Hap baker range carroll county landfill

Claudia F. Parvanta, PhD Professor

Director, Florida Prevention Research Center College of Public Health

University of South Florida Tampa, Florida

Sarah Bauerle Bass, PhD, MPH Associate Professor

Director, Risk Communication Laboratory Department of Social and Behavioral Sciences

College of Public Health Temple University

Philadelphia, Pennsylvania

Health Communication

Strategies and Skills for a New Era

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Library of Congress Cataloging-in-Publication Data Names: Parvanta, Claudia F., author. | Bass, Sarah Bauerle, author. Title: Health communication: strategies and skills for a new era / Claudia Parvanta, Sarah Bauerle Bass. Description: Burlington, Massachusetts: Jones & Bartlett Learning, [2020] | Includes bibliographical references and index. Identifiers: LCCN 2018009707 | ISBN 9781284065879 (pbk.) Subjects: | MESH: Health Communication | Health Education Classification: LCC RA423.2 | NLM WA 590 | DDC 362.101/4—dc23 LC record available at https://lccn.loc.gov/2018009707

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Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix Case Study Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . xi Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .xv About the Authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xvii

Chapter 1 Your World, Your Health . . . . . . . . . . 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Major Factors Affecting Health Outcomes . . . . . . . . . . . 1 Socially Defined You . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 How to Change This Picture . . . . . . . . . . . . . . . . . . . . . . . .14 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18 Key Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18 Chapter Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18

Chapter 2 Communication 101: What’s Health Got to Do with It? . . . . . . . . 21

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .21 Communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .21 Communicating About Health . . . . . . . . . . . . . . . . . . . . .26 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .34 Key Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .34 Chapter Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .34 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .34

Chapter 3 Getting It Right: Words, Numbers, and Meaning . . . . . . . . . 37

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .37 Health Literacy Basics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .39 What Creates Good or Poor Health Literacy? . . . . . . .40 Determinants of Health Literacy . . . . . . . . . . . . . . . . . . .42 Tools to Enhance Health Literacy . . . . . . . . . . . . . . . . . . .49 Developing and Assessing Materials . . . . . . . . . . . . . . .51 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .57 Key Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .58 Chapter Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .58 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .58

Appendix 3A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .61 Appendix 3B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .65 Appendix 3C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .67

Chapter 4 Health Communication Practice Strategies and Theories . . . . . . . . . 69

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .69 Core Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .70 Selecting a Practice Strategy: The Behavioral

Economics of Choice . . . . . . . . . . . . . . . . . . . . . . . . . . . .70 Working with Theory in Health

Communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .73 Theory Used to Guide Informing . . . . . . . . . . . . . . . . . . .73 Theory Used to Persuade . . . . . . . . . . . . . . . . . . . . . . . . . .75 Applying Theory to Practice Strategies . . . . . . . . . . . . .78 Media Channel Selection . . . . . . . . . . . . . . . . . . . . . . . . . .81 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .82 Key Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .82 Chapter Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .82 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .82

Chapter 5 Creating Meaningful Health Communication . . . . . . . . . . . . . . . . 85

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .85 Understanding Your Audience . . . . . . . . . . . . . . . . . . . . .85 McGuire’s Hierarchy of Effects . . . . . . . . . . . . . . . . . . . . . .91 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 Key Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 Chapter Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 Appendix 5A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102

Chapter 6 Media and Communication Channel Selection and Planning: The Plot Thickens . . . . 107

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 The Big Media Picture . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108

Contents

vi Contents

Communication Channels . . . . . . . . . . . . . . . . . . . . . . . 108 Communication Channel Selection . . . . . . . . . . . . . . 121 A Final Word: How Media Use and Health

Disparities Are Related . . . . . . . . . . . . . . . . . . . . . . . . . 122 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 Key Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 Chapter Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 Appendix 6A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 Appendix 6B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130 Appendix 6C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136 Appendix 6D . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141

Chapter 7 Planning Health Communication Interventions . . . . . . . . . . . . . . . . . 149

Introduction: Form, Storm, Norm, or Inform? . . . . . 149 The Planning Cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152 Planning Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 Formative Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154 Ok, Now What? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 From the Creative Brief to Concepts, Messages,

and Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 Next? Choosing Settings and Channels . . . . . . . . . . 166 Final Thoughts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 Key Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 Chapter Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 Appendix 7A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 Appendix 7B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180 Appendix 7C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 Appendix 7D . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189 Appendix 7E . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192

Chapter 8 Implementation and Evaluation . . . . . . . . . . . . . . . . . . . 201

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201 Preparing a Logic Model . . . . . . . . . . . . . . . . . . . . . . . . . 202 Final Strategy Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 208 Production and Dissemination Factors . . . . . . . . . . . 210 The Implementation Plan . . . . . . . . . . . . . . . . . . . . . . . . 211 Monitoring and Evaluating Your Program . . . . . . . . 220

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229 Key Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233 Chapter Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233 Appendix 8A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234

Chapter 9 Communication in the Healthcare Setting . . . . . . . . . . . . 241

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241 Effective Interpersonal Communication . . . . . . . . . . 241 Communication Strategies for Difficult

Conversations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 250 Competent Cross-Cultural Communication . . . . . . 252 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255 Key Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255 Chapter Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 256

Chapter 10 School Health . . . . . . . . . . . . . . . 259 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 259 Schools Are a Logical Site for Health

Communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 259 Leading Health Issues and the Youth Risk

Behavior Surveillance System . . . . . . . . . . . . . . . . . . 261 Promoting Movement and Physical Activity in

All Academic Classrooms . . . . . . . . . . . . . . . . . . . . . . 263 Systems Approaches to Promoting Health in

Schools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265 National Initiatives to Support Health Promotion

for Students . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 268 Resources for School-Based Health Promotion . . . 269 Health Communication Specialists in Schools . . . . 271 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271 Key Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271 Chapter Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 272

Chapter 11 Workplace Health . . . . . . . . . . . . 275 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275 Why Workplace Health? . . . . . . . . . . . . . . . . . . . . . . . . . . 276 A Word About Terminology . . . . . . . . . . . . . . . . . . . . . . 276 Evolution of Workplace Health Programs . . . . . . . . . 277

Contents vii

Setting the Stage: The Relationship Between Health Insurance and Workplace Health Programs . . . . . . . . . . . . . . . . . . . 279

Common Workplace Health Program Elements: Where We Are with Workplace Health . . . . . . . . . . 281

Diabetes, Tobacco, and Physical Activity . . . . . . . . . . 282 Stress in the Workplace . . . . . . . . . . . . . . . . . . . . . . . . . . 282 Health Coaching . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 286 Tools and Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . 286 Emerging Trends: Where Workplace

Health Is Going . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 289 Creating a Culture of Health Within

the Workplace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 292

Return on Investment . . . . . . . . . . . . . . . . . . . . . . . . . . . 296 Conclusion: The Work–Health Connection . . . . . . . 297 Key Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 297 Chapter Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 298 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 298 Appendix 11A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 301 Appendix 11B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 303 Appendix 11C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 307

Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 309 Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 317

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The authors of chapters not written solely by the lead authors are listed below in alphabetical order.

Linda Fleisher, PhD, MPH, is a Senior Scientist at the Research Institute at the Children’s Hospital of Philadelphia. She is also adjunct faculty at Fox Chase Cancer Center and Perelman School of Medicine at University of Pennsylvania in Philadelphia. Dr. Fleisher is co-author of Chapter 6.

Heather Gardiner, PhD, MPH, is Associate Professor and Director of the Health Disparities Laboratory in the Department of Social and Behavioral Sciences at Temple University, College of Public Health. Dr. Gardiner is author of Chapter 9.

Alesha Hruska, MPH, MS, MCHES, is Adjunct Instructor at the University of the Sciences, Department of Behavioral and Social Sciences. Ms. Hruska is co-author of Chapter 11.

Laurie Maurer, PhD, MA, recently completed her doctoral studies at Temple University in the Department of Social and Behavioral Sciences, College of Public Health and was a Research Assistant in the Risk Communication Laboratory. Dr. Maurer is co-author of Chapter 5.

Elisa Beth McNeill, PhD, MS, is Clinical Associate Professor and Coordinator of Health and Physical Education Teacher Certification in the Department of Health and Kinesiology at Texas A&M University. Dr. McNeill is author of Chapter 10.

Jeannine L. Stuart, PhD, is President of AREUFIT Health Services, Inc., in West Chester, Pennsylvania. Dr. Stuart is co-author of Chapter 11.

Contributors

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Authors of case studies that appear in chapter boxes or appendices are listed below in the order in which their case material first appears in the book.

Appendix 3A: Use of Patient Activation Tool (PAT) for Shared Decision Making in Pediatric Appendicitis

Dani O. Gonzalez, MD Center for Surgical Outcomes Research, The Research Institute, Nationwide Children’s Hospital, Columbus, Ohio Department of Surgery, Icahn School of Medicine at Mount Sinai, New York, New York

Katherine J. Deans, MD, MHSc Center for Surgical Outcomes Research, The Research Institute, Nationwide Children’s Hospital, Columbus, Ohio Department of Pediatric Surgery, Nationwide Children’s Hospital, Columbus, Ohio

Peter C. Minneci, MD, MHSc Center for Surgical Outcomes, The Research Institute at Nationwide Children’s Hospital, Columbus, Ohio

Appendix 5A: Demographic and Behavioral Target- ing to Encourage Colonoscopy in Low-Literacy Afri- can Americans

Thomas F. Gordon, PhD Professor, Department of Psychology, University of Massachusetts-Lowell, Lowell, Massachusetts

Box 6-3: Reaching Adolescents for HPV Immuniza- tion Using Facebook

Salini Mohanty, DrPH, MPH University of Pennsylvania, Philadelphia, Pennsylvania

Emily Gibeau, MPH Pennsylvania Department of Health, Harrisburg, Pennsylvania

Ayla Tolosa-Kline, MPH Philadelphia Department of Public Health, Philadelphia, Pennsylvania

Caroline Johnson, MD Philadelphia Department of Public Health, Philadelphia, Pennsylvania

Appendix 6A: Los Angeles County’s Sugar Pack Health Marketing Campaign

Noel Barragan, MPH Chronic Disease and Injury Program, Department of Public Health, Los Angeles County Health Agency, Los Angeles, California

Tony Kuo, MD, MSHS Chronic Disease and Injury Program, Department of Public Health, Los Angeles County Health Agency, Los Angeles, California

Appendix 6B: Text4baby as a Surveillance/Informa- tion Dissemination Tool During Zika Outbreak

Jodie Fishman, MPH, MCHES Zero to Three, Washington, DC

Appendix 6C: The Use of Virtual Worlds in Health Promotion

Joan E. Cowdery, PhD Michigan University, Ypsilanti, Michigan

Sun Joo (Grace) Ahn, PhD Grady College of Journalism & Mass Communication, University of Georgia, Athens, Georgia

Case Study Contributors

xii Case Study Contributors

Appendix 6D: Health Promotion and Social Change Through Storytelling Across Communica- tion Platforms

Hua Wang, PhD, MA University of Buffalo, Buffalo, New York

Arvind Singhal, PhD The University of Texas at El Paso, El Paso, Texas

Appendix 7A: Using PhotoVoice in Formative Research

Rickie Brawer, PhD, MPH Thomas Jefferson University, Philadelphia, Pennsylvania

Ellen J. Plumb, MD Thomas Jefferson University, Philadelphia, Pennsylvania

Melissa Fogg, MSW Mural Arts Philadelphia, Philadelphia, Pennsylvania

Brandon Knettel, PhD, MA Duke University Global Health Institute, Durham, North Carolina

Margaret Fulda, MSW, LSW, MPH JFK Behavioral Health Center, Philadelphia, Pennsylvania

Abbie Santana, MSPH Thomas Jefferson University, Philadelphia, Pennsylvania

Melissa DiCarlo, MPH, MS Thomas Jefferson University, Philadelphia, Pennsylvania

James Plumb, MD, MPH Thomas Jefferson University, Philadelphia, Pennsylvania

Appendix 7B: Steps in Tailoring a Text Messaging– Based Smoking Cessation Program for Young Adults: Iterative Intervention Refinement

Michele L. Ybarra, PhD Center for Innovative Public Health Research, San Clemente, California

Appendix 7C: Better Bites

Brian J. Biroscak, PhD, MPH Yale University, New Haven, Connecticut

Ashton Potter Wright, DrPH, MPH City of Lexington, Lexington, Kentucky

Anita Courtney, MS, RD Lexington Tweens Nutrition and Fitness Coalition, Lexington, Kentucky

Carol A. Bryant, PhD, MS University of South Florida, Tampa, Florida

Appendix 7D: Social Marketing to Increase Partici- pation in WIC

Tiffany Neal, MPH, MCHES Thomas Jefferson Health District, Virginia Department of Health, Richmond, Virginia

Appendix 7E: Asthma Self-Management Mobile Application for Adolescents: From Concept Through Product Development to Testing

Tali Schneider, MPH, CHES Florida Prevention Research Center, University of South Florida, Tampa, Florida

Jim Lindenburger Center for Social Marketing, University of South Florida, Tampa, Florida

Appendix 8A: The Challenges of Evaluating a Supplemental Nutrition Education Program for Low-Income Families

Kami J. Silk, PhD Michigan State University, East Lansing, Michigan

Evan K. Perrault, PhD University of Wisconsin-Eau Claire, Eau Claire, Wisconsin

Caroline J. Hagedorn, MA Independent Researcher, Washington, DC

Samantha A. Nazione, PhD Berry College, Mount Berry, Georgia

Case Study Contributors xiii

Lindsay Neuberger, PhD University of Central Florida, Orlando, Florida

R. Paul McConaughy, MA Michigan Fitness Foundation, Lansing, Michigan

Khadidiatou Ndiaye, PhD George Washington University, Washington, DC

Box 9-4: Shared Decision Making: Decision Counseling Program at Thomas Jefferson University

Ronald E. Myers, DSW, PhD Division of Population Science and Center for Health Decisions, Department of Medical Oncology, Sidney

Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA

Anett Petrich, RN, MSN Division of Population Science and Center for Health Decisions, Department of Medical Oncology, Sidney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA

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As with anything, it truly takes a village, and in this case, it took a village of dedicated and incredible peo- ple who helped us make this book happen. Many of the people who helped with ideas or materials for this book are credited where their contributions appear. We thank them for providing cutting-edge thinking as well as examples of health communication in action. Their work represents some of the best of the best, and we truly appreciate being able to showcase it in this textbook.

But we would be remiss to not shout out to those specific people who helped us every step of the way, without whose help this book would never have come to fruition. On the editorial side, Alesha Hruska, MPH, MS, at University of the Sciences and Laurie Maurer, PhD, MA, at Temple University contributed valuable critiques as well as editorial assistance in putting the book together. They also contributed to or co-wrote two chapters. Richard Harner, MD, provided his edi- torial touch everywhere. The book would simply not be here without their work. Thanks also to Virginia Liddell, BS, Shreya Kandra, MD, MPH, and Vijay Pra- japati, BDM, at the University of South Florida, and Jessie Panick, BS, and Mohammed Al Hajji, MPH, at

Temple University for their help with everything from editorial assistance to developing ancillary materials and helping us keep track of all the details.

The Jones & Bartlett Learning crew of Mike Brown, Carter McAlister, Vanessa Richards, Merideth Tumasz, Maria Leon Maimone, and Toni Ackley all provided great help and support. We thank Richard Riegleman, who originally came to us with the idea of having a book geared not only to public health students, but also to anyone who could incorporate health communication principles into their studies and work, for his insights and help with the process and conceptualization of the book.

Last but not least, we would like to acknowledge the support of our colleagues at Temple University, the University of the Sciences, and the University of South Florida for their support while we toiled away at get- ting this book done. And to our families, who endured us talking about, working on, and complaining fiercely about the book, we thank you for your patience and constant support.

—Claudia F. Parvanta, PhD, and Sarah Bauerle Bass, PhD, MPH

Acknowledgments

xvii

© Galkin Grigory/Shutterstock

Claudia Parvanta, PhD, is a Professor of Commu- nity and Family Health, College of Public Health, and Director of the Florida Prevention Research Center at the University of South Florida, Tampa. Her work in Florida focuses on reducing disparities in health through community-based prevention marketing. Between July 2005 and December 2016, she led the Department of Behavioral and Social Sciences at the University of the Sciences in Philadelphia where her research emphasized health literacy and cultur- ally competent health communication. From 2000 to 2005, Dr. Parvanta headed the Division of Health Communication at the Centers for Disease Control and Prevention. She was central to the agency’s com- munication response to the 9/11 attacks, anthrax, and severe acute respiratory syndrome. Before govern- ment and academia, Dr. Parvanta worked at Porter Novelli, a global social issues communication com- pany. Dr. Parvanta has designed, managed, or evalu- ated health and nutrition social marketing programs in more than 20 countries. She is the 2016 recipient of the Public Health Education and Health Promotion Division of APHA’s Distinguished Career Award.

Sarah Bauerle Bass, PhD, MPH, is an Associ- ate Professor in the Social and Behavioral Sciences department in the College of Public Health at Temple University and Director of the Risk Communication Laboratory. With over 25 years of experience in health communication, her work focuses on development and testing of culturally and developmentally appro- priate materials, specializing in use of commercial

marketing techniques and new technologies to address health disparities. She teaches health communication at the undergraduate and graduate levels, as well as risk communication and community-based interven- tion development at Temple University. As Director of the Risk Communication Laboratory, her research has advanced the field of health communication by applying commercial marketing techniques to the development and testing of messages and interven- tions. Using perceptual mapping and vector modeling methods, Dr. Bass has shown how 3-D imaging can enhance message development and tailor it for specific behavior or attitude barriers. Dr. Bass is also utilizing psycho-marketing methods to assess emotional and physiological response to and processing of health messages through visual, graphic, web, or textual mes- sage elements using eye tracking, pupilometer, EKG, and skin conductance measures. She has a number of currently funded studies using these techniques to develop culturally and literacy appropriate health communication interventions to help audiences make better medical decisions. Prior to Temple, she was the Public Information Coordinator for the West Virginia Department of Public Health’s HIV/AIDS program where she developed all communication materials and implemented statewide communication campaigns. She is the recipient of the Riegelman Award for Excel- lence in Undergraduate Public Health Education from the Association of Schools and Programs in Public Health, and the Great Teacher and Lindback Awards for distinguished teaching from Temple University.

About the Authors

CHAPTER 1

Your World, Your Health Claudia Parvanta

LEARNING OBJECTIVES

By the end of this chapter, the reader will be able to:

■ Identify major factors affecting life expectancy and health outcomes. ■ Define the approximate proportion of risk of premature death attributed to health care, genetics, social and

environmental factors, and individual behavior. ■ Explain how biological attributes of age, race, and sex are conditioned by social interpretations when it comes

to health. ■ Describe the leading causes of death for college-age individuals. ■ Diagram an ecological model for a health issue. ■ Explain how a communicator can use the people and places model to plan an intervention.

▸ Introduction

Mickey Mantle is known for saying, “If I knew I was going to live this long, I’d have taken better care of myself.” There is a good chance that many readers will not know that Mickey Mantle was a center fielder and first base- man for the New York Yankees from 1951 through 1968, and is considered one of the greats in the game. After decades of alcohol abuse, Mantle died of liver disease and a heart attack in 1995 at the age of 63.

Jumping forward in time, an insurance company ran an ad in which it asked people to place a blue sticker on a wall to indicate the age of the oldest person they knew. The 400 participants created a histogram that peaked around the age of 95. The advertisers

pointed out that the U.S. retirement age of 65 was developed around the time that Mickey Mantle was playing ball—and the average life expectancy was 61. By the year 2000, life expectancy had reached 74 for males and 79 for females,1 and similar increases are projected through 2050. What does this increase in average life expectancy reflect?

▸ Major Factors Affecting Health Outcomes

Turning the question around, we can ask what fac- tors are associated with dying “before your time,” or as population scientists put it, premature death. FIGURE 1-1 illustrates the approximate contribution of major factors to premature death.

© Galkin Grigory/Shutterstock

1

Are you surprised by this breakdown? Here is more about each major risk factor.

Health Care: The 10% Solution Even though the United States spends more on health care than any other high-income country, Americans have the lowest life expectancy at birth and a greater prevalence of chronic diseases com- pared to the citizens of other high-income countries. Prior to the implementation of the Affordable Care Act of 2010 (ACA), the United States spent 17.1% of its gross domestic product on health care. This was nearly twice what was spent in the United Kingdom (8.8%), for example. This spending was driven by greater use of expensive medical technologies (e.g., computed tomography scans) and higher healthcare and medication prices, but not more frequent doctor visits or hospital admissions.2 So, Americans spend more money on drugs, tests, and fees but do not reap the benefit of healthier and longer lives. Why? Part of the reason is that so many individuals turn to health care only when something bad has already happened. In addition, many other factors contribute to our risk.

Genetics and Health: 30%3 The human genome contains about 20,500 genes. Of all these genes, we differ from every other human on earth by only about 1%. But it is this tiny percentage that determines our unique appearance, our potential for specific diseases, and our response to external fac- tors, including therapeutic drugs.

As you learned in high school biology, in suc- cessful conception and pregnancy, the 23 chromo- somes from your genetic father and 23 from your genetic mother develop into a 100-trillion-cell adult.

The 3 billion pairs of DNA letters that are copied and packaged during reproduction often contain slight variations that have no impact on health. But, some- times these genetic instructions produce a damaged protein, extra protein, or no protein at all, which can result in a genetic mutation. Single gene muta- tions are responsible for more than 10,000 disor- ders. There are screening tests that parents can use prior to conception to identify autosomal recessive carrier status for more than 580 conditions. Auto- somal recessive genes are not normally expressed in the heterozygous state, but if two carriers repro- duce, they have a 25% chance that their offspring will be homozygous for the trait, and therefore have the condition. With appropriate genetic counseling, couples can avoid the heartache of giving birth to a child with a quickly fatal disease, such as Tay-Sachs, or a painful condition that shortens life, such as sickle cell anemia.

Women who carry a mutated form of either the BRCA1 or BRCA2 gene have an increased risk (i.e., greater than the 1 in 9 probability that all women carry) of developing breast or ovarian cancer at some point in their lives. Other adult onset diseases, such as colon cancer and heart disease, have genetic compo- nents. At this point in time, we have not discovered a genetic variation underlying most diseases.

The study of genetic variation, or genomics, is increasingly important in the development of treat- ments and drugs. These may be targeted to an indi- vidual’s genome or the genome of the disease agent (e.g., a virus or a genetic form of cancer). As time goes on, we are discovering more genomic factors that may allow us to live more years free of disease. It is an exciting time for genomics, but for now, your best shot at being healthy is largely up to you—or is it?

Individual Behavior: 40% Individual behaviors, which include what you eat, drink, or smoke; your sexual and reproductive activity; how fast you drive; how long you sit on the couch; and so on, play a significant role in determining your lon- gevity. A study summarized the impact of six behav- iors that the U.S. government has tracked in relation to changes in life expectancy and quality-adjusted life expectancy from 1960 to 2010.4 Overall life expectancy increased by 6.9 years during this period. As shown in FIGURE 1-2, the authors of the study esti- mated that reductions in cigarette smoking and motor vehicle fatalities contribute nearly 2 of these years; however, the benefit of these gains is partially offset by the negative effect of rising obesity and accidental drug overdose.

FIGURE 1-1 Risk of premature death attributed to different factors.

Health care 10%

Genetics 30%

Social & environmental

20%

Individual behavior 40%

Data from Schroeder SA. We can do better—improving the health of the American people. N Engl J Med. 2007;357:1221-1228.

2 Chapter 1 Your World, Your Health

We still could add many years to our life span by adopting healthier behaviors; for example, fewer than 13% of Americans eat the recommended five to seven daily servings of vegetables and fruits. It takes more than just a friendly reminder to get most people to change from an unhealthy to a beneficial behavior. For many, the choice seems out of their hands, which brings us to a discussion of social determinants of health (SDH).

Social and Environmental Factors: 20% Although some social and environmental factors directly affect health (such as gang membership, air pollution, or toxic exposure to lead paint), oth- ers work indirectly by limiting or shaping access to resources or lifestyle options; for example, “…chil- dren born to parents who have not completed high school are more likely to live in [unsafe] neighbor- hoods… have exposed garbage or litter, and have poor or dilapidated housing and vandalism….”5 A seminal meta-analysis concluded that social deter- minants are associated with a third of premature deaths in the United States.6

Because of the power of social determinants and the long history of disparities in the distribution of resources along societal lines, the World Health Organization (WHO)7 and the U.S. government have adopted an SDH approach in setting priorities for action. For example, Healthy People 2020, launched in 2010 by the U.S. Department of Health and Human Services, organizes SDH around five key domains: (1) Economic Stability, (2) Neighborhood and Phys- ical Environment, (3) Education, (4) Community and

Social Context, and (5) the Health Care System. Other organizations include other factors, such as access to food, as shown in FIGURE 1-3.

Although problems with low literacy (listed under the Education domain) or playgrounds (listed under Neighborhoods) may seem outside the literal domain of health, not being able to read or under- stand English can have a tremendous impact on tak- ing care of oneself or one’s family. And access to safe playgrounds, sidewalks, and other green spaces is closely associated with risks of obesity. Your world is made up of social determinants, and because these determinants have a profound influence on your health, we will discuss them in greater depth in the sections that follow.

▸ Socially Defined You For centuries, humans have been recording informa- tion about births, deaths, and significant illnesses and noting the individual’s gender (male or female) and age, if known.

There were biological, social, and cultural forces that shaped these events. These forces still function today and determine, or at least provide a strong pre- dictive contribution to, our own health outcomes.

There are protective factors, and similarly prob- lems, associated with differences in:

■ Sex and gender ■ Race and ethnicity ■ Age ■ Environment ■ Societal factors

FIGURE 1-2 Impact of behavioral changes on life expectancy, 1960–2010. Reproduced from National Bureau of Economic Research. How behavioral changes have affected U.S. population health since 1960. Bull Aging Health. 2015;1. http://www.nber.org/aginghealth/2015no1/w20631.html. Accessed July 2, 2015.

1.5

1.0

0.5

0.0

–0.5

–1.0

–1.5

C ha

ng e

in li

fe e

xp ec

ta nc

y (y

ea rs

)

Smoking

1.26

0.43

0.06

–1.00

–0.26

0.03

0.46

Motor vehicles

Alcohol

Obesity Poisonings Firearms

Total

Increases in obesity, poisonings (e.g., drug overdoses), and �rearm deaths decreased life expectancy

Declines in smoking, motor vehicle fatalities, and heavy drinking increased life expectancy

Socially Defined You 3

http://www.nber.org/aginghealth/2015no1/w20631.html
These factors—added onto your genetic makeup— affect your personal health in ways that can be either beneficial or harmful.

Sex and Gender8 The term sex in biology refers to genetic expression of the genes inherited from one’s parents. In most cases individuals are either XY or XX. Those with one X and one Y chromosome in every cell of the body are bio- logically male; biological females have two X chromo- somes in every cell. Because these cells make up all the tissues and organs, there are sex-linked differences throughout our physiology, including but not limited to genitalia, hormones, and glandular development. In addition, biological males and females can express dif- ferent symptoms when ill; may experience sensations such as pain differently; and respond differently to medications and substances, including addictive ones. Recognizing these biological differences, the U.S. gov- ernment requires that clinical trials of new drugs or other medical interventions include both men and women, unless there is a clear rationale not to do so (e.g., a study of a prostate cancer drug or intrauterine device). For most of recorded history, individuals have been classified as “male” or “female” with little further thought. Medical science began documenting varia- tions more effectively in the 20th century.9

Some individuals are born with undetermined genitalia at birth, which may also be true on a cellu- lar level (i.e., some cells contain XX and others XY, or other variations). These conditions are referred to as intersex. It is possible for an individual to not be aware of subtle intersex variations, whereas others may be

very aware of what they see and feel. Today’s medi- cal standards advise against surgical interventions until the affected individual can make that decision. The thought that a parent may wish to “fix” a child’s body to look more like the sex they see most clearly expressed leads us to a discussion of gender.

Gender is a social or cultural concept that reflects how men and women, boys and girls, are meant to look and behave. By the age of 2 or 3, children will express strong identities as girls or boys, which are then rein- forced or discouraged by their parents, teachers, or others in their social world. When children behave in ways that are discordant with their biological ref- erences (e.g., their genes, their genitalia), they may be labeled as gender nonconforming. This can be as casual as a girl playing with a truck and a boy playing with a doll. Some children eventually become comfortable adopting the societal roles assigned to their gender. Others may wish to change their outward appearance and fully behave in ways they feel are consistent with their internal concept of themselves. The term trans- gender refers to a range of behaviors associated with making this change. Some individuals go on to have gender reassignment surgery and take hormones to support this change.

As individuals mature to the point of seeking inti- mate partners, the term sexual orientation becomes meaningful. Sexual orientation refers to being sexu- ally and romantically attracted to persons of the same or opposite sex. Kinsey and others have described a spectrum of attraction from consistently preferring the opposite sex (heterosexual), through preferring members of either sex (bisexual), to consistently preferring the same sex (homosexual).10

FIGURE 1-3 Social determinants of health.

Neighborhood and physical environment

Housing

Transportation

Safety

Parks

Playgrounds

Walkability

Zip code/geography

Economic stability

Employment

Income

Expenses

Debt

Medical bills

Support

Mortality, morbidity, life expectancy, healthcare expenditures, health status, functional limitations

Health outcomes

Literacy

Education Food

Hunger

Access to healthy options

Language

Early childhood education

Vocational training

Higher education

Community and social

context

Social integration

Support systems

Community engagement

Discrimination

Stress

Healthcare system

Health coverage

Provider availability

Provider linguistic and

cultural competency

Quality of care

Reproduced from Heiman HJ, Artiga S. Beyond health care: the role of social determinants in promoting health and health equity. KFF webpage. https://www.kff.org/disparities-policy/issue-brief/beyond-health-care-the-role-of-social-determinants-in-promoting-health -and-health-equity/. Published November 4, 2015. Accessed April 20, 2018.

4 Chapter 1 Your World, Your Health

https://www.kff.org/disparities-policy/issue-brief/beyond-health-care-the-role-of-social-determinants-in-promoting-health-and-health-equity/
https://www.kff.org/disparities-policy/issue-brief/beyond-health-care-the-role-of-social-determinants-in-promoting-health-and-health-equity/
How Do Sex and Gender Affect Health Outcomes? It is well known that, on average, women live lon- ger than men, but they also experience more days of illness or disability. Setting aside the risks associ- ated with childbearing, why should women expe- rience more “sick time” and still outlive their male contemporaries?

Few researchers have separated the risks associ- ated with the biological condition of being female or male from the lived experience of gendered identities. In other words, we have little data apart from birth outcomes that truly show the vulnerability associated with an XX or XY genotype versus the risks accumu- lated as a girl or a boy matures in a particular envi- ronment. Using the WHO’s original Global Burden of Disease, published in 2002, Snow11 noted that the XY genotype is a necessary (but not sufficient) con- dition for the risk of hemophilia, prostate cancer, and testicular cancer. Being born XX was associated with a greater risk of breast and ovarian cancer, and all maternal causes of death. TABLE 1-1 shows conditions worldwide from which men and women lose more active years of life.

Most of the conditions in Table 1-1 are connected to social expectations for men and women. Virtually every human society expects boys and men to take risks and demonstrate courage or “manhood,” often resulting in the higher rates of fatalities due to hunt- ing accidents, local fights, warfare, or even car crashes. Women and girls too often fall victim to the ugly side of the same expectations, resulting in domestic vio- lence, rape, conflict, and trafficking. Women also are more subject to culturally sanctioned traditions of bodily mutilation, limits on property ownership, or freedom of movement, which are upheld by both men and women in their societies.12 Risks for girls can be even more extreme, as in the case of femicide.

Femicide. Along with other sex-linked traits, slightly more boys are born alive than girls, with a resulting 105 boys born for 100 girls. In most cultures, this imbalance evens out as slightly more girls survive infancy. However, there are many societies where the perceived need and desire for males leads to parents killing female infants at birth, through either neglect or force. When and where ultrasound technology became widely available, abortion replaced infanti- cide by allowing so-inclined parents to detect and abort a female fetus; for example, in China, the birth ratio is presently 120 boys for every 100 girls. In India, despite a 1994 law banning use of ultrasound for sex selection, for second-born children, there are only 76

females born for every 100 males.13 In both countries, demographers warn of the stresses to society caused by these “missing” women. Numerous international agencies and voluntary organizations are working to reduce these gender inequalities. (A good place to start is with the United Nations Entity for Gender Equality and the Empowerment of Women at http:// www.unwomen.org/en/.)

TABLE 1-1 Conditions with Greatest Difference in Global Burden of Disease for Men and Women

Conditions for Men

War

Gout

Alcohol use disorders

Road and traffic accidents

Violence

Other intentional injuries

Drug use disorders

Lymphatic filariasis

Mouth and propharynx cancers

Lung cancer

Liver cancer

Drowning

Bladder cancer

Conditions for Women

Breast cancer

Gonorrhea

Chlamydia

Trachoma

Migraine

Posttraumatic stress disorder

Rheumatoid arthritis

Panic disorder

Data from Snow RC. Sex, Gender and Vulnerability. Population Studies Center Research Report 07-628. Ann Arbor, MI: Population Studies Center, University of Michigan; 2007.

Socially Defined You 5

http://www.unwomen.org/en/
http://www.unwomen.org/en/
Sexual Orientation and Health The National Health Interview Survey (NHIS) has been conducted annually in the United States for 57 years. BOX 1-1 provides some information about the overall survey methods as well as questions pertaining to sexual orientation, used for the first time in 2013.

TABLE 1-2, reprinted from the National Health Sta- tistics report, shows the sexual orientation among U.S.

adults aged 18 and over, by sex and age group, based on data from the 2013 survey. Among all U.S. adults aged 18 and over, 96.6% identified as straight, 1.6% identified as gay or lesbian, and 0.7% identified as bisexual. Of the remaining 1.1% of adults, 0.2% iden- tified as “something else,” 0.4% selected “I don’t know the answer,” and 0.6% did not provide an answer.

The sexual orientation variables were analyzed against selected health behaviors, health status

BOX 1-1 National Health Interview Survey Methodology

Methods NHIS is an annual multipurpose health survey conducted continuously throughout the year and serves as a primary source of health data on the civilian noninstitutionalized population of the United States.a Data are collected by trained interviewers with the U.S. Census Bureau using computer-assisted personal interviewing (CAPI), a data collection method in which an interviewer meets with respondents face-to-face to ask questions and enter the answers into a laptop computer. When necessary, interviewers may complete missing portions of the interview over the telephone.

Analyses in this report were based on data collected from 34,557 sample adults aged 18 and over. The conditional sample adult response rate (i.e., the number of completed sample adult interviews divided by the total number of eligible sample adults) was 81.7%. The final sample adult response rate, calculated by multiplying the conditional response rate by the final family response rate, was 61.2%.b

Sexual Orientation Questions The first of the four cascading sexual orientation questions that were included in the 2013 NHIS, which is asked of all sample adults aged 18 and over, reads, “Which of the following best represents how you think of yourself?” It has five response options, which vary slightly by respondent sex.

For male respondents, they are: ■ Gay, ■ Straight, that is, not gay, ■ Bisexual, ■ Something else, and ■ I don’t know the answer.

For female respondents, the response options are: ■ Lesbian or gay, ■ Straight, that is, not lesbian or gay, ■ Bisexual, ■ Something else, and ■ I don’t know the answer.

Although not an explicit response option, respondents could refuse to provide an answer to any of these questions. For the initial sexual orientation question (and the “something else” and “I don’t know the answer” follow-up questions),

flashcards listing the response options were handed to respondents in the face-to-face interview setting. Respondents were asked to report the number corresponding to their answer. When the questions were administered over the telephone, the interviewer read the response options. Complete text and details of the NHIS sexual orientation questions are provided in the 2013 Sample Adult survey questionnaire, which can be accessed on the NHIS website: http://www.cdc.gov/nchs/nhis.htm.

a National Center for Health Statistics. National Health Interview Survey, 2013. Public-use data file and documentation. Available from: http://www.cdc.gov/nchs/nhis/ quest_data _related_1997_forward.htm

b National Center for Health Statistics. 2013 National Health Interview Survey (NHIS) public use data release survey description. 2014. Available from: ftp://ftp.cdc.gov/pub/ Health_Statistics /NCHS/ Dataset_Documentation/NHIS/2013/ srvydesc.pdf

Reproduced from Ward BW, Dahlhamer JM, Galinsky AM, Joestl SS; Division of Health Interview Statistics, Centers for Disease Control and Prevention (CDC), U.S. Department of Health and Human Services. Sexual Orientation and Health Among U.S. Adults: National Health Interview Survey, 2013. Hyattsville, MD: National Center for Health Statistics. https://www.cdc.gov/nchs /data/nhsr077.pdf

6 Chapter 1 Your World, Your Health

http://www.cdc.gov/nchs/nhis.htm
https://www.cdc.gov/nchs/data/nhsr077.pdf
https://www.cdc.gov/nchs/data/nhsr077.pdf
http://www.cdc.gov/nchs/nhis/quest_data_related_1997_forward.htm
http://www.cdc.gov/nchs/nhis/quest_data_related_1997_forward.htm
indicators, and access to health care. BOX 1-2 summa- rizes some of the results from this analysis.

This somewhat dry summary suggests that men and women who identified as lesbian, gay, or bisexual on this national survey were insured and participated in basic healthcare options in about the same propor- tion as their self-identified heterosexual counterparts. Those who self-identified as gay or lesbian were more likely to engage in smoking and drinking than their heterosexual counterparts. Although the NHIS asked about these health risks, it did not ask about unpro- tected sex or violence.

Other U.S. health data show that a higher percent- age of lesbian or gay adults (56.4%) and bisexual adults (47.4%) report intimate partner violence compared to heterosexual adults (17.5%). In addition, although the Centers for Disease Control and Prevention (CDC) estimates that men who have sex with men (MSM) account for 4% of the U.S. male population aged 13 or

older, the rate of new human immunodeficiency virus (HIV) diagnoses among MSM in the United States is 44 times that of other men.14

Another risk for individuals who identify as les- bian, gay, bisexual, or transgender (LGBT) that dis- tinguishes them from their heterosexual counterparts is being the target of hate crimes. Even before the 2016 shooting rampage at a gay nightclub in Orlando, Florida, the Federal Bureau of Investigation (FBI) documented more hate crimes against LGBT peo- ple than any other collective group. Nearly 20% of the 5462 single-bias hate crimes reported to the FBI in 2014 were because of the target’s sexual orienta- tion, or how the perpetrator perceived their victim’s orientation.15

So, your chromosomes, gender identification, sex- ual orientation, sexual behavior, and societal reactions to your gender identity and behavior all comprise how sex and gender influence your health risks.

TABLE 1-2 National Health Statistics Report—Sexual Orientation

Sexual Orientation

Gay or Lesbiana Straightb Bisexual

Number in Thousands

Percentc (Standard Error)

Number in Thousands

Percentc (Standard Error)

Number in Thousands

Percentc (Standard Error)

Overall 3729 1.6 (0.09) 224,163 97.7 (0.11) 1514 0.7 (0.06)

Sex

Men 2000 1.8 (0.14) 108,093 97.8 (0.15) 481 0.4 (0.06)

Women 1729 1.5 (0.12) 116,071 97.7 (0.15) 1033 0.9 (0.10)

Age Group (Years)

18–44 2028 1.9 (0.15) 104,947 97.1 (0.18) 1153 1.1 (0.12)

45–64 1422 1.8 (0.16) 77,686 97.8 (0.17) 289 0.4 (0.07)

65 and over 278 0.7 (0.13) 41,531 99.2 (0.14) 73 0.2 (0.05)

Note: Estimate has a relative standard error greater than 30% and less than or equal to 50% and should be used with caution as it does not meet standards of reliability or precision. a Response option provided on the National Health Interview Survey was “gay” for men, and “gay or lesbian” for women. b Response option provided on the National Health Interview Survey was “straight, that is, not gay” for men, and “straight, that is, not gay or lesbian” for women. c Percent distributions in this table may not equal exactly 100.0% due to rounding. Reproduced from National Health Interview Survey. National Center for Health Statistics website. http://www.cdc.gov/nchs/nhis/index.htm. Accessed February 20, 2018.

Socially Defined You 7

http://www.cdc.gov/nchs/nhis/index.htm
BOX 1-2 Prevalence of Selected Health Indicators by Sexual Orientation for Adults Aged 18–64

Data from Ward BW, Dahlhamer JM, Galinsky AM, Joestl SS; Division of Health Interview Statistics, Centers for Disease Control and Prevention (CDC), U.S. Department of Health and Human Services. Sexual Orientation and Health Among U.S. Adults: National Health Interview Survey, 2013. Hyattsville, MD: National Center for Health Statistics. https://www.cdc.gov/nchs/data/nhsr077.pdf

Health-Related Behaviors ■ Current cigarette smoking:

• A higher percentage of adults aged 18–64 who identified as gay or lesbian (27.2%) or bisexual (29.5%) were current cigarette smokers compared with their counterparts who identified as straight (19.6%).

■ Binge drinking: • A higher percentage of adults aged 18–64 who identified as gay or lesbian (35.1%) or bisexual (41.5%) reported

having had five or more drinks in one day at least once in the past year compared with those who identified as straight (26.0%).

■ Meet federal guidelines for aerobic physical activity: • There were no significant differences among adults aged 18–64 who identified as gay or lesbian (57.9%), bisexual

(55.5%), or straight (52.3%).

Health Status Indicators ■ Health status described as excellent or very good:

• No significant differences were found by sexual orientation for the percentage of adults aged 18–64 with excellent or very good health, neither overall nor among men. Among women, however, a higher percentage of those who identified as straight (63.3%) were in excellent or very good health compared with women who identified as gay or lesbian (54.0%).

■ Experienced serious psychological distress in the past 30 days: • A higher percentage of adults aged 18–64 who identified as bisexual (11.0%) experienced serious psychological

distress in the past 30 days compared with their counterparts who identified as gay or lesbian (5.0%) or straight (3.9%). ■ Considered “obese” based on calculated weight and height (i.e., not asked directly):

• No significant differences were found overall in the percentage of adults aged 18–64 who were obese. A higher percentage of men aged 18–64 who identified as straight (30.7%) were obese than men who identified as gay (23.2%); among women aged 18–64, a higher percentage of those who identified as bisexual (40.4%) were obese than women who identified as straight (28.8%).

Healthcare Service Utilization and Access ■ Received influenza vaccination in the past year:

• A higher percentage of adults aged 18–64 who identified as gay or lesbian (42.9%) received an influenza vaccination in the past year compared with those adults aged 18–64 who identified as straight (35.0%).

■ Ever been tested for HIV: • A higher percentage of men who identified as gay (79.5%) or bisexual (56.7%) compared to straight (33.0%)

have ever been tested for HIV. Among women, the differences in testing were not statistically significant (51.6% identified gay or lesbian, 52.6% identified bisexual, and 40.2% identified straight).

■ Has a usual place to go for medical care: • Among men aged 18–64, no significant differences in having a usual place to go for medical care were found

(gay: 81.2%, bisexual: 74.5%, straight: 76.4%). Among women aged 18–64, by contrast, a higher percentage of those who identified as straight (85.5%) had a usual place to go for medical care than those who identified as gay or lesbian (75.6%) or bisexual (71.6%).

■ Failed to obtain needed medical care in past year due to cost: • Among women aged 18–64, a higher percentage of those who identified as gay or lesbian (15.2%) failed to

obtain needed medical care in the past year due to cost compared with those who identified as straight (9.6%). No significant differences by sexual orientation were found among men aged 18–64 for this indicator.

■ Currently uninsured: • Among men aged 18–64, a higher percentage of those who identified as straight (21.9%) were uninsured

compared with those who identified as gay (15.7%). Among women, 19.1% of those who identified as gay or lesbian, 24.9% who identified as bisexual, and 18.4% of those who identified as straight were currently uninsured, but the difference was not statistically significant.

8 Chapter 1 Your World, Your Health

https://www.cdc.gov/nchs/data/nhsr077.pdf
FIGURE 1-4 Population by race and Hispanic origin (percent of total population), 2012 and 2060.

Race and Ethnicity FIGURE 1-4 shows the statistics from the 2010 U.S. cen- sus (reported in 2012) on how many people identi- fied themselves by a specific race as well as Hispanic ethnicity. It also shows the projected population in 2060. The largest change predicted for the future will be the near doubling of the ethnically Hispanic population, with some small increases in Asian and “other” groups, which includes Native Americans as well as Native Alaskans, Hawaiians, and Pacific Islanders. What do these broad classifications mean in terms of health?

Changing Views of Race and Ethnicity Have you sent a cheek swab to National Geographic to have your ancestry determined? Or maybe you have tried 23andMe.com? These fun activities com- pare your mitochondrial DNA (passed down from your mother) and some markers on your Y chromo- somes (from your father) to detect your deep, deep roots. And by deep, we mean learning where your ancestors lived more than 500 years ago. From actual eons of migration, mixing, and mingling, humanity is incredibly diverse, with much more variation exist- ing within a so-called “racial group” than between racial groups. Therefore, many social scientists assert that race is not based in biology but constructed by society.

For example, skin color, a 19th-century approach to defining race, is controlled by more than 378 genetic loci. These genes regulate melanin production and

the skin’s reaction to light of various wavelengths.16 Anthropologist Nina Jablonski has pointed out that the geographical distribution of human skin color is related to distance from the equator. At more north- ern or southern latitudes, the level of ultraviolet B (UVB) rays hitting Earth’s surface decreases due to the planet’s tilt. The equator is bathed year-round in UVB rays, but seasonal variations mean that people in Northern Europe receive virtually no UVB exposure in winter. As a result, Jablonski said, humans living near the equator developed darker skin tones (to pro- tect against the harmful effects of too much exposure), whereas those in northern climates developed lighter hues and are more efficient at synthesizing vitamin D from sunlight.17

Any population-level traits, including autosomal recessive conditions such as sickle cell disease (SCD) or Tay-Sachs, are carried down through generations due to social factors that have brought groups of people into gene pools (breeding populations) over time. (See BOX 1-3 for more about these two con- ditions.) Sometimes populations had control over these groupings; at other times, they were against their wishes.

When many people share cultural traits, such as language, appearance, food, religion, dress, and meaningful symbols, and have a common ances- tral homeland, they may be considered to have an ethnic identity. Does it match up with a set of physical or physiological traits? It can, if the pop- ulation has lived and reproduced in the same place over a long period.

White alone

Black alone

AIAN alone

Asian alone

NHPI alone

Two or more races

Non- hispanic

white alone

Hispanic (of any race)

2012 2060

13 15

1.2 1.5 5.1

8.2

0.2 0.3 2.4 6.4

69 63

43

17

31

78

Abbreviations: AIAN, American Indian and Alaska Native; NHPI, Native Hawaiian and Other Pacic Islander.

Reproduced from United States Census Bureau; U.S. Department of Commerce. Washington, DC. https://www.census.gov/newsroom/releases/img/racehispanic_graph.jpg. Accessed March 7, 2018.

Socially Defined You 9

http://23andMe.com?
https://www.census.gov/newsroom/releases/img/racehispanic_graph.jpg
Therefore, although race may not be clearly defined biologically, it is very real socially, by which we mean that society may allocate valued resources based on this construct. Ethnicity tends to work through the trans- mission of cultural learning from one generation to another. As such, race and ethnicity can strongly affect health outcomes through the media of culture and society, including selection of mates from within only specific groups.

Age Have you seen the questions in TABLE 1-3 before? If so, you are likely to be one of nearly 23,000 stu- dents (graduate and undergraduate) who completed the American College Health Association’s National College Health Assessment in the past few years. Table 1-3 shows data from the first set of questions that asks about topics addressed by college health information providers as well as student interest in these topics.

More than 50% of students wanted more informa- tion about the following topics, in descending order of interest:

■ Stress reduction ■ Nutrition ■ Helping others in distress ■ Sleep difficulties ■ Depression and anxiety ■ Physical activity

Lagging only slightly behind was information pertaining to sexual assault or violence prevention, sexually transmitted diseases (STDs), and suicide pre- vention. Runners-up included tobacco use, pregnancy prevention, and cold/flu/sore throats. If you were a health education coordinator at a university, what would you do with these data?

Now compare the issues of concern to col- lege students to the data in FIGURE 1-5 showing the CDC’s depiction of the leading causes of death by age group in the United States. Examining the columns

BOX 1-3 Diseases of Origin?

Sickle Cell Diseasea Red blood cells that contain normal hemoglobin are disc shaped, which allows the cells to move easily through large and small blood vessels to deliver oxygen. Sickle hemoglobin can form stiff rods within the red cell, changing it into a crescent or sickle shape. Sickle-shaped cells can stick to vessel walls, causing a blockage that slows or stops the flow of blood. When this happens, oxygen cannot reach nearby tissues.

People who have SCD inherit two abnormal hemoglobin genes, one from each parent. In all forms of SCD, at least one of the two abnormal genes causes a person’s body to make hemoglobin S. When a person has two hemoglobin S genes, hemoglobin SS, the disease is called sickle cell anemia. This is the most common and often most severe kind of SCD. Hemoglobin SC disease and hemoglobin Sβ thalassemia are two other common forms of SCD.

A common myth about SCD is that it is an African disease affecting only people in Africa or their descendants. In fact, SCD occurs more often among people who come from areas where malaria was common, such as Africa, but also including the Middle East, India, some Mediterranean countries, and Latin America. Anthropologists theorize this is related to the protective effect that the sickle cell mutation provides against malaria infection in the heterozygous state.

Tay-Sachs: Not Only a “Jewish Disease”b Tay-Sachs is a neurodegenerative disease that is fatal in the homozygous state. Babies born with Tay-Sachs disease appear normal at birth, but begin to show symptoms at 4 to 6 months of age. Children then gradually lose their sight, hearing, and swallowing abilities, and usually die by the age of 5 years.

Jewish individuals whose families originated in Eastern Europe, so-called Ashkenazi Jews, have long known to test for carrier status of Tay-Sachs before starting a family. Among the more orthodox populations that arrange marriages, rabbis often require blood tests before condoning a match. Of course, practicing Judaism as a religion had nothing to do with the disease directly, but because Jews in that part of the world limited their marriages to within their communities, and the carrier status was nonfatal, the gene was maintained at a higher rate within this ethnic group. Today, it is known that French Canadian, Cajun (Louisiana), and Irish populations also have higher than average rates of the disease. These days, due to more mixing of populations than was done in past centuries, all young adults are advised to get genetic screening before starting families.