edition the handbook of health behavior...

The Handbook of Health Behavior Change

E D I T I O N3

Sally A. Shumaker, PhD, is a tenured Professor in Public Health Sciences —Social Sciences and Health Policy, Senior Associate Dean for Research, and Co-Director of the Translational Science Institute. She received her Ph.D. in Social Psychology from the University of Michigan and completed postdoctoral training in environmental and health psychology from the University of Cali-fornia, at Irvine and Los Angeles, respectively. Dr. Shumaker’s research is by nature interdisciplinary and translational, and she has worked with scientists from throughout the world representing a range of health, basic, and social/be-havioral science disciplines. In addition to her senior leadership roles, she has an active research portfolio and is the recipient of a number of grants and con-tracts from the NIH, Foundations and Industry. Dr. Shumaker has written more than 200 journal articles, books, and chapters in the areas of cognitive aging and dementia, disability, HRQL, adherence, and psychosocial factors in disease pro-gression. She holds Fellow status in several professional organizations and is the former president and current secretary-treasurer of an international public policy association. Dr. Shumaker has received national awards in mentoring, behavioral health science, research, and leadership training.

Judith K. Ockene, PhD, MEd, MA, is a tenured Professor of Medicine and Chief of the Division of Preventive and Behavioral Medicine in the Department of Medicine at the University of Massachusetts Medical School (UMMS). She holds the Barbara Helen Smith Chair in Preventive and Behavioral Medicine and is Interim Vice Provost for Faculty Affairs at UMMS. Dr. Ockene is the re-cipient of numerous NIH grants funding research in the prevention of illness and disability and the promotion of health and quality of life for individuals and communities. Much of her research now focuses on women’s health affect-ing morbidity, mortality, and quality of life in older women. Dr. Ockene teaches medical and public health students, residents in training, community physi-cians, and a variety of other health care providers how to help patients make lifestyle changes for the prevention and control of disease and adaptation to illness. Dr. Ockene’s work is at the intersection of clinical medicine and public health. She has more than 150 publications in preventive and behavioral.

Kristin A. Riekert, PhD, is an Assistant Professor of Medicine in the Division of Pulmonary and Critical Care Medicine, Department of Medicine at The Johns Hopkins University and Co-Director of the Johns Hopkins Adherence Research Center ( JHARC). The JHARC serves as a national advisory center on the assess-ment of adherence in clinical trials and conducts ongoing studies of adherence as-sessment and promotion. Dr. Riekert received her PhD in Clinical Psychology from Case Western Reserve University where she specialized in pediatric psychology. She completed postdoctoral training in health psychology at The Johns Hopkins University. Dr. Riekert is the Principal Investigator or Co-Principal Investigator of several NH and foundation sponsored intervention trials focused on improving adherence and health outcomes in cystic fibrosis and asthma. Dr. Riekert’s primary areas of research interest are: psychosocial predictors of adherence in pediatric chronic illness, measurement of adherence, development of culturally and devel-opmentally appropriate interventions to improve adherence, developmental as-pects of transitioning responsibility for health behaviors and care, patient-reported outcome methodology, health care disparities, and doctor-patient communication.

The Handbook of Health Behavior Change

E D I T I O N3

Sally A. Shumaker, PhD

Judith K. Ockene, PhD, MEd, MA

Kristin A. Riekert, PhD

Editors

New York

Copyright © 2009 Springer Publishing Company, LLC

All rights reserved.

No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior permission of Springer Publishing Company, LLC.

Springer Publishing Company, LLC11 West 42nd StreetNew York, NY 10036www.springerpub.com

Acquisitions Editor: Sheri W. SussmanProduction Editor: Julia RosenCover design: Joanne E. HonigmanComposition: Apex CoVantage

08 09 10 11 12/5 4 3 2 1 Library of Congress Cataloging-in-Publication Data

The handbook of health behavior change / Sally A. Shumaker, Judith K. Ockene, Kristin A. Riekert, editors.–3rd ed. p. ; cm. Includes bibliographical references and index. ISBN 978-0-8261-1545-4 (alk. paper) 1. Health behavior. 2. Health attitudes. 3. Self-care, Health. 4. Behavior modifi cation. I. Shumaker, Sally A. II. Ockene, Judith K. III. Riekert, Kristin A. [DNLM: 1. Health Promotion. 2. Behavior Therapy. 3. Health Behavior. 4. Patient Compliance. WA 590 H2356 2008] RA776.9.H36 2008 613—dc22 2008024564

Printed in the United States of America by Hamilton Printing Company.

The author and the publisher of this Work have made every effort to use sources believed to be reliable to provide information that is accurate and compatible with the standards generally accepted at the time of publication. The author and publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers’ use of, or reliance on, the information contained in this book.

The publisher has no responsibility for the persistence or accuracy of URLs for external or third-party Internet Web sites referred to in this publication and does not guarantee that any content on such Web sites is, or will remain, accurate or appropriate.

This book is dedicated to all of the people who work hard to maintain a healthy lifestyle in the midst of multiple personal, social and cultural challenges—and to all the health care professionals who work hard to help their patients succeed in

meeting the challenges of healthy living.

vii

Tables and Figures. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .xiii

Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .xix

Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxvii

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xxxi

Section I Health Behavior Change and Maintenance: Theory and Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Judith K. Ockene

Chapter 1 Theories of Prevention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Susan J. Curry and Marian L. Fitzgibbon

Chapter 2 Theoretical Models and Strategies for Improving Disease Management by Patients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

Noreen M. Clark and Christy R. Houle

Chapter 3 Culture and Health-Related Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . 39

Milagros C. Rosal and Jamie S. Bodenlos

Chapter 4 The Transtheoretical Model of Behavior Change . . . . . . . . . . . . . . . 59

James O. Prochaska, Sara Johnson, and Patricia Lee

Chapter 5 Multilevel Theories of Behavior Change: A Social Ecological Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85

Margaret Schneider and Daniel Stokols

Chapter 6 Models of Provider-Patient Interaction and Shared Decision Making . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107

Michael G. Goldstein, Judith DePue, and Alessandra N. Kazura

Contents

viiiChapter 7 Relapse Prevention and the Maintenance of

Optimal Health . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127

Christian S. Hendershot, G. Alan Marlatt,

and William H. George

Chapter 8 Motivational Interviewing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 Claire A. Lane and Stephen Rollnick

Chapter 9 E-Health Strategies to Support Adherence . . . . . . . . . . . . . . . . 169 Patricia D. Franklin, Ramesh Farzanfar, and

Deborah D. Thompson

Section II Interventions for Lifestyle Change . . . . . . . . . . . . . . .191 Judith K. Ockene

Chapter 10 Addressing Tobacco Use and Dependence . . . . . . . . . . . . . . . . 193 Denise G. Jolicoeur, Beth M. Ewy, Judith K. Ockene,

Lori Pbert, and David B. Abrams

Chapter 11 Promoting Dietary Change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 Barbara S. McCann and Viktor E. Bovbjerg

Chapter 12 Adherence to Physical Activity Recommendations and Interventions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235 Bess H. Marcus, Joseph T. Ciccolo, Dori Whitehead,

Teresa K. King, and Beth C. Bock

Chapter 13 Adoption and Maintenance of Safer Sexual Practices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 253 Michelle J. Naughton and Scott D. Rhodes

Chapter 14 Intervention Elements Promoting Adherence to Mindfulness-Based Stress Reduction (MBSR) Programs in a Clinical Behavioral Medicine Setting . . . . . . . . . 271 Paul G. Salmon, Saki F. Santorelli, Sandra E. Sephton,

and Jon Kabat-Zinn

Chapter 15 Multiple Risk Behavior Change: What Most Individuals Need . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 287 Judith J. Prochaska and Janice M. Prochaska

Contents

ix Section III Measurement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .307

Kristin A. Riekert

Chapter 16 Measuring Adherence to Medication Regimens in Clinical Care and Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 309 Michiko Otsuki, Emmanuelle Clerisme-Beaty,

Cynthia S. Rand, and Kristin A. Riekert

Chapter 17 The Measurement of Physical Activity . . . . . . . . . . . . . . . . . . . . 327 Sara Wilcox and Barbara E. Ainsworth

Chapter 18 Changes in Substance Use Behavior . . . . . . . . . . . . . . . . . . . . . 347 Donald M. Dougherty, Michael A. Dawes, and Sylvain Nouvion

Chapter 19 Statistical Issues in Measuring Adherence: Methods for Incomplete Longitudinal Data . . . . . . . . . . . . . . . . 375 Mark R. Conaway, W. Jack Rejeski, and Michael E. Miller

Section IV Obstacles and Predictors of Lifestyle Change and Adherence . . . . . . . . . . . . . . . . . . . . . . . . .393

Sally A. Shumaker

Chapter 20 Predictors of Patient Adherence: Patient Characteristics . . . . 397 Jacqueline Dunbar-Jacob, Leigh A. Gemmell, and Elizabeth A. Schlenk

Chapter 21 Biopsychological Obstacles to Adoption and Maintenance of a Healthy Lifestyle . . . . . . . . . . . . . . . . . . . . . . . 411 Neil E. Grunberg and Laura Cousino Klein

Chapter 22 Adolescent Tobacco Use and the Social Context . . . . . . . . . . . . 427 Christina K. Holub, David G. Altman, and Christine Jackson

Chapter 23 Psychosocial Barriers to Adherence and Lifestyle Change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 445 Summer L. Williams, M. Robin DiMatteo, and Kelly B. Haskard

Chapter 24 Changing Clinical Behavior: Implementing Guidelines to Improve Primary Care Practice . . . . . . . . . . . . . . . . . . . . . . . . 463 Elizabeth Dugan, Katherine Dodd, and Shellie Ellis

Contents

x Section V Lifestyle Change and Adherence Issues

Within Specific Populations . . . . . . . . . . . . . . . . . . . . . .479

Sally A. Shumaker

Chapter 25 Lifestyle Interventions for the Young . . . . . . . . . . . . . . . . . . . . . 483 Carolyn E. Ievers-Landis and Dawn Witherspoon

Chapter 26 Problems With Adherence in the Elderly . . . . . . . . . . . . . . . . . . 499 Carolyn L. Murdaugh and Kathleen Insel

Chapter 27 Optimizing Adherence in Older Adults With Cognitive Impairment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 519 Barbara Resnick, Elizabeth Galik, Eun Shim Nahm,

Marianne Shaughnessy, and Kathleen Michael

Chapter 28 Adherence Issues Among Adolescents With Chronic Diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 545 Michael A. Rapoff

Chapter 29 Health Disparities and Minority Health . . . . . . . . . . . . . . . . . . . . 589 Melicia C. Whitt-Glover, Bettina M. Beech, Ronny A. Bell,

Sharon A. Jackson, Kismet A. Loftin-Bell, and David L. Mount

Section VI Lifestyle Change and Adherence Issues Among Patients With Chronic Diseases . . . . . . . . . . . . . . . 607

Kristin A. Riekert

Chapter 30 Adherence for Patients With Chronic Obstructive Pulmonary Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 609 Robert M. Kaplan

Chapter 31 Aging, Cognition, and Diabetes: The Transition From Self-Care to a Caregiver for Diabetes Self-Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 627 Laura H. Coker

Chapter 32 Adherence to Treatment and Lifestyle Changes Among People With Cancer . . . . . . . . . . . . . . . . . . . . . 643 Amy H. Peterman, David Victorson, and David Cella

Chapter 33 Adherence and HIV: A Lifetime Commitment . . . . . . . . . . . . . . 659

Contents

xi Scott D. Rhodes, Kenneth C. Hergenrather, Aimee M. Wilkin,

and Richard Wooldredge

Chapter 34 Lifestyle Change and Adherence Issues Among Patients With Heart Disease . . . . . . . . . . . . . . . . . . . . . . 677 Laura L. Hayman

Chapter 35 Does Cognition Influence Type 2 Diabetes-Related Adherence? . . . . . . . . . . . . . . . . . . . . . . . . . . . 693 David L. Mount

Section VII Lifestyle Change and Adherence: The Broader Context . . . . . . . . . . . . . . . . . . . . . . . . . . .709 Sally A. Shumaker

Chapter 36 Adherence and the Placebo Effect . . . . . . . . . . . . . . . . . . . . . . . 713 Susan M. Czajkowski, Margaret A. Chesney, and Ashley W. Smith

Chapter 37 Collaboration Between Professionals and Mediating Structures in the Community: Social Determinants of Health and Community-Based Participatory Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 735 Suzanne B. Cashman and Laurie G. Forlano

Chapter 38 Ethical Issues in Lifestyle Change and Adherence . . . . . . . . . . 757 Nancy M. P. King

Chapter 39 Adherence and Health Outcomes: How Much Does Adherence Matter? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 771 Kelly B. Haskard, M. Robin DiMatteo, and Summer L. Williams

Chapter 40 Lessons Learned: What We Know Doesn’t Work and What We Shouldn’t Repeat . . . . . . . . . . . . . . . . . . . . . 785 Deborah J. Bowen and Uli Boehmer

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 795

Contents

xiii

Section I

Chapter 1

Table 1.1 5-Year Myocardial Infarction (MI) Risk and Risk Factors . . . . . . . . 11

Chapter 2

Figure 2.1 The Health Belief Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Figure 2.2 The continuous and reciprocal nature of self-regulation processes in disease prevention and management . . . . . . . . . . . . 28

Figure 2.3 Allies coalition model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Chapter 4

Figure 4.1 The pros and cons (in T scores) by stages of changefor 48 problem behaviors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

Table 4.1 Stages of Change in Which Change Processes Are Most Emphasized . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

Figure 4.2 Point prevalence abstinence (%) for four treatment groupsat pretest and at 6, 12, and 18 months . . . . . . . . . . . . . . . . . . . . . . . . . 76

Chapter 5

Figure 5.1 Depiction of Bronfenbrenner’s Bioecological Systems Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88

Figure 5.2 Postulated algorithm describing the vicious cycle wherein stress, poor diet, and low physical activity all

Tables and Figures

xivcontribute to hyperinsulinemia and obesity, which then feeds back, via impaired leptin sensitivity, to furtherexacerbate the cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96

Chapter 6

Table 6.1 Barriers to Provider Involvement in Behavior Change Interventions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109

Table 6.2 Core Competencies for Self-Management Support . . . . . . . . . . . . 114

Table 6.3 The 5 As for Behavioral Counseling and Health Behavior Change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116

Figure 6.1 The Chronic Care Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118

Figure 6.2 Self-management support: An ongoing process . . . . . . . . . . . . . . 120

Chapter 7

Figure 7.1 Dynamic model of relapse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133

Chapter 8

Figure 8.1 Reflective listening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159

Chapter 9

Table 9.1 Comparison of Attributes of E-health Strategies . . . . . . . . . . . . . . 178

Figure 9.1 User interaction intensity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179

Section II

Chapter 10

Table 10.1 Pharmacologic Product Guide: FDA-Approved Medications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202

Tables and Figures

xv Chapter 15

Figure 15.1 Excess pharmaceutical costs due to excess risks, age and gender adjusted . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 296

Figure 15.2 Excess disability costs due to excess risks. . . . . . . . . . . . . . . . . . . . 296

Table 15.1 Recruitment Incentives and Participation Rates . . . . . . . . . . . . . . . 300

Section III

Chapter 17

Table 17.1 Useful Resources for the Measurement of Physical Activity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328

Table 17.2 Issues to Consider When Selecting a Physical Activity Measure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 330

Table 17.3 Examples of Self-Report Physical Activity Measures for Adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333

Chapter 18

Table 18.1 Substance Use Screening Measures, Questionnaires, and Structured and Semistructured Interviews . . . . . . . . . . . . . . . 351

Table 18.2 Laboratory Measures of Substance Use . . . . . . . . . . . . . . . . . . . . . . 360

Chapter 19

Table 19.1 A Monotone-Nonresponse Pattern . . . . . . . . . . . . . . . . . . . . . . . . . . . 380

Table 19.2 LIFE Home-Based Physical Activity Logs Collected During Maintenance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 384

Table 19.3 Estimated Intercepts and Slopes for Log Minutes of Physical Activity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 385

Figure 19.1 Plot of actual and predicted values at each month of follow-up . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 386

Tables and Figures

xviSection V

Chapter 27

Table 27.1 Description of the Interventions to Facilitate Adherence in CI Older Adults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 532

Chapter 28

Table 28.1 Nonadherence Rates for Selected Chronic Disease Regimens (Studies That Include or Exclusively Report on Adolescents) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 548

Table 28.2 Adherence Intervention Studies Involving Adolescents With Chronic Diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 568

Chapter 29

Figure 29.1 PEN-3 conceptual framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 599

Section VI

Chapter 30

Figure 30.1 Results of treadmill endurance exercise tests for patients in the rehabilitation (Rehab) and education groups at baseline and for 12 months of follow-up . . . . . . . . . . . . . . . . . . . . . . 616

Figure 30.2 Changes in the Quality of Well-Being Scale (QWB). . . . . . . . . . . . . 618

Figure 30.3 Walking compliance by cognitive, behavioral, or control groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 619

Figure 30.4 Mean change in QWB (multiplied by 100) by group . . . . . . . . . . . . 620

Chapter 33

Figure 33.1 Domains affecting adherence to HAART and viral load among persons living with HIV/AIDS . . . . . . . . . . . . . . . . . . . . . . . . . 661

Tables and Figures

xviiChapter 34

Table 34.1 Actions to Increase Adherence to Treatment Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 681

Chapter 35

Figure 35.1 Neurocognitive markers of everyday functioning . . . . . . . . . . . . . 697

Section VII

Chapter 36

Table 36.1 The Influence of Adherence on 5-Year Mortality Rates in the Coronary Drug Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 715

Figure 36.1 The effects of adherence on health outcomes . . . . . . . . . . . . . . . . . 720

Tables and Figures

xix

David B. Abrams, PhD Office of the Director National Institutes of Health Bethesda, MD

Barbara E. Ainsworth, PhD, MPH Department of Exercise and Wellness Arizona State University Mesa, AZ

David G. Altman, PhD Center for Creative Leadership Greensboro, NC

Bettina M. Beech, DrPH Division of Internal Medicine and Public

Health Vanderbilt University School of

Medicine Nashville, TN

Ronny A. Bell, PhD, MS Department of Epidemiology and

Prevention Division of Public Health Sciences Maya Angelou Research Center on

Minority Health Wake Forest University School of

Medicine Winston-Salem, NC

Beth C. Bock, PhD Department of Psychiatry and Human

Behavior Centers for Behavioral and Preventive

Medicine Brown Medical School and

The Miriam Hospital Providence, RI

Jamie S. Bodenlos, PhD Division of Preventive and Behavioral

Medicine Department of Medicine University of Massachusetts Medical

School Worcester, MA

Uli Boehmer, PhD Social and Behavioral Sciences

Department School of Public Health Boston University Boston, MA

Viktor E. Bovbjerg, MPH, PhD Department of Public Health Sciences University of Virginia School of Medicine Charlottesville, VA

Deborah J. Bowen, PhD Social and Behavioral Sciences Department School of Public Health Boston University Boston, MA

Suzanne B. Cashman, ScD Department of Family Medicine and

Community Health University of Massachusetts Medical


David Cella, PhD Center on Outcomes, Research, and

Education Evanston Northwestern Healthcare

and Northwestern University Feinberg School of Medicine

Evanston, IL

Contributors

xx Margaret A. Chesney, PhD National Center for Complementary and

Alternative Medicine National Institutes of Health Bethesda, MD

Joseph T. Ciccolo, PhD Department of Psychiatry and Human


Medicine Brown Medical School and

The Miriam Hospital Providence, RI

Noreen M. Clark, PhD Center for Managing Chronic Disease University of Michigan Ann Arbor, MI

Emmanuelle Clerisme-Beaty, MD, MHS Division of Pulmonary and Critical

Care Medicine The Johns Hopkins University Baltimore, MD

Laura H. Coker, PhD Department of Social Sciences and

Health Policy Division of Public Health Sciences Wake Forest University School of Medicine Winston-Salem, NC

Mark R. Conaway, PhD Division of Biostatistics and

Epidemiology Department of Public Health University of Virginia Health Systems Charlottesville, VA

Susan J. Curry, PhD Institute for Health Research and Policy University of Illinois at Chicago Chicago, IL

Susan M. Czajkowski, PhD Clinical Applications and Prevention Branch Division of Prevention and Population

Sciences National Heart, Lung, and Blood Institute National Institutes of Health Bethesda, MD

Michael A. Dawes, MD Neurobehavioral Research Laboratory

and Clinic University of Texas Health Science

Center at San Antonio San Antonio, TX

Judith DePue, EdD, MPH Centers for Behavioral and Preventive

Medicine The Miriam Hospital/Brown Medical

School Providence, RI

M. Robin DiMatteo, PhD Department of Psychology University of California,

Riverside Riverside, CA

Katherine Dodd, MPH Division of Geriatric Medicine University of Massachusetts Medical

School and The Meyers Primary Care

Institute Worcester, MA

Donald M. Dougherty, PhD Neurobehavioral Research Laboratory

and Clinic University of Texas Health Science

Center at San Antonio San Antonio, TX

Elizabeth Dugan, PhD Division of Geriatric Medicine University of Massachusetts Medical

School and The Meyers Primary Care

Institute Worcester, MA

Jacqueline Dunbar-Jacob, PhD, RN, FAAN School of Nursing Pittsburgh, PA

Shellie Ellis, MA Translational Science Institute Wake Forest University School of


Contributors

xxi Beth M. Ewy, MPH, CHES Center for Tobacco Treatment Research

and Training Division of Preventive and Behavioral

Medicine University of Massachusetts Medical


Ramesh Farzanfar, PhD Medical Information Systems Unit Boston University Medical Center Boston, MA

Marian L. Fitzgibbon, PhD Institute for Health Research

and Policy University of Illinois at Chicago Chicago, IL

Laurie G. Forlano, DO, MPH Department of Family Medicine and

Community Health University of Massachusetts Worcester, MA

Patricia D. Franklin, MD, MPH, MBA Department of Orthopedics and Physical

Rehabilitation University of Massachusetts Medical

Center Worcester, MA

Elizabeth Galik, PhD, CRNP University of Maryland School

of Nursing Baltimore, MD

Leigh A. Gemmell, PhD VA Pittsburgh Healthcare System Pittsburgh, PA

William H. George, PhD Department of Psychology University of Washington Seattle, WA

Michael G. Goldstein, MD Clinical Education and Research Institute for Healthcare

Communication New Haven, CT

Neil E. Grunberg, PhD Department of Medical and Clinical

Psychology Uniformed Services University of the

Health Sciences University of the Health Sciences Bethesda, MD

Kelly B. Haskard, PhD Department of Psychology Texas State University San Marcos, TX

Laura L. Hayman, PhD Nursing College of Nursing and Health

Sciences University of Massachusetts-Boston Boston, MA

Christian S. Hendershot, MS Department of Psychology University of Washington Seattle, WA

Kenneth C. Hergenrather, PhD, MSEd, MRC Department of Counseling Human and

Organizational Studies Graduate School of Education and

Human Development The George Washington University Washington, D.C.

Christina K. Holub, MPH Department of Health Behavior and

Health Education University of North Carolina at Chapel

Hill Chapel Hill, NC

Christy R. Houle, MPH Center for Managing Chronic Disease University of Michigan Ann Arbor, MI

Carolyn E. Ievers-Landis, PhD Division of Behavioral Pediatrics and

Psychology Rainbow Babies and Children’s

Hospital Case Western Reserve University School

of Medicine Cleveland, OH

Contributors

xxii Kathleen Insel, RN, PhD Division of Nursing Practice University of Arizona Tucson, AZ

Christine Jackson, PhD Public Health and Environment RTI International Research Triangle Park, NC

Sharon A. Jackson, PhD Northrop Grumman Division of Heart Disease and Stroke

Prevention National Center for Chronic Disease

Prevention and Health Promotion Centers for Disease Control and Prevention Atlanta, GA

Sara Johnson, PhD Pro-Change Behavior Systems, Inc. West Kingston, RI

Denise G. Jolicoeur, MPH, CHES Division of Preventive and Behavioral

Medicine University of Massachusetts Medical School Worcester, MA

Jon Kabat-Zinn, PhD Department of Medicine (Emeritus) Center for Mindfulness in Medicine,

Health Care, and Society University of Massachusetts Medical School Worcester, MA

Robert M. Kaplan, PhD Department of Health Services UCLA School of Public Health Los Angeles, CA

Alessandra N. Kazura, MD Center for Tobacco Independence

Maine Health Portland, ME

Nancy M. P. King, JD Department of Social Sciences and

Health Policy Wake Forest University School of


Teresa K. King, PhD Department of Psychology Bridgewater State College Bridgewater, MA

Laura Cousino Klein, PhD Department of Biobehavioral Health Pennsylvania State University University Park, PA

Claire A. Lane, PhD Cardiff University Nursing, Health and Social Care

Research Center Cardiff, UK

Patricia Lee, MA University of Alabama at Birmingham School of Public Health Birmingham, AL

Kismet A. Loftin-Bell, MALS, MSL Department of Epidemiology and

Prevention Wake Forest University School of


Bess H. Marcus, PhD Department of Community Health and

Psychiatry and Human Behavior Brown University Providence, RI

G. Alan Marlatt, PhD Department of Psychology University of Washington Seattle, WA

Barbara S. McCann, PhD Department of Psychiatry and Behavioral

Sciences University of Washington School of

Medicine Seattle, WA

Kathleen Michael, PhD, CCRN Baltimore Veterans Administration

Medical Center Geriatrics Research Education and Clinical Center University of Maryland School


Contributors

xxiii Michael E. Miller, PhD Department of Biostatistical Sciences Wake Forest University School of


David L. Mount, PsyD, MA Department of Internal Medicine Maya Angelou Research Center on

Minority Health Hypertension and Vascular Research

Center Wake Forest University School of


Carolyn L. Murdaugh, RN, PhD, FAAN Professor and Associate Dean for

Research University of Arizona Tucson, AZ

Eun Shim Nahm, PhD, RN University of Maryland School


Michelle J. Naughton, PhD Department of Social Sciences and

Health Policy Wake Forest University School of


Sylvain Nouvion, PhD Department of Psychiatry and Behavioral

Medicine Wake Forest University School of


Michiko Otsuki, PhD Department of Psychology University of South Florida,

St. Petersburg St. Petersburg, FL

Lori Pbert, PhD Division of Preventive and Behavioral

Medicine University of Massachusetts Medical


Amy H. Peterman, PhD Department of Psychology University of North Carolina at Charlotte Charlotte, NC

James O. Prochaska, PhD Cancer Prevention Research Center University of Rhode Island Kingston, RI

Janice M. Prochaska, PhD Pro-Change Behavior Systems, Inc. West Kingston, RI

Judith J. Prochaska, PhD, MPH Department of Psychiatry University of California, San Francisco San Francisco, CA

Cynthia S. Rand, PhD Department of Medicine The Johns Hopkins University Baltimore, MD

Michael A. Rapoff, PhD Department of Pediatrics University of Kansas Medical Center Kansas City, KS

W. Jack Rejeski, PhD Department of Health and Exercise Science Wake Forest University Winston-Salem, NC

Barbara Resnick, PhD, CRNP, FAAN, FAANP Ziporkin Gershowitz Chair in

Gerontological Nursing University of Maryland School


Scott D. Rhodes, PhD, MPH Department of Social Sciences and

Health Policy Wake Forest University School

of Medicine Winston-Salem, NC

Stephen Rollnick, PhD Department of General Practice Cardiff University Centre for Health Sciences Research Cardiff, UK

Contributors

xxiv Milagros C. Rosal, PhD Division of Preventive and Behavioral

Medicine Department of Medicine University of Massachusetts Medical School Worcester, MA

Paul G. Salmon, PhD Department of Psychological and Brain

Sciences University of Louisville Louisville, KY

Saki F. Santorelli, EdD, MA Center for Mindfulness in Medicine,

Health Care, and Society Division of Preventive and Behavioral

Medicine Department of Medicine University of Massachusetts Medical School Worcester, MA

Elizabeth A. Schlenk, PhD, RN School of Nursing Pittsburgh, PA

Margaret Schneider, PhD Department of Planning, Policy, and Design School of Social Ecology University of California Irvine, CA

Sandra E. Sephton, PhD Department of Psychological and Brain

Sciences and James Graham Brown Cancer Center

University of Louisville Louisville, KY

Marianne Shaughnessy, PhD Baltimore Veterans Administration

Medical Center Geriatrics Research Education and Clinical Center University of Maryland School of Nursing Baltimore, MD

Ashley W. Smith, PhD, MPH Outcomes Research Branch, Applied

Research Program Division of Cancer Control and

Population Sciences National Cancer Institute National Institutes of Health Bethesda, MD

Ralph L. Smith, PhD Department of Pediatrics University of Kansas Medical Center Kansas City, KS

Daniel Stokols, PhD Department of Planning, Policy, and

Design Department of Psychology and Social

Behavior School of Social Ecology University of California Irvine, CA

Deborah D. Thompson, PhD USDA/ARS Children’s Nutrition

Research Center Department of Pediatrics Baylor College of Medicine Houston, TX

David Victorson, PhD Center on Outcomes, Research and

Education Evanston Northwestern Healthcare and

Northwestern University Feinberg School of Medicine

Evanston, IL

Dori Whitehead, PhD Department of Psychiatry and Human


Medicine Brown Medical School and The Miriam

Hospital Providence, RI

Melicia C. Whitt-Glover, PhD Department of Epidemiology and

Prevention Division of Public Health Sciences Maya Angelou Research Center on

Minority Health Wake Forest University School of Medicine Winston-Salem, NC

Sara Wilcox, PhD Department of Exercise Science Arnold School of Public Health University of South Carolina Columbia, SC

Contributors

xxvContributors

Aimee M. Wilkin, MD, MPH Department of Internal Medicine Wake Forest University School of Medicine Winston-Salem, NC

Summer L. Williams, MA Department of Psychology University of California,

Riverside Riverside, CA

Dawn Witherspoon, MA Department of Psychology Case Western University Cleveland, OH

Richard Wooldredge, MA Northwest Care

Consortium Winston-Salem, NC

xxvii

The first edition of this book was published in 1988, growing out of a recogni-tion in medicine and public health that many acute and chronic diseases can be prevented or at least have their impact lessened by increased attention to the adoption and maintenance of behaviors for optimal health. This recognition evolved from the many epidemiologic investigations demonstrating the exis-tence of a strong relationship among the onset, progression, and exacerbation of diseases and alteration of lifestyles, such as smoking cessation, developing healthy eating habits, taking medications as prescribed, increasing physical ac-tivity, and practicing safe sex. There was also increased awareness that for the adoption of healthy behaviors to occur and be sustained there were not only demands and responsibilities placed on the individual at risk. There were also demands placed on the health care system and its providers; on other chan-nels within the community such as schools, worksites, and churches; and on the social and political context in which change occurs. That first edition included 24 chapters covering theory, lifestyle interventions, obstacles to change and adherence, population-specific issues, and what we then termed “the broader context.”

More than 20 years later, a comparison of this third edition to the original provides a vivid view of just how much this field has grown and, to a lesser degree, how many challenges remain the same. There is no question that re-search on behavior change and adherence has become more central to clinical research and care—no longer a peripheral or add-on element but recognized as an essential part of the health and well-being of the public. Further, there is an increased recognition of just how complex the issue of behavior change and maintenance is, and how embedded this issue is in the entire fabric of a society—going far beyond the ability of a single individual to change his or her approach to preventive care and treatment. And yet people and their health professionals continue to struggle with achieving optimal lifestyles and adher-ing to the medical regimens and health behaviors that will minimize diseases and their impact. This book provides an updated and substantially expanded view of the theoretical and empirical literature on the factors that influence the adoption of healthy behaviors and the individual, interpersonal, social, and cul-tural factors that can inhibit or promote behavior change. In keeping with the evolution of this field, we have added a number of new chapters to fully reflect this important area of health research and care.

Preface

xxviii Chapters 1–9 in Section I of the book provide a review of past and current

theoretical models of health behavior change, disease prevention, disease man-agement, and relapse prevention. In addition, models of the maintenance of new behaviors are considered. Reviews are provided of some of the more cur-rent techniques used to enhance adherence are provided—such as motivational interviewing and shared decision-making.

Chapters 10–15, Section II, focus on a range of some of the more critical areas of health behaviors—providing updated reviews and the complexities of these specific lifestyle interventions among diverse patient populations. Health behaviors considered include tobacco use, diet, physical activity, safer sexual practices, and stress reduction. Recognizing that healthy lifestyles most often encompass multiple behaviors and are best considered within the context of their interdependence, the final chapter tackles the complexities of multiple risk behavior change.

In the earlier two editions of this book, measurement issues were addressed within other chapters or as a single chapter within a section as there was limited information on this topic at that time. As a further demonstration of the growth of this field, the current edition dedicates a full section to measurement. Chap-ters 16–19 in Section III review adherence assessment in both clinical care and research, assessing physical activity and substance abuse reliably, and some of the statistical issues addressed when measuring and analyzing adherence behavior in the research setting.

In Section IV, chapters 20–24 address the factors that predict or serve as ob-stacles to lifestyle change and adherence. Authors consider individual patient characteristics, biological and psychosocial factors, the social context, and the unique challenges associated in trying to change physician practices in clinical settings to be more congruent with best practices as they relate to health behav-ior recommendations. With the growing recognition of the multiple levels of in-fluences—from intrapersonal to societal and policy—in determining behavior, all of the authors in this section ground their presentations in this broader and, admittedly, more complex view of behavior change and maintenance.

Chapters 25–29 in Section V consider the unique and similar issues associ-ated with maintained behavior change within specific populations. Populations considered include: the young, the elderly, adults with cognitive impairments, and adolescents with chronic diseases. In addition, the final chapter addresses the complicated interrelationships among health disparities, minority status, and heath behavior change.

Medical regimen adherence is a major problem in clinical care and re-search. In Section VI (chapters 30–35), authors discuss the challenges associ-ated with adhering to the often complicated health regimens faced by people with chronic diseases. These include patients with chronic obstructive pulmo-nary disease (COPD), diabetes, cancer, and HIV. In addition, chapter 34 looks at adherence issues among patients with multiple chronic diseases, while chap-ter 35 considers the role of cognition in adherence behavior among patients with type 2 diabetes.

In the final section of the book (chapters 36–40), authors consider the issues of behavior change and adherence within a broader context. The first chapter addresses the subtle interaction between placebo effects and adherence and the implications of this interaction for any behavior change believed by an indi-

Preface

xxixPreface

vidual to be health enhancing. In the second chapter, authors consider the value of social determinants of health coupled with community-based participatory research in realizing the full potential of achieving lasting lifestyle changes. The role of ethics is explored as it relates to the issue of adherence and how it is framed—particularly with respect to the clinical versus research setting. The final two chapters of the book ask two very different but critical issues that, in some ways, bring us back to the beginning: Does adherence matter? And, have we really learned anything in our years of research on this topic?

In total, this book represents an updated and thorough examination of the factors that influence people’s choices to change their behaviors in order to en-hance their health, and the intrapersonal, interpersonal, sociocultural, and pol-icy factors that can both positively and negatively affect the choices made and one’s ability to achieve a desired behavior. This book is particularly valuable at the graduate student level in the fields of public or population health, health psychology, health communications, and medical sociology and anthropology. In addition, advanced-level undergraduate students in or population health-related courses within the social sciences will find this of value. The content of this book will also be informative to clinical investigators, behavioral and social scientists, and practitioners who grapple with the issues confronting individu-als who must make well-informed decisions regarding their health-related be-haviors, change many difficult health habits, and adopt new behaviors.

xxxi

Contents

The editors kindly acknowledge the following individuals who contributed to making this new edition possible:

Sonya Ashburn, Assistant to the Editors, The Handbook of Health Behavior Change (3rd ed.)

The following people provided content expertise in reviewing chapters in The Handbook of Health Behavior Change (3rd ed.):

Michiko Otsuki, PhD

Stephenie Lemon, PhD

Sherry Pagoto, PhD

Roger Luckmann, PhD

Milagros Rosal, PhD

Jacki Hecht, RN, MSN

Gbenga Ogedegbe, MD, MPH, MS

Jamie Bodenlos, PhD

Karen Potvin Klein, MA, ELS (Wake Forest University School of Medicine) pro-vided proofreading and editorial assistance.

Acknowledgments

1Section

1

Health Behavior Change and Maintenance: Theory and Techniques

Judith K. OckeneEditor

Chapters in Section I provide a detailed review of a wide variety of theories of behavior change addressing cognitive, interpersonal, social, and cultural fac-tors that are proposed to have an effect on an individual’s behavior and change of those behaviors. Section I also includes chapters that address specific strat-egies that help facilitate behavior change.

Theories attempt to explain cause-effect relationships and help to provide a basis for understanding and predicting behavior, behavior change, and main-tenance; for developing interventions to achieve changes in health-risk behav-iors; and for evaluating the outcomes of the interventions. No single theory is all-encompassing.

2 The first chapter in Section I, by Curry and Fitzgibbon, provides “Theories

of Prevention” that the authors posit is needed to close the “gap between what we can achieve and what we do achieve for disease prevention.” The second chapter, by Clark and Houle, “Theoretical Models and Strategies for Improv-ing Disease Management by Patients,” reviews several models and theories that have been used to address adherence in self-management of health and dis-ease. Other chapters present the transtheoretical model of behavior change, multilevel theories of behavior change, and models of provider-patient interac-tion and shared decision-making. Chapters addressing techniques for health behavior change and maintenance also are included. The techniques include intervention for relapse prevention and maintenance, motivational interview-ing, and e-health strategies to support adherence. There also is a chapter on the influence of culture on behavior.

Even though there are many theories and models available, there is still much we have not been able to explain or prove about why and how people make changes in health-risk behaviors and, just as importantly, maintain those changes. To fill in the black box of behavior change, we must be able to move outside the box. Theories can be used to guide us but should not constrain our creativity. We must be open to integrating, expanding, and testing our theories in order to expand our base of knowledge and to using what we learn from practice to alter our theories.

Section 1

3

1

At the beginning of the 20th century, the three leading causes of death were pneumonia/influenza, tuberculosis, and gastritis. These three diseases ac-counted for more than a third of all deaths at the time (Brownson & Bright, 2004). Advances in microbiology formed the foundation for infectious disease prevention during the first half of the 20th century. Following Koch’s work in the late 1800s on the anthrax bacillus showing how bacteria could cause dis-ease, numerous pathogenic organisms were discovered, and the germ theory of prevention emerged as a driving force in medicine and public health (Bullough & Rosen, 1992). Some prevention efforts were derived from advances in the biomedical sciences after the discovery that antibodies from infected organ-isms could be used to inoculate healthy individuals against pathogen-borne diseases. By identifying environmental sources of exposure to disease-causing

Susan J. Curry and Marian L. Fitzgibbon

Theories of Prevention

4 The Handbook of Health Behavior Change

bacteria, the germ theory of prevention also spurred wide-scale investments in the public health infrastructure to create healthier environments (e.g., clean water, better sanitation, improved nutrition).

The success of interventions derived from the germ theory of prevention were evident by the mid-20th century. By 1951, death rates from infectious dis-eases had fallen dramatically, and increases in life expectancy also were evident. In 1900, average life expectancy at birth was 46 years for males and 48 years for females. By 1950, life expectancy had increased to 66 and 71 years, respectively (National Center for Health Statistics, 2006).

Currently, heart disease, cancer, and stroke are the leading causes of death, and they account for approximately two-thirds of all deaths (Brownson & Bright, 2004; Brownson, Remington, & Davis, 1998). The shift from infectious to chronic diseases as major causes of premature morbidity and mortality necessitated a shift in theories of prevention. Chronic diseases, in contrast to infectious dis-eases, are characterized by a noncontagious origin, a long period of illness or disability, a prolonged latency period between exposure to the risk factors and negative health outcome, and multiple risk-factor etiology (McKenna, Taylor, Marks, & Koplan, 1998).

Three tenets of this chapter are that (1) a significant proportion of pre-mature morbidity and mortality from chronic disease is preventable; (2) there is a substantial gap between what we can achieve and what we do achieve for disease prevention; and (3) closing this gap may be facilitated by a simple and clearly articulated “health behavior theory of prevention.”

What do we mean by a health behavior theory of prevention? Let’s start with what we mean by theory. First, there is nothing magical or mystical about theory. It is simply a statement about causal relationships. The validity of these causal relationships may or may not be conclusively proven (Deutsch & Krause, 1965). Theories of prevention, therefore, are statements about causal relation-ships between exposures or risk factors and disease incidence (primary pre-vention) and progression (secondary prevention). Given our focus on health behavior, we can narrow this definition further by defining a health behavior theory of prevention as statements about causal relationships between health behaviors and disease incidence and progression.

Prevention theory enhances our work as scientists and practitioners in many ways. Theory helps us build the science of prevention by directing our hypotheses and research questions and informs the selection of appropriate populations to study. Ultimately, theories of prevention determine intervention approaches including individual treatments, models of health care delivery, public health practice, and health policy.

In the years following World War II, epidemiologists began to focus on the etiology of chronic diseases, particularly lung cancer and coronary heart dis-ease (CHD) (Susser, 1985; White, 1990). The epidemiological evidence for an association between cigarette smoking and lung cancer initially received the most attention as a behavioral risk factor, because it posed a challenge to a large and powerful industry that was then perceived to be invulnerable (Glantz, Slade, Bero, Hanauer, & Barnes, 1996; Kluger, 1996). Early studies that suggested this association encountered numerous objections. The objections resulted, in part, from the fact that the conclusions were based on statistical correlations from observational studies, which could never in themselves prove causation,

5Chapter 1 Theories of Prevention

and the fact that cigarette smoking as a single behavior was linked to a large number of chronic disease outcomes (Berkson, 1958; Doll, 1999). However, strong and consistent evidence for the association continued to emerge from laboratory studies and autopsy reports, as well as from observational studies. In 1957, a national scientific study group concluded that there was a causal re-lationship between smoking and cancer (Study Group on Smoking and Health, 1957). However, the tobacco industry and some scientists continued to argue that none of the studies had actually demonstrated a causal relationship. Their response contributed inadvertently to an overdue expansion in methodological rigor in the fields of statistics and epidemiology and a related increase in our understanding of how epidemiologic research can support laboratory studies and clinical research (Cornfield et al., 1959). Ultimately, there was consensus that this groundbreaking research had demonstrated that tobacco use, particu-larly cigarette smoking, causes or contributes to a number of chronic diseases (Parascandola, 2004; Talley, Kushner, & Sterk, 2004; White, 1990).

These first epidemiologic studies conducted in the 1940s and 1950s led an advisory committee to the U.S. Surgeon General to conclude that cigarette smok-ing was a cause of lung and laryngeal cancer and the primary cause of chronic bronchitis (Surgeon General, 1964). This information ultimately culminated in the Surgeon General’s Report on smoking and health and led to a number of advances, including increased research into the development of chronic disease and tobacco use, evaluation of prevention and cessation programs, campaigns to reduce or prevent smoking, and the dissemination of this information to the public (Brownson & Bright, 2004).

On a related but somewhat different pathway, researchers began to think in terms of “risk factors” for the development of coronary heart disease, with the idea that certain behaviors moderated the probability of disease. For example, in the 1940s, the Framingham Heart Study was launched as a major, prospective epidemiological study to determine the major risk factors for heart disease. The study identified six major risk factors, including hypertension, elevated blood lipids, cigarette smoking, sedentary lifestyle, obesity, and diabetes (Bullough & Rosen, 1992). The concept of “risk factors” forced researchers to think of chronic disease as the outcome of multiple factors and required a strategic change in thinking about chronic diseases and their complications as being preventable rather than inevitable (Brownson & Bright, 2004). In other words, a reduction in chronic disease could best be achieved by altering factors that place a person at increased risk. Burgeoning research in this area has led to a better understand-ing of the tremendous influence that certain behaviors can exert upon health.

By 1979 the Surgeon General’s Report on Health Promotion and Disease Prevention noted that an analysis of the 10 leading causes of death in the United States in 1976 indicated that as much as half of mortality was due to unhealthy behavior or lifestyle (U.S. Department of Health Education and Welfare, 1979). The health behavior theory of disease prevention had emerged.

Disease Prevention Through Health Behavior Change

In 1993, McGinnis and Foege published an analysis of the actual causes of death in the United States (McGinnis & Foege, 1993). They showed that tobacco use,


unhealthy diet and activity patterns, and alcohol use are the top three actual causes of death in the United States. Together these health behaviors account for nearly 40% of all deaths. Extrapolating from their data, each hour, we can conclude that as many as 85 Americans die prematurely due to tobacco use, poor nutrition, and inactivity.

In addition to the devastating human costs, the health care costs associated with treating chronic diseases are staggering. The combined total of private, public, and personal dollars spent on health care in the United States is al-most $2 trillion dollars per year, which amounts to more than 15% of our gross domestic product (GDP) (Heffler et al., 2005). No other industrialized nation spends more than 10% of its GDP on health care. Fries and colleagues esti-mated that preventable illnesses were responsible for 70% of all medical care spending, and health insurance claims are higher for individuals with at least one behavioral risk factor than for individuals with no behavioral risk factors (Fries et al., 1993; Millman & Robertson Inc., 1995). Unfortunately, spending all of this money does not lead to better health outcomes. The United States ranks behind 44 other countries in life expectancy and 41 countries in infant mortal-ity (Central Intelligence Agency, 2007). In a recent study, out of 13 countries studied, the United States ranked 12th when compared on 16 health indicators (Starfield, 2000).

Disease prevention is not new, and links between behavior and prevention have been articulated for thousands of years. For example, traditional Chinese medicine’s (TCM) focus on prevention dates back more than 2,500 years and rec-ommends eating healthful foods, engaging in physical labor, and doing breathing exercises (Selin, 2003). More than 2,000 years ago, Hippocrates (c. 460–377 b.c .) taught that “If we could give every individual the right amount of nourishment and exercise, not too little and not too much, we would have found the safest way to health.” The following sections focus on the evidence for three behavioral risk factors for a number of chronic diseases: tobacco use, unhealthy diets, and physical inactivity.

The Top Three Behavioral Risk Factors

Tobacco Use Tobacco use remains the leading cause of preventable morbidity and mortality in the United States and is responsible for more than 30% of all cancer deaths (American Cancer Society, 2005). For the most part, smoking prevalence has declined, but recently there has been a troubling leveling off. Currently, ap-proximately 21% of the adult population, or 45 million adults, smoke cigarettes (American Cancer Society, 2007). Even with the dramatic decline in prevalence from 60% before World War I, tobacco-related diseases still contribute to ap-proximately 440,000 premature deaths each year (American Cancer Society, 2007). Current smokers have 20 times the rate of lung cancer of those who have never smoked (U.S. Public Health Service, Office of the Surgeon General, 1989) The risk of lung cancer among cigarette smokers increases with the duration of smoking, as well as with the number of cigarettes smoked per day (Doll & Peto, 1978). In a model developed by Doll and Peto, duration of smoking increased the probability of disease more than the number of cigarettes smoked per day (Doll


& Peto, 1978). Therefore, individuals who initiate smoking at a young age have a greater likelihood of developing lung cancer than those who started later (U.S. Department of Health and Human Services, 1988). This strongly suggests that approaches that delay the age of onset of smoking in a population or prevent smoking altogether could have a substantial impact on the incidence of lung cancer by shortening the average duration of smoking. That said, numerous studies have also shown that cigarette smokers can derive benefit by quitting at any age (U.S. Public Health Service, Office of the Surgeon General, 1989). And it is clear that the likelihood of developing lung cancer is lower among people who quit smoking than among those who continue to smoke (U.S. Department of Health and Human Services, 1990).

Diet and Nutrition In addition to smoking, it is now widely understood that unhealthful diets and physical inactivity play a significant role in the causation and progression of chronic disease, although the numbers attributable to these causes vary (Cen-ters for Disease Control & National Center for Chronic Disease Prevention and Health Promotion, 2003). The concentrated focus on changes in nutrition and physical activity as avenues to promote heath is relatively recent. Until the 1970s and the hearings held by the U.S. Senate Select Committee on Nutrition and Human Needs, the focus of nutrition policy had been on undernutrition, rather than chronic disease prevention (Brownson, Remington, & Davis, 1998). Since the controversial dietary goals for the United States were published in 1977, numerous scientific papers have supported the relationship between a typical U.S. diet and chronic diseases such as heart disease, cancer, diabetes, and stroke (U.S. Senate Select Committee on Nutrition and Human Needs, 1977) These ef-forts have contributed to improvements in the dietary habits of Americans.

Overall, a diet that includes a large variety of fruits, vegetables, and whole grains has been strongly associated with reductions in coronary heart disease, stroke, and type 2 diabetes (Michels, 2005). However, the results of studies at-tempting to isolate nutritional factors related to cancer prevention have been less compelling (McCullough & Giovannucci, 2004). This may be because spe-cific nutrients do not exert a protective effect in isolation. Protective effects may also depend on dose, timing, and duration of exposure or nutrient status (Kushi et al., 2006). On the other hand, diets low in fat and high in fruits, vegetables, and whole grains are consistent with energy balance and may contribute to a lower body weight (Rolls, Ello-Martin, & Tohill, 2004). An unhealthful diet, over-all, appears to be an independent risk factor for certain chronic diseases but also plays a crucial role in its effect on chronic disease through the influence on the development and maintenance of obesity by altering energy balance (Cen-ters for Disease Control & National Center for Chronic Disease Prevention and Health Promotion, 2003).

Physical Activity and Energy Expenditure Energy expenditure, while also an independent risk factor for certain chronic diseases, is also an important component of energy balance (Hill & Wyatt, 2005). Unfortunately, it is estimated that only 38.5% of adults in the United States meet the national guidelines for physical activity (Simpson et al., 2003). A recent


study found that physically inactive women had a rate of all-cause mortality that was 52% higher than that of physically active women; their risk of cardio-vascular mortality was doubled, and their risk of cancer-related mortality was 29% higher (Hu et al., 2004).

When energy intake is balanced with energy expenditure, body weight re-mains constant. Thus, overweight and obesity can occur when energy intake is greater than energy expenditure for a sustained period of time (Hill & Wyatt, 2005). However, there are gaps in our knowledge about the health risks of obe-sity, and deaths attributable to obesity are difficult to calculate for a variety of reasons. Body mass index (BMI) is influenced by energy intake and energy ex-penditure levels, which may affect health in ways independent of or mediated by BMI. Estimates of the number of deaths attributable to obesity have ranged from 112,000 (Flegal, Graubard, Williamson, & Gail, 2005) to 280,000 (Allison, Fon-taine, Manson, Stevens, & Van Itallie, 1999) to 400,000 (Mokdad, Marks, Stroup, & Gerberding, 2004; Mokdad, Marks, Stroup, & Gerberding, 2005). These dis-parate findings in obesity-attributable deaths underscore the need to develop more sophisticated approaches that could lead to more consistent estimations. Nonetheless, despite the varying estimations, there is no doubt that a decrease in unhealthful dietary and sedentary behavior patterns could translate into a lowering of the elevated risk of morbidity and mortality associated with obesity.

Excess body weight is an independent risk factor for cardiovascular dis-ease, as well as a contributor to other risk factors such as hypertension and type 2 diabetes (Eckel, 1997). Moreover, in 2002, a working group at the Inter-national Agency for Research on Cancer concluded that there was convincing evidence that being overweight (body mass index [BMI] ≥ 25 kg/m 2 ) or obese (BMI ≥ 30 kg/m 2 ) is associated with risk of cancers of the endometrium, colon, and kidney (Calle, Rodriguez, Walker-Thurmond, & Thun, 2003). Recent data also suggest that successful weight loss and the avoidance of adult weight gain could translate into significant reductions in breast cancer rates (Harvie et al., 2005). Calle and colleagues estimated that 90,000 deaths due to cancer could be prevented annually if individuals could achieve and maintain a BMI of 25 kg/m 2 (Calle et al., 2003).

While there is widespread debate as to how individuals can best achieve energy balance, it is clear that the balance between energy intake and energy expenditure through physical activity is a critical component in the mainte-nance of a healthy body weight (Hill & Wyatt, 2005). The consistency of the energy balance message, along with similar messages from the American Heart Association (Mosca et al., 2004; Pearson et al., 2002; Williams et al., 2002), the National Cholesterol Education Program Adult Treatment Panel (Expert Panel on Detection Evaluation and Treatment of High Blood Cholesterol in Adults, 2001), and the American Academy of Pediatrics (Krebs, Jacobson, & the Ameri-can Academy of Pediatrics Committee on Nutrition, 2003) underscores the in-controvertible evidence that the burden of illness today due to chronic disease is, in part, preventable (McGinnis & Foege, 1993).

National Prevention Priorities Because a considerable number of early deaths among Americans could be prevented through modification of behavioral risk factors, there needs to be a


commitment, combined with a comprehensive plan, to make the changes pos-sible (McGinnis & Foege, 1993). Decisions about smoking, level of activity, and dietary intake are fundamentally and intrinsically linked to individual, cultural, environmental, and commercial factors (Ammerman et al., 2003). Therefore, messages related to preventive health care need to address these root causes of chronic disease in a format that can enhance motivation and promote and mon-itor effective action (Ammerman et al., 2003; McGinnis & Foege, 2004). Efforts to set health objectives that can be monitored are a recent phenomenon. A 1978 paper published by the Institute of Medicine (IOM) was the first to establish ob-jectives for public health (Nightingale, Cureton, Kalmar, & Trudeau, 1978). The work of the IOM in this area led to the 1979 Surgeon General’s Report on Health Promotion and Disease Prevention (U.S. Department of Health Education and Welfare Public Health Service, 1979) and culminated in 1990 in the publication of Healthy People 2000 , which contained 22 priority areas and 319 health objec-tives to be achieved by the year 2000 (U.S. Department of Health and Human Services, Public Health Service, 1990). Many of the objectives of Healthy People 2000 were achieved (U.S. Department of Health and Human Services, 2000). However, phenomena such as increasing overweight and obesity rates, as well as an increase in the incidence of diabetes, ultimately led to a set of objectives that focused more specifically on lifestyle behavior change (U.S. Department of Health and Human Services, 2000).

Currently, the U.S. Public Health Service has established two primary health goals for the year 2010: (1) to increase quality and years of health life; and (2) to eliminate health disparities among Americans. In an effort to achieve these goals, the U.S. Public Health Service has published 467 health objectives di-vided into 26 specific areas (U.S. Department of Health and Human Services, 2000). The core of the objectives for Healthy People 2010 is based on the sci-entific evidence documenting the relationship between behavioral risk factors and the development of chronic disease. In fact, 5 of the 10 leading indicators for the health of the nation are health behaviors. The objectives for these be-haviors are quite ambitious and include reducing the prevalence of smoking among adults by 50%, doubling the percentage of adults who engage in regular physical activity, and reducing the proportion of overweight and obese children by at least 50% and the proportion of such adults by 35%.

While there is considerable debate regarding the effectiveness of setting ambitious and, some believe, unachievable goals, there is little doubt that modi-fication of behavioral risk factors will make the largest contribution to reductions in morbidity and mortality from the major diseases. For example, Byers and col-leagues estimated achievable reductions in cancer incidence and mortality rates between 1990 and 2010 (Byers et al., 1999). Overall, 47% of the achievable reduc-tions in cancer incidence and 51% of the achievable reductions in cancer mortal-ity came from reductions in tobacco use. A similar analysis for coronary mortality conducted in the United Kingdom indicates that 44% of achievable reductions would come from reductions in tobacco use (Critchley & Capewell, 2003).

Indeed, over the past few decades, there have been substantial improve-ments in chronic disease morbidity and mortality rates (Strong, Mathers, Leeder, & Beaglehole, 2005). For example, deaths from cardiovascular disease have been reduced significantly (Minino, Heron, & Smith, 2006), and cancer mortality also has declined (Minino et al., 2006). While the reasons for this improvement are


multifaceted, health behavior changes have contributed to the decline, particu-larly adherence to recommendations involving diet, physical activity, and absti-nence from smoking.

In summary, the underlying science is available to support the health be-havior theory of prevention. Over the past several decades, our knowledge of the causes of chronic disease, including effective intervention techniques, has increased exponentially. However, we continue to face challenges in translat-ing preventive health knowledge into improved health (Glasgow, Lichtenstein, & Marcus, 2003). A more rapid translation of scientific results could signifi-cantly reduce the burden of chronic disease, as well as the health disparities in chronic disease that exist for many underserved segments of our population (Kumanyika & Morssink, 2006).

From Theor y to Action

High-Risk and Population-Based Prevention Strategies The previous section highlights evidence for two basic tenets of a health behav-ior theory of prevention: reductions in the prevalence of health risk behaviors are associated with reductions in premature morbidity and mortality (e.g., de-clines in smoking prevalence and decreases in lung cancer and cardiovascular disease), and increases in the prevalence of health risk behaviors are associated with increases in premature morbidity and mortality (e.g., increased weight from unhealthful diets and lack of physical activity and increases in the incidence of type 2 diabetes). Unfortunately, science and practice are not inextricably linked. A fundamental challenge for the health behavior theory of prevention is moving from theory to action, which involves pull-through from research to practice. In this section we consider two types of prevention strategies—high-risk and population-based approaches.

In his seminal book, The Strategy of Preventive Medicine, Geoffrey Rose in-troduces the high-risk approach to prevention in the context of “the prevention paradox,” which he defines as “a preventive measure that brings large benefits to the community offers little to each participating individual” (Rose, 1992). One way to deal with this paradox is to adopt a high-risk strategy that focuses on identifying individuals or groups of individuals known to be at high risk for disease and concentrates prevention and intervention efforts on reversing or reducing their risk level. Individuals with no or mildly elevated risk are es-sentially left alone. Examples of high-risk strategies for behavioral risk-factor modification include tobacco cessation interventions targeted at smokers with genetic markers of susceptibility to lung cancer (e.g., Bize, Burnand, Mueller, & Cornuz, 2005), diet and physical activity interventions targeted to nondiabetic individuals with elevated blood glucose and body mass indices greater than 25 (e.g., Diabetes Prevention Research Group, 2002), and interventions to increase compliance with mammography screening targeted at women with a family his-tory of breast cancer (e.g., Curry, Taplin, Barlow, Anderman, & McBride, 1993). Appealing aspects of a high-risk approach to prevention include its practica-bility, appropriateness, cost-effectiveness, and potentially high benefit-to-risk ratio. Wilson and Jungner elaborated these advantages 40 years ago and noted


that targeting interventions to clearly identified high-risk individuals can be easily integrated into the current organization and culture of health care, pro-vides a cost-effective use of resources, provides interventions that are appro-priate to the individual, and avoids “interference” with those who are not at special risk (Wilson & Jungner, 1968). Moreover, because all interventions bring some costs and possible adverse effects, the benefit-to-risk ratio for prevention interventions is likely to be higher in populations where the potential benefits are greatest.

The prospective advantages of a high-risk prevention strategy are tempered by several potential limitations. Wilson and Junger raise concerns that if preven-tion becomes “medicalized,” there may be negative effects on individuals who are “labeled” and that high-risk strategies focus primarily on individuals and so can fail to address key contextual determinants of risk factors and/or diseases. As a result, the high-risk approach can “isolate” high-risk individuals by asking them to adopt behaviors that have minimal social and environmental supports. Most important is their observation, echoed by many others, that the high-risk approach is limited by imprecise prediction; most risk, including behavioral risk, is probabilistic, not deterministic. This means that some (even many) “high-risk” individuals will stay well and that some low-risk individuals will get sick. Rose aptly summarizes the implications of imprecise risk as a fundamental axiom of preventive medicine: “A large number of people exposed to a small risk may generate many more cases than a small number exposed to a high risk.” He further notes that in the context of this axiom a high-risk prevention strategy would be addressing only the margins of the problem (Rose, 1992).

The information in Table 1.1 helps to illustrate this axiom and the potential limitations of a high-risk prevention strategy. These are data for men aged 40 to 59 years who were screened for risk factors related to myocardial infarction (MI), as well as for the presence of early disease. The second column of the table indicates that among all men in this group, 15% were found to have elevated risk factors and 2% were found to have elevated risk factors plus early disease. Thus, 85% of the population would be considered risk-free. The third column shows the percentage of men who had an MI in the 5 years following screening. Among those with elevated risk factors and early disease, nearly one-quarter,

1.1 5-Year Myocardial Infarction (MI) Risk and Risk Factors

Screening Result % of men % with MI% of all MIs in

this group

All men 100 4 100Elevated risk factors 15 7 32Elevated risk factors +

early disease 2 22 12

Note. From The Strategy of Preventive Medicine, by G. Rose, 1992, p. 50. New York: Oxford University Press. Copyright 1999 by Oxford University Press. Reprinted with permission.


22%, of them had an MI, whereas 7% of those with only elevated risk factors had an MI. Across the entire population of men, there was a 4% incidence of MI. The last column of the table shows the percentage of all MIs that are accounted for by those in the elevated-risk categories; 32% of all MIs occurred among men with elevated risk factors, and 12% occurred among those with elevated risk factors and early disease.

Thus, the majority of MIs (~68%) occurred in men with no known risk fac-tors. These data lead to two important observations. First, even among men with elevated risk factors, the majority did not have MIs (93% and 78%, respectively). Second, a high-risk prevention approach, even if 100% successful, would pre-vent only one-third of all future MIs.

As the name implies, a population-based approach to prevention targets all individuals, regardless of risk status, with the goal of shifting the entire risk factor distribution in a positive direction. In many ways, the strengths and limi-tations of a population-based prevention strategy are the mirror image of those outlined for the high-risk approach. On the plus side, population-based pre-vention takes a less “medical-model” approach and includes social, organiza-tional, environmental, and policy strategies that change the context and social norms for individual change. Conversely, a population-based strategy may be less cost-effective; since resources are allocated for a much broader spectrum of the population, it may fail to leverage the resources and influence of the health care system, and, by exposing more individuals to interventions with potential adverse effects, may have a smaller overall benefit-to-risk ratio (cf. Jeffery, 1989; Lichtenstein & Glasgow, 1992). In essence, a population-based prevention strat-egy brings us to a fundamental question derived from the prevention paradox: will moderate and achievable change in the population as a whole lead to re-ductions in the prevalence and negative consequences of disease?

With regard to behavioral risk factors, Rose points out that this question can be addressed by observing the correlation between the population average and the prevalence of deviance (Rose & Day, 1990). Population averages can be cal-culated without the “outliers” to reduce the influence of extreme values (which determine the prevalence of deviance) on the observed associations. Using data from a large, longitudinal cohort study, Rose reports correlations between the prevalence of high blood pressure and population averages of salt intake, weight, and alcohol intake that range from .64 to .78. Extrapolating further, he calculates the expected reduction in the prevalence of risk factors associated with changes in the population average. For example, Rose calculated a 25% reduction in the prevalence of obesity with an average loss of 1 kg (2.25 lbs) in the population and a 25% drop in the prevalence of heavy drinking if the aver-age intake of all drinkers fell by 10% (Rose, 1992, p. 65). These data lend support to population-based approaches to behavioral risk factor modification that aim for modest changes across a broad spectrum of individuals.

Of course, high-risk and population-based approaches are not mutually ex-clusive. Optimal health outcomes through behavioral risk-factor modification are more likely to be achieved by the two approaches combined. Moreover, as definitions of risk and disease are modified to encompass larger proportions of the general population, the distinction may become increasingly blurred. The trend toward defining “pre-disease” (e.g., prehypertension, prediabetes) as well as toward lowering diagnostic thresholds (e.g., hypercholesterolemia, type 2


diabetes, overweight, and obesity) results in a decrease in the proportion of the population defined as “well” (Kaplan, 2005). One estimate is that lower thresh-olds for hypercholesterolemia, hypertension, type 2 diabetes, and overweight would result in fully 75% of the entire U.S. adult population qualifying for a chronic disease diagnosis (Kaplan, Ganiats, & Frosch, 2004). Given the com-mon pathway of health behaviors as important for both the prevention and the management of chronic disease, we can see that the population and high-risk approaches may very well converge.

Health Behavior Theory of Prevention and Emerging Paradigms of Disease Prevention Thought leaders in health psychology point to the need for health psycholo-gists to “look beyond current concepts and methods in prevention science” to achieve the considerable potential of health psychology, which includes health behavior theory (Smith, Orleans, & Jenkins, 2004). Dr. Elias Zerhouni, Director of the National Institutes of Health, presents a vision for the future of NIH in the context of the “4 Ps” of medicine that “will be more predictive, personalized, preemptive, and participatory” (Zerhouni, 2006; Zerhouni, 2007). Dr. Zerhouni describes a transformation of the health care process in which there is a “con-tinuous participation of individuals, communities, and healthcare institutions as early as possible in the natural cycle of a disease process.” By identifying bio-markers (e.g., genetic variants, molecular changes, individual-level measures of environmental exposures) that are predictive of later development of seri-ous disease, the vision is for biological “preemption” of disease before it occurs. Notably absent in this vision is any explicit attention to prevention beyond the level of individual biology (Glasgow, Fisher, Haire-Joshu, & Goldstein, 2007).

What we can see in this vision is a merging of the population and high-risk approaches to prevention. In essence, all individuals become “high risk” as they are monitored throughout the life cycle for “predisease,” and the indicators of predisease will largely be at the molecular level. However, behavior will still play a large role in the translation and adoption of biomedical advances, par-ticularly as associations between molecular markers of disease and known en-vironmental factors are articulated. Moreover, the predictive, personalized, and preemptive vision raises a number of key questions that an expanded health behavior model of prevention can address (cf. McBride, 2005). At what point in the life span should intensive screening for biomarkers of disease begin? What are the criteria for determining the value of a biomarker in formulating a prevention strategy at the individual level? Important considerations include issues of sensitivity and specificity of a biomarker in predicting future disease, the potential for detecting “pseudodisease” (i.e., markers of disease that do not affect overall life expectancy and quality of life; Black & Welch, 1997), and the availability of proven preventive interventions and their risk-benefit profiles (cf. Mahadevia, Kamanger, & Samet, 2003). How can we communicate com-plex biomedical information to individuals with average to low health literacy? What are the psychological consequences of looking for markers of predisease and of finding “false positive” indications? Will individuals avoid the health care system for fear of being labeled “at risk” and losing health coverage, em-ployment opportunities, and so on? Will more precise feedback on the risk of


serious disease result in meaningful reductions in behavioral risk factors? Will this expanded medical model of disease prevention overload the medical sys-tem logistically and financially?

None of these are new questions; they are critical issues for effective transla-tion from theory practice. It is notable that even with our rich scientific evidence that behavioral risk factors contribute substantially to premature morbidity and mortality, that improvements in rates of heart disease and cancer are inextri-cably linked to reductions in tobacco use, and that the increased prevalence of type 2 diabetes is associated with increased rates of overweight and obesity, the biomedical community has not embraced the health behavior theory of disease prevention. There is a wide translational gap between what we as a society can do and what we actually do to address behavioral risk factors (Curry, 2004). Our health behavior research is often “chasing the bus” of new knowledge, for exam-ple, trying to understand why individuals fail to obtain recommended screening tests or how to better achieve successful behavior change. Accelerated transla-tion of findings from these emerging prevention paradigms will occur only if the theory, science, practice, and policy related to a health behavior theory of prevention are an integral part of the transdisciplinary collaboration for actual-izing this new vision.

References Allison, D. B., Fontaine, K. R., Manson, J. E., Stevens, J., & Van Itallie, T. B. (1999). Annual deaths

attributable to obesity in the United States. Journal of the American Medical Association, 282, 1530–1580.

American Cancer Society. (2005). Cancer facts and figures, 2005. Atlanta: American Cancer Society.

American Cancer Society. (2007). Cancer facts & figures, 2007. Atlanta: American Cancer Society.

Ammerman, A., Corbie-Smith, G., St. George, D. M., Washington, C., Weathers, B., & Jackson-Christian, B. (2003). Research expectations among African American church leaders in the PRAISE! project: A randomized trial guided by community-based participatory research. American Journal of Public Health, 93, 1720–1727.

Berkson, J. (1958). Smoking and lung cancer: Some observations on two recent reports. Journal of the American Statistical Association, 53, 28–38.

Bize, R., Burnand, B., Mueller, Y., & Cornuz, J. (2005). Biomedical risk assessment as an aid for smoking cessation. Cochrane Database of Systematic Reviews, 4, CD004705.

Black, W. C., & Welch, H. G. (1997). Screening for disease. American Journal of Roentgenol, 168 (January), 3–11.

Brownson, R. C., & Bright, F. S. (2004). Chronic disease control in public health practice: Look-ing back and moving forward. Public Health Reports, 119, 230–238.

Brownson, R. C., Remington, P. L., & Davis, J. R. (Eds.). (1998). Chronic disease epidemiology and control (2nd ed.). Washington, DC: American Public Health Association.

Bullough, B., & Rosen, G. (1992). Preventive medicine in the United States: 1900–1990: Trends and interpretations. Canton, MA: Watson Publishing International.

Byers, T., Mouchawar, J., Marks, J., Cady, B., Lins, N., Swanson, G. M., et al. (1999). The American Cancer Society challenge goals. How far can cancer rates decline in the U.S. by the year 2015? Cancer, 5 , 715–727.

Calle, E. E., Rodriguez, C., Walker-Thurmond, K., & Thun, M. J. (2003). Overweight, obesity, and mortality from cancer in a prospectively studied cohort of U.S. adults. New England Journal of Medicine, 348, 1625–1638.

Centers for Disease Control & National Center for Chronic Disease Prevention and Health Promotion. (2003). Physical activity and good nutrition: Essential elements to prevent chronic diseases and obesity 2003. Nutrition in Clinical Care, 6, 135–138.


Central Intelligence Agency. (2007). The world factbook. Retrieved April 20, 2007, from https://www.cia.gov/cia/publications/factbook/index.html

Cornfield, J., Haenszel, W., Hammond, W., Lilienfeld, E., Shimkin, A., & Synder, E. (1959). Smok-ing and lung cancer: Recent evidence and a discussion of some questions. Journal of the National Cancer Institute, 22, 173–201.

Critchley, J. A., & Capewell, S. (2003). Substantial potential for reductions in coronary heart disease mortality in the U.K. through changes in risk factor levels . Journal of Epidemiology and Community Health, 57 (4), 243–247.

Curry, S. J. (2004). Toward a public policy agenda for addressing multiple health risk behaviors in primary care. American Journal of Preventive Medicine, 27(2 Suppl), 106–108.

Curry, S., Taplin, S., Barlow, W., Anderman, C., & McBride, C. (1993) A randomized trial of the impact of risk assessment and feedback on participation in mammography screening. Preventive Medicine, 22 (3), 350–360.

Deutsch, M., & Krause, R. M. (1965). Theories in social psychology. New York: Basic Books. Diabetes Prevention Research Group. (2002). Reduction in the incidence of type 2 diabetes with

lifestyle intervention or metformin. New England Journal of Medicine, 346 (6), 393–403. Doll, R. (1999). Tobacco: A medical history. Journal of Urban Health, 76, 289–313. Doll, R., & Peto, R. (1978). Cigarette smoking and bronchial carcinoma: Dose and time relation-

ships among regular smokers and lifelong non-smokers. Journal of Epidemiology & Com-munity Health, 32, 303–313.

Eckel, R. H. (1997). Obesity and heart disease: A statement for healthcare professionals from the Nutrition Committee, American Heart Association. Circulation, 96, 3248–3250.

Expert Panel on Detection Evaluation and Treatment of High Blood Cholesterol in Adults. (2001). Executive Summary of the Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). Journal of the American Medical As-sociation, 285, 2486–2497.

Flegal, K. M., Graubard, B. I., Williamson, D. F., & Gail, M. H. (2005). Excess deaths associated with underweight, overweight, and obesity. Journal of the American Medical Association, 293, 1861–1867.

Fries, J. F., Koop, C. E., Beadle, C. E., Cooper, P. P., England, M. J., Greaves, R. F., et al. (1993). Reducing health care costs by reducing the need and demand for medical services. The Health Project Consortium. New England Journal of Medicine, 329, 321–325.

Glantz, S. A., Slade, J., Bero, L., Hanauer, P., & Barnes, D. (1996). The cigarette papers. Berkeley: University of California Press.

Glasgow, R. E., Fisher, E. B., Haire-Joshu, D., & Goldstein, M. G. (2008). NIH science agenda: A public health perspective. American Journal of Public Health, 97, 1936–1938.

Glasgow, R. E., Lichtenstein, E., & Marcus, A. C. (2003). Why don’t we see more translation of health promotion research to practice? Rethinking the efficacy-to-effectiveness transi-tion. American Journal of Public Health, 93, 1261–1267.

Harvie, M., Howell, A., Vierkant, R. A., Kumar, N., Cerhan, J. R., Kelemen, L. E., et al. (2005). Association of gain and loss of weight before and after menopause with risk of postmeno-pausal breast cancer in the Iowa women’s health study. Cancer Epidemiology Biomarkers and Prevention, 14, 656–661.

Heffler, S., Smith, S., Keehan, S., Borger, C., Clemens, M. K., & Truffer, C. (2005). U.S. health spending projections for 2004–2014. Health Affairs (January–June), Suppl. Web Exclusives:W5-74–W5-85.

Hill, J. O., & Wyatt, H. R. (2005). Role of physical activity in preventing and treating obesity. Journal of Applied Physiology, 99, 765–770.

Hu, F. B., Willett, W. C., Li, T., Stampfer, M. J., Colditz, G. A., & Manson, E. (2004). Adiposity as compared with physical activity in predicting mortality among women. New England Jour-nal of Medicine, 351, 2694–2703.

Jeffery, R. W. (1989). Risk behaviors and health: Contrasting individual and population perspec-tives. American Psychologist, 44 (9), 1194–1202.

Kaplan, R. M. (2005). Screening for cancer: Are resources being used wisely? Recent Results in Cancer Research, 166, 315–334.

Kaplan, R. M., Ganiats, T. G., & Frosch, D. L. (2004). Diagnostic and treatment decisions in U.S. healthcare. Journal of Health Psychology, 9 (1), 29–40.


Kluger, R. (1996). Ashes to ashes, America’s hundred-year cigarette war, the public health and the unabashed triumph of Philip Morris. New York: Vintage Books.

Krebs, N. F., Jacobson, M. S., & the American Academy of Pediatrics Committee on Nutrition. (2003). Prevention of pediatric overweight and obesity. Pediatrics, 112, 424–430.

Kumanyika, S. K., & Morssink, C. B. (2006). Bridging domains in efforts to reduce disparities in health and health care. Health Education & Behavior, 33, 440–458.

Kushi, L. H., Byers, T., Doyle, C., Bandera, E. V., McCullough, M., McTiernan, A., et al. (2006). American Cancer Society 2006 Nutrition and Physical Activity Guidelines Advisory Com-mittee. American Cancer Society Guidelines on Nutrition and Physical Activity for cancer prevention: Reducing the risk of cancer with healthy food choices and physical activity. CA: A Cancer Journal for Clinicians, 56, 254–281.

Lichtenstein, E., & Glasgow, R. E. (1992). Smoking cessation: What have we learned over the past decade? Journal of Consulting and Clinical Psychology, 60 (4), 518–527.

Mahadevia, P. J., Kamangar, F., & Samet, J. (2003). Background paper for chapter 7, Adopting new technology in the face of uncertain science: The case of screening for lung cancer. In S. J. Curry, T. Byers, & M. Hewitt (Eds.), Fulfilling the potential for cancer prevention and early detection . Washington, DC: National Academies Press.

McBride , C. M. (2005). Blazing a trail: A public health research agenda in genomics and chronic disease. Prevention of Chronic Disease . Retrieved April 16, 2007, from http://www.cdc.gov/pcd/ issues/2005/apr/05_008.htm

McCullough, M. L., & Giovannucci, E. L. (2004). Diet and cancer prevention. Oncogene, 23, 6349–6364.

McGinnis, J. M., & Foege, W. H. (1993). Actual causes of death in the United States [see com-ments]. Journal of the American Medical Association, 270, 2207–2212.

McGinnis, J. M., & Foege, W. H. (2004). The immediate vs. the important. Journal of the American Medical Association, 291, 1263–1264.

McKenna, M. T., Taylor, W. R., Marks, J. S., & Koplan, J. P. (1998). Current issues and challenges in chronic disease control. In R. C. Brownson, P. L. Remington, & J. R. Davis (Eds.), Chronic disease epidemiology and control (2nd ed., pp. 1–26). Washington, DC: American Public Health Association.

Michels, K. B. (2005). The role of nutrition in cancer development and prevention. International Journal of Cancer, 114, 163–165.

Millman & Robertson Inc. (1995). Health risks and their impact on medical costs. Minneapolis, MN: Millman & Robertson Inc.

Minino, A. M., Heron, M. P., & Smith, B. L. (2006). Deaths: Preliminary data for 2004. National Vital Statistics Reports, 54, 1–49.

Mokdad, A. H., Marks, J. S., Stroup, D. F., & Gerberding, J. L. (2004). Actual causes of death in the United States, 2000. Journal of the American Medical Association, 291, 1238–1245.

Mokdad, A. H., Marks, J. S., Stroup, D. F., & Geberding, J. L. (2005). Correction: Actual causes of death in the United States, 2002. Journal of the American Medical Association, 293 (3), 293–294.

Mosca, L., Appel, L. J., Benjamin, E. J., Berra, K., Chandra-Strobos, N., Fabunmi, R. P., et al. (2004). Evidence-based guidelines for cardiovascular disease prevention in women. Cir-culation, 109, 672–693.

National Center for Health Statistics. (2006). Health, United States, 2006 with chartbook on trends in the health of Americans. Hyattsville, MD: National Center for Health Statistics.

Nightingale , E. O., Cureton, M., Kalmar, V., & Trudeau, M. B. (1978). Perspectives on health pro-motion and disease prevention in the United States. Washington DC: National Academy of Sciences (staff paper).

Parascandola, M. (2004). Two approaches to etiology: The debate over smoking and lung cancer in the 1950s. Endeavour, 28, 81–86.

Pearson, T. A., Blair, S. N., Daniels, S. R., Eckel, R. H., Fair, J. M., Fortmann, S. P., et al. (2002). AHA guidelines for primary prevention of cardiovascular disease and stroke: 2002 update: Con-sensus panel guide to comprehensive risk reduction for adult patients without coronary or other atherosclerotic vascular diseases. American Heart Association Science Advisory and Coordinating Committee. Circulation, 106, 388–391.

Public Health Service. (1964). Smoking and health: Report of the advisory committee to the Sur-geon General of the Public Health Service. Washington, DC: Public Health Service (DHEW publication no. PHS 64–1103).


Rolls, B. J., Ello-Martin, J. A., & Tohill, B. C. (2004). What can intervention studies tell us about the relationship between fruit and vegetable consumption and weight management? Nutrition Reviews, 62, 1–17.

Rose, G. (1992). The strategy of preventive medicine. New York: Oxford University Press. Rose, G., & Day, S. (1990). The population mean predicts the number of deviant individuals.

British Medical Journal, 301, 1031–1034. Selin, H. (Ed.). (2003). Medicine across cultures: History and practice of medicines in non-

Western cultures. Dordrecht: Kluwer Academic Publishers. Simpson, M. E., Serdula, M., Galuska, D. A., Gillespie, C., Donehoo, R., Macera, C., et al. (2003).

Walking trends among U.S. adults: The Behavioral Risk Factor Surveillance System, 1987–2000. American Journal of Preventive Medicine, 25, 95–100.

Smith, T. W., Orleans, C. T., & Jenkins, C. D. (2004). Prevention and health promotion: Decades of progress, new challenges, and an emerging agenda. Health Psychology, 23 (2), 126–131.

Starfield, B. (2000). Is U.S. health really the best in the world? [Editorial] Journal of the Ameri-can Medical Association, 284 (4), 483–485.

Strong, K., Mathers, C., Leeder, S., & Beaglehole, R. (2005). Preventing chronic diseases: How many lives can we save? Lancet, 366, 1578–1582.

Study Group on Smoking and Health. (1957). Smoking and health. Science, 125, 1129–1133. Surgeon General. (1964) . Smoking and health. Report of the Advisory Committee to the Surgeon

General of the Public Health Service. Retrieved March 9, 2007, from http://profiles.nlm.nih.gov/NN/B/C/X/B/

Susser, M. (1985). Epidemiology in the United States after World War II: The evolution of tech-nique. Epidemiologic Reviews, 7, 147–177.

Talley, C., Kushner, H. I., & Sterk, C. E. (2004). Lung cancer, chronic disease epidemiology, and medicine, 1948–1964. Journal of the History of Medicine & Allied Sciences, 59, 329–374.

U.S. Department of Health and Human Services. (1988) . The health consequences of smoking: Nicotine addiction: A report of the Surgeon General, 1988. Retrieved March 9, 2007, from http://profiles.nlm.nih.gov/NN/B/B/Z/D/

U.S. Department of Health and Human Services. (1990) . The health benefits of smoking cessa-tion: A report of the Surgeon General. Retrieved March 9, 2007, from http://profiles.nlm.nih.gov/NN/B/B/C/T/

U.S. Department of Health and Human Services. (2000). Healthy People 2010. Washington, DC: Author.

U.S. Department of Health and Human Services, Public Health Service. (1990). Healthy People 2000 (No. DHHS Publication No. PHS 91-50212). Washington, DC: Author.

U.S. Department of Health, Education, and Welfare, Public Health Service. (1979). Healthy People: The Surgeon General’s report on health promotion and disease prevention. Re-trieved March 9, 2007, from http://profiles.nlm.nih.gov/NN/B/B/G/K/_nnbbgk.pdf

U.S. Public Health Service, Office of the Surgeon General . (1989). Reducing the health con-sequences of smoking: 25 years of progress: a report of the Surgeon General. Retrieved March 9, 2007, from http://profiles.nlm.nih.gov/NN/B/B/X/S/

U.S. Senate Select Committee on Nutrition and Human Needs. (1977). Dietary goals for the United States.

White, C. (1990). Research on smoking and lung cancer: A landmark in the history of chronic disease epidemiology. Yale Journal of Biology and Medicine, 63, 29–46.

Williams, C. L., Hayman, L. L., Daniels, S. R., Robinson, T. N., Steinberger, J., Paridon, S., et al. (2002). Cardiovascular health in childhood: A statement for health professionals from the Committee on Atherosclerosis, Hypertension, and Obesity in the Young (AHOY) of the Council on Cardiovascular Disease in the Young, American Heart Association. Circulation, 106, 143–160.

Wilson, J. M. G., & Jungner, G. (1968). The principles and practice of screening for disease. WHO Public Health Papers 34. Geneva: World Health Organization.

Zerhouni, E. A. (2006). NIH in the post-doubling era: Realities and strategies. Science, 314 (5802), 1088–1090.

Zerhouni, E. A. (2007). FY2008 Director ’ s Budget Request Statement, March 6, 2007. U.S. De-partment of Health & Human Services, National Institutes of Health. Retrieved April 13, 2007, from http://www.nih.gov/about/director/budgetrequest/fy2008directors budgetrequest.htm

edition the handbook of health behavior...

Documents