (i.e., stages of development) based on heritable predispositions.

Menu Amuse-Bouche: What’s for Lunch? Course 1: The Earliest Influences—Prenatal Development Prenatal “Consumption” Impact on Eating Course 2: Infancy and Toddlerhood (up to Age 2) Neophobia Forming Associations Course 3: Early Childhood (Ages 3–8 Years) Characteristic Consumption Picky Eaters Environmental Influences Course 4: Middle Childhood (Age 9 and Beyond) Developing Habits Peer Influences and Branded Experiences Response to Stress, Anxiety, and Depression

167 168 168 169 169 171 176 176 176 178 181 183 183 185 185

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Dessert: Resisting Temptations Dining Review Gochisousama Glossary

187 188 188 189

Amuse-Bouche: What’s for Lunch? An Internet search for school lunches reveals news articles showing beautiful selections from around the world, and thinly veiled detest for school lunches in the United States. These cherry-picked images fail to acknowledge that school cafeterias are not a global norm and thus most kids pack lunch from home. Within the United States, there is tremendous variability in the foods brought from home and those prepared at school even with the National School Lunch Program (NSLP) established by US President Harry Truman in 1946 to provide nutrition access at school (United States Department of Agriculture, USDA, 2019). In 2018, about 30 million children participated in the NSLP in the United States, and another 14 million in the School Breakfast Program (USDA, 2019). School lunches are available for all students to purchase, and eligible students receive free or reduced-price lunch and breakfast based on family household income. On school days, a large portion of energy is consumed and expended at school, so these programs present a substantial opportunity to encourage health and nutrition. Adequate nutrition is essential for physical, cognitive, and psychosocial development, and kids from food-insecure households are more likely to eat school meals than children from higher socioeconomic status (SES) groups (USDA). Breakfast interventions have complementary benefits by increasing cognitive performance in undernourished children, improving attendance (Politt, 1995) and providing psychosocial benefits (Murphy et al., 1998). During the COVID-19 pandemic, it is estimated that billions of in-school meals were missed, despite innovative strategies from home delivery to universal meal offerings (Borkowski et al., 2021). Despite the USDA nutritional requirements for school lunches, the surrounding food environment including vending machines and nearby stores are not regulated. The number of vending machines and the types of snacks and beverages they provide influence eating among teenagers (Neumark-Sztainer et al., 2005). When students age 10–12 purchase school lunch plus items from the vending machine, consumption of the school lunch decreases while food waste and sugar intake increase (Templeton, Marlette, & Panemangalone, 2005). And, when adolescents have an “open campus” policy allowing lunch leave, they are more likely to consume fast food (Neumark-Sztainer et al.). In younger kids, recess before lunch, instead of recess after lunch, removes time incentives to stop eating, increases fruit and vegetable consumption, and decreases afternoon hunger (Price & Just, 2015). From these studies it is evident that policies at the local school and community level influence student consumption beyond the reach of broader government programs.

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Course 1: The Earliest Influences—Prenatal Development From conception to birth, the placenta transports nutrients (e.g., glucose, amino acids, and fatty acids) and oxygen to a fetus (Brett et al., 2014). Growth of the fetus depends on the mother’s nutrient intake and the ability of the placenta to pass along those nutrients via the umbilical cord. The pregnant mother’s diet, including prenatal vitamins (Kaiser & Allen, 2002), and placental health, marked by transport proteins and electrochemical exchange routes, play key roles in successful fetal development and growth (Scholl et al., 1997). Midway through the gestation period, the fetus begins consuming nutrients in addition to this “passive” feeding through the circulatory system.

Prenatal “Consumption” Observations and images of swallowing motions in utero fetuses raised questions regarding the functions of the swallowing observed: (1) Is the content of amniotic fluid impacted by food and drink choices of the mother? (2) Is the fetus ingesting amniotic fluid? (3) Can the fetus extract nutrients from the amniotic fluid? Studies then provided answers, indicating that amniotic fluid is affected by a mother’s consumption (e.g., Mennella, Johnson, & Beauchamp, 1995, found that amniotic fluid smells more “garlicy” when mothers consumed garlic pills); that amniotic fluid contents appear in the intestines of the fetus (Lev & Orlic, 1973); and that nutrients, like proteins, from the amniotic fluid are metabolized by the gut of the fetus (Pitkin & Reynolds, 1975). Thus, a pregnant mother’s food and drink choices affect nourishment of the fetus, in part, through composition of the amniotic fluid swallowed by the fetus. Swallowing results from maturation—beginning regularly around week 18—and fetal swallowing tends to occur at roughly six times the rate of swallowing in adult humans, which results in more fluid volume ingested in fetuses than adults (El-Haddad et al., 2004, 2005). Thirst signals further provoke fetal swallowing. When amniotic fluid is more hydrated from the mother’s consumption of water instead of caffeinated beverages, swallowing occurs less frequently (Sherman, Ross, & Ervin, 1990). Additionally, atypical swallowing is related to an abundance or an undersupply of amniotic fluid to the fetus (Brace, Anderson, & Cheung, 2014) from inappropriate absorption of fluid by the fetus, over- or underproduction of amniotic fluid by the mother, or for unknown reasons. When mothers lose large volumes of water, as with morning sickness or vigorous exercise, their child is more likely to prefer salty foods as babies and adults (Crystal & Bernstein, 1995, 1998) and this relation presumably is mediated by hydration of the fetus. Amniotic fluid levels are routinely monitored through prenatal healthcare for signs of fetus viability (Dubil & Magann, 2013) because newborns are at increased risk of requiring neonatal intensive care unit support if amniotic fluid level drops below the 5th percentile.

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Impact on Eating Flavors from amniotic fluid impact postnatal acceptance of flavors. This includes general flavor profiles (e.g., food types) and specific flavors (Nolte & Mason, 1995). In one study demonstrating this effect, Mennella, Jagnow, and Beauchamp (2001) randomly assigned women to drink 100 mL of carrot juice or water for 3 weeks during their last trimester of pregnancy. Infants of mothers who drank carrot juice exhibited fewer negative facial expressions and consumed slightly more when fed carrot-flavored cereal compared to infants whose mothers did not drink carrot juice. From effects like exposure to carrot juice, it follows that consumption of varied foods and flavors during pregnancy increases the likelihood that, as infants and toddlers, children will accept and consume varied foods (Cooke & Fildes, 2011).

Course 2: Infancy and Toddlerhood (up to Age 2) It was believed that infant flavor preferences were universally similar until evidence surfaced of their variability across individuals in the past 15 years (e.g., Schwartz, Issanchou, & Nicklaus, 2009; Mennella, 2006). Variable preferences could be attributed to prenatal experience as just described, heritable differences in taste sensitivity discussed in Chapter 5, and other factors like exposure to various foods in infancy. Keeping these genetic and prenatal variations in mind, other findings regarding infant acceptance of flavors are now addressed. Sweet. Preference for sweet is believed to be innate, as newborns prefer sweetened water to regular water (Beauchamp & Moran, 1982), and enhanced by experiences with sucrose. In the short term, consuming sweets is satisfying. Long-term consumption of sweets drives desire for sweets while lesser contact with sweets keeps desire for sweets at bay. If children are accustomed to foods prepared plainly or with salt, they will choose those familiar preparations over sweetened versions. Author SS was raised on savory grits in the Southern United States and was off-put by similar—but sweetened—breakfast oats when visiting northern regions. But, we cannot entirely terminate or reverse sweet preferences. Even if you practically eliminated exposure to sweets, an impossible feat in most contemporary cultures, it would be difficult to observe the level of disgust to sweets that is observed for bitter and sour. The persistence of sweet preferences could be due to pleasant taste, the energy provided, or other functions like analgesia (Blass & Hoffmeyer, 1991; Pepino & Mennella, 2005). Thus, sugar cravings are amenable to environmental influences, even though basic acceptance and preferences for sweet tastes remain an underlying tendency. Salty. Children ages 4–24 months will consume saline solution, with neutral consumption prior to 4 months and waning consumption after 2 years of age (Beauchamp, Cowart, & Moran, 1986). Much like sweets, however, salt exposure breeds preference for salts. After observing no preference for salt in 2-month-olds, researchers retested the

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same babies at age 6 months to analyze salt preference as a function of how often salted, starchy foods were offered by parents. Babies with a history of high-sodium starchy food offerings preferred salty to nonsalty solutions at 6 months old, whereas babies with little or no starch exposure did not. Further, when retested at ages 3 and 4 years, preferences for and consumption of salt and/or salty foods remained consistent across the subsets of children based on their history of salty, starchy foods (Stein, Cowart, & Beauchamp, 2012). Bitter and Sour. Newborn infants express disgust when provided with bitter-tasting and sour-tasting substances (Desor, Maller, & Andrews, 1975), but they still drink bitter substances with similar acceptance as water (Schwartz, Issanchou, & Nicklaus, 2009). Within months of birth, bitter-tasting substances—even ones previously consumed—are less often consumed and more likely avoided by children. Much of this research involves infants prescribed to drink a bitter-tasting formula, protein hydrolysate, which is consumed more readily by babies who have early experience with it (Kajuira, Cowart, & Beauchamp, 1992). From this, it seems early and repeated experiences with bitter tastes make them more palatable for infants. In one such study, infants were assigned to consume regular or bitter formula. Beginning at 2 weeks of age, the infants (1) consumed regular formula for 7 months; (2) bitter formula for 7 months; (3) bitter formula 3 months before regular formula for 4 months; or (4) regular formula 4 months before bitter formula for 3 months. Babies then were given a test containing the two familiar formulas and a novel bittertasting formula. Babies with prior experience drinking the bitter-tasting formula were more accepting of the familiar and novel bitter-tasting formulas, as measured by their facial expressions, amount consumed, and mothers’ judgments of child enjoyment (Mennella, Griffin, & Beauchamp, 2004). Moreover, 7 months of experience with bitter tastes created stronger effects than did 3 months of experience. Flavor Preferences. Babies choose a variety of tastes to consume, including some unsweet, but options available drive this pattern. In landmark research, Clara Marie Davis (1928–1939) studied 6- to 11-month-olds who were provided 10–12 whole foods at each meal and self-selected what and how much to eat (as described in Birch, 1999; Wilson, 2016). The babies thrived. Previously malnutritioned babies gained weight, developed affinities for all sorts of foods, and ate a balanced diet. Unfortunately, despite some cautions (e.g., Birch, 1999, and Davis herself) against doing so, the study was used to argue that children will consume “what their bodies need.” But two critical elements of Davis’s research were the foods available— only whole, nonprocessed options—and the variety provided at each meal. A child with access to options that include sweet foods will not choose diverse flavors and nutrients, but instead will develop exclusive preference for sweets. Exposure to a variety of foods fosters acceptance of novel foods (Gerrish & Mennella, 2001), but this is bounded by parents’ flavor profiles since they are likely to offer flavors to babies that they themselves accept. The only fruit or vegetable that limits subsequent intake of vegetables is potatoes (Gerrish & Mennella). Thus, a variety of flavors, with perhaps isolated potato offerings, is a promising strategy.

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Chew on This: Failure to Thrive In extreme cases, children’s consumption—or a lack thereof—can lead to insufficient growth, a condition known as failure to thrive (FTT; Frank & Zeisel, 1988). Causes of FTT can be organic or nonorganic, meaning it can have clear medical bases or additional social and environmental influences. The prevalence of FTT ranges from 1% to 10% in industrialized nations (Ross et al., 2017) and typically is defined as weight and height below the 5th percentile, based on age-related norms, as well as weight deceleration (or, “weight velocity” over time under the 5th percentile; Olsen et al., 2007). The prognosis for children with the diagnosis is promising with medical and behavioral interventions that address caloric intake and consumption habits (Cole & Lanham, 2011). In some cases, particularly without treatment, FTT can lead to longer-term developmental effects such as relatively small stature and cognitive deficits. The goal of any treatment is to obtain “catch-up growth” and improve nutrient intake henceforth (Homan, 2016). Close monitoring is necessary as recurrent FTT, characterized by relapses, can occur.

Neophobia Protective functions of neophobia from an evolutionary perspective were discussed in Chapter 3. Initially, young infants trust the substances given to them, mainly through the breast where mother’s body has done the protective job of preparing the food. As months pass, and babies begin consuming solid foods—around 6 months of age, neophobia arises (Moding & Stifter, 2016). In our evolutionary history, older babies who did not exhibit neophobia (instead, eating anything available both familiar and unfamiliar) were less likely to survive and pass along genetic material to subsequent generations. Neophobia decreases with increased exposures to a variety of foods as discussed in Chapter 7. The present focus is neophobia as related to development. Developmental stages proposed by Erik Erikson and Jean Piaget foster understanding of child behavior that may seem illogical from an adult perspective. These theorists identify the central crisis at work during the first year or two of life as you trust the world around you. Given caregiver responsiveness, including safe/secure food and drink experiences, you are more likely to trust your surroundings and develop a sense of hope—about life generally and, perhaps, eating specifically. Given strained or unmet food needs and consumption, you may be wary of foods and eating. Because such confidence in the world is not developed fully in this first year, we “test” the safety and trustworthiness of foods, caregivers, and the eating situation when transitioning to solid foods (Table 8.1). From Piaget’s model, too, food is part of the physical world about which we still are gathering information. Oblivious to social etiquette, babies want to play with food. The

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Table 8.1  Developmental stages and typical patterns of eating Age

Cognitive Development (Piaget)

Psychosocial Development (Erikson)

Some Typical Patterns of Eating

0–6 months

Sensorimotor (visually and orally learning about things)

Trust/Hope

Mostly liquid diet; tries everything provided; driven by hunger, comfort, and interest

6 months—

Sensorimotor (touching things more)

Trust/Hope

Neophobia appears; plays with food, eats slowly

1–2 years

Sensorimotor (or transitioning to preop)

Leading into autonomy

Neophobia continues; plays with food, eats slowly

2–3 years

Preoperational

Autonomy/Will

Picky eating appears; driven by familiarity, texture, and taste; exhibits more independence in requests and refusals

3–4 years

Preoperational

Initiative/Purpose

Picky eating heightens; more independence exerted

4–5 years

Preoperational

Initiative/Purpose

Picky eating remains or heightens; asks for foods, meals, restaurants; verbally refuses or complains; cannot comprehend digestion, food effects on long-term health

5–6 years

Preoperational (transitioning to operations)

Leading into industriousness

Continued conflict between child wants, plus inability to understand physical effects of foods, and family schedule and/ or parental pleas; develops clear preferences

1 year

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Table 8.1  Developmental stages and typical patterns of eating (continued) Age

Cognitive Development (Piaget)

Psychosocial Development (Erikson)

Some Typical Patterns of Eating

6–7 years

Leading into operations

Industry/Competence

Helps prepare food; talks more about foods, meals; can gain confidence and comfort with different foods

7–9 years

Operational thought

Industry/Competence

Can talk about menus, family planning of meals with grocery lists; makes food for themselves; tries new combinations of foods that they create

>10 years

Formal operations

Identity

Peers influence food preferences, especially for snacks and “junk foods”; food decisions can be moral based on reasons beyond self; items consumed help define the self, create identity/brand

food, like most substances during this age Freud dubbed the “oral stage,” will eventually make its way into a baby’s mouth; but, preferably, only after being smashed, examined visually, and even thrown to the ground. Food and drink are a core part of existing in the world, and babies are still figuring it out. It should be no surprise that slower feedings, where babies were given time to smell, touch, and attend to foods, can increase consumption (Escalona, 1945) as sensory properties of foods influence children’s acceptance of foods (e.g., Nicklaus, 2011). Expecting a child to sit with complete trust and without physical curiosity in foods offered may be demanding too much from a development perspective and, moreover, young children who play with their food are more likely to accept fruits and vegetables in years that follow (Coulthard & Thakker, 2015). Neophobia in those subsequent years is addressed in the next course of this chapter.

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Morsel: Breastfeeding Perhaps no other part of caregiving for new baby is as critical as breastfeeding. Various epistemologies exist concerning the importance and prioritization of breastfeeding originating from cultural norms (Amir, 2011), religious ideologies (Stroope et al., 2018), income (McFadden et al., 2019), politics, and industry (Thulier, 2009). Policies that support breastfeeding benefit infant and maternal health. The effects are most profound in low- and middle-income countries, where over 800,000 child deaths are attributed to suboptimal breastfeeding, and resulting malnutrition, each year (Black et al., 2013). Evidence supporting breastfeeding is abundant, particularly in reducing childhood morbidity and mortality (Victora et al., 2016). Providing proper nutrition to infants has correlated advantages of enhanced cognitive and socioemotional development, improved immunity from mother’s antibodies, and decreased risk of noncommunicable diseases like obesity and type 2 diabetes (Prado & Dewey, 2014). The breastfeeding mother also benefits in health and wellness, decreasing the risk of breast and ovarian cancer, and from birth spacing (Figure 8.1) (Victora et al.).

Figure 8.1  Breastfeeding benefits. Created by Stephanie da Silva based on Burnier, Dubois, & Girard (2011).

One advantage is infant exposure to a variety of flavors compared to only the taste of milk or formula (Mennella, 2009), which can translate into better acceptance of flavor variety, including vegetables, and preference for the previously experienced

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flavors during weaning (Dunn & Lessen, 2017; Mennella, Jagnow, & Beauchamp, 2001; Sullivan & Birch, 1994). Some evidence indicates that breastfed babies are less likely to consume restricted diets during toddlerhood and childhood. For instance, daughters who are breastfed exclusively at least 6 months consume more vegetables and are less prone to picky eating at age 7 (Galloway, Lee, & Birch, 2003). Anna Freud asserted that feeding does more than provide nourishment; it serves as a developmental antecedent to positive feeding behavior and heathy food attitudes (Cargill, 2007). Subsequent attachment theorists also emphasize physical closeness and other aspects of feeding as predictive of healthy parent– child relationships. Global efforts are ongoing to increase the likelihood that women will attempt and continue feeding with breastmilk (McFadden et al., 2019). The World Health Organization (WHO) created the Global Breastfeeding Collective to increase support and communicate the recommendations of exclusive breastfeeding up to 6 months of age and then continued breastfeeding with the introduction of complementary foods through age 2. Yet, only 41% of infants worldwide are exclusively breastfed for the first 6 months of life (WHO, 2017), and suboptimal rates vary by geographic region. In developing areas of the world, lower SES and rural living is associated with exclusive breastfeeding (Hitachi, et al., 2019; Adair, Popkin, & Guilkey, 1993), and breastmilk provides an advantage over formula, which must be mixed with (clean and safe) water. In high-income countries, by contrast, family income complicates the interpretation of positive outcomes correlated with breastfeeding (Whalen & Cramton, 2010; Sharma & Byrne, 2016) and formula options are readily available, regulated and safe, and nutritionally equivalent to breastmilk. Modifiable factors associated with breastfeeding include knowledge of the benefits of breastmilk, self-efficacy, and social support (Mitra et al., 2004). Breastfeeding is a learned behavior requiring systemic support, and interventions that include counseling during and after pregnancy enhance self-efficacy in breastfeeding (McFadden et al., 2019; WHO). Unfortunately, health education can do little to ameliorate some logistical barriers to breastfeeding, such as lack of social support (Adair, Popkin, & Guilkey, 1993, Whalen & Cramton, 2010), early return to work (Steurer, 2017), and lack of supportive workplace policies (Steurer, 2017). Health concerns (e.g., recovery from cesarean birth and postpartum depression) also limit breastfeeding (Whalen & Cramton, 2010). Recognizing these breastfeeding impediments can help medical providers and policymakers support caregivers across age, ethnicity, and SES to achieve healthy outcomes for children.

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Forming Associations Although prenatal exposure matters, postnatal exposure more directly impacts development of diet. Beyond availability, food exposure is socially mediated as parents model consumption or express emotions while offering particular foods (Harper & Sanders, 1975). By age 2, approach or avoidant tendencies toward meal times and specific foods are observed. Escalona (1945) described her observations when feeding babies 10 days to 24 months old during her time as a nursery psychologist (1938–40). She described higher prevalence of food fussiness among babies fed by high-anxiety mothers, like those who provide counterproductive time constraints while feeding, and that babies exhibiting food refusal with mothers and familiar caregivers often accepted food offered by unfamiliar caregivers. Calm caregiver voice was correlated with increased consumption in babies. Escalona also reported that babies’ preferences for tomato and orange juices corresponded with caregivers’ juice preferences. Unknowingly, caregivers influenced babies’ liking of the substance they were feeding the babies, perhaps through subtle cues (e.g., facial expressions, muscle tension, lower vocal tone). Early reinforcement plays a key role in our relationships with food. First, babies who are less motivated to eat can be “trained” to consume more calories via reinforcement procedures. As one example, Chorna et al. (2014) played audio of mothers’ voices dependent on rate of sucking by infants. As a result of this training, the infants consumed greater volume of liquid and consumed it more quickly during feeding times. Second, babies who seek and work for food, defined by their willingness to move a bar or mobile, are more likely to become obese, presumably because the role of food as a major source of reinforcement continues through life (a trajectory mapped by Kong & Epstein, 2016). For some infants, main sources of positive interactions with caregivers are associated with feeding, making it one of the most meaningful experiences in early life (Haradon et al., 1994). Caregiver practices, such as offering food in times of child distress, also signal food as a source of security (Stifter & Moding, 2015). When food is a primary source of positive experiences, eating can become a general habit, a phenomenon known as Eating in the Absence of Hunger (EAH). Asta and colleagues (2016) reported that EAH in babies predicts subsequently higher body mass indices (BMIs) during toddlerhood. To combat the strict association of food as reward, Kong and colleagues (2016) tested the impact of a 6-week enriched music program, compared to a control playdate group, on food reinforcement in children 9–16 months old. Providing children with alternative sources of fun reduced their seeking of food (relative to other rewards).

Course 3: Early Childhood (Ages 3–8 Years) Characteristic Consumption In their book about picky eating, Rowell and McGlothin (2015) devote a whole chapter— over 10% of the book—to typical eating of children, which may include gagging,

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rejecting previously liked foods, varying amount consumed across meals, or preferring carbohydrates over other foods. Nutritionally, children’s consumption is similar worldwide (Galloway et al., 2005) in that kids need to consume more vegetables, fruits, and whole grains and consume less sugar and fat than they currently do (Birch & Doub, 2014). According to several surveys and assessments (e.g., “Feeding Infants and Toddlers Study”) children regularly consume more calories than needed in a day (Stallings, 2018). Dubbed “traditional feeding practices,” caregiver tendencies from the mid-20th century may be harmful in conditions of energy-dense food abundance (Birch & Anzman-Frasca, 2011). Some of these feeding efforts (Birch & Doub, 2014) include: . Offering food when children cry or show distress—(feeding to soothe) 1 2. Feeding frequently when food is available 3. Providing portions that are large 4. Having preferred foods available 5. Pressuring consumption of food offered These traditional practices in contemporary contexts are unfortunately related to excessive eating in some children and picky eating in other children. A combination of practices 4 and 5 seem to breed picky eating, whereas practices 1, 2, 3, and 4 are correlated with overeating and child obesity. Through these practices, children’s consumption becomes cued by external events rather than internal signals of energy needs. Children are encouraged when and what to eat (and to do it efficiently) throughout their days when food is available. The question, “Are you hungry?” occurs less than, “You need to eat,” “It is time to eat,” and so on. Many kids in industrialized nations with high caregiver control in feeding develop little sense of autonomy over their consumption, manifesting as mindlessly or voraciously eating when food is present or refusing to eat lesser preferred foods (Birch & Fisher, 1998). One way to study children’s food selections without immediate caregiver influence is to observe children’s consumption during school lunch. In a study of American schoolchildren, Ishdorj et al. (2015) found that chicken nuggets were the most preferred entrée and potatoes, of various preparations, were the most preferred vegetable in 5to 10-year-olds. Dark green leafy vegetables were the least preferred and most wasted vegetable. Between 40% and 50% of vegetables, overall, were wasted during school lunch periods. Interestingly, though, relative consumption and waste of foods is based on other foods provided on the same plate (i.e., at the same meal). For example, burgers were wasted more when served with tater tots than when served with fresh sweet potato sticks; green beans were wasted most when served with chicken nuggets, a food rarely wasted regardless of its accompanied foods, and green beans were wasted less when served with steak fingers (a low-preferred entrée). To translate these findings to other settings, novel and lesser-preferred foods are more likely to be accepted and consumed when offered in isolation or without preferred foods available. Neophobia usually peaks in early childhood, but often worsens before waning (Pliner & Salvy, 2006). Resistance to new foods, especially fruits and vegetables, is more likely at

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ages 4–6 than at younger ages (e.g., Caton et al., 2014). Some of the increased neophobia involves heightened awareness and responsiveness to foods per se, but children also experience greater initiative needs at this age. Whereas children 2–3 years old may be content with the independent act of feeding themselves, children who are 5 years old may demand additional independence of deciding when, what, and where (if applicable) to eat. At ages 5–6, then, what might occur is a power struggle over the children’s attempts to carry out their own plans or ideas of consumption. Instead of appreciating caregiver reasoning in advocating vegetables, children associate mealtimes—and veggies, particularly—with negative emotions, thwarted initiatives, and punitive outcomes including hunger.

Picky Eaters Liking is the main factor that drives consumption in most kids. But some children, currently termed “picky eaters,” like and consume limited numbers of foods to the point that entire food groups may be omitted from their diets (Dovey et al., 2008). Several standardized measures exist that have yielded three indicators of picky eating: (1) refusing new food, (2) perceived consumption of too few calories, and (3) desire for specific food preparation (Brown and Perrin, 2018). Picky eating can be short term, lasting 2 years or less, or persistent, which is defined as 3 years or longer (Toyama & Agras, 2016), and it varies in severity. In one case a picky eater may avoid vegetables, and, in another case, a picky eater may consume only 3–4 glasses of milk per day (Conway et al., 2018). Picky eating occurs in roughly 50% of American children by age 2 years (Carruth et al., 2004; McCormick & Markowitz, 2013). As with neophobia, picky eating declines universally with age, in most cases resolving itself via maturation and socialization (Marchi & Cohen, 1990), though it persists into adolescence and adulthood for a subset, roughly 15–20% by some estimations, of the population (Mascola, Bryson, & Agras, 2010). At this point, you may be wondering about the distinguishing features of picky eating compared to neophobia, which was just reviewed in the last section. Experts, too, have contemplated the differences between these concepts and their manifestations in children. Table 8.2 contains commonly cited features of neophobia and picky eating as described by Dovey et al. (2008) in their review. Picky eating, compared with neophobia, has stronger environmental roots and is more cause for vigilance in case it persists. Neophobia

Picky Eating

Definition

Fear of novel or unknown foods (determined by sight and smell)

Rejection of large proportion of foods, familiar and unfamiliar (determined by taste and texture)

Prevalence

Nearly 100% of children

Up to 50% of children

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Neophobia

Picky Eating

Predictors

Inherent aspect of the “Omnivore • Strong preference for sweet and Dilemma” as neophobia is protective salty foods against unknown and potentially • Availability of preferred foods dangerous food items • Parental pressure to eat • Predispositions, such as picky eating in parents and maternal age

Appears

During weaning, introduction of solid foods

As early as age 2 with peak prevalence among 3-year-old children

Peak Intensity Between 2 and 6 years

Between 4 and 6 years

Solutions

• Exposure, exposure, and exposure • Modeling consumption • Decrease availability of preferred foods • Flavor pairings • Caregiver patience without pressure • Time/Maturation

• Exposure to food variety • Time/Maturation

Caregiver pressure is linked to children’s food rejections and picky eating (e.g., Batsell et al., 2002; Fisher et al., 2002; Galloway et al., 2005), but it is possible that picky eating exists prior to caregiver pressure. It also is unclear whether pressure to eat involves strict consequences for eating or refusing foods rather than caregiver pleas followed by release from the request. Adding to the complexities of mealtime is the finding that caregiver pressure to consume fruits and vegetables is used more often by those who themselves eat fewer fruits and vegetables (Fisher et al.), so caregiver instruction can conflict with modeled behavior. Primary concerns with picky eating are its negative impact on growth and health, but the current consensus is that most picky eaters have nutritional needs met (Falciglia et al., 2000; Toyama & Agras, 2016), even though they consume fewer vegetables and variety (especially, textural variety) than nonpicky eaters (van der Horst et al., 2016). Overall, picky and nonpicky eaters have similar heights, weights, and nutrient consumption (Carruth & Skinner, 2000); similar fat mass (Carruth et al., 1998); and similar caloric energy intake (Galloway et al., 2005). Secondary concerns are mealtime disruptions like tantrums and family inconveniences (e.g., packing special foods or avoiding particular restaurants). A final worry over picky eating is its persistence into adulthood and connection to disordered eating (Ellis et al., 2018). About 18% of child picky eaters continue to be picky eaters and to experience social eating anxiety as adults. Picky eating has been linked to later anorexia nervosa by some researchers, especially in cases where the picky eating involves lower body weight and when caregivers apply pressure to eat (e.g., Marchi & Cohen, 1990). This cycle can linger to provide a template for adulthood eating.

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Tackling picky eating can be challenging. Galloway et al. (2005) recommend use of modeling, where caregivers consume vegetables and fruits, and recommend caregivers avoid labeling a child as a “picky eater” or pressuring children to eat fruits and vegetables. The manipulation of available alternatives was mentioned earlier: imagine the uphill battle to convince a child to eat broccoli presented on the plate alongside two preferred food items. Instead, small amounts of the food presented alone are more likely to be consumed. For picky eaters, relatively more repeated exposures to foods, a strategy many folks recommend, is required for food acceptance compared to the 14 exposures typically required for acceptance of new foods among nonpicky eaters (Dovey et al., 2008). Beyond exposure, changing the calorie density or sweet taste can impact subsequent acceptance of less palatable foods. Caton et al. (2014) found that infusing calories into an artichoke mixture, but not sweet taste without calories, increased the likelihood that older preschool children would try that food again. In addition to pairing lesser-preferred foods with energy intake, pairing them with preferred flavors like a favorite condiment can increase acceptance of liking of the food (though no greater than produced by mere exposure alone, Anzman-Frasca et al., 2012). The most difficult aspect among these strategies, which are returned to in the next section, is that children must be exposed to the actual taste of the food for liking to increase, which means children have to consume the foods prior to liking them.

Morsel: Avoidant Restrictive Food Intake Disorder More extreme or dysfunctional versions of restrictive feeding are subsumed under the label Avoidant Restrictive Food Intake Disorder (ARFID; DSM-5; ICD-11; see Chapter 11). ARFID is defined as “an eating or feeding disturbance … manifested by persistent failure to meet appropriate nutritional and/or energy needs with one (or more) of the following: ● ● ● ●

Significant weight loss Significant nutritional deficiency Dependence on enteral feeding or oral nutritional supplements Marked interference with psychosocial functioning” (National Eating Disorders Association, NEDA, 2018)

Compared to picky eating, which is characterized by consumption of preferred foods, extended mealtimes, consuming many calories through drinks/liquids, and consumption of lesser preferred foods when camouflaged, characteristics of ARFID include FTT, atypical weight, delays in eating progression across developmental stages to include extension of picky eating and neophobia beyond expected years,

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negative impact on family functioning, and anatomical roadblocks to consumption by mouth (McCormick & Markowitz, 2013). Sometimes children develop food refusal to the point that inpatient or intensive outpatient treatment is recommended to address nutritional deficiencies and disrupted functioning (de Moor, Didden, & Korzilius, 2007; Dovey et al., 2009). Manikam and Perman (2000) recommend multidisciplinary treatment, involving gastroenterologist, nutritionist, occupational therapist, and behavior therapist. The first treatment step is to determine whether physical reasons (e.g., anatomical limitations) exist for the food refusal. Illness, compared to temperament, habits, and oral motor skills, best predicted eating problems in early childhood when studied via retrospective survey (Johnson & Harris, 2004). Prevalence of ARFID is below 5% among the general population of children and is roughly 20% among those undergoing medical care for eating disorders (Micali & Cooper-Vince, 2020; Nicely et al., 2014). ARFID is more likely in children with Autism Spectrum Disorder, ADHD, or intellectual disabilities, with up to 80% prevalence in these groups (Adamson & Morawska, 2017). Treatment includes nutritional supplements with behavioral interventions to determine the function(s) of the food refusal (e.g., access to tangibles) and foster food acceptance (de Moor, Didden, & Tolboom, 2005; Williams, Field, & Seiverling, 2010). It is common for children to eat in clinics or schools where instructional control is high while refusing to eat with caregivers or in the home. Caregiver training is usually part of treatment (Werle, Murphy, & Budd, 1993).

Environmental Influences Children are more likely to consume fruits and vegetables if they are readily available, caregivers model their consumption, and access to processed foods is limited (Birch & Fisher, 1998; Birch & Marlin, 1982; Fisher et al., 2002; Ishdorj et al., 2015; Nicklas et al., 2001). Verbal comments surrounding food and during modeled consumption are influential, especially in 5- to 10-year-olds (Greenhalgh et al., 2009; Roach et al., 2017). Even mediated messages by strangers (e.g., videoed facial expressions or computerized facial expressions of pleasure, neutrality, or disgust) alter flavor acceptance in children (Baeyens et al., 1996; Barthomeuf, Droit-Volet, & Rousset, 2012). And once children observe an older child make negative comments or refuse food, later seeing someone appreciate and consume the food does not reverse the initial negative impression. This means that caregiver positive comments about vegetables at home may not overcome prior exposure to peers’ negative reactions to vegetables. In fact, laboratory studies of food-related comments by Pesch and colleagues (2018) revealed that most comments

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by mothers had little influence on child consumption, even when using direct, negative statements aimed at restricting intake (e.g., “You’re eating both of those? No! Don’t! On my gosh” or “Put that down. Quit eating any more”). A common strategy of restricting access to certain foods effectively decreases their consumption momentarily, but has the inadvertent effect of increasing liking and later attempts to obtain the foods (Bauer et al., 2017; Fisher & Birch, 1999). Using food as a reward also can backfire because it becomes associated with satiety, contributing to the dessert effect (Chapter 7). Even more, there is a message conveyed regarding the relative value of the foods when some are forbidden or encouraged (Birch et al., 1982). No parent has ever said: “Come on, pleeeeease try a bite of cake.” Such pleas can decrease children’s consumption of the food, as shown in a study where caregivers stated, “Finish your soup, please” (Galloway et al., 2006). If using contrived attempts to increase liking and preference for foods, nonfood tangible rewards and nontangible rewards are best (Cooke et al., 2011). Lowe and colleagues (2004) increased children’s consumption and ratings of fruits and vegetables at school lunch and home using a video of Food Dude and rewards. In their program, teachers distributed stickers among students who were tasting fruits and vegetables and further distributed pencils, pens, and so on when a whole serving of fruits or vegetables was consumed. Offering rewards without pressure is critical (Cooke et al., 2011), as in the “Tiny Tastes” program for alleviating children’s picky eating. Small bites of new foods are provided every day for 14 days and sampling of the foods is rewarded with a sticker. The food must be tasted, but only one taste per meal is required and children may spit out the food if they do not like it. Each bite is designed for tasting and flavor acceptance, not substantial consumption, which avoids practicing consumption as a means to reward (Birch, Marlin, & Rotter, 1984). This low-pressure, consistent exposure with a nonfood reward produces increased eating and liking of the food. Wardle et al. (2003) reported similar outcomes by repeatedly offering sweet pepper to children who earned stickers for trying them. Tiny Tastes guidelines recommend that meals contain 1–2 foods that are liked by children, along with 1–2 new foods for novel tasting. Increased food acceptance is more likely when warm, positive experience surround meal times, as when children help prepare meals. The CHEFFs (Cooking, Healthy Eating, Fitness and Fun) program in family shelters and a Head Start program involving food interactions produced improved attitudes toward and acceptance of novel foods (Miller et al., 2017; Rodriguez et al., 2013). Simply providing adult attention at mealtimes also increases consumption. Warm greetings of a child’s name and food name while children ate cashews increased consumption of cashews across 20 exposures and increased likelihood the child would accept and consume other nuts, illustrating that the effect extended to other foods in the same groups (Birch, 1981). A final message about environmental influence is that picky eating is less amenable to contextual manipulations than is nonpicky eating. For example, use of autonomy promotion with praise successfully increased green bean consumption among nonpicky

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eaters, but had no impact on picky eaters (Jordan et al., 2020). In fact, the Tiny Tastes program is not indicated for children with food phobia, strong aversions, or sensory processing disorders. Such severe forms of picky eating are simply harder to modify.

Course 4: Middle Childhood (Age 9 and Beyond) Developing Habits Consumption tendencies in childhood are fairly stable through age 10 and picky eating may still be present. In fact, the best predictor of number of accepted foods at age 8 is the number of accepted foods at age 4 (Skinner et al., 2002), although food selection shifts from earlier focus on appearance and texture to taste (Zeinstra et al., 2007). By following participants for nearly 20 years, Nicklaus et al. (2005) found that food variety and vegetable consumption measured among children ages 2–3 years were consistent with food neophobia scores (Pliner & Hobden, 1992) measured at ages 4 through 22 years. Thus, early life habits tend to hold through middle childhood and beyond. Though critical for the shaping of lifelong habits (per Alberga et al., 2012), middle childhood is an understudied period with most research centering around eating disorders. Both childhood digestive problems and pica are associated with later bulimia (Marchi & Coehn, 1990), and adolescent girls who are high achieving and anxious are at greater risk for disordered eating (O’Dea & Abraham, 1999). Family contention around meals and childhood self-control predict later adolescent consumption (e.g., binging or avoiding foods), with onset of puberty playing an additional role in risks for disordered eating. Physical body changes among girls, marked by spreading hips and adipose deposits, trigger body concerns at the same time that social comparisons heighten to foster unhealthy expectations and more attention to consumption (Attie & Brooks-Gunn, 1989). Moreover, obesity among girls is associated with earlier menarche which is, in turn, associated with greater body image concern and lower self-esteem (Hazen, Schlozman, & Beresin, 2008). By comparison, obesity in boys is associated with delayed pubertal onset that conflicts with pressures to enhance physical stature among boys. Young adolescent boys who mature earlier tend to have greater selfconfidence, social popularity, academic achievement, and athletic achievement (Hazen et al.; McCabe & Ricciardelli, 2004), but pubertal onset is related variably to their potential for attempts to increase muscle, disordered eating, use of food supplements or steroids (Keel, Fulkerson, & Leon, 1997; Ricciardelli, & Finemore, 2002; McCabe & Ricciardelli). Among all children, popularity and acceptance with peers is a major protective factor against body concerns and disordered eating, whereas body-focused teasing from peers is a risk factor for binge eating and dieting (Haines et al., 2006). As a final comment, these relations are most prevalent in societies where media outlets, such as television and social media, are dominant. Among girls especially, media

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exposure is a primary risk factor for disordered eating (Becker & Hamburg, 1996; Hesse-Biber et al., 2006). NEDA (National Eating Disorders Association) recommends carefully navigating conversations around food so the focus is health instead of body weight or dieting. In middle childhood, children seek a sense of competency through psychosocial attempts at industriousness. They may become more involved in meal decisions and preparation, which is one way to introduce new foods and flavors they previously resisted (Ehrenberg et al., 2019; van der Horst, Ferrage, & Rytz, 2014; Zahr & Sibeko, 2017). Because they now understand concrete operations of the physical world, older children can use recipe measurements and comprehend digestion and related health concerns (Zeinstra et al., 2007). Caregivers can begin productive conversations about food effects on the body and mind. Beware, however, older children are confused by mixed messages, such as caregivers encouraging healthy acts but not doing them (Hebestreit et al., 2010). A departure from the impact of pressure on young children, teenagers are more likely to consume fruits and vegetables when pressured to do so during meals (Videon & Manning, 2003). Flavor–flavor associations continue to be influential in older children and adolescents. For example, sodium/salt can be added to bitter-tasting substances to lessen bitter flavor for children 7–10 (Mennella, Pepino, & Beauchamp, 2003). To sum, middle childhood provides opportunities for caregivers to educate their (now) older children who may begin understanding and appreciating health-based arguments while also deciding which foods and drinks become part of their repertoire and identity. The twist is that, although caregiver messages may be increasingly heard at this age, their influence is weakening. Children’s food habits are most similar to caregivers through adolescence, at which point increasing independence and access to other food options allows consumption to be driven by personal liking more than any earlier time in life. Rozin (1991) referred to the small-to-modest correlations between food preferences of caregivers and older children as a paradox. Within cultures, there is individual and cross-family variation in consumption, and one would expect caregivers and children to be more similar in food selections and preferences than others of the same culture; but Rozin found this was not necessarily the case. College students were likely to have similar values regarding foods as their parents (e.g., believing meat-eating is wrong), but their preferences were only mildly related to their caregiver preferences. These patterns hold true even when implicit preferences, as measured by Guidetti et al. (2012) with the Implicit Associations Task (see Chapter 6), were compared. Caregivers influence adolescent perceptions of healthy food decisions, whereas peers influence perceptions toward junk foods. Similarity in caregiver-and-child eating while at home is a function of the shared environment (availability, schedule, social support), but food selections can, and often do, diverge during adolescence and young adulthood when children gain control of their environments. As Rozin (1996) argues, the first years of life may not be as important as once believed in determining lifelong

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consumption. Instead, the transition to independence amidst social influence may have greater impact for the remaining years.

Peer Influences and Branded Experiences As meals increasingly are shared among peers, peers increasingly impact food exposure and food acceptance (Bargiota et al., 2013). This peer influence is demonstrated in the astonishing pace by which Starbucks spread during the 1990s, entering the top 10 of fastfood eateries in 1996. In the United States, Starbucks was the top-rated restaurant among teens for several years running until 2018 (Piper/Sandler, 2020). Its popularity, along with that of other coffee houses, has been dubbed the “teenage coffee effect,” characterized by a 25% increase in caffeine consumption in the teenage bracket. Eating can be as “trendy” as anything else among teens/adolescents, and this influence of brands and trends is entrenched in social media. Note the rise of food influencers on Instagram, with Gordon Ramsay, @gordongram, as Number 1 with over 9 million followers in 2020. Through vivid photos and enticing descriptions, these influencers can turn an unknown or vilified food into the next must-eat. Peer groups share eating habits, but we do not know if the shared habits exist prior to group membership or if the shared habits develop from assimilation to the crowd (Mackay & LaGreca, 2007). When these tendencies cut across familial and socioeconomic factors, it is more convincing that social influence occurs within the groups since members probably bring with them different food experiences and preferences. With only 7.3% of articles published on food marketing specifically studying teenagers, there is much to be learned about adolescent consumption, particularly its social influences (Truman & Elliott, 2019). We do know that teenagers, like their younger selves, continue to consume too few vegetables and whole grains (Devlin et al., 2013), but programs can help. One school-based peer leadership program, based on Teens Eating for Energy and Nutrition at School (TEENS) curriculum, increased healthy food choices across 16 different schools in the northern United States (Story et al., 2002). Another 8-week online program successfully increased vegetable intake and exercise among adolescents (Cullen et al., 2013). Additional efforts like these could counteract current teen food marketing that is based on convenience and taste with little nutritional information (Bibeau et al., 2012).

Response to Stress, Anxiety, and Depression In their review of 8- to 18-year-old children, Hill et al. (2018) reported that the impact of stress on unhealthy eating can begin in children who are as young as age 8, and similar relations between negative emotions and eating have been documented in children as young as 5 years old (Michels et al., 2012). Children who experience more problematic events and negative emotions are more likely to consume diets containing fats and sweets

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Figure 8.2  Structural equation model of behavioral outcomes linked to negative affect among adolescents. Created by Stephanie da Silva based on Puhl and Luedicke (2012).

with fewer fruits and vegetables, but there are individual differences in this tendency based on EAH and early relationships with foods (e.g., feeding to soothe in response to stress; Miller et al. 2018). Still, negative affect is a significant predictor of disordered eating for adolescents across demographics (e.g., gender) and situations (Leon et al., 1999). Figure 8.2, based on Puhl and Luedicke (2012), illustrates three problematic behavioral correlates of negative thoughts and emotions related to avoidance, health, and eating. “Avoidance Strategies” involve avoiding physical activities, gym class, being around others, and eating in the presence of others, whereas “Health Behavior” involves attempting to eat healthier foods and increased exercise. “Increased Eating” refers to feeling like eating more, tending to eat more, and binging or overeating when upset. For girls, all three behavior categories are linked to negative affect whereas boys are not more likely to engage in Health Behavior when experiencing negative affect. The source of the negative affect may be related to food or one’s body, but negative emotions and mood from any source can trigger eating, which implies a coping mechanism/function of food-oriented behavior and eating (Espeset et al., 2012; Suisman et al., 2008). For example, negative mood and other symptoms of depression are associated with increased caloric intake (Dingemans et al., 2009). Boredom also can trigger eating, although its mechanism is not clear (Crockett, Myhre, & Rokke, 2015). Perhaps eating and drinking provide distraction, stimulation, or meaning/purpose, which is supported by the finding that people eat exciting or enticing foods when bored rather than bland foods (Moynihan et al., 2015). In one interesting experimental test of boredom among young adults, Havermans et al. (2015) found the same conditions of boredom that cause people to overeat bite-sized chocolate candies also made it more likely participants would self-inflict electric shocks. From their results, it was concluded that eating when

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bored provides escape from the aversiveness of boredom more than access to reward. Binge eating tendencies are predicted by boredom susceptibility and experience seeking scores in adolescent boys (Laghi et al., 2015), suggesting that staying engaged mentally in tasks preemptively offsets a need to escape the doldrums with food preoccupation. Adolescents with depression are less likely to engage in health-promoting behaviors, including eating three meals per day (Fulkerson et al., 2004) and more likely to engage in some form of disordered eating (Santos, Richards, & Bleckley, 2007). Regular activity combats the effects of depressive symptoms in teens as it does in adults. Generally speaking, adolescents, especially girls, with depression and anxiety should have limited exposure to body image messaging centered on weight, weight loss, and dieting that may generate behaviors with those foci and create or make worse depressive symptoms. This conversation continues in Chapter 11.

Dessert: Resisting Temptations In the context of eating, self-control can involve skipping the chocolate cake for later payoffs of improved health instead of giving into immediate desires (i.e., eating chocolate cake). The biopsychological basis of self-control was introduced in Chapter 4. Here addressed is the developmental trajectory of our capacity to resist temptations. Immediate accessibility, taste, and satiety are all temptations of consumption, and children vary in their reactions to these, with some showing greater (natural) ability to delay gratification. To test impulsive tendencies, Walter Mischel (1974) conducted “marshmallow experiments” where children were told they could have one marshmallow immediately or wait until the researcher returned several minutes later to gain a second marshmallow. In one study, deferred gratification at age 4 significantly predicted BMI 30 years later (Schlam et al., 2013). Each additional minute of waiting during initial testing as a child predicted a 0.2-point body mass reduction in participants as adults. Of course, self-regulation does not comprise all factors contributing to BMI, but impulsivity seems to be a piece of the obesity pie as it is connected with greater EAH (Tan & Lumeng, 2018). Fortunately, self-regulation—showing restraint in the presence of (edible) temptations— can be improved and is not a permanent trait. Nearly 40 years ago, Mischel and Mischel (1983) proffered “rules” for generating better self-control that still hold true in modern self-regulation approaches. They include: (1) Direct attention away from short-term temptations by becoming engrossed in another activity; (2) Remember later payoffs, perhaps through intentional reminders like verbal statements; (3) Place all short-term temptations out of view if possible or do not look at or focus on the short-term temptation; (4) Think about the long-term rewards/payoffs logically (in a “cold” manner) rather than emotionally (in a “hot” manner). These rules coincide with more recent recommendations and support for “impulse control” training in children who show signs of impulsivity, such as EAH in the presence of food (Tan and Lumeng, 2018).

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Dining Review Key Elements

Recommended Reviews

Whet your appetite: Why are some kids picky eaters?

Discuss with your peers how you learn about new foods and when and why you attempt new recipes. Is the source of information socially mediated?

The amuse-bouche: What’s for lunch?

Explore lunch options for children in your community. Are lunches available through schools? In what capacity? What other options for foods and drinks are provided to students during their hours at school?

Course 1: Prenatal

Describe the critical role of amniotic fluid in early consumption.

development Course 2: Infancy and toddlerhood

Review the idea of food as reward. What happens when children have available energy-dense foods, especially in times of emotional significance?

Morsel: Breastfeeding

Brainstorm solutions for existing barriers to breastfeeding. Specifically, in your community, are any of these solutions feasible? How?

Course 3: Early childhood

Distinguish between neophobia and picky eating. How are they different in characteristics and prevalence?

Morsel: ARFID

Investigate options for caregivers who have children with ARFID. What resources are available near you?

Course 4: Middle childhood

How did your eating change from age 10 until now? Do you recognize significant changes? What influenced those? Are your current habits like those of your caregivers or (present and past) peers?

Dessert: Resisting temptations

Find and discuss videos of Mischel’s marshmallow tests and recent replications of it by researchers and parents via social media. To what extent are the wait times of children driven by consistent traits or specifics of the situation?

Gochisousama Thanks to the Chefs! ●

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Birch, L. L., & J. O. Fisher (1998), “Development of eating behaviors among children and adolescents,” Pediatrics, 101: 539–49. Mennella, J. (2008), “The sweet taste of childhood,” in A. L. Basaum, A. Kaneko, C. M. Shephers, & G. Westheimer (eds.), The Senses: A Comprehensive Reference, pp. 183–8. San Diego, CA: Academic Press.

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●

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Mennella, J. A. (2009), “Flavour programming during breast-feeding,” Advances in Experimental Medicine and Biology, 639: 113–20. Pesch, M., & J. C. Lumeng (2017), “Methodological considerations for observational coding of eating and feeding behaviors in children and their familie,” International Journal of Behavioral Nutrition and Physical Activity, 14: 170.

Glossary Assimilation:

In psychology, refers to transition of behavior and tendencies among a person or minority group to align with those of a majority group

Avoidant/Restrictive Feeding classification of restrictive feeding recognized by and Intake Disorder (ARFID): DSM-5 and ICD-11 that involves persistent failures to meet appropriate nutritional and/or energy needs Delay(ed) gratification:

the act or ability to put off rewards or pleasing experiences for benefit (e.g., larger payoffs) to self or others

Eating in the Absence of Hunger (EAH):

consumption of foods, especially those of high palatability, when satiated

Failure to thrive (FTT):

early life condition, sometimes life threatening, recognized by restricted growth and usually accompanied by restricted consumption

Picky eating:

pattern of consumption, usually in children ages 2–8, marked by exclusion of foods or entire food groups

Self-control:

choice of larger, later rewards over smaller, sooner rewards (or, choice of smaller, sooner aversives over larger, later aversives)

Chapter 9 “When in Rome …”: Social Influences on Eating Whet Your Appetite: Is Eating Contagious? How is eating influenced by your social circle? Where do you hear of the latest diet trends? If you are vegetarian, are you drawn to others who eat similarly? Do you get ideas for recipes, meal preparation, or places to shop from neighbors and friends? This chapter explores social influences on our eating and drinking, from the social context to norms and social networks.

Menu Amuse-Bouche: Dieting Among Social Networks Course 1: Ecological Influences—Consumption in Context Commercial Presence: Supermarkets and Restaurants Course 2: Food Messages and Beliefs Stereotyped Beliefs Persuading Consumers Social Norms Course 3: The Presence of Others Stimulus Enhancement and Social Facilitation Social Networking: “Birds of a Feather …” Conformity and Obedience Course 4: Kid Foods—A Microcosm of Social Influence Dessert: Chocolate Croissants—The French Paradox Dining Review Gochisousama Glossary

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Amuse-Bouche: Dieting Among Social Networks Imagine you open Instagram to see a friend has lost 15 kg. He posts before and after photos, images of meals, and a smiling selfie from the doctor’s office after reaching goals. He seems rejuvenated and happy. You wonder what inspired his change and how he achieved it, sparking social influence on eating. The reactions of friends and others’ success stories, in person or socially mediated, affect our perceptions of healthy choices. Diets are more often attempted when we see their success in others. Fad diets create waves in a culture as users imitate friends’ methods, with norms for activity and eating traveling in social circles (Ball et al., 2010). Some of the most successful diet plans in the world, such as WW (formerly known as Weight Watchers), are effective in part from the social connection and support they provide. Perhaps this role of social support explains why medically prescribed plans can fail to sustain habit changes long term; at some point, we eat and drink alone with diminished attention to our progress. As an example, most contestants on Biggest Loser, an American weight loss competition, complete amazing feats of weight loss while on the show, living in a “bubble” of exercise and restricted food access among a tight-knit group of allies, and then regain much of the weight after the show (Kolata, 2016). Social support is critical for more subtle dietary changes as well, like increasing fruit and vegetable intake (Denham, Manogian, & Schuster, 2007; Sorkin et al., 2014; Steptoe et al., 2004). Social isolation, conversely, is a significant barrier for adherence to dietary restrictions (e.g., in cases of celiac; Bacigalupe & Plocha, 2015). Dieting, like all eating, is a social enterprise. At home, workplace, school, and social events, the presence of others provides nudges through the food and drinks that are consumed and discussed in our presence. In the age of social media, the eating habits of folks we will never meet can sway our consumption. In short, eating habits travel in social circles. Various aspects of social influence on consumption are identified in Figure 9.1 and outline the organization of this chapter from contextual influences, often at the societal level, to the most proximal of social influence, which occurs when we eat and drink in the presence of others.

Figure 9.1  Diagram of social influences on eating. Created by Stephanie da Silva.

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Course 1: Ecological Influences—Consumption in Context The environments in which we eat and drink are impacted, if not entirely controlled, by others. Caregivers purchase groceries, provide access to restaurants, and prepare foods for us. None of these variables should be taken lightly; they create our world of food and make consumption of particular substances possible and more likely. When fresh fruits and vegetables are precut by someone and made available on a table or counter while “junk foods” are locked away, we are more likely to eat the former (Mann, 2015). These ecological effects are seen in humans and nonhuman animals. Young roof rats in Israel and Cyprus only eat pine seeds from the insides of cones if those cones are prestripped or partially stripped by adult rats. The availability of the stripped cones strewn about, a contextual change created by adult rats, encourages younger rats to consume pine seeds and to hone their stripping skills (Aisner & Terkel, 1992; Galef, 2003). More directly, hens call, peck at food, and then drop food in front of their chicks, and, thereafter, chicks eat the food (Roper, 1986). In human studies, the person—often a spouse or caregiver—who creates most of the meals in the home is dubbed the family food preparer (FFP). These FFPs have the most influence on household consumption habits. FFPs who consume more high-fat foods have family members who consume more high-fat foods. When an FFP eats more fruits and vegetables, so do other members of their family (Hannon et al., 2003). Beyond our daily contexts, like home, entire food communities are shaped by the people who inhabit or lead them. Local farmers select and make available fresh crops. Policymakers determine subsidies for food production, transportation routes and limits, and market values of foods. Government allocation of land to various industries, like energy or food production, impacts global food availability and prices (Rask & Rask, 2011). Business practices also determine portion and package sizes. These are all social enterprises that indirectly impact eating and drinking by forming the world in which we live and consume.

Commercial Presence: Supermarkets and Restaurants “Big-box” supermarket stores aimed at selling lower-cost extra-large packages of foods have increased in number (Basker, Klimek, & Hoang Van, 2012). Bulk purchasing trends began in the late 1980s in the United States and spread to other parts of North America, South America, Central Europe, and South Africa in the 1990s (Reardon et al., 2003). Rapid growth of the “supermarket revolution” continued in Thailand, Malaysia, Indonesia, and China during the first decade of this century (Reardon, Timmer, & Minten, 2012). In 2007, Walmart, a supercenter brand from the United States, was distinctly the largest retailer in the world (Basker et al.), though Amazon surpassed its first-place status in 2019. Global popularity of supercenters stems from several factors: women working

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outside the home, constricting family budgets, lower cost with increased demand for processed foods, increased access to refrigeration, and personal transportation access (Lucan, Gustafson, & Jilcott Pitts, 2012; Reardon et al.2003, 2012; Tallie et al., 2016). In short, bulk buying is possible with, and even suits, a suburban lifestyle—a way of living that has spread internationally (Feng, Zhou, & Wu, 2008; Grant et al., 2013; Tallie et al.). We do not fully know (yet) the impact of grocery supercenters, or suburbanism broadly, on consumption. Access to safe and reliable food is necessary for health, but there are concerns about the impact of supercenters on consumption habits. The presence of Walmart supercenters is related to increased obesity rates and decreased prevalence of adults who consume recommended amounts of fruits and vegetables (Bonanno & Goetz, 2012). Obesity may increase by 2.4% likelihood when another Walmart supercenter is added per 100,000 residents (Courtemanche & Carden, 2011), but additional analyses are needed to rule out alternative explanations. The role of the food environment in obesity is addressed further in Chapter 10.

Morsel: FAFH Consumption In the past two decades, eating meals and snacks outside the home has increased (Gallagher, 2019; Saksena et al., 2018). Researchers distinguish between eating food at home (FAH) and food away from home (FAFH) to track their relative rises and falls. Prior to 2020, families were steadily spending more each year on FAFH than previous years. By one analysis, consumers were visiting restaurants equally or less often, but spending more dollars at those establishments (Rose, 2016). In the United States, the year 2016 was the first in history when households spent more on FAFH compared to FAH (measured by grocery expenditures; US Census Bureau). Compare that to 1970 when less than 26% of household food expenditures were on FAFH. Reasons posed for increased FAFH are time constraints, convenience, and availability of options. Single-parent households spend more money on FAFH than dual-parent households and people in countries with higher gross domestic product (GDP) spend more on FAFH. In these wealthier nations, FAFH expenditure tends to comprise a relatively lower percent of household income (Kavanagh, 2019) even though the absolute expenditure on FAFH is larger relative to other places and past decades (Gallagher, 2019). Managing schedules and “life” may be easier with FAFH, especially quick service restaurants (QSRs), but there are downsides. Eating out usually translates into increased caloric intake and is associated with higher BMIs (Courtemanche & Carden, 2011; Courtemanche et al., 2016). The “bread and butter,” figuratively and literally, of restaurants is high contents of fat, salt, and sugar in foods (e.g., Kunert

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et al., 2013), common in eateries from street vendors (Karimi, Wawire, & Mathooko, 2017) to high-end restaurants. Even when lower-calorie options are available, higher energy-density restaurant offerings can be enticing once in their presence. Butter, lard, and oils—all contributing to taste and satiation—bring back customers, although some consumers are swayed by lower-fat menu options (Fitzpatrick, Chapman, & Barr, 1997; Yi, Zhao, & Joung, 2018). Companies encourage FAFH spending before and during restaurant visits. Customer acquisition depends on word of mouth, which is “talk” among community members occurring increasingly through media, like Facebook and Instagram (Kwok & Yu, 2012). Positive experiences related to food, dining service, and restaurant atmosphere—but not price—are linked to customers’ positive electronic word of mouth (Jeong & Jang, 2010). Conversational and informational posts with images (e.g., menu and updates) are more liked on social media than marketing posts, videos, and external links to web material (Kwok & Yu, 2012). It is particularly important for a restaurant to be authentically represented by social media so that customer expectations align with experience (Yi, Zhao, & Joung, 2018). Inside the restaurant, restaurants can maximize profits through menu design (Pulido, 2018). When items are accompanied by complex descriptions, their perceived quality is higher and patrons are more likely to choose them and expect the item to be costlier (McCall & Lynn, 2008). Thus, restaurant owners can intentionally complicate descriptions for items that yield higher margins. Price anchoring is a relative placement strategy used with mixed effects. A menu with a high-cost item that yields lower margins for owners, such as a prime cut of beef, placed before a lower-cost item that yields larger margins, can make patrons more likely to purchase the relatively cheaper item and contribute to greater restaurant earnings. This is a cognitive bias, sometimes called anchoring bias, where our perception of the second item is affected by initial exposure to a high-priced standard, or “anchor.” Restaurants post-COVID-19. The majority of information provided here addresses restaurant use and success pre-COVID. The pandemic of 2019–2020 drastically changed the restaurant landscape and early data indicate that FAFH dropped with a return to greater expenditures on groceries (Ellison et al., 2020). We are only beginning to understand how restaurants and their patrons will operate in a midand post-COVID world.

Course 2: Food Messages and Beliefs The average person is exposed to over 35,000 messages of product branding in a week. Worldwide, the most recognizable brand logos include several food and

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drink sources: Walmart (#3), Coca-Cola (#8), McDonald’s (#16), Pepsi (#17), and Starbucks (#21; Casella, 2017). Companies aim to break through the crowded market to gain buyer attention in a constantly changing landscape. One way to reach consumers is to attach meaning to products, such that foods and drinks create identities and belonging. Two examples of altered branding are relevant here. Taco Bell, an international QSR, rebranded in 2016 with appeals to health-conscious consumers. Their changes included lower sodium, natural instead of artificial flavors and colors, antibiotic-free chicken, and extended vegetarian and vegan options (Carroll, 2019; Weiss, 2020). Sales jumped 6.7% from 2017 to 2018 by overhauling menu options while retaining their core customer base (Lock, 2020). By comparison, a cost-saving attempt by Coca-Cola in the mid-1980s served to alienate their customer base when it stopped distributing its original formula Coca-Cola to offer New Coke. Consumers were outraged, even forming protest groups, like the “Old Cola Drinkers of America.” Under the pressure of 5,000–8,000 angry phone calls per day, Coca-Cola rereleased its original formula as “Coca-Cola Classic” only months later (Gorman & Gould, 2015; Haoues, 2015). Short-sightedness of Coca-Cola in pulling its top-selling products from shelves is a reminder that products represent more than something to eat or drink— they help define us. The meaning of food as addressed across dimensions in Chapter 1 (Ogden, 2003) is further elaborated through interaction with others. Social groups determine a number of food distinctions and classifications, the most basic being food and nonfood. Food classifications include social foods, such as a national dish like Hungarian goulash, and these classifications occur at several levels of society, from subcultures to family units, to signify identity. What does food communicate to others? What does it “say” or convey? In many cultures, food is a signal of love and care. Caregivers nurture offspring by providing nutrients. In some cultures, people bring food in times of grief, illness, or family strain to signal support. Food also indicates what type of experience, exchange, or interaction is occurring. Children provided sweets, for example, are signaled that this is a time of celebration. Food sharing, known as commensalism, is a significant aspect of many cultures worldwide, and studies confirm that intimacy usually increases as a function of food sharing (Miller, Rozin, & Fiske, 1998). But commensalism is not so simple. For centuries, consumption of similar foods has instilled trust while the explicit passing of food among hands can express cooperation or conflict (Woolley & Fishback, 2016). Food can welcome people, compliment people, or indebt people. Even in offering food, some power is achieved because it establishes implicit obligation to reciprocate. Reciprocity norms exist among many groups and indicate that a person is expected to give back to a person after receiving something. Control of food also can exert power in more explicit ways. Food refusal, for instance, can undermine family meals (Chapter 8), business deals, or social relationships. Long-term refusal—or, fasting—may formally express dissatisfaction with social or political causes.

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Stereotyped Beliefs Food helps define the person consuming it and the culture to which they belong. When observing specific acts of eating or drinking in someone, we often draw general conclusions about them, a tendency called correspondence bias (Gilbert & Malone, 1995). That is, others’ behavior is interpreted as stable and attributed to personality (“Wow, she’s a big drinker” in referring to someone who has over-enbibed on a rare occasion we happen to observe; Gilbert & Malone). Comparatively, variations and contextual factors in our own eating and drinking are recognized and articulated (e.g., “I’m not eating very much tonight because I had a late lunch”). Because observed consumption in others is viewed as stable and permanent, eating and drinking habits are noted and remembered as characteristics of people or groups to which they belong. In other words, observing others eat and drink can lead to stereotypes or beliefs about their consumption. One example is the belief that people in England drink hot tea; for many English, the stereotype may be true but it could be a mistake to assume that a person from England drinks tea (as Author SS once did when she took her British colleague a set of teas for her birthday only to be told that they prefer coffee). Stereotypes comprise the cognitive component of prejudices, or prejudgments, which also include affective and behavioral components. Prejudices are attitudes, or evaluations, toward things, events, or people. We could be prejudiced—forming premature attitudes—toward foods, drinks, restaurants, people, and so on as they relate to consumption. When a restaurant names itself by a particular label, immediate attitudes are formed about the type of experience the restaurant will offer, including its food and drinks. These prejudices can be negative, making us less likely to visit the restaurant, or positive, making the restaurant alluring. Negative prejudices can escalate or manifest in discrimination, the differential treatment of a person or group based on some characteristic or membership. One example is known colloquially as “lunchbox bullying,” and involves children being teased and harassed for bringing particular foods in their lunchbox that do not fit local cultural norms (White, 2011). Media portrayals of consumption and its related products can perpetuate stereotypes and prejudices surrounding consumption. The outgroup homogeneity effect, a tendency to view all members of a group or similar groups as sharing similar characteristics, occurs when there is little interaction between food cultures. An example is a tendency for nonAsians to imagine and picture all Asian dishes to be eaten with chopsticks. Presumed use of chopsticks is an incorrect generalization, or overgeneralization, because people from the Philippines, Indonesia, and several other Asian countries eat with forks. From private food bloggers to large corporations, misrepresentations occur and drive misunderstanding. And overlooked differences among cultures can be offensive (see microaggressions) and maintain stereotypes. Consumption varies a great deal within cultures, or across individuals. Media messages can foster superficial insights or flexible, nuanced, and more accurate perceptions.

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Chew on This: Microaggressions in Food Branding Microaggressions occur when messages subtly work against images, information, or rights of marginalized groups. In 2016, Bon Appetit magazine was accused of microaggressions against Asian cultures when it published a video about the proper way to eat pho that featured a White American chef as demonstrator and claimed “Pho is the new Ramen,” implying that all Asian cultures and cuisine could be lumped together and compared with one “leading trend.”

To combat perpetuated ignorance, government agencies have banned offensive advertising. The Advertising Standards Authority (ASA) of the UK prohibits advertisements that limit viewers’ understanding/perceptions of societal group members based on roles or stereotypes portrayed, lack of diversity, and belittling of subgroups. These new standards were released in 2018 (Tiffany, 2019), the same year Sweden issued similar bans on sexist and racist advertisements posted outdoors (Savage, 2018). Even where bans are not in place, social pressure is encouraging companies to reconsider their brands. For example, Dreyer announced plans to rename its ice cream treat known as “Eskimo Pie,” where Eskimo is a derogatory term imposed by non-Indigenous people for people of Arctic regions, like Siberia and Greenland (Hersher, 2016) and considered inappropriate by most Alaska Natives. Possibly the most hopeful example of progress is in the American beer industry, notoriously sexist in its marketing (Forsyth, 2018). The US Brewers Association banned “sexually explicit, lewd, or demeaning brand names, language, text, and graphics” in advertisements (Forsyth, 2018) and the UK Beer Festival prohibited beers with sexist names (e.g., “Dizzy Blonde”) from its 2019 exhibitions. Worldwide, however, there remain blatantly sexist alcohol products and ads, even in otherwise progressive cultures like Australia (Fridlund, 2019). Beer names like “Raging Bitch” and “Wailing Wench” remind us that work remains to be done in overcoming sexism in marketing of foods and drinks.

Persuading Consumers Social psychologists recognize that exposure alone does not guarantee a person will be influenced by information (Figure 9.2). Persuasion is believed to occur through a central route that relies on logical consideration of information and arguments and/or a peripheral route. The peripheral route, based on cues (e.g., emotional signals) outside and sometimes unrelated to a central message, is the faster route to persuasion but with shorter-lived effects. Peripheral routes of persuasion often are involved in appeals to high-energy foods, like those eaten during celebrations where happy times, smiling

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Figure 9.2  Routes to persuasion. Created by Stephanie da Silva.

faces, and pleasant feelings occur. Celebrity or expert testimony is another way to persuade someone with peripheral cues (Petty, Cacioppo, & Schumann, 1983). Pepsi has employed celebrities from Michael Jackson to Shakira, to Kylie Minogue in global marketing of their soda with little mention of product quality. In fact, criticisms surface that challenge celebrities to consider health impacts of their endorsements. Bragg et al. (2013, 2016) found celebrities overwhelmingly endorse “energy-dense, nutrient-poor products,” which is not surprising because such products with lower nutritional quality must rely on peripheral cues, rather than information, in their ads. It requires more effort to change opinions via the central route, but the change is more likely to persist. This harder-to-achieve persuasion is based on information and requires more effort on the part of the consumer. Children shoppers age 9–13 do not use nutritional information when selecting products and their parents use such information only sparingly, avoiding it if the information is too technical or overwhelming (Norgaard & Brunso, 2009). It is difficult, if not impossible to find marketing strategies that rely purely on logical and rational arguments about a food or drink. Even when there are good reasons to consume a food or drink, advertisers make efforts to elevate the attractiveness of products with peripheral cues (e.g., with product packaging, enjoyable music, heartwarming storyline, or key words such as “new”; Pratkanis & Aronson, 1998). The 1993– 2014 campaign funded by the California Milk Processor Board is an example of blended peripheral and central advertising. The peripheral route is tapped via celebrities, like Elton John, in appealing (fun and attractive) poses with “milk mustaches,” a postconsumption

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white mark left on one’s upper lip, and the 2-word catchphrase “Got Milk?” The central route is accessed through a compelling reason to drink milk. For example, the Elton John ad read, “Want strong bones? Drinking enough low-fat milk now can help prevent osteoporosis later.” Though the Chapter 3 conversation around lactase persistence reveals the limited inclusivity of its message for nutrition, the two-route tactic of “Got Milk?” was so successful that the American milk industry relaunched it as #gotmilk on TikTok in 2020.

Social Norms The messages, implicit or explicit, about food and eating drive social norms that indicate accepted and appropriate behavior, including consumption, of group members (Higgs, 2015). When members of a group share daily rituals and lifestyles, standards for “how to eat” and “what to consume” develop (Stock, 2014). Descriptive norms refer to commonly share beliefs and actions among a group, which serve as signals and guides for behaviors and articulated attitudes (e.g., an observation that most people eat popcorn at the movie theatre or a stated description by someone, such as “Everyone eats popcorn at the movie”; Liu, Thomas, & Higgs, 2019). Prescriptive norms, by comparison, work through social approval and are communicated after behavior or beliefs are shared by someone (e.g., “Oh, yes, you are right that red wine is better with steak” or “Why would you choose that wine?”). Norms can be explicitly maintained by rules or instructions (e.g., minimum age for legal consumption of alcohol), but often are implicitly indicated by actions and statements of others. For instance, someone sneaking alcohol into a wedding reception or saying, “I can’t believe there is no alcohol at this wedding,” implies that alcohol should be a regular part of such a celebration. Norms depend on those with whom you surround yourself as much as the broader culture, in part because norms affect us most when they are internalized and viewed as relevant for the situation. As an example, a society may have strict norms around thinness that are not influential unless peer groups and family adopt and practice that norm (Twamley & Davis, 1999). Norms can influence us whether or not they are legitimate. In fact, it is the perception of a norm that matters as we navigate the world of food (Robinson, 2015). We look to others for information about eating norms to determine socially approved food items and quantities (Robinson et al., 2014). Since our experiences are limited and biased, we create erred norm estimations—a tendency known as pluralistic ignorance. One such example on college campuses involved estimating average comfort level with drinking alcohol. Students overestimated the extent to which their peers (i.e., students generally) are comfortable drinking alcohol (Prentice & Miller, 1993). Actual comfort levels (on a 1–11 scale, where 11 is very comfortable) were 4.68 among women and 6.03 among men, but students of both genders believed the normed comfort level to fall between 7.00 and 7.07.

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In many cases, personal behavior and attitudes shift to align with perceived norms, especially when we value the audience’s opinion(s)/approval. This means that college students—even those who are uncomfortable consuming alcohol—may behave as if they are comfortable with its consumption to fit the normed attitudes they believe exist. Albani et al. (2018), for instance, found pluralistic ignorance among high schoolers who rated healthy and unhealthy foods in terms of something they do not want to eat or something they want to eat often. There was a perception that unhealthy foods are viewed as more appealing among the majority/group, which influenced ratings by individual students. Likewise, in evaluating one’s beliefs, decisions, and behavior relative to perceived norms, judgment errors occur. A consensus bias, or false consensus effect, involves faulty belief that a personal behavior tendency is more common, and thus more socially accepted than it actually is (Ross, Greene, & House, 1977). A person who regularly eats scones for breakfast will overestimate the extent to which others eat scones for breakfast. People who overeat during holiday events are more likely to perceive overeating in those contexts as more common than in reality. Portion size is an example of a norm that influences food offerings and consumption, further supported via the unit bias heuristic (Chapter 6). Portion sizes become normed through varied experiences, such as comments: “I can’t believe that’s all you’re eating; don’t you want more?” A recent rise in outrageous, giant milkshakes is a sweet example. “Freakshakes” seem to have originated in Australia, thereafter spreading to the UK and the United States. Entire cupcakes, ice cream sandwiches, candy bars, cookies, donuts, and more are piled high above a milkshake. (Dare we mention sprinkles, marshmallows, gummy snacks, and other smaller toppings that adorn these shakes?) These assortments average nearly 1300 kcal, the equivalent of two meals per many government dietary guidelines. And Freakshakes rose, or should we say “piled,” into being around 2016, which means they became a global trend in fewer than 5 years. The more common they become, the more likely their sizes—which are double that of traditional milkshakes— become the norm. One way we know portion size is socialized is because portion size effect (PSE) is stronger in older children than younger children, and strongest yet in adults (Rolls, Engell, & Birch, 2000; Rolls et al., 2004). The younger a person, the more likely they are to consume similar amounts regardless of the portion size provided or surrounding physical cues (e.g., size of the table). Let’s imagine the adult and child in the face of a Freakshake. The adult paid four to five times the cost of a traditional milkshake and is faced with a consumption challenge; they are likely to (try to) finish it. The child is less likely to focus on completion of the shake, no matter its initial portion size, and will stop as excitement and hunger deteriorate with stomach bloating and taste satiation. Personal portion sizes are generally larger than recommended by government agencies and scientists (Lewis, Ahern, & Solis-Trapala, 2015). Increased portions in restaurants and store aisles are correlated with increased obesity, leaving the World Health Organization (and others) to conclude that portion size changes in recent decades

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may be responsible for global increases in body weight. Young and Nestle (2003) tracked portion size increases in the United States, noting increases in the 1970s, more drastically shifts in the 1980s, continuing for some products. The only food for which portion sizes did not increase within and outside the home in that time span was pizza (Nielson & Popkin, 2003). Take sodas as an example (Ghorayshi, 2012). At McDonald’s, the original size of a fountain drink in 1955 was 7 fluid oz, roughly 0.21 L. Over 60 years later, in the United States, the medium size drink is 21 oz (0.62 L), three times as large, and a large drink is 30 oz (0.88 L). But portion sizes vary across cultures, another indication that portion size is socialized. McDonald’s drinks are largest in the United States, Canada, and Singapore and smaller in Japan; whereas the size of a serving of French fries is largest in Japan. Some redeeming news is that portion sizes generally have stabilized and even reversed in the last 10–20 years. A pinnacle of serving size occurred around or shortly after 2010 and currently there is a downward trend in food size obtained when buying a product (mind you, for the same price). This trend is dubbed “shrinkflation.” According to the UK Office for National Statistics (2017), between 2012 and 2017, 2529 products decreased in size while only 614 products increased in size. Commonly shrunk products include ice cream, coffee, and chips. Mars, Inc., for example, decreased the sizes of Mars and Snickers bars. In the United Kingdom, the single chocolate bar size decreased from 62.5 g to 58 g, in 2009, and further to 48 g in 2013 (Hills & Poulter, 2013). In Australia, a similar reduction from 60 g to 53 g occurred for the Mars bar while comparable shrinkage in Snickers bars occurred in the United States. Skeptics argue that serving sizes were decreased to cut costs, especially with rising expenses of chocolate production. Whatever the motive, consumers—and their waistlines—may benefit from smaller portions or the implication that the larger size is meant to be shared (Mann, 2015). Norms also exist for the numbers, types, and orders of courses at a meal (Robinson, 2015). In France a small salad may be consumed between the entrée and dessert, but salads comprise the meal starter or entire meal in the United States. Soup is a “steeped” tradition of meals in Russia and China (Chen, 2009) that also tends to curb total calorie consumption in a sitting (Flood & Rolls, 2007). In southern China, lo foh tong, translated as “old fire soup,” identifies a variety of slow-cooking broths believed to have medicinal impacts. Sweetened breads are a main staple of breakfast in the United Kingdom (Yates & Warde, 2015) and whole grain varieties are more commonly consumed with lunch proteins in Mediterranean regions. It is easy to see how these norms become a way of life and influence consumption for many people.

Course 3: The Presence of Others Stimulus Enhancement and Social Facilitation Stimulus enhancement refers to attention drawn to stimuli in our surroundings. For consumption, locations where food is accessed, prepared, and consumed can be

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enhanced by others’ use of them and foods themselves can become enhanced via cues they have been consumed. When parents or conspecifics (i.e., other members of the same species) eat in particular areas, rats and fowl are more likely to eat in those same areas, even when other equally palatable feeding sites are available (Galef, 1981; McQuoid & Galef, 1992). Nonhumans also attend to stimuli correlated with others’ eating; turtles, for example, are more likely to approach and eat food from a food source that they watched another turtle use (Davis & Burghardt, 2011; Galef, 1981; Krebs, MacRoberts, & Cullen, 1972; Suboski, 1989; Visalberghi & Addessi, 2001). Food sources can be enhanced through odor cues as well (Munger et al., 2010; Valsecchi & Galef, 1989). These stimulus enhancement effects lead to altered attraction to and preference for particular food sources, including prey encountered and later pursued. It is not hard to imagine how stimulus enhancement extends to humans gathered around a food truck, flocking to the newest restaurant, or accessing snacks from cupboards of a kitchen. We tend to eat more in the presence of others (de Castro & Brewer, 1992; de Castro, 1990) and spend more time at the table when dining with others, giving us extra time to consume. These tendencies exemplify a classic social facilitation effect in that behavior is facilitated, or maximized, by the social context (Clendenen, Herman, & Polivy, 1994). Keep in mind, however, social facilitation effects vary based on level of arousal and mastery of the task. On a first date, for example, a person might be so nervous that they eat and drink more slowly than normal. Add to that any novelty or challenge, such as a new restaurant or food, and consumption can be inhibited by the presence of another person. Heightened self-monitoring interferes with consumption in such a situation. Once comfortable with people and context, the presence of others tends to arouse us and provide distraction in a way that increases our eating.

Social Networking: “Birds of a Feather …” Folks with similar interests, lifestyles, and proximity to each other often share similar styles of eating and drinking. And, with the advent of social media, shared consumption extends to acquaintances who never share a meal. Nearly half of all food consumers learn something about food through social media. Anthropologists and social psychologists have referred to the spread of attitudes and habits through a culture as social contagion. It occurs on larger scales, at the level of subcultures, and in smaller friend groups or tribes. Body weights, for instance, are more similar among friends, and people sharing tables in restaurants eat more similarly to each other relative to people eating at different tables. In interpreting these similarities, keep in mind that we do not have experimental evidence showing that the group membership exists prior to development of consumption patterns. Social network analysis demonstrates the spread of obesity status across shared social ties over 30 years of the obesity epidemic (Christakis & Fowler, 2007). Group members

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may affiliate based on lifestyle (e.g., food selection and activity levels), bringing with them particular tendencies, although it is likely that at least some contagion results in habits influencing others in the circle. Among all social relationships, including friends and siblings, spouses have the most similar eating practices, which makes sense since spouses likely share the most meals and share a food environment (Pachucki, Jacques, & Christakis, 2011). Adolescent friends are likely to share fast-food consumption and binge eating habits (Fletcher, Bonell, & Sorhaindo, 2011; Goldschmidt et al., 2014), as found among college sorority members (Crandall, 1998). Specifically: (1) binge eating differed across sororities such that one sorority socially supported moderate amounts of binging while another sorority socially supported high levels of binging and (2) the probability of binge eating when an opportunity arose increased across semesters, meaning that binge eating fell more in line with sorority habits the longer that a student was in a sorority. Alcohol use and snack consumption are most similar and influential among peers (Pachucki, Jacques, & Christakis, 2011), while “healthier” eating patterns are the least influential among peers. So, that cake you bring with you is likely to impact others more than fresh celery.

Conformity and Obedience The presence of others may present opportunities to conform to their menu selections, utensil choice, and whether or not you decide to order alcohol. If someone tells you directly to try something, your likelihood of trying it increases to obey their social request. This means the types of foods you eat are directly impacted by others, what they say and do. Find yourself at a gathering where everyone else is only picking at hor d’ourves, and you probably will not eat much even if experiencing hunger pangs. But when attending a party where others are eating large plates of fatty foods and consuming alcohol, you are more likely to follow suit. More explicit statements, such as “You need another drink” or “You must try…!” demand what should be consumed per the rules in a particular setting or group. Household meals are just one example of situations where strong rules exist for eating. When, what, and how families eat are socialized early. Author SS is reminded of her mother who insisted the 3- to 6-year-old grandchildren eat with utensils at her dining table; meanwhile, at home, they generally ate with their hands. To imagine household influences, think about how your consumption would differ if you lived alone or in a family unit. First, you would be more likely to eat when ready—as opposed to, let’s say, rules regarding family or cultured meal times. Second, you would tend to prepare only the food you are interested in eating. When eating with others, you prepare a larger variety of foods to accommodate varied tastes of those present. Third, you are prone to pay more attention to your consumption without the distraction of other people. These factors can help explain why married individuals are at greater risk for gaining weight (Eng et al., 2005; Meltzer et al., 2013).

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As with other behaviors, conformity of eating is not restricted to shared group membership or close familiarity. When college students were tested in a lab with unknown peers who ate available vegetables, they ate more vegetables (Hermans et al, 2009). Conversely, when tested with peers who ate fresh chocolate chip cookies or peers who resisted the chocolate chip cookies, participants’ consumption of the cookies was influenced in the direction of their peers’ choices to consume or not consume. Perhaps most interestingly, the participants maintained their choices to eat or resist the cookies when they were later presented the cookies alone (Howland, Hunger, & Mann, 2012). This latter effect illustrates normative influence, social pressure created from a norm or rule.

Course 4: Kid Foods—A Microcosm of Social Influence As a final course of this social psychology meal, the invention and impact of kid foods are examined as an illustration of social factors in food and eating. One hundred years ago, there were no “kid foods;” there was just food and children ate the same things as adults. Over time, it was realized that children provide powerful avenues to adult expenditures and, to boot, that children are less capable of critically evaluating commercials to discern valid information (Livingstone & Helsper, 2006), hence the invention of food and drink products for children. Given susceptibility of children to advertisements, Norway and Sweden banned advertisements during children’s shows while other countries, like Korea, Canada, and Australia, limit the number of food ads for children to decrease exposure and enticement (e.g., use of cute cartoon characters). In most places, branding of kid foods occurs readily during children’s programming, though its content and frequency vary across cultures (e.g., high frequency of sweets advertisements appear in Greece and high frequency of fast food advertisement appear in the United States; Lobstein & Dibb, 2005). We now turn to two particular products aimed at children, ready-to-eat cereals (RTECs) and restaurant menus, to illustrate the social reasons and rises of the kid foods industry. Children’s Cereals. The first ready-to-eat-cereal (RTEC), Granula, was created in 1863 (Severson, 2016). RTECs in terms of purpose, content, and preparation have not changed much in their 150-year history. They are precooked, processed for long shelf life, packaged in cardboard boxes, and consumed dry or with milk in a way that makes them “ready to eat.” A timeline of major cereals includes Corn flakes in the early 1900s, Rice Krispies and Wheaties in the 1920s, and Cheerios in the 1940s (Severson). As early as 1948, RTEC makers began adding sugar to the product and marketing to kids, yielding the first children’s cereals. Frosted Flakes (1950s) and Lucky Charms (1960s) were launched, and many others, like Count Chocula and Fruity Pebbles (1970s), followed. Beyond the colors, sugars, and blatant inclusion of chocolate, marshmallows, and sweet coatings, there were characters created to appeal to children, like “Tony the Tiger” for

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Frosted Flakes. Some cereals took explicit aims at children, like Trix cereal whose ads contained a rabbit being told: “Silly rabbit! Trix are for kids.” Although children’s cereals shifted away from whole grains to sugars (as much as 43% sugar by weight), their packaging, ironically—or perhaps as intentional compensation— contains more “healthy” messaging than adult cereals that contain more nutrients (Song, Halvorsen, & Harley, 2014). One study (Elliott, 2019) analyzed contents of kid foods in grocery stores of Canada in 2009 and 2017, finding little to no nutritional changes in that time. Over 88% of kid foods in grocery stores fell short of the WHO Nutrient Profile Model for Marketing to Children. Only the sodium levels of the kid foods decreased from 2009 to 2017, with sugar and fat contents remaining similar. Contrary to the contents of these kid foods, nutritional claims on the fronts of these product packages increased nearly threefold from 2009 (when 31.4% contained a nutritional claim) to 2017 (when 86.6% contained a nutritional claim). It appears that makers of kid foods realized the impact of supplementing a traditional peripheral, emotional message for kids with a central, logical message for the adult purchasers (Figure 9.3). Outside store aisles, RTECs are marketed to children on TV and Internet more than any other food (Alvy & Calvert, 2008; Powell, Szczypka, & Chaloupka, 2007), and children’s cereals are 13 times more likely to be purchased if they are advertised (compared to a fourfold increase in adult cereal purchases with marketing; Castetbon, Harris, & Schwartz, 2012). Concern around children’s RTECs center on encouragement of sugary foods to children and the message that different foods exist for children and adults. Recommended self-regulation by companies have left small, if any, marks on the marketing landscape (Harris & Kalnova, 2018), such that marketing high-sugar foods will continue if companies are left to their own devices. With the rise in social media, product

Figure 9.3  Nutritional quality and nutritional messaging of kid foods in Canada 2009 and 2017 (Elliott, 2019). Created by Stephanie da Silva based on Elliott (2019).

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placement in vlogs and other streamed information, promotion of unhealthy foods to children is unlikely to change any time soon. This is not to say that RTECs generally are “bad” for individuals and societies. Consumption of any RTEC is common worldwide, especially in Europe and North America. For example, roughly 90% of schoolchildren in Poland consume RTECs with milk for breakfast and over 40% eat RTECs with milk for snack (Winiarska-Mieczan et al., 2016). RTECs have solved problems regarding food insecurities and malnutrition because they are fortified with nutrients like vitamin D, cheaply made, and distributed across long distances, portable, and easily consumed. Within-country comparisons reveal that children who consume RTECs are more likely to consume higher amounts of nutrients in a day. The best cereals nutritionally (with potassium, calcium, and magnesium) are bran and wholegrain cereals, though fewer than 30% of children consume these cereals. Over 80% of children prefer sweetened cereals, and the nutritional value of most RTECs is minimal unless eaten with milk (Winiarska-Mieczan et al.). Relatedly, packaging of RTECs can lead caregivers to believe they are providing a more nutritious breakfast than they are. When comparing RTEC consumers to children who eat meat and eggs for breakfast or who skip breakfast, RTEC consumers have relatively lower BMI (Cho et al., 2003). Other studies also found lower BMI among RTEC eaters (Albertson et al., 2009; Barr, DiFrancesco, & Fulgoni, 2016), but there are limitations of their outcomes. Albertson and colleagues found relatively lower BMI and LDL cholesterol in boys who eat RTECs (compared to boys who do not) but they studied only children with LDL above the 80th percentile, making it a skewed comparison for RTEC eaters. Barr, DiFrancesco, and Fulgoni (2016) reported lower BMI among RTEC eaters compared to adults who eat other types of breakfasts, but prevalence and likelihood of being overweight was no different among RTEC and other-breakfast eaters. The point is that, when comparing RTEC to high-fat breakfast or no breakfast, RTECs appear harmless, if not a helpful and convenient option. Problems with RTEC are that their nutritional value falls short of what is possible nutritionally if children instead consume fresh fruits, vegetables, and whole grains. Children’s Menus. A second player in major shifts from “food” to adult and kid food as subtypes is children’s menus. Prior to women’s rights movements in the UK and elsewhere, children were rarely seen in restaurants and were with mothers or women caretakers who were not permitted to dine in most public dining establishments (with some excluding women until the mid-1900s!). With more women dining out and with increased acceptance of children in public spaces, the turn of the 20th century saw restaurants develop menu items of smaller portions and smaller costs to serve family needs (Haley, 2009). Not surprisingly, then, the earliest children’s menus appeared in department stores (e.g., in 1916 at Marshall Fields in Chicago, IL, USA) where women could be found shopping with children in tow. By the mid-1900s, women were outside the home more often and their children were eating in places other than the home.

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Today, Harrods department store boasts a Disney café, illustrating the extent to which scores and restaurants now appeal to children and families. Chicken nuggets—a fried handheld snack for kids—have been around since the 1950s. Burger Chef, a now closed QSR in the United States, created the first kids’ meal containing a dessert and toy. It would be difficult to find any American restaurant franchise, especially among QSRs, that does not currently offer a kid-friendly meal. Even some higher-cost establishments provide smaller and cheaper options for children. As FAFH increased in recent decades, there was pushback to make children’s menu items healthier (McCluskey, Mittelhammer, & Asiseh, 2012). But there seems too much profit in child marketing for elimination of kid foods. Children 12 and under are estimated to spend USD 25 million per year on food and drink products, but they drive spending of another USD 200 billion per year. Nearly 2 billion dollars per year are spent for sweet and salty drinks and snacks. With that purchasing power, it appears that “kid food” is here to stay as parents, schools, and other consumers purchase child-friendly items to create smiles, attract consumers, and elevate profits (Story & French, 2004).

Dessert: Chocolate Croissants—The French Paradox In the 1990s researchers recognized a paradox among the French (Opie, Lamont, & Lecour, 2011; Renaud & de Lorgeril, 1992). Though they consumed high quantities of saturated fats similar to amounts eaten in other industrialized nations, French men had about one-third the mortality from cardiovascular heart disease of men in other fatconsuming nations. There were many possible culprits in dietary habits of the French that folks examined for their heart-protective effects. One explanation was that French consume cheese, but not other dairy products. Another was that French eat few prepackaged or overprocessed foods. Maybe it is because the French do not snack between meals (“graze”) or that their biggest meal occurs at lunch. In the end, red wine—a staple of French meals—was identified as the protective factor. Some early studies (e.g., Renaud & de Lorgeril, 1992) indicated that moderate, consistent wine consumption among the French could combat heart disease by preventing platelet buildup and adhesion, a precursor of heart disease, although the protective effect seemed to happen at high concentrations of alcohol in the wine (de Lange et al., 2003). In the past 30 years, increasing evidence suggests health benefits of light-to-moderate wine consumption include increased insulin sensitivity, decreased oxidative stress, and increased high-density lipoprotein (HDL) cholesterol (Lippi et al., 2010). And these effects are particular to red wine, a combined result of polyphenols, grape skins, and the alcohol itself (Stanley & Mazier, 1999). Unfortunately, there are two potentially misleading messages of this paradox. The first is a message about diets rich in saturated fats, such as cheese, chocolates, cream, and red meats. Reports of the French paradox nearly implied that any fatty diet is okay so long

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as you drink wine with it. It could be destructive to think that adding saturated fats, like cheese and chocolate croissants, to your diet to “be like the French” will improve your health. The French do, however, have habits that could be helpful to someone aiming to better regulate their eating. They tend to eat slowly, savoring food, and have little guilt over food enjoyment; they eat fresh rather than processed and packaged foods; and they eat lighter meals later in the day. If one were to glean dietary advice from the French paradox, it should focus on these facets—not the cheese. French also consume smaller portions (Rozin et al., 2003), something we discussed at length earlier in this chapter. A second messages is about red wine consumption and its potential for reducing risk of heart disease in countries of high prominence (Higgins & Llanos, 2015). When red wine is consumed in large quantities, it works against heart health. Cardiovascular disease risk is greatest among heavy drinkers, followed by nondrinkers, and then light drinkers. The medical community is hesitant, particularly in cultures valuing abstinence (Peele, 2003), to issue blanket recommendations to consume red wine for cardiovascular benefit. 1. Consumers often overestimate the size of a glass of wine, which is 5 oz or roughly 147 mL. Even physicians report difficulties in understanding recommended units of consumption (Lopez Santi et al., 2018). Most contemporary red wine glasses hold around 415 mL (and some hold as much as 449 mL, 60% of a liter!), compared to 66 mL in the 1700s (Zupan et al., 2017). As we discussed, consumption increases as the containers used to allocate portions increases, and some estimate that 25% reductions in glass sizes could lead to 40% reduction in consumption (Kersbergen et al., 2018). Filling a modern glass half-way already reaches a 200 mL threshold for cardiovascular benefits. Have a second glass of the same size and you will be close to Heavy Episodic Drinking (HED), or what is sometimes called “binge drinking.” Current standards for HED are roughly 5 drinks, with each drink containing 8–14 g of alcohol (Jackson, 2008). Drinking half a bottle (325 mL) or a whole bottle (750 mL) through dinner will not produce the heart benefits as 1–2 glasses (less than 300 mL per day). Other physical effects (e.g., liver damage and immune suppression) of moderate-toheavy wine consumption beg the question of whether the potential heart benefits are worth their risks in cases where consumers do not regulate their intake well. 2. Individuals differ in gains from drinking red wine. The benefits of drinking wine occur most for middle-aged women and men, challenging the recommendation to consume wine for other age populations. Further, coronary improvements from red wine may vary across regions, where natives of Mediterranean countries (e.g., France, Spain) benefit from drinking red wine to a greater extent than do people from other regions, like Scandinavia (Guallar-Castillon et al., 2001; Poikotainen, Vartiainen, & Korhonen, 1996). Worldwide wine consumption has increased in the past 50 years from greater availability and affordability of wine. In the UK, wine consumption quadrupled between 1960 and 1980, and then doubled from 1980 to 2004. In the United States, table wine

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increased from under 50 gallons per year in the 1950s to over 600 gallons per year in 2010. But Italy and France still are the highest per capita wine consumers in the world (Consumer Goods & FMCG, 2018). Once again, we see the power of social networks on consumption. Alcohol is linked with health detriment to a much greater degree than health benefit. Education regarding safe, moderate wine consumption may provide health benefits in many countries or social circles (Guilford & Pezzuto, 2011). To “be like the French” thus requires we consider the ecology of eating and apply lessons from this chapter to moderate portion sizes and wine consumption.

Dining Review Key Elements

Recommended Reviews

Whet your appetite: Is eating contagious

Discuss with your peers how you learn about new foods and when and why you attempt new recipes. Is the source of information socially mediated?

The amuse-bouche: Among

Think of a fad diet trending in your community. What is its mechanism of growth and maintenance? What social support do you see at work in its success?

social networks Course 1: Ecology of eating

Identify your various food environments, and then apply ways that your surroundings are affected by other people in ways that direct your consumption.

Morsel: FAFH consumption

Have you ever tracked your spending for food at and away from home? It is a useful exercise, exposing habits, tendency toward consumerism, and ways to save. What variables do you think affect FAH and FAFH most?

Course 2: The presence

Discuss ways that you have observed food habits and alcohol consumption travel in circles. What have you noticed when a new restaurant opens in town?

of others

marketing

Spend some time watching current advertisements for children’s cereals. Are they persuasive via central or peripheral routes? Explain.

Dessert: The French Paradox

What are the risks of extrapolating the French Paradox? Connect this to the critical thinking encouraged in Chapter 2.

Course 3: Media and

Gochisousama Thanks to the chefs! Recommended Reading ●

Bentley, A. (2014), Inventing baby food: Taste, health, and the industrialization of the American diet, University of California Press.

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Galef, B. G., Jr. (2005), “Social learning,” in I. Q. Whishaw & B. Kolb (eds.), The Behavior of the Laboratory Rat: A Handbook with Tests, pp. 363–70, Oxford University Press. Murcott, A. (2019), Introducing the Sociology of Food & Eating, Bloomsbury.

Glossary Anchoring bias:

a mistake in thinking that occurs when information is judged according to (or “anchored” by) information provided before it

Attitude:

an evaluation of something or someone involving three components: cognitive, affective, and behavioral

Central route:

slow acting, rational mode of persuasion that involves conscious processing of information or claims

Commensalism:

food sharing

Consensus bias:

faulty view of one’s behavior as being more common among others, or a greater comparison group, than it actually is

Discrimination:

mistreatment or differential treatment of a person or group based on specific characteristics or group membership

Outgroup homogeneity effect: tendency to view members of a group to which we do not belong as more similar than they are; failing to see subtle differences among individuals of other groups to which we do not belong Overgeneralization:

incorrectly extending a rule or belief about a trait or person beyond its reach or actual relevance

Peripheral route:

fast acting, emotional mode of persuasion; may be illogical and subconscious

Prejudices:

a prejudgment; premature evaluation, or attitude, toward an object, event, or person

Reciprocity norm:

often implicit, a cultural expectation that acts of kindness or proved benefits will be likewise returned by those who receive them

Social contagion:

a spread of attitudes or behaviors across people

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Social facilitation:

behavioral disruption from heightened arousal caused by the presence of other people

Social norms:

rules or accepted behavior among group members that may be implicitly or explicitly shared

Stereotype:

a belief that members of particular groups share characteristics, abilities, or tendencies

Stimulus enhancement:

the drawing of attention to an object or place that results in more interaction with that object or place by an observer

Chapter 10 Overnutrition and Public Health Whet Your Appetite: The Labels of Shape How do we determine our own ideal weight and shape? Some people rely on numbers on the scale, and others focus on the fit of their clothes, appearance, or even their activity level. Our self-perceptions commonly echo the terms and labels applied to describe shape, from thin or fat to pear-shaped or curvy. When shopping for clothing, descriptions of the size and shape of the garments, and how they fit on our body, further influence perception and language around self and shape. In this chapter, the challenging landscape of overnutrition is navigated with consideration of the contributing factors, correlated stigmas and outcomes, and future directions toward mitigation and acceptance from the perspectives of psychology and public health.

Menu Amuse-Bouche: Weight Stigma Course 1: Patterns and Prevalence Defining and Detecting Obesity Health Risks of Overnutrition and Obesity The Global Obesity Epidemic Course 2: How Did We Get Here? Etiology of Overnutrition and Obesity Biopsychological Contributions Gene–Environment Interactions Obesity as a Contemporary Phenomenon The Food Addiction Debate Stress, Resources, and Health Disparity Course 3: Interventions Interventions Targeting Physiology and Metabolism Dieting and Exercise Pharmaceutical and Surgical Treatments Modifying Our Social Environment

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Psychological Considerations for Interventions Dessert: Body Positivity Dining Review Gochisousama Glossary

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Amuse-Bouche: Weight Stigma In a typical day, as we move about the world, we receive multiple cues about standards for body size and shape within the environment. From the size of restroom stalls to the shape of chairs, these cues typify norms for appearance and body size. The potential for social norms to influence eating, described in Chapter 9, informs our discussion of weight stigma. Standards of beauty persist surrounding diverse shapes and sizes, despite efforts to interrogate sociocultural norms for appearance like the “thin ideal” in media and advertising. Add to this pervasive thin messaging and contentious policies, such as airlines requiring travelers of a specific size to purchase two tickets, and the conversations can contribute to weight stigma and personal shaming. The rapid increase in obesity rates in the past four decades suggests social and environmental influences, rather than individual characteristics, are to blame. Yet weight stigma and discrimination are widespread, from healthcare settings, to the workplace, media, and educational institutions, arising from harmful stereotypes related to the conditions of overweight and obesity. Weight stigma and discrimination beget a cycle, as being victimized by negative prejudices can increase stress and isolation, undermine selfregulation, and contribute to physical inactivity and/or emotional eating (Tomiyama, 2014). The anecdote to weight discrimination is body positivity, emerging in social media and cultural discourse, and now an area of academic inquiry. This movement challenges the dominant idealized body image to foster acceptance of all body shapes and sizes (Sastre, 2014). Recent advances in equity and fat acceptance call into question the weight-related terminology used in healthcare settings (Puhl, 2020) as obesity is a highly stigmatized condition. In 2013, the American Medical Association formally recognized obesity as a disease (Pollack, 2013), thus providing motivation to use language and terminology that enhances respect. Given the global prevalence of the conditions of overweight and obesity, weight stigma itself presents a significant hurdle to improving population health and wellness.

Course 1: Patterns and Prevalence The term obesity is used to describe a condition characterized by excess body weight and fat accumulation presenting a risk to health. Obesity is considered a heterogeneous,

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or varied, condition as it does not always present in the same manner, at the same developmental period, or from the same causes. The simplest explanation is that obesity results from positive energy balance due to overnutrition, or overeating. This explanation, however, fails to account for nuanced factors leading to a surplus energy intake, addressed with the biopsychosocial approach.

Defining and Detecting Obesity The conditions of overweight, obesity, and overnutrition can be operationalized in several ways. The Centers for Disease Control and Prevention (CDC) describes overweight and obesity as body weight greater than what is considered healthy for one’s height, and the World Health Organization (WHO) definition emphasizes excessive fat accumulation that presents a risk to health. In contrast, overnutrition is a form of malnutrition, characterized by the excess consumption of food and nutrients to the point of adverse health consequences such as accumulation of body fat, overweight, and obesity (WHO, 2012). These definitions emphasize body composition, and body mass index (BMI) is a common screening tool for overweight and obesity in both children and adults. Obesity is indicated with BMI over 30 kg/m2, and overweight is defined as BMI of 25.0 to 29.9 kg/ m2. Recall from Chapter 2, BMI indicates body proportions, and the relationship between BMI and adiposity varies by age, sex, and ethnicity (Camhi et al., 2011; Vanderwall et al., 2017). BMI does not specifically measure adiposity, so alternate screening tools such as waist-to-height ratio are superior for discriminating obesity-related health risks in diverse populations (Ashwell, Gunn, & Gibson, 2012) and they are equally feasible to calculate, requiring only a tape measure. As people come in all shapes and sizes, detection of overnutrition as a health risk is more complicated than use of BMI cutoffs.

Health Risks of Overnutrition and Obesity It is difficult to overstate the adverse impacts of overnutrition on population well-being. The WHO estimates 4 million people died in 2017 due to health consequences from overweight and obesity. In their analysis of health data from nearly 200 countries, Afshin and colleagues (2019) identified poor diet, characterized by overconsumption of processed foods high in sodium with underconsumption of whole grains and fruits, as risk factors accounting for half of the deaths and two-thirds of the disease burden globally. Suboptimal diet is the leading cause of death in the world. In the United States, obesity is estimated as the second leading cause of preventable death (Yoon et al., 2014). Although BMI is an imperfect metric of health, BMI is correlated with fat mass (60–90%) and serves as a predictor of mortality (Prospective Studies Collaboration, 2009). This collaborative analysis of over 50 studies including 900,000 adults indicates lowest risk of death for BMI 22–25 kg/m2, and a 30% increased risk of all-cause mortality for each 5 kg/m2 increase in BMI above 25 kg/m2.

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The health consequences of overnutrition are described as “metabolic syndrome,” a constellation including central obesity (around the midline of the body), insulin resistance, type 2 diabetes (T2D), and hypertension that increase the risk for cardiovascular disease (Eckel, Grundy, & Zimmet, 2005). Both the metabolic changes of obesity and the increased fat mass itself contribute to these risks (Bray, 2004): ●

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The longitudinal link between lifestyle, obesity, and coronary heart disease is well established (Hubert et al., 1983). Coronary events (heart attacks) are a substantial risk, but the harmful cardiovascular effects of obesity extend to hypertension, heart failure, embolism, stroke, and increased risk of hospitalization (Murphy et al., 2005). Obesity increases risk for several cancers, notably colon, renal, pancreatic, and postmenopausal breast cancer (Vucenik & Stains, 2012), worsens prognosis of all types of cancer, and increases risk of cancer-related mortality (Calle et al., 2003). Excess adiposity increases risk for neurological diseases and cognitive decline. Risk for Alzheimer’s disease, the leading cause of dementia in the United States, is doubled in obese compared to normal weight individuals (for review, see O’Brien et al., 2017). Increased fat mass has implications for joint pain and mobility, increasing risk for arthritis, plus gastroesophageal reflux and obstructive sleep apnea (Bray, 2004). The weight stigma and discrimination experienced by folks who are overweight or obese can lead to unfavorable mental health outcomes (Andreyeva, Puhl, & Brownell, 2008).

The consequences of overnutrition for morbidity and mortality establish the need for early detection, but use of BMI cutoff points for the conditions of overweight and obesity fails to detect health behaviors early enough to avoid these risks, even when implemented in children (Ikeda, Crawford, & Woodward-Lopez, 2006). In public health, the term “primary prevention” is used to describe efforts to stop disease (or injury) before it occurs and screening to detect a disease early is considered to be secondary prevention (Hoelscher et al., 2015). The spread of the obesity epidemic as described in the next section demonstrates the lack of efficacy of our screening practices.

The Global Obesity Epidemic You have undoubtedly heard of the obesity epidemic, a term used to describe the spread of obesity as a disease among many individuals at the same time. From 1999 to 2018, the prevalence of obesity in the United States increased from 30.5% to 42.4% of the adult population (CDC). Globally, from 1980 through 2010, overweight and obesity increased by 27% in adults and 47% in children, and now the prevalence of overnutrition exceeds undernutrition in every region of the world (Lobstein et al., 2015). Childhood obesity is increasing fastest in developing countries, up to 30% more than developed countries (WHO). Children with obesity face similar consequences to adults, from metabolic syndrome to psychological harm from bullying and body image disturbance, thus screening for overnutrition and obesity occurs during medical checkups.

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The rapid increases in global rates of overnutrition and subsequent burden of disease exacerbate inequality and health disparity. The population distribution of overweight and obesity is uneven as children and adults from racial and ethnic minority groups and those with fewer socioeconomic resources experience increased prevalence and severity of disease (Kumanyika et al., 2012) and have less capacity to bear the medical care costs associated with obesity. Rather than a narrow, individual psychological perspective, the epidemic is best understood by integrating social and public health data.

Course 2: How Did We Get Here? Etiology of Overnutrition and Obesity In the four decades of the obesity epidemic, the investment of considerable time, efforts, and money into research to curb the impacts of obesity reveals the complexity of this phenomenon. The etiology of overnutrition and obesity is described below to inform discussion of obesity interventions later in this chapter.

Biopsychological Contributions Positive energy balance is an influence on becoming overweight and obese; thus, it is imperative to interrogate the roles of homeostasis, metabolism, and energy regulation in the etiology of obesity. The control of energy homeostasis is accomplished by a redundant and complex system that evolved to potently stimulate hunger, motivate eating, and ensure survival (Berthoud, 2002). Homeostatic assumptions, such as the glucostatic and lipostatic perspectives, argue the availability of glucose or fat (respectively) drives energy consumption and expenditure. But the mechanisms of hunger and satiety are more complex than simple detection of macronutrients (see Chapter 4). This perspective is eroded by evidence that energy regulation, and thus weight, is determined by external and contextual factors beyond homeostasis. People eat in discrete meals rather than continuously, and intake of energy, macronutrients, and micronutrients varies each day. A period of overeating (several weeks in a laboratory setting) is not followed by a compensatory reduction in calorie intake, but rather a return to baseline feeding (Chow & Hall, 2014). In contrast, the settling zone theory accommodates non-homeostatic influences in eating (Levitsky, 2005). Rather than a discrete optimal body weight, physiology sets a range of possibilities. The contemporary prevalence of obesity is evidence for factors beyond homeostatic processes in the role of obesity, as weight is more likely to increase than decrease within a settling zone (Mann et al., 2007). Advances in biopsychology and behavioral neuroscience provide a more compelling explanation of eating than traditional homeostatic approaches (Smith, 2000). In both the rare cases of genetic-induced obesity and the predominant phenotype of diet-induced obesity (described in Chapter 4), overnutrition is explained by increased meal size rather

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than increased meal frequency (Smith, 2000; Farley et al., 2003). The role of increased meal size points to a problem of signaling or sensing of feedback provided by satiety signals. During the course of a meal, the orosensory properties of food first provide positive feedback to keep eating. Once sufficient calories and nutrients are ingested, fullness is signaled by peripheral signals including the activation of mechanoreceptors plus neuropeptides like cholecystokinin (CCK) and peptide YY (PYY). This negative feedback projects to the brainstem and then to higher brain regions to stop eating. Serotonin (5-HT) promotes satiety by decreasing meal size and duration through reciprocal regulation with gut–brain neuropeptides, as serotonin decreases the hunger signals NPY/AgRP and augments satiety signals like melanocortins to curb intake (Lam et al., 2010; Voigt & Fink, 2015). Reduced signaling of or responsiveness to negative feedback can explain ingestion of larger meals. Most evidence for this approach to obesity focuses on insulin and leptin, which under normal circumstances work together to regulate energy stores and metabolism (Schwartz & Porte, 2005). Neurons of the hypothalamus are responsive to insulin and leptin levels (Abizaid, Gao, & Horvath, 2006) and with ample fat stores, insulin and leptin inhibit energy intake. Yet both insulin levels (Bagdade et al., 1967) and leptin levels (Halaas et al., 1997) increase during obesity. This may seem paradoxical, but it reveals the function of these signals to prevent starvation and the resistance to their feedback for satiety. Insulin resistance is the defining feature of T2D, as both peripheral tissues and neurons become resistant to the elevated levels of insulin. Similarly, individuals who are obese have increased plasma leptin, yet it fails to communicate satiety in the brain. Leptin and insulin resistance occur in the rare cases of gene-induced obesity (e.g., the ob mouse, Figure 4.1) and the more common diet-induced obesity. Leptin and insulin resistance were once believed a consequence of obesity, but a better explanation is that aberrant brain processing of nutrient-related signals and energy storage catalyzes events leading to excess adiposity and eventually obesity (Schwartz & Porte, 2005). Exposure to hyperpalatable foods and subsequent overconsumption sets into motion a pathological cascade of cellular signaling plasticity. Plasticity allows us to make adaptive adjustments, regulating food intake based on our current nutrient status and our energy stores (Morton et al., 2006). Remember the organization of the arcuate nucleus favors positive energy balance consistent with the evolutionary explanation (see Figure 4.4). When the arcuate NPY/AgRP neurons are activated, they promote feeding and inhibit satiety signals (Dietrich & Horvath, 2013). In response to food deprivation, feedback upregulates the excitatory input to NPY/AgRP neurons to promote synaptic plasticity (Yang et al., 2011). High-fat diets and treatment with leptin also result in synaptic reorganization of the cells in the arcuate nucleus (Dietrich & Horvath, 2013), and the insulin resistance of T2D involves changes in the responsiveness of the arcuate neurons (Morton et al., 2006). Plastic responses to highfat diet favor positive energy balance (Horvath et al., 2010) and impact food reward

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signaling, essentially releasing the “brakes” on eating (Rossi et al., 2019). This “soft wiring” of the hypothalamus, characterized by synaptic plasticity based on metabolic and hormonal inputs, is determined by gene–environment interactions and helps account for the outcome of obesity as a response to the modern food environment.

Gene–Environment Interactions Genes are involved in both gene-induced and diet-induced instances of obesity, but dietinduced obesity is only weakly heritable. Given that the obesity epidemic is a relatively recent phenomenon, it is unlikely obesity results from changes in genetic predispositions since the human gene pool has not drastically changed in one or two generations. Yet a seminal study showed parental obesity is the strongest risk factor for childhood and adolescent obesity (Reilly et al., 2005). This predictive relationship is complicated, as families share genes, learned associations with food (Chapter 7) and the food environment (Chapter 9). Heritability can contribute to obesity through monogenetic, polygenetic, and epigenetic mechanisms. ●

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Monogenetic causes of obesity are studied by genome-wide association studies (GWAS) that scan for variations shared among people as a marker for a specific condition or disease. Over 200 genetic loci associated with obesity have been identified (Speakman et al., 2018). Monogenetic obesity is rare but provides insight to the causes and potential treatments for obesity. In a polygenetic pattern of inheritance, a single gene variant has little effect on the phenotype; rather, the combination of predisposing factors is considered (Hinney, Vogel, & Hebebrand, 2010). This polygenetic pattern makes sense given the observable variability across people in traits contributing to metabolism, energy level, and eating habits such as appetite and our tendency to watch what we eat, called dietary restraint. Nutrition provides the building blocks for proper methylation, the most common form of epigenetic change guiding the functional distinction of cells early during prenatal development. Epigenetic modifications have been identified for leptin, NPY, and insulin genes (Milagro et al., 2013). As maternal nutrition is a modifiable variable, these examples illustrate the potential for prevention of metabolic disorders caused by epigenetic mechanisms and, perhaps in the future, treatment options.

Obesity as a Contemporary Phenomenon The current food environment is characterized by availability and convenience of hyperpalatable foods; thus, it is obesogenic as it contributes to surplus of energy intake, overnutrition, and the conditions of overweight and obesity. Fast food and ready-to-eat convenience food exemplify ultra-processed hyperpalatability, with long ingredient lists

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designed to keep the consumer wanting more. How does the type of food consumed influence subsequent eating and health? Consider the only randomized controlled trial (RCT) investigating the outcomes of a diet high in ultra-processed foods (Hall et al., 2019). The researchers randomly assigned 20 adults to receive either an ultra-processed or unprocessed diet for 2 weeks in an inpatient setting, and for the subsequent 2 weeks the other diet. In addition to the robust design, this study is notable for its use of a simple and inexpensive unprocessed diet. For instance, breakfast one day consisted of prepared brand-name oatmeal with almonds and blueberries and dinner was a stir fry meat from the freezer section with rice, broccoli, and orange slices. In contrast, the ultra-processed breakfast included a sugary cereal and packaged blueberry muffin and the dinner was canned chili with all the fixings (cheese, chips, sour cream, and salsa), canned peaches (in syrup), and diet soda. Participants were instructed to eat ad libitum, as much as they like, and had access to snacks in both conditions. Participants in the ultra-processed condition consumed approximately 500 more calories per day, with the difference mostly accounted for by increased carbohydrate consumption. In other words, the characteristics of the food consumed impacts subsequent eating behaviors. During the 2 weeks of the ultra-processed condition, participants gained approximately 1 kg (not accounted for by baseline differences in BMI). This seems rather minor but imagine the weight gain over the course of 1 year if this pattern is sustained. Yet during the unprocessed diet portion of the study, participants lost weight while reporting similar fullness and satisfaction with their meals. Significant evidence supports the cumulative effect of small but significant increases in daily energy consumption during the course of the obesity epidemic, particularly of refined sugars and soft drinks (Finkelstein, Ruhm, & Kosa, 2005).

Morsel: Reward and Food Porn As author LC composes this section, she pauses to scroll through social media, greeted by many images of food (and funny pets) as our interests guide the accounts followed. These food pics are flawless—a perfect swirl of glossy gelato, a plump shortcake piled with whipped cream and macerated strawberries, chorizo and potato tacos with a juicy lime wedge, and a filled donut perfectly dusted with sugar from her favorite shop. All are displayed on beautiful ceramic plates, tilted just so by a delicate hand sporting a fresh manicure. This is food porn, images of food at its most appealing, a term entered in UrbanDictionary. com in 2005. Where and how often do you encounter highly pleasing images of yummy food? The images matter, as food appearance including gloss and shape alters expectations for the taste of the food (Delwiche, 2012). The function of the reward system elucidates why pressures to eat are difficult to combat, but this explanation

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does not necessitate a dysfunction or problem within an individual. Rather, the reward hypothesis for obesity identifies the environment geared for overconsumption, easily activating hedonic overeating. The availability of hyperpalatable junk foods, including food images via advertisements and environmental cues, promotes hunger via ghrelin signaling (Schüssler et al., 2012), primes automatic eating behaviors (Harris, Baugh, & Brownell, 2009), and augments reward to promote further wanting and overconsumption (Berridge et al., 2010). Scrolling through food porn activates hedonic hotspots, especially when hungry (Berridge et al., 2010), and the orbitofrontal cortex to enhance motivation to procure food (Wang et al., 2004). Dysregulation of the reward system is hypothesized in many instances of overconsumption, from drugs to gambling to overeating. The positive-incentive perspective, introduced in Chapter 4, explains the brain’s attribution of incentive salience to food rewards (Berridge et al., 2010) via dopamine signaling after periods of overeating palatable foods. Unfortunately, foods high in calories and fat augment reward valuation (DiFeliceantonio et al., 2018), as early dopamine release in reward areas of the brain correlates with the immediate sensory properties of tasty food as a reflection of food wanting (Thanarajah et al., 2019). Neurobiological evidence suggests that regular consumption of highly palatable foods typical of the “Western diet” augments motivational wanting and overeating. And those beautiful food images have the potential to boost wanting and motivate a snack or treat after a quick break to scroll.

The Food Addiction Debate The escalation of the obesity epidemic kindled a debate around the potential for food to be an addictive substance, and experts in nutrition, health, and food studies have emerged as vocal proponents on both sides. A similarity between drugs and food is the variability in reward value; note most evidence for food addiction comes from sugar and highly palatable foods, typically intensely sweet or rich, high in sugar, other carbohydrates, and/or fats. The biopsychological evidence for the role of the reward network in pleasure, eating, and addiction is well established. Palatable foods trigger dopamine release in reward networks discussed in Chapter 4, including the VTA and NAcc (Avena et al., 2008), and sensitize dopamine receptors (Colantuoni et al., 2001). The reward circuit is especially responsive to palatable foods high in both fats and carbohydrates (DiFeliceantonio et al., 2018). Palatable foods also activate the endogenous opioid system (Drewnowski et al., 1992) and limbic system circuitry similar to drugs of abuse (Colantuoni et al.). Neuroimaging evidence shows craving-related patterns of activity in obese participants, specifically in the insula and frontal cortex (Wang et al., 2006).

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There are three main arguments against the legitimacy of food addiction: 1. Food is essential for survival, unlike nicotine, alcohol, and other drugs. 2. Obesity is a modern affliction while food is certainly not; difficulties with overconsumption are unique to our contemporary world. 3. Craving and overeating occur for all people in some circumstances; calling food addictive and endorsing the diagnosis over-pathologizes ordinary life. Unlike drugs of abuse, processed foods likely have multiple ingredients with addictivelike properties (Gearhardt et al., 2011). Kima Cargill (2017) argues additives, engineered by food companies to be sweeter, saltier, and tastier than anything found in nature, deliver the hedonic properties of these foods. Similarly, Graham Finlayson (2017) and other researchers credit hedonic overeating to the mismatch between evolutionary preference for energy-dense foods and modern patterns of consumption. These arguments are especially compelling as they acknowledge the risk of casting food as a dangerous substance and further complicating human relationships with food. Furthermore, focus on highly processed food shifts blame from the individual person to the big food industry, a notorious contributor to the obesogenic nature of the modern environment.

Stress, Resources, and Health Disparity The modern environment is often stressful, whether it be daily hassles and time pressure, or more significant traumas, economic inequality, and systemic racism. Whereas moderate adversity promotes resilience and the ability to respond to stressors (Seery et al., 2013), significant stress negatively impacts physical health and wellness, including eating. Humans react in a variety of ways when responding to interpersonal, financial, work, or other strains. Although some folks (about 20%) do not change their eating habits when stressed, individuals above normal weight tend to increase weight in stressful periods, and those who are normal to underweight tend to under-eat in times of stress (Dallman, 2009). Perceived stress typically promotes eating, particularly of palatable foods that activate the reward system, as hedonic self-medication results in stress reduction (Adam & Epel, 2007). Stress and negative emotions are cognitively demanding, producing cognitive load by occupying attention, executive function, and mental capacity. Cognitive load enhances susceptibility to food advertisements (Zimmerman & Shimoga, 2014) and leads to disinhibited eating, particularly in participants high in dietary restraint (Ward & Mann, 2000). The conditions of overweight and obesity have increased globally; however, there are observable differences by socioeconomic group (Ball & Crawford, 2005) and ethnicity (Ogden et al., 2006), representing disparity internationally (Blüher, 2019). This stratification is explained through pervasive systematic inequalities in the United States that trigger stress and adverse health outcomes (Bailey et al., 2017), including obesity (Siervo, Wells, & Cizza, 2009). The adverse impacts of overnutrition on health further

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exacerbate health disparity, from medical expenses to absenteeism at work (Finkelstein et al., 2005). Maternal and early life stress, including malnutrition, abuse, and neglect, are associated with lower socioeconomic status (SES) and are predictors of increased long-term adiposity (Milagro et al., 2013). The epigenetic modifications described earlier are heritable changes in gene expression and thus explain how the diet or environment of our parents and grandparents can influence later health outcomes in later generations. The observable health disparities are associated with neighborhood factors such as presence of food deserts and swamps, which confirm the well-defined gradient between SES and diet quality (Darmon & Drewnowski, 2008). Availability and convenience vary dramatically by geographic region and SES. Consider neighborhood-level characteristics— access to food and healthcare, plus amenities like green space opportunities for physical activity all impact health. The types of food retailers present influence food cost, food choice and thus energy balance, food security, and even diet-related health outcomes (Morland & Evenson, 2009; Black & Macinko, 2009). It would seem that access to grocery stores and markets with affordable fresh produce and lean proteins predicts lower obesity rates, but—unfortunately—this relationship is unclear as these types of stores cluster in more affluent neighborhoods in many high-income countries (Morland et al., 2002). In contrast, many lower-income neighborhoods face a scarcity of grocery and fresh food options, with greater dependence on convenience stores to purchase food (Pearson et al., 2005). These areas are referred to as “food deserts” for their lack of access to healthy options. Living in a food desert increases risk for obesity, even when controlling for features of the home food environment (Chen, Jaenicke, & Volpe, 2016). As discussed in Chapter 9, “big-box” supercenters can impact nearby food systems by making food more available, with the immediate effect of decreased food insecurity. Decreased food prices are estimated to account for over 40% of the increased BMI during the 1980s and early 1990s in the United States (Lakdawalla & Philipson, 2002). Supercenters encourage one-stop shopping with more nonperishable items and fewer fresh foods purchased (Taillie, Ng & Popkin, 2015). Oftentimes, supercenters are situated in commercial areas surrounded by fast food options. Researchers have termed areas with excessive fast food and unhealthy options as “food swamps” in contrast to food deserts described above (Rose et al., 2009). Geographic proximity to a food swamp is a stronger predictor of obesity than lack of grocery store options (Cooksey-Stowers, Schwartz, & Brownell, 2017), and frequently food swamps arise to fill an opening in an area that previously lacked food retailers. The economics of overconsumption include the cost of products in addition to proximity of the market. An inverse relation between energy density and cost of food items is documented well in the United States, Australia, and the Netherlands (Darmon & Drewnowski, 2015). White bread and cookies are more affordable than lean fish and fresh produce. The economic hypothesis for obesity argues high energy intake is associated with affordability of energy-dense foods and thus overnutrition (Drewnowski & Specter, 2004). Unfortunately, this gradient in energy density and cost has worsened over time; in

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relation to the consumer price index, fresh fruits and vegetables have become comparably more expensive while sugars, sweets, and sugar-sweetened beverages (SSBs) more affordable (Brownell & Freiden, 2009). Households with less income are more likely to purchase energy-dense foods such as SSBs (Valizadeh, Popkin, & Ng, 2020), and may have less time for meal preparation, thus consuming foods with higher energy density (Sarmugam & Worsley, 2015). Time constraints feed impulsivity and may encourage fewer and larger shopping trips to supercenters; add in stress and a limited budget, and folks are more likely to buy and keep convenient, processed foods (Jabs & Devine, 2006). The economic hypothesis for obesity is compounded by Westernization of diet, exemplified by the underconsumption of fruits and vegetables, overconsumption of ultraprocessed foods and animal proteins (Malik, Willett & Hu, 2013), and highly palatable foods rich in saturated fat and refined sugar but low in fiber. This is not exclusive to rich industrialized nations and contributes to obesity-related diseases in low- and middleincome countries (Drewnowski & Popkin, 1997). The pronounced shift in the global food environment influences food choices to increase the risk of the obesity and the associated health consequences.

Course 3: Interventions The evidence presented thus far provides multiple avenues for interventions to decrease overweight and obesity, yet many efforts are directed solely at individuals while omitting social and contextual influences. These limited intervention efforts are wildly disappointing as they expect the individual to change regardless of the larger-scale, societal factors in play. The most successful interventions are those that address the various biopsychosocial contributions to overnutrition and the related health consequences (Figure 10.1).

Interventions Targeting Physiology and Metabolism Interventions for obesity that are biological in nature target energy balance or feedback signals of hunger and satiety to promote weight loss via diet, exercise, pharmaceuticals, or surgery.

Dieting and Exercise When people want to lose weight, they typically attempt dieting or exercise, targeting energy balance by decreasing energy intake and/or increasing energy expenditure. Dieting, the intentional limiting of energy intake for the purpose of weight loss or weight maintenance, is rather ubiquitous. In the United States, 99% of survey respondents reported making some dietary change in their lifetime like eating more fruits and vegetables (Chapman & Ogden, 2010). Hill (2017) estimates 40–60% of women and 20–40% of men are currently trying to lose weight, though only a subset of those are actively dieting. The variety of

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Figure 10.1  A diagram of the biological, psychological, and social contributions to overnutrition. Created by Leighann Chaffee.

diets and the subsequent market for related products is vast, forecasted for $206 billion globally in 2019. The challenge with identifying an optimal dietary intervention is that each person needs something different. Preferences, culture, resources, and biology all impact whether or not an intervention is practical and efficacious. Some people swear by the miracle of low-carbohydrate diets (Ebbeling et al., 2018) and others find low-fat diets work just as well (Gardner et al., 2018). Hall and colleagues’ (2019) study on ultra-processed diets described previously in this chapter demonstrates that the type of foods consumed matter, but rigorous dietary interventions are understudied and difficult to execute. Relative to diet studies, there is far more economic investment in pharmaceutical research such as clinical trials for a new drug. After all, most people will more readily take a pill once per day than change their diets, and diets require long-term changes in contrast with the quicker fixes provided by drug treatments.

Morsel: The False Promises of Dieting Despite the massive market for dieting products, our global health status indicates no sign of their efficacy. Dieting claims and food cults abound, from swallowing tapeworms in the early 1900s (not advised) to the cabbage soup diet of the 1950s and the more recent wave of green juice recipes, these ideas are not new yet

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remain trendy. Diets succeed initially in their capacity to produce an energy deficit and subsequent, also usually short-term, weight loss. We are constantly bombarded with advertisements, influencers, and products for dieting and health, but promises made by dieting programs rely on pseudoscience (see Chapter 2). One common scheme employed to sell them is use of sciency buzzwords and phrases, like antioxidant and detoxifying, to mislead consumers with invalid claims. Anecdotal evidence for miracle diet cures is also rather common, where individual success stories are displayed without credible support. One reason these anecdotes are so appealing is they are relatable, visually powerful, and lack context. To this latter point, dieting promotions omit two key elements: (1) all the dieting failures and (2) challenges of the process. Without this contextual information, consumers are unable to determine general success rates of the dieting program and unable to see “what they are signing up for” in terms of food restrictions or increased energy expenditures. Claims regarding food effects such as the power of a specific food for weight loss can grow via social mechanisms, described in Chapter 9, into the latest diet trend. The Sirtfood Diet (Goggins & Matten, 2001), made famous by celebrities, claims that consumption of foods activating specific genes (Sirt1, involved in a broad range of physiological functions including metabolism and aging) help curb appetite and enhance metabolism. Combined caloric restriction and consumption of specific foods comprise the underlying strategy for this diet. However, the foods include blueberries, arugula olive oil, kale, and green tea—those we know as “healthy” regardless of diet. You can see how the diet contains just enough scientific basis to convey its supposed validity and trustworthiness. Adding spinach to your smoothie to make green juice is rather harmless, but there are risks associated with dieting. Some argue dieting programs should face the same rigorous clinical trial system as pharmaceuticals (Nestle, 2007), especially in light of some documented adverse effects. In 2020, warnings about the F-Factor diet circled on social media, countered by claims of defamation by the diet’s creator (Rosman & Ellin, 2020). The website for the Food and Drug Administration plus the blog of Marion Nestle post notices about potentially dangerous dieting. Especially in folks who are very active or have preexisting conditions, calorie deficits deplete energy, causing fatigue and irritability, or adverse medical effects. Why would someone risk their health using an untested dieting program? Unfortunately, the pursuit of thinness rather than health is a key motivator for dieting (Calder & Mussap, 2015), and many dieting ads appeal to a culture of thinness. Given the challenges of traditional diets described thus far and the lack of consensus from experts on the “best” or most efficacious dieting program, we empathize with the appeal of a promised quick fix.

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Our propensity for obesity illustrates the evolutionary advantage of a “deference” to weight gain (Morton et al., 2006). Engaging in calorie restriction to lose weight is fought by adaptations, including the slowing of resting metabolic rate, to maintain weight for survival. This propensity to regain lost weight was highlighted by outcomes of the popular reality television show “The Biggest Loser” also referred to in Chapter 9. There was significant variability in outcomes, but most of the 14 contestants who participated in follow-up assessments regained the weight they lost during the competition (Fothergill et al., 2016). The participants showed metabolic adaptation to weight loss, with a suppression of resting metabolic rate by approximately 500 calories per day at follow-up (compared to their baseline). Unfortunately, this pattern of physiological offset holds true across dietary interventions. For example, diets commonly recommend high-protein, low-carbohydrate energy intake. A dietary increase in protein to 30% total calories (even without cutting carbohydrates) enhances satiety and decreases energy intake, likely due to enhanced brain sensitivity to satiety signals (Weigle et al., 2005). Yet, high-protein diets can be counterproductive as failure to consider the specific source of protein results in increased risk for cardiovascular disease (Lagiou et al., 2012). When an RCT is used to test the efficacy of a plant-based, low-fat diet as compared to “ketogenic” diet high in animal protein content and low in carbohydrates, participants in the low-fat, plant-based diet group consumed significantly less total energy and dietary fat than the low-carbohydrate, high-protein group, yet there was no significant difference in fullness or satisfaction (Hall et al., 2021). Although, in this study, the ketogenic (high-protein and low-carbohydrate) diets reduced glucose and insulin levels, the ketogenictype diet is associated with adverse outcomes and cardiac risks (in animal models and human tissues, Xu et al., 2021). A large review study showed little support for long-term outcomes of calorie restriction and a lack of consistent evidence that dieting improves health (Mann et al., 2007). The metabolic adaptations noted above are confirmed by other researchers, which backs the argument that changes in diet are rarely adequate and must be multifaceted endeavors, incorporating increased movement and moderated use of alcohol to be sustained over years to support any chance of weight loss (MacLean et al., 2011). Another way to target energy balance is through increased expenditure, and exercise is a common component of attempts at weight loss. Similar to diet, there are abundant options for exercise, with significant variability in individual responsiveness (Hammond et al., 2019). The physical and psychological health benefits of exercise are numerous in addition to weight control. However, some folks worry exercise increases appetite and question whether exercise supports weight loss despite fairly robust evidence that exercise (of sufficient vigor and duration) supports weight loss and maintenance (e.g., Jakicic et al., 2008). Sustained exercise can decrease fat mass and increase lean muscle, which improves resting metabolic rate and insulin regulation (Blundell et al., 2015). These changes accompany greater sensitivity to appetite feedback signals, curbing hunger and augmenting satiety (Blundell et al., Evero et al., 2012). So, why do questions of the efficacy of exercise to effect body weight remain? First, light and moderate exercise may not produce a sufficient energy deficit to impact weight,

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hence the importance of proper exercise intensity. In fact, many studies of prescription exercise programs for weight loss prescribe a smaller energy deficit than similar programs of dietary restriction, a significant limitation in comparing the caloric restriction versus expenditure for weight loss (Catanacci & Wyatt, 2007). More problematic is the role of compensatory health beliefs described in Chapter 6, which is the idea that poor health behaviors can be compensated for by engaging in a behavior of health promotion, or vice versa (Knäuper et al., 2003). It is certainly acceptable for people to sometimes engage in less-than-optimal behaviors related to health, such as enjoying a favorite dessert or rich meal, but consistently justifying overnutrition adds up over time. Imagine the instance of large lunch from a fast food establishment (easily topping 1000 calories) compensated by adding a 30-minute walk after dinner (a maximum of 300 calories). To summarize, exercise can be a helpful mechanism for sustained body weight maintenance but the exercise should be of sufficient intensity and duration and there should be caution in assuming that engaging in such exercise allows for dietary splurges. Thoughts and cognitions in addition to compensatory health beliefs impact adherence to the program. Applying social cognitive theory (Bandura, 1998) to health promotion, the realization of one’s goals (e.g., diet and exercise programs), in part, depends on a person’s beliefs that they can successfully complete the action (self-efficacy expectations) and can reach their desired result (outcome expectations). Positive cognitions, like having a goal, facilitated exercise and healthy eating, but negative thoughts and feelings impeded these behaviors (e.g., in young adult cancer survivors, Wu et al., 2015). Unfortunately, people routinely underestimate the enjoyment of physical activity, demonstrating a forecasting bias evident across various forms of exercise (Ruby et al., 2011). This effect is driven by a myopic focus on the beginning of the workout, expected to be the most unpleasant part. Ruby and colleagues (2011) found by simply prompting participants to think of all parts of the workout, the expected outcome of enjoyment increased as did participants’ intentions to engage in exercise.

Chew on This: Exercise to Train Your Brain Perhaps you have heard that exercise is beneficial for cognition and synaptic plasticity (e.g., Cotman & Berchtold, 2002). Physical activity has nuanced impacts on eating behavior that vary across individuals, but the reduction in fat mass and increase in fat-free mass (muscle) increase responsiveness to satiety signals (Blundell et al., 2015). Is this finding also explained by plasticity? Periods of interval training (on a cute treadmill built just for lab rats) evokes synaptic reorganization in the arcuate nucleus, with an inhibitory effect on the NPY/AgRP hunger signals, and an excitatory effect on the POMC-expressing neurons (He et al., 2019). A single bout of exercise produces these neurally mediated effects on hunger and satiety, and repeated exercises enhance this cellular mechanism, reinforcing the influence of exercise on metabolism.

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Diet and exercise are essential components of any intervention for obesity and considerations for overall health. But the barriers to dieting and exercise programs are numerous and many are quite obvious. Consider the investment of time and money when adjusting diet and physical activity (Drewnowski & Eichelsdoerfer, 2010). Both can be quite costly. Additionally, the onset of a restrictive diet or a tough exercise program has the potential to be unpleasant, which may further erode the ability to follow the plan and the efficacy of diet and exercise revealed by high dropout rates of these programs (Catanacci & Wyatt, 2015).

Pharmaceutical and Surgical Treatments In the 1990s, the diet drug Fen-Phen rose in popularity and it was prescribed to millions, mostly individuals frustrated with traditional dieting and exercise. Though it was widely popular and successful for weight loss, Fen-Phen increased risks for the severe side effects of hypertension and valvular heart disease and was thus withdrawn from the market in 1997 (Wadden et al., 1998). Fen-Phen serves as a warning of the dangers of diet medication, but discovery of its mechanism of action by stimulating serotonin (5-HT) release in the arcuate nucleus to promote satiety signaling (Heisler et al., 2002) motivated the development of other pharmaceutical options for weight loss. Serotonin has multiple mechanisms, promoting satiety through interactions on brainstem neurons and by antagonizing arcuate NPY/AgRP neurons (see Figure 4.4). Because serotonin receptors have actions relating to cardiovascular function, cardiac side effects are common among subsequent serotonergic drugs developed for weight loss prompting their eventual removal from the market (for review see Adan, 2013). There is potential to target central appetite hormones via neurotransmitters and also the challenges in developing a safe and efficacious drug for weight loss. Let us now explore three other approaches among the variety of pharmaceutical treatments: ●

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The widely used drug Orlistat, which acts in the body rather than the brain, limits the absorption of dietary fat consumed rather than impacting appetite or satiety. This drug reduces weight by under 3 kg in 1 year, but it has a high rate of discontinuation for unwanted gastrointestinal side effects (Padwal & Mujumdar, 2007). Drugs targeting the endocannabinoid system are a new potential target given the function of this system in pleasure and appetite (see Chapter 4). A cannabinoid receptor (CB1) antagonist, rimonabant, was approved in Europe in 2006 for the treatment of obesity but caused depression and anxiety and, therefore, was removed from the market in Europe and was never approved in the United States (Di Marzo & Després, 2009). It is hypothesized that patients who are avoiding palatable foods and taking rimonabant to lose weight experience a withdrawal-like syndrome, as heightened cannabinoid signaling in the amygdala causes negative emotional symptoms (Blasio et al., 2013). A recent clinical trial for the drug semaglutide, an analogue for glucagon-like peptide-1 (GLP-1), shows promising efficacy for weight loss when paired with lifestyle

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intervention (Wilding et al., 2021). This drug is used to treat diabetes because GLP-1 functions to decrease blood glucose levels by enhancing insulin function. Potential barriers to its success are similar to the other treatments discussed, including longterm maintenance, gastrointestinal side effects, and cost. Given the redundant and complex neurobiological system governing consumption, it is of no surprise that a drug acting on one signal is rarely successful, particularly given the feedback failures associated with positive energy balance. While pharmaceutical interventions are enticing in their ease of use, there is unfortunately (yet) no magic antidote for obesity. More recently, surgical interventions like gastric bypass have been developed for cases where obesity presents a significant threat to health and vitality. Bariatric surgeries include a variety of procedures; for review, see Baptista and Wassef (2013). There are risks associated with surgery, but these procedures result in significant weight loss (compared to a nonintervention group) and decreased medical complications associated with morbidity (Adams et al., 2012). Immediately after surgery appetite ratings are low and dietary adherence is high, and weight loss is facilitated by strict limitations on the quantity of food that can be consumed due to the alterations in gastrointestinal track. Then, 1 to 2 years post-surgery, more active cognitive control of weight loss is required to prevent return to presurgical eating habits originally leading to overnutrition (Bryant et al., 2020). The parallel initial improvements in quality of life may diminish over time with adverse impacts on mental health (Adams et al., 2011). The patterns of initial improvements followed by obstacles merit sustained nutritional and psychological support for patients after their bariatric surgery. Bariatric surgery can improve quality of life (Sarwer et al., 2010) and decrease healthcare costs (Sampalis et al., 2004), yet only a small percentage of individuals who are eligible follow through with the procedure due to risks and costs (English et al., 2018). The variability in success of biological interventions for weight loss makes obvious the importance of integrating psychological and social perspectives.

Modifying Our Social Environment The biopsychosocial model for overnutrition and obesity provides rationale for comprehensive programs to target the social context surrounding the behaviors contributing to overnutrition, affected by policies and regulations, organizational strategies, healthcare settings, and educational campaigns, in addition to individual knowledge and skills. Modifying the larger obesogenic environment acknowledges the global food system as a main driver of the condition of obesity and its epidemic status (Blüher, 2019) and shifts responsibility from the individual to the corporation and government authority to protect population health. As an example, policies restricting or banning food marketing toward children have become more common, now enforced in Chile,

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Turkey, the UK, Uruguay, Taiwan, and others (Taillie et al., 2019). Regulations and policies should address convenience of hyperpalatable foods and costs of healthful alternatives like fresh produce (Lowe & Levine, 2005; also see Chapter 6). Price policies may take the form of a sin tax, for example, on SSBs, similar to those on tobacco, alcohol, and now marijuana products. Though we emphasize taste as the most important determinant of consumption, price does matter (Powell et al., 2012). One argument against price increases is disproportionate impact on lower-income households, though evidence shows this is not the case for food and beverage price policies (Sassi et al., 2018) as low-income consumers receive substantially more health benefits with indirect effects via lower healthcare spending, demonstrating they are not regressive taxes. Sin taxes only address one aspect of cost, thus “thin subsidy” price policies are suggested to make fresh produce and lean proteins more accessible. This approach is less rigorously tested with empirical methods; however, there is evidence indicating a thin subsidy increases fresh food consumption with the most robust effects in low-SES households (Cornelson, Mazzocchi, & Smith, 2019). To consider food costs more broadly, the high price of produce and low price of processed foods is partially explained by agriculture subsidies primarily supporting high-calorie foods such as processed commodities derived from corn, wheat, and soybeans. Agriculture subsidies are widely accepted as a contribution to the obesity epidemic in the United States (Ludwig & Pollack, 2009) and Europe (Elinder, 2005), thus driving international food prices. Perhaps more imperative is reducing economic and resulting health disparities. Differences in disposable income by SES means not all consumers are privileged with the same degree of food choice (Drewnowski, 2009) or opportunity for access to healthy food and safe physical activity (Black & Macinko, 2009). Any chance for reversing trends in obesity will require sustained intervention. Gortmaker and colleagues (2011) and other research groups recommend a systems perspective with straightforward recommendations. They prioritize policies to improve the food and “built environment” with increased funding for prevention programs, emphasizing the importance of leadership from governmental and health agencies, population health monitoring, and embedding actions within health and non-health sectors. The recommendations were integrated into the WHO strategies and United Nations policy, yet regional implementation is variable and undermined by more immediate threats to population health, resistance from commercial industries, and lack of adequate resources. Our own knowledge can empower us in small ways to promote health for ourselves and our community; however, insufficient prioritization of population health and wellness continues to compromise most efforts to abate this epidemic.

Psychological Considerations for Interventions Lowe and Levine (2005) posited that “the most relevant question is not why so many people in developed countries are overweight but why everyone is not overweight.”

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With the assumption that an individual is following a diet to meet their needs for a safe and active lifestyle, we can interrogate psychological influences on (the lack of) weight loss success. When a person experiences food restriction, whether from dieting or the experience of hunger, they become focused on food (Polivy, 1996). Evolutionary success of humans was dependent on valuing immediate gratification such as a palatable snack over future rewards, known as delay discounting (see Chapter 4 and 8). Yet many people are unaware of this tendency and overestimate the ability to resist temptation, experiencing a “cold–hot empathy gap” (Fisher & Rangel, 2014), introduced in Chapter 6. For instance, when planning a diet in a neutral (cold) state, the capacity to resist temptation in a hungry (hot) state is overestimated. Dieters experience a cognitive conflict between goals and behaviors, demonstrating a dissociation of evaluations, with positive immediate implicit attitudes toward high-calorie foods conflicting with negative explicit evaluations of the same foods (Hoefling & Strack, 2008). Palatable food monopolizes motivation and attention: individuals who are chronic dieters have an attentional bias toward food-related cues, like advertisements and nutrition labels (Polivy & Herman, 2017). Dieting also makes it likely someone perceives deprivation from eating less than they want, even in the absence of caloric deficit (Lowe & Levine, 2005). A dieter might remove temptations from their home environment to reduce exposure to treats they intend to avoid (Appelhans et al., 2016) and incorporate their favorite foods in a small amount or for special occasions to avoid feelings of deprivation (Polivy, 1996). These strategies also require successful self-regulatory skills up to the task of perpetually avoiding hedonically driven eating in the obesogenic environment. Appelhans et al. (2016) propose a model of temptation management based on avoiding temptation and resisting the urge to act impulsively in the hot state supported through self-regulatory commitment strategies. Recall from Chapter 4 the motivational model for self-control asserts that our confidence in resisting temptation predicts our success. Bear in mind, resisting temptation through active suppression of cravings demands far greater executive function capacity than broader policy interventions: for instance, targeting SSB consumption through soda taxes does not require commitment by an individual. Promoting health and enjoyment, rather than discouraging or stigmatizing certain patterns of eating, is a promising approach. Consider the oft-touted health benefits of the Mediterranean diet, exemplified by fresh produce, olive oil, and, of course, wine. The foods have alluring qualities due to the fat content from rich olive oil and cheese, and commercialized images of the Mediterranean diet conjure vacation and relaxation. In contrast to the Western diet, there is greater consumption of fruit, vegetables, legumes, whole grains and fish, yet less red meat and processed foods (Willett, 2006). The success of the Mediterranean diet is supported by Afshin and colleagues’ epidemiological study (2019) reporting the importance of promoting optimal diet through encouraging varied intake of fruits, vegetables, and whole grains, rather than focusing on reducing sugar and fat intake. Additional factors can elevate enjoyment of eating without adding calories including shared meals, cooking, and eating until content but not overfull (Rozin, 2005).

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Collective cultural action can embrace proactive policies to foster a focus on health (over dieting) and intentional and enjoyable food selection (over sacrifice). The evidence provided in this chapter provides clear argument against individual responsibility, evoking blame and weakness, as the dominant explanation for obesity.

Dessert: Body Positivity Weight discrimination and bias have significant consequences, in the workplace and healthcare setting (Puhl & Heuer, 2011), actually increasing risk for obesity (Sutin & Terracciano, 2013) and even decreasing life expectancy (Sutin, Stephan, & Terracciano, 2015). The explanation of obesity as a function of individual responsibility in eating too much and exercising too little produces weight stigma and associated consequences for physical and mental health, and personal responsibility narratives contribute to consistently stronger bias toward people with a higher body weight in a multinational sample (Puhl et al., 2015). Personal responsibility accounts of obesity are challenged via movements for body positivity and fat acceptance. Body positivity messaging is now mainstream and promotes acceptance and lack of prejudice, but some members of the health care community worry that this messaging normalizes obesity and its related health risks. This area of research is relatively new, and the potential for body positivity efforts to reduce weight stigma, discrimination, and their negative consequences for individuals and groups is unknown. Implementation of these strategies is not uniformly successful: one well-known marketing campaign promoting body positivity was criticized for depicting only traditionally attractive Caucasian women, and viewing these advertisements led to both positive and negative emotional experiences (Kraus & Myrick, 2017). Social media, which is an uncontrolled communication platform, plays an important role in promoting body positivity, as the nuance of personal experience and the touching nature of human stories are lost in academic discussion of overnutrition and public health; one such story is recommended in the ancillary materials for this chapter. Early evidence shows that cultivating social media streams for exposure to content emphasizing body positivity may encourage adaptive health behaviors such as partaking in activities with a focus on functional benefits like improving strength and mood (Cohen, Newton-John & Slater, 2020). The Health at Every Size movement provides opportunities for self-education and networking (Association for Size Diversity and Health, 2020). Without this intentional presence, however, filtered posts, camera angles, comments, and memes perpetuate thin ideals and marginalization of larger body sizes. Research on the fat acceptance movement suggests that beyond working toward personal self-acceptance, personal dedication to social change may improve body experience and psychological well-being (McKinley, 2004). Advocate and writer Aubrey Gordon, of the pseudonym Your Fat Friend (2020), suggests individuals can break the cycle of shame and negative evaluation within ourselves through radical compassion (the

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imperative to offer inclusive empathy and kindness to all, including the self), recognizing the sources of pressure and our own internal biases, diversifying our social media feed and sources of information.

Dining Review Key Elements

Recommended Reviews

Whet your appetite

Reexamine the question of your ideal body now that you have finished this meal proper. What perceptions and labels around body size and shape were involved in promoting your ideal?

The amuse-bouche

What consequences are associated with weight stigma? Define body positivity and describe its role in combatting the thin ideal.

Course 1: Patterns and prevalence

Differentiate the terms overnutrition and obesity. Describe the time frame and characteristics of the obesity epidemic. For further exploration, track the epidemic geographically across regions and connect it with food availability by region.

Course 2: Etiology

Use the concepts described in this section to diagram the individual and societal contributions to overnutrition

Morsel: Food porn

Develop an experiment to test the impacts of viewing attractive images of food on feelings and/or behavior.

Course 3: Interventions

Find examples of a comprehensive intervention for overnutrition and consider whether such a change would be appealing or successful for you. Consider it in light of your lifestyle and evidence from this section.

Morsel: Dieting promises

Identify an example of a dieting trend and its promises to evaluate potential risks and benefits of the diet—be sure to consult credible research about its outcomes.

Dessert: Body positivity

Find examples of marketing campaigns that do and do not promote inclusive standards of appearance. Use the Your Fat Friend blog to evaluate the potential impacts of the advertisements.

Gochisousama Thanks to the chef! Recommended reading: ●

Myths and misconceptions about obesity: Casazza, K. et al. (2013), “Myths, presumptions, and facts about obesity,” NEJM, 368(5): 446–54.

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Tommy Tomlinson essay—The weight I carry: https://www.theatlantic.com/health/ archive/2019/01/weight-loss-essay-tomlinson/579832/. A review of pharmaceutical treatments for obesity: Adan, R. A. H. (2013), “Mechanisms underlying current and future anti-obesity drugs,” Trends in Neurosciences, 36(2): 133–40. Prescription medication for weight management: NIH website resource https://www. niddk.nih.gov/health-information/weight-management/prescription-medicationstreat-overweight-obesity. Beware the promise of miracle diets and supplements: FDA resource https://www.fda.gov/consumers/consumer-updates/beware-productspromising-miracle-weight-loss. Marion Nestle updated blog posts https://www.foodpolitics.com/tag/supplements/.

Glossary Body positivity:

the social movement challenging the dominant idealized body image with the goal to foster acceptance of all body shapes and sizes

Dietary restraint:

a condition of chronic dieting and self-regulation of eating, typically measured by self-report survey instrument

Dieting:

limiting of energy intake intentionally for the purpose of weight loss or weight maintenance

Economic hypothesis for obesity: an explanation for overnutrition and obesity that emphasizes the inverse relation between energy density of the food and the cost, such that junk foods high in calories (plus fat and sugar) are cheaper than fresh produce and lean protein, causing overnutrition and obesity Etiology:

the cause(s) of a specific condition or disease

Obesity:

described as body weight greater than what is considered healthy for one’s height (by the Centers for Disease Control and Prevention, CDC) and as an excessive fat accumulation that presents a risk to health (by the World Health Organization, WHO)

Obesity epidemic:

the spread of obesity as a disease among many individuals at the same time (from 1980 to present)

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Obesogenic:

causing obesity

Overnutrition:

a form of malnutrition, characterized by the excess consumption of food and nutrients to the point of adverse health consequences such as the accumulation of body fat, overweight, and obesity

Settling zone theory:

the theory of weight regulation that physiology sets a range of possibilities for body weight based on energy intake and expenditure that may fluctuate according to environmental and nutritional factors

Chapter 11 Beyond the Golden Cage: Eating Disorders Warning: This chapter contains content regarding disordered eating and the thin ideal essential for fully understanding eating and drinking. However, we recognize that such information can serve as triggers for people with a history of eating disorders, preoccupation with body image or feeding, or disordered eating patterns. Please consult resources, such as the National Eating Disorders Association, if you are challenged by reading this material.

Whet Your Appetite: Western Media Brainstorm implicit messaging conveyed in mainstream media regarding body image and food. Consider film, celebrities in advertisements, and the ubiquity of social media. What are the norms for appearance communicated by these images? Have you noticed social media photos and posts encouraging an unrealistic ideal for thinness? In this chapter, eating disorder prevalence and risk factors are described, including the mechanism by which cultural norms for body image impact health. Finally, potential treatments for restoring non-disordered eating are reviewed.

Menu Amuse-Bouche: Fiji and Eating Disorders Course 1: Definitions, Diagnostic Criteria, and Impact Anorexia Nervosa Bulimia Nervosa Binge Eating Disorder Other Eating Disorders Course 2: Etiology Sociocultural Contributors to Disordered Eating

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Psychobiological Contributors to Disordered Eating Course 3: Treatment and Solutions Individual and Familial Approaches Pharmacotherapy Educational Programs Dessert: Enticing, Dissatisfying Portrayals Dining Review Gochisousama Glossary

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Amuse-Bouche: Fiji and Eating Disorders In the 1980s and 1990s, eating disorders (EDs) were consider “culturally bound syndromes” unique to high-income countries of the global West, specifically Europe and North America (DiNicola, 1990). In contrast, contemporary epidemiological trends of EDs indicate a broader global distribution (Pike, Hoek, & Dunne, 2014). The sociocultural patterning of EDs is studied through the movement of people to a new region, or movement of cultural innovations, as when television or brands arrive to a new area of the world. For example, in 1998, television was introduced to rural communities in the nation of Fiji in the south Pacific. Becker (2004) conducted interviews 3 years after the arrival of TV in a sample of adolescent females, collecting narrative data to explore themes around body image. The interviews revealed a significant shift in the idealization of certain body shape, moving away from the traditionally valued robust female form to an admiration of a “Western” thin ideal, which participants associated with social and material success. Most problematic is the occurrence of disordered eating attitudes and behavior, including restriction and purging, after the arrival of Western media. This pattern is not unique to the rural community of Fiji. Eating pathology is associated with transnational migration and upward social mobility, as well as globalization and urbanization of regions (Becker, 2004). The emergence of EDs corresponds with industrialization of countries, even those from similar areas of the globe. In Asia, for instance, EDs arose earlier in Japan alongside its earlier industrialization in the 1970s, surfacing later in areas of southeast Asia and China that were not industrialized until the 1990s (Pike, Hoek, & Dunne, 2014). Similar ED presence among Arab countries coincides with industrialization, first in Egypt in the 1980s and later elsewhere (e.g., Pakistan) as thin ideal and dieting spread. In North America and Western Europe, EDs grew more prevalent across racial and ethnic groups in the 21st century (Pike, Hoek, & Dunne, 2014). In sum, cultural transitions in the contemporary global world challenge traditional assumptions and ethnicity-based distinctions in the presentation of eating disorders. These findings

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highlight the need for awareness of intersectional and plural identities as well as the wide reach of ED risk and symptomatology.

Course 1: Definitions, Diagnostic Criteria, and Impact As described in Chapter 10, eating is not always regulated by physiological need nor does it necessarily conform to societal and scientific conventions. When eating and drinking are driven primarily by hunger, with variety in the foods and nutrients that compose diet, consumption is deemed typical or nondisordered (Zucker, 2017). Disordered eating, or non-normative eating, varies from typical, healthy eating in some consistent manner but often does not disrupt daily living or functioning (Tanofsky-Kraff & Yanovsk, 2004). Let’s say a person ritualistically consumes the same breakfast each morning, avoids sugar, or habitually eats while stressed. These cases involve peculiarities about people’s relationships with food, but may not pose physiological or psychological burden and may persist through a lifetime without significant impact on functioning. In contrast, symptoms can develop further into a diagnosable eating disorder (Pereira & Alvaregna, 2007). Risks for escalation from disordered eating to an ED include the use of food to cope with life events or emotions, adherence to restrictive or fad diets, and negative self-evaluation based on consumption or body image. The prevalence of any form of disordered eating is as high as 50%, with some reporting its greater incidence among those who are overweight and female (Croll et al., 2002; Nagata et al., 2018; Sparti et al., 2019), but this is difficult to estimate because much disordered eating goes unrecorded and untreated. Full EDs, by comparison, are estimated to occur in 1–3% of the population and are problematic for the person with the disorder and those around them. The International Classification of Diseases (ICD-11) contains criteria for six Feeding and Eating Disorders (FEDs) as part of its chapter “Mental, Behavioral, and Neurodevelopmental Disorders” (see Table 11.1; Claudino et al., 2019). Two FEDs—pica and avoidant-restrictive food intake disorder (ARFID)—were discussed in Chapters 1 and 8. The remaining FEDs are addressed in this chapter. ED diagnosis currently involves classification of the presence or absence of a disorder. Professionals cite three factors for determining whether an abnormal eating pattern indicates the presence of an ED: behaviors, intensity, and functionality (Zucker, 2017). For behaviors, the number and frequency are important indicators. A person may count calories as their only non-consumption behavior directed at food, or they may count calories, track grams of fat and sugar, record body weight and composition, and search for lean recipes. The intensity, or obsessive nature, of the calorie counting also matters. If the action is used as a gauge for choosing lower-calorie options or whether to indulge in desserts, it could be no cause for concern. If calorie counting is compulsive to the extent a person becomes distraught if the number of calories in a dish is unknown or if they think about calories hours before meals, the calorie counting could be disruptive to daily life

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Table 11.1  Characteristics of Feeding and Eating Disorders (FEDs) Typical Eating/ Nondisordered Eating

Disordered Eating/ Non-normative Eating

May be part of an Eating Disorder

When considering what to order from a menu, selects the item that has 400 fewer calories among two equally preferred options.

Maintains a strict self-rule to never order a meal containing more than 800 calories.

Carefully estimate calories consumed at every meal. Feelings of stress and schedule disruption accompany the habit.

Limits purchases of processed Avoids all processed foods to include rejection of foods to a small number of offerings from hosts of items or small percent of events or occasions. purchases.

Fears all processed foods and worries about incidental consumption of them. Carefully plans meals and social engagements accordingly.

Hopes to consume more fruits and vegetables when possible, but mostly selects items that taste good and are enjoyable to eat.

Plans, records, and reflects on fruits and vegetable consumption. Experiences guilt and stress over attainment of enough fruits and vegetables, which can disrupt sleep and jeopardize relationships.

Counts the numbers and varieties of fruits and vegetables consumed each day into an app.

The examples included in this table serve illustrative purposes only and do not provide criteria intended for diagnostic purposes. All diagnoses of ED should be conducted by qualified professionals based on a number of indicators.

and indicate presence of an ED. Calorie counting could be associated with a person’s malnutrition or health deterioration, loss of social interaction or increased isolation, and/ or create conflict within the family (as when a person refuses to attend gatherings or eat at specific times). These latter situations illustrate disruption in functionality. To illustrate the behavior-disorder spectrum of disordered eating, a full one-third of American women report some compensatory mechanism, like use of laxatives or self-induced vomiting, to control weight, despite their not having a diagnosis of an ED (Reba-Harrelson et al., 2009). Evaluation of disorders is complex and cannot be determined at first glance because behaviors can be normative or disordered, and if chronic and dysfunctional symptom presentation may warrant identification of a disorder (EDs, Compulsions, and Addictions Service, EDCAS, 2014).

Chew on This: Diagnostic Guidelines Two diagnostic guidelines dominate the world stage of eating disorders: The Diagnostic and Statistical Manual of Mental Disorders (5th ed., DSM-5) published by the American Psychiatric Association (2013) and the International Classification

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of Diseases (11th revision, ICD-11) published by the World Health Organization (2019) and used for nations’ report codes beginning 2022. Key distinctions between the books include purpose, scope, and accessibility (APA, 2009). The purpose of the DSM is identification of mental illnesses for treatment by psychiatrists, psychologists, and other licensed treatment providers who gather patient symptoms. The DSM is a standard reference for students and professionals in practice and requires intensive training prior to use. The ICD, by comparison, has widespread educational, identification, and reporting purposes for 194 nations and—as such—is distributed at little or no cost. Because it is based on public health goals of capturing prevalence and symptoms of disease, the ICD-11 contains over 55,000 codes of all disease types. It is the current standard used for most insurance billing globally. Experts anticipate the ICD to become the singular, unified reference material for diagnostic criteria and information about diseases while the DSM will continue to be used as denser reference material for mental health practitioners (APA, 2009; Uher & Rutter, 2012). In fact, the DSM and ICD diagnostic contents have grown increasingly similar in their last two revisions and the DSM references ICD codes directly.

Because EDs range in severity, there are attempts to capture and label disorders along the dimension on which they occur. Only the most recent version of the Diagnostic and Statistical Manual of Mental Disorders (5th ed., DSM-5) includes indicators of disorder severity, where BMI (kg/m2) marks anorexia nervosa (AN) severity, purging frequency marks bulimia nervosa (BN) severity, and frequency of binge episodes marks binge eating severity. The presence of severity indicators allows practitioners to identify significance of client symptoms and to select appropriately scaled treatments, but more research will determine if new severity indicators are helpful for clinical differentiations (e.g., Smith et al., 2017). Some early evidence points to other indicators, such as number of different purging behaviors—rather than their frequency of occurrence—as better for measuring more or less extreme versions of a disorder (Forrest, Jacobucci, & Grilo, 2020; Gianini et al., 2017). In the following sections, the diagnostic criteria and symptoms of these EDs are explained.

Anorexia Nervosa AN is characterized by underconsumption, restricted feeding, and low body weight. Internally, there is a mental storm focusing on body size and weight, worrying about weight gain, and pondering methods to lose weight or avoid weight gain. Specifically, three diagnostic criteria currently are used for AN (Claudino et al., 2019): 1. low body weight or rapid weight loss that cannot be explained by other factors, like famine or disease;

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2. restrictive feeding or calorie expenditure behavior that persists over time; and 3. high prioritization placed on low body weight and its role in self-evaluation. Fortunately, diagnosed AN is rare. The point prevalence, or rate of occurrence at a given time, is 0.3–1.0% and risk of lifetime development around 1.2–2.2% among women (Arcelus et al., 2011; Smink, van Hoeken, & Hoek, 2012), though it ranks third among chronic illness in American adolescents behind only obesity and asthma. In Europe, AN prevalence is between 1% and 4% and is believed to be lower elsewhere, but the higher European numbers could be due to better capture of its presence. Information from nonEuropean regions of the world is limited due to lesser recognition and reporting of EDs, but they appear on the rise in Asia and Latin America (Hoek, 2016). Indirect evidence further implies thin ideals and AN have reached most corners of the globe. For example, the top 10 countries for Internet searches about AN and BN were all Latin nations (e.g., Bolivia and Mexico; Eli, 2018). This means the disorders are quite salient in places with low reported incidence. The AN once more attributed to young Euro-women in wealthy nations is a global phenomenon without age, sex, gender, or economic boundary (RebaHarrelson et al., 2009). Psychological distress connected to AN is intense for the person with the disorder and their loved ones. Food and body image are dominant themes that compromise productivity at school or work, social engagement, and sympathy from others. Unlike many other mental illnesses that go largely “unseen,” AN and its impacts often are in public view (Berner et al., 2013). Adolescents with AN are less likely to exhibit low BMI compared to adults with AN, but the disorder is cognitively stressful in all cases (Sawyer et al., 2016). A lack of energy and nutrient intake also causes physical distress. Hormones respond to slow metabolism and redirect energy from noncritical functions, like reproduction (leading to amenorrhea in many females) and bone health, to critical functions (e.g., maintaining heart and lungs). In fact, the presence of disordered eating with amenorrhea and osteoporosis is known as “the triad” since the three components are commonly interrelated (Peters & Rooney, 2003), especially among girls and women who exercise regularly (Torstveit & Sundgot-Borgen, 2005). Other physical effects of AN are low systolic blood pressure, low heart rate, low red blood cell count, low white cell count, and low body temperature (Misra et al., 2004). Listlessness, heart arrythmia, and muscle atrophy occur as effects of chronic self-starvation (Fazeli & Klibanski, 2018). The body can become accustomed to undersupply of food and slowed biological functions, such that dangerous reactions to physical exertion or refeeding can occur—even causing congestive heart failure (Ratcliffe & Bevan, 1985; Schocken, Holloway, & Powers, 1989). The combined burden on the body and mind contribute to AN as a leading cause of death among all mental illness (Arcelus et al., 2011). Death can occur slowly due to heart failure or suddenly, as in a cardiac arrest (Jáuregui-Garrido & Jáuregui-Lobera, 2012) or suicide, which claims over 20% of the deaths among those with AN (Arcelus et al.). In the most recent, 2019, Global Burden of Disease study, AN and BN ranked

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12th among all diseases in terms of years of life lost as its result. Mortality rates are over 5% higher among those with AN than those without it. Like other EDs, an AN diagnosis commonly occurs with another mental illness. In the United States, 56% of AN diagnoses are accompanied by diagnosis of another mental condition. For example, roughly 48% of people with AN also have an anxiety disorder and 42% also have a mood disorder (National Institutes of Health, 2017).

Bulimia Nervosa BN—or, bulimia, as it is known for short—shares two critical characteristics with AN: preoccupation with body image and behavioral attempts to limit calories absorbed or compensate for calories consumed (Claudino et al., 2019). Both AN and BN may involve purging via laxatives, exercise, or self-induced vomiting. Differentiating between the two disorders can be confusing for nonexperts. In both the DSM-5 and ICD-11, BN is diagnosed only when criteria for AN are not met. The first critical distinction is that BN involves binge-eating episodes, where large amounts of food are consumed in one sitting marked by a loss of control. When binging, the foods consumed are usually avoided at other times (e.g., in front of other people or as part of their otherwise restrictive diet) and eating can occur rapidly when binging even if no hunger is present. A second critical distinction is that BN diagnosis does not require sub-typical body weight or significant loss in body weight. Persons with BN usually have body weights and BMI within normal ranges. The point prevalence of BN is lower than AN by 0.2–0.7% in North America and Europe, which means it is less likely to exist among the population at a specific time (Nagl et al., 2016). Its lifetime prevalence, however, is slightly higher than AN especially among Latinx populations (Chavez & Insel, 2007). Like AN, BN creates both physical and mental strain. Additional components of BN include secrecy and planning of binge episodes triggering relationship problems and emotions like guilt and shame. Although BN is associated with normal weight ranges, it has negative physical effects (e.g., enamel erosion, esophagitis; Anderson, Shaw, & McCargar, 1997) vary based on the compensatory behaviors (Santonicola et al., 2019). BN is associated with a 1.9% increased mortality rate (Arcelus et al., 2011). Comorbidity of other mental conditions with BN is especially striking. In the United States, over 80% of people with BN have a diagnosed anxiety disorder and over 70% have a mood disorder. In all, nearly 95% of people with BN present with another diagnosed mental condition (National Institutes of Health, 2017).

Binge Eating Disorder Binge Eating Disorder (BED) is characterized by binging episodes. As observed in bulimia, binging involves a loss of control over eating, eating can occur very rapidly and often alone, and the foods consumed are usually foods or drinks avoided at other times.

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To qualify for the disorder, binge episodes must be recurrent (i.e., at least once per week for 3 months) without a medical basis (e.g., Prader–Willi syndrome) and daily life must be disrupted or impaired. The distinguishing feature of BED compared to BN is the absence of compensatory behaviors. BED was recognized as its own, separate disorder in the past 10 years via the most recent versions of the DSM and ICD. Its global prevalence is estimated to be 0.9% without differences across countries of varied incomes. It is twice as likely to occur in women than men (Erskine & Whiteford, 2018). In the United States, the point prevalence of BED was 1.2% as of 2017 with a lifetime prevalence estimated to be 2.8% (National Institutes of Health). BED is the most prevalent of all specific EDs that appear in the DSM-5 and ICD-11. The physical impact of BED is not completely known, as the intensity of binge episodes correlates with body weight and BMI (Guss et al., 2002), making it difficult to disentangle the effects of binging from general effects of added body weight. Binge eating is more common among overweight individuals, but the relation is moderated by body satisfaction/dissatisfaction, where likelihood of binging is greater for those who report some dissatisfaction with their bodies and/or weights (Sonneville et al., 2012). Like other EDs, BED comes with psychological risks. Concern for body size and weight, emotion regulation difficulties, and social conflicts are associated with BED (Marzilli, Cerniglia, & Cimino, 2018). Almost 80% of BED diagnoses present with the diagnosis of another mental condition: the comorbidity is 43.3% for impulse control disorders, 46% mood disorders, and 65% for anxiety disorders (National Institutes of Mental Health, 2017).

Other Eating Disorders Rumination-Regurgitation syndrome (RRS; ICD-11; WHO, 2019), or rumination syndrome (DSM-5; APA, 2013), occurs mostly in children but also in adolescence and adults (Tack et al., 2011). This condition involves uncontrollable, effortless regurgitation of food during or shortly after (i.e., within 10 minutes of) its consumption that occurs several times per week and persists across weeks or months. Another more common use of rumination in psychology refers to repetitive cognitions, as when people mentally replay negative events and emotions. To differentiate these repetitive thoughts from rumination of food, especially because mental ruminations are correlated with a variety of disordered eating, the ICD-11 term, RRS, is used herein. Food, when regurgitated, may be re-chewed or spit out but the event is distinguishable from vomiting. Regurgitation can lead to unintentional weight loss, though weight loss is not a diagnostic criterion. To be classified as an ED, the person must be at least 2 years of age and physiological reasons for regurgitations (e.g., gastrointestinal disease) must be eliminated. The discounting of potential medical reasons for regurgitation makes it difficult to estimate the prevalence of RRS because diagnosis and treatment are often mingled to address physical and psychological causes and effects. Pure RRS is rare (1015 according to Ahn et al., 2011). However, only a portion of flavor combinations are found in global cuisine. Ahn and colleagues’ (2011) network analysis shows each cuisine has highly prevalent ingredients, called “founder ingredients” present in early recipes from specific geographical locations. These researchers examined flavor combinations tending to repeat in regional cuisines, noting the pairing of similar flavor compounds (e.g., milk and vanilla) was common in recipes from North America, Latin America, and Western Europe. In contrast, dissimilar combinations—complementary to the palate—characterize recipes from East Asia. Examples include sweet-and-spicy barbecue sauce and hoisin, also exemplified by Thai cuisine’s harmony of spicy, sour, salty, and sweet tastes (Greeley, 2009).

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Flavor combinations central to specific cuisines represent preference with purpose. That is, food preferences and practices are not random or by chance. Rather, shared tendencies are often correlated with health and wellness benefits. This is exemplified by the common mixtures of spices to capitalize on synergism and maximize antimicrobial properties (Sherman & Billings, 1999). Religion-specific rules concerning food preparation offer another example. Halal food laws stress cleanliness, including rules for the slaughter of animals, limiting contamination and supporting food safety (see Regenstein, Chaundry, & Regenstein, 2003). Islamic rules emphasize humane treatment of animals and discourage food wasting (Eliasi & Dwyer, 2002), sustaining community well-being. Also consider the practice of smoking fish, appearing in many global cuisines. The process of fish smoking varies by geographic region, with distinctions in brining, spices, and the variety of wood used. These efforts are worthwhile; smoking removes the water content, increasing the concentration of proteins and the portability of the fish for travel, preventing spoilage to ensure the summer catch lasts through the winter months (Kiczorowska et al., 2019). No wonder smoked fish is a global treat—from Nigeria (Silva et al., 2011) to the circumpolar Arctic people (Johnson et al., 2009), smoked fish is a cross-cultural food tradition with adaptive benefits. Fermented foods further demonstrate the global spread of a beneficial food process. The preparation of Kimchi, made from cabbage or sometimes other root vegetables, starts with days in a liquid brine solution, traditionally buried underground. As the bacteria grow in the solution, they feed on the sugar of the cabbage and convert it into lactic acid, as fermentation occurs. Kimchi has received credit for health benefits from shiny hair to improved digestion, but the true power is in the “live” cultures that support gut microbiome health (see Chapter 4), only recently recognized by Western medicine. Sauerkraut, kefir, tempeh, and of course beer further exhibit the culinary tradition and global spread of fermented foods. The global preference for certain foods (e.g., spices, smoked fish) is attributed to their protective benefits. Food taboos are similarly widespread (Meyer-Rochow, 2009) and also provide health and social advantages. Omnivores, like humans, face challenges in navigating the food world, aided by specific food prohibitions. In Fiji, large reef fish are the primary source of protein, yet pregnant and lactating mothers avoid rock cod, barracuda, moray eel, and shark due to existing taboos. Heinrich and Heinrich (2010) observed the avoided marine fish are a source of food poisoning because they accumulate ciguatera toxins, and incidents of food poisoning are reduced by about half from women’s adherence to the taboo. Further, taboos are notably selective. In the same fishing villages of Fiji, similar foods (e.g., freshwater eel) with lower risk of toxins are not avoided, and prohibitions become less rigorous after birth to accommodate the caloric demands of breastfeeding. Food taboos can be an expression of empathy and morality, as when people who keep animals as pets do not consume them or other members of its species, even in times of hunger. Resource management is assisted by

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food taboos to decrease competition between adjacent groups. For example, in Native Alaskan populations, Aleut and Inupiat people both consume whale as a dominant seasonal source of protein, whereas the Tlingit people do not consume whale as long as other food, like land animals, are available (Kuhnlein & Humphries, n.d.) to decrease competition with adjacent groups. The food preferences and practices described thus far are valuable for survival and wellness, but also emerge within social and cultural contexts. In much of the contemporary world, food choices are influenced by factors beyond necessity, with status and consumer culture also at work (Wright, Nancarrow, & Kwok, 2001). The concept of preference with purpose illuminates adaptive eating, yet under some conditions, humans and animals alike consume a suboptimal diet that decreases longevity. Note the craze around individual food items facilitated by social media, where attractive images of food augment desire to eat (see Chapter 10). The almond and avocado trends of the past decade, propagated via wellness and foodie culture, highlight problematic food preferences and patterns of consumption for society and the planet. Almonds, once an ordinary member of the mixed nut crowd, outpaced its peers in demand in the early 2000s and reached peak price at $4/pound in the United States in 2014 (Swegal, 2017). Eighty percent of the global almond supply is produced in California where acreage devoted to almonds increased through 2016 (Swegal) while almond butter, almond milk, and almond flour soared in popularity. Almond products are trendy replacements for other food items due to their nutrient profile and health benefits (e.g., Tan & Mattes, 2013). However, almonds demand a lot of water to grow, depleting aquifers, worsening drought, threatening fish and other animal populations (Hamblin, 2014). Remember the warning of nutritionism from Chapter 1? Almonds exemplify the shortsightedness of judging a food solely by the specific macronutrients and micronutrients it contains without attention to externalities like environmental impact.

Chew on This: Oro Verde The current avocado trend peaked in North America and Europe following almonds, with avocado toast, avocado oil, and even avocado lotion driving 7.1 lbs of per capita avocado consumption in the United States in 2015 (USDA). Similar to almonds, the health benefits of “good fats” drove popularity and demand outpaced domestic production. Now, a majority of avocados consumed in the United States are imported, causing environmental issues in Mexico due to demands for water and land. Avocados became a conflict commodity, similar to the other green gold (marijuana), with takeovers of small farmers and corruption in the supply chain (Dehghan, 2019; Miller, 2018). Avocados are an important staple for certain regional cuisines, but their rise as a food trend produces adverse geopolitical and environmental consequences.

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The overly enthusiastic consumption of trendy food commodities is a socially enhanced though unsustainable behavior. Food habits and beliefs, even when problematic, reflect the values and motives of both the individual and the culture. The increased globalization of food, described in the next section, may result in both the loss of some culinary distinctions but increased acceptance of diverse cuisines.

Globalization and Culinary Trends During the 19th and 20th centuries, the best cuisine, the best chefs, and the best restaurants were French. This dominance extends from Brillat-Savarin coining the term gastronome in his 1825 writings, through the rise of the modern restaurant scene and the publication of Escoffier’s 1903 Le Guide Culinaire (Barlösius, 2000). It continued in the 20th century with Le Guide Michelin, the arbiter of French cuisine that became the international restaurant rating system still used today, and the predominance of chef training under the French culinary tradition. French cuisine was largely codified with rigid techniques, from the five mother sauces to the menu and kitchen brigade. These designations established professional standards for chefs and preserve specific dishes, but new generations of chefs push back on old standards to instill new traditions (Steavenson, 2019). By the beginning of the 20th century, globalization and greater attention to good food among the masses threatened the dominance of French cuisine. Globalization, used to broadly describe the interdependence of the world from people and culture to information and economy, characterizes our contemporary food system. This is not the first period in which globalization altered a culinary landscape. During the Middle Ages, when spices were rare and expensive in Europe, spice use was a status symbol, and exciting complementary flavor pairings were common (Singh, 2015). Yet colonialism increased the availability of spices to everyone in Europe, and cultural snobbery of the wealthy who sought to differentiate themselves from the commoner, triggered a culinary transition to subtle (i.e., bland) seasonings that typifies much of European cuisine today. Today, globalization inspires food, and cuisine is considered an avenue to promote cultural acceptance. Globalization occurs through intentional and communal processes, like food sharing and mutual appreciation. Social influences on eating contribute to both adaptive and arbitrary (even maladaptive) cultural traditions (Franz & Matthews, 2010). When immigrants cannot access traditional ingredients, they adapt recipes to the available ingredients or techniques, but maintain camaraderie through shared meals (Paresecoli, 2014). For example, the use of avocado as an ingredient in Americanized sushi seeks to mimic the fatty mouthfeel of tuna that is less accessible than in Japan. But social pressure can also manifest as less adaptive outcomes. Experimental evidence shows that when participants who are immigrants to the United States face a subtle challenge to their American identity, they make more prototypically American food choices (Guendelman, Cheryan, & Monin, 2011), with deleterious health consequences over time. Lunchbox bullying (Chapter 9) illustrates the pressure immigrants face to conform to local culinary

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customs and the missed opportunities in “lunchbox moments” for pride, joy, and sharing among peers (Saxena, 2021). Beyond physiological explanations of nutritional benefits, eating habits are influenced by complex psychological and social processes. Consider the development of the controversial fusion food, a meal combining elements of different culinary traditions, an example of creativity beget by exposure to diverse ideas. The definition of fusion food depends on historical context. Chocolate, tomatoes, and potatoes all originated in the Western hemisphere, but the presence of these ingredients in European cuisine occurred through “fusion” at some point (Spence, 2018). Fusion food is considered fancy in some circles, yet many fusion foods are quite humble, like Hawaiian pizza (originating in Canada), innovative ice cream flavors, and Author LC’s favorites: the poké-rito. Most any “American restaurant” or neighborhood pub offers fusion dishes. Fusion cuisine can be accomplished with disregard to values and customs, or with respect to culinary traditions. Skeptical responses to fusion food demonstrate a tension between tradition and innovation, as some question its place in our food landscape, instead arguing for more “authentic” regional cuisine.

“As American as Apple Pie”: Cultural Appreciation or Appropriation? Journalist, producer, and activist Jennifer 8. Lee explores the intersection of culture and urban life, including the global spread of Chinese cuisine in her short film The Search for General Tso (2014, related sources in Gochisousama). She provocatively asks, “If our benchmark for Americanness is apple pie, you should ask yourself: how often do you eat apple pie, versus how often do you eat Chinese food?” (Lee, 2008). Members of multiethnic communities enjoy the privilege of access to global cuisines. In the United States, immigrants and their children are 28% of the overall population (Migration Policy Institute, 2020), and there are 40,000 Chinese food establishments (Wu, n.d.). The prevalence of Chinese food and restaurants in the American diet demonstrates the outcomes of globalization and questions culinary authenticity. Given the increased attention and market for global cuisines in much of the world, special attention is warranted to cultural appropriation, the adoption of elements from another culture and using them as your own. Appropriation tends to be exploitive in nature and fails to grant credit to the source or origin of ideas, symbols, artifacts, foods, styles, and so on, often occurring within a context of marginalization, to perpetuate the dominance, negative stereotypes or degradation of cultural symbols (Rogers, 2006). Even when unintentional, biased attitudes can permeate food culture and narratives. Cultural appropriation raises questions such as who is permitted to produce and profit from goods with a specific cultural origin. In the United States, experience and knowledge of Mexican and Latinx cuisine may arise from familial ties (18.5% of the US population identifies as Latinx or Hispanic), first-hand travel experience, or Mexican-American restaurants. Yet these avenues do not yield consistent appreciation, respect, and awareness. Many food staples of the Southwest such as maize/corn arise from pre-Spanish culinary traditions of

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Indigenous people, whose cuisine was further influenced by Spanish colonialism (Pilcher, 2001). Diverse regional cuisines from New Mexico to Oaxaca are offered in both traditional and appropriated forms. These examples raise questions of “authenticity” and power, for who determines which foods are authentic for a given cuisine? Abarca (2004) argues that authenticity and legitimacy impact inclusion, and exclusion, of certain people from participating in a cuisine. The demand for “authentic” foods from a cuisine implies the existence of particular meals or dishes that are not authentic or real. If we stress “authentic” food, the preparer is restrained to specific methods, and creativity is stifled (Abarca, 2004). Celebrity chefs and restaurateurs possessing designation of “expert” have used their fame to grant legitimacy to their own takes on cuisines and dishes with which they have no shared heritage or meaningful experience. Take the example of writing cookbooks for specific cuisines—printed recipes become items of copywrite, ownership, and profit. When recipes are gleaned through communication, narrative, and oral history, the source (a person) of the recipes does not receive credit or compensation (Heldke, 2001). Recipes published in a cookbook or online may not grant credit or preserve the cuisine, but rather commodify the dish, making it accessible and comfortable to the consumer (Heldke). Traditional and Indigenous Knowledge (see Chapter 1), the accumulation of observations and wisdom passed down through generations, is similarly vulnerable to exploitation and profit by outsiders. Heldke (2001) ascribes penchant for diverse global cuisine as more than innocent curiosity. The desire to learn from an exotic other can come from a place of privilege unique to Western colonizing societies. To identify and alleviate tendencies of cultural appropriation, we must first acknowledge our privilege related to food, culture, and people. Take care to avoid narratives of the “exotic other,” the ideal that personal culture and beliefs form a baseline to which others deviate. Ask whether commodification is occurring, in which the subordinate culture is creating profit for others. Contrast appropriation with appreciation, grounded in learning about another culture and broadening perspectives. Ideally the relationship is one of mutual choice—for instance the original source of a recipe volunteers to contribute to a cookbook and is compensated appropriately (Heldke). When inspired by the work of others, just as we should not plagiarize in the academic domain, it is imperative to give credit to cultural sources of knowledge, ideas, and, of course, cuisine. The desire to enjoy diverse cuisines from around the globe is not always tinted with privileged attitudes and may promote acceptance and understanding, though the benefits require cultural humility on the part of the consumer (Abarca, 2010). Importantly, appreciation of diverse global cuisine is not a substitute for meaningful inclusivity or equity.

Course 2: Food Policy Global and local food pathways are shaped by more than culture, as policy and environment influence the availability and cost of commodities. Economic resources

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impact food access and cuisine, illustrated by increases as per capita sugar consumption paralleling increases in income of a country (Popkin & Nielsen, 2003). As discussed in Chapter 10, a gradient between socioeconomic resources and diet quality exists in much of the industrialized world, as diets of fresh produce and lean protein tend to cost more (Darmon & Drewnowski, 2015) though there are some exceptions. Communities with strong social ties and maintenance of cultural traditions demonstrate consistently highquality diets (Darmon & Drewnowski, 2008). In economically developing nations, the relationship between social class and diet is in the amount of food available rather than the quality of the food. Bear in mind, there is enough food to feed all the world’s people (United Nations, 2019), yet 690 million people were undernourished in 2019, worsening due to the COVID19 global pandemic (FAO, 2020). Over the past 5 years, a growing number of people have reduced access to both quality and quantity of food, and two billion people did not have sufficient and regular access to nutritious food in 2019 (FAO, 2020). According to the Food and Agriculture Organization (FAO) of the United Nations (UN), “food security exists when all people, at all times, have physical and economic access to sufficient safe and nutritious food that meets their dietary needs and food preferences for a healthy and active life” (FAO, 2008). The additional factors of dietary diversity, food storage availability (e.g., refrigeration and power), and stability of these dimensions over time must be simultaneously met. The Food Insecurity Experience Scale is a measurement tool used to indicate the degree of food insecurity a person is experiencing (Figure 12.2).

Figure 12.2  Food insecurity. The degrees of food insecurity according to the Food and Agriculture Organization of the United Nations. Source: http://www.fao.org/in-action/voices-of-the-hungry/fies/en/.

If we have enough food to prevent global hunger, why is nearly 10% of the world’s population undernourished? The FAO of the UN defines four key contributions: 1. Natural disaster and drought, both coinciding with climate change, cause acute and seasonal food shortages. 2. Overexploitation of the environment, including poor farming practices that harm future crops. 3. The poverty trap, as food insecurity co-occurs with poverty, and hunger perpetuates poverty. 4. Conflict and war cause hunger through the use of food as a weapon and the displacement of people away from their homes, livelihoods, and food supply. The

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relationship between hunger and conflict is bidirectional, as constraints on resources including food availability can fuel conflict (Messer, Cohen, & Marchione, 1999). In 2006–2008, a global food crisis was created by doubling of grain prices (Brown, 2013). The financial impact varied by nation due to trade policies and by individual based on the proportion of income spent on food. In the United States and UK, the average household spends less than 10% of their income on food, so many households can manage cost increases. However, households with fewer economic resources spend proportionally more, and average consumers in 10 countries spend over 40% of their household income on food (World Economic Forum, 2016), leaving them little flexibility to spend more when food prices rise. War and conflict serve as both a cause and consequence of hunger. During a conflict, hunger is frequently used as a weapon, food supplies are cut off and civilian food aid may be hijacked (Messer et al., 1999). Food workers are recruited for wartime efforts or displaced by conflict, while farmland and food production facilities may be destroyed. Food production can suffer even after the conflict resolves, as infrastructure and food supply require time and aid to rebuild (Messer et al.). The association between conflict and hunger is bidirectional because food insecurity, in turn, can serve as the catalyst for conflict. This is exemplified by uprisings as a response to food scarcity throughout history from the French Revolution to the cultural uprising after the Great Chinese famines. In a modern example, the ballooning of world grain prices from 2006 to 2008 spurned food protests, riots, and partially fueled uprisings of the Arab Spring (Brown, 2013). Egypt is the world’s largest wheat importer (FAO, 2014), where bread is called aish (translating to life), and bread prices rose by nearly 40% during this period (Zurayk, 2011). With the food supply further strained by population growth and high temperatures, suppliers restricted exportation and sold their products locally (Brown). Existing tensions in the region were catalyzed by the contextual forces of food insecurity. Significant global conflicts are followed by a period of food insecurity and simultaneous displacement of persons. From 2005 to 2015, the number of displaced persons in the Middle East region grew from 5 million to approximately 23 million, the majority from Syria, Iraq, and Yemen (Pew, 2016). Refugees, persons who are unable to return to their region of origin due to risk of persecution, are consistently vulnerable to food insecurity. We might assume initial food insecurity upon resettlement improves over time, but the evidence is mixed in the United States, as economic hardship and food insecurity can persist for decades (Peterman et al., 2013). The process of acculturation, or adjustment to the lifestyle of the new region, is expected to improve economic condition. Unfortunately, as mentioned previously, acculturation to high-income countries correlates with worsening diet, increased intake of snacks, fast food, and sugar-sweetened beverages (Ayala, Baquero, & Klinger, 2008). The impact of refugee and immigrant status on food security and dietary quality has implications for the scaffolding of economic and food support after arrival into high-income countries to address health disparity and promote wellness.

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Food Sovereignty The majority of hunger occurs in rural areas of developing nations, where food insecurity is an issue of development. The global food system disadvantages smallscale production for families and communities. Focus on discussion of food security/ insecurity alone downplays the exploitation and subsequent hunger caused by contemporary capitalism and neoliberal trade policies. Before the current export-oriented food economy, colonization drastically altered the food landscape for Indigenous peoples. In the 1400s, development of international trade routes, seizure of land, and ecological destruction were compounded by cultural indoctrination that devalued traditional food knowledge (Raschke & Cheema, 2007). The effects of colonialism on Indigenous peoples, including dispossession of land and forced removal, massacres, and prohibition of cultural practices, caused immediate and intergenerational trauma with lasting health disparities (Coté, 2016). Subsequent neocolonial forces deposed Indigenous crops to spurn the “nutrition transition” to Western diet, increasing SES and health disparities. One proposal for more equitable distribution of resources is food sovereignty, the aim of La Via Campesina, a collective of farmers’ representatives established in 1993 (Desmarais & Nicholson, 2013). In contrast with large multinational food corporations, food sovereignty prioritizes local food systems defined by local people, production through sustainable methods, and the rights of people to healthy and culturally appropriate food (Nyéléni, 2007). The need for inclusive, democratic systems is supported by evidence that free-market (export-oriented) economies produces hunger, from Haiti and Niger to wealthy nations, as farmers starve while selling specialized commodities to large corporations (Mackintosh, 2011). Indigenous food practices and decolonization (Coté, 2016) are foci of food sovereignty, fostering discourse and relationships with Indigenous people and maintaining their food practices. One tangible example of this movement is the establishment of seed libraries, from the Hudson Valley Seed Library in New York to the Pima County Public Library program in Arizona. Indigenous seeds are reclaimed, honoring Traditional and Indigenous Knowledge (Duffy, 2017). Activists also employ principles of food sovereignty in urban communities within the United States in movements for food justice; for example, community garden projects demonstrate the shared emphasis on social justice, self-sufficiency, and cultural identity (Aikon & Mares, 2012). Food sovereignty approaches are complicated to implement across the food system, and additional evidence is needed to support their efficacy (Jones, Shapiro, & Wilson, 2015). Academic literature celebrates small efforts, like seed libraries and community gardens, failing to address complexities of food-deficit regions dependent on importing food due to lack of arable land and limits of urban food production (Edelman et al., 2014). Addressing these concerns will bolster the transformative potential of food sovereignty to address health equity.

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Morsel: COVID-19 and Food Insecurity Community is an important mechanism for food access, and the periods of quarantine during COVID-19 are a challenge to social connection and well-being. Notable for the present discussion is the impact on hunger as the number of people facing food insecurity is expected to double according to the UN World Food Programme (WFP, 2020). The pandemic interrupted food aid, and childhood malnutrition was projected to worsen by 14% in 2020 alone unless significant steps are taken (Headley et al., 2020). Though final figures are not available at the time of writing, preliminary data showed the COVID lockdown in Mexico reduced food security in households with children by 15% (Gaitán-Rossi et al., 2020) and in the United States, 37% of folks who lost work during COVID reported food insecurity and 39% reported eating less due to financial constraints (Raifman, Bor, & Venkataramani, 2021), though unemployment benefits mitigated food insecurity. Though nonprofit organizations like the World Central Kitchen have provided millions of meals to those in need, the situation is only worsening at the time of writing (fall of 2020) as the lines for food banks extend for miles in many major metropolitan areas, and the pandemic worsens low- and middle-income countries already strained for resources. The pandemic illuminated the uneven capacity of the public safety net to weather tumultuous circumstances. Consequences of this failure extend beyond individual households, as restaurants struggle to stay afloat on takeaway alone (Gursoy & Chi, 2020), essential food service workers at restaurants and grocery stores risk exposure to the virus (Parks et al., 2020), and meat and poultry processing plants and other industrial food facilities operated in unsafe conditions (CDC, 2020). Each example intensifies the disproportionate effect of the pandemic on vulnerable groups (Stephenson, 2020). Comprehensive solutions include addressing food insecurity across the food system, mobilizing health and social services to monitor and address food insecurity in vulnerable groups, protecting frontline health and food workers, and ensuring workers can follow safety protocols by providing adequate paid sick and family leave (Parks et al.).

Consumption and Consumerism Our discussion of food insecurity is in stark contrast to the hyperconsumption of food goods and services in high-income countries today. The sheer variety of options available (also see Chapter 6), from the grocery store to the farmers market to the restaurants you frequent, is a source of joy and stimulation for many. Franz Kafka said, “So long as

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you have food in your mouth, you have solved all of your problems for the time being,” articulating the pleasure of consumption. Such ignorance of related events, like external consequences of food decisions, yields complex problems. Consumerism encourages the purchase of commodities and services, demonstrated by increased spending on goods and especially food away from home (see Chapter 9) in the past decades. In a world that increasingly cares about food, culinary “lust” (Cargill, 2007) for food commodities is maintained by media, like television and Internet, through which eating-related interest is satiated. Globalization and commodification of cuisine is exemplified by the proliferation of a “foodie” ethos, mostly in wealthy nations. This food-centric attitude extends beyond the taste of food to the adoption of niche food philosophies and ethical consumerism, emphasizing buying organic, sustainability, humane care of animals, workers’ rights, or other noble causes. Caring about home-cooked meals is a noble cause. Recent popularity in meal kits serves as an interesting example of the struggle between appreciating meals, time pressure, and consumerism. Meal kits include portioned ingredients, step-by-step instructions, and yield a full meal in about 30 minutes, no planning or shopping required. Various options appeal across price points, dietary needs, and food preferences. Imagine coming across the wrappings from portioned ingredients in the future—Genevieve Walker (2017) postulates these would be indistinguishable from the remnants of a fast food value meal. Another criticism is meal kits contribute to consumerism—although they serve a purpose in providing a convenient of a meal delivered with instructions—costs are inflated, and they are inaccessible for many people as a result. Despite the concerns, meal kits offer solutions to complicated problems—for someone who cares about home-cooked meals, they handle preparation, accommodate mediocre kitchen skills, and relieve time pressure. Meals prepared and cooked at home are qualitatively superior in nutrient composition to those away from home (Mancino, Todd, & Lin, 2009). In young adults, home cooking is associated with better diet quality, but a lack of time is a commonly reported barrier (Larson et al., 2006). The promise of home meals to improve well-being generated intervention programs for improving cooking skills. These programs vary in target age group, length and skills taught, and the rigor of the methods used to evaluate outcomes. Some have promising results, from improvement in elementary-age children’s attitudes toward and consumption of home-cooked meals (Hersch et al., 2014), to enhanced fruit and vegetable intake and cooking confidence in adults (Reicks, Kocher & Reeder, 2018). Despite minimal experimental evidence (Farmer, Touchton-Leonard, & Ross, 2018) the positive psychosocial outcomes to enhance socialization and motivation to cook are heartening. Our tendencies of consumerism come as a price, psychologically and socially. A related useful distinction is in defensive versus creative behavior (Scitovsky, as cited by Barbezat, 2016). Defensive behaviors protect us from discomfort and satisfy immediate needs, while creative behaviors improve welfare through complex actions. Opting to eat fast food defends against immediate discomfort, but preparing a meal with friends—a creative endeavor—promotes well-being. Psychologist Kima Cargill (2015) argues the

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pressures to consume are explained by existential dilemmas of modern life, for example, the burden of work productivity and loss of community. It is challenging to reconcile the pressures of consumerism as a person who eats and cares about food and wellbeing. Addressing complex issues in our food system requires individual attention to the psychological forces at play coupled with civic responsibility to question the status quo.

Course 3: Food as a Cultural Asset Above the door to the first (European) restaurant hung the motto “Come unto me, all ye that labor in the stomach, and I will restore you,” attributed to the owner Boulanger, 1765, though public eateries existed long before this time. The word restaurant is derived from the French restaurer, which means to restore. As you learned in Chapter 1, the field of psychology supplements food studies disciplines, enhancing our appreciation and understanding of consumption. But the dedication of academic psychology to the study of food is relatively recent. In the 1990s, Paul Rozin argued that the centrality of food and eating in our life mandated greater attention from the field (e.g., Rozin, 1996). Consumption provides insights to biological processes, individual development and experiences, and cultural values. The preferences and practices described earlier in this chapter reveal biopsychosocial forces driving eating and drinking. Perhaps the most consequential evolutionary advantage of preference with purpose is that of cooked food, rendering starches and complex proteins more easily digestible to increase the net energy gain (Wrangham & Carmody, 2010) and support the large brains of Homo sapiens. Cooked food is a more efficient source of nourishment, allowing us our small jaw, facilitating the articulation of language, and enhancing the free time to share meals and build community. Beyond nourishment, food links us to community and culture. Food as a cultural asset is evident during periods of cultural oppression and subsequent recovery. When food systems are nationalized, for instance, in the communist Soviet Union, Czechoslovakia, and Mao’s rule in China, food scarcity is common, and cooking becomes a matter of survival. In China, catering was nationalized and centralized in the 1950s, regional cuisines were isolated from outside influence and dictated by state-published cookbooks (Klein, 2007). Similarly, in former Czechoslovakia, every restaurant, cafeteria, and home kitchen were to prepare dishes from the Book of Standards which emphasized cooking economically from available ingredients (Smith, 2018). After Czechoslovakia’s Velvet Revolution in 1989, culinary recovery was delayed by the expense of fresh vegetables and the slow return of tourism. Eventually, inspiration from global cuisine, farmer’s markets, and food bloggers spurned the revival and popularity of traditional Czech cuisine (Smith). Though these events are detrimental to the quality of cuisine for a period, the proliferation of traditional and regional cuisines in recovery exemplifies the resilience of food as a cultural asset.

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Chew on This: How to Cook a Wolf In a powerful illustration of informational influence, How to Cook a Wolf (1942) aimed to provide a “timeless model for cooking, eating, and living pleasurably under any circumstance.” During the Second World War, when food rations were used in many countries, American cook M. F. K. Fisher provided over 70 delightful recipes based on simple, affordable food basics. The book provided an example of how to thrive—as marked by tasteful and enjoyable eating experiences—in the face of limited food availability. It is still regarded highly by culinary critics today. During these food rations, the consumption of novel organ meats was promoted by serving them in visually familiar ways (McDade & Collins, 2019), which perhaps provides lessons into generating positive attitudes for consuming other unfamiliar foods, such as insects described in Chapter 1.

When we share food with others, we display and maintain intimacy to bolster our relationships (Rozin, 1999). Commensalism, food sharing described in Chapter 9, enhances intimacy and is a significant aspect of many cultures worldwide (Miller, Rozin, & Fiske, 1998). Explanations from evolutionary and biopsychology answer why specific eating behaviors are advantageous. But if animals are wired to maximize energy intake it seems counterproductive to share food, yet food sharing is more likely during food scarcity. In the long term, food sharing results in the social benefits of affiliation and reciprocity. Food sharing preserves genetic endowment by protecting those who share DNA or those who will help protect offspring (Nunes et al., 2019) or by garnering paybacks when needed. When vampire bats’ probability of regurgitated blood donations to other bats were experimentally blocked or allowed, female bats who previously donated more blood to other bats received significant increases in donations—both in number of non-kin donors and their size of donation (Carter & Wilkinson, 2015). By giving in good times, the bats received help when they needed it. In the short term, explanations from behavioral psychology highlight the immediate benefits for the food sharer in reducing harassment from other members of the group (Stevens & Gilby, 2004), referred to as “ganging up on free riders” (Boyd, Gintis, & Bowles, 2010). From this perspective, food sharing is learned via negative reinforcement to avoid aversive social interactions (see Chapter 7). Social psychological perspectives provide the empathy–altruism hypothesis, which argues that humans may share food to alleviate one’s own aversive state of negative emotions brought about by empathizing with others' plights, such as hunger (Batson et al., 1989). As you can see, there is no shortage of payoffs for food sharing. The institutions of culture and civilizations, from restaurants to grocery stores to transportation networks, facilitate our ability to eat and enjoy food (Rozin, 1999), providing opportunities to learn from our own and other cultures. Common food choices within

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groups emerge in infancy, framing food choice as a social, rather than purely nutritional, dilemma to enhance understanding of cultural eating behaviors (Liberman et al., 2016). When we are young, table activities serve as developmental antecedents to our later food experiences, as a means to transmit cultural knowledge (Cargill, 2011). The Australian product vegemite, a yeast extract similar to the British marmite, was marketed for its health benefits as a source of B vitamins (Rozin & Siegal, 2003). The preference for vegemite is a marker of cultural identity, as vegemite is enjoyed almost exclusively by those who first taste it in childhood. By studying the role of culture in a community and in a person, we glean better understanding of both similarities and diversity, advancing appreciation of psychological processes involved in eating (Wang, 2016).

The Humble Dumpling: Creativity and Cuisine From bao to pelmeni to samosa, many global cuisines possess a form of the dumpling. Dumplings can be sweet like aebleskiver and Švestkové knedlíky, savory wontons and gyoza, or either in the case of empanadas. Why are these joyous little pillows so ubiquitous? They provide solutions to several problems. Each dumpling has a carbohydrate dough pocket that serves as a vehicle for tasty fillings, the ingredients tend to be affordable, and they are portable. In Chapter 2, creativity is defined beyond the traditional artistic sense, to include the generation of novel ideas and solutions to problems, as innovation facilitates the movement from an idea to an outcome. The dumpling exemplifies this type of creativity, providing an answer to the challenge of affordable portable food. The contemporary ubiquity is evidence of their success. From victory gardens to COVID sourdough starters, food is a creative outlet to promote well-being in the most challenging of times. The academic study of creativity reveals its potential to enhance positive emotions and well-being (e.g. Conner, DeYoung, & Silvia, 2018). The act of cooking contributes to social bonding and improvement in mood (Mosko & DeLach, 2020), often a signal of love and support. Creativity is nurtured in the proper setting, as opportunity for challenge, a sense of purpose, and collaborative relationships enhances creativity at work (Allen, 2012). It is easy to imagine a restaurateur designing the kitchen to embody these characteristics, but perhaps more challenging to expect them in our own kitchen. Creativity can also present as the synthesis and extension of elements seen elsewhere, in the case of fusion food, or new interpretations of the dumpling. While creativity was a necessity for most of human history, it now seems a luxury, or at least a choice, in a time of abundant options. Sometimes when we cook, we aim to produce something beautiful, but typically our goals center around nourishment. Cooking is an opportunity for “everyday” creativity, more functional than aesthetic, motivated by satisfying both biological and cultural needs (Allen, 2012). Cooking skills can solve the problem of basic needs for nourishment and the complexity of navigating our modern food environment. The definition of creativity above demonstrates adaptive benefits of behavioral flexibility, allowing folks to acquire and prepare foods given

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the resources available. This form of creativity is less celebrated than large-scale creative achievements, but daily and personal instances of creativity and discovery improve wellbeing (Connor, DeYoung, and Silvia, 2016) as well as the food prepared. As a reader of this chapter, you likely have faith in the capacity of shared meals to restore and bring folks together. In some ways, caring about food is now easier than ever given globalization, the proliferation of a food-centric ethos, and the vast academic and popular culture domains for food-related information, including the rise of the psychology of eating. The claim that food is a cultural asset is widely supported, from museum and art exhibits depicting the beauty of food, journalistic interrogation of cuisine, the success of food-related entertainment media, and interdisciplinary academic and scholarly pursuits addressing food and eating.

Dessert: Reflections at the End of the Meal In 2020, at the intersection of the global coronavirus pandemic and pivotal moment for racial justice in the United States and around the globe, food scholars brought questions of ethics and eating to the public forum. The values and consequences of food choices are apparent, from detriments of cultural appropriation to the environmental impacts of following a food trend and the treatment of food workers across the food system. These issues demonstrate the complexity of navigating the modern food environment and abundant choices in the ways we eat. How do concepts from the text impact or connect with your personal food philosophy? The goal of this text, to provide a thorough yet thought-provoking review of the contemporary understanding of the psychology of eating, may have inspired or confirmed your own food values. It can feel overwhelming to distill the lessons down to the most essential take-aways. Our understanding of eating is bolstered by the assertion that cuisine includes not just food but also the common social roots connecting the people who care about the food. Be encouraged to identify the most inspiring material and the concepts that inform your professional pursuits. Food and eating provide ample opportunities for the pursuit of social justice. Think of this as an exercise to “pick your passion,” encouraging optimism for the multiple avenues by which people can positively impact the well-being of ourselves and our community.

Dining Review Key Elements

Recommended Reviews

Whet your appetite: Spices

Does geographic location influence cuisine beyond the ingredients, spices, and flavorings used? Brainstorm specific examples.

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Key Elements

Recommended Reviews

The amuse-bouche: Cooking

In what ways do your personal cooking practices promote food safety? Identify spices and seasonings used, as well as other methods.

Course 1: Cooking and cuisine

Now that we have reached the conclusion of the text, do you agree with this definition of cuisine? Are there other components of features you would add to this definition? Does this definition adequately incorporate the psychology of eating?

Course 2: Food policy

Identify a specific food policy designed to secure food safety or sovereignty in a community. Next, find assessment research on the efficacy of that type of intervention. What are barriers to more widespread use of that program?

Morsel: COVID-19 and food

Locate additional historical events that challenged our food system. Describe the time course and reach of that event, and make projections for longer-term outcomes of Covid-19.

insecurity Course 3: Food as a cultural asset

Dessert: Reflection

In what ways can the “food as a cultural asset” approach improve our well-being and relationship with food? Incorporate concepts and evidence from previous chapters, for example, food and development, disordered eating, learning, and cognition. In what ways is food a creative outlet for yourself and your loved ones? What are your essential take-aways from the psychology of eating and your reflections at the conclusion of the text?

Gochisousama Thanks to the Chef! Recommended Reading ● ●

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The Search for General Tso (2014), a documentary film about Chinese food in America Civil Eats, a nonprofit organization and daily news source for critical analysis of the food system, http://civileats.com Arizona State University Project Humanities resources, https://projecthumanities.asu. edu/content/cultural-appropriation

Glossary Consumerism:

encourages the purchase of goods and services

Correspondence bias:

the tendency to interpret others’ behavior as stable and attributable to aspects of their personality/way of being, and our own behavior to situational factors

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Cuisine:

characterized by the ingredients, spices and seasonings, techniques, guidelines, and the people that care about a particular type of food, typically shared in a geographic region

Cultural appropriation:

the adoption of elements from another culture and using them as your own, tends to be exploitive in nature and fails to grant credit to the source or origin of ideas, symbols, artifacts, foods, styles, and so on

Culture:

the shared attitudes, behaviors, values, and traditions within a group of people or community that are passed to subsequent generations

Food security:

“exists when all people, at all times, have physical and economic access to sufficient safe and nutritious food that meets their dietary needs and food preferences for a healthy and active life” (FAO, 2008)

Food sovereignty:

the rights of the people to healthy and culturally appropriate food, prioritizes local food systems defined by the local people, and production through sustainable methods

Fusion:

dishes or cuisine that combines elements from differing culinary traditions

Globalization:

broadly describes the interdependence of the world, from people and culture to information and economy

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Index

Note: Page numbers in bold and italics refer to tables and figures, respectively.

abolishing operation 152, 163 acceptance and commitment therapy (ACT) 252–3 acculturation 269 acetylcholine 88 adaptation 60–1, 68, 226 adaptive eating 49, 264 adipose (fat) tissue 76, 77, 79, 80, 94, 183 adiposity and BMI 28, 214 excess 215, 217 adolescents with anorexia nervosa 241 binge eating 167, 187, 203 BMI 28 caregivers influence on 184 with depression 187 disordered eating in 183, 186–7, 248–9, 255 fast-food consumption 167, 203 obesity 218, 241 peer influence 185 advertisements children food 207, 230 and conditioned responses 150–1, 157 offensive advertising, ban on 197 ageusia 99 agouti-related peptide (AgRP) 83 agriculture subsidies, and obesity epidemic 192, 230 alcohol (ethanol) 115–16, 208–9, 227 excessive drinking 160–1 French paradox 203, 207–9 norms 197, 199–200 polydipsia 145, 148, 159, 161 psychoactive effects of 115–16 reward 30, 51, 88 sommeliers 113–14 taste sensitivity 105 almonds 264

amenorrhea 51, 68, 241 American Psychological Association (APA) 37 American Society for Nutrition 129 amino acids 12, 76, 103 amniotic fluid 168–9 amygdala 84, 87, 89, 94, 108, 109, 112, 116, 146, 148, 249 Anaya, Jordan 36 ancestral past, appeal of 43, 47, 48–9 anchoring bias 194, 210 animal intelligence 154–5 Animal Welfare Act 38 anorexia nervosa (AN) 240–2, 248, 257 diagnosis of 240–1 and emotional dysfunction 250 and internalization of thin ideal 249 media portrayals of 255 mortality 241–2 pharmacotherapy 253–4 prevalence of 241 psychological distress connected 241 and reward system 251 self-regulatory control 249–50 serotonin-based mechanism 250 anorexigenic signals 78, 80, 83, 87, 96 anosmias 99, 106, 118 anterior cingulate cortex (ACC) 84, 85, 113 antioxidants craze 43 dieting 225 appetite hormones and signals 77–8, 87, 90, 91, 96, 115, 133, 229, 251 appetitive motivation 88 arcuate nucleus 82, 83, 88, 217, 228 arousal 54, 68, 83, 87, 88, 134, 202 arthropods 3, 4–5 assimilation 185, 189 Association for the Study of Food and Society (ASFS) 6

354

attitudes, towards food 3, 8, 9, 16, 17, 21, 23, 29, 43, 127, 137, 138, 139, 140, 141, 151, 182, 196, 199, 200, 210, 231, 237, 262, 266, 267, 272, 278 automatic attitudes 137 authentic foods/cuisine 49, 121, 194, 266, 267, 278 avocados 264, 265 avoidance strategies, and negative emotions 186 avoidant-restrictive food intake disorder (ARFID) 180–1, 189, 238 Axel, Richard 108 Bandura, Albert 156 bariatric surgeries 229, 230 behavior 9–10, 74–5, 91, 137–8 behavioral economics 121, 129 behavioral psychology 8, 136 behavior-disorder 239 classical conditioning 144–51 defensive behaviors 272 and eating disorder 238, 242–3 food-seeking behavior 83–4 health behaviors 13–14, 41, 128–9, 186–7, 233 hyperkinetic behavior 42, 46 innate behavior systems 52–4 in known wait times 162 measures 27 models 156, 163 and motivation 74, 87 observant learning 156–62 operant conditioning 151–6 theory of planned behavior 23 belief perseverance 21, 42, 45 beneficence 37 binge drinking 159, 161, 208 binge eating 92, 160 and boredom 187 and polydipsia 161 risk factors 183 and social networking 203 binge eating disorder (BED) 242–3, 257 comorbidity 243 diagnosis 243 pharmacotherapy 254 physical impact of 243 prevalence 243 and reward system 251 biological preparedness 57, 69, 149, 163 biopsychology of eating 72–5 and brain 80–94

Ind ex

endocannabinoids 94–5 hunger and satiety signals 11, 77–80, 83–4, 88, 115, 217 metabolism and homeostasis 75–7 motivation 74–5 nervous system and endocrine system 72–4 positive-incentive perspective 75 reward network 220 biopsychosocial approach 9–10, 10, 18, 65– 6, 273 to alcohol consumption 116 to overnutrition and obesity 214, 223, 230 to pica 9 bitter taste 103–5, 114, 146, 159, 170, 184 blood glucose diabetes 80 levels of 75–6 and willpower 85–6, 90 body composition 28, 137–8, 214 body dissatisfaction 246–7, 248–9, 250, 253, 257 body image distortion 248, 254, 257 body mass index (BMI) 214, 255 and adiposity 28, 214 and anorexia nervosa 239, 241, 253 below-normal 51 BMI cutoffs 28, 43, 215 and bulimia nervosa 242 limitations of 28 and RTECs 206 and self-control 187 body positivity 213, 232–3, 235 boredom, impact on eating 186–7 “bottomless bowl” study 36 bottom-up processing, 118, 138 in gustation and olfaction 112–13 Bouchet, Frédéric 114 brain 80–7, 94 complexity in 80 and glucose consumption 76 integration of signals 90–3 interoceptive cues 83–4 structures and anatomy for regulating eating 76, 81, 82 brain development, pattern of 80–4 branded experiences 185 breakfast 130–2 cereal 131 contemporary breakfast 132 imperative 131–2 breastfeeding 174–5, 263 Buck, Linda 108 bugs as food 1–2, 3, 8. See also arthropods

Index 355

bulimia nervosa (BN) 183, 242, 257 comorbidity 242 diagnosis 242 mortality rate 242 pharmacotherapy 254 prevalence 242 and reward system 251 self-regulatory control 250 serotonin-based mechanism 250 cafeterias 27, 59, 69, 156, 273 caffeine 103, 153, 154, 185 California Milk Processor Board 198–9 calories 12 calorie counting 238–9 information in menus of restaurants 127 Capaldi, Elizabeth 5, 146 caregivers practices, impact on food consumption 176 pressure, linked to children’s food rejections and picky eating 179 Carême, Marie-Antoine 112, 117 Cargill, Kima 221, 272 L-carnitine 91 case studies 32, 45 categorical thinking 99, 102, 122–4, 128, 139, 141 categorization 121–3 celebrations, food and drinks in 3 celebrities 198 Centers for Disease Control and Prevention (CDC) 16, 28 central nervous system 74, 76, 80, 111, 115 central route, of persuasion 197, 198, 199, 210 Chaffee, Leighann 4–5 CHEFFs (Cooking, Healthy Eating, Fitness and Fun) program 182 chewing gum 90, 134–5 children cereals of 204–6 early childhood 176–83 failure to thrive condition 171 food marketing, restrictions or ban on 230 infancy and toddlerhood 169–76 kid foods, social influence 204–7 lunches 167–8 middle childhood 183–7 negative experiences with a food 158–9 with obesity 215 prenatal development 168–9 ready-to-eat-cereal (RTEC) 204–6 resisting temptations 187

restaurant menus 206–7 self-control 187 verbal comments, influence over consumption 181–2 Chinese cuisine 273 chocolate, craving for 153–4 choice, definition of 69 cholecystokinin (CCK) 78, 88, 91, 148, 217 cholesterol 12, 39, 206, 207 cilantro 40, 111 cingulate cortex 84, 146 anterior cingulate cortex (ACC) 84, 85, 113 citrus fruits 122 classical conditioning 144–6 conditioned responses, application of 150–1 conditioned taste aversion 148–50, 163–4 flavor–flavor associations 146–7, 147 flavor–nutrient associations 147, 147–8 Coca-Cola 195 cocaine- and amphetamine-related transcript (CART) 83 cognition 121–32, 139, 141 categorization 121–3 and food choices 124–32 heuristics 123–4 parallel automatic processes of 136 collateral consumption 160–2 colonialism, impact on food landscapes 265, 267, 270 color 117, 121–2, 195 comfort food 71, 94 commensalism 195, 210, 274 communicating with others, via food 195 comparative anatomy 49–50 compensatory health beliefs 128–9, 132, 141, 227 conditioned reinforcers 155, 163 conditioned responses (CRs) 144, 145–6, 150–1, 163 conditioned stimuli (CS) 144–5, 150, 151, 163 conditioned taste aversion (CTA) 137, 148–50, 159, 163–4 development of 149–50 confirmation bias 42, 45 conflicts of interest, in food industry 132 conformity, of eating 203–4, 248 congruency with expectation 124 consensus bias 200, 210, 248 constructed emotion, theory of 65, 70 consumerism 271–3, 277 consumption tracking 27, 59, 93, 135 contagion 64–5, 128, 129, 139, 141, 202–3, 248

356

controversies, in psychology of eating 43 cooked foods 47, 51, 52, 103, 273 cooking foods and brain growth 51–2 and properties of food for consumption 51 cooking hypothesis 50–2, 69 and correlated changes in anatomy 52 corollaries 50, 69 correspondence bias 196, 277 cortex 84 counterconditioning 150, 164 COVID-19 ageusia 99 anosmia 99 and food insecurity 271 impact on restaurants 194 and sensory loss 110–11 creativity behaviors 272 and cuisine 266–7, 275–6 crickets 2 cue exposure with response prevention (CERP) 145–6 cues 144–5 cuisine 261, 278 and adaptive eating 264 authenticity of foods 267 Chinese cuisine 273 and creativity 275–6 cultural appropriation 266–7, 278 cultural values and rules 262 Czech cuisine 273 flavor combinations 262–3 food as a cultural asset 273–5 food policy 267–73 founder ingredients 262 French cuisine 265 fusion food 266 globalization and culinary trends 265–6 haute cuisine 262 ingredients and seasonings 261 preference with purpose 262–5 protective benefits 263 recipes 261 religion-specific rules 263 reservation of food items for special occasions 261 spices 260 culture 3, 18, 262, 278 cultural appropriation, of cuisine 266–7, 278 cultural asset, food as 273–5, 276 cultural identity, food as 3

Ind ex

culturally-bound syndromes 237 and taste 102, 105, 110, 111 Czech cuisine 273 Darwin, Charles 63, 65 da Silva, Stephanie 3 Davis, Clara Marie 170 decision making, of food 58, 84–5, 86, 89, 121, 123–4, 127, 128, 133, 141 defensive behaviors 272 delay discounting 85, 121, 231, 248, 249 delay(ed) gratification 187, 189 depression, impact on eating 65, 87, 91, 110, 152, 161, 186–7, 229 descriptive norms 199 dessert effect 146, 148, 163, 182 developmental stages and typical patterns of eating 172–3 diabetes 48, 80 and low birth weight 61–2 prevalence 62 type 1 80 type 2 61–2, 80, 116, 130, 174, 215 dialectical behavior therapy (DBT), for EDs 252 dietary changes, corollaries of 50 dietary prescriptions 14 dietary restraint 88, 138, 218, 221, 235, 246, 247 diet-induced obesity 80, 216–18 dieting 235 false promises of 225–6 and obesity 223–6 social influences on 191 digestion and metabolism 11, 18 factors impacting in 12 fiber 12 high-density lipoprotein (HDL) cholesterol 12 low-density lipoprotein (LDL) cholesterol 12 pancreas 12 discrimination 110, 196, 210, 213, 232 disgust sensitivity 64–6 disinhibition 115, 156 disordered eating 257. See also eating disorders (EDs) among girls 183, 186 behavior-disorder spectrum of 239 non-normative eating 238, 258 displacement activity 160–2 displacement of persons 269 dopamine 64, 87–9 alcohol 115 eating disorders 251 flavor associations 148

Index 357

food addiction debate 220 reward system 92, 94, 115, 220 dose insensitivity 122, 128, 129, 141 dual-process model, modes of thinking 136–7 dumplings 275 Dungeness crab 4–5 dynamic inconsistency, in food choices 127–8 early childhood Avoidant Restrictive Food Intake Disorder (ARFID) 180–1 characteristic consumption 176–8 environmental influences 181–3 picky eating 178–80 eating disorders (EDs) 257 anorexia nervosa (AN) 240–2 associated and risk factors for 246, 248–9 behaviors, intensity, and functionality factors 238 binge eating disorder (BED) 242–3, 254 biopsychological etiology of 249 and body dissatisfaction 246–7, 248–9, 250, 253 bulimia nervosa (BN) 242 diagnosis 238–40 and drive for thinness 249 educational programs 254 environmental factors 251 etiology 246–51 and exercise 253 familial factors 248 in Fiji 237 genetic factor 251 globally 237–8 individual and familial approaches to 252–3 insula 249 interoceptive awareness 249, 257 Muscular-Oriented Disordered Eating (MODE) 244 Night Eating Syndrome (NES) 244, 258 orthorexia 244–5 Other Specified Feeding or Eating Disorder (OSFED) 244 pharmacotherapy 253–4 portrayals of 254–5 psychobiological contributors to 248–51 psychotherapies for 252–3 purging disorder 244 reward-related contributions to 251 rumination-regurgitation syndrome (RRS; rumination syndrome) 243–4 serotonin-based mechanism of 250–1

severity 239–40 sociocultural contributors to 246–8 sociocultural patterning of 237 Unspecified Feeding or Eating Disorder 244, 258 Eating in the Absence of Hunger (EAH) 176, 189 eating pace 120–1 E. coli 149 ecological influences 192 commercial presence 192–3 food away from home (FAFH) 193–4, 207 restaurants 193–4 supermarkets 192–3 economics of overconsumption 222–3 effect size 34, 41, 46 emotions basic and primary 63–6 constructed emotion, theory of 65 dysregulation 250 functions in consumption 64 negative emotions (See negative emotions) role in eating 3 time orientations 66 empathy–altruism hypothesis 274 endocannabinoids 92–3, 94–5, 229 endocrine system 72–4 endorphins 145 energy-dense food 177 energy density 12, 18, 147 and nutrient density, difference between 15 energy homeostasis 77 in brain 83 control of 84 energy model 85 energy needs, in eating 93 enforcement in eating 155–6 enhanced cognitive-behavior therapy (ECBT), for EDs 252 enteric nervous system 91, 96 entomophagy 1–2, 4–5, 8, 9, 18 epigenetic 63, 69, 222 episodic memory 133 Erikson, Erik 171 Escoffier, Auguste 3, 104, 112 establishing operation 152, 164 The Ethical Principles of Psychologists and Code of Conduct 38 ethical research 35–6 animal subjects 38–9 conflicts of interest 39–40 human participants 37–8 ethnic identity 3

358

ethnographies 32, 46, 48 European dietary guidelines 40 evaluative conditioning 150–1 evolution 49, 69 evolutionary psychology 49–52, 66 comparative anatomy 49–50 cooking hypothesis 50–2 fire, harnessing of 50–2 executive control and function 85, 86, 126–7, 141, 221, 232 exercise for eating disorders 253 efficacy of 227 and obesity 227 and positive cognitions, 227 for training brain 228 experience, power of 143–4 experiments 29, 30–2, 46 explicit attitudes 137 explicit memories 137 Expression of the Emotions in Man and Animals, The 63 external validity 26, 34, 46 extinction 9, 150, 164 extinction procedure, to eliminate CRs 150 extra-homeostatic factors, in eating 93 fad diets 43, 191 failure to thrive condition 171, 189 false consensus effect 200 familial patterning, of eating disorders 251 family-based therapy (FBT), for eating disorders 252 family food preparers (FFPs) 192 fast food 86, 124, 127, 167, 203, 204, 218, 222, 227, 272 fasting 43, 90, 145, 195 fat acceptance movement 233 feedback 76 in endocrine system 74 signal 79–80 feeding and eating disorders (FEDs) 238, 239 Feingold Diet 42 Fen-Phen 228 fermented foods 91, 104, 113, 263 fetal swallowing 168 F-Factor diet 225–6 fiber 12, 48 Fiji, eating disorders in 237 Finlayson, Graham 221 fire, harnessing of 50–2 fixed action patterns (FAPs) 52, 53, 69

Ind ex

flavor associations, basic processes of 148 flavor–flavor associations 146–7, 147, 184 flavor–nutrient associations 147, 147–8, 152 flavors 98 of amniotic fluid 169 based on chemistry 104 combinations 262–3 flavor pairing 114 network 113 perception 111–17 of spices, herbs, and seasonings 260 flavor–sweet associations 150 fluids and homeostasis 77 food addiction 220–1 Food and Agriculture Organization (FAO) 268 food and beverage pairings 114 Food and Drug Administration 226 food at home (FAH) 193 food aversions, learning process 148–50 food away from home (FAFH) 193–4, 207 food-borne pathogens 106 food branding, microaggressions in 197 food choices 2–3, 4–5, 120–1 based on food labels/nutrition labels 125–6 and behavioral economics 129–30 breakfast 130–2 and categorical thinking 128 celebrations and special events 129 and cognitive fallacy 128 and contagion 128 decision making 124 dynamic inconsistency 127–8 and health beliefs 128–9 impact of socioeconomic status on 124 microvariety 125 and tastes 127 food classifications 3 food commodity(ies) 22, 265, 272 food cravings 92, 145–6, 152–4, 169 food deprivation 74–5 food deserts 222 food dichotomies 128 food influencers 185 food insecurity 268–70 and COVID-19 271 Food Insecurity Experience Scale 268 food labels 125–7 food memory, and appetite and satiety 133 food messages 194–5 food neophobia 54, 69 food poisoning 149, 164 food policy 267–9

Index 359

consumption and consumerism 271–3 COVID-19 and food insecurity 271 food sovereignty 270 food popularity and consumption patterns 262 food porn 219–20 food prescriptions 14 food procurement and foraging 52–60 comparisons and individual differences 60 food Selection models 54–8 foraging in contrived settings 58–9 innate behavior systems 52–4 food refusal/rejection 65 bases for 3 disgust 64–6 social influence 195 food-related comments, impact on consumption 181–2 food security 268, 278 food selection models 54–8 matching law (TML) 56–8, 69 optimal foraging theory (OFT) 55–6 food sharing 274, 276 food sovereignty 270, 278 food studies 4–5, 18 anthropology 4 economics 4 history studies 4 nutrition 4 sociology 4 food swamps 222 food taboos 263–4 food values 276 foraging 54, 55, 69 in cafeteria 59 comparisons and individual differences 60 in contrived settings 58–9 foraging bee 56 Fox, Arthur 104–5 French cuisine 265 Freud, Anna 175 Freud, Sigmund 173 Frontiers in Psychology 6–7 functional foods 13–14, 18 fusion food 266, 275, 278 GABA 88, 92, 115, 116 gastric factors and satiety, relationship between 72 gastronome 265 gender identity, and body dissatisfaction 247 gene–environment interactions 218 gene-induced obesity 217

genotype 61, 69 ghrelin in hunger signal 78, 83, 132 in reward network 89, 92, 220 Giessen Raw Food Study 51 glial cells 73 global food crisis (2006–2008) 269 globalization 278 and cuisine 265, 272 glucagon 76 glucose 12, 42, 62, 75, 76, 77, 86 glutamate 88, 103 glycogen 75, 76 gonadal hormones 90–1 Gordon, Aubrey 233 grocery 27, 127, 192, 222 kid’s food in 205 purchasing tax 130 supercenters 193 group foraging 60 gustation 99–106, 118 gustatory pathway 100–1 primary tastants 101–4 taste sensitivity 104–6 gustatory pathway 100–1, 102 gustin (CA6) 105 gut–brain axis 74, 91–2 gut–brain neuropeptides 77–8, 79, 88, 96, 217 gut microbiome 74, 96, 263 habituation 143, 152, 164 Halaas, Jeffrey 80 halal foods 263 haute cuisine 262 Hazda hunter-gatherer society 48 health and enjoyment promotion, for patterns of eating 232 Health at Every Size movement 233 health behaviors 13–14, 41, 128–9, 186–7, 233 health disparity and obesity 221–2 and overnutrition 222 health halo effect 139–40, 141 health literacy, in food choice 127 Healthy, Hunger-Free Kids Act (2012), United States 131 healthy diet 15 dietary guidelines 16 energy density 15 food choices 16 nutrient density 15 and nutritional information 16–17

360

nutritionism 16–17, 19 hedonic hotspots 92 heritability, and obesity 218 heuristics 123–4, 130, 141, 200 high-fat diets 91, 217 hippocampus 84, 87, 108, 109, 132–3 home-cooked meals 272 homeostasis 76, 77, 96, 216 energy 83, 91, 94 hominins 49, 50, 69 Homo habilis 49 Homo sapiens 49, 69 honey 48 hormones 74 appetite hormones 77–8, 90, 91, 229, 251 gonadal hormones 90–1 peptide hormone 75 thyroid hormones 74 household meals 203 How to Cook a Wolf 274 hunger 217, 269 and food sovereignty 270 motivation for food 75 pangs 72, 95 and satiety signals 11, 77–80, 83–4, 88, 115, 217 signals, and serotonin 88 stomach contraction theory 72 war and conflict relationship with 269 hyperconsumption 271–2 hyperglycemia 42, 46 hyperkinetic behavior 42, 46 hyperlipidemia 12 hyperpalatable foods 126, 217, 218–19 hypoglycemia 76 hypothalamus 74, 81–3, 87, 96 arcuate nucleus 82, 83 and brain networks 82 functions 81, 82 lateral hypothalamus (LH) 82, 83 periventricular hypothalamus (PVH) 83 ventromedial hypothalamus (VMH) 82, 83 hypothesis 23, 46 ice cream 113 Ideal Free Distribution model 60 identity creation 195 Ikeda, Kikunae 103 imitated eating. See observational learning Implicit Association Test (IAT) 137 implicit attitudes 137–8 body composition 137

Ind ex

dietary restraint 138 hunger status 137 working memory capacity 138 implicit memory 137 Indigenous people diets 48 ecological knowledge 9 food practices 270 and thrifty genotype 62, 70 industrialized diets 48 infants and toddlers avoidant tendencies 176 bitter and sour taste 170 breastfeeding 174–5 caregiver practices and food consumption 176 early reinforcement 176 eating in the absence of hunger (EAH) 176 flavor preferences 170–1 forming associations 176 neophobia 171–3 salty taste 170 sweet taste 169 influences, in motivation for food 75 ingestive behavior 5, 75, 81, 84, 88, 93 innate behavior systems 52–4, 169 and experience 54 fixed action patterns (FAPs) 53 reflexes 53 temperament 53–4 insect, consumption of 1–2, 3, 8. See also entomophagy insomnia, psychological effects of alcohol 115 Institutional Animal Care and Use Committee (IACUC) 39 Institutional Review Board (IRB) 37 insula 64, 84, 89, 101, 102, 108, 113–14, 116, 119, 220, 249 insulin 75, 80, 96, 217 dysregulation 80 resistance 80, 115, 217 integration of signals 89 gonadal hormones 90–1 microbiome 91–2 and rewards 92–3 internal validity 26, 46 interoception 100, 119 interoceptive awareness 249, 257 interoceptive cues 83–4 interpersonal therapy (IPT), for EDs 252–3 intracellular fluid 77 intragastric feeding 72 intravascular fluid (blood plasma) 77

Index 361

Inuit communities 62 isobutyl isobutyrate 106–7 Jackson Laboratory 79 jaw, of Homo sapiens 49 Journal of the American Medical Association 36 judgment 123, 124–5, 126, 129, 141 Kafka, Franz 271–2 Kahneman, Daniel 121 Keys, Ancel 74–5 kid foods 204–7 branding of 204 contents, in grocery stores 205 marketing 207 ready-to-eat-cereal (RTEC) 204–6 Kreidl, Alois 144 La Cerva, Gina Rae 117 lactase and lactase persistence 66–7, 69 lactose and lactose intolerance 66–7, 69 lateral hypothalamic orexin (hypocretin) neurons 83 Latin America, dietary guidelines 40 La Via Campesina 270 learning processes 143–4. See also classical conditioning; observational learning; operant conditioning Lee, Jennifer 8. 266 leptin 79–80, 83, 88, 89, 90, 115, 133, 217, 218 receptors 80 resistance 92, 217 lexicographic decision rule 123 licorice intoxication 154 limbic pathway 107–8, 109 system 83–4 limited diet 99 lipids 12 Loftus, Elizabeth 135 Logue, Alexandra 5 long-term energy reservoir 75–7 LOVER 109 low-carbohydrate, high-protein diet 226 lunchbox bullying 196, 265–6 macronutrients 12, 13, 15, 16, 19, 76, 77, 88, 94, 126, 216, 264 Maillard, Louis Camille 104 Maillard reaction, and umami 103–4 maldigestion 66–7

malnutrition 9, 13, 14, 61, 170, 174, 206, 214, 222, 239, 245, 249 Man v. Food (TV program) 159 marijuana 94 marshmallow experiments 187 the matching law (TML) 56–8, 69 maximizers 125 meal kits 272 meal size, and overnutrition 216–17 meat consumption 48–9 media communication of cultural norms through 248 exposure, impact on eating 183–4 portrayals of consumption and its related products 196 portrayals of eating disorders 255 medicine effect 150, 164 Mediterranean diet 232 Meiselman, Herbert 25, 43 melanocortins 83, 94, 217 melanocortin receptors (MC3R and MC4R) 83 memory 121, 124, 132–7, 139 age-related decline 110 -based dietary assessment methods 41, 136 diagram 134 episodic memory 133 hippocampus and 84 and nutrition research 135–6 odor-evoked memory 109 working memory 133, 138 Mendelian inheritance patterns 105 mere exposure effect 143, 164, 180 meta-analysis 34 metabolic diseases 61–2, 88 metabolic syndrome 215 metabolism 11, 19, 75, 77, 96 and energy reservoirs 76 and homeostasis 75–7 Mexico, and sin tax 130 microaggressions 196, 197 micronutrients 12, 13, 14, 15, 16, 19, 39, 102, 125–6, 216, 264 microbiome 74, 91–2, 263 microvariety 125 middle childhood branded experiences 185 developing habits 183–5 peer Influences 185 response to negative emotions 185–7, 186 Mindless Eating: Why We Eat More Than We Think 36 modeled eating. See observational learning

362

monogenetic causes of obesity 218 monosodium glutamate (MSG) 21, 103 mood and carbohydrate consumption, relation between 152–3 dysregulation 65 and food, relationship between 87 motivation 74–5, 96 motivational incentive value 75 motivational model 86, 232 mukbang 157 multisensory integration 116–17 Muscular-Oriented Disordered Eating (MODE) 244 Myers, Kevin 152 myristicin 154 National Academies of Sciences, The 40 National Health and Nutrition Examination Survey (NHANES) 127, 135 National School Lunch Program (NSLP) 167 natural selection 7, 49, 55, 60, 63, 69 nature–nurture debate 63, 69 negative emotions and avoidance strategies 186 and health behavior 186 impact on eating 185–6 increased eating due to 186 middle childhood responses 185–7 and obesity 221 negative-state relief model of consumption 66 Neolithic lifestyle 49 Neophobia 54, 69, 143 during developmental stage 171–3 in early childhood 177–8 nervous system 72–4, 73 Nestle, Marion 226 neuroendocrine 80, 83, 90 neuropeptides 77–8, 79, 83, 88, 93, 217 neurotransmitters 73, 97 acetylcholine 88 dopamine. See dopamine GABA 88, 92, 115, 116 glutamate 88, 103 serotonin 87–9, 217, 228, 250 signaling 87–90 new foods first encounter with 143 rejection of 2 resistance, in early childhood 177–8 Night Eating Syndrome (NES) 244, 258 nociception (pain perception) 106

Ind ex

noxious stimuli 148 nondecaying isotopes 48 nonfood reinforcers and punishers 155–6 non-normative eating 238, 258 nontasters 105–6, 114 norms 67, 201. See also social norms norovirus 149 NPY/AgRP 83, 88, 94, 115, 217, 228 nucleus accumbens (NAcc) 88, 89, 92, 94, 220 nutrient density 147 nutrition and diet study, challenges of 14–15 knowledge and beliefs, in food choice 127 labels, regulations of 21, 125, 126, 231 macronutrients 12, 13, 15, 16, 19, 76, 77, 88, 94, 126, 216, 264 micronutrients 12, 13, 14, 15, 16, 19, 39, 102, 125–6, 216, 264 research 135–6 study of 11–15 nutritional science 11 nutritionism 16–17, 19 Nutrition Labeling and Education Act (NLEA) (1990) 126 obedience 203–4 obesity and overweight 13, 235 among girls 183 biopsychological contributions 216–18 and body positivity 232–3 in boys 183 as a contemporary phenomenon 218–19 definition of 213–14 diet-induced obesity 80, 216–18 and dieting 223–6 as a disease 213 and eating disorders 248 economic hypothesis for 223, 235 epidemic 215–18 epigenetic mechanisms 218 etiology 216–23, 235 and exercise 227 and Food Addiction Debate 220–1 gene–environment interactions 218 gene-induced obesity 217 and health disparity 221–2 health risks of 214–15 and heritability 218 and homeostasis 216 interventions 223–32 and leptin 80, 92, 217 monogenetic causes of 218

Index 363

ob knockout mouse model for 79 patterns and prevalence 213–16 pharmaceutical and surgical treatments for 228–9 polygenetic causes of 218 psychological considerations for interventions 231–2 reward hypothesis, and food porn 219–20 risk and associated health consequences 223 social environment modification for 230–1 social influences 213 and stress 221 surgical interventions for 229–30 obesity epidemic 192, 230, 235 obesogenic 218, 230, 232, 235 observational learning 156–7, 157 attention 157–8 combined effects and individual differences 159–60 motivation 158–9 motoric reproduction 158 retention 158 observed learning 196 observed suboptimal foraging 56 odors 108–9 -evoked memory 109–10 signals 116 Ogden, Jane 3, 5, 151 Oji-Cree 62 Olestra, tale of 39 olfaction 100, 106–7, 119 individual similarities and differences 110–11 odor-evoked memories 109–10 olfactory bulb 108–9 olfactory cues 109 olfactory neuroepithelium 107 olfactory neurons, neurogenesis and plasticity of 109–10 olfactory pathway 107, 107–9 ontogenetic selection 60, 70 operant chamber 160, 164 operant conditioning 151 operational definition 23, 27, 28, 46 opioid agonist 92 antagonists 92 endogenous 92, 94, 115, 116, 220 hotspot 92 signaling 94 opium alkaloids 154 optimal diet theory 55 optimal foraging theory (OFT) 55–6, 70

orbitofrontal cortex (OFC) 84, 85, 86–7, 89, 101, 102, 107, 108, 113–14, 116, 117, 132–3, 249 orexigenic effects 78, 83, 97 orexin 83, 88, 92, 94, 115 Orlistat 229 orthorexia 244–5, 255, 258 osmometric thirst 77 osmoreceptors 77 Other Specified Feeding or Eating Disorder (OSFED) 244, 258 outgroup homogeneity effect 196, 210 overgeneralization 196, 210 overnutrition 214, 235 biological, psychological, and social contributions to 224 biopsychological contributions 216–17 definition of 214 etiology 216–23 and health disparity 222 health risks of 214–15 and presurgical eating habits 229–30 socioeconomic impacts 216 overweight. See obesity and overweight pairings 114 palatable foods impact on motivation and attention 231 and reward system 220, 221 Paleolithic diets 48–9 pancreas 11, 12, 75–6, 80 papillae 100, 100, 104 paradigm 26, 46 paradox of choice 125 parallel processing 136–9 Pasteur, Louis 115 Pasteur’s quadrant of scientific inquiry 25 patch foraging 55 pathogens 50, 69 Pavlov, Ivan 144–5, 151, 154 peer influences 185 peptides 76, 78–9, 217 peptide hormone 75 peptide YY (PYY) 78, 217 perceived norms 200 perception 99, 119, 127, 128, 139–40 and behavior control 23 of chemical compounds 106 of emotions 63, 64–5 flavor perception 111–17 influences on 184–5 of label claims 8 norms 199–200

364

of odors 108, 109, 110, 111 taste perception 101, 103, 105–6 peripheral nervous system 74 peripheral route, of persuasion 197–8, 210 persuasion central route 197, 198, 199, 210 persuading consumers 197–9 peripheral route 197, 198–9, 210 routes to 197–8, 198, 210 pharmacotherapy for anorexia nervosa 253–4 for binge eating disorder 254 for bulimia nervosa 254 for obesity 228–9 phenotype 61–3, 70 phenotypic plasticity 61, 70 phenylalanine hydroxylase (PAH) 61 phenylketonuria (PKU) 61 phenylthiocarbamide (PTC) 104–5. See also 6-n-propylthiouracil (PROP)) pheromones 106, 119 Philadelphia, sugar-sweetened beverage purchases in 130 phylogenetic selection 60, 70 physiological measures 27 physiological needs 74–5 Piaget, Jean 171, 173 pica 9–10, 19, 183, 238 picky eating 176–7, 178–80, 189 and Avoidant Restrictive Food Intake Disorder (ARFID), comparison between 180–1 concerns with 179 environmental influence 183–4 and neophobia, comparison between 178–9 tackling 180 piriform cortex 107, 108 placebos 30, 86, 253 planned behavior theory 23 plant-based foods 48 plasticity 89, 100, 109, 217 phenotypic 61 neuroplasticity 73, 89, 101 synaptic 217, 218, 228 plating and presentation 117 pluralistic ignorance 199, 200 polydipsia 160–1, 164 poor diet, impact of 214 portion sizes 16, 123, 136, 145, 192, 200–1, 206, 208, 209, 219 positive energy balance 83–4, 217 positive-incentive perspective 75, 88, 94, 97, 220 post-ingestinal consequences 152

Ind ex

preference with purpose 260, 262–5, 273 prefrontal cortex (PFC) 84–5, 94, 114 anorexia 250 and hippocampus, connections between 133 medial prefrontal cortex (mPFC) 85–7 orbitofrontal cortex (OFC) 84, 85, 86–7, 89, 101, 102, 107, 108, 113–14, 116, 117, 132–3, 249 and reward 126 prejudice(s) 196, 210, 213 prenatal consumption 168–9 prescriptive norms 199 presence of others social facilitation 202 stimulus enhancement 201–2 price policies 230 primary tastants 101–4 bitter 103 salt 102 sour 102–3 sweet 102 umami 103 priming 137, 138 probiotics 91 processed foods 16, 48, 49, 51, 62, 103, 204 advertisement of 151 demand for 193 and food addiction 221 overconsumption of 214, 223, 230, 232 procurement and consumption decisions 124–32 product branding and messaging, classical conditioning in 150 productive stupidity 43 PROP/PTC test strips 106 pro-opiomelanocortin (POMC) 83 6-n-propylthiouracil (PROP) 105. See also phenylthiocarbamide (PTC) protective neophobia 143 proteins 12, 76–7, 263 consumption of animal proteins 3, 48, 223, 264 lean protein 15, 222, 230, 268 leptin 79–80, 83, 88, 89, 90, 92, 115, 133, 217, 218 protein hydrolysate 170 umami 103, 104 and insect consumption 2, 5 Proust, Marcel 109 Proustian memory 109 pseudoscience 43–4, 46, 225 psilocybin 154 psychoactive 164

Index 365

psychoactive properties of chocolate 153–4 effect 115, 154 substances 94, 115 psychogenic polydipsia (PPD) 161 psychology 5–10, 19 psychology of eating 2, 4, 5–7, 6, 11, 15, 19, 21, 22, 25–6, 27, 38, 41 psychotropic effect 154 puberty 183 Public Health Service Policy on Humane Care and Use of Laboratory Animals 38 punishment 117, 151, 155–6, 159, 164, 165 purging disorder 244, 258 raw foods 47, 50–1 ready-to-eat-cereal (RTEC) advantages 206 concerns 204–6 ready-to-eat convenience food 218 reciprocity norms 195, 210 redundant mechanisms 74–5 red wine, for cardiovascular benefit 208 reflexes 53, 70 reflexive actions 154–5 refugees 269 regurgitation 243–4 rehearsal of enjoyable aspects 138 reinforcement in eating 159, 165 food as reinforcers for other (nonconsumption) behavior 154–5 reinforcing and punishing effects of eating food 151–4 releasers 53, 70 religion-specific food preparation 3, 263 researcher, features of 40–3 collaboration of sciences 41 creativity 40 curiosity and enthusiasm 40 humility 42–3 skepticism and critical thinking 41 research methods applied research 25–6, 41, 45 archival research 27 basic research 7, 24–5, 45 case studies 32, 46 confidentiality 37 conflicts of interest 39–40 converging operations 29, 45 cross-sectional studies 31–2 data falsification 36–7 deductive thinking 23 empiricism 21

ethnographies 32 experiments 29, 30–2, 46 food industry, and nutrition research 39–40 longitudinal studies 32 nonexperimental research 29, 32 nonmaleficence 37 null hypothesis significance testing 33–4 peer-review process 24 p-hacking 36–7 quasi-experimental research 29 randomized controlled trials (RCTs) 30 replication 34 research design 24–32 research location 26 scientific claims evaluation 33–40 scientific fraud 36–7 scientific research process 22–4 self-report methods 27 systematic review 34 theory attributes 23 third factor 42, 46 treatment of factors 29–32 variability 35 voluntary participation 37 restaurants children’s menu 206–7 food away from home (FAFH) 193–4 retention 49, 70 reward 92–3, 126–7 dopamine reward system 92, 94, 115, 220 endocannabinoid 92–3, 94–5, 229 and food porn 219–20 hedonic hotspots 92 liking of 92 network 88, 92, 220 positive-incentive perspective 75, 88, 94, 97, 220 wanting of 92 reward system 88, 162 and anorexia nervosa 251 and binge eating disorder 251 and bulimia nervosa 251 dysregulation of 220 and EDs 251 and palatable foods 220, 221 rimonabant 229 Rolls, Barbara 133 Rosenthal, Robert 35 roughage 49, 70 Rozin, P. 3, 5, 65, 128, 184–5, 247, 273 rumination-regurgitation syndrome (RRS; rumination syndrome) 243–4, 258

366

saliva 100, 144 salt taste 77, 100, 101, 102, 104, 105, 124, 168, 170, 221, 262 Sapolsky, Robert 84 satiety signals 11, 19, 77–80, 83–4, 217 and alcohol 115 insulin 80 and serotonin 88 vagus nerve 78 satisficers 125 saturated fats 12, 16, 126, 207–8, 223 schedule-induced polydipsia (SIP) 160–1, 162, 165 schemas 124 School Breakfast Program, United States 131 Schwartz, Barry 125 Schwartz, Martin 43 science, need for 21 scientific research process 22–3. See also research methods construct of interest 23, 45 dissemination 24, 46 hypothesis 23, 46 theory 23, 46 seasonings 260 seed libraries 270 selection 49, 70 self, food as a feature of 3 self-control 85–6, 89, 97, 187, 189, 249–50 and blood glucose levels 85, 90 in food choice 127 self-medication 152 self-monitoring 202 self-reference effect 138 self-regulation 86, 89–90, 187 self-reported attitudes 137, 146 self-report methods 135–6 semaglutide 229 sensation 7, 25, 99, 100, 106, 108, 119 sensitization 143, 165 sensory aspects of food items 112 sensory-specific satiety 133, 141, 143 serotonin (5-HT) 87–9, 217, 228 serotonin dysfunction 250 settling zone theory 216, 235 sham feeding procedures 72 short-term energy reservoir 75–7 sign stimuli 53, 70 sin taxes 129–30, 230 Sirtfood Diet 225 sixth sense 99–100 small exceptions, in cognition 129

Ind ex

social class and diet, relationship between 268 social contagion 202–3, 210 social facilitation 202, 210 social groups, food distinctions and classifications by 195 social influences on dieting 191 on eating 191, 265 food messages and beliefs 194–201 French paradox 207–9 kid foods 204–7 obesity 213 presence of others 201–4 social networks 191 social interaction, food as 3 socially mediated reinforcers 155–6 social networking 202–3 social norms 199–201, 210 and disordered eating 246 impact on body image and ideals 248 portion sizes 200–1 Society for the Study of Ingestive Behaviors (SSIB) 6 socioeconomic status (SES) 31, 131, 167, 231 and diet quality 268 food choices 124 and obesity 221, 222 overnutrition 216, 221 sommeliers 113–14 sour taste 102–3, 170 special occasions and small exceptions 129 spices 260, 265 spicy food 105–6 stereotyped beliefs 196–7, 211 stimuli, food and food-related 54, 144–5, 146 stimulus enhancement 201–2, 211 stomach contraction theory, of hunger 72 stress 30–1, 33–4, 91 and disordered eating 239, 241, 244 impact on eating 125, 185–6 and obesity 221–2 stuffy nose (rhinorrhea) 99 subdisciplines of psychology 7–8 suboptimal diet 16, 214 sugar cravings 169 sugar high 42 sugar-sweetened beverages 39, 129, 130, 223, 230, 232, 269 supercenters 222 supermarket stores 192–3 supertasters 105–6

Index 367

supplements 13, 14, 91 survival mechanisms 60–6 and food 88 primary emotions in consumption 63–6 thrifty phenotype 61–3, 70 Su Wen collection 101 sweet 34, 100–1, 102, 104, 113–14, 122, 155, 195, 204, 207, 220, 262, 275 cravings 153 flavor-sweet association 150 preference for 169, 170 Taco Bell 195 taste 98, 117 conditioning 148–50 in food choices 127 sensitivity 104–6, 119 signals 89 Taste Avoidant Learning (TAL) 156, 159 taste buds 113 taste receptor 2 family (TAS2R) 105 tasters 105–6 nontasters 105–6, 114 supertasters 105–6 temperament 53–4, 70 temperature, influence over flavor 113 temporal cues 145 temptation management 232 thalamic-orbitofrontal pathway 107–8 Thaler, Richard 121, 127 theobromine 153 thin ideal 237, 246, 247 internalization of 248, 249 thinness, and eating disorders 249 “thin subsidy” price policies 230 thrifty phenotype 61–3, 70 thyroid hormones 74 Tiny Tastes program 182, 183 tongue and papillae 101 top-down influences, in flavor perception 117 top-down processing 111, 112–13, 116–17, 119 traditional feeding practices 177 Traditional Knowledge 8–9, 19 trimethylamine-N-oxide (TMAO) 91 TRPV1 106 Tsimane people 48

Tu, Youyou 8–9 two-factor theory 65 ultra-processed foods/diets 126, 218–19, 224 umami 100, 103–4, 112 unconditioned reinforcers 155, 165 undernourishment 62, 167, 268–9 unit bias 123, 124, 141, 200 United Nations, Sustainable Development Goals 2 United States and cafeterias 59 dietary guidelines 40 and food labels 126 research involving controlled substances 95 South, and food choices 127 unknown stimuli 54 unprocessed diet 219 unspecified feeding 244, 258 vagus nerve 74, 78, 81, 99 variability, in taste sensitivity 104 variation 49, 70 ventral tegmental area (VTA) 88 verbal comments, influence over consumption 181–2 vicarious punishment 156, 165 vicarious reinforcement 156, 165 visual cues, in flavor perception 117 volumetric thirst 77 vomeronasal organ 106 Walker, Genevieve 272 Wansink, Brian 36–7, 43 war and conflict, relationship with hunger 269 Watson, John 150 weight discrimination and bias 213, 232 weight stigma 213 WEIRD samples 34–5, 43 Westernization of diet 223 wine consumption 208–9 tasting 113–14 working memory 133, 134, 137, 138 World Central Kitchen 271 World Health Organization (WHO) 16, 28, 135 Wrangham, Richard 51, 52, 273

368