Neuropsychology of cardiovascular disease [Second ed.] 9781848726567, 1848726562, 9781848728790, 1848728794

Table of contents :
Cover
Half Title
Title Page
Copyright Page
Dedication
Table of Contents
List of Contributors
Acknowledgments
Preface
Part I Behavioral and Biomedical Risk Factors
1 The Effects of Tobacco Smoke on Cognition and the Brain
2 Alcohol Consumption, Brain, and Neurocognition
3 Activity and Neurocognitive Health in Older Adults
4 Hypertension, Blood Pressure, and Cognitive Functioning
5 Effects of Cholesterol and N-3 Fatty Acids on Cognitive Functioning, Decline, and Dementia
6 Cognition in Diabetes and Pre-Diabetes Stages
7 Neurocognitive Aspects of Obesity
8 Inflammation and Preclinical Neurocognitive Decline
9 Homocysteine, Folic Acid, B Vitamins, and Cognitive Functioning: A Review of the Literature
10 Resting and Stress-Reactive Cortisol
Part II Cardiovascular Disease and Interventions
11 Subclinical Cardiovascular Disease and Neurocognition
12 Clinical Cardiovascular Disease
13 Neurocognitive Changes Following Coronary Artery Bypass Grafting
14 Neuropsychology of Heart Failure
Part III Dementia and Stroke
15 Vascular Cognitive Impairment
16 Cardiovascular Risk Factors and Dementia
17 White Matter Disease, Stroke, and the Heterogeneity of Vascular Dementia
18 Structural Brain Mechanisms and Dementia
Index

Citation preview

NEUROPSYCHOLOGY OF CARDIOVASCULAR DISEASE

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in the United States and most westernized nations. Both CVDs and their risk factors confer substantial risk for stroke and dementia, but are also associated with more subtle changes in brain structure and function and cognitive performance prior to such devastating clinical outcomes. Indeed, it has been suggested that there exists a continuum of brain abnormalities and cognitive difficulties associated with increasingly severe manifestations of cardiovascular risk factors and diseases that precede vascular cognitive impairment and may ultimately culminate in stroke or dementia. This second edition examines the relations of a host of behavioral and biomedical risk factors, in addition to subclinical and clinical CVDs, to brain and cognitive function. Associations with dementia and pre-dementia cognitive performance are reported, described, and discussed with a focus on underlying brain mechanisms. Future research agendas are suggested, and clinical implications are considered. The volume is a resource for professionals and students specializing in neuropsychology and related fields, and for other physicians and health care professionals who work with patients with, or at risk for, CVDs. Shari R. Waldstein, PhD, is Professor of Psychology, Gerontology, and Medicine at the University of Maryland, Baltimore County and University of Maryland School of Medicine. Merrill F. Elias, PhD, MPH, FAHA, is Professor of Psychology and Cooperating Professor at the Graduate School of Biomedical Science and Engineering at the University of Maine.

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NEUROPSYCHOLOGY OF CARDIOVASCULAR DISEASE Second Edition

Edited by Shari R. Waldstein and Merrill F. Elias

Second edition published 2015 by Psychology Press 711 Third Avenue, New York, NY 10017 and by Psychology Press 27 Church Road, Hove, East Sussex BN3 2FA Psychology Press is an imprint of the Taylor & Francis Group, an informa business © 2015 Shari R. Waldstein and Merrill F. Elias The right of the editors to be identified as the authors of the editorial material, and of the authors for their individual chapters, has been asserted in accordance with sections 77 and 78 of the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this book may be reprinted or reproduced or utilized in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. Trademark notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. First edition published by Psychology Press 2001 Library of Congress Cataloging-in-Publication Data Neuropsychology of cardiovascular disease / edited by Shari R. Waldstein and Merrill F. Elias. – Second edition. pages cm Includes bibliographical references and index. 1. Neurobehavioral disorders. 2. Neurologic manifestations of general diseases. 3. Cardiovascular system–Diseases–Complications. 4. Cardiovascular system–Diseases–Psychological aspects. I. Waldstein, Shari R. II. Elias, Merrill F., 1938RC455.4.B5N475 2015 616.8′4–dc23 2014029749 ISBN: 978-1-84872-879-0 (hbk) ISBN: 978-1-84872-656-7 (pbk) ISBN: 978-1-31585-187-7 (ebk) Typeset in Bembo by Wearset Ltd, Boldon, Tyne and Wear

With love, to my sister Diane. Shall we continue to enjoy the same stories again and again? S.R.W. To the memory of my friend, student, and colleague, Norman (Norm) R. Schultz, Jr. PhD, who refused to let me get out of this business and gave everything to it he possibly could. M.F.E.

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CONTENTS

List of Contributors Acknowledgments Preface

x xiv xv

PART I

Behavioral and Biomedical Risk Factors 1 The Effects of Tobacco Smoke on Cognition and the Brain Gary E. Swan and Christina N. Lessov-Schlaggar

1

3

2 Alcohol Consumption, Brain, and Neurocognition Francesco Panza, Vincenza Frisardi, Davide Seripa, Alberto Pilotto, and Vincenzo Solfrizzi

35

3 Activity and Neurocognitive Health in Older Adults Michelle C. Carlson and Vijay R. Varma

79

4 Hypertension, Blood Pressure, and Cognitive Functioning Merrill F. Elias, Amanda L. Goodell, and Michael A. Robbins

109

viii

Contents

5 Effects of Cholesterol and N-3 Fatty Acids on Cognitive Functioning, Decline, and Dementia Matthew F. Muldoon and Sarah M. Conklin

150

6 Cognition in Diabetes and Pre-Diabetes Stages Augustina M. A. Brands, Esther van den Berg, Roy P. C. Kessels, and Geert Jan Biessels

184

7 Neurocognitive Aspects of Obesity Kelly M. Stanek, Lindsay A. Miller, and John Gunstad

219

8 Inflammation and Preclinical Neurocognitive Decline Anna L. Marsland

238

9 Homocysteine, Folic Acid, B Vitamins, and Cognitive Functioning: A Review of the Literature Georgina E. Crichton, Michael A. Robbins, and Merrill F. Elias 10 Resting and Stress-Reactive Cortisol Nida Ali, Vincent Corbo, Laura Copeland, and Jens C. Pruessner

265

295

PART II

Cardiovascular Disease and Interventions

317

11 Subclinical Cardiovascular Disease and Neurocognition Carrington R. Wendell and Shari R. Waldstein

319

12 Clinical Cardiovascular Disease Nathalie Stroobant, Merrill F. Elias, and Amanda L. Goodell

343

13 Neurocognitive Changes Following Coronary Artery Bypass Grafting Patrick J. Smith, Joseph P. Mathew, and James A. Blumenthal 14 Neuropsychology of Heart Failure Ronald A. Cohen and Karin F. Hoth

378

409

Contents

ix

PART III

Dementia and Stroke

475

15 Vascular Cognitive Impairment José G. Merino and Vladimir Hachinski

477

16 Cardiovascular Risk Factors and Dementia Chengxuan Qiu and Laura Fratiglioni

495

17 White Matter Disease, Stroke, and the Heterogeneity of Vascular Dementia Catherine C. Price, Peter Nguyen, Melissa Lamar, and David J. Libon

524

18 Structural Brain Mechanisms and Dementia Samuel N. Lockhart and Charles DeCarli

553

Index

579

CONTRIBUTORS

Nida Ali, MSc, Department of Psychology, Faculty of Science, McGill University, Montreal, Quebec, Canada. Geert Jan Biessels, MD, PhD, Department of Neurology, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, the Netherlands. James A. Blumenthal, PhD, Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA. Augustina M. A. Brands, PhD, Regional Psychiatric Centre/Zuwe Hofpoort Hospital, Woerden, the Netherlands; Department of Experimental Psychology, Utrecht University, the Netherlands. Michelle C. Carlson, PhD, Department of Mental Health, Center for Aging and Health, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. Ronald A. Cohen, PhD, Department of Psychiatry and Human Behavior and the Brain Sciences Program, Alpert School of Medicine, Brown University, Providence, RI, USA. Sarah M. Conklin, PhD, Department of Psychology, Allegheny College, Meadville, PA, USA. Laura Copeland, MSc, Department of Educational and Counseling Psychology, Faculty of Education, McGill University, Montreal, Quebec, Canada. Vincent Corbo, PhD, Translational Research Center on Traumatic Brain Injury and Stress Disorders, Boston Veterans Affairs Research Institute, Boston University School of Medicine, Boston, MA, USA.

Contributors

xi

Georgina E. Crichton, PhD, Nutritional Physiology Research Centre, University of South Australia, Australia. Charles DeCarli, MD, Department of Neurology and Center for Neuroscience, University of California Davis, Davis, CA, USA. Merrill F. Elias, PhD, MPH Department of Psychology and Graduate School of Biomedical Sciences, University of Maine, Orono, ME, USA. Laura Fratiglioni, PhD, Aging Research Center, Karolinska InstitutetStockholm University and Stockholm Gerontology Research Center, Stockholm, Sweden. Vincenza Frisardi, MD, Department of Geriatrics, Center for Aging Brain, Memory Unit, University of Bari, Bari, Italy. Amanda L. Goodell, MA, Department Psychology, University of Maine, Orono, ME, USA. John Gunstad, PhD, Department of Psychology, Kent State University, OH, USA; Institute for Clinical and Translational Research, Summa Health System. Vladimir Hachinski, MD, DSc, FRCPC, Department of Neurology, University of Western Ontario, London, Ontario, Canada. Karin F. Hoth, PhD, National Jewish Health and University of Colorado Denver, Denver, CO, USA. Roy P. C. Kessels, PhD, Helmholtz Institute, Utrecht University, the Netherlands; Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen and Radboud University Nijmegen Medical Centre, the Netherlands. Melissa Lamar, PhD, Department of Psychiatry, University of Chicago, Chicago, IL, USA. Christina N. Lessov-Schlaggar, PhD, Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA. David J. Libon, PhD, Department of Neurology, Drexel University College of Medicine, Philadelphia, PA, USA. Samuel N. Lockhart, PhD, Imaging of Dementia and Aging Lab, Center for Neuroscience, University of California Davis, Davis, CA, USA. Anna L. Marsland, PhD, RN, Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA. Joseph P. Mathew, MD, Department of Anesthesiology, Duke University Medical Center, Durham, NC, USA.

xii

Contributors

José G. Merino, MD, MPhil, Johns Hopkins Community Physicians, Bethesda, MD, USA. Lindsay A. Miller, MA, Department of Psychology, Kent State University, OH, USA. Matthew F. Muldoon, MD, MPH, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA. Peter Nguyen, BS, Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA. Francesco Panza, MD, PhD, Geriatric Unit and Gerontology-Geriatric Research Laboratory, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy. Alberto Pilotto, MD, Geriatric Unit and Gerontology-Geriatric Research Laboratory, IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy. Catherine C. Price, PhD, Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA. Jens C. Pruessner, PhD, McGill Centre for Studies in Aging and Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Quebec, Canada. Chengxuan Qiu, MD, PhD, Aging Research Center, Karolinska InstitutetStockholm University, Stockholm, Sweden. Michael A. Robbins, PhD, Department of Psychology and Graduate School of Biomedical Sciences, University of Maine, Orono, ME, USA. Davide Seripa, PhD, Department of Geriatrics, Center for Aging Brain, Memory Unit, University of Bari, Bari, Italy. Patrick J. Smith, PhD, Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC, USA. Vincenzo Solfrizzi, MD, PhD, Department of Geriatrics, Center for Aging Brain, Memory Unit, University of Bari, Bari, Italy. Kelly M. Stanek, PhD, Department of Psychology, Kent State University, OH, USA. Nathalie Stroobant, PhD, Laboratory for Neuropsychology, Ghent University, University Hospital Ghent, Ghent, Belgium. Gary E. Swan, PhD, Center for Health Sciences, SRI International, Menlo Park, CA, USA.

Contributors

xiii

Esther van den Berg, PhD, Department of Neurology, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, the Netherlands and Department of Experimental Psychology, Utrecht University, the Netherlands. Vijay R. Varma, MPH, Department of Mental Health, Center for Aging and Health, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. Shari R. Waldstein, PhD, Department of Psychology, University of Maryland, Baltimore County, Division of Gerontology & Geriatric Medicine, University of Maryland School of Medicine, and Geriatric Research Education and Clinical Center, Baltimore VA Medical Center, Baltimore, MD, USA. Carrington R. Wendell, PhD, Department of Radiology, Johns Hopkins School of Medicine, Baltimore, MD, USA.

ACKNOWLEDGMENTS

We wish to offer our thanks to the individuals who contributed to this volume. First, and foremost, we’d like to thank each of our authors for their wonderful contributions, and their patience and support during the publication process. We also extend a hearty thanks to our students who provided incredibly helpful technical assistance. Special thanks go to Amanda L. Goodell and Rachel Valentine Torres (University of Maine), and Alina Lightchaser and Salam Syed (UMBC) for their tireless help with the final document! Thanks as well to Allyssa Allen, Faren Grant, Jason Kisser, Jessica McNeely, and Mollie Sprung (UMBC) for their technical help with the final manuscript. We also thank our editors at Taylor and Francis, Paul Dukes and Georgette Enriquez, for supporting a second edition of this volume.

PREFACE

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in the United States and most westernized nations. Both CVDs and their associated risk factors confer substantial risk for cerebrovascular events including ischemic and hemorrhagic stroke, vascular dementia, and Alzheimer’s disease. Yet, prior to such devastating clinical outcomes, cardiovascular risk factors and diseases are associated with a more subtle impact on brain structure and function and cognitive performance. Indeed, it has been suggested that there exists a continuum of brain abnormalities and cognitive impairment associated with increasingly severe manifestations of cardiovascular risk factors and diseases that may ultimately culminate in stroke or dementia. In 2001, we published the first edited volume to examine the Neuropsychology of Cardiovascular Disease (Lawrence Erlbaum Associates, Inc.). This volume addressed the impact of selected traditional cardiovascular risk factors, cardiovascular diseases and their treatments, stroke and vascular dementia on the brain and cognitive function. Since that time, research in this area of investigation has increased tremendously. A multitude of large sample epidemiological investigations has been published, further clinical research studies evaluating underlying biological mechanisms are now available, and many interventions trials have been conducted. It is now increasingly recognized that a host of behavioral and biomedical (both traditional and new) cardiovascular risk factors negatively impact the brain and cognitive function. Furthermore, both subclinical vascular disease and overt CVD negatively influence the brain and cognition. It is also clear that cardiovascular risk factors and diseases are associated with increased incidence and prevalence of vascular dementia, Alzheimer’s disease, and mixed forms of dementia, possibly via both common and dissimilar pathways.

xvi

Preface

Thus, the aim of our second edition is not just to update the chapters included in the original Neuropsychology of Cardiovascular Disease volume, but rather to significantly expand the scope and focus of the work in several ways: (1) inclusion of a broader spectrum of cardiovascular risk factors; (2) coverage of both subclinical and clinical manifestations of CVD, with links to relevant treatments; and (3) increased focus on risk factors and mechanisms of vascular cognitive impairment and dementias. Whenever possible, authors address the issues: (a) What domains of cognitive function are most affected? (b) What are relevant vulnerability or resilience factors? (c) What is the clinical significance of the effects? (d) What are the mechanisms underlying the noted relations? (e) Is there evidence of impact on quality of life, daily function, treatment adherence? (f ) Is there relevant intervention research?

PART I

Behavioral and Biomedical Risk Factors

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1 THE EFFECTS OF TOBACCO SMOKE ON COGNITION AND THE BRAIN Gary E. Swan and Christina N. Lessov-Schlaggar

Tobacco smoke is probably the single most significant source of toxic chemical exposure to humans. The World Health Organization forecast cigarettes will kill nearly nine million people per year globally by 2030 (Mathers & Loncar, 2006). Smoking is associated with an increased incidence of cardiovascular disease (CVD) including coronary heart disease (CHD) (e.g., angina, myocardial infarction, sudden-death, and congestive heart failure), cerebrovascular disease (e.g., transient ischemic attacks, stroke), and vascular diseases (e.g., claudication, aortic aneurysm, and atherosclerosis), and is the primary cause of chronic obstructive pulmonary disease (COPD) (e.g., mucous hypersecretion, interference with ciliary function, and alveolar destruction) (Centers for Disease Control, 1989). Direct medical and lost productivity costs in the United States (U.S.) alone totaled an estimated $193 billion per year between 2000 and 2004 (Lloyd-Jones et al., 2010). Smoking is a causative factor of CHD and raises the risk of developing it by 2–4 times and the risk of dying from it by 2–3 times. Cigarette smoking approximately doubles the risk of death due to stroke and increases the risk for peripheral vascular disease (PVD) by more than 10 times. On average, smokers die 13–14 years earlier than do nonsmokers (Lloyd-Jones et al., 2010). In the U.S. in 2008, among individuals 18 years of age or older, 23.1% of men and 18.3% of women were regular smokers. Almost 60% of U.S. children aged 3–11 (an estimated 22,000,000) are exposed to sidestream smoke. Approximately 443,000 people die each year in the U.S. of illness attributable to smoking. The Centers for Disease Control and Prevention estimates that of this total about 129,000 people die each year due to smoking attributable vascular disease (80,000 from ischemic heart disease, 21,000 from other heart disease, 16,000 from cerebral vascular disease, 1,900 from atherosclerosis, 8,500 from aortic aneurysm, and

4

G. E. Swan and C. N. Lessov-Schlaggar

1,300 from arterial disease). The nicotine in smokeless tobacco increases risk for sudden death due to ventricular arrhythmias and sidestream smoke causes 46,000 deaths due to CHD (Centers for Disease Control and Prevention, 2010). The present chapter reviews current evidence involving prospective studies of the relationship between smoking and neurobehavioral outcomes in children and in adults. In children, early vulnerability factors such as prenatal exposure to cigarette smoke and differences in brain processing in children at risk for smoking are reviewed. In adults the relationship between smoking and single assessments of cognitive status, serial measures of cognitive performance, “preclinical” morphological outcomes such as brain atrophy, white matter hyperintensities (WMHIs), silent infarcts, and disease outcomes such as vascular dementia (VaD) and Alzheimer’s disease (AD) are reviewed. A conclusion of this review is that while there is substantial evidence that smoking is harmful to the brain at both the functional and morphological levels, much more work is needed as to the further specification of high-risk smoking behavior (e.g., smoking topography), functional outcomes, morphological outcomes, and the probable synergies that exist between smoking and other cerebrovascular risk factors including genetic variation to heighten risk for negative outcomes.

Constituents of Tobacco Smoke Mainstream Smoke To understand the toxic effects of tobacco smoke on the cardio- and cerebrovascular systems, it is important to characterize its complex nature. Cigarette smoke consists of two phases: a particulate (tar) phase and a gas phase. The particulate phase contains more than 1017 free radicals per gram while the gas phase contains more than 1015 free radicals per puff. Whereas the radicals associated with the gas phase have a shorter lifespan (seconds), those associated with the particulate phase are longer-lived (hours to months) (Ambrose & Barua, 2004). Among the 4,700 compounds found in tobacco smoke, many are associated with brain toxicity including vinyl chloride, a risk factor for brain cancer, hydrogen cyanide, and arsenic. Other components that could negatively impact the pulmonary system with secondary effects on the central nervous system (CNS) include acrolein, acetaldehyde, formaldehyde, and cadmium (tobacco smoke is the main source of cadmium in humans) (Bernhard, Rossmann, & Wick, 2005; Fowles & Dybing, 2003). Still other components with potential cardiovascular or CNS effects include ammonia, cresol, catechol, carbon monoxide, hydroquinone, lead, methyl ethyl ketone, nitric oxide, phenol, styrene, toluene, and butane (Fowles & Dybing, 2003). From the standpoint of brain toxicity, the presence of heavy metals in tobacco smoke is particularly troubling given epidemiologic evidence that metal

Effects of Smoking on Cognition and the Brain

5

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influences cognitive and brain outcomes.

exposure is a risk factor for AD pathology primarily through an increase in oxidative stress (Liu et al., 2006). Lifetime exposure to lead, as marked by levels in bone in older adults, is associated cross-sectionally with lower levels of functioning in the domains of language, processing speed, eye–hand coordination, executive functioning, verbal memory and learning, visual memory, and visual construction (Shih et al., 2006), with steeper declines in global cognitive

6

G. E. Swan and C. N. Lessov-Schlaggar

function (Weisskopf et al., 2004), and with increases in white matter lesion burden, decreases in total brain volume, frontal and total gray matter volume, and parietal lobe white matter volume (Rowland & McKinstry, 2006; Stewart et al., 2006). While many of the toxic constituents of tobacco arise from the plant itself, others derive from the manufacturing process and still others are purposely added to enhance the flavor, aroma, and/or addictiveness of nicotine. For example, ammonium compounds enhance the reinforcing aspects of cigarettes by (a) enrichment of the mainstream smoke with nicotine; (b) more complete and faster absorption of nicotine; (c) enhanced impact of nicotine at both peripheral and central nicotinic receptors; and (d) improvement of the sensory characteristics of the substance (Willems, Rambali, Vleeming, Opperhuizen, & van Amsterdam, 2006). Menthol flavoring also enhances absorption of nicotine and cancerous nitrosamines (Squier, Mantz, & Wertz, 2010). Although the toxic effects of ammonium compounds (along with many others) appear to be directed largely at the pulmonary system, we would still expect tobacco smoke to have an indirect deleterious effect on the CNS, because pulmonary health is intimately connected to the functioning of the brain (Richards, Strachan, Hardy, Kuh, & Wadsworth, 2005).

Sidestream Smoke Given the toxicity of mainstream tobacco smoke described above, it is perhaps not surprising that sidestream smoke (the smoke from the burning end of a cigarette combined with the exhaled smoke from the smoker) contains the same CNS toxic components and, for some constituents, at higher levels. Sidestream condensate is 2–6 times more tumorigenic per gram than mainstream condensate (Schick & Glantz, 2005; Whincup, Papacosta, Lennon, & Haines, 2006). In the NHANES III survey of 5,683 children between the ages of six and 16 years, higher levels of cotinine (a biomarker for sidestream smoke exposure in nonsmokers) were associated with deficits in reading, math, and visuospatial reasoning but not short-term memory (Yolton, Dietrich, Auinger, Lanphear, & Hornung, 2005), suggesting an adverse effect of sidestream smoke on cognition in children. The effects on cognition from sidestream smoke may not be limited to children and adolescents. Sidestream smoke is also associated with CVD with relative risks of 1.2–1.3, with the effects being, on average, 80 to 90% as large as those from active smoking (Barnoya & Glantz, 2005). Analysis of 4,809 nonsmoking adults aged 50 years or more from the Health Survey of England and English Longitudinal Study of Ageing who also provided saliva samples for cotinine assay (Llewellyn, Lang, Langa, Naughton, & Matthews, 2009) concluded that increased exposure to sidestream smoke was associated with 8–44% increase in risk for cognitive impairment. Of significance in this study was the use of a

Effects of Smoking on Cognition and the Brain

7

biomarker to quantify exposure to sidestream smoke in adults, the adjustment for a wide variety of known risk factors for cognitive impairment, and the use of a global score of cognitive performance derived from a compilation of wellknown, standardized tests of attention and processing speed, time orientation, immediate and delayed verbal memory, prospective memory, numeracy, and verbal fluency.

Nicotine Chronic nicotine exposure induces increased numbers of CNS nicotinic acetylcholine receptors (nAChRs) in animals and human smokers in vivo (Sabbagh, Lukas, Sparks, & Reid, 2002). Neuronal nicotinic acetylcholine receptors are ligand-gated ion channels consisting of ] and ^ subunits. At least 17 nAChRs have been identified with the heteromeric ]4^2 being the most common subtype in the brain and the homomeric ]7 being the next most common. Postmortem and laboratory studies demonstrate that smokers have widespread up-regulation of nAChRs, likely related to desensitization of these receptors from nicotine exposure. Nicotinic acetylcholine receptors are widespread throughout the brain, with particularly high density in the thalamus and basal ganglia (Brody et al., 2004).

Epidemiological Evidence of the Relationship between Tobacco Smoke and Brain Outcomes Children The majority of adult smokers (>80%) initiate cigarette smoking in adolescence. Therefore, childhood and adolescent risk factors for smoking behavior may represent early targets for CVD risk prevention. Decades of research have shown that the pathway to cigarette smoking is a complex interplay of genetic, family, social, cultural, and psychiatric risk factors (Swan et al., 2003). Over 11% of pregnant women in the U.S. smoke cigarettes (Centers for Disease Control, 2004). Nicotine can have direct effects on nAChRs, which are present in the brain and spinal cord at four weeks of gestation (HellstromLindahl, Gorbounova, Seiger, Mousavi, & Nordberg, 1998), suggesting that they play an important role in nervous system development. There is evidence both for and against the association of maternal smoking during pregnancy and offspring cigarette smoking (Al Mamun et al., 2006; Buka, Shenassa, & Niaura, 2003; Cornelius, Leech, Goldschmidt, & Day, 2000, 2005; Kandel & Udry, 1999; Kandel, Wu, & Davies, 1994; Knopik et al., 2005; O’Callaghan et al., 2006; O’Callaghan et al., 2010; Roberts et al., 2005; Silberg et al., 2003). Maternal smoking during pregnancy is highly correlated with maternal smoking later on (Cornelius et al., 2005; Kandel & Udry, 1999),

8

G. E. Swan and C. N. Lessov-Schlaggar

suggesting that smoking during pregnancy may index maternal tobacco dependence (Agrawal et al., 2008). Smoking during pregnancy is itself a heritable phenotype (34% heritability) and 54% of its genetic variance is in common with that of tobacco dependence, suggesting that some of the same genetic factors that predispose to smoking during pregnancy also predispose to tobacco dependence (Agrawal et al., 2008). Thus, the smoking mother is transmitting to her offspring genetic risk for tobacco dependence and is inflicting potentially deleterious effects on fetal growth and neural development through cigarette smoke exposure. In addition, women who smoke are likely to have children with men who also smoke (assortative mating) (Di Castelnuovo, Quacquaruccio, Donati, de Gaetano, & Iacoviello, 2009), thus increasing the transmission of genetic risk for smoking behavior. In fact, spousal concordance for other major CVD risk factors is also substantial (Di Castelnuovo et al., 2009), many of which are also heritable (Fava, Ricci, Burri, Minuz, & Melander, 2008; Pilia et al., 2006; Silventoinen & Kaprio, 2009). Further, cigarette smoking is comorbid with other substance use and psychopathology in part due to shared genetic risk with these conditions (Fu et al., 2007; Swan, Carmelli, & Cardon, 1996; True et al., 1999). Therefore, offspring of mothers who smoke inherit genetic predisposition for substance use and psychopathology more generally, not necessarily specific to cigarette smoking (Knopik, 2009; Roza et al., 2009). In order to distinguish the effect of maternal smoking during pregnancy from genetic transmission of a risk profile, studies need to account for parental history of smoking and of other CVD risk factors and parental psychopathology. Prenatal exposure to cigarette smoke has been associated with elevations in systolic blood pressure (SBP) in infants and toddlers in analyses that did not adjust for familial risk for elevated SBP (Geerts et al., 2007; Lawlor et al., 2004) and in toddlers in well-adjusted analyses (Oken, Huh, Taveras, Rich-Edwards, & Gillman, 2005). It also seems that some of the effect of maternal smoking on SBP is mediated by offspring body mass index (BMI) (Oken et al., 2005). On the other hand, the positive association of prenatal exposure and BMI in threeyear-olds remains significant after adjustment for confounders including maternal and paternal BMI (Oken et al., 2005). The significance of this association persists into adulthood, where 45-year-old men and women whose mothers smoked during pregnancy had higher BMI and larger waist circumference compared to their counterparts whose mothers did not smoke during pregnancy, after adjustment for confounders (Power, Atherton, & Thomas, 2010). In addition, mean BMI and mean waist circumference increased as a function of increasing number of cigarettes smoked per day by the pregnant mother (Power et al., 2010). Despite the conventional wisdom that maternal smoking during pregnancy in humans leads to negative cognitive outcomes in children (Rogers, 2009; Thompson, Levitt, & Stanwood, 2009), a closer look at the evidence supports overall weak effects of this relationship, which can be rendered nonsignificant

Effects of Smoking on Cognition and the Brain

9

with appropriate adjustment for parental cognitive ability. Some of the conventional wisdom may stem from strong evidence in animals about the teratogenic and long-term effects of prenatal nicotine exposure on behavioral and cognitive outcomes in the offspring. Just as for tobacco dependence, cognitive abilities are substantially heritable (Finkel, Pedersen, McGue, & McClearn, 1995; Wright et al., 2001). Thus, reports that maternal smoking during pregnancy is associated with lower cognitive performance and general intelligence in their offspring (Fried, Watkinson, & Gray, 2003; Julvez et al., 2007; Lambe, Hultman, Torrang, Maccabe, & Cnattingius, 2006) may be a function of incomplete covariate adjustment. The relationship between smoking during pregnancy and offspring cognitive abilities does not remain significant after accounting for maternal IQ (Batty, Der, & Deary, 2006; Breslau, Paneth, Lucia, & PanethPollak, 2005; Kafouri et al., 2009) and is reduced after accounting for parental education (Batty et al., 2006; Fried et al., 2003). One well-controlled study shows a decrement in English, math, and science achievement as a function of prenatal exposure to cigarette smoke, but the effect was small (O’Callaghan et al., 2010). Of course, while general cognitive ability as indexed by IQ is heritable, there are cognitive domains such as working memory or learning strategy that are only modestly influenced by genetic factors (Kremen et al., 2007; Swan et al., 1999). Therefore, studies that show that maternal smoking during pregnancy is associated with decrements in working memory and mental rotation tasks (Fried & Watkinson, 2001) may not be as heavily confounded by lack of accounting for family history of the specific cognitive outcome. It is also possible that significant associations between prenatal exposure to cigarette smoke and offspring cognitive performance are obscured in human studies because of hidden interactions between maternal smoking and offspring genotype. For example, one study showed that maternal smoking during pregnancy was associated with lower general cognitive ability in four-year-olds, but only in children who were carriers of a null allele of the GSTM1 (glutathione S-transferase mu 1) gene whose enzyme product is involved in detoxification of tobacco smoke constituents (Morales et al., 2009). Maternal smoking during pregnancy has been related to deficits in the efficiency of auditory processing in adolescents (Jacobsen, Slotkin, Mencl, Frost, & Pugh, 2007). Adolescents exposed to cigarette smoke prenatally compared to controls also had decreased water diffusion in left frontal cortex regions that subserve executive control and in the front anterior portion of the corpus callosum (genu) that serves to interconnect regions of the left and right frontal cortex, in response to a finger-tapping task, suggesting alteration of white matter integrity in these regions (Jacobsen et al., 2007). These results further suggest possible disruption of the trophic actions of acetylcholine, as well as other neurotransmitter systems, during nervous system development (Slotkin, 1998). Overall, prenatal nicotine exposure may exert effects on offspring outcome via deleterious effects on fetal growth, or as part of a maternal latent substance

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use/comorbid psychopathology/CVD risk profile. Prenatal nicotine exposure may also change the sensitivity of the organism to later environmental influences (Abreu-Villaça, Seidler, & Slotkin, 2004), which could trigger a given behavioral trajectory and would thus become the salient, proximal affectors of behavior and may mask, in statistical analysis, the sensitivity change initially conferred by prenatal nicotine exposure. It is possible that a direct effect of maternal smoking during pregnancy on offspring outcomes does exist, perhaps at high levels of smoking, which may be associated with increased infant mortality, which, in turn, would decrease the ability to detect such an effect in surviving offspring.

Adults Silent Brain Infarcts, WMHI, Leukoaraiosis, Other Volumetric Measures Given that smoking is a risk factor for stroke, it is reasonable to suspect that it is also associated with “preclinical” brain changes that may precede the onset of symptomatic stroke or other forms of clinical disease. In 1,737 participants aged 55–70 the prevalence of silent cerebral infarction was 1.8 times greater in current smokers compared to nonsmokers (Howard et al., 1998). A larger number of pack years of smoking was associated with higher prevalence, suggesting a dose–response relationship. While a later study of 1,077 participants of age 60–90 years did not find an association between smoking status and the prevalence of silent brain infarct, it did observe an association with the prevalence of symptomatic infarcts (Vermeer, Koudstaal, Oudkerk, Hofman, & Breteler, 2002). Longitudinal follow-up found that smoking was associated with an accelerated risk, 1.4, for incident silent brain infarct (e.g., new infarcts following initial evaluation; Vermeer et al., 2003). A positive smoking history has also been observed as a risk factor for silent brain infarcts in younger individuals (aged 15–49 years) who present with a first-ever ischemic stroke (Putaala et al., 2009). WMHIs and subcortical atrophy are associated with lower performance or decline on measures of executive function and global cognitive function (Longstreth et al., 2005; Soderlund et al., 2006). Smoking was an independent risk factor for worsening of white matter grade in a subset of participants 65 years and older who were examined twice by MRI over an interval of five years. While not finding a direct association between smoking and WMHI, a second study of non-demented community-dwelling older adults did find an association between lower levels of peak expiratory flow rate, an indicator of certain forms of lung disease for which smoking is a risk factor, and WMHI (Murray et al., 2005). Smoking history is associated with WMHI in most but not all studies (Brody et al., 2004).

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Studies of the association of smoking with volumetric measures of atrophy suggest that greater exposure is associated with smaller overall brain volumes, lower prefrontal cortical gray matter, and greater levels of WMHI (Brody et al., 2004; Longstreth et al., 2001; Swan et al., 2000). Smokers also had smaller relative cortical gray matter volumes and densities in the prefrontal cortex, smaller left dorsal anterior cingulate cortex volumes and lower cerebellar gray matter densities than nonsmokers (Brody et al., 2004). There is the possibility that differences in brain characteristics could pre-date the onset of smoking, thereby potentially confounding these associations.

Cognition In the first prospective study of the relationship between smoking in middle age and later cognitive performance (over a 20-year interval), continuous smoking over that interval was associated with an increased risk of cognitive impairment (odds ratio = 1.4) on the Cognitive Ability Screening Instrument (CASI; Galanis et al., 1997; Teng et al., 1994). Using more specific measures of processing speed, memory, and executive function in samples of middle- to old-age individuals, smoking was a strong and independent predictor of decreased processing speed and memory, along with a reduced Mini-Mental State Exam (MMSE) score (Aleman, Muller, de Haan, & van der Schouw, 2005; Lee et al., 2009). In the same cohort CVD was associated with lower memory performance (Muller, Grobbee, Aleman, Bots, & van der Schouw, 2007). These studies demonstrate that smoking can have both direct and indirect (via CVD) negative effects on cognition.

Cognitive Decline In this section, we consider the evidence for an association between smoking and subsequent change in cognitive performance as assessed at two or more time points in individuals aged 40–70 years. An early study administered a cognitive battery to 10,963 individuals on two occasions separated by six years. The presence of hypertension and diabetes at baseline was associated with greater decline in cognitive performance, but smoking status was not associated with change in cognitive performance (Knopman et al., 2001). Subsequent evidence, however, showed that smoking is associated with greater decline in verbal memory and visual search speed (Nooyens, van Gelder, & Verschuren, 2008; Richards, Jarvis, Thompson, & Wadsworth, 2003; Sabia, Marmot, Dufouil, & Singh-Manoux, 2008); MMSE scores (Collins, Sachs-Ericsson, Preacher, Sheffield, & Markides, 2009; Ott et al., 2004); memory in older adults without an APOE a4 (apolipoprotein E) allele (Reitz, Luchsinger, Tang, & Mayeux, 2005); auditory verbal learning and executive function (Starr, Deary, Fox, & Whalley, 2007); and the transition from normal cognition to mild cognitive impairment (Cherbuin et

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al., 2009; Smith et al., 2008). In an interesting analysis, the maintenance of cognitive health (defined as no change or increasing performance on the MMSE over eight years) was more common in older adults without a smoking history as compared to those who did smoke at some time in their lives (Yaffe et al., 2009). In an attempt to separate the effects of aging from the effects of smoking, the studies cited above either adjusted for age in the prediction models or conducted analyses on the sample after stratification by age group.

Dementia Consistently, studies have reported an association between smoking and an accelerated risk for dementia, AD, and VaD (Meyer, Rauch, Rauch, & Haque, 2000; Stella et al., 2007; Tyas et al., 2003). Only a few studies have failed to find an association between smoking and dementia (Kalmijn et al., 2000) or AD (Bhargava, Weiner, Hynan, Diaz-Arrastia, & Lipton, 2006; Bowirrat, Friedland, Farrer, Baldwin, & Korczyn, 2002). One study showed that risk factors associated with the probability of conversion of mild cognitive impairment (MCI) to dementia included atrial fibrillation and low serum folate levels but not smoking (Ravaglia et al., 2006). In a notable study, the risk of AD in male smokers followed from mid-life to late life increased with pack years of smoking at medium and heavy smoking levels (Tyas et al., 2003). In an autopsied subsample, the number of neuritic plaques increased with amount smoked. When very heavy smokers were excluded, there was a strong dose–response relationship among smokers between amount smoked and risk of AD, AD plus cerebrovascular disease, and all dementias combined. Compared with light smokers, the adjusted risk of AD was significantly increased among smokers, with an even higher risk of AD in the heavy smoking group. Compared with never smokers, former smokers had significantly more neuropathology in the neocortex and slightly more in the hippocampus. Medium and heavy smokers had significantly more neocortical neuropathology than light smokers. A focus of study in the etiology of AD has been on the role played by atherosclerotic vascular risk factors in increasing the risk of cognitive impairment, AD, and vascular cognitive impairment (Gorelick, 2004). Casserly and Topol (2004), in their review of the evidence, concluded that vascular risk factors converge to increase the presence of mis-folded amyloid ^ after a substantial incubation period, thereby contributing to the risk of AD. This hypothesized convergence received empirical support in a study by Newman et al. (2005) in which the incidence of dementia and of AD was higher in the presence of CVD other than stroke. Rates of AD were the highest in those with peripheral arterial disease (PAD), with an adjusted hazard ratio of 2.4. Again, the evidence suggests that smoking can have both direct and indirect negative effects on risk for neurodegeneration.

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A meta-analysis of 19 prospective studies (a total of 26,374 participants followed for dementia outcomes and a total of 17,023 participants followed for cognitive decline; mean age = 74 years) with at least 12 months of follow-up concluded that compared to never smokers, current smokers were at significant increased relative risk for incident AD (1.8), incident VaD (1.8), and any dementia (1.3). Current smokers also demonstrated greater annual declines in MMSE scores. Relative to former smokers, current smokers had higher relative risk for AD (1.7) and an increased annual rate of decline on the MMSE, thereby suggesting the importance of smoking cessation to cognitive outcomes in older adult smokers (Anstey, von Sanden, Salim, & O’Kearney, 2007).

Possible Mechanisms Underlying the Effects of Smoking Oxidative Stress Compared with nonsmokers, active smokers have more than 25% lower circulating concentrations of anti-oxidants such as ascorbic acid, ] carotene, ^ carotene, and cryptoxanthin. Direct exposure from cigarette smoke represents only a portion of the total oxidative stress eventually experienced by the smoker. Cigarette smoke also contributes to additional endogenous oxidant formation through effects on the inflammatory immune response pathway. Cigarette smoke could also result in increased metabolic turnover with antioxidant micronutrients expended in response to the increased oxidative stress caused by cigarette smoking or, alternatively, smoking could decrease micronutrient absorption (Alberg, 2002; Csiszar et al., 2009). Oxidative stress damage is also intimately linked to glutamate neurotoxicity. An excessive concentration of extracellular glutamate overactivates ionotropic glutamate receptors, resulting in intracellular calcium overload and a cascade of events leading to neuronal cell death (Butterfield, Perluigi, & Sultana, 2006). Exposure of rat brain to cigarette smoke results in an increase of reactive oxygen species (ROS) and nitric oxide synthase (NOS) leading to lipid peroxidation, protein oxidation, and DNA damage. In this model, cigarette smoke also induces heat shock proteins and apoptosis, a conserved response to various conditions including oxidative stress (Anbarasi, Kathirvel, Vani, Jayaraman, & Shyamala Devi, 2006). In mouse brain, six months of exposure to sidestream smoke resulted in increase of ROS in the cerebellum, frontal cortex, hippocampus, and striatum along with an increase in lipid peroxidation. An increase in pro-inflammatory markers in all areas of the brain was also observed (Manna et al., 2006). Cadmium, a component of tobacco smoke, induces cellular death in cortical neurons in culture, possibly through apoptotic or necrotic mechanisms as a secondary effect of oxidative stress (Lopez, Arce, Oset-Gasque, Canadas, & Gonzalez, 2006).

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Inflammation Molecular components of the inflammatory response are found to be in increased concentrations in AD and in lower amounts in the aging brain without dementia. Inflammatory markers are also reliably increased in the presence of atherosclerosis (Whalley, Deary, Appleton, & Starr, 2004). During the acute phase of inflammatory states, there are quantifiable increases in C-reactive protein, white blood cell count, and fibrinogen, and decreases in serum albumin (Bakhru & Erlinger, 2005; Domagala-Kulawik, 2008). Interleukin-6 (IL-6) and interleukin-8 (IL-8) are important in the recruitment and activation of inflammatory cells. The induction of these pro-inflammatory mediators is regulated by the activation of a redox sensitive transcription factor. This transcription factor has been shown to be activated by a wide variety of agents including cigarette smoke (Kode, Yang, & Rahman, 2006). Moreover, IL-6 levels have been reported to be associated with lower MMSE scores with smoking as one of the strongest covariates associated with IL-6 in older adults (Wright et al., 2006). Cross-sectional studies (Marioni et al., 2010; Marsland, Gianaros, Abramowitch, Manuck, & Hariri, 2008; Marsland et al., 2006) reported associations between greater levels of IL-6 and lower cognitive performance in middle-aged (Marsland et al., 2006) and in older adults (Marioni et al., 2010). Increased IL-6 levels are associated with greater cognitive decline over time in many prospective studies (Jordanova, Stewart, Davies, Sherwood, & Prince, 2007; Rafnsson, Deary, Smith, Whiteman, & Fowkes, 2007; Schram et al., 2007; van den Kommer, Dik, Comijs, Jonker, & Deeg, 2008) but not all (Gimeno, Marmot, & Singh-Manoux, 2008). Recent work in animals suggests IL-6 influences age-related loss of GABAergic interneurons in the forebrain, therefore providing a potential mechanism for the IL-6–cognitive decline association (Dugan et al., 2009). See Chapter 8 in this volume for further discussion (Marsland, 2015). An important paper examined the effects of tobacco smoke on isolated human brain microvasculature endothelial cells which are present at the blood– brain barrier (Hossain et al., 2009). This work revealed a strong proinflammatory response in these cells even at low concentrations of tobacco smoke condensate. At the endothelial level, upregulation of cell adhesion molecules was observed. Increased upregulation was also seen for vascular adhesion molecules, chemokines, and cytokines. The upregulation of other genes such as APOE and SAA1 (serum amyloid 1) showed, for the first time, that tobacco smoke affects gene transcription that could be atherogenic directly at the blood– brain barrier. Data from 15,489 individuals demonstrated that inflammatory and traditional risk factors improved with decreased intensity of smoking in a dose-dependent and temporally concurrent manner. The results suggest that the inflammatory response to smoking may be reversible with reduced tobacco exposure and

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subsequent smoking cessation (Bakhru & Erlinger, 2005). However, while it is well known that risk for lung and CVD declines with increasing duration of smoking cessation, surprisingly little is known about the more immediate effects of smoking cessation on immunological markers and the time course of normalization of these markers (Domagala-Kulawik, 2008). One study identified significant decreases in neutrophils, macrophages, and pigmented macrophages in sputum over a 12-month interval following smoking cessation (Swan et al., 1992). A prospective study that illustrates increased emphasis on investigation of markers of molecular inflammatory processes following smoking cessation showed that among patients without respiratory disease, C-reactive protein (CRP) and IL-6 levels declined with increasing periods of smoking cessation (Sunyer et al., 2009). Individuals with the rs2069840 variant of IL-6 were especially susceptible to the inflammatory effects of tobacco smoke. However, while there is strong longitudinal prospective evidence that respiratory symptoms and lung function improve with increased periods of smoking cessation, there is weaker evidence for change in inflammatory markers measured at the molecular level and more work is needed in this area (Willemse, Postma, Timens, & ten Hacken, 2004).

Atherosclerosis The damaging effect of smoking on the endothelium seems to be the final common pathway leading to atherosclerosis (Román, 2005). Endothelial lesions result not only in stroke, but also in a number of alterations of the blood–brain barrier, cerebral blood flow, and brain metabolism. Tobacco smoke contains a complex mixture of free radicals that cause morphological changes of the endothelium, formation of blebs (bladder-like structures with thin walls that may be filled with fluid), leakage of macromolecules, and increased endothelial cell death (Pittilo, 2000; Román, 2005). Smoking worsens atheromatous plaque formation in carotid arteries, and increases hypertension, blood coagulability, serum viscosity and fibrinogen (Román, 2005). Smoking is a major risk factor for PAD (Willigendael et al., 2004) and carotid atherosclerosis is associated with brain atrophy in older adults (Kin et al., 2007). Cigarette smoking predisposes individuals to vasomotor dysfunction, inflammation, and modification of lipids, important components of the initiation and progression of atherosclerosis (Ambrose & Barua, 2004; Balakumar & Kaur, 2009). Several animal studies have demonstrated that both mainstream and sidestream cigarette smoke exposure are associated with a decrease in vasodilatory function. Nitric oxide, a free radical, is primarily responsible for the vasodilatory function of the endothelium. Not only is nitric oxide a vasoregulatory molecule, it helps regulate inflammation, leukocyte adhesion, platelet activation, and thrombosis. Therefore, an alteration in nitric oxide biosynthesis could have primary and secondary effects on the initiation and progression of atherosclerosis and on thrombotic events (Ambrose & Barua, 2004).

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Interaction with Other Risk Factors Tobacco smoking does not occur in isolation of other risk factors that contribute to negative cognitive or brain outcomes; however, this research area is mostly unexplored. For example, although alcohol and tobacco use commonly co-occur (Kessler et al., 1996), the importance of their combined effect on the brain and cognition was only later recognized (Gazdzinski et al., 2005; GentryNielsen, Top, Snitily, Casey, & Preheim, 2004). A series of papers from the same research group demonstrated that chronic smoking in alcohol-dependent individuals is associated independently with reduced N-acetylaspartate (NAA) in frontal and midbrain regions (Durazzo, Gazdzinski, Banys, & Meyerhoff, 2005), gray matter loss in the neocortex and increased temporal white matter volume (Durazzo, Cardenas, Studholme, Weiner, & Meyerhoff, 2007; Gazdzinski et al., 2005), reduced cerebral perfusion in frontal and parietal regions (Gazdzinski et al., 2006), and greater number of errors on the Wisconsin Card Sorting Task (Durazzo et al., 2005), a possible result of the neurotoxic effects of tobacco smoke (Durazzo, Gazdzinski, & Meyerhoff, 2007). Moreover, the presence of chronic smoking appears to inhibit the recovery of cerebral white matter (Gazdzinski, Durazzo, Mon, Yeh, & Meyerhoff, 2010), cerebral perfusion (Mon, Durazzo, Gazdzinski, & Meyerhoff, 2009), and metabolite concentrations in the medial temporal lobe (Gazdzinski et al., 2008) in abstinent (from alcohol) alcoholics. These results suggest the importance of assessing and controlling for the effects of smoking history in studies of the effects of alcohol on the brain (see Chapter 2 in this volume by Panza, Frisardi, Seripa, Pilotto, & Solfrizzi, 2015). Other interactions with potential importance to understanding the relationship between smoking and cognitive and brain outcomes involve those with variation in genes that are implicated by themselves or in combination in the pathogenesis of cerebrovascular disease. For example, Pezzini et al. (2004) showed that in relatively young people (average age of 34.7 years), the APOE a4 allele and cigarette smoking act synergistically to increase risk for a cerebral ischemic event. There is some evidence that carriers of APOE a4 have a reduced antioxidant capacity thereby explaining the adverse synergy that exists with tobacco smoke (Proteggente et al., 2006).

Effects Secondary to Other Conditions As noted previously, it is possible that smoking’s apparent direct effect on the risk for adverse cognitive and brain outcomes is due to secondary or indirect effects on other risk-enhancing conditions. For example, although CHD was not associated with increased risk for dementia in one study (Bursi et al., 2006), in another study, hippocampal volumes in individuals with coronary artery disease (CAD), compared to those of healthy controls, were smaller and,

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because the cases and controls were not different on conventional risk factors, suggested that CAD’s effects on the hippocampus could be due to an unmeasured third variable common to both such as environmental stress, a correlate of smoking, and also with known negative impact on this brain structure (Koschack & Irle, 2005). Another secondary effect of smoking on cognition could be through its impact on PVD. A number of studies have reported that individuals with PVD (diagnosed either directly or indirectly) have lower levels of cognitive function. Rao, Jackson, and Howard (1999) reported that 25% of patients with PVD had scores lying within the bottom 5% of control group scores for attention, calculation, and one test of frontal lobe function. Another study relying on clinically determined CVD in men reported significant associations between cognitive function and angina, ECG ischemia, past myocardial infarction, and intermittent claudication (an indicator of PVD), and concluded that individuals with PVD have, on average, a significant reduction in cognitive function equivalent to 4–5 years of additional age (Elwood, Pickering, Bayer, & Gallacher, 2002). In addition to the cross-sectional studies described above, there has been more recent attention to prospective investigations of the relationship between PAD as indexed by a relatively simple measure known as the ankle–brachial artery index (ABI) created by the ratio of the SBP measured at each of these sites. A ratio of b90 is a sensitive and specific indicator of angiogram-determined vascular disease. The ABI is an indicator of generalized atherosclerosis because it has been associated with higher rates of concomitant coronary and cerebrovascular disease and has been related to increased incidence of all-cause and cardiovascular-specific mortality, myocardial infarction, and stroke independently of baseline cardiovascular disease and risk factors (Fowkes et al., 2008). Prospectively, atherosclerotic disease has been associated with greater decline in processing speed and verbal memory after adjustment for confounders (Price et al., 2006; Rafnsson, Deary, Smith, Whiteman, & Fowkes, 2007). For further discussion of relations of PVD and atherosclerosis to cognitive function, see Chapters 11 (Wendell & Waldstein, 2015) and 12 (Stroobant, Elias, & Goodell, 2015) in this volume. Of importance to this chapter is the call by Rafnsson, Deary, and Fowkes (2009) for more attention to secondary prevention in patients who are determined to have PAD either through more intensive (e.g., angiography) or less intensive (e.g., ABI) measures. Unfortunately, the presence of PAD is underdiagnosed in asymptomatic individuals despite the availability of the simple and inexpensive ABI. The prevalence of PAD as determined by the ABI may be as high as 41% in asymptomatic high cardiovascular risk patients (Mourad et al., 2009). A meta-analysis involving close to 50,000 men and women determined that a combination of the ABI with the Framingham Risk Score (weighting and summing the presence of cardiovascular risk factors including cigarette smoking, blood pressure, total and high density lipoprotein cholesterol, and diabetes

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mellitus to generate a risk score) may improve the ability to predict subsequent cardiovascular and cerebrovascular events (Fowkes et al., 2008). Given the fact that there are few, if any, accepted interventions to reduce or minimize cognitive decline in aging individuals, the management of PAD risk factors including smoking cessation could be of critical importance to maintaining cognitive health (Rafnsson et al., 2009). Another potential mediator of the smoking–cognitive/brain outcomes association is lung function. As mentioned previously, Richards et al. (2005) found that forced expiratory volume after one second (FEV1) was associated with lower psychomotor speed cross-sectionally and longitudinally, independent from smoking. The authors note that cognitive function may be a marker of the general integrity of the neurorespiratory regulation system. Smoking could adversely affect pulmonary status through its impact on COPD (Rytila et al., 2006), which, in turn, could have negative consequences for cognitive and brain integrity (Dodd, Getov, & Jones, 2010). Indices of lung function were associated with overall brain atrophy, higher ventricle to brain ratio, larger WMHI volume, slower information-processing speed, and less fine motor dexterity independently of smoking (Sachdev et al., 2006). COPD was prospectively associated with lower composite cognitive performance (Hung, Wisnivesky, Siu, & Ross, 2009). An intriguing set of findings concerning the relationship between nicotinic receptor variation in the gene cluster on chromosome 15q25 and smoking quantity, PAD, and COPD may provide further insight into whether smoking has direct or indirect effects on cognitive decline. Variants in this gene cluster were first reported to be associated with nicotine dependence by Saccone et al. (2007) as a result of a genomewide association study (GWAS). A subsequent series of papers confirmed this association (Liu et al., 2010; Thorgeirsson et al., 2008; Thorgeirsson et al., 2010; Tobacco and Genetics Consortium, 2010) and also reported associations with both PAD (Thorgeirsson et al., 2008), lung cancer (Amos et al., 2008; Hung et al., 2008), and COPD (Pillai et al., 2009). It remains to be determined whether genetic variation at this locus operates independently of smoking or through the effects of smoking to increase risk for PAD and COPD (Bierut, 2010). Despite the lack of causal clarity, a metaanalysis of genetic associations and PAD concluded that the variant at the chromosome 15 locus (rs1051730) is one of only three variants to withstand quantitative review (IL-6 and ICAM-1 (intercellular adhesion molecule 1) being the other two; Zintzaras & Zdoukopoulos, 2009).

Benefits of Smoking Cessation as Secondary Prevention Smoking cessation in patients with CHD can reduce the risk of subsequent cardiac events and mortality by as much as 50%, which is at a level consistent with the impact of other secondary preventive measures such as use of statins

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for lowering cholesterol levels, aspirin, beta blockers, or angiotensin-converting enzyme inhibitors (Critchley & Capewell, 2003). The available data suggest that providing smokers with suspected or recently diagnosed cardiovascular and/or other medical conditions with the tools necessary to stop smoking is an opportunity that should be recognized and encouraged by the attending physician, staff, and patient. Smoking cessation for general medical patients is one of the most cost-effective medical interventions available to physicians (Javitz et al., 2004a, 2004b). Considered to be a “best practice,” behavioral counseling combined with an FDA-approved medication should be provided to the smoking patient seeking to quit (Tobacco Use and Dependence Guideline Panel, 2008). In addition to the usual in-person individual or groupbased counseling, a number of other effective counseling formats are now available including proactive telephone calls from a service organization (Zbikowski, Hapgood, Smucker Barnwell, & McAfee, 2008), a telephone-based quit line (Bush et al., 2008), and a Web-based format (Shahab & McEwen, 2009). Our own research suggests that any of these formats, when coupled with medication, will result in similar sustained quit rates, usually in the range of 25–35% of those followed for six months post-cessation (Swan et al., 2010). Several medications are also available for the patient to use concurrently with the cessation counseling and these include nicotine replacement therapy (available in several formulations with gum and transdermal patch being available without a prescription from a physician), bupropion (a dopaminergic agonist), and varenicline (a nicotinic receptor partial agonist). The selection of the precise combination of counseling format and medication should be consistent with practice guidelines (Tobacco Use and Dependence Guideline Panel, 2008) and patient preferences. Each of the medications have commonly reported side effects and it should be expected that the physician and patient will engage in a period of trial-and-error to find the best combination of counseling format and medication that is consistent with patient medical history, results in the fewest side effects, minimizes withdrawal symptoms, and maximizes long-term quit rates.

Conclusions and Future Directions Tobacco smoke is a highly complex mixture of compounds, many of which have known toxic effects on the cardiovascular, cerebrovascular, and pulmonary systems. Because of the number of compounds present in tobacco smoke, a complete picture of organ-specific toxicity is not yet available. However, there is sufficient evidence at the epidemiologic level to support the conclusion that, in adults, a history of smoking is clearly associated with reduced cognitive functioning, preclinical changes in the brain (atrophy, silent infarcts, and WMHIs), accelerated cognitive decline (executive function, verbal memory, speed of processing), and increased risk for dementia (AD and VaD). Exposure to sidestream smoke, especially in fetuses and children, is associated with poorer

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neurocognitive performance. While the precise mechanisms underlying these associations is not completely understood, work in animal models and at the cellular level suggest that tobacco smoke increases oxidative stress in the brain and other organs and induces an inflammatory response. Smoking cessation at any age is expected to result in reduced exposure to toxic, pro-inflammatory, and pro-atherogenic substances that result in disease states that impact cognitive capabilities.

More Specific Measures of Cognition and Brain Function Almost all of the epidemiological evidence for a smoking–cerebrovascular disease connection has relied upon broad, fairly non-specific measures of smoking (e.g., classifications such as current, never, former smoking) or cumulative measures of exposure (e.g., pack years). To enhance further understanding of this relationship, future studies should incorporate topographical measures of smoking (e.g., puff volume, puff rate), biomarkers of exposure (e.g., cotinine), and biomarkers of oxidative stress, inflammation, and/or atherosclerosis (Scherer, 2005). More prospective studies involving the impact of smoking cessation on immune responses are also needed (see Chapters 8 and 11 in this volume (Marsland, 2015; Wendell & Waldstein, 2015)). Except for investigations reported within the last few years, much of the epidemiologic evidence for an adverse impact on smoking on brain function has relied upon global, non-specific measures such as the MMSE. No doubt this is a consequence of the difficulty of incorporating more time-intensive measures of specific cognitive functions into large epidemiologic investigations. Nevertheless, the incorporation of more specific measures such as of working memory could lead to enhanced understanding of the deleterious effects of smoking on brain function.

Interaction with Other Risk Factors and Pre-Existing Conditions Another area that is likely to lead to increased understanding of the tobacco smoke–brain connection is the interaction with other risk factors such as alcohol dependence and depression. The possibility of gene-exposure interactions has been raised in the literature and suggests that some people, by virtue of their genetic background, may be more susceptible to the harmful effects of tobacco smoke on the brain. Pre-existing vulnerability to smoking behavior is an important and complex confound in studies that compare smokers and nonsmokers on measures associated with cognitive performance and brain processing.

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Considering the Importance of Prenatal Exposure to Cigarette Smoke While nicotine may have beneficial effects on cognitive processes in adults, the opposite effect may be the case in developing fetuses and younger children. Nicotine induces free radicals, depletes antioxidant defense mechanisms, and increases markers of oxidative stress in neural cells (Qiao, Seidler, & Slotkin, 2005). Whereas early conventional wisdom viewed the use of NRT in pregnant women seeking to stop smoking as preferable to their continued smoking (and may still be in very heavy smokers), current best practice indicates caution with regard to the use of NRT in pregnancy because of concern for undesirable negative effects on fetal development and subsequent functional status (American College of Obstetricians and Gynecologists, 2010).

Statistical versus Clinical Significance Many of the studies summarized in this chapter reported statistically significant decrements in cognition that may be preclinical in nature that have not yet risen to full-blown clinical conditions. In addition to deleterious direct effects through mechanisms described in this chapter, the chronic use of tobacco also results in several debilitating conditions such as CHD, COPD, and PAD, each of which has well-documented negative effects on functional status and quality of life in aging adults (Lovell et al., 2009; McCarthy, Zhou, Hser, & Collins, 2002; McDermott, 2006; Nazir & Erbland, 2009). The eventual health trajectory in the smoking individual that culminates in significant clinical outcomes with functional consequences depends on the duration of the smoking itself, the presence of other contributing personal risk factors (genetic and behavioral) and their interaction with smoking, along with exposure to environmental pathogens such as second-hand smoke.

Impact on Quality of Life The impact of smoking on functional status (e.g., activities of daily living, quality of life) depends on the age of the exposed individual and the duration of exposure. It is also important that the reader keep in mind the critical distinction between medicinal nicotine such as that delivered through a transdermal patch and non-medicinal nicotine such as that delivered through a cigarette in the presence of many harmful chemicals and metals. The acute effects of nicotine on cognition in adults have been extensively studied and are characterized by enhanced selective attention, recognition memory, and working memory in nonsmokers and nondeprived smokers (Ernst, Heishman, Spurgeon, & London, 2001; Foulds et al., 1996; Kumari et al., 2003; Le Houezec et al., 1994; Perkins et al., 1994; Phillips & Fox, 1998; Pritchard, Robinson, & Guy, 1992).

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The most commonly replicated cognitive effect of nicotine administration is improved performance and reaction times on tasks that require vigilant attention in nicotine-dependent smokers (Brody, 2006; Ilan & Polich, 2001; Rezvani & Levin, 2001). Based on this evidence, it is reasonable to conclude that while the acute, short-term effects of medicinal nicotine and nicotine delivered through tobacco on cognitive performance and brain function may be positive for some adults, the highly addictive nature of nicotine in its most commonly used form (tobacco) increases the chances that the smoker will continue to use tobacco on a long-term basis with use extending over decades.

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2 ALCOHOL CONSUMPTION, BRAIN, AND NEUROCOGNITION Francesco Panza, Vincenza Frisardi, Davide Seripa, Alberto Pilotto, and Vincenzo Solfrizzi

Dementia is estimated as affecting approximately 6% of the population aged 65 and older; the prevalence increases exponentially with age, being 40–70% at the age of 95 years and over (Qiu, De Ronchi, & Fratiglioni, 2007). In westernized countries, the most common forms of dementia are Alzheimer’s disease (AD) and vascular dementia (VaD), with respective frequencies of 70% and 15% of all dementias (Whitehouse, Sciulli, & Mason, 1997). In this chapter, with the term “predementia syndrome” we identify all conditions with age-related deficits in cognitive function reported in the literature, and including a mild stage of cognitive impairment based on a model of normality and the presence of pathological conditions considered predictive of early stages of dementia (Panza et al., 2005). Within the term “predementia syndromes,” mild cognitive impairment (MCI) is, at present, the most widely used term to indicate non-demented aged persons with no significant disability and a mild memory or cognitive impairment that cannot be explained by any recognizable medical or psychiatric condition (Panza et al., 2005; Petersen et al., 1999) with a high rate of progression to dementia (Petersen et al., 1999). Recently, a subclassification of MCI has been proposed according to its cognitive features (including dysexecutive MCI and amnestic MCI (aMCI) or aMCI and non-amnestic MCI (naMCI); single or multiple domain aMCI or naMCI) and clinical presentation (MCI with parkinsonism or cerebrovascular disease) or likely etiology (MCI-AD, vascular MCI, or MCI-Lewy Body Disease), and all represent an attempt to exert some control over this heterogeneity (Panza et al., 2010). The clinical presentation of VaD varies greatly depending on the causes and location of cerebral damage (Román et al., 2004). The heterogeneous group of syndromes and diseases characterized by cognitive impairment resulting from a cerebrovascular etiology has been

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defined recently with the term Vascular Cognitive Disorder (VCD) (Román et al., 2004; Sachdev, 1999). The main categories of VCD are Vascular Cognitive Impairment (VCI) (i.e., vascular cognitive impairment no dementia (vascular CIND) and vascular MCI), VaD, and mixed AD plus cerebrovascular disease (CVD), previously termed “mixed dementia” (Román et al., 2004; Sachdev, 1999). See Chapter 15 of this volume for further discussion (Merino & Hachinski, 2015).

Lifestyle-Related Factors, Dementia, and Predementia Syndromes At present, there is no curative treatment for dementia and AD, nor is there a therapeutic approach to prevent the conversion of MCI to dementia (Frisardi, Solfrizzi et al., 2010). Epidemiological evidence in particular supports the hypothesis that modifiable vascular and lifestyle-related factors are associated with the development of dementia and predementia syndromes in later life, opening new potential avenues for the prevention of these diseases (Panza et al., 2009). Among lifestyle- and vascular-related factors, the impact of diet and physical activity has also been the subject of recent interest (Panza et al., 2009). In particular, the Mediterranean diet pattern has been demonstrated to be protective against cardiovascular disease (CAD) and cognitive decline, thanks to properties of its micro- and macro-nutrients enclosing in fruits, vegetables, fish, legumes, cereals, and in low to moderate alcohol intake. Regarding the latter, existing and emerging evidence from population-based, longitudinal cohort studies predominantly (but also from some case-control studies) suggest that alcohol consumption, particularly red wine within limits and/or of certain types, decreases risk of cognitive impairment or decline, predementia, and dementia syndromes. This is despite chronic alcohol abuse causing progressive neurodegenerative disease (Panza et al., 2009). However, some of the variability in these studies may be due to cross-sectional designs used, restrictions by age or sex, or incomplete ascertainment (Panza et al., 2009). It is especially important to examine data for men and women separately when alcohol consumption is a predictor variable, because gender-based consumption levels are very different. In virtually every study that included both sexes, women consumed alcohol less frequently and in smaller amounts than men. Moreover, education, smoking, or the widely recognized AD genetic risk factor apolipoprotein E (APOE) a4 allele often modified the association between alcohol drinking and cognitive impairment or decline. Indeed, reported association between fewer years of education and predementia and dementia syndromes is supported by the majority of studies, although few studies have investigated lifestyle factors as a possible covariant with education (Panza et al., 2009). Socioeconomic and educational factors, which contribute to drinking behavior in different populations and countries, might influence the strength of association of alcohol and cognitive

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impairment or decline. Furthermore, the APOE a4 allele, which has variable prevalence in different geographic locations (Panza et al., 1999) could be a possible effect modifier for the associations between alcohol/vascular risk factors and dementia syndromes (Panza et al., 2009). It is also possible that over time, possibly influenced by cognitive decline, alcohol consumption will change. Therefore, long-term follow-up studies are needed to clarify the outcomes of these changes. Furthermore, aspects of when and how drinking is measured and how these measurements relate to when and how cognitive decline is measured are important sources of variability that need to be borne in mind in these studies. Chapter 1 on tobacco and Chapter 3 on activity level in this volume are relevant to this discussion on lifestyle factors above (Carlson & Varma, 2015; Swan & Lessov-Schlaggar, 2015). In this chapter, we summarize the findings of the studies of alcohol consumption in cognitive impairment or decline, predementia, and dementia syndromes. We review clinical and epidemiological studies from the international literature, including both cross-sectional and longitudinal studies that involved subjects aged 60 years and above, and where description of the diagnostic criteria for predementia or dementia syndromes has been attempted. Special attention is paid to the possible mechanisms behind reported associations of alcohol drinking with cognitive impairment or decline, predementia, and dementia syndromes.

Alcohol Consumption and Cognitive Functions in Older Age Although changes in cognition are typically not demonstrated until the 7th or 8th decade of life, alcohol may compound already slight age-related cognitive differences (Gilbertson, Ceballos, Prather, & Nixon, 2009). The literature remains sparse with regard to studies of the effects of acute alcohol administration among older drinkers, but studies of younger adults showed that impairment caused by blood alcohol concentrations (BACs) of 40 mg/100 ml may adversely affect a variety of cognitive and behavioral measures. Given the negative effects of aging on the metabolism of alcohol (e.g., slower metabolism of alcohol, ineffective clearing; Gilbertson et al., 2009), findings obtained from studies of younger adults may differ from the performance effects of acute low or moderate alcohol doses in older adults; however, in general, alcohol impairs performance on psychomotor tracking, driving tasks, perception, sustained attention, and information processing (Panza et al., 2009). Several studies have assessed the effects of regular and chronic alcohol consumption and cognitive function among older adults, but with inconsistent results (Panza et al., 2009) (Tables 2.1 and 2.2). Early studies involving relatively small samples of young to middle-aged male social drinkers supported the notion that drinking at any level was associated with poorer performance on cognitive tests (Panza et al., 2009). However, other studies corroborated these

2,040 participants aged 65 and older from a communitydwelling sample of black Americans

Hendrie Cross-sectional, et al., 1996 population-based

Subjects

270 men and women aged 65–89 years

Setting and study design

Goodwin Cross-sectional, et al., 1987 population-based

Reference

Results and conclusions

Community Screening Interview for Dementia, delayed recall of the EBMT, and ADL; evaluation of alcohol consumption

Also after potential confounders were included, there was a small but significant dose effect of drinking for the drinkers, with subjects in the heaviest drinking category scoring poorest in cognitive tests and daily functioning. The scores of abstainers were worse than those of subjects in the lightest drinking category

Cognitive abilities assessed with a 30-item Present or past alcohol intake was not associated with decreased cognitive, mental status questionnaire, abstract psychological, or social status thinking measured with the HCT, and WMS. Emotional status measured by a 92-item self-rating checklist, and social interaction evaluated with a revised form of the Interview Schedule for Social Interaction. Alcohol consumption assessed during a three-day period and questionnaires about present and past alcohol intake

Methods

TABLE 2.1 Principal cross-sectional studies on the relationship between alcohol consumption and cognitive impairment in older subjects

574 men and 815 women, aged 59–71 years

589 male participants aged 59–69 years

1,870 men aged 55–69 years

Dufouil Cross-sectional, et al., 1997 population-based

Carmelli Cross-sectional, et al., 1997 population-based

Elwood Cross-sectional, et al., 1999 population-based

CAMCOG and MMSE, AH4 evaluating verbal and mathematical reasoning, and CRT. Evaluation of alcohol intake and smoking habits

MMSE, DSST, and BVRT. Evaluation of alcohol intake, smoking habits, and APOE genotyping

MMSE, TMT-B, WAIS-Revised, BVRT, Benton Facial Recognition Test, Paced Auditory Serial Addition Test, Auditory Verbal Learning Test, RPM, Word Fluency Test, and Finger Tapping Test; evaluation of alcohol intake and smoking habits

Light and moderate drinking showed no association with cognitive functions. Cigarette smoking showed no association, but there is evidence that the more able smokers quit and become ex-smokers continued

After adjustment for age, education and CVD, smoking was significantly associated with poor cognitive function in current smokers compared with never smokers, whereas light drinking (one or fewer drinks per day) showed a protective effect compared with abstainers. Stratification by APOE a4 indicated that the protective effect of light drinking was stronger and the harmful effect of smoking was weaker among APOE a4 carriers than among noncarriers

In men, no significant relation between alcohol consumption and cognitive scores was found. In contrast, among women, with a range of daily alcohol consumption between zero and approximately four drinks, an overall positive linear association between cognitive scores and alcohol consumption was found, also after adjustment for age, income, education, and depressive symptomatology

Neuropsychological battery that provided measures of general cognitive ability, executive function, and memory, evaluation of alcohol intake and cigarette smoking habits

395 participants aged 60–84 years

No evidence for a beneficial J-curve or threshold effect for drinking was found, but did not reveal any detrimental effect. No detrimental effect of smoking was found in any analysis; nor was there any evidence of an interaction between alcohol and cigarette use on any cognitive measure

Adjusting for potential confounders, alcohol consumption was associated with decreased probability of cognitive impairment, a daily alcohol consumption of less than 40 g for women and 80 g or less for men might be associated with a decreased probability of cognitive impairment

Schinka Cross-sectional, et al., 2002 population-based

Results and conclusions

Hodkinson Abbreviated Mental Test score, 15,807 and evaluation of alcohol intake hospitalized patients, mean age 70.9 years

Methods

Zuccalà Cross-sectional, et al., 2001 multicenter pharmacoepidemiology survey

Subjects

1,836 participants CASI, CRT, and NART. Evaluation of Lower cognitive test scores were observed aged 65 and older alcohol intake and cigarette smoking habits for men who were either abstainers or in the heavy drinking group. For women, a linear relationship between alcohol consumption and cognitive performance was seen on two of the four measures of cognitive functioning, suggesting a possible positive relationship between light to moderate drinking and cognitive performance

Setting and study design

Bond et al., Cross-sectional and 2001 longitudinal, population-based (8 years)

Reference

TABLE 2.1 Continued

883 participants aged 65 years old and over

760 men aged 65–89 years

1,735 subjects aged 60–74 years

Lindeman Cross-sectional, et al., 2005 population-based

Reid et al., Cross-sectional, 2006 population-based

Cooper et al., 2009

AUDIT, TIC-m, NART the 12-item Short Form HSPCS

TMT-B, DSST, FAS Test, and Hopkins Verbal Learning test, and evaluation of alcohol use

MMSE, WAIS-Revised, Digits Forward, Fuld Object–Memory Evaluation, CDT, and two color TMT; evaluation of alcohol intake

MMSE and ADL, evaluation of alcohol intake, and smoking habits

In people who were not problem drinkers, higher alcohol intake was not associated with improved current cognition after controlling for premorbid intelligence and physical health

Current light to moderate drinking (i.e., seven or fewer drinks per week), as compared to never and former drinkers, and the number of years drinking at this level are both associated with better cognitive performance in older males

Older participants who ingested alcohol had significantly better test scores than did the abstainers on seven of nine cognitive function tests after adjusting for differences in sex, ethnicity, age, and years of education

Alcohol drinking was associated with cognitive impairment, and in all people who drink every day, there was a significantly increased risk of cognitive impairment. Smoking was also related to cognitive impairment, and current smoking was associated with a significantly increased risk of cognitive impairment

Notes HCT: Halstead Category Test; WMS: Wechsler Memory Scale; EBMT: East Boston Memory Test; ADL: Activities of Daily Living; MMSE: Mini-Mental State Examination; TMT: Trail Making Test; WAIS: Wechsler Adult Intelligence Scale; BVRT: Benton Visual Retention Test; RPM: Raven Progressive Matrices; DSST: Digit Symbol Substitution Test; APOE: apolipoprotein E; CVD: cerebrovascular disease; CAMCOG: Cambridge Cognitive Examination; CRT: Choice Reaction Time; CASI: Cognitive Abilities Screening Instrument; NART: National Adult Reading Test; CDT: Clock Drawing Test; AUDIT: Alcohol Use Disorders Identification Test; TIC-m: Telephone Interview for Cognitive Status; HSPCS: Health Survey’s Physical Component Score.

Cross-sectional, population-based

3,012 participants aged 60 years old and over

Zhou et al., Cross-sectional, 2003 population-based

Dent et al., Longitudinal, random 209 men, mean 1997 sample of veterans of age: 64.3 years World War II (9 years)

WAIS, WMS, BVRT, RPM, Rey Auditory Verbal Learning Test, Controlled Oral Word Association Test, Boston Naming Test, NART, CRT, and HCT evaluation of alcohol intake and noncontrast computed tomography

MMSE, evaluation of alcohol intake and smoking habits

Persistent lifelong consumption of alcohol and the level of intake seemed not to have any impact on cognitive performance among men in old age

After adjustment for age, education, and smoking status, men with CVD/diabetes and low-to-moderate alcohol intake had a significantly lower risk for poor cognitive function than abstainers. Alcohol intake was not associated with cognitive decline

489 men aged 69–89 years

Launer Cross-sectional and et al., 1996 longitudinal, population-based (3 years)

Change in only one of the three cognitive tests (digit span) was significantly associated with one alcohol category (15 ml per day), and no dose–response relation was observed

Results and conclusions

4,739 twins born Two self-reported drinking histories (1970s No evidence was found to indicate an between 1917 and and 1980s) and a telephone mental status association between moderate long-term 1927 interview (1990 and 1991) alcohol intake and lower cognitive scores in aging individuals. There was a suggestion of a small protective effect of past moderate alcohol intake on cognitive function with aging

Structured performance tests of immediate memory, digit span (from WAIS), and orientation; diagnosis of AD; evaluation of alcohol intake and smoking habits

Methods

Christian Retrospective cohort et al., 1995 and co-twin-control study

Subjects

513 subjects aged 65 years and over

Setting and study design

Herbert Longitudinal, et al., 1993 population-based (3 years)

Reference

TABLE 2.2 Principal longitudinal studies on the relationship between alcohol consumption and cognitive decline in older subjects

1,786 subjects, aged 55–88 years

Elias et al., 1999

Cross-sectional and longitudinal, population-based (24 years)

511 men and women aged 40–80 years

Edelstein Longitudinal, et al., 1998 population-based (13–18 years)

There were few significant associations between health habits and cognitive performance and these were not found consistently across cognitive measures

Eight cognitive tests of verbal memory, learning, visual organization and memory, attention, abstract reasoning, and concept formation; evaluation of weekly alcohol intake

continued

Women who drank moderately (2–4 drinks/ day) showed superior performance in many cognitive domains relative to abstainers. For men, superior performance was found within the range of 4–8 drinks/day, although fewer significant relations were observed. These results were confirmed by prospective analyses of 24-year drinking history

MMSE, TMT-B, Category Fluency, Moderate alcohol consumption and cigarette BFSRT, and BVRT, evaluation of alcohol smoking patterns, reported 13–18 years and intake and smoking habits 3–7 years previously were weakly and inconsistently associated with subsequent cognitive function

327 subjects, aged MMSE, Reid Memory Test, tests of verbal 75 years and over fluency, subsets of the Boston Naming Test and similarities; CDT, and copied drawings of a cube, coils, and interlocking infinity loops; diagnosis of dementia and AD; evaluation of physical exercise, alcohol and smoking use

Broe et al., Longitudinal, 1998 population-based (3 years)

1,389 subjects, aged 59–71 years

Dufouil Longitudinal, et al., 2000 population-based (4 years)

Subjects

833 subjects over 60 years

Setting and study design

Leibovici Longitudinal, et al., 1999 population-based (3 years)

Reference

TABLE 2.2 Continued

MMSE, evaluation of alcohol consumption, APOE genotyping, and smoking habits

A computerized neuropsychometric examination assessed attention, primary and secondary memory, implicit memory, visuospatial ability, and language. Diagnosis of AD and evaluation of alcohol and tobacco consumption were also performed

Methods

Alcohol consumption was associated with a decreased risk of cognitive decline in individuals without the APOE a4 allele, whereas moderate drinking increased the risk of decline in APOE a4 allele carriers. Also, lifetime smoking was a risk factor for cognitive decline in individuals without the APOE a4 allele. The data also suggested a slight protective effect of smoking in APOE a4 allele carriers

Wine consumption was associated with an increased risk of decline over time in attention and in secondary memory. Smoking was associated with a decreased risk for decline over time in attentional and visuospatial functioning. No clear combined effect of smoking and drinking was found, even though smoking was found to increase the risk of decline in language performance when adjusted on wine consumption

Results and conclusions

continued

Cross-sectionally, better cognitive performances have been observed with higher levels of alcohol drinking, while alcohol was not associated with 4-year declines in cognition

516 subjects aged Cognitive by unit-weighted consisted of 70 years and older four intellectual abilities (perceptual speed, episodic memory, fluency, and knowledge), each assessed by composites of two tests, evaluation of alcohol consumption and smoking behavior

Older subjects who were abstinent before the age of 60 had poorer cognitive outcome than did those who drank mildly or moderately

Verhaeghen Cross-sectional and et al., 2003 longitudinal, population-based (4 years)

MMSE, evaluation of alcohol intake and smoking habits

Positive association between a history of moderate alcohol consumption and cognitive performance in the elderly, as men who had consumed up to one drink a day during middle age were later found to have significantly better cognitive test results than nondrinkers

1,083 subjects, aged 65–74 years

No association between alcohol consumption and onset of cognitive impairment was found. Persistent cigarette smoking into late life increased the risk for cognitive impairment

CASI, and evaluation of alcohol intake 3,556 men of Japanese ancestry, aged 71 to 93 years

Longitudinal, population-based (9–12 ears)

Cervilla et al., 2000b

889 subjects, aged Cognitive impairment assessed at baseline 65 or over and 1 year later using the organic brain syndrome (OBS) cognitive impairment scale from the short CARE structured assessment, evaluation of alcohol intake and smoking habits

Galanis Longitudinal, et al., 2000 population-based (18 years)

Longitudinal, population-based (1 year)

Cervilla et al., 2000a

Telephone Interview for Cognitive Status, EBMT, TICS 10-word list, a test of verbal fluency, and the digit span backward test. Evaluation of alcohol consumption and APOE genotype

12,480 subjects aged 70–81 years

1,836 participants CASI, evaluation of alcohol intake and aged 65 and older cigarette smoking habits

1,681 individuals aged 65 years or older

Stampfer Cross-sectional and et al., 2005 longitudinal, population-based (2 years)

Bond et al., Cross-sectional and 2005 longitudinal, population-based (8 years)

Ganguli Longitudinal, et al., 2005 population-based (7 years)

Neuropsychological test panel of the CERAD, and among these tests: MMSE and TMT. Evaluation of alcohol intake and smoking habits

Methods

Setting and study design

Subjects

Reference

TABLE 2.2 Continued

This cohort showed a consistent pattern of better baseline scores and lesser decline over time in individuals who consumed alcohol minimally or moderately, compared to those who reported no drinking at baseline

Alcohol consumers had higher scores (less cognitive decline) on cognition, measured by the CASI over an 8-year follow-up period, than abstainers. There were no significant gender differences in the absolute scores on CASI, and the rate of change over time did not vary

After multivariate adjustment, moderate drinkers had better mean cognitive scores than nondrinkers. For cognitive decline, on test of general cognition, the relative risk of a substantial decline in performance over a 2-year period was 0.85 among moderate drinkers, as compared with nondrinkers. There were no significant differences in risks according to the beverage and no interaction with the APOE genotype

Results and conclusions

5,033 subjects, aged 70 years and older

Arntzen Longitudinal, et al., 2010 population-based (7 years)

Notes WAIS: Wechsler Adult Intelligence Scale; AD: Alzheimer’s disease; MMSE: Mini-Mental State Examination; CVD: cerebrovascular disease; WMS: Wechsler Memory Scale; BVRT: Benton Visual Retention Test; RPM: Raven Progressive Matrices; NART: National Adult Reading Test; CRT: Choice Reaction Time; HCT: Halstead Category Test; CDT: Clock Drawing Test; TMT: Trail Making Test; BFSRT: Buschke-Fuld Selective Reminding Test; APOE: apolipoprotein E; CASI: Cognitive Abilities Screening Instrument; CERAD: Consortium to Establish a Registry for Alzheimer Disease; EBMT: East Boston Memory Test: 12 WMT: 12 Word Memory Test.

12 WMT, Digit-Symbol Coding Test of Light to moderate wine consumption is the WAIS, Tapping Test, and evaluation of associated with better cognitive performance alcohol intake after 7 years of follow up compared with low alcohol intake in both men and women

Adapted Telephone Interview for For older adults with a level of cognitive Cognitive Status, and evaluation of alcohol functioning within normal ranges, moderate intake amounts of alcohol, an average of one drink or less daily, was protective for women, but not men

2,716 subjects, aged 70 years and older

McGuire Longitudinal, et al., 2007 population-based (4 years)

The nondrinkers both at mid-life and later had a poorer cognitive performance than drinkers, especially in the domains related to fluid intelligence, i.e., executive function, psychomotor speed, as well as episodic memory, whereas the other cognitive functions showed little association with alcohol drinking. No interactions between APOE a4 and alcohol or sex and alcohol were found

MMSE, and neuropsychological tests evaluating episodic memory, semantic memory, psychomotor speed, executive function, prospective memory, and subjective memory. Evaluation of alcohol intake, smoking habits, and APOE genotyping

1,341 participants aged 65–79 years

Ngandu Longitudinal, et al., 2007 population-based (21 years)

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results for a subsample of women whose drinking patterns were similar to their male counterparts (Panza et al., 2009). Subsequent research with male and female college students and elderly men led to the conclusion that no significant negative relation exists between social drinking and level of cognitive functioning, although elevated alcohol consumption among young female social drinkers were related to better performance on many cognitive tests (Panza et al., 2009). The relation between the level of alcohol consumption and cognitive performance is complex and follows both linear and quadratic functions (Christian et al., 1995; Goodwin et al., 1987; Hendrie, Gao, Hall, Hui, & Unverzagt, 1996; Launer, Feskens, Kalmijn, & Kromhout, 1996). In fact, light to moderate drinkers of alcohol perform at a higher cognitive level than either abstainers or heavy drinkers (Hendrie et al., 1996), although there are some notable exceptions (Goodwin et al., 1987; Launer et al., 1996). One study in particular, found that consumption of up to 5–6 g of alcohol per day (1–2 drinks) was correlated with better cognitive performance than abstaining in older African-American adults (Hendrie et al., 1996). On the other hand, in one report, statistical adjustment for age, income, education, and gender rendered the findings nonsignificant (Goodwin et al., 1987). In another study, the protective effects of moderate alcohol consumption (odds ratio [OR]: 0.30; 95% confidence interval [CI]: 0.20–0.70 for less than one drink and OR: 0.20; 95% CI: 0.1–0.4 for one to two drinks per day) were limited only to those participants who exhibited clinical conditions associated with atherosclerosis (Launer et al., 1996). However, significant variability in different countries on the level of alcohol content in drinks, as well as in the criteria used in different articles to define terms such as light, moderate, and heavy drinking, makes the interpretation of findings difficult (Panza et al., 2009).

Cross-Sectional Studies Lower levels of alcohol intake have proportionally greater effects in the elderly, due to their reduced lean body mass and lower percentage of body weight made up of water. In fact, in several cross-sectional studies, moderate drinking, from up to one drink per day (up to 14 g of alcohol) to four drinks per day (52 g of alcohol), as compared with nondrinking, has been associated with better performance in many cognitive domains (Bond, Burr, McCurry, Graves, & Larson, 2001; Bond et al., 2003; Carmelli, Swan, Reed, Schellenberg, & Christian, 1999). In fact, the Kame project, a study that used data from 1,836 cognitively intact elderly Japanese American men and women aged 65 and older, found that up to 26 g of alcohol per day for women was associated with higher Cognitive Abilities Screening Instrument (CASI) scores (Bond et al., 2001). In a recent cross-cultural comparison of Japanese and non-Hispanic White American older adults, the Kame project found that current consumption of alcohol (13–26 g of alcohol, 1–2 drinks per day), compared to abstinence or past alcohol

Alcohol Consumption, Brain, and Neurocognition

49

consumption, was more strongly associated with higher CASI scores for women than men (Bond et al., 2003). Furthermore, in cross-sectional studies, both better (Dufouil, Ducimetière, & Alperovitch, 1997; Lindeman, Wayne, Baumgartner, & Garry, 2005; Reid et al., 2006; Schinka et al., 2002) and poorer (Yoshitake et al., 1995; Zhou et al., 2003) cognitive performances have been observed in association with higher levels of alcohol drinking (see Table 2.1). In particular, the issue of sex differences in the relation of alcohol consumption and cognitive performance was addressed by Dufouil and colleagues (1997) using data from the Epidemiology of Vascular Aging (EVA) study. This study included 574 men and 815 women, aged 59–71 years. No association between drinking and cognition was found for the male participants; while for the female participants, moderate alcohol consumption was associated with better performance on seven of the cognitive tests and an overall composite score (Dufouil et al., 1997). In fact, the OR for higher cognitive performance (i.e., the top 10% of the distribution of summary scores from the neuropsychological battery) was 2.5 (95% CI = 1.1–5.7) for women who usually consumed two or more drinks per day in comparison with nondrinkers. Interestingly, in this study, alcohol intake was associated with a lower risk of cognitive deterioration among subjects without an APOE a4 allele, but a higher risk in APOE a4 carriers. In fact, compared with nondrinkers, non-a4 carriers who reported drinking two drinks or more per day had a 50% decreased risk of cognitive deterioration (Dufouil et al., 1997). At the same time, some studies have found no associations between alcohol drinking and several cognitive functions (Elwood et al., 1999; Schinka et al., 2002). Elwood and colleagues (1999) did not find any significant association between alcohol consumption and cognitive function among 1,870 men aged 55–69 years from the Caerphilly Study, though ex-drinkers had markedly lower test scores than either current drinkers or men who had never drunk alcohol. Finally, recent data on 1,735 subjects aged 60–74 years interviewed for the 2000 British National Psychiatric Morbidity Survey, representative of people living in private homes, suggested that in people who were not problem drinkers, higher alcohol intake was not associated with improved current cognition after controlling for premorbid intelligence and physical health (Cooper et al., 2009).

Prospective Studies The studies assessing prospective changes in cognition have had contradictory results (see Table 2.2). Drinkers in general have been proposed to have a greater decrease in global cognitive function (Dufouil et al., 2000) and attention (Leibovici, Ritchie, Ledesert, & Touchon, 1999) as compared with nondrinkers, but moderate drinkers (about one drink or less than 15 ml of alcohol per day) are thought to have less decline in general cognition (relative risk [RR]: 0.77; 95% CI: 0.67 to 0.88) (Stampfer, Kang, Chen, Cherry, & Grodstein, 2005) or

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F. Panza et al.

psychomotor speed (Herbert et al., 1993) than nondrinkers. Further, some studies showed no association at all (Broe et al., 1998; Cervilla, Prince, & Mann, 2000; Launer et al., 1996; Verhaegen, Borchelt, & Smith, 2003). However, in the Gospel Oak project, moderate drinkers (one to 30 units per week, with one unit equivalent to a glass of wine or a single measure of spirits) were not more protected against onset of cognitive impairment if compared with nondrinkers and heavy drinkers (30 units and over per week) (Cervilla, Prince, & Mann, 2000). Among longitudinal studies, Launer and colleagues (1996) showed in the Zutphen Elderly Study that men with cardiovascular disease or diabetes and light to moderate alcohol intake had a significantly lower risk of poor cognitive function compared to abstainers, obtaining effects of large magnitude for less than one drink (OR: 0.30; 95% CI: 0.20–0.70) and for one to two drinks per day (OR: 0.20; 95% CI: 0.10–0.40); but, alcohol intake was not associated with cognitive decline in a three-year follow-up. Finally, in a representative elderly cohort followed over an average of seven years, a pattern of light to moderate drinking (from drinking once a month or less to drinking daily and weekly), compared to not drinking, was associated with lesser average decline in cognitive domains over the same period. In particular, in according to EVA study results, the seemingly beneficial effects of alcohol intake against cognitive decline appeared concentrated in the areas of executive functions for light drinking (OR: 0.20; 95% CI: 0.05–0.85) and moderate drinking (OR: 0.05; 95% CI: 0.01–0.45), and general mental status for light drinking (OR: 0.30; 95% CI: 0.14–0.65) and moderate drinking (OR: 0.08; 95% CI: 0.02–0.28) (Ganguli, Vander Bilt, Saxton, Shen, & Dodge, 2005). Very recently, in the Tromsø Study, light to moderate wine consumption was associated with better cognitive performance after seven years of follow-up compared with low alcohol intake in both men and women. In men, moderate consumption of beer was associated with better scores on tapping tests, but not on the other cognitive tests. No consistent association was seen between spirit consumption and cognitive test scores (Arntzen, Schirmer, Wilsgard, & Mathiesen, 2010). Associations between current cognitive performance and alcohol drinking 5–24 years earlier have also been studied, with conflicting results (Cervilla, Prince, Joels, Lovestone, & Mann, 2000; Christian et al., 1995; Dent et al., 1997; Edelstein, Kritz-Silverstein, & Barrett-Connor, 1998; Elias, Elias, D’Agostino, Silbershatz, & Wolf, 1999; Galanis et al., 2000; McGuire, Ajani, & Ford, 2007; Ngandu et al., 2007) (Table 2.2). Although there were some gender differences in observed associations, data from 1,469 relatively well-educated, non-institutionalized subjects from Rancho Bernardo, California offered no compelling evidence that social drinking caused or prevented impaired cognitive function 13–18 years later (Edelstein et al., 1998). The large number of comparisons and inconsistent results suggest that the few statistically significant findings may be chance results resulting from analyses of multiple dependent variables without protection.

Alcohol Consumption, Brain, and Neurocognition

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In the Framingham Heart Study, the mean levels of alcohol consumption over 24 years prior to neuropsychological testing were examined in relation to cognitive performance (Elias et al., 1999). The association between alcohol consumption and cognitive performance was analyzed separately for men and women, since the researchers anticipated a different gender-based alcohol–cognition relationship (Elias et al., 1999). Test performance of moderate male drinkers (>2 and 4 and 2 drink/day

Setting and study design

Solfrizzi Longitudinal, 1,445 men and et al., 2007 population-based study women aged (3.5 years) 65–84 years

Reference

TABLE 2.3 Continued

Participants with a history of smoking or harmful alcohol consumption, hypertension, or who took medication for anxiety or depression were at increased risk of transitioning to MCI or any MCD

Wine was protective for dementia, and the association was strongest among women who consumed wine only. In contrast, consumption of spirits at baseline was associated with slightly increased risk of dementia

In patients with MCI up to one drink/day of alcohol or wine may decrease the rate of progression to dementia. No significant associations were found between any levels of drinking and the incidence of MCI in non-cognitively impaired individuals vs. abstainers

Results and conclusions

In the cross-sectional section of this study, moderate alcohol consumption were associated with a decreased OR of MCI and aMCI (but not naMCI)

Notes WAIS: Wechsler Adult Intelligence Scale; AD: Alzheimer’s disease; OR: odds ratio; 95% CI: 95% confidence interval; MMSE: Mini-Mental State Examination; CDT: Clock Drawing Test; VaD: vascular dementia; MCI: mild cognitive impairment; APOE: apolipoprotein E; RR: relative risk; AUDIT: Alcohol Use Disorders Identification Test; MCD: mild cognitive disorder; aMCI: amnestic mild cognitive impairment; naMCI: non-amnestic mild cognitive impairment.

Diagnosis of dementia; evaluation of alcohol intake and smoking habits

Longitudinal, hospital- 176 MCI patients Diagnosis of dementia in MCI patients, In a cohort of Chinese older patients with based study (2 years) aged >60 years MMSE, and evaluation of alcohol intake at MCI, a J-shaped relationship may exist baseline between alcohol consumption and cognitive impairment. The cognitive functions of both heavy drinkers and abstainers decreased to a significantly greater degree during follow up than that of patients who consumed light– moderate alcohol. In MCI patients, heavy drinking may increase the risk for dementia

1,462 women Roberts Cross-sectional and aged 38–60 years et al., 2010 longitudinal, population-based study (34 years)

Xu et al., 2009

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(OR: 1.45; 95% CI: 0.43–4.89). A greater reduction of risk was observed for men (OR = 0.37) than for women (OR = 0.76) (Deng et al., 2006). Moreover, the effect of light to moderate drinking seemed most prominent for AD (OR: 0.63; 95% CI: 0.55–0.72) than for VaD (OR: 0.31; 95% CI: 0.19–0.51) or other dementia (OR: 0.45; 95% CI: 0.12–1.69) (Deng et al., 2006). In a nested case-control study of 373 cases with incident dementia and 373 controls, selected from 5,888 adults aged 65 years and older who had participated in the Cardiovascular Health Study (CHS), the adjusted OR for dementia among those whose weekly alcohol consumption was less than one drink was 0.65, compared with abstention; was 0.46 and 0.69 compared with one to six drinks and with seven to 13 drinks, respectively, and was 1.22 when compared with 14 or more drinks (Mukamal et al., 2003). A trend toward greater odds for dementia associated with heavier alcohol consumption was most apparent among men and participants bearing an APOE a4 allele, with similar relationships of alcohol use with AD and VaD (Mukamal et al., 2003). In the Copenhagen City Heart Study that rated alcohol consumption in a different manner than many other studies, the risk of developing dementia was significantly lower among monthly wine drinkers (HR: 0.43; 95% CI: 0.23–0.82), in weekly wine drinkers (HR: 0.33; 95% CI: 0.23–0.82) and, but not significantly, in daily drinkers. An increased risk for beer and for spirits was found in monthly, weekly, and daily drinkers, but not significantly. No difference was found between men and women. No association was found between any number of drinks (fewer than 1, 1–7, 8–14, 15–21, 22 or more) of alcohol consumed per week and the risk of dementia (Truelsen, Thudium, & Grønbæk, 2002). The findings from the CHS were consistent with the PAQUID Study (Orgogozo et al., 1997) and the Rotterdam Study (Ruitenberg et al., 2002), but suggested a higher risk of dementia with consumption greater than two drinks per day. Surprisingly, the Rotterdam Study found that the lower risk of dementia associated with alcohol use was more consistent among individuals with an APOE a4 allele (Ruitenberg et al., 2002), but no significant interaction was detected. In the Washington Heights Inwood-Columbia Aging Project, with 908 subjects aged 65 years and older, the number of drinks per week was collected at baseline and subjects were classified as nondrinkers, light drinkers (less than one drink per month to six drinks a week), moderate drinkers (1–3 drinks a day), and heavy drinkers (more than three drinks a day). The light and moderate drinking categories were combined because of the low number of moderate drinkers. A significantly lower risk of AD was found in light to moderate wine drinkers in elderly individuals without the APOE a4 allele (HR = 0.44). No modification effect by sex was found (Luchsinger, Tang, Siddiqui, Shea, & Mayeux, 2004). Some other population-based, prospective studies with longer follow-up periods studied the effects of different patterns of alcohol intake on dementia (Järvenpää, Rinne, Koskenvuo, Räihä, & Kaprio, 2005; Mehlig et al., 2008; Simons, Simons, McCallum, & Friedlander, 2006). In fact, in the Finnish Twin

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61

Cohort Study with a follow-up period of 25 years, reports of mid-life binge drinking (i.e., alcohol exceeding the amount of five bottles of beer or a bottle of wine on one occasion at least once per month) or losing consciousness due to excessive alcohol intake at least twice during the previous year were risk factors for dementia later in life (RR: 3.2; 95% CI: 1.2–8.6) (Järvenpää et al., 2005). A longitudinal cohort study conducted in Dubbo, Australia, on 2,805 subjects aged 60 years and older, initially free of cognitive impairment and followed for 16 years, confirmed that a modest intake of alcohol seemed to offer substantial protection against the onset of dementia, showing larger effect for 15–28 units per week (HR: 0.40; 95% CI: 0.21–0.79) (McCallum, Simons, Simons, & Friedlander, 2007; Simons et al., 2006). Finally, in the Prospective Population Study of Women in Goteborg, Sweden, in a 34-year follow-up, wine was protective for dementia (current drinking vs. former or never drinking) (HR: 0.60; 95% CI: 0.40–0.80), and the association was strongest among women who consumed wine only (HR: 0.30; 95% CI: 0.10–0.80). In contrast, consumption of spirits at baseline was associated with slightly increased risk of dementia (HR: 1.50; 95% CI: 1.00–2.20) (Mehlig et al., 2008). For predementia syndromes, in a group of 369 non-demented, communitydwelling older men who participated in the National Heart, Lung, and Blood Institute (NHLBI) Twin Study, alcohol consumption was found to be slightly protective (RR: 0.93; 95% CI: 0.88–0.99), but if individuals with CVD were excluded from the analysis this association disappeared (DeCarli et al., 2001). Very recently, in the cross-sectional portion of the Mayo Clinic Study of Aging, moderate alcohol consumption was associated with a decreased OR of MCI and aMCI (but not naMCI) (Roberts et al., 2010). The impact of alcohol consumption on the incidence of MCI was evaluated in 1,445 cognitively normal individuals and on its progression to dementia in 121 patients with MCI, aged 65 to 84 years, participating in the Italian Longitudinal Study on Aging (ILSA), a large, population-based, prospective study with a sample of 5,632 subjects aged 65–84 with a 3.5-year follow-up. Patients with MCI who consumed up to one drink per day of alcohol had a reduction in the rate of progression to dementia in comparison with patients with MCI who never consumed alcohol (HR: 0.15; 95% CI: 0.03–0.78). Overall, versus nondrinkers, patients with MCI who consumed less than one drink per day of wine had a decrease in the rate of progression to dementia of about 85% (RR: 0.15; 95% CI: 0.03–0.77). Moderate intake of alcohol deriving from wine, controlling for the intake of alcohol deriving from other sources, was also associated with a significantly lower rate of progression to dementia. No significant associations were found between any levels of drinking and the incidence of MCI in non-cognitively impaired individuals versus abstainers (Solfrizzi et al., 2007). These findings from the ILSA on the impact of alcohol intake on the MCI progression to dementia were confirmed in a cohort of Chinese MCI patients, in which was found a J-shaped relationship between alcohol consumption and cognitive

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impairment. The cognitive functions of both heavy drinkers and abstainers decreased to a significantly greater degree during follow-up than those of patients who consumed light to moderate alcohol. In MCI patients, heavy drinking may increase the risk for dementia (Xu et al., 2009). Other studies have also examined the effect of alcohol consumption on risk for the incidence of MCI (Anttila et al., 2004; Cherbuin et al., 2009; Espeland et al., 2005) (Table 2.3). After an average follow-up of 23 years, nondrinkers (OR: 2.15; 95% CI: 1.01–4.59) and frequent drinkers (OR: 2.57; 95% CI: 1.19–5.52) were both more than twice as likely to have MCI in old age as occasional drinkers (Anttila et al., 2004). However, the APOE genotype seemed to modify the relationship, such that the risk of old age dementia increased with increasing mid-life alcohol consumption only among carriers of the APOE a4 allele (Anttila et al., 2004). In the ILSA sample, we failed to confirm these findings, but we note that the alcohol consumption reported was a mid-life determination (Solfrizzi et al., 2007). Probably, a follow-up period longer than 3.5 years would have revealed that moderate alcohol consumption might influence the incidence of MCI. On the other hand, our findings are consistent with those obtained in the Women’s Health Initiative Memory Study with a 4.2 year-follow-up, which found that moderate alcohol intake (r1 drink per day) was associated with an approximately 50% reduced risk of combined probable dementia and MCI (OR: 0.40; 95% CI: 0.28–0.99) (Espeland et al., 2005). However, after adjusting for demographic and socioeconomic factors and baseline Modified Mini-Mental State Examination (3MSE), the significance disappeared (Espeland et al., 2005). Recently, in the PATH Through Life Study, participants with a history of smoking or harmful alcohol consumption, hypertension, or who took medication for anxiety or depression were at increased risk of transitioning to MCI or any mild cognitive disorder (i.e., various predementia syndromes including also MCI) (Cherbuin et al., 2009).

Meta-Analyses on Alcohol Consumption, Cognitive Decline, and Dementia Recently, a systematic review with meta-analysis was carried out to investigate any relationship between incident cognitive decline or dementia in the elderly and alcohol consumption. Studies had been conducted between 1995 and March 2006, and only included longitudinal data on subjects aged r65 years (Peters, Peters, Warner, Beckett, & Bulpitt, 2008). Outcomes measured were variably defined ranging from dementia alone or as well as various subtypes (mainly AD and VaD) or of subtypes of dementia (AD and VaD) alone or in combination (Peters et al., 2008). Meta-analyses suggested that, at least in epidemiological studies, light to moderate alcohol use was associated with a 38% reduced risk of unspecified incident dementia. Also in the studies included in this meta-analysis, there was no close agreement as to what might be con-

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sidered an “appropriate” level of alcohol consumption particularly since the classification of light to moderate drinking varied widely. Possible benefit against dementia was shown for a variety of definitions including more than one drink per day, for weekly or monthly wine consumption, for 250–500 ml (usually wine), for more than three drinks per day, and from one to 28 units per week (Peters et al., 2008). For effects on AD risk, light to moderate alcohol was associated with a significantly reduced risk of 32%, defining optimal amounts as weekly consumption of wine, 1–6 or more than two drinks per week, or more than three drinks/250–500 ml per day (usually wine), or where studied by gender, 1–3 per day in males (Peters et al., 2008). Although the point estimates were also in a similar direction for VaD and cognitive decline (0.82 and 0.89 respectively), the results were not statistically significant (Peters et al., 2008). With regard to effects on cognitive function, results for what could be considered “optimal” or non-deleterious consumption were mixed regarding the amount consumed per month or per day; in subjects with cardiovascular disease or diabetes where results ranged from one to two drinks per week, while for VaD patients 1–3 drinks per day in males appeared to be beneficial (Peters et al., 2008). Finally, another recent meta-analysis included 15 prospective studies (follow-ups ranged from two to eight years), with samples including 14,646 participants evaluated for AD, 10,225 participants evaluated for VaD, and 11,875 followed for any type of dementia (Anstey, Mack, & Cherbuin, 2009). This meta-analysis indicated that light to moderate alcohol intake was associated with a 25–28% reduction in risk of AD, VaD, and any dementia compared with alcohol abstinence in older adults. Heavy drinking was not associated with increased risk of dementia in this study (Anstey et al., 2009). The results of these two meta-analyses were confirmed by a systematic review of health behavioral risks (physical activity, smoking, alcohol drinking, body mass index, and diet and nutrition) on cognition in community representative samples aged 65 years and older, with prospective cohort design and multivariate analysis; results suggested that moderate alcohol consumption tended to be protective against cognitive decline and dementia, but nondrinkers and frequent drinkers exhibited a higher risk for dementia and cognitive impairment (Lee et al., 2010). Finally, a recent systematic review and metaanalysis, reviewing 143 papers that described the relationship between moderate consumption of alcohol and some aspect of cognition, identified two groups: publications from 1977 to 1997 involved neuropsychological evaluations of mostly young-to-middle-aged (18–50 years old) subjects, whereas studies after 1997 examined mental status in mostly older (r55 years old) individuals (Neafsey & Collins, 2011). The earliest studies in younger subjects indicated that moderate drinking impaired cognition, although many later studies from the same period found no difference in cognition between drinkers and nondrinkers. In contrast, studies in older subjects overwhelmingly found that moderate drinking either reduced or had no effect on the risk of cognitive

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impairment or dementia. From a meta-analysis of 74 studies in older individuals, which estimated ratios of risk, an RR of 0.77 was calculated for cognitive risk (dementia or cognitive impairment/decline) associated with moderate drinkers compared with nondrinkers (Neafsey & Collins, 2011). This benefit applied to both men and women, and to all forms of dementia and cognitive impairment. It was found with both light and moderate drinking, whereas heavy drinking was associated with a trend toward higher risk for cognitive impairment and dementia. Wine appeared to be more beneficial than beer or spirits, but only a small number of studies distinguished between alcohol types, some of which reported no difference. There were no apparent geographical factors to account for the findings, because significant benefit persisted in 14/19 countries for which country-specific data were available, with 3/5 of the remaining countries showing nonsignificant reductions as well (Neafsey & Collins, 2011). Although alcohol affects men and women differently, in this very large meta-analysis there were no significant differences between alcohol’s effects on different types of dementia, as seen for overall dementia (0.77), AD (0.73), and VaD (0.66) (Neafsey & Collins, 2011). However, the State-of-theScience Conference convened by the National Institutes of Health found insufficient evidence to draw firm conclusions on the association of any modifiable factors with risk of AD, yet suggested that low or moderate alcohol intake was associated with decreased AD risk (Daviglus et al., 2011).

Alcohol and Cognitive Disorders: Possible Mechanisms Many potential mechanisms have been suggested for interpreting the intricate relationship between alcohol consumption and cognitive function (see Figure 2.1). Negative effects of heavy alcohol drinking on cognitive function have been attributed to alcohol-related nutritional deficiency or direct neurotoxic effects of ethanol (Panza et al., 2009; Frisardi, Panza et al., 2010). In fact, an extensive body of research indicates that alcohol addiction is associated with abnormalities in brain morphology, cerebral glucose and amino acid metabolism, monoaminergic and cholinergic transmitter systems, microcellular structure and function, regional cerebral blood flow and neurocognition disorders (Panza et al., 2009; Frisardi, Panza et al., 2010). Positive effects of moderate alcohol drinking on cognitive function have been attributed to flavonoids or other antioxidants, which may reduce the risk for dementia directly and indirectly by protecting against CVD (Figure 2.1). In fact, alcohol drinking has been associated with fewer brain infarcts and was shown to have a U-shaped relationship with the prevalence of white matter lesions (WML) (Panza et al., 2009). Indeed, higher doses of alcohol may affect cognitive functioning through increased release of acetylcholine from the hippocampus (Fadda & Rossetti, 1998), which is an important neurotransmitter in memory and attention (Panza et al., 2009). In contrast, evidence from animal studies indicated that low doses

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Association with fewer brain infarcts and U-shaped relationship with white matter lesions Association in APOE
4 carriers with hippocampal and amygdalar atrophy

Stimulation of the release of hippocampal acetylcholine in animal models

Light to moderate alcohol consumption

Protection against dementia via a reduction in vascular risk factors: #
increased prostacyclin concentrations #
reduced generation of thromboxane A2 #
inhibition of platelet function-increased levels of HDL cholesterol

Wine consumption may exert a protective effect also through the antioxidant effects of polyphenols richly represented in red wine

FIGURE 2.1 Synopsis of the mechanism by which light to moderate alcohol intake

could be protective against cognitive impairment or decline in older age or against predementia and dementia syndromes. This figure lists various possible mechanisms of light to moderate alcohol consumption linked to their neuroprotective properties against cognitive decline including modulation of cerebrovascular disease (e.g., white matter lesions), stimulation of the release of hippocampal acetylcholine in animal models, association with hippocampal and amygdalar atrophy, reduction in vascular risk factors or through the antioxidant effects of polyphenols richly represented in red wine.

of alcohol may stimulate the release of hippocampal acetylcholine (Stancampiano et al., 2004). Another mechanism by which moderate alcohol intake may protect against dementia is via a reduction in vascular risk factors (Figure 2.1). In fact, moderate doses of alcohol may alter blood clotting mechanisms though increase of prostacyclin concentrations and reduction of thromboxane A2 generation and thus may inhibit platelet function (Panza et al., 2009). Moderate alcohol consumption may also contribute to increased plasma levels of endogenous tissue-type plasminogen activator (tPA), a serine protease that regulates intravascular fibrinolysis, and fibrinolytic activity while decreasing plasma fibrinogen levels (Panza et al., 2009). Furthermore, binge drinking and excessive alcohol consumption were also associated with an increased risk of atrial fibrillation (Mäki et al., 1998; Thornton, 1984), while there is a small but growing literature indicating that

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atrial fibrillation is related to lower cognitive performance (Elias et al., 2006). An important future research goal might be to determine whether light and moderate drinking raises the risk of atrial fibrillation as does binge drinking and heavy drinking. On the other hand, the positive effects of moderate and light drinking are attenuated or even reversed when it takes place in individuals who are taking various medications used in the treatment of atrial fibrillation, coronary artery disease, or drug-eluting coronary stents (Camm et al., 2010), particularly in those patients with atrial fibrillation presenting with an acute coronary syndrome and/or those undergoing percutaneous coronary intervention/stenting (Lip et al., 2010). Therefore, more studies are needed in some sub-populations for which drinking seriously potentiates adverse drug effects. It is also known that alcohol is associated with increased levels of high density lipoprotein (HDL) cholesterol, its subfractions HDL2 and HDL3, and its associated apolipoproteins A-I and A-II (Panza et al., 2009). The association with HDL cholesterol is deemed to account for up to a half of the reduction in coronary events associated with moderate alcohol consumption (Panza et al., 2009). On the other hand, excessive lowering of naturally occurring total cholesterol levels may be associated with poorer performance on cognitive measures (Elias, Elias, D’Agostino, Sullivan, & Wolf, 2005). Moreover, light to moderate alcohol use is associated with a lower prevalence of MRI-defined WMLs and subclinical infarcts (den Heijer et al., 2004), although MRI abnormalities, HDL cholesterol levels, and fibrinogen levels only marginally influenced the association of alcohol consumption and dementia in the CHS (Panza et al., 2009). While the aforementioned vascular factors could affect the risk of unspecified dementia and, probably, of VaD, other experimental and clinical findings may partly explain the suggested protection against AD provided by light to moderate alcohol consumption. Small amounts of alcohol have been reported to be associated with a lower prevalence of vascular brain findings and, in APOE a4 carriers, with hippocampal and amygdalar atrophy as assessed by MRI (den Heijer et al., 2004). Experimental studies found that ethanol initially increases hippocampal acetylcholine release, which could conceivably improve memory performance (Panza et al., 2009). Processes that originate, modulate, or precipitate the deposition of ^-amyloid (A^) in the brain, such as oxidative stress, rather than vascular processes, may better explain the development of AD, and the vascular effects of the alcohol in alcoholic beverages may not be enough to explain the protective effects of the moderate intake of alcohol from dementia, even if the increased plasma tPA levels (Panza et al., 2009) could promote A^ clearance, since tPA is responsible for the formation of plasmin, suggested to be an A^-degrading enzyme (Miners et al., 2008). Wine consumption may exert a protective effect, either through alcohol intake itself, or through the antioxidant effects of polyphenols richly represented in red wine, or through both (Panza et al., 2009; Frisardi, Panza et al., 2010). Red-wine polyphenols are a complex mixture of flavonoids (mainly anthocyanins and

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flavan-3-ols) and non-flavonoids (such as resveratrol and gallic acid). Flavan-3ols are the most abundant, with oligomeric and polymeric procyanidins (condensed tannins) often representing 25–50% of the total phenolic constituents (Waterhouse, 2002). A recent study identified procyanidins as the principal vasoactive polyphenols in red wine and showed that they are present at higher concentrations in wines from areas of southwestern France and Sardinia, where traditional production methods ensure that these compounds are efficiently extracted during vinification (Corder et al., 2006). In the five-year follow-up PAQUID cohort, a significant inverse association between flavonoid intake and the risk of dementia was found (Commenges et al., 2000), suggesting that the antioxidant properties of the flavonoids in wine may help prevent the oxidative damage implicated in dementia. Furthermore, oxidative stress is also likely to develop in the brain, contributing to neuronal death by various mechanisms such as formation of A^ peptide, DNA damage, and abnormal tau protein (Panza et al., 2009). The presence in wine of nonalcoholic components, such as particular antioxidants, could explain a differential effect of wine on dementia since liquor that does not seem to have as strong an effect has been shown to have less antioxidant activity than wine (Panza et al., 2009). Nonetheless, in some studies on the neuroprotective role of moderate alcohol consumption, the most typically consumed alcohol types were beer and spirits (Panza et al., 2009). It is also possible that moderate lifestyles in general, which obviously vary according to different cultural environments, protect from cognitive impairment. Thus, it may not be the direct effect of alcohol or specific substances in alcoholic drinks that provide the protection, but moderate alcohol drinking may be an indicator of a complex set of favorable social and lifestyle factors. A protective effect of alcohol on cognitive function in moderate drinkers may reflect a relatively poor health status among abstainers or because cognitive status influences alcohol consumption and overall health status (Panza et al., 2009). In fact, regular moderate wine consumption is often associated with reduced morbidity and mortality from a variety of chronic diseases in which inflammation is a root cause (Walzem, 2008). On the other hand, persons with higher cognitive performance levels tend to be more successful, better educated, to use drink in a social and business context, and are possibly more prone to report drinking patterns accurately. Wine comes in a wide variety of styles that contain different ethanol and polyphenol contents. Controversy remains as to whether the alcohol or polyphenols contribute more to the health benefits of regular moderate wine consumption. The overall effect of wine consumption on health depends upon the total amounts consumed, the style and possibly the pattern of consumption (Walzem, 2008). The apparent effect of wine consumption may be modified by other aspects of diet: for example, those consuming various levels of alcohol may also consume differential volumes of fruit, vegetable, and whole grain and as such phytochemical intake and benefit may vary, particularly if wine may serve as a primary dietary source of phytochemical (Walzem, 2008).

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Alcohol is also a potent modulator of fatty acid metabolism and is known to influence the fatty acid profiles of different organs (Panza et al., 2009). In animal studies, chronic alcohol exposure has been shown to decrease long-chain polyunsaturated fatty acids (PUFA) concentrations, especially docosahexaenoic acid and arachidonic acid in liver and brain tissues, depending on dosage and length of alcohol exposure (Panza et al., 2009).

Conclusions In the past few years, an increasing body of evidence has emphasized the importance of identifying modifiable risk factors for preventing cognitive decline and delaying the dementia onset. Among these, vascular and lifestylerelated factors for predementia and dementia syndromes have been an area of intensive research, and cumulative evidence has suggested that vascular risk factors may be important in the development of MCI, dementia, and AD (Panza et al., 2009). In several longitudinal studies, light to moderate drinking of alcoholic beverages has been proposed as being protective against the development of age-related changes in cognitive function, predementia syndromes, and cognitive decline of degenerative (AD) or vascular origin (VaD). However, contrasting findings also exist. Light to moderate alcohol drinking has been proposed as a protective factor against MCI and dementia in several longitudinal studies, but contrasting findings also exist and deriving overall conclusions from these studies has many limitations. Many of these studies were limited to cross-sectional design, restriction by age or sex, or incomplete ascertainment. Moreover, outcomes measured, the range of beverages that are available, drinking patterns and how they are categorized as well as follow-up periods studied and possible interactions with other lifestyle- (i.e., smoking) or genetic-related (i.e., APOE genotype) factors are all sources of great variability. Indeed, the body of evidence examined in this chapter and the recent meta-analyses cited (Anstey et al., 2009; Neafsey & Collins, 2011; Peters et al., 2008) of all research published within the last 10 years suggested that light to moderate alcohol use may be associated with a reduced risk of unspecified incident dementia, AD, and VaD, while for cognitive decline and predementia syndromes the current evidence is only suggestive of a protective effect. Thus, at present, the most commonly used outcome measures for these kinds of studies appear to be unspecified dementia, AD, and VaD, where prevalence and diagnostic classifications make the studies more practical compared with the small number of studies reporting other subtypes of cognitive decline. These are more difficult to classify, which is often further complicated by the relatively high vascular factor contribution to AD cases. On the other hand, the cardiovascular mechanisms that related to the suggested protective effects of alcohol may have an even greater effect on VaD (Table 2.4).

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TABLE 2.4 Key points of clinical and epidemiological studies on the relationships among

alcohol consumption and dementia and predementia syndromes A. Among lifestyle-related factors, an increasing body of epidemiological evidence suggests that light to moderate alcohol consumption could offer some benefit for some health outcomes including cognitive function, and heart disease B. Light to moderate alcohol drinking has been proposed as a protective factor against the development of age-related changes of cognitive function, predementia syndromes, and cognitive decline of degenerative (Alzheimer’s disease, AD) or vascular origin (vascular dementia, VaD) in several longitudinal studies, but contrasting findings also exist C. Light to moderate alcohol use may be associated with a reduced risk of unspecified incident dementia and AD, while for VaD, cognitive decline, and predementia syndromes the current evidence is only suggestive of a protective effect D. Different outcome measures, types of beverages, measurement of drinking patterns, or follow-up periods, or possible interactions with other lifestyle-related (e.g., smoking) or genetic factors (e.g., APOE or other genes) are current sources of great variability where there need to be efforts to refine E. Epidemiological evidence suggested that the protective effects of alcohol are more likely with wine consumption and the absence of an apolipoprotein E (APOE) a4 allele. At present, there is no indication that light to moderate alcohol drinking would be harmful to cognition and dementia, and it is not possible to define a specific beneficial level of alcohol intake

Furthermore, there are other important sources of variability that may influence the results of studies on the association between alcohol consumption and cognition. In fact, most of these studies used self-reported alcohol intake, and the reliability of self-reports may be affected by the level of cognition. Another major reason for variability, in cross-sectional studies and longitudinal studies, may be that investigators used different cognitive measures across studies, and many used too few cognitive measures or a single measure. In fact, in a very recent meta-analysis, there was a clear distinction between the studies that used only some type of mental status exam, such as the Mini-Mental State Examination (MMSE), the Telephone Interview for Cognitive Status™ (TICS™), or the TELE telephone interview, and the studies that measured various aspects of cognition primarily by a wide variety of neuropsychological tests (Neafsey & Collins, 2011). In particular, there were 69 studies without ratios of risks providing a total of 87 judgments of whether cognition was worse, no different, or better in drinkers than in nondrinkers or in heavy drinkers than in light drinkers, and the 60% of the studies that used only these mental status exams found that drinkers have a reduced risk of dementia or cognitive impairment compared with nondrinkers (Neafsey & Collins, 2011). On the contrary, when the subjects were evaluated by standard neuropsychological tests in younger subjects (180) was associated with moderately higher risk of dementia and AD, regardless of adjustment for baseline cognitive performance (Fratiglioni, Winblad, & von Strauss, 2007; Guo et al., 2001; Guo, Viitanen, Winblad, & Fratiglioni, 1999; Qiu, Winblad, Fastbom, & Fratiglioni, 2003; Qiu, Winblad, Viitanen, & Fratiglioni, 2003). However,

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this same set of Kungsholmen studies indicated that not only SBP but also low DBP were associated with AD and dementia in general (Fratiglioni et al., 2007; Qiu, von Strauss, Fastbom, Winblad, & Fratiglioni, 2003). The Kungsholmen study (Qiu, Winblad, Viitanen et al., 2003) of PP in relation to incident dementia in 1,270 individuals (75 years and older) free from dementia at baseline is of importance as PP provides a marker of arterial stiffening and poor cerebral circulation. Results indicated a U-shaped association between level of PP and incidence of AD as well as all other dementias investigated. Nagai, Hoshide, and Kario (2010) suggest that the low BP finding may be related to poor cerebral circulation. The problem with studying relations between BP and dementia in later life is that it is impossible to separate the influence of dementia on BP from the influence of BP on dementia. In analyses with pooled three-year follow-up data from the Göteborg H-70 and Rotterdam studies, an inverse association was found between BP, systolic and diastolic, and risk of dementia, but only for participants taking antihypertensive medications (Ruitenberg et al., 2001). Low BP has been more consistently related to dementia than has hypertension (Guo, Viitanen, Fratiglioni, & Winblad, 1996; Morris et al., 2001; Qiu, von Strauss et al., 2003; Qiu, von Strauss, Winblad, & Fratiglioni, 2004; Ruitenberg et al., 2001; Verghese, Lipton, Hall, Kuslansky, & Katz, 2003), especially in persons over 80 years of age (Qiu et al., 2005). In the Bronx Aging study, low DBP (