SMOKING 

AND 

TOBACCO 

CONTROL 

MONOGRAPH 12 

Population

Based Smoking

Cessation 

Proceedings of a Conference on 

What Works to Influence Cessation 

in the General Population 

U.S. DEPARTMENT OF HEALTH 

AND HUMAN SERVICES 

Public Health Service 

National Institutes of Health 

National Cancer Institute 
MONOGRAPH


SMOKING

AND

TOBACCO

CONTROL

12 

Population 

Based Smoking 

Cessation 

Proceedings of a Conference 

on What Works to 

Influence Cessation in the 

General Population 

U.S. DEPARTMENT OF HEALTH


AND HUMAN SERVICES


Public Health Service


National Institutes of Health


National Cancer Institute

Smoking and Tobacco Control Monographs Issued to Date 

Strategies to Control Tobacco Use in the United States: a blueprint for public health action in the 1990’s. Smoking 

and Tobacco Control Monograph No. 1. Bethesda, MD: U.S. Department of Health and Human Services, 

Public Health Service, National Institutes of Health, National Cancer Institute. NIH Publication No. 92-3316, 

December 1991. 

Smokeless Tobacco or Health: An international perspective. Smoking and Tobacco Control Monograph No. 2. 

Bethesda, MD: U.S. Department of Health and Human Services, Public Health Service, National Institutes of 

Health. NIH Publication No. 92-3461, September 1992. 

Major Local Tobacco Control Ordinances in the Unites States. Smoking and Tobacco Control Monograph No. 3. 

Bethesda, MD: U.S. Department of Health and Human Services, Public Health Service, National Institutes of 

Health. NIH Publication No. 93-3532, May 1993. 

Respiratory Health Effects of Passive Smoking: Lung cancer and other disorders. The Report of the U.S. Environmental 

Protection Agency. Smoking and Tobacco Control Monograph No. 4. Bethesda, MD: U.S. Department of Health 

and Human Services, Public Health Service, National Institutes of Health, NIH Publication No. 93-3605, 

August 1993 

Tobacco and the Clinician. Interventions for Medical and Dental Practice. Smoking and Tobacco Control 

Monograph No. 5. Bethesda, MD: U.S. Department of Health and Human Services, Public Health Service, 

National Institutes of Health. NIH Publication No. 94-3693, January 1994. 

Community-based Interventions for Smokers: The COMMIT Field Experience. Smoking and Tobacco Control 

Monograph No. 6. Bethesda, MD: U.S. Department of Health and Human Services, Public Health Service, 

National Institutes of Health. NIH Publication No. 95-4028, August 1995. 

The FTC Cigarette Test Method for Determining Tar, Nicotine, and Carbon Monoxide Yields of U.S. Cigarettes. Report 

of the NCI Expert Committee. Smoking and Tobacco Control Monograph No. 7. Bethesda, MD: U.S. 

Department of Health and Human Services, Public Health Service, National Institutes of Health. NIH 

Publication No. 96-4028, August 1996. 

Changes in Cigarette Related Disease Risks and Their Implication for Prevention and Control. Smoking and Tobacco 

Control Monograph No. 8. Bethesda, MD: U.S. Department of Health and Human Services, Public Health 

Service, National Institutes of Health. NIH Publication No. 97-4213, February 1997. 

Cigars. Health Effects and Trends. Smoking and Tobacco Control Monograph No. 9. Bethesda, MD: U.S. 

Department of Health and Human Services, Public Health Service, National Institutes of Health. NIH 

Publication No. 98-4302, February 1998. 

Health Effects of Exposure to Environmental Tobacco Smoke. The Report of the California Environmental Protection 

Agency. Smoking and Tobacco Control Monograph No. 10. Bethesda, MD: U.S. Department of Health and 

Human Services, Public Health Service, National Institutes of Health, National Cancer Institute. NIH 

Publication No. 99-4645, August 1999. 

State and Local Legislative Action to Reduce Tobacco Use. Smoking and Tobacco Control Monograph No. 11. 

Bethesda, MD: U.S. Department of Health and Human Services, National Institutes of Health, National 

Cancer Institute, NIH Publication No. 00-4804, August 2000. 
Acknowledgments


Population Based Smoking Cessation: Proceedings of a Conference on 

What Works to Influence Cessation in the General Population was developed 

under the editorial direction of Donald R. Shopland, Special Expert, 

Tobacco Control Research Branch, National Cancer Institute, Bethesda, 

Maryland. 

This monograph is the result of a conference and set of analyses 

commissioned and funded jointly by the National Cancer Institute and the 

Tobacco Control Section of the California Department of Health Services. 

The conference was held on June 8 and 9, 1998 in San Diego, California. 

Draft sections of this volume were subjected to peer review and revision, 

and the resultant draft of the entire volume was also subjected to peer 

review and revision. 

The senior scientific editor for this monograph was David M. 

Burns, M.D., Professor of Medicine, University of California San Diego, San 

Diego, California. Richard H. Amacher was the managing editor of the 

volume and project director for the KBM Group Inc., Silver Spring, 

Maryland, who contracted with the National Cancer Institute to produce 

this volume. William Ruppert, M.S., Health Program Specialist, Tobacco 

Control Section, California Department of Health Services, Sacramento 

California, was the project officer for the contract with the Tobacco Control 

Section, California Department of Health Services. 

Chapter 1 

Chapter 2 

Smoking Cessation: 

Recent Indicators of 

What’s Working at a 

Population Level 

Cessation and Cessation 

Measures Among Adult 

Daily Smokers: National 

and State-Specific Data 

David M. Burns, M.D. 

Professor of Medicine 

School of Medicine 

University of California at 

San Diego 

San Diego, CA 

David M. Burns, M.D. 

Professor of Medicine 

School of Medicine 

University of California at 

San Diego 

San Diego, CA 

i 
Smoking and Tobacco Control Monograph No. 12 

Chapter 3	 Restrictions on 

Smoking in the 

Workplace 

Christy M. Anderson, B.S.


Statistician


Tobacco Control Policies


Project 

University of California at 

San Diego 

San Diego, CA 

Michael Johnson, Ph.D.


California Department of 


Health


Tobacco Control Section


Sacramento, CA


Jacqueline M. Major, M.S.


Statistician


Tobacco Control Policies 


Project 

University of California at 

San Diego 

San Diego, CA 

Lois Biener, Ph.D.


Senior Research Fellow


University of Massachusetts


Boston, MA


Jerry Vaughn, B.S.


Programmer/Analyst


Tobacco Control Policies 


Project 

University of California at 

San Diego 

San Diego, CA 

Thomas G. Shanks, M.P.H., M.S.


Principal Statistician


Tobacco Control Policies 


Project 

University of California at 

San Diego 

San Diego, CA 

David M. Burns, M.D. 

Professor of Medicine 

School of Medicine 

University of California at 

San Diego 

San Diego, CA 

ii 
Acknowledgements 

Chapter 4	 Population Impact of 

Clinician Efforts to 

Reduce Tobacco Use 

Chapter 5	 Impact of Medications 

on Smoking Cessation 

Thomas G. Shanks, M.P.H.,


M.S.


Principal Statistician


Tobacco Control Policies 


Project 

University of California at 

San Diego 

San Diego, CA 

Jacqueline M. Major, M.S.


Statistician


Tobacco Control Policies 


Project 

University of California at 

San Diego 

San Diego, CA 

Kathryn B. Gower, B.S. 

Statistical Assistant 

Tobacco Control Policies 

Project 

University of California at 

San Diego 

San Diego, CA 

Donald R. Shopland


Coordinator


Smoking and Tobacco 


Control Program (STCP)


National Cancer Institute


Bethesda, MD


Jack F. Hollis, Ph.D.


Kaiser Permanente


Center for Health Research


Portland, OR


John R. Hughes, M.D.


Professor


Department of Psychiatry


University of Vermont


Burlington, VT


David M. Burns, M.D.


Professor of Medicine


School of Medicine


University of California at


San Diego


San Diego, CA


iii 
Smoking and Tobacco Control Monograph No. 12 

Chapter 6	 Effect of Cost on 

Cessation 

Chapter 7 Self-Help Materials 

Chapter 8	 Telephone Quitlines for 

Smoking Cessation 

Dave Sweanor, J.D.


Senior Legal Council


Non-Smokers’ Rights Assoc.


Smoking and Health Action


Foundation


Ottowa, ON


David M. Burns, M.D.


Professor of Medicine


School of Medicine


University of California at


San Diego


San Diego, CA


Christy M. Anderson, B.S.


Statistician


Tobacco Control Policies


Project 

University of California at 

San Diego 

San Diego, CA 

Susan J. Curry, Ph.D.


Director


Center for Health Studies


Group Health Cooperative


of Puget Sound


Seattle, WA


Jacqueline M. Major, M.S.


Statistician


Tobacco Control Policies 


Project 

University of California at 

San Diego 

San Diego, CA 

Shu-Hong Zhu, Ph.D. 

Assistant Professor 

Cancer Prevention and 

Contol Center 

University of California at 

San Diego 

San Diego, CA 

iv 
Acknowledgements 

Chapter 9 

Chapter 10 

Chapter 11 

Mass Media in Support 

of Smoking Cessation 

Community-Wide 

Interventions for 

Tobacco Control 

Interaction of 

Population-Based 

Approaches for Tobacco 

Control 

Robert E. Sparks, Ph.D. 

Associate Professor 

School of Human Kinetics 

University of British 

Columbia 

Vancouver, BC 

Lawrence W. Green, Dr.P.H. 

Institute of Health 

Promotion Research 

University of British 

Columbia 

Vancouver, BC 

K. Michael Cummings, 

Ph.D., M.P.H. 

Chairman 

Department of Cancer 

Prevention, Epidemiology, 

and Biostatistics 

Roswell Park Cancer 

Institute 

Buffalo, NY 

Howard A. Fishbein, 

Dr.P.H., M.P.H. 

The Gallup Organization 

Rockville, MD 

Jennifer B. Unger, Ph.D. 

Research Assistant Professor 

Institute for Prevention 

Research 

University of Southern 

California 

Los Angeles, CA 

C. Anderson Johnson, Ph.D.


Director


Institute for Prevention


Research 

University of Southern 

California 

Los Angeles, CA 

v 
Smoking and Tobacco Control Monograph No. 12 

Louise Ann Rohrbach, M.D. 

Research Assistant Professor 

Institute for Prevention 

Research 

University of Southern 

California 

Los Angeles, CA 

Beth Howard-Pitney, Ph.D. 

Stanford Universty 

Stanford, CA 

Tess Boley Cruz, Ph.D. 

University of Southern 

California 

Los Angeles, CA 

Clyde Dent, Ph.D. 

University of Southern 

California 

Los Angeles, CA 

Kim Ammann Howard, Ph.D.


Stanford Universty


Stanford, CA


We gratefully acknowledge the following distinguished scientists, 

researchers, and others, both in and outside the Government, who contributed critical reviews or assisted in other ways: 

Dileep G. Bal, M.D.


Chief


Cancer Control Branch


California Dept. of Health Services


Sacramento, CA


Neal Benowitz, M.D.


Professor of Medicine


University of California at


San Francisco


San Francisco, CA


Lester Breslow, M.D., M.P.H.


Professor


University of California at


Los Angeles


Los Angeles, CA


Carolyn Celebuki, Ph.D.


Director of Research and Evaluation


Massachusetts Dept. of Public 


Health


Boston, MA


Gregory Connolly, D.M.D, M.P.H.


Director


Tobacco Control Program


Massachusetts Dept. of Public 


Health


Boston, MA


Jeri Day, M.P.H.


Health Education Consultant


California Dept. of Education


Sacramento, CA


vi 
Acknowledgements 

Richard Daynard, Ph.D., J.D.


President


Tobacco Control Resource Center


Northeastern University


Boston, MA


Michael Fiore, M.D.,M.P.H.


Director


Center for Tobacco Research and


Intervention


University of Wisconsin


Madison, WI


Karen Gerlach, Ph.D., M.P.H.


Program Officer


Robert Wood Johnson Foundation


Princeton, NJ


Gary Giovino, Ph.D.


Research Scientist


Roswell Park Cancer Institute


Buffalo, NY


Thomas Glynn, Ph.D.


Director of Cancer Science & Trends


American Cancer Society


Washington, DC


Ellen Gritz, Ph.D.


Chair


Department of Behavioral Science


MD Anderson Cancer Center


Houston, TX


Suzanne Hildebrand-Zanki, Ph.D.


Director


Tobacco-Related Disease Program


University of California


Oakland, CA


Rosalie Lopez Hirano


Office Chief


Tobacco Education & Prevention 


Program


Arizona Dept. of Health Services


Phoenix, AZ


Holly Hoegh


Research Scientist


Cancer Surviellance Section


California Dept. of Health Services


Sacramento, CA


Thomas P. Houston, M.D.


Director


Dept. of Preventive Medicine


American Medical Association


Chicago, IL


Corinne Husten, M.D., M.P.H.


Office of Smoking and Health


Centers for Disease Control and 


Prevention


Atlanta, GA


Marta Induni


Research Associate


Cancer Surveillance Section


California Dept. of Health Services


Sacramento, CA


Thomas J. Kean, M.P.H.


President


Strategic Health Concepts


Englewood, CO


Rae Kine, B.S.


Consultant


Healthy Kids Program


California Dept. of Education


Sacramento, CA


Max Larsen, Ph.D.


Senior Vice President


The Gallup Organization


Rockville, MD


Robert Leischow, M.P.H.


Projects Administrator


Tobacco Education Prevention


Program


Arizona Dept. of Health Services


Phoenix, AZ


Jon Lloyd, M.A.


Tobacco Control Section


California Dept. of Health Services


Sacramento, CA


Gerardo Marin, Ph.D.


Senior Associate Dean


College of Arts & Sciences


University of San Francisco


San Francisco, CA


vii 
Smoking and Tobacco Control Monograph No. 12 

Jesse Nodora, Dr.P.H.


Local Projects Administrator


Arizona Dept. of Health Services


Phoenix, AZ


C. Tracy Orleans, Ph.D. 

Senior Program Officer 

The Robert Wood Johnson 

Foundation


Princeton, NJ


Pamela Powers, M.P.H.


Program Directors


Program for Nicotine & Tobacco


Research


Universiy of Arizona


Tuscon, AZ


Dorothy Rice, B.A., Sc.D.


Professor Emeritus


Institute for Health and Aging


University of California at


San Francisco


San Francisco, CA


Sue Roberts, M.S.


Local Program Evaluation


Tobacco Control Section


California Dept. of Health Services


Sacramento, CA


April Roeseler, M.S.P.S.


Chief of Local Programs Unit


Tobacco Control Section


California Dept. of Health Services


Sacramento, CA


William Ruppert, M.S.


Health Program Specialist


Tobacco Control Section


California Dept. of Health Services


Sacramento, CA


Carol Russell, M.P.H.


Chief of Program Services


Tobacco Control Section


California Dept. of Health Services


Sacramento, CA


Zenen Salazar, B.Ed.


Health Educator


Program for Nicotine & Tobacco


Research


University of Arizona


Tuscon, AZ


Robin Shimizu, M.P.H.


Assistant Chief


Tobacco Control Section


California Dept. of Health Services


Sacramento, CA


Jana Kay Slater, Ph.D.


Independant Consultant


Comprehensive School Health 


Program


California Dept. of Education


Sacramento, CA


Colleen Stevens, M.S.W.


Chief, Media Campaign Unit


Tobacco Control Section


California Dept. of Health Services


Sacramento, CA


Lawrence Wallack, Ph.D., Dr.P.H.


Professor


School of Public Health


University of California at Berkeley


Berkeley, CA


Ken Warner, Ph.D.


Department of Health Management


School of Public Health


University of Michigan


Ann Arbor, MI


viii 
Acknowledgements 

The editors and STCP staff members gratefully acknowledge the following individuals at the Tobacco Control Policies Project, University of 

California San Diego, San Diego, California, for their assistance with the 

scientific data and preparation of the manuscript: 

Sharon Buxton 

Administrative Assistant 

Robert W. Davignon, M.S. 

Production Editor 

Don F. Harrell 

Administrative Assistant 

Kristina M. Webb 

Project Assistant 

Finally, the editors and the STCP staff members would like to acknowledge the contributions of the following staff members at KBM Group, 

Inc., Silver Spring, Maryland, who provided technical and editorial assistance in the preparation of this monograph: 

Brian E. Steyskal 

Editor/Graphic Designer 

Cynthia M. DeLano 

Assistant Editor 

Ann L. Kreske 

Editorial Assistant 

Yaa Nsia Opare-Phillips 

Administrative Assistant 

Analyses of the data presented in this volume were supported, in part, 

by a contract from the Department of Health Services, Tobacco Control 

Section (Contract #96-26468). The analyses, interpretations, and conclusions are those of the authors, editors and are the result of the peer review 

process used to produce this volume. They are not necessarily those of the 

California Department of Health Services. 

ix 
Contents


Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .i


Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .xi


Chapter 1: Smoking Cessation: Recent Indicators of What’s 


Working at a Population Level . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1


Introduction and Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1


What Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7


Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23


References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .23


Chapter 2: Cessation and Cessation Measures among Adult 


Daily Smokers: National and State-Specific Data . . . . . . . . . . . . .25


Cessation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .25


Measures of Cessation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .27


Multivariate Logistic Modeling of Cessation Data . . . . . . . . . . . . . .43


Cessation in California . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .50


Smoking Behavior in Massachusetts: 1993 to 1997 . . . . . . . . . . . . .55


Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .57


Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .58


Appendix 1 (Tables 2-7 through 2-20) . . . . . . . . . . . . . . . . . . . . . . .61


Appendix 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .93


References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .97


Chapter 3: Restrictions on Smoking in the Workplace . . . . . . . . . . .99


Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .99


Changes in Smoking Behavior with Implementation


of Smoking Restrictions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .104


Cessation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .111


Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .117


References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .126


Chapter 4: Population Impact of Clinician Efforts


to Reduce Tobacco Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .129


Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .129


Rationale for Clinician-Delivered Tobacco Interventions . . . . . . .129


How Many Patients Receive Tobacco Advice and


Assistance, and Do They Quit? . . . . . . . . . . . . . . . . . . . . . . . . .131


Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .152


References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .153


xi 
Smoking and Tobacco Control Monograph No. 12 

Chapter 5: Impact of Medications on Smoking Cessation . . . . . . . .155


Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .155


Use of Medications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .156


Efficacy/Effectiveness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .158


Interpretation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .162


Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .163


References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .163


Chapter 6: Effect of Cost on Cessation . . . . . . . . . . . . . . . . . . . . . . . .165


Background on the Role of Price/Taxation . . . . . . . . . . . . . . . . . . .165


Overview of Recent Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .166


The Canadian Experience . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .168


Effects of Cost on Measures of Cessation . . . . . . . . . . . . . . . . . . . .170


Long-Term Successful Cessation . . . . . . . . . . . . . . . . . . . . . . . . . . .170


Measures of Cessation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .171


Caveats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .172


Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .174


Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .175


References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .177


Chapter 7: Self-Help Materials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .179


Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .179


Utilization of Self-Help Materials . . . . . . . . . . . . . . . . . . . . . . . . . .180


Impact of Self-Help Materials on Smoking Cessation . . . . . . . . . .184


General Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .186


References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .187


Chapter 8: Telephone Quitlines for Smoking Cessation . . . . . . . . . .189


The Strengths of Telephone Quitlines . . . . . . . . . . . . . . . . . . . . . . .189


The Use of Telephone Quitlines . . . . . . . . . . . . . . . . . . . . . . . . . . .190


Efficacy of Telephone Quitlines . . . . . . . . . . . . . . . . . . . . . . . . . . .192


An Area for Synergy: Telephone Quitline as a Support


for Physician Advice and Adjuvant Treatment for NRT . . . . . .195


Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .196


References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .196


Chapter 9: Mass Media in Support of Smoking Cessation . . . . . . . .199


Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .199


California and Massachusetts Antismoking 


Advertising Campaigns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .200


Stanford Five-City Project (FCP) . . . . . . . . . . . . . . . . . . . . . . . . . . .203


Community Intervention Trial for Smoking 


Cessation (COMMIT) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .207


Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .209


References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .214


xii 
Contents 

Chapter 10: Community-Wide Interventions for 


Tobacco Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .217


Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .217


Are These Assumptions Correct? . . . . . . . . . . . . . . . . . . . . . . . . . . .217


Do Community-Wide Interventions Work? . . . . . . . . . . . . . . . . . .218


What Lessons Have We Learned? . . . . . . . . . . . . . . . . . . . . . . . . . .219


Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .220


References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .221


Chapter 11: Interaction of Population-Based Approaches


to Tobacco Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .223


Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .223


Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .223


Framework for Our Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .223


Independant Evaluation Methods . . . . . . . . . . . . . . . . . . . . . . . . . .225


Sampling Schemes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .225


Data Collection Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .226


Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .226


Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .227


Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .233


References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .233


xiii 
Smoking Cessation: Recent 

Indicators of What’s Working 

at a Population Level 

David M. Burns 

INTRODUCTION Smoking cessation is the principal means by which a current 

AND OVERVIEW cigarette smoker can alter his or her future risk of disease 

(U.S.DHHS, 1990). Prevention of smoking initiation among adolescents can 

reduce smoking prevalence, but adolescents contribute little to rates of 

smoking-related illness until they have been smoking for 30 or more years. 

Cessation is often examined at the individual level in order to determine the effects of cessation interventions or to define individual predictors 

of who will or will not be successful in their cessation attempts. However, 

for these individual effects to create a substantive public health benefit, 

they must sum to create a significant change at the population level. 

Powerful interventions that affect only a few individuals will have little 

impact on disease rates, whereas weaker interventions that impact large 

numbers of smokers will have important and cumulative effects on disease 

rates. In addition, many interventions (e.g., price increases, changes in 

social norms, etc.) are delivered to the population as a whole rather than to 

individual smokers one at a time, and it is these population-based interventions that have formed the core of the tobacco control efforts currently 

underway in California, Massachusetts, and several other states. 

This volume examines cessation at the population level. By population 

level, we mean that all segments of society form the denominator for evaluation of the effectiveness of tobacco control interventions. Therefore, this 

volume relies heavily on representative surveys of smoking behaviors in 

state and national populations. By doing so, it defines measures of cessation 

that can be used to assess the effects of tobacco control programs or public 

policy changes on smoking behavior. It then uses those measures to identify who is quitting, who is being successful, who is being exposed to various 

tobacco control interventions, and which tobacco control interventions are 

proving effective. 

Can We Change A persistently high smoking prevalence (CDC, 2000), coupled 

Cessation Rates in with the low rates of success of those trying to quit, is discourthe Population? aging to those interested in tobacco control and has led to 

suggestions that tobacco control efforts should be redirected to focus predominantly on preventing smoking initiation during adolescence. This pessimism is not supported by actual experience with smoking cessation over 

the past several decades. Currently, almost 50 percent of all of those who 

have ever smoked are former smokers (CDC, 2000). 

1

Smoking and Tobacco Control Monograph No. 12 

This high rate of cessation is neither accidental nor a result of the aging 

of the smokers in the population, nor is it due to other demographic shifts. 

Figure 1-1 presents cessation rates for White males born during sequential 

5-calendar-year periods (birth cohorts) as they advance in time (and age) 

over the period from 1940 to 1988. Prior to the mid 1950s, cessation was 

uncommon at any age. With the scientific demonstration of the risks associated with smoking during the mid-1950s, and with widespread press coverage of lung cancer risks for smokers, cessation rates began to increase 

(Figure 1-1). 

These observations provide strong evidence that cessation is not simply 

a naturally occurring consequence of aging. It has changed dramatically 

across all age groups following identification of, and widespread education 

about, the risks caused by smoking. Some individuals clearly do respond to 

risk information with a change in behavior, and the number of individuals 

responding is sufficient to influence cessation rates in the population; but 

the size of the effect on the population is modest and leaves the vast majority of smokers continuing to smoke. 

Data on cessation rates over time also suggest that public health efforts 

to change smoking behavior can have an effect above and beyond the 

effect of information on risk alone. During the period from 1967 to 1970, 

anti-smoking television spots were broadcast in large numbers as a result of 

an FCC ruling that required the spots as a fairness doctrine in response to 

broadcast cigarette advertising (U.S.DHHS, 1989; Warner, 1989). Together 

with this counter-advertising, there was a substantial effort on the part of 

many professional and voluntary health organizations to help smokers quit. 

The result of this media-led activity was a substantial increase in cessation 

rates across all age and racial groups and in both genders (Burns et al., 

1997). When cigarette advertisements were removed from the broadcast 

media, and anti-smoking spots nearly disappeared as well (Lewit et al., 

1981), cessation rates leveled off or declined. The temporal association of 

change in cessation rates with these events strongly suggests that deliberate 

programmatic efforts can alter smoking behavior at the population level 

and provides one cornerstone of the foundation for current comprehensive 

tobacco control campaigns. 

Since the 1970s, our understanding of effective tobacco control strategies has gradually shifted away from a focus solely on the individual smoker and toward a focus on changing the environment within which the 

smoker smokes (NCI, 1991). Initial efforts focusing on educating the smoker and providing clinic-based cessation assistance have been augmented by 

efforts to change community norms, increase the cost of cigarettes, restrict 

where smoking is allowed, and provide societal based persistent and 

inescapable messages to quit coupled with support for cessation. This shift 

is toward -multi-component programs that address norms as well as the 

needs of individuals. These concepts are reflected in the current state-based 

comprehensive tobacco interventions funded by the NCI, Centers for 

Disease Control and Prevention (CDC), and Robert Wood Johnson 

Foundation (CDC, 1999a). In California and Massachusetts, these comprehensive approaches have been funded at substantial levels for several years 

2 
Chapter 1 C Y Cessation Rate (percentage) NH D Figure 1-1 Annual Smoking Cessation Rates by Calendar Year for 5-Year Birth Cohorts of White Males Born between 1900 and 1929 

3

Smoking and Tobacco Control Monograph No. 12 

(since 1989 in CA, and 1993 in MA). More recently, Arizona, Oregon, and 

Florida have developed programs, and the Master Settlement Agreement 

between the State Attorneys General and the tobacco industry will provide 

resources that some other states may use to initiate their own programs. 

The programs in California and Massachusetts have been associated 

with reductions in various measures of smoking behavior (Biener et al., 

1997; Pierce et al., 1998), and their program elements are being replicated 

in other states. This volume examines what we know about the components and the effects of these existing programs in an effort to provide 

guidance to states as they develop or modify their own tobacco control 

campaigns. The analyses presented here are limited to the areas where we 

have data, and this limitation makes it difficult to evaluate every aspect of 

the current programs. In particular, the community organization components of the programs—widely accepted as a critical foundation for any successful tobacco control effort—are difficult to quantify and, therefore, are 

examined only in passing in this volume. 

Measures of Cessation Traditional measures of cessation include cessation 

and Changes in attempts, and measures of cessation success for various 

Cessation Nationally periods of time following a quit attempt, as well as cumulative measures of cessation such as the fraction of ever smokers who are 

currently former smokers. The cessation measures presented in this monograph differ somewhat from these traditional measures in order to improve 

their utility in evaluating different components of tobacco control programs. Traditional survey measures of cessation are intended to measure 

rates of cessation in the entire population of smokers and, therefore, must 

include all smokers in the denominator. We limit our analyses to those 

smokers of age 25 and older to ensure that changes in observed behavior 

are not related to the smokers still being in the process of becoming regular 

smokers. For similar reasons, and because occasional smokers may respond 

differently to a question about being off cigarettes for 24 hours or more (the 

definition of a quit attempt), we eliminate all those who were not daily 

smokers 1 year prior to the survey. 

The goal of these limitations is to relate recent exposures to tobaccocontrol influences to recent cessation behavior; thus, cessation activity 

within the last year is the focus of all of the measures. During the year preceding the survey, individuals who were daily smokers 1 year prior to the 

survey may have quit and relapsed, may have become an occasional smoker, may have become a former smoker, or may have become a former smoker of 3 or more months’ duration. This set of measures allows examination 

of cessation attempts and cessation success as separate measures, and it 

allows independent assessment of those factors that promote cessation 

activity and those factors that enable cessation success. 

Figure 1-2 presents the above measures for the United States as measured by the Current Population Survey (CPS) for the years 1992/93 and 

1995/96 (see Chapter 2). There is a clear and statistically significant decline 

in cessation activity and cessation success between these two surveys. The 

decline is statistically significant for each of the measures of cessation activ4

Chapter 1 

Figure 1-2 

1992/93 and 1995/96 CPS: Percentage of Daily Smokers (Age 25+ Years) 1 Year Prior 

to the Survey Who Reported Some Change in Their Smoking Status during that Year 

0

10

15

20

25

30

35

40 Quit 

3+ Months

Short Term

(Quit <3 Months)

Occasional 

Smoker

Failed 

Quit Attempt

992/93 CPS 1995/96 CPS

Former 

Smokers

Current Smokers

Who Made Some

Change

Percentage

ity and cessation success, with the exception of “becoming an occasional 

smoker.” The decline is present for both genders and for all age, race, and 

educational groups. The decline in cessation is proportionately greater 

among those with higher levels of income. This decline in cessation contributes to the observed absence of a decline in per-capita cigarette consumption in the United States during those same years and is a major public health concern (CDC, 1999b). 

When the demographic correlates of cessation are examined in the CPS 

(see Chapter 2), smokers aged 65 years and older are much less likely to 

make a cessation attempt than younger smokers, but they are much more 

likely to be successfully quit for 3 or more months. Thus, older smokers 

appear to be less likely to attempt to change their smoking behavior, but 

when they do, they are substantially more likely to be successful. 

Differences between racial and ethnic groups are less pronounced. AfricanAmericans have significantly higher rates of cessation activity than nonHispanic Whites, but they also have significantly lower rates of being quit 

for 3 or more months. Asian/Pacific Islanders also have significantly higher 

rates of cessation activity compared to non-Hispanic Whites, with a nonsignificant lower rate of 3+ month cessation success. 

Rates of both cessation activity and 3+ month cessation success are significantly higher among smokers with higher levels of educational attainment. A similar pattern is seen with level of income, where both cessation 

activity and 3+ month cessation success are significantly higher among 

5 
Smoking and Tobacco Control Monograph No. 12 

smokers with higher family incomes. The percentage of all cessation activity that has resulted in 3+ months of successful cessation is relatively uniform across the middle strata of family income, but it is higher for the top 

income stratum and lower for the lowest income stratum. 

There is a clear decline in cessation activity with increasing number of 

cigarettes smoked per day; however, the picture for cessation success is less 

clear. Those who reported smoking 1-4 cigarettes per day 1 year prior to the 

survey were significantly more likely to be successfully quit for 3+ months 

than were smokers who reported smoking 5-14 or 15-24 cigarettes per day. 

However, once the category of 1-4 cigarettes per day is excluded, there is no 

trend of lower likelihood of 3+ month successful cessation with increasing 

number of cigarettes smoked per day across the remaining number of cigarettes per day categories. These data suggest that, within that group of 

smokers who are likely to be dependent smokers (those who smoke 5+ cigarettes per day), heavier smokers are less likely to attempt to quit. However, 

when these heavier smokers do attempt to quit, they may be as likely to be 

successful in that attempt (i.e., quit for 3 or more months) as those who 

smoke less than one pack per day. These cross-sectional data need to be 

interpreted with caution in the light of other data from a 5-year longitudinal follow-up of current smokers in the COMMIT study (Hymowitz et al., 

1997), which show a consistent decline in successful cessation with increasing number of cigarettes smoked per day. The reasons for the differences 

between these two forms of analyses are unclear. 

Comparison of California Since California and Massachusetts have conducted 

and Massachusetts to the large, well-funded tobacco control interventions 

Remaining States over the period covered by the Current Population 

Surveys, one measure of the success of these tobacco control efforts is to 

examine whether cessation rates are higher in these states compared to the 

remaining states where interventions have been more modest. Because 

smoking prevalence and cessation are influenced by differences between 

states in demographic characteristics and number of cigarettes smoked per 

day, we examined measures of cessation using multivariate logistic regression analyses to control for those variables (see Chapter 2). 

Both California and Massachusetts had statistically significantly higher 

cessation activity compared to other states. Massachusetts had an increase 

in cessation attempts, and California had an increase in the likelihood of 

becoming an occasional smoker. Both Massachusetts and California also 

had increases in the likelihood of becoming a former smoker in the last 

year compared to other states. The likelihood of achieving 3+ months of 

cessation success was also significantly higher in California, and higher 

with borderline significance (p = 0.051) for Massachusetts, when compared 

to the remaining states. 

These analyses demonstrate that California and Massachusetts had 

higher rates of cessation activity and cessation success when compared to 

the remaining states, and that the decline between surveys in cessation 

rates (particularly 3+ month successful cessation) is less in California than 

in the remaining states. While a national trend toward lower cessation 

6

Chapter 1 

activity occurred between 1992/93 and 1995/96, the impact of this trend 

was less pronounced in California and Massachusetts than in the remaining 

states. The higher rates of cessation activity and cessation success in 

California and Massachusetts provide evidence for a substantial impact of 

the tobacco control programs on cessation in these two states. 

WHAT WORKS The differences in cessation activity and success that exist in 

California and Massachusetts may support an overall effect of tobacco control programs on cessation, but they do little to define which components 

of the programs are working. In reality, it is probably never possible to 

definitively define the specific causal effects of a specific component of any 

of these programs because they are not delivered in isolation and because 

many of their effects may be created by synergistic interactions between 

program elements. However, by examining differences in cessation behaviors among individuals exposed or not exposed to different program elements, it is possible to identify those program components associated with 

increases in cessation activity and success. In addition, there are substantial 

variations across the states in public policies on tobacco, including taxes 

and restrictions on where people can smoke, and these differences can be 

compared to differences in rates of cessation to examine the association of 

these public policies and cessation. 

Demonstrations of association do not meet traditional standards for 

defining causal relationships. The randomized controlled trials needed to 

define a cause-and-effect relationship are impossible to undertake for most 

public policy changes, especially taxation. However, the linkage of 

policy/program exposure to successful cessation provides valuable assistance 

to those developing and refining tobacco control programs. Analyses can 

define both the reach of these components into the smoking population 

and the ability of the programs to affect under-served segments of the population. They also define the changes in the smoking behavior of smokers 

exposed to each policy. The combination of reach and effect generates an 

estimate of the likely public health impact of each component, and estimating the impact for the population can aid those who are responsible for 

program design in allocating resources across the various components of a 

comprehensive tobacco control strategy. 

Public Policy Changes in public policies on tobacco can affect large numbers of 

Components individuals at minimal cost. Increasing the cost of cigarettes 

through taxation (Chapter 6) and restrictions on smoking in the workplace 

(Chapter 3) are two public policy changes for which substantial bodies of 

information exist to define their effectiveness. 

Changes in the cost of cigarettes repeatedly have been demonstrated to 

be associated with a reduction in measures of total and per-capita consumption of cigarettes, and most studies have shown a relatively consistent 4 

percent decline in consumption for each 10 percent increase in price. More 

limited data are available for cessation, but there is a similarity in the annual changes in sales-weighted price of cigarettes and changes in calendar-year 

rates of 1 year successful cessation. In addition, when differences across 

states in cost of cigarettes are compared to differences in state-specific rates 

7

Smoking and Tobacco Control Monograph No. 12 

of cessation activity and success, controlling for differences in demographic 

factors and number of cigarettes smoked per day, there is a statistically significant association between higher cost and higher rates of both cessation 

activity and cessation success. These observations support the probability 

that an increase in the cost of cigarettes can influence not only short-term 

cessation attempts but also long-term cessation success. 

Recently, there has been a dramatic increase in the fraction of the working population protected by total bans on smoking in the workplace—from 

3 percent in 1986 to 64 percent in 1996. Multiple workplace observations 

have demonstrated that instituting a change in workplace smoking restrictions is accompanied by an increase in cessation attempts and a reduction 

in number of cigarettes smoked per day by continuing smokers. Once 

restrictions on smoking in the workplace have been successfully implemented, they continue to have effects. Observations from the longitudinal 

follow-up in the COMMIT trial and from cross-sectional data from the CPS 

both demonstrate that being employed in a workplace where smoking is 

banned is associated with a reduction in the number of cigarettes smoked 

per day and an increase in the success rate of smokers who are attempting 

to quit (see Chapter 3). There may also be a small effect of increasing the 

frequency with which smokers attempt to quit. General environmental 

norms about smoking may also play a role in promoting smoking cessation, 

since multivariate logistic regression analyses of the effect of workplace 

restrictions on smoking show small independent effects on cessation activity and success for both the actual restrictions in the smoker's workplace and 

for the average level of workplace restrictions in the state as a measure of 

the social norms regarding smoking (Figure 1-3). 

Pharmacological and The health care system has long been recognized as a logHealth Care Systems ical and potentially productive means of reaching smokInterventions ers with a cessation message and promoting their successful cessation. Approximately 70 percent of smokers see a physician each 

year, creating the potential to reach large numbers of smokers with a cessation message. The fraction of patients who report having been advised in 

the last year by their physician to quit smoking remains too low, but it has 

been increasing over time and now exceeds 50 percent of smokers. 

A variety of pharmacological approaches to smoking cessation have 

been approved by the FDA over the last two decades, including nicotine 

replacement therapy with gum, patches, nasal and oral inhalers, and bupropion. The patch and gum have been approved for over-the-counter sale 

since 1996. 

Both physician advice and pharmacological treatment have been established in controlled clinical trials to have a substantive effect on long-term 

smoking cessation, and this volume addresses the evidence for an effect at 

the population level. Once these interventions move beyond the controlled 

investigational setting where there is careful attention to the intervention 

protocol, it is likely that they are used in isolation, without the additional 

support provided in the clinical trial, and without such support, they may 

be less effective. Analyses of cessation activity and success among those 

8

Chapter 1 

1.000000

1.199997

1.399994

1.51.699991

State Ban +5%

Total Work Ban

Former 

(3+ months)

Former 

(any length)

Change Attempt

1.6

1.4

1.2

1.0

Cessation Measure

Odds Ratio

0.9

Figure 1-3 

Odds Ratios for Cessation Activity and Cessation Success for Smokers Working in 

Workplaces where Smoking Is Banned or Living in States where there Is High 

Prevalence of Workplace Smoking Bans—Data Source: 1995/96 CPS 

who were daily smokers 1 year prior to the 1996 California Tobacco Survey 

suggest that this may indeed be the case. When multivariate logistic regression analyses are performed on physician advice to quit, controlling for age, 

gender, level of education and income, race/ethnicity, and number of cigarettes smoked per day, there is a significant increase in the likelihood of 

making any change or making a cessation attempt among those receiving 

physician advice to quit, but there is no effect on likelihood of being successfully quit or being quit for 3 or more months (Figure 1-4). These data 

suggest that physician advice to quit in the real world is having an effect on 

cessation attempts, but little effect on long-term cessation success. 

A similar, but more encouraging, picture is evident when population 

data on the effect of nicotine patches and gum on cessation activity and 

success are examined. About 21 percent of those who tried to quit during 

the year previous to the 1996 California Tobacco Survey reported using 

nicotine patches or gum. When the current smoking status of all those who 

had made a quit attempt in the last 12 months is examined by the method 

of cessation assistance they reported using, 17 ± 2 percent of those who 

reported using no cessation assistance were former smokers at the time of 

the 1996 California Tobacco Survey. Of those who reported using patch or 

gum, either alone or in combination with other methods, 32 ± 5 percent 

were former smokers at the time of the survey. When the data were ana9 
Smoking and Tobacco Control Monograph No. 12 

0

2

Former Smoker 

(3+ months)

Former Smoker 

(any length)

Cessation 

Attempt

Any 

Change

Odds Ratio

Figure 1-4 

Multivariate Logistic Regression Analysis of Physician Advice to Quit on Cessation 

Activity and Success, Controlling for Gender, Race/Ethnicity, Education Level, Income 

Level, and Number of Cigarettes Smoked per Day—Data Source: 1996 CTS 

lyzed for those who had been quit for 3+ months at the time of the survey, 

results were less impressive (11.2 ± 2.6 percent for any use of patch or gum 

versus 9.7 ± 0.7 percent for no methods). The results for 3+ month cessation were not statistically different, possibly due to the small number of 

observations. Thus, examination of population-based data on gum and 

patch use suggest that they are a part of a large number of cessation 

attempts and are likely to make a substantive difference in the success rate 

of those attempts. However, the rates of success in the California population are well below those demonstrated in clinical trials, which suggests 

that there is substantial potential to increase both utilization of nicotine 

replacement products and the impact of these products on the success rate 

of smokers trying to quit. 

The gap between the effect achieved in clinical trials and the population data defines the potential that can be achieved if these modalities are 

delivered in a more comprehensive and organized manner and integrated 

with the other available cessation resources. If physician advice achieves the 

effectiveness demonstrated in clinical trials, it could result in as many as 

750,000 additional quits among the 35 million smokers who visit their 

physicians each year. If the success rate of pharmacological interventions 

matched that in the clinical trials, as many as 500,000 additional quits each 

year could be achieved, and an even greater number could be expected if 

larger numbers of smokers who are trying to quit could be persuaded to use 

pharmacological methods. 

10 
Chapter 1 

One approach to improving the results seen with physician advice and 

pharmacological interventions is to increase the fraction of smokers who 

receive advice or use cessation assistance. However, a great deal of research 

and programmatic support has already been committed to increasing the 

frequency with which physicians advise their smoking patients to quit, and 

this effort has shown a substantial increase in the fraction of patients who 

report that their physicians have advised them to quit. Independently, 

pharmaceutical companies have advertised the availability of cessation 

treatments extensively, which has resulted in substantial demand for and 

use of these interventions. Both of these efforts should continue, but it is 

not clear that additional resources would add to the number of individuals 

encountering either of these interventions, and given the limited evidence 

for a population-based effect on long-term cessation for either of these 

interventions as they are currently practiced, allocation of additional 

resources may not be appropriate. 

The principal limitation for these two interventions is not simply that 

they are utilized by too few individuals, but rather that the promise of these 

interventions as established in clinical trials is not fulfilled in their realworld applications. One of the differences between the clinical trials and 

real-world applications is that in clinical trials, the investigatory team 

ensures that the intervention is delivered according to the research protocol. These protocols often specify the content and extent of physician 

advice, directions on how to best use the medications, an offer of additional support if desired, and an expressed intent to follow up on the individual's cessation effort. Many of these components may be lacking in the realworld application of these clinically proven interventions, and this lack 

may explain at least part of the difference in effectiveness between the clinical trials and the population-based data. 

The answer to improving the effectiveness of these interventions may 

not lie in providing additional resources into the health care system to 

change physician behavior or additional promotional activity for pharmaceutical assistance with cessation. The answer may be to try to supplement 

these interventions by linking them with other components of comprehensive tobacco control interventions to improve their effectiveness. For example, linking physician advice with telephone hotline counseling, providing 

information on how to effectively utilize over-the-counter medications at 

community cessation events, and encouraging healthcare systems to view 

cessation as a population-based intervention delivered across all interactions with the system rather than as a process initiated exclusively by 

physicians. 

If other components of a comprehensive tobacco control program can 

be linked to physician advice and pharmacological assistance, it may be 

possible to provide the enhanced level of support and follow-up that characterized the delivery of these interventions in the clinical trial setting as 

these interventions are delivered to large segments of the population. When 

this was done within a large HMO setting (Curry et al., 1998), and when 

the barriers to accessing these modalities were reduced by lowering or eliminating the cost to smokers, cessation results were consistent with those 

11 
Smoking and Tobacco Control Monograph No. 12 

achieved in clinical trials. This experience suggests that the limited population effects of physician advice and pharmacological assistance represent 

limitations in the integration of the support provided to smokers who are 

trying to quit rather than absolute limitations of these approaches when 

they are utilized in the general population. The frequency with which 

physician advice is provided to smokers as well as the frequency with which 

smokers are using pharmacological assistance are both increasing, and these 

increases should be supported and encouraged. To obtain the maximal benefit from these effective interventions, we need to integrate them into 

health care delivery systems, link them to community cessation resources, 

and create an environment that encourages their access. Once these steps 

have been taken, dramatic improvements in population-based rates of cessation are possible (Curry et al., 1998). Moreover, it is reasonable to expect 

that the experience could be replicated in other settings. 

Self-Help Materials Two common components of most comprehensive tobacco 

and Media control programs are mass media messages and self-help 

materials. They share the ability to reach large numbers of individuals at 

relatively low cost. However, they are not autonomous interventions wherein goals are achieved simply by delivering the self-help materials to the 

smoker or by having the smoker exposed to the media message. Chapters 7 

and 9 make it clear that both of these tobacco control channels are just 

that, channels. They are methods by which other tobacco control interventions can be facilitated, reinforced, and publicized and by which agendas 

can be set; but in isolation, without integration into a more comprehensive 

approach to cessation, they have little effect. 

Evidence reviewed and presented in this volume supports the effectiveness of tobacco control programs that are media led and media intensive. It 

is impossible to separate the effect of the media from that of the rest of the 

program in those programs conducted in California and Massachusetts. 

This is partly due to the difficulty of causal attribution intrinsic to a multicomponent program conducted with a non-experimental approach. 

However, the media component of these programs was never conceptualized as an independent intervention, but rather was integrated into the 

overall campaigns to support multiple program goals. Both California and 

Massachusetts use media as one of several integral components of the programs targeting each of their major tobacco control campaign goals, rather 

than viewing media as a single independent intervention. As a result, the 

effects of media are melded with the impacts of the other components used 

to accomplish their goals. Media messages and strategies are defined by, and 

customized for, each of the campaign goals, and there is no single, independent, and unified media intervention that can be evaluated for its contribution as a separate tobacco control intervention. 

California and Massachusetts, and those media-led tobacco control trials that have demonstrated positive results, have used media in conjunction 

with community-based programs and public policy interventions. Media 

outlets have been used to set agendas for changing the restrictions on 

where smoking is allowed by educating smokers about the risks of second12

Chapter 1 

Figure 1-5 

Percentage of Current Smokers Making a Quit Attempt by Number of Media Modalities 

in which Smoking Messages were Recalled 

0

10

20

30

40

50

All 

Three

Some of 

the Three

None of 

the Three

990 1996

Survey Year

Percentage Who Made a Quit Attempt

1990: Television, radio, or newspaper/magazine in the last week 

1996: Television, radio, or billboard in the last month 

Source: 1990, 1996 California Tobacco Surveys 

hand smoke exposure, to trigger contemplation of cessation and cessation 

attempts in conjunction with referral to telephone counseling cessation 

services, and as one component of a multilevel campaign to de-normalize 

tobacco use. 

Figure 1-5 demonstrates an association between media recall and cessation attempts for the 1990 and 1996 California Tobacco Surveys as support 

for the role of media in triggering cessation attempts as part of an overall 

campaign to promote cessation and facilitate cessation success through 

community organization, referral to telephone counseling and other cessation assistance, and de-normalization of tobacco use. In this context, the 

role played by the media campaign is to encourage smokers to consider 

quitting and to trigger quit attempts. The media is supported by the changing community norms about smoking and by other persistent and 

inescapable messages to quit in the smoker's environment. 

Cessation success is facilitated by referral to cessation assistance and by 

other factors including restrictions on smoking in the workplace; therefore, 

media used in this way might not have a direct role in facilitating cessation 

success. Indeed, the same California surveys that showed an association 

between media exposure and cessation attempts, found no association with 

cessation success. Thus, were the media campaign to be viewed as a standalone intervention, it would be judged a failure, whereas, when the data are 

examined from the perspective of the media campaign as a component 

13 
Smoking and Tobacco Control Monograph No. 12 

intended to trigger cessation, with other aspects of the cessation intervention facilitating cessation success, the evidence is suggestive of a positive 

effect for those components of the overall media campaign that were targeting the smoker to promote cessation. 

A similar perspective emerges when the evidence on self-help programs 

is evaluated. When self-help programs are looked at as independent tobacco 

control interventions, multiple trials and several meta-analyses have 

demonstrated that they have little independent effect (see Chapter 7). 

However, the role of self-help materials may not be as an independent 

intervention, but as a component of other interventions. Self-help materials 

can provide information on the availability of assistance or on appropriate 

use of medication, or they can translate advice into different languages and 

initiate or maintain contact between smokers and those offering cessation 

assistance, among other roles. 

Community-Wide Changing the environment in which the smoker lives and 

Approaches and smokes to provide persistent and inescapable messages to 

Interaction across quit coupled with support for cessation have been goals of 

Channels most comprehensive tobacco control approaches to cessation (NCI, 1991). But accomplishing these goals has been problematic. 

Approaches that attempted to stimulate communities into promoting smoking cessation, such as COMMIT (see Chapter 10), have yielded only modest 

results among light to moderate smokers and have had no effect on heavy 

smokers. The limited impact of these community activation approaches 

may be due to an underestimate of the time required for them to be implemented sufficiently enough to impact smoking behavior and by their decision to intervene at the level of small communities, rather than at the state 

level where more powerful policy options such as tax increases are possible. 

However, almost all of the population-based interventions described in 

this volume impact smokers within their own communities, and all of the 

interventions are felt to be critically dependent on community norms about 

smoking behavior for their success. For example, changes in workplace 

restrictions are most often implemented in individual workplaces, and their 

passage into law is most often accomplished in local, rather than state jurisdictions. In addition, effective enforcement of restrictions on smoking in 

public locations and workplaces is dependent on the norms and expectations of smokers and nonsmokers alike. 

In California, where the largest number of local ordinances has been 

implemented, it has been community organization in support of these ordinances that has allowed for their successful adoption and implementation. 

It is impossible to conceive of this success taking place without the activation of the local communities, and this local community activation has 

resulted in the adoption of comprehensive restrictions on smoking at the 

state level in all workplaces, including bars. The evidence contained in this 

volume suggests that restrictions on smoking in the California workplaces 

play a substantive role in the higher rates of successful cessation in 

California, as compared to other states. However, even with this operational 

success at the community level, it would be difficult, given current designs, 

14

Chapter 1 

to demonstrate a direct association between the community activation that 

yielded the change in smoking restrictions and community-specific cessation rates. 

Telephone counseling services—first demonstrated to be effective in 

clinic settings—have also been provided in California, and there is considerable data supporting their effectiveness in promoting long-term successful 

cessation (see Chapter 8). However, these services are implemented over 

large areas, and it is difficult to see their impact in population-based surveys. Clearly, their utility is dependent on the resources provided in terms 

of the number of smokers that can be reached, but even more critically, 

their success is dependent on their links to other community organizations 

for referrals and to media- and community-based promotions for self-referral of smokers. Absent these community-based roots, telephone counseling 

services are of very limited utility, and their success must be attributed to 

their associated community-level programs as much as to the counseling 

itself. 

Several new approaches to providing individualized counseling have 

been developed, approaches that offer the potential to provide assistance to 

the general population of smokers. Interventions based on computer-driven 

algorithms that tailor the intervention and counseling provided to the individual smoker have been developed. The potential to provide this kind of 

tailored intervention over the internet—accessible in public locations where 

smokers would have access, on home computers, or on handheld devices 

provided to smokers—could overcome some of the resistance smokers traditionally have to more intensive, but more effective, smoking cessation 

interventions. 

As Chapter 11 demonstrates, there are synergies created across tobacco 

control intervention channels, and the matrix for those synergies is local 

programmatic activity. Exposure to individual tobacco control program elements was associated with changes in anti-smoking attitudes and behaviors, 

and these effects were significantly greater among those who were exposed 

to more than one component. 

What Works at the Any analytic approach is limited by the tools it uses and 

Population Level also by its perspective on the problem it studies. This volume is no different; we have chosen to utilize a set of measures of smoking 

cessation activity and success, and we have linked them to various measures 

of policy and programmatic tobacco control interventions. These associations provide measures of the independent relationships between exposure 

to tobacco control interventions and changes in smoking behavior, and 

these associations provide useful insights into what components of tobacco 

control program are working. However, this approach is less able to examine the interactions and synergies across these programmatic elements, synergies that may be critical for their success. 

15

Smoking and Tobacco Control Monograph No. 12 

With these caveats in mind, what can we say about what works? If the 

transtheoretical model of smoking behavior change (Prochaska and 

DiClemente, 1991) is used as a framework for examining population-based 

smoking cessation activity and success, one synthesis of how programmatic 

elements impact cessation is presented in Figure 1-6. This model postulates 

that smokers cycle through stages where they are disinterested in cessation, 

contemplate quitting, make a quit attempt, and are either successful or 

relapse to smoking. The relapse to smoking may be followed by a period of 

disinterest in cessation, or the smoker may think about making an additional cessation attempt. In the figure, cessation influences are at the stage 

of the process they are likely to influence, with internal personal characteristics presented inside the circle and external environmental influences presented outside the circle. 

Together, the formulation in Figure 1-6 and the evidence presented in 

this volume suggest that individual components of a comprehensive tobacco control program may affect the process of cessation at different stages. 

For example, mass-media campaigns may get smokers to think about the 

need to quit, physician advice may trigger a cessation attempt, and working 

in a smoke-free environment may facilitate cessation once a cessation 

attempt is made. An additional advantage of the formulation is that it facilitates identification of potential synergistic interactions among different 

program components. 

For example, physician advice seems to have a significant impact on the 

likelihood of a smoker making a quit attempt, but little effect on long-term 

cessation success; so as an isolated cessation intervention, it has little 

impact on smoking prevalence. But if the smokers who are attempting to 

quit can be linked to interventions that have their effect predominantly on 

improving long-term success (e.g., telephone counseling, clinic-based cessation assistance, or pharmacological treatment), the net effect on long-term 

cessation is likely to be substantially greater that the sum of the effects of 

these interventions offered independently. 

Public information about the risks of smoking, negative images about 

being a smoker, and physician warnings about the risk of smoking can all 

convert a smoker who is not interested in quitting into one who is considering a cessation attempt. Both the desire to set a good example for children and concerns about being dependent on smoking are reasons smokers 

give for wanting to quit; acute illness can often trigger cessation activity as 

well. 

Data presented in this volume demonstrate that smokers of younger 

ages, with higher levels of education and income, and who smoke fewer 

cigarettes per day are more likely to try to quit. In addition, this volume 

provides evidence to support the impact of media campaigns, restrictions 

on smoking in the workplace, physician advice to quit, and increased cost 

of cigarettes as population-based influences increasing cessation activity. 

The forces influencing smoking cessation attempts are different from 

those leading to longer term cessation success. For example, older smokers 

are less likely to report making a cessation attempt in the last 12 months, 

16

Chapter 1 PRECONTEMPLAT ON SHORT TERM SUCCESS CONTEMPLAT ON ACT ON LONG TERM SUCCESS A E m Am W m Am W CNG m TH N m C B CE m R m w M C m C m N B A AmG L E m O O A A w C D Y A G L E B G E m C A D m M C m W R NmC C E RmA Q Figure 1-6 The Process of Cessation 

17

Smoking and Tobacco Control Monograph No. 12 

but they are more likely to be successfully quit for 3 or more months based 

on that cessation attempt, suggesting that efforts to promote cessation 

among older smokers can yield important cessation benefits. In contrast, 

African-American smokers report rates of cessation activity in the last 12 

months similar to those of other racial and ethnic groups, but their likelihood of being successfully quit for 3 or more months based on that activity 

is significantly lower. 

A variety of environmental and interventional influences have substantial impacts on successful cessation. Evidence provided in the remaining 

chapters of this volume supports an effect of changes in cost and environmental restrictions on smoking in the workplace on long-term success. 

Nicotine replacement therapy is shown to be associated with improved cessation success at the population level, confirming its demonstrated effect in 

clinical trials. Telephone counseling and clinic-based cessation efforts have 

been established as effective interventions for those who receive them, but 

there is little evidence that they are reaching a sufficient proportion of the 

smoking population to effect cessation at the population level. Physician 

advice—which has also been demonstrated effective for long-term cessation 

in clinical trials and shows a strong association with cessation activity in 

population data—appears to have little effect on cessation success in the 

overall population, at least as it is currently being practiced. 

Quantifying the Figure 1-7 presents a simplified model of the cessation 

Effect of Population- process, focusing on those interventions examined in subBased Cessation sequent chapters of this monograph. The evidence presentInterventions ed suggests that the principal population-based cessation 

effect of physician advice and media campaigns is on promoting cessation 

attempts, with less evidence supporting an effect of these interventions on 

longer term cessation success. In contrast, the predominant effects of 

restrictions on where smoking is allowed, increasing cost of cigarettes, pharmacological interventions, and comprehensive tobacco-control campaigns 

seem to be in promoting longer term cessation success. 

The analyses presented in subsequent chapters are often formulated as 

odds ratios for cessation activity or success, and therefore it is possible to 

estimate the population-based impact of these interventions using the fraction of the population exposed to the intervention and the difference in 

cessation attempts or success between the exposed and non-exposed populations. Estimates derived from the subsequent chapters in this monograph 

are presented in Table 1-1 for comprehensive tobacco-control programs, 

physician advice, and bans on smoking in the workplace. In addition, estimates developed in subsequent chapters are utilized for physician advice 

(Chapter 4), use of medication (Chapter 5), and increases in taxes (Chapter 

6). The goal is to provide a rough comparison of the effects on cessation 

across these modalities, with the understanding that effects presented for 

one intervention may contain direct and synergistic effects from other 

interventions, and therefore, the numbers presented are not mutually 

exclusive cessation effects. 

18

Chapter 1 SMOKER QU T SUCCESSFUL CESSAT ON Con emp a on T h n H n Phy n A v M n C R n n m k n Ph m Th y C m h n v T C n P m R ap P v n on Figure 1-7 Population Based Smoking Cessation 

19

Smoking and Tobacco Control Monograph No. 12 

756,000 At least 90 percent of all patients are advised 

508,111 All states have tobacco control programs 1.32 57,246 57,049 506,360 

Tobacco Control comparable in scope to California Program and Massachusetts 

189,000 Effect of physician advice in the real 0.91 0 2,276,986 3,497,231 Advised by 1.60 

Physician to Quit world matches that in trials (Odds ratio 

for cessation = 1.3) Cost Increases 20 percent from 1996 values 

Medication — — — — 150,000 500,000 Effect of medication in the real world 

matches that in trials 

Optimal Health Care System Intervention to quit and at least 45 percent are 

provided with optimal counseling 

in Cigarette Cost
Total Work Ban 1.09 312,112 576,918 1.34 119,828 221,493 All workplaces are smoke free


Potential Conditions Required Odds


Ratio Effect Effect Ratio Effect Effect for Potential Effect


Table 1-1 Current and Potential Impact of Population-Based Smoking Cessation Interventions 

Cessation Attempt Former, 3+ Months 

1,139,309 — — 222,298 20% Increase — — 

Odds Current Current Potential 

Comprehensive 1.04 

20

Chapter 1 

In the United States, the CPS estimates that there are approximately 44 

million smokers, and about one-third of them (14 million) attempt to 

change their smoking behavior each year. Only 3.6 percent (about 1.5 million) of those who were smoking every day 12 months ago are successful 

for 3 or more months at the time of the survey. 

The estimates in Table 1-1 utilize the odds ratios for cessation attempts 

and cessation success presented in Chapter 2 for the state of California, as 

compared to other states, with the exclusion of Massachusetts. The numbers are estimates of the difference in cessation produced by these two wellfunded tobacco control programs. Since most other states also have substantial tobacco control efforts underway (funded by ASSIST, IMPACT, and 

other sources), these estimates underestimate the true effect of tobacco control campaigns; and they estimate only the increment in effect that would 

be expected from the difference in intensity and funding between the programs in Massachusetts and California and those in the remaining states. 

The column in the table labeled Potential Effect presents an estimate for the 

effect expected if all states adopted programs similar to those of California 

and Massachusetts. It would appear that tobacco control programs have a 

modest effect on the already high rate of cessation attempts among smokers, but a much larger proportional effect on successful cessation. If comprehensive tobacco control programs were implemented nationally, rates of 

successful cessation might be increased by one-third, approaching 500,000 

additional smokers who were abstinant for at least 3 months. 

The largest current contributions to successful cessation come from 

total bans on smoking in the workplace (119,828 quits) and from pharmacological interventions (150,000 quits). If all workplaces were smoke-free, 

the rate of cessation lasting at least 3 months might increase by more than 

100,000 quits per year, and if the success of pharmacological interventions 

in the general population matched that of clinical trials, an additional 

350,000 quits might be achieved. 

Physician advice to quit, as it is currently practiced in the general population, appears to have a large effect on cessation attempts, but little effect 

on long-term cessation success. If the success of physician advice were comparable to that found in clinical trials, an additional 189,000 successful 

quits might be expected. This number represents a substantial number of 

quits, but is only a small fraction of the increase in quit attempts promoted 

by this modality. In contrast, approximately 750,000 additional successful 

quits might be achieved if the health care delivery system were to deliver 

optimal cessation assistance to all of their insured population. 

An increase in the cost of cigarettes could also increase both cessation 

attempts and cessation success, with a 20 percent increase in cost generating an additional 222,000 successful quits. The increase in cost of cigarettes 

($0.45 per pack) that may, over time, result from the Master Settlement 

Agreement of the state Attorneys General lawsuits would be approximately 

a 20 percent increase. If and when it is translated into an actual change in 

the price of cigarettes to the smoker (i.e., when the additional discounting 

21 
Smoking and Tobacco Control Monograph No. 12 

that accompanied the increase in cost is no longer reducing the actual price 

paid by the consumer), this price increase may result in an increase in the 

number of cessation attempts and successful quits. 

Summary and Synthesis Examination of the numbers in Table 1-1 suggests that 

of Policy Effects there are powerful current and potential effects of existing tobacco control interventions for smoking cessation. However, it also 

demonstrates that there are significant gaps in their interactions with one 

another. The most obvious of these gaps is between the enormous number 

of estimated quit attempts generated by physician advice and the absence 

of an effect on successful cessation. However, there are also significant gaps 

between what is currently being realized with medication and what might 

be expected to be achieved—the same is true for comprehensive tobacco 

control programs. These gaps offer opportunities to improve tobacco control programs, particularly by taking advantage of synergies that might exist 

across these independent interventions. 

Physician advice to quit is associated with over 2.2 million quit 

attempts currently and has the potential to be associated with almost 3.5 

million quit attempts. However, these attempts are not translating into cessation success in large numbers. A substantial research and programmatic 

effort has been made by the NCI, CDC, and other professional and voluntary organizations to train physicians to intervene and provide cessation 

advice to all of their smoking patients. As Chapter 4 demonstrates, this 

effort has resulted in a substantive increase in the fraction of smoking 

patients who report that their physicians have advised them to quit smoking. These efforts to encourage physicians to provide cessation advice have 

been quite successful, with the fraction of patients reporting cessation 

advice from physicians more than doubling since 1974. However, this effort 

may not have improved successful long-term cessation rates substantively 

in the population, and the potential for cessation when this channel is utilized alone is a modest 189,000 quits. 

The lesson from these estimates is not that more effort should be devoted to encouraging physicians to provide advice to quit, but rather that 

there is a substantial number of cessation attempts currently being generated by physician advice that are not being translated into successful cessation. This group of cessation attempts represents an enormous opportunity 

if we can link those making cessation attempts with other tobacco control 

interventions that can facilitate long-term success. 

The simplest of these interactions would be linking physician advice to 

quit with telephone counseling or other community or health care system 

cessation assistance. An example of what might be possible to achieve 

through these linkages is provided at the bottom of Table 1-1, where 

increased physician advice is coupled with optimal cessation interventions 

to generate a 2.3-fold increase in the rate of successful spontaneous cessation (see Chapter 4). The potential for this linked approach is estimated to 

be over 750,000 successful quits, and these kinds of linkages have been 

demonstrated to be effective within a single health care delivery system 

(Curry et al., 1998). 

22

Chapter 1 

A second association with large numbers of cessation attempts can be 

found with an increase in the cost of cigarettes. Adding media messages 

promoting cessation, linking to telephone counseling services, energizing 

health care systems to provide cessation messages and assistance, and timing community and other local tobacco control efforts to coincide with and 

take advantage of the increased cessation activity provided by an increase 

in the cost of cigarettes may help convert more of the cessation attempts 

into cessation successes. 

Table 1-1 provides estimates for those tobacco control interventions 

where there are sufficient data to generate estimates. It is likely that many 

of the community activation strategies and local lead agency efforts in 

California provide a critical foundation for implementation of some of the 

public policy interventions (e.g., restrictions on smoking in the workplace). 

But the difficulty in quantifying and measuring these activities makes them 

less visible to the analytic approach used in this monograph. It is also likely 

that these program areas offer great opportunities for synergy in enhancing 

cessation success with the policy interventions described above. For example, linking local cessation assistance activities with workplaces who have 

made voluntary changes in smoking restrictions would increase the efficiency of the efforts to recruit smokers into these programs and would increase 

the effectiveness of the workplace change in creating successful cessation. 

SUMMARY Approximately one-half of current ever-smokers have become 

former smokers, and most of this cessation activity has coincided with a 40-

year effort to educate and inform smokers about the risks of smoking. Large 

media-led tobacco control programs have also coincided with increases in 

smoking cessation, suggesting that tobacco control approaches can alter 

smoking behavior. This volume presents evidence supporting the effects of 

restrictions on where people can smoke, of increasing the cost of cigarettes, 

of providing physician advice to quit coupled with cessation assistance, of 

pharmacological assistance, and of telephone hotlines on cessation among 

smokers in the general population. It also provides evidence that many of 

these interventions are being implemented in the general population in 

ways that are less effective than expected based on clinical trials. Increasing 

the effectiveness of these interventions and linking multiple interventions 

to provide synergy offer great opportunities to improve rates of populationbased smoking cessation. 

23

Smoking and Tobacco Control Monograph No. 12 

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Biener, L., Roman, A.M. 1996 Massachusetts Adult 

Tobacco Survey: Tobacco Use and Attitudes after 

Three years of the Massachusetts Tobacco Control 

program. Technical Report and Tables. Boston: 

Center for Survey research, University of 

Massachusetts, 1997. 

Burns, D., Lee, L., Shen, Z., Gilpin, B., Tolley, D., 

Vaughn, J., Shanks, T. Cigarette Smoking 

Behavior in the United States. In: Changes in 

Cigarette-Related Disease Risks and Their 

Implication for Prevention Smoking and Tobacco 

Control Monograph No. 8, Burns, D., Garfinkel, L., 

Samet, J. (editors). U.S. Department of Health 

and Human Services, National Institutes of 

Health, National Cancer Institute. NIH 

Publication No. 97-4213, 1997. 

Centers for Disease Control and Prevention. 

Cigarette smoking among adults—United States, 

1998. Morbidity and Mortality Weekly Report 

49(39):881-884, 2000. 

Centers for Disease Control and Prevention. Best 

Practices for Comprehensive Tobacco Control 

Programs-August 1999. U.S. Department of Health 

and Human Services, Centers for Disease Control 

and Prevention, National Center for Chronic 

Disease Prevention and Health Promotion, Office 

on Smoking and Health, 1999a. 

Centers for Disease Control and Prevention. 

Cigarette Smoking Among Adults—United States, 

1997. Morbidity and Mortality Weekly Report 

48(43):993-996, 1999b. 

Curry, S.J., Grothaus, L.C., McAfee, T., Pabiniak, C. 

Use and cost effectiveness of smoking-cessation 

services under four insurance plans in a health 

maintenance organization. New England Journal 

of Medicine 339(10):673-679, 1998. 

Hymowitz, N., Cummings, K.M., Hyland, A., Lynn, 

W.R., Pechacek, T.F., Hartwell, T.D. Predictors of 

smoking cessation in a cohort of adult smokers 

followed for five years. Tobacco Control 6(suppl 

2):S57-S62, 1997. 

Lewit, E.M., Coate, D., Grossman, M. The effect of 

government regulation on teenage smoking. 

Journal of Law and Economics 24:545-569, 1981. 

National Cancer Institute, 1991. Strategies to Control 

Tobacco Use in the United States: a blueprint for 

public health action in the 1990s. Smoking and 

Tobacco Control Monograph No. 1. U.S. 

Department of Health and Human Services, 

Public Health Service, National Institutes of 

Health, National Cancer Institute. NIH 

Publication No. 92-3316, 1991. 

Pierce, J.P., Gilpin, E.A., Emery, S.L., Farkas, A.J., Zhu, 

S.H., Choi, W.S., Berry, C.C., Distefan, J.M., 

White, M.M., Soroko, S., Navarro, A. Tobacco 

Control in California: Who’s Winning the War? La 

Jolla, CA: University of California, San Diego, 

1998. 

Prochaska, J.O., DiClemente, C.C. Stages and 

processes of self-change in smoking: Toward an 

integrative model of change. Journal of Consulting 

and Clinical Psychology 59:295-304, 1991. 

U.S. Department of Health and Human Services. The 

Health Benefits of Smoking Cessation. U.S. Dept of 

Health and Human Services, Public Health 

Service, Centers for Disease Control and 

Prevention, National Center for Chronic Disease 

Prevention and Health Promotion, Office on 

Smoking and Health. DHHS Publication No. 

(CDC) 90-8416, 1990. 

U.S. Department of Health and Human Services. The 

Health Consequences of Smoking: 25 years of 

Progress. U.S. Dept of Health and Human 

Services, Public Health Service, Centers for 

Disease Control, Office on Smoking and Health. 

DHHS Publication No (CDC) 89-8411, 1989. 

Warner, K.E. Effects of the antismoking campaign: 

an update. American Journal of Public Health 

79:144-151, 1989. 

24

Cessation and Cessation Measures 

among Adult Daily Smokers: 

National and State-Specific Data 

David M. Burns, Christy M. Anderson, Michael Johnson, Jacqueline M. Major, 

Lois Biener, Jerry Vaughn, Thomas G. Shanks 

Reducing initiation rates of cigarette smoking and encouraging smoking 

cessation are principal goals of tobacco control programs, including those 

in California, Massachusetts, Arizona, Florida, Oregon, and other states. 

This volume focuses on cessation, and more specifically on population 

measures of progress in cessation rates. Its objectives are to examine what 

we know about what drives cessation on a population basis and to offer our 

best judgements on what approaches appear to be working and what 

approaches appear to have less impact. 

CESSATION Cessation is a process rather than a specific event. It begins with a 

decision to stop smoking and ends with abstinence from cigarettes maintained over a long period of time (U.S.DHHS, 1990). Cessation occurs at the 

individual level, and a substantial body of science examines the processes 

that individuals go through as they become former smokers—the individual 

determinants of success or failure in the process of cessation are also well 

described (U.S.DHHS, 1990). Several staged measures of change in individual cessation have been developed to link measures of intention to quit and 

actual cessation behavior in order to define where smokers are in their individual cessation efforts and to predict the likelihood of future cessation 

activity and success (Prochaska et al., 1991; Pierce et al., 1998a & b; 

U.S.DHHS, 1990). This volume recognizes and draws upon this important 

body of work, but the focus here is on examining the impact of programs 

and strategies that change cessation in the general population, rather than 

on an examination of the dynamics of the cessation process itself. 

Since measurement of programmatic effect is the goal in this work, 

measures of cessation are selected with the following criteria in mind: 

1. The measures should reflect as narrowly as possible the target 

population of most cessation interventions—i.e., regular daily 

smokers who have completed the process of taking up cigarette 

smoking. Other groups, including occasional smokers and young 

adults still in the process of becoming addicted to cigarettes, are 

important segments of the smoking problem, but they are often 

quite different from regular daily smokers in their smoking 

behaviors. Including them in measures of cessation can lead to 

confusion in the evaluation of the results. In addition, different 

cessation intervention strategies are often utilized with these 

populations. 

25

Smoking and Tobacco Control Monograph No. 12 

2. Measures should allow for the establishment of a close temporal 

link between a programmatic intervention and the cessation 

measure. For example, the quit ratio (the ratio of former smokers 

to ever-smokers) may be a good measure of total cessation in a 

population, but it is a cumulative measure of all successful cessation in a population over time and is therefore less useful in 

examining the effect of recent programmatic efforts on cessation 

activity. 

3. The measures should also examine both cessation activity and 

cessation success as separate entities. Some programmatic activity 

may have an effect principally by stimulating cessation attempts, 

while not significantly increasing longer term cessation success. 

Other actions may have their effect predominantly in enabling 

those who are trying to quit to be more successful in the long 

term. 

None of these criteria require that the chosen measures cover all segments of the smoking population or all stages of cessation in smokers. 

We are attempting to analyze the effect of programs on as clean and 

unambiguous a measure of cessation as possible. As is often true, it is necessary to narrow the population in which a measurement is made in order to 

improve the ability to identify an effect and to decrease the “noise” in the 

measure. Those who are still in the process of becoming regular cigarette 

smokers, and those who do not smoke daily, may respond to the questions 

on quit attempts (being off for 24 hours or more) with positive answers that 

reflect variations in their current pattern of use rather than a clear attempt 

to alter their future smoking behavior. Lumping these two groups together 

may confuse analyses of the effects of tobacco control programs on cessation rates. 

Among smokers who do not smoke every day, it is more difficult to 

know what measures of voluntary 24-hour cessation (a cessation attempt) 

mean relative to their future smoking behavior, and it is even more difficult 

to relate that change in behavior to programmatic-driven cessation. 

While still under the age of 25, some smokers are likely to be in the 

process of developing their addiction to cigarettes. Some of the change in 

their smoking behavior is due to real cessation activity, but some is due to 

smokers who are still experimenting with smoking and who will not be 

progressing to become regular smokers. As it is impossible to determine 

which of these phenomena are driving the change in behavior, measures 

that include those smokers under age 25 mix changes due to experimentation with those that are due to actual cessation activity. Elimination of 

smokers under age 25 from the measure essentially eliminates most of those 

who are still experimenting with cigarettes and thus makes the measure a 

cleaner measure of cessation activity. Additionally, someone who is in the 

process of beginning to smoke and who does not go on to become a regular 

smoker is likely to have been influenced by quite a different set of factors 

than someone who was a regular smoker and who has now successfully 

quit. 

26 
Chapter 2 

In the set of measures presented in this volume we have decreased the 

“noise” in the measure of cessation behavior by limiting the measure to 

those who are regular daily smokers and to those who are old enough to 

have completed the process of smoking uptake (age 25 years and older). 

MEASURES OF A variety of cessation measures are used in this report, but much 

CESSATION of the analysis of national and state-specific data uses a set of 

measures designed to meet the criteria described above. 

The denominator for all of these cessation measures is that group of 

smokers who reported that they were daily cigarette smokers 1 year prior to 

the survey and who were 25 years of age or older at the time of the survey. 

The broadest measure of cessation activity used for this group is one that 

includes any change in smoking behavior (a cessation attempt, becoming 

an occasional smoker, or currently being a former smoker). This is a measure of cessation activity without regard to whether the cessation effort led 

to a successful change in smoking behavior, and this measure is termed cessation activity in this chapter. 

The Current Population Survey (CPS) did not ask current occasional 

smokers whether they had made a quit attempt in the last 12 months, and 

so change from being a current daily smoker 12 months prior to the survey 

to being a current occasional smoker at survey time is reported as a separate 

measure or as part of the change measure for this survey. It was not possible 

to measure cessation attempts among current occasional smokers using the 

CPS data. However, analyses of the California Tobacco Survey (CTS) data, 

where occasional smokers were asked about cessation attempts, reveal that 

three-quarters of those who reported being daily smokers 1 year prior to the 

survey, but who reported being occasional smokers at the time of the survey, also reported making a quit attempt in that 12-month period. We 

therefore included those who changed from being daily smokers to being 

occasional smokers in the group of smokers who were attempting to change 

their smoking behavior. 

The cessation attempt measure includes all those who have made a successful or unsuccessful cessation attempt in the last 12 months, but 

excludes current occasional smokers for analyses. A cessation attempt is 

defined by the question: “During the past 12 months, have you stopped 

smoking for 1 day or longer because you were trying to quit smoking?” 

We also use two measures of cessation success. The first is all those who 

were daily smokers 1 year prior to the survey and former smokers at the 

time of the survey. This is a measure that includes former smokers of all 

durations, and it is the broadest measure of cessation success, but it 

includes large numbers of individuals who will relapse back to smoking. To 

more accurately assess the impact of cessation interventions on longer term 

cessation success, we also calculated the percentage of those who were daily 

smokers 1 year prior to the survey and were former smokers of 3 or more 

months duration at the time of the survey. This group contains a much 

higher fraction of those who will be successful in staying off cigarettes longterm and has been used as a reasonable measure of successful cessation by 

27

Smoking and Tobacco Control Monograph No. 12 

numerous smoking cessation interventions. In some instances the fraction 

of cessation activity that has resulted in successful cessation of 3 months or 

more (percentage of 3+ month success over percentage with some cessation 

activity) is calculated to estimate the fraction of cessation activity that 

results in successful cessation overall. This fraction is called the fraction of 

cessation activity that has resulted in long-term success. 

The numerator for both of these measures of 3+ month cessation success automatically excludes that fraction of daily smokers 1 year prior to the 

survey who quit within the 3 months immediately preceding the survey, 

since they cannot have been successfully quit for 3+ months when surveyed. Some of these individuals who are excluded from the numerator will 

be successful in their efforts to quit, and their exclusion leads to an underestimate of the fraction of the population that will be successful. 

Correspondingly, some of those who were successfully quit for 3+ months 

at the time of the survey will relapse to smoking, and their inclusion in the 

denominator leads to an overestimation of the true rate of successful longterm cessation. The effects of these two sources of error will tend to offset 

one another, and the purpose of developing these measures is to evaluate 

the effects of tobacco control interventions on the population, rather than 

to measure cessation success at the level of the individual. Approximately 

65 percent of all quitters relapse in the first 3 months, with 10 percent 

more relapsing from 3 to 6 months after quitting and an additional 3 percent relapsing between 6 months and 1 year following a quit attempt (Hunt 

et al., 1971; U.S.DHHS, 1988). As a result, these measures of 3+ month success are useful approximations of actual rates of long-term successful cessation rates in the population and can be used to evaluate the relative impact 

of tobacco control interventions on rates of long-term cessation in populations of smokers. 

Analyses of national and state-specific data are presented for the 

Current Population Survey Tobacco Use Supplement, which was conducted 

in the months of September, January, and May during 1992/93 and 

1995/96. Analyses are also presented for the California Tobacco Surveys carried out in 1990, 1993, and 1996, as well as for the Massachusetts Tobacco 

Surveys. 

28

Chapter 2 

Table 2-1 

Current Population Survey: Cigarette Prevalence among All Adults, 18 Years and Older 

Smoking Status Sample 

Daily Occasional Former Never Size 

1992/93 % ± CI % ± CI % ± CI % ± CI (n) 

Total 19.61 0.18 4.23 0.09 22.49 0.19 53.67 0.22 275,895 

Male 21.86 0.27 4.61 0.14 26.99 0.29 46.54 0.32 127,377 

Female 17.57 0.24 3.89 0.12 18.39 0.24 60.16 0.30 148,518 

Daily Occasional Former Never 

1995/96 % ± CI % ± CI % ± CI % ± CI (n) 

Total 19.05 0.18 4.04 0.09 21.76 0.19 55.16 0.23 233,741 

Male 21.19 0.28 4.47 0.14 25.80 0.30 48.54 0.34 107,527 

Female 17.09 0.24 3.64 0.12 18.07 0.25 61.20 0.32 126,214 

National and State- The ultimate measure of success for a tobacco control proSpecific Prevalence gram is the prevalence of smoking in the general population 

of Current and (Table 2-1). Smoking prevalence is the result of the comFormer Smokers bined effects of trends in smoking initiation and smoking 

cessation. However, prevalence is a relatively poor measure of cessation 

activity because initiation occurs largely during adolescence whereas cessation occurs throughout adult life, and rates of both cessation and initiation 

have varied markedly over time (Burns et al., 1997). 

There is substantial variation in current smoking prevalence in the 

United States, both geographically and demographically. The prevalences of 

daily and occasional smoking, estimated from the 1992/93 (Table 2-7) and 

the 1995/96 CPS (Table 2-8), are presented in Appendix 1, along with the 

prevalence of former and never smoking status for the major demographic 

groups and for each state in order of increasing daily smoking prevalence. 

With the exception of Utah, where a large fraction of the population is of 

the Mormon faith with its prohibition against smoking, California is the 

state with the lowest smoking prevalence in both survey years. This difference persists even when smoking prevalence for each state is standardized 

to the racial/ethnic distribution of the United States, indicating that the 

lower prevalence of smoking in California is not due exclusively to the 

higher prevalence of Asian and Hispanic populations in the state. 

Two other potential measures of cumulative population-based cessation 

are presented in Table 2-9 (Appendix 1). They are the prevalence of former 

smokers and the quit ratio (the ratio of former smokers to ever smokers). 

The table is arranged in order of decreasing quit ratio. These measures estimate the cumulative cessation that has occurred over time in a population, 

but are less precise measures of recent cessation activity. In addition, they 

are heavily influenced by the age of the population and by differences in 

demographic factors, such as level of education, where small differences in 

rates of cessation accumulate to create larger differences in the prevalence 

of former smokers. These difficulties limit the use of former smoker prevalence and the quit ratio as measures of cessation activity in response to 

recent tobacco control efforts. 

29

Smoking and Tobacco Control Monograph No. 12 

Measures of Cessation Table 2-2 presents smoking status at the time of the surActivity and Success, vey for those who were 25 years of age or older at the 

National and by State time of and who had been daily cigarette smokers 1 year 

prior to the survey as measured by the 1992/93 CPS. Table 2-3 presents the 

same measures for the 1995/96 CPS. The measures are presented for the 

subgroups of age, race/ethnicity, education, income, and number of cigarettes smoked per day, as well as by state. 

There are five current smoking status conditions in these tables: 

1. Current daily smoker who has not made a quit attempt in the 

last year, 

2. Current daily smoker who has made a quit attempt in the last 

year, 

3. Current occasional smoker, 

4. Current former smoker who has been quit for less than 3 months, 

and 

5. Current former smoker who has been quit for 3 or more months. 

These measures of smoking status at the time of the survey can be 

assembled into several measures of cessation activity and success that 

include progressively higher fractions of those likely to experience longterm success (Figure 2-1). The broadest measure of cessation activity is 

defined by including all those who have made quit attempts (successful or 

unsuccessful) or who have become occasional smokers in the last 12 

months. This measure is defined by adding together all of the categories in 

the table except for the first (Daily smoker, No quit attempt). This, then, is 

a measure of all who were daily smokers 12 months prior to the survey who 

have had any positive change in their smoking behavior and is presented in 

Figure 2-1. It is also the broadest measure of any cessation effect for a tobacco control program. 

The broadest measure of cessation success is all daily smokers 1 year 

prior to the survey who are former smokers at the time of the survey, and it 

is defined by adding former smokers of less than 3 months duration to former smokers of 3+ months duration. This measure includes a substantial 

number of individuals who will relapse in the future, but it also excludes 

those who relapse early after a cessation attempt. Since a large fraction of 

those who relapse do so within the first several weeks of a cessation attempt 

(U.S.DHHS, 1990), this measure is a better measure of the rate of long-term 

cessation success. 

Figure 2-1 presents measures of cessation for the 1992/93 and 1995/96 

Current Population Surveys. There was a statistically significant decline in 

cessation activity between 1992/93 and 1995/96 for the nation as a whole, 

with the broadest measure of cessation activity among daily smokers 1 year 

prior to the survey declining from 36.5 percent in 1992/93 to 31.6 percent 

in 1995/96. This decline in cessation activity between 1992/93 and 1995/96 

was evident and statistically significant in each subcomponent of the cessation activity measure, and both cessation attempts and the fraction of cessation activity that has resulted in 3+ month cessation success declined dur30

Chapter 2 

17 

Population Sample 

No Quit Attempts 

% ± CI % ± CI % ± CI % ± CI % ± CI (N) (n) 

Size Size 

Total 63.52 0.58 25.71 0.52 3.26 0.21 2.41 0.18 5.10 0.26 31,801,272 40,321 

16,782,017 19,173 5.04 0.36 2.59 0.26 2.80 0.27 25.05 0.72 0.79 Male 64.52 

Female 62.40 0.85 26.45 0.77 3.77 0.33 2.21 0.26 5.17 0.39 15,019,256 21,148 Age (Years) 

25–44
45–64 65.10 1.00 23.70 0.90 3.00 0.36 2.70 0.34 5.50 0.48 10,309,965 13,222


18,448,325 22,937 

3,042,982 4,162 7.70 1.03 2.15 0.56 4.13 0.77 18.34 1.50 67.68 1.81 

Race/Ethnicity 

Non-Hispanic 

White 64.11 0.64 24.98 0.57 3.06 0.23 2.56 0.21 5.30 0.30 25,995,472 34,591 

Hispanic
African-Americ. 59.90 1.81 29.78 1.69 4.65 0.78 1.54 0.46 4.13 0.73 3,432,421 3,246


1,573,496 1,357 

Asian/PI
Native Americ. 67.27 5.81 26.91 5.50 1.94 1.71 1.65 1.58 2.23 1.83 304,999 518


483,188 592 

6,735,717 8,261 <12


12 64.71 0.87 25.24 0.79 2.88 0.30 2.40 0.28 4.77 0.39 13,943,590 18,073


7,657,376 9,734 13–15


16+ 56.72 1.80 27.54 1.62 4.51 0.75 3.77 0.69 7.45 0.95 3,464,589 4,253


Household Income 

<$10,000 68.95 1.36 23.14 1.24 3.32 0.53 1.28 0.33 3.31 0.53 5,260,222 6,572 

6,468,466 8,436 $10,000-19,999


$20,000-29,999 63.37 1.36 26.57 1.25 2.77 0.46 2.27 0.42 5.02 0.62 5,742,370 7,332


7,732,799 9,862 $30,000-49,999


$50,000-74,999 58.17 1.74 27.90 1.59 3.77 0.67 3.17 0.62 6.99 0.90 3,658,500 4,527


1,550,783 1,869 $75,000+


Unknown 65.28 2.73 24.27 2.46 3.15 1.00 2.11 0.82 5.19 1.27 1,388,133 1,723


11,697 

Table 2-2 1992/1993 Current Population Survey: Current Smoking Status among Self-Respondents, 25 Years and Older, Identified as Daily Smokers 1 Year Ago 

Current Smoking Status 

Quit < 3 Months Quit 3+ Months 

4.45 0.32 

4.94 1.59 3.95 1.92 

4.00 0.51 5.61 0.56 4.25 0.54 5.65 0.56 7.74 1.45 

Other . . . . . . . . . . 

Daily Former 

2.30 0.24 

2.01 1.03 2.54 1.55 

1.44 0.31 2.67 0.39 2.09 0.38 3.03 0.42 3.53 1.00 

3.26 0.28 

3.65 1.38 3.80 1.88 

2.87 0.44 3.72 0.46 3.29 0.47 3.13 0.42 4.22 1.09 

Quit Attempts Occasional 

28.05 0.71 

26.92 3.26 31.43 4.57 

22.15 1.08 23.86 1.13 26.93 1.08 29.02 2.46 28.87 1.11 

61.95 0.76 

62.47 3.55 58.28 4.85 

69.55 1.20 59.13 1.20 66.50 1.26 61.26 1.18 55.49 2.70 

Education (Years) 

65+ 

31

Smoking and Tobacco Control Monograph No. 12 329 

615 

Population Sample 

Size Size No Quit Attempts 

% 

± CI 

%

± CI 

%

± CI 

%

± CI % 

± CI (N) (n) 

States 

Alabama 67.50 4.94 24.40 4.53 1.95 1.46 1.71 1.37 4.43 2.17 554,406 580 

69,481 531 Alaska


Arizona 63.45 5.03 26.97 4.63 2.77 1.72 1.88 1.42 4.92 2.26 440,379 386


376,141 664 Arkansas


California 61.68 2.20 25.67 1.98 4.00 0.89 2.25 0.67 6.41 1.11 2,779,568 2,095
Colorado
Connecticut 63.28 5.43 26.58 4.97 1.10 1.17 4.33 2.29 4.70 2.38 422,146 396


419,378 475 

54,721 216 Columbia 

Florida 63.69 2.30 25.73 2.09 2.88 0.80 2.42 0.73 5.28 1.07 1,786,118 1,787 

Georgia
Hawaii 61.70 5.55 28.14 5.14 4.16 2.28 1.45 1.37 4.55 2.38 119,260 296


892,435 460 

132,278 564 Idaho


Illinois 62.87 2.69 26.13 2.44 3.48 1.02 2.87 0.93 4.65 1.17 1,406,702 1,526
Indiana
Iowa 64.62 4.94 25.50 4.50 3.21 1.82 2.37 1.57 4.31 2.10 347,097 613


786,930 533 320,527 607 Kansas


Kentucky 75.13 3.81 18.07 3.39 1.92 1.21 2.09 1.26 2.78 1.45 675,928 673
Louisiana
Maine 61.91 4.41 28.59 4.11 3.82 1.74 1.42 1.08 4.26 1.83 204,879 569


525,758 425 633,135 396 Maryland


Massachusetts 58.16 2.68 28.56 2.46 3.29 0.97 3.33 0.98 6.66 1.36 743,094 1,431
Michigan
Minnesota 59.85 5.13 27.13 4.65 4.25 2.11 2.03 1.47 6.75 2.62 564,585 523


1,351,737 1,944 

92,776 4.52 2.21 1.58 1.33 2.30 1.60 25.40 4.64 66.19 5.04 

338,314 4.06 2.09 2.20 1.56 2.34 1.60 29.96 4.85 61.44 5.16 Mississippi 

Quit < 3 Months Quit 3+ Months 

3.18 1.74 4.90 2.10 5.29 2.49 2.81 2.29 2.52 1.55 

4.86 2.12 4.53 2.08 5.17 2.20 6.19 2.62 5.23 2.33 4.96 1.09 

Daily Former 

2.31 1.49 2.89 1.63 1.81 1.48 1.46 1.66 2.52 1.55 

2.54 1.55 3.68 1.88 1.91 1.36 1.92 1.49 2.68 1.69 2.09 0.72 

Table 2-2 (continued) 

Current Smoking Status 

2.23 1.47 2.22 1.44 4.71 2.35 6.19 3.34 2.95 1.67 

3.77 1.87 1.01 1.00 1.71 1.29 2.75 1.78 5.24 2.33 2.86 0.84 

Quit Attempts Occasional 

24.25 4.26 23.85 4.15 24.41 4.77 22.12 5.75 28.85 4.47 

23.60 4.18 21.65 4.12 20.47 4.00 24.18 4.66 28.55 4.72 29.68 2.30 

68.04 4.63 66.13 4.61 63.78 5.34 67.42 6.50 63.16 4.76 

65.23 4.69 69.14 4.62 70.74 4.51 64.96 5.19 58.29 5.15 60.40 2.46 

Delaware District of 

32

Chapter 2 

Population Sample 

Size Size No Quit Attempts 

% ± CI % ± CI % ± CI % ± CI % ± CI (N) (n) 

757,383 605 Missouri


Montana 66.76 4.99 22.45 4.42 3.81 2.03 2.15 1.54 4.82 2.27 101,771 592
Nebraska
Nevada 69.29 4.12 23.87 3.81 1.91 1.22 1.32 1.02 3.61 1.66 212,335 582


173,790 543 

New Hampshire
New Jersey 61.40 2.70 27.51 2.48 2.97 0.94 2.31 0.83 5.81 1.30 875,804 1,365


150,153 339 

New Mexico
New York 61.26 2.05 26.68 1.86 3.36 0.76 3.32 0.75 5.37 0.95 2,074,672 2,347


180,763 440 

North Carolina
North Dakota 62.41 5.33 26.50 4.86 5.76 2.57 2.76 1.80 2.57 1.74 67,949 512


973,548 1,900 

1,574,578 2,054 Ohio


Oklahoma 66.58 4.50 21.37 3.91 2.83 1.58 2.86 1.59 6.35 2.33 471,743 611


364,440 453 Oregon


Pennsylvania 62.51 2.49 26.92 2.28 3.77 0.98 2.11 0.74 4.69 1.09 1,536,773 1,836


Rhode Island
South Carolina 67.85 4.23 21.99 3.75 3.16 1.59 2.64 1.45 4.36 1.85 495,343 602


125,657 353 

South Dakota
Tennessee 64.72 4.30 25.70 3.94 2.75 1.47 2.01 1.26 4.83 1.93 783,596 664


80,533 596 

2,013,625 1,694 Texas


Utah 61.89 6.20 27.56 5.70 5.20 2.83 0.74 1.09 4.61 2.68 131,888 298
Vermont


Virginia 62.48 4.34 26.59 3.96 3.29 1.60 2.18 1.31 5.46 2.04 852,061 614


86,374 385 

659,444 468 Washington


West Virginia 73.28 4.09 20.54 3.74 2.16 1.35 1.17 0.99 2.84 1.54 315,718 720


Wisconsin
Wyoming 58.80 5.61 29.45 5.20 3.79 2.18 2.04 1.61 5.92 2.69 63,279 412


640,276 702 

Quit < 3 Months Quit 3+ Months 

5.27 2.21 5.46 2.39 5.02 2.41 6.34 2.57 

4.12 0.95 5.39 1.10 5.04 2.43 

7.57 2.94 4.28 2.05 4.58 1.19 

5.00 2.24 7.63 2.67 

4.90 2.12 

Daily Former 

3.04 1.70 2.05 1.49 4.41 2.27 2.06 1.50 

2.49 0.75 2.25 0.72 1.59 1.39 

2.51 1.74 2.23 1.49 2.14 0.82 

2.10 1.48 2.06 1.43 

2.26 1.46 

Table 2-2 (continued) 

Current Smoking Status 

3.22 1.75 2.54 1.65 3.83 2.12 4.10 2.09 

3.08 0.83 3.43 0.89 3.35 2.00 

3.46 2.03 3.18 1.77 

3.51 1.89 3.31 1.80 

4.26 1.98 

3.97 1.11 

Quit Attempts Occasional 

Note: CI = 95% confidence interval. Values with insufficient data are not reported. 

24.26 4.24 28.90 4.77 24.18 4.73 26.88 4.68 

22.80 2.01 25.55 4.84 

23.47 4.71 24.68 4.36 25.45 2.48 

30.50 4.74 28.33 4.53 

25.39 4.27 

24.95 2.11 

64.21 4.74 61.05 5.13 62.56 5.34 60.61 5.16 

67.51 2.25 63.98 2.34 64.47 5.31 

62.98 5.37 65.63 4.80 63.86 2.74 

58.89 5.06 58.67 4.96 

63.19 4.74 

33

Smoking and Tobacco Control Monograph No. 12 Population Sample No Quit Attempts % 

± CI 

%

± CI 

%

± CI 

%

± CI % 

± CI (N) (n) 

Size Size 

Total 68.3 0.6 23.2 0.5 2.9 0.2 1.9 0.2 3.6 0.2 32,402,966 32,917 

17,058,593 15,358 3.8 0.3 2.1 0.2 2.7 0.3 22.7 0.7 0.8 Male 68.7 

Female 67.8 0.9 23.7 0.8 3.2 0.3 1.8 0.2 3.5 0.3 15,344,373 17,559 Age (Years) 

25–44
45–64 70.1 1.0 21.9 0.9 2.5 0.3 1.9 0.3 3.6 0.4 10,989,936 11,328


18,390,046 18,168 

3,022,984 3,421 5.0 0.9 1.9 0.6 3.8 0.8 16.5 1.5 72.8 1.8 

Race/Ethnicity 

Non-Hispanic 

White 68.8 0.6 22.6 0.6 2.7 0.2 2.1 0.2 3.8 0.3 26,285,210 27,991 

1,699,613 1,278 Hispanic


African-Americ. 65.3 1.9 26.7 1.7 4.3 0.8 1.2 0.4 2.4 0.6 3,432,483 2,681


593,903 507 Asian/PI


Native Americ. 68.1 5.4 23.3 4.9 3.2 2.1 2.7 1.9 2.6 1.9 391,757 460


Education (Years) 

<12 73.7 1.2 19.8 1.1 2.4 0.4 1.4 0.3 2.7 0.5 6,436,011 6,297 

13,951,150 14,391 12


13–15 63.7 1.2 26.2 1.1 3.5 0.5 2.4 0.4 4.2 0.5 8,434,966 8,627


3,580,839 3,602 5.2 0.8 2.5 0.6 3.7 0.7 24.8 1.6 

<10,000 

10,000-19,999 70.1 1.4 22.5 1.2 2.7 0.5 1.3 0.3 3.4 0.5 5,815,762 5,998 

4,484,102 4,529 

20,000-29,999
30,000-49,999 66.5 1.2 24.4 1.1 3.1 0.4 2.2 0.4 3.8 0.5 7,838,442 8,086


5,707,800 5,843 4,157,714 4,179 50,000-74,999


75,000 + 64.6 2.3 23.6 2.1 3.2 0.9 2.7 0.8 5.8 1.1 2,175,925 2,099


2,223,221 2,183 3.1 0.8 1.5 0.6 2.9 0.8 19.2 1.9 73.2 2.1 Unknown 

1995/1996 Current Population Survey: Current Smoking Status among Self-Respondents, 25 

Years and Older, 

Identified as Daily Smokers 1 

Year Ago 

Current Smoking Status 

Quit < 3 Months Quit 3+ Months 

3.4 0.3 

3.6 1.4 4.6 2.0 

3.3 0.3 

3.0 0.6 3.3 0.5 3.9 0.7 

Daily Former 

2.0 0.2 

1.4 0.9 2.1 1.3 

1.8 0.3 

1.7 0.4 2.0 0.4 2.4 0.5 

Quit Attempts Occasional 

3.1 0.3 

4.1 1.5 3.7 1.8 

2.6 0.3 

3.4 0.6 2.5 0.5 2.9 0.6 

25.0 0.7 

23.0 3.2 26.8 4.2 

22.5 0.8 22.6 1.4 22.6 1.3 25.0 1.5 

66.5 0.8 

68.0 3.5 62.9 4.6 

69.8 0.9 63.8 1.8 69.3 1.6 69.5 1.4 65.8 1.7 

THousehold Income (Dollars) 

able 2-3 

65+ 16+ 

34

Chapter 2 

363 403 

Population Sample 

Size Size No Quit Attempts 

% ± CI % ± CI % ± CI % ± CI % ± CI (N) (n) 

States 

Alabama 65.3 5.0 27.5 4.7 3.5 1.9 1.5 1.3 2.2 1.5 523,282 462 

74,796 318 Alaska


Arizona 65.0 4.9 22.6 4.3 2.8 1.7 4.0 2.0 5.6 2.4 487,618 486


376,963 517 Arkansas


California 64.3 2.3 24.2 2.1 4.4 1.0 2.1 0.7 4.9 1.1 2,784,977 1,705
Colorado
Connecticut 64.5 5.7 28.3 5.3 2.1 1.7 1.9 1.6 3.2 2.1 372,503 270


442,528 453 

59,954 271 Columbia 

Florida 67.0 2.4 24.0 2.2 2.8 0.8 2.0 0.7 4.3 1.0 1,827,730 1,467 

Georgia
Hawaii 66.3 5.6 22.1 4.9 4.3 2.4 2.4 1.8 4.9 2.6 127,499 236


868,971 518 130,940 454 Idaho


Illinois 70.2 2.6 22.1 2.4 3.0 1.0 1.6 0.7 3.0 1.0 1,493,937 1,356
Indiana
Iowa 70.5 4.8 21.8 4.3 2.2 1.5 1.8 1.4 3.6 1.9 350,680 459


920,599 565 335,856 494 Kansas


Kentucky 72.8 3.8 20.9 3.5 0.9 0.8 2.9 1.4 2.5 1.3 694,650 590
Louisiana
Maine 67.2 4.6 25.3 4.3 1.6 1.2 1.4 1.1 4.5 2.0 190,227 443


533,278 393 559,659 332 Maryland


Massachusetts 62.0 3.4 28.1 3.1 2.7 1.1 2.8 1.1 4.4 1.4 713,012 825
Michigan
Minnesota 64.6 5.2 26.6 4.8 4.1 2.1 2.0 1.5 2.6 1.7 539,599 478


1,329,879 1,389 

97,745 2.9 1.8 1.8 1.4 2.7 1.7 19.4 4.2 73.2 4.7 

343,817 3.0 1.7 2.1 1.5 2.0 1.4 23.9 4.3 69.0 4.7 Mississippi 

Quit < 3 Months Quit 3+ Months 

4.0 2.0 3.8 1.8 4.6 2.2 3.0 2.1 2.3 1.4 4.6 2.2 3.5 1.7 2.3 1.6 3.9 2.0 3.6 2.1 4.2 1.1 

Daily Former 

1.3 1.1 1.6 1.2 2.9 1.8 2.0 1.7 2.9 1.6 3.9 2.0 0.8 0.8 0.9 1.0 1.4 1.2 2.3 1.7 1.5 0.7 

Table 2-3 (continued) 

Current Smoking Status 

Quit Attempts Occasional 

3.5 1.9 1.8 1.3 3.9 2.1 4.1 2.5 2.2 1.4 3.9 2.0 2.2 1.3 2.7 1.7 3.5 1.9 4.5 2.4 3.2 1.0 

26.2 4.5 19.2 3.7 23.3 4.5 25.2 5.4 23.7 4.1 20.2 4.2 18.8 3.6 20.5 4.2 19.5 4.0 25.7 5.0 28.0 2.6 

65.0 4.8 73.7 4.1 65.3 5.1 65.7 5.9 68.9 4.5 67.5 4.9 74.6 4.0 73.6 4.5 71.7 4.6 63.9 5.5 63.1 2.8 

Delaware District of 

35

Smoking and Tobacco Control Monograph No. 12 Population Sample Size Size No Quit Attempts % 

± CI 

%

± CI 

%

± CI 

%

± CI % 

± CI (N) (n) 

773,750 503 Missouri


Montana 69.4 4.6 21.8 4.1 3.0 1.7 1.9 1.4 3.8 1.9 113,892 523
Nebraska
Nevada 70.4 4.2 23.3 3.9 1.7 1.2 1.5 1.1 3.0 1.6 247,950 451


177,818 418 

New Hampshire
New Jersey 70.0 2.9 21.6 2.6 2.0 0.9 2.5 1.0 3.8 1.2 894,347 937


161,335 364 

New Mexico
New 

York 68.0 2.1 23.3 1.9 3.1 0.8 1.9 0.6 3.8 0.9 2,040,575 1,794


196,482 439 

North Carolina
North Dakota 72.7 4.8 19.7 4.3 2.8 1.8 3.1 1.9 1.8 1.5 74,276 455


1,035,647 1,226 1,606,599 1,534 Ohio


Oklahoma 73.8 4.2 20.8 3.9 2.6 1.5 1.0 1.0 1.8 1.3 448,326 588


374,521 389 Oregon


Pennsylvania 68.0 2.5 23.7 2.3 2.9 0.9 1.6 0.7 3.8 1.0 1,595,350 1,572
Rhode Island
South Carolina 77.9 4.1 16.7 3.7 2.3 1.5 1.8 1.3 1.4 1.1 508,076 393


137,521 345 

South Dakota
Tennessee 71.3 4.1 20.0 3.6 2.8 1.5 1.8 1.2 4.2 1.8 823,937 510


84,867 494 

2,125,005 1,415

Texas
Utah 69.3 6.1 23.0 5.6 3.1 2.3 2.1 1.9 2.6 2.1 132,775 265
Vermont


Virginia 68.9 4.3 23.6 4.0 1.8 1.2 1.5 1.1 4.2 1.9 892,527 570


84,435 404 

645,346 398

Washington
West Virginia 71.5 3.9 20.6 3.5 2.9 1.5 1.5 1.1 3.4 1.6 295,884 628


Wisconsin
Wyoming 70.7 4.8 20.0 4.2 2.6 1.7 2.0 1.5 4.8 2.3 64,619 504


686,410 551 

Quit < 3 Months Quit 3+ Months 

3.7 1.8 1.9 1.5 4.8 2.3 4.2 2.1 

3.0 1.1 3.5 1.0 4.2 2.2 4.5 2.2 3.1 1.8 3.1 1.0 

4.3 2.1 3.4 2.0 

3.7 1.9 

Daily Former 

1.7 1.3 3.0 1.9 2.6 1.7 2.3 1.5 

1.8 0.8 1.9 0.7 1.4 1.3 2.1 1.5 2.1 1.5 1.5 0.7 

2.0 1.5 3.5 2.1 

2.4 1.5 

Table 2-3 (continued) 

Current Smoking Status 

Quit Attempts Occasional 

1.9 1.3 3.2 1.9 4.0 2.1 4.1 2.0 

2.8 1.1 2.2 0.8 2.9 1.9 3.0 1.8 4.1 2.0 3.2 1.0 

2.3 1.6 2.4 1.7 

4.5 2.1 

22.7 4.1 22.8 4.6 24.4 4.7 24.5 4.4 

18.2 2.5 21.1 2.2 21.3 4.5 30.1 4.9 25.9 4.4 24.4 2.4 

23.7 4.5 26.3 4.9 

25.1 4.3 

70.1 4.5 69.0 5.0 64.2 5.2 64.9 4.9 

74.2 2.8 71.2 2.5 70.2 5.1 60.3 5.2 64.8 4.8 67.8 2.6 

67.7 4.9 64.3 5.3 

64.2 4.8 

Note: CI = 95% confidence interval. 

36

Chapter 2 

Figure 2-1 

1992/93 and 1995/96 CPS: Percentage of Daily Smokers 1 Year Prior to the Survey 

Who Reported Some Change in Their Smoking Status during that Year, Age 25+ Years 

0

10

15

20

25

30

35

40

Quit 

3+ Months

Short Term

(Quit <3 Months)

Occasional 

Smoker

Failed 

Quit Attempt

992/93 CPS 1995/96 CPS

Former 

Smokers

Current Smokers

Who Made Some

Change

Percentage

ing this period. It is disconcerting that the largest proportionate decline in 

the subcomponents of the cessation activity measure was for those who had 

been quit for 3 months or more (5.1 ± 0.3 percent in 1992/93 declining to 

3.6 ± 0.2 percent in 1995/96), since that is the measure with the greatest 

likelihood of predicting long-term successful cessation. 

The 10 states with the highest rates of any cessation activity in 1992/93 

were Massachusetts, Maryland, Washington, Wyoming, Vermont, Minnesota, Michigan, New Mexico, Nebraska, and New York. Massachusetts, 

Maryland, Washington, Minnesota, and Michigan repeated their appearance among the top 10 states in 1995/96. The states with the lowest rates of 

cessation activity in 1992/93 were the District of Columbia, Alabama, North 

and South Carolina, Alaska, Indiana, Nevada, Kansas, West Virginia, and 

Kentucky. The states of Kentucky, Kansas, North and South Carolina, and 

Indiana were also among the bottom 10 states in 1995/96. 

The 10 states with the highest rates of 3+ month successful cessation in 

1992/93 were Washington, Rhode Island, Minnesota, Massachusetts, 

California, Oklahoma, New Mexico, Louisiana, Wyoming, and New Jersey. 

California, Wyoming, Rhode Island, and Massachusetts were again among 

the top 10 states in 1995/96. The state with the highest rate of 3+ month 

cessation in 1995/96 was Arizona, which implemented a tax-funded tobacco control program in 1995. States with the lowest rates of 3+ months of 

cessation in 1992/93 included North Carolina, Mississippi, Nevada, Alaska, 

37

Smoking and Tobacco Control Monograph No. 12 

West Virginia, District of Columbia, Kentucky, North Dakota, and Georgia. 

Only Kentucky, Georgia, and North Dakota were in the bottom group again 

in 1995/96. 

Extrapolation of differences in these cessation measures between states 

to differences in the success of tobacco control programs is problematic for 

several reasons. Small differences between states are often within the confidence intervals of the estimates, and so the relative ranking of states with 

similar measures has little legitimacy. In addition, population differences 

between the states in age, education, and racial/ethnic composition can 

confound the use of these estimates as outcome measures for tobacco control programmatic activity. However, the range of values for these measures 

across the states is broad relative to the confidence intervals. Therefore, 

states at the higher end of each measure's range are statistically different 

from the states at the lower end of the range, and the differences are large 

enough that they are unlikely to be explained by differences in population 

demographics alone. For example, when the prevalence estimates for the 

different states are standardized to the racial and ethnic distribution of the 

United States, there is little difference in the relative ranking among the different states (unpublished analyses). In order to control for the influence of 

these demographic differences across the states on the measures of cessation 

we are using, we will first present analyses of the measures stratified by each 

demographic factor and then combine these factors in a multivariate logistic regression analysis. This analysis will allow us to examine the influence 

of the variables on cessation and to examine whether California and 

Massachusetts have greater rates of cessation activity and success than the 

remaining states. 

Differences in cessation There are dramatic differences in cessation activity 

activity by age, race/eth- and success with age (Figure 2-2). Older smokers are 

nicity, education, income, much less likely to make a cessation attempt, but are 

and number of cigarettes much more likely to be successfully quit for 3 or more 

smoked per day months. Both the absolute fraction of daily smokers 1 

year prior to the survey who are now former smokers of 3 or more months 

duration and the fraction of those who have had any cessation activity who 

are now former smokers of 3 or more months duration are higher at older 

ages. Thus, older smokers appear to be less likely to attempt to change their 

smoking behavior; but when they do, they are substantially more likely to 

be successful. The decline in cessation activity between 1992/93 and 

1995/96 as noted in Figure 2-1 is evident for each of the age groups. 

Differences among racial and ethnic groups are less pronounced (Figure 

2-3). African-Americans have significantly higher rates of cessation activity 

than non-Hispanic Whites, but they also have significantly lower rates of 

being quit for 3 or more months. Asian/Pacific Islanders also have significantly higher rates of cessation activity compared to non-Hispanic Whites, 

with a nonsignificant lower rate of 3+ month cessation success. 

Figure 2-4 presents the cessation measures by level of educational 

attainment and demonstrates that both cessation activity and 3+ month 

cessation success are significantly higher among smokers with higher levels 

38

Chapter 2 

Figure 2-2 

1992/93 and 1995/96 CPS: Percentage of Daily Smokers 1 Year Prior to the Survey 

Who Report Some Change in Their Smoking Status during that Year, by Age 

0

10

15

20

25

30

35

40

Quit 3+ Months Quit <3 Months Occasional Smoker Quit Attempt

92/93 95/96 92/93 95/96 92/93 95/96

Age (Years)

25-44 45-64 65+

Percentage

of educational attainment. The largest proportional differences across strata 

of educational attainment are for former smokers and former smokers of 3+ 

months' duration, where there is almost a doubling in rates from the lowest 

to the highest level of education. The percentage of all cessation activity 

that has resulted in 3+ months of successful cessation also increases with 

increasing level of educational attainment 

A similar pattern is seen with level of income (Tables 2-2 and 2-3), 

where both cessation activity and 3+ month cessation success are significantly higher among smokers with higher family incomes. The percentage 

of all cessation activity resulting in 3+ months of successful cessation is relatively uniform across the middle strata of family income, but it is higher 

for the top income stratum and lower for the lowest income stratum. 

Table 2-4 shows the current smoking status of individuals who reported 

that they were daily smokers 1 year prior to the California Tobacco Survey. 

It presents the change in smoking behavior that occurred over that year, 

both for changes in number of cigarettes reported and for becoming a former smoker. Most smokers (almost three-quarters) of more than five cigarettes per day continued to smoke the same number of cigarettes, even 

though many had made a quit attempt during that year. Smokers of 1-4 cigarettes per day were less consistent, with 14.2 percent increasing the 

amount that they smoked, 18.3 percent becoming occasional smokers, and 

39

Smoking and Tobacco Control Monograph No. 12 Figure 2-3 1992/93 and 1995/96 CPS: Percentage of Daily Smokers 1 

Year Prior to the Survey Who Report Some 

Change in Their Smoking Status during that 

Year, Age 25+, by Racial or Ethnic Group 

Qu + M n h Qu < M n h O n m k Qu A mp

N v

Am n

A n P A n

Am n

H p n N n H p n

Wh Percentage

40

Chapter 2 

Figure 2-4 1992/93 and 1995/96 CPS: Percentage of Daily Smokers 1 Year Prior to the Survey Who Report Some Change in Their Smoking Status during that Year, Age 25+, by Level of Education Qu + M n h Qu < M n h O n m k Qu A mp + Y Y Y < Y L v Edu n Percentage

41

Smoking and Tobacco Control Monograph No. 12 Occasional Pop. Samp. # Smoked
 1 Year 25+ 15–24 5–14 1–4 Unknown Smoker <3 Months 3+ Months Unknown Size Size
 Ago 

%

± CI

%

± CI

%

± CI

%

± CI

%

± CI

%

± CI

%

± CI

%

± CI

%

± CI (N) (n) 

Overall
25+ 69.5 2.8 13.2 1.8 3.9 1.1 0.6 0.6 0.0 0.1 1.8 0.6 5.2 1.4 5.5 1.1 0.3 0.3 703,264 1,542


2,894,421 6,211 

15–24
5–14 0.5 0.4 5.6 1.3 74.1 2.8 1.8 0.7 0.1 0.2 7.0 1.6 5.0 1.3 5.6 1.6 0.4 0.3 779,441 1,560


1,266,356 2,835 

1–4
Unknown 9.5 8.9 26.1 12.3 20.3 9.6 2.6 3.5 20.8 9.7 11.3 8.5 2.7 3.0 6.7 8.3 . . 38,593 71


106,769 203 

0.4 0.2 

0.4 0.3 

1.3 1.6 

California 

Tobacco Survey: Current Smoking Status Compared to Smoking Status 1 

Year Ago for Daily Smokers 

1 Year Ago, 25 

Years and Older 

Current Smoker: Cigarettes Smoked per Day Former Smoker: Quit Duration 

5.0 0.8 

4.2 0.9 

6.8 3.5 

4.8 0.7 

4.2 0.8 

8.3 5.9 

4.6 0.7 

3.2 0.9 

18.3 8.2 

0.3 0.2 

0.0 0.0 

0.4 0.7 

2.9 0.5 

0.8 0.5 

50.7 11.0 

26.0 1.5 

10.1 1.4 

12.6 8.1 

Note: CI = 95% confidence interval; “.” = insufficient data. 

37.6 1.3 

74.4 1.6 

1.1 1.0 

18.3 1.1 

2.7 0.7 

0.5 1.1 

TData Source: 1996 CTS 

able 2-4 

42

Chapter 2 

16.4 percent quitting. With the exception of this lowest number of cigarettes per day category (1-4 cigarettes per day), there was little difference in 

the prevalence of being a former smoker or a former smoker of 3+ months 

duration with increasing number of cigarettes per day. However, the prevalence of being a current occasional smoker declined significantly when 

those who smoked 5-14 cigarettes per day 1 year prior to the survey were 

compared to those who smoked 25 or more cigarettes per day, suggesting 

that heavy smokers are less likely to become occasional smokers as a change 

in smoking behavior. 

MULTIVARIATE As described above, smoking prevalence and cessation 

LOGISTIC MODELING rates vary substantially with age, race/ethnicity, and other 

OF CESSATION DATA demographic characteristics; and income and educational 

attainment are not evenly distributed across racial and ethnic subgroups of 

the population. This makes it difficult to evaluate the actual influence of 

these characteristics on cessation rates from stratified analyses alone. 

Multivariate logistic regression modeling techniques allow the effects of 

each characteristic to be estimated while controlling for the influence of the 

other characteristics in the model. The results of this approach can be 

expressed as a set of odds ratios which estimate the ratio of a given cessation measure—e.g., 3+ month successful cessation—among individuals with 

different levels of a characteristic—e.g., level of income—while controlling 

for the effects of the other characteristics—i.e., gender, age, race/ethnicity, 

education, and number of cigarettes smoked per day. This form of analysis 

gives a much clearer picture of the real influence of these demographic 

characteristics on the smoking cessation measures. These analyses were performed on the CPS data for 1992/93 and for 1995/96, and the complete 

results for each of the cessation measures are presented in Appendix 1 as 

Tables 2-10 and 2-11. A more complete description of these methods is presented as Appendix 2. 

The discussion that follows is largely confined to an examination of 

“Any cessation activity” (the measure labeled change in the tables, which 

includes those who make a cessation attempt, become occasional smokers, 

or are former smokers of any duration) and the measures of “Cessation of 

any length” and “Cessation of 3+ months.” 

Figure 2-5 presents the odds ratios from a multivariate logistic regression analysis of the 1992/93 CPS data for any cessation activity (quit 

attempt, becoming an occasional smoker, or successful quitting) in the prior 

year among those who were daily cigarette smokers 1 year prior to the survey and who were at least 25 years of age. Figure 2-6 presents that same 

analysis for the 1995/96 CPS. It is clear that the independent effects of race 

and ethnicity on cessation activity seen in Figure 2-3 are much less dramatic once adjustments are made for the differences in education, income, and 

number of cigarettes smoked per day across the different racial and ethnic 

groups. African-Americans have a slightly higher rate of cessation activity 

compared to non-Hispanic Whites in 1992/93, but not in 1995/96; whereas 

Hispanic smokers have minimally lower rates of cessation activity in 

1995/96, but not in 1992/93. 

43

Smoking and Tobacco Control Monograph No. 12 Current Population Survey 1992/93: Odds Ratios for Any Cessation Activity 

2 +5

15 24

5 14

1 4

$75 0 +

$50 $74 9

$30 $49

$20 $29

$10 $19

<$10

1 +6 e Y ra s

13 1 Y5 ae sr

1 Y2 ae sr

<1 Y2 ae sr

O ht re

Afr ci na mA re

H si p na ci

Non H si p Wh ti e

6 +5

45 64

25 4

F me l a e

M l a 1.00 e 1.00 1.00 1.00 1.00 1.00 1.05 0.82 0.98 1.13 1.01 0.90 1.43 1.40 1.15 1.67 1.52 1.37 1.28 1.12 0.56 0.82 0.44 Odds Ratio

G A R E E H m C D Figure 2-5 

44

Chapter 2 52 + 51 42 5 41 1 4 7$ 5 0 + 5$ 0 7$ 4 9 3$ 0 4$ 9 2$ 0 2$ 9 1$ 0 1$ 9 $< 01 61 + e Y a 31 51 e Y a 21 e Y a 1< Y2 ae t O eh f A ci na mA e i H ap i n c o N n i H p h W ti e 56 + 54 46 52 4 eF a m el a M 1.00 el 1.00 1.00 1.00 1.00 1.00 0.96 0.76 1.03 1.03 0.89 0.88 1.42 1.48 1.17 1.10 1.07 1.07 0.96 0.95 0.46 0.68 0.32 Odds Ratio G A R E E H m C D Figure 2-6 Current Population Survey 1995/96: Odds Ratios for Any Cessation Activity 

45

Smoking and Tobacco Control Monograph No. 12 

In contrast to the similarity of cessation activity across racial and ethnic 

groups, there are substantial effects of age, education, income, and cigarettes smoked per day. In both surveys, rates of any cessation activity 

decline with increasing age and number of cigarettes smoked per day. 

However, cessation activity increased with increasing level of educational 

attainment in both surveys. The effect of income was different between surveys. In 1992/93, there was a dramatic and consistent increase in cessation 

activity with increasing level of income, but in the 1995/96 survey there 

was no income effect. When similar multivariate logistic analyses are performed on the 1990 and 1996 California Tobacco Surveys (Tables 2-12 and 

2-13 in Appendix 1), there are also no consistent effects with level of 

income. This suggests that there may be no continuing effect of level of 

income on cessation activity once age and level of education are controlled 

for in the analyses, but that there was an effect in 1992/93, possibly due to 

a reduction in cigarette price during that period. Philip Morris reduced the 

price of Marlboro cigarettes in 1993, and the other manufacturers followed 

suit. The effect found in the analyses of the 1992/93 CPS data may have 

been due to higher cessation activity among higher income groups during 

these years, but a more likely explanation would be a reduction in cessation 

activity among lower income smokers for whom price can more reasonably 

be argued to have an effect. 

Figures 2-7 and 2-8 present multivariate logistic regression analyses of 

the 1992/93 and 1995/96 CPS for the measure of successful cessation (3+ 

month former smokers). The odds ratios for 3+ month cessation success 

presented in Figures 2-7 and 2-8 are a result of the cessation activity presented in Figures 2-5 and 2-6. One might expect that those factors that lead 

to higher rates of cessation activity might also lead to higher rates of 3+ 

month successful cessation because one must make a quit attempt in order 

to become a former smoker. This pattern is indeed present for the relationship with educational attainment, where both cessation activity and 3+ 

month cessation success increase with increasing level of education. 

However, a quite different pattern emerges when the effects of age or cigarettes smoked per day are examined. 

The odds ratios for cessation activity decrease significantly with increasing age for both the 1992/93 and 1995/96 CPS (Figures 2-5 and 2-6, change 

measure in Tables 2-9 and 2-10). However, the odds ratios for 3+ month 

successful cessation increases with increasing age (Figures 2-7 and 

2-8, Tables 2-10 and 2-11), even in the face of fewer attempts to quit. This 

suggests that the factors that drive cessation attempts may differ from the 

factors that determine cessation success. It also suggests that older smokers 

may be less likely to try to change their smoking behavior, but when they 

do try to quit, they are far more likely to be successful. Similar results were 

seen for the 1990 and 1996 CTS (Tables 2-12 and 2-13), but the results were 

not always statistically significant. 

The pattern of cessation with increasing number of cigarettes smoked 

per day is also complex. There is a clear decline in cessation activity 

(change measure in the tables) with increasing number of cigarettes smoked 

per day. However, the association with cessation success is less clear (Figures 

46 
Chapter 2 

2-7 and 2-8). Those who reported smoking 1-4 cigarettes per day were significantly more likely to be successfully quit for 3+ months than were 

smokers who reported smoking 5-14 or 15-24 cigarettes per day. Successful 

cessation was less likely for those smoking 25+ cigarettes per day than for 

those smoking 1-4 cigarettes per day, but the difference was not statistically 

significant. However, once the category of 1-4 cigarettes per day is excluded, there is no trend of lower likelihood of 3+ month successful cessation 

with increasing number of cigarettes smoked per day across the remaining 

number of cigarettes per day categories. 

It is possible that overreporting of the number of cigarettes smoked per 

day by former smokers may contribute to the absence of a progressive 

decline in the likelihood of successful cessation, but the absence of any suggestion of a trend would be difficult to explain by overreporting alone. 

Additionally, a follow-up of respondents to the 1990 California Tobacco 

Survey was conducted in 1992, and the rates of 3+ month cessation at the 

time of follow-up for those who reported smoking different numbers of cigarettes per day in 1990 are as follows: 25+ cigarettes/day, 7.25 percent; 15-

24 cigarettes/day, 6.60 percent; 5-14 cigarettes/day, 10.7 percent; 1-4 cigarettes/day 23.53 percent. These rates are based on small numbers of observations and are not representative of the population, but they suggest that 

even when number of cigarettes smoked per day is recorded before a cessation attempt, there is little variation in rates of cessation lasting 3+ months 

or more among those who smoke five or more cigarettes per day. The high 

rates of cessation among those who smoke 1-4 cigarettes per day may 

reflect a substantial number of smokers in this category who are smoking 

this low number of cigarettes per day because they are actively attempting 

to change their smoking behavior. 

In contrast to the CPS data, a logistic regression performed on data 

from a 5-year longitudinal follow-up of 13,415 current smokers from the 

COMMIT Study (Hymowitz et al., 1997) revealed a consistent trend in 

declining cessation success with increasing number of cigarettes smoked per 

day. It is unclear whether the differences between the results of these two 

studies are due to differences in their data collection design (longitudinal 

vs. cross-sectional), differences in the calendar years in which the data were 

collected, or differences in the outcome measures recorded. These data 

taken together suggest that smokers of 25 or more cigarettes per day are less 

likely to attempt to quit. It is less certain whether those who have made an 

attempt to quit are less likely to be successful if they are heavy smokers. 

Cessation in states with Recent evidence has demonstrated a slowing of the 

large tobacco control pro- rate of decline in cigarette consumption and smokgrams (California and ing prevalence for both the nation and for 

Massachusetts) compared to California. Analyses of these trends have raised 

the rest of the United States questions about the recent effectiveness of the 

California Tobacco Control Campaign (Pierce et al., 1998a & b), with the 

suggestion that reductions in funding have dramatically reduced the effectiveness of tobacco control effort during the 1993-1996 period. Cessation is 

one measure of the effectiveness of tobacco control programs; and various 

cessation measures for California and Massachusetts—two states with large, 

47

Smoking and Tobacco Control Monograph No. 12 Figure 2-7 Current Population Survey 1992/93: Odds Ratios for Successful Cessation of 3+ Months Duration 

2 +5

15 24

5 14

1 4

$75 0 +

$50 $74 9

$30 $49

$20 $29

$10 $19

<$10

1 +6 e Y ra s

13 1 Y5 ae sr

1 Y2 ae sr

<1 Y2 ae sr

O ht er

Afr ci na mA re

H si p na ci

Non H si p Wh ti e

6 +5

45 64

25 4

F me l a e

M l a 1.00 e 1.00 1.00 1.00 1.00 1.00 1.12 2.15 0.62 0.96 1.17 1.19 1.51 1.31 1.13 2.22 2.14 1.77 1.56 1.26 0.59 0.65 0.86

G A R E E H m C D Odds Ratio

48

Chapter 2 

Figure 2-8 Current Population Survey 1995/96: Odds Ratios for Successful Cessation of 3+ Months Duration 2 +5 15 24 5 14 1 4 $75 0 + $50 $74 9 $30 $49 $20 $29 $10 $19 <$10 1 +6 e Y ra s 13 1 Y5 ae sr 1 Y2 ae sr <1 Y2 ae sr O ht re Afr ci na mA re H si p na ci Non H si p Wh ti e 6 +5 45 64 25 4 F me l a e M l a 1.00 e 1.00 1.00 1.00 1.00 1.00 0.97 1.59 1.06 0.73 1.13 1.01 1.84 1.59 1.27 1.61 1.14 1.15 1.02 1.08 0.61 0.70 0.83 G A R E E H m C D Odds Ratio

49

Smoking and Tobacco Control Monograph No. 12 

well-funded tobacco control programs—can be compared to the remaining 

48 states using the two sets of CPS survey data. Because smoking prevalence 

and cessation are influenced by differences between states in demographic 

characteristics and number of cigarettes smoked per day, it is difficult to 

directly compare population prevalence measures of current smoking or of 

cessation as an evaluation of the differences in the effectiveness of various 

states’ tobacco control efforts. We examine measures of cessation among 

adults as one direct measure of the success of these tobacco control efforts 

using multivariate logistic regression analyses to control for demographic 

differences and differences in number of cigarettes smoked per day. We 

compare measures of cessation among California and Massachusetts adults 

with those of the remaining states. 

To control for differences between California and the remaining states 

in demographic composition and numbers of cigarettes smoked per day, 

multivariate logistic regression modeling of the cessation measures was conducted for each of the surveys and then for the combined survey data set, 

with survey year and geographic location (California, Massachusetts, or 

other states) as variables in the analysis. The odds ratios for these analyses 

are presented in Table 2-5, and the complete results of the analysis are presented in Table 2-14. 

The results demonstrate a clear time trend across the two surveys. There 

was a significant decline in the prevalence of any cessation activity and of 

3+ month cessation success between the 1992/93 and 1995/96 surveys, with 

no significant change in the likelihood of becoming an occasional smoker. 

Both California and Massachusetts had statistically significantly higher 

cessation activity (the change measure in the tables) compared to other 

states. Massachusetts had an increase in cessation attempts, and California 

had an increase in likelihood of becoming an occasional smoker. Both 

Massachusetts and California also had increases in the likelihood of a current daily smoker becoming a former smoker in the last year, compared to 

other states. The likelihood of achieving 3+ months of cessation was also 

significantly higher in California—and higher with borderline significance 

(p = 0.051) for Massachusetts—when compared to the remaining states. 

These analyses demonstrate that cessation activity declined in 

Massachusetts, California, and the rest of the states between 1992/93 and 

1995/96. However, California and Massachusetts had higher rates of successful cessation and cessation activity when compared to the remaining 

states. The higher rates of cessation activity and cessation success in 

California and Massachusetts provides evidence for a substantial impact of 

the tobacco control programs on cessation in these two states. 

CESSATION IN CALIFORNIA In 1988, California passed Proposition 99, which 

Michael Johnson and Jacqueline Major	 increased the taxes on cigarettes by 25 cents per 

pack, and a part of that tax increase was used to 

fund a tobacco control program. As part of that program, detailed surveys 

of smoking behavior were conducted in 1990 and 1996, with more limited 

surveys conducted in 1992 and 1993. 

50

Chapter 2 

(0.65 -0.76) 

(1.17 -1.49) 

(1.00 -1.55) 

1Cessation Activity: Includes those who have made a quit attempt, have become occasional smokers, or have become former smokers. 2Cessation Attempt: Includes those who have made a quit attempt or have become former smokers. Occasional smokers are excluded from both the numerator and denominator. 3Occasional: Includes those who reduced from smoking everyday, to smoking some days. 

*Also adjusted for gender, age, race/ethnicity, education, household income, and number of cigarettes per day. 

Former, 3+ Months 

95% CI 

Odds Ratios* and 95% Confidence Intervals for Measures of Cessation in California and Massachusetts Compared to the Remaining States 

Odds 

Ratio 

1.00 

0.70 1.00 

1.32 

1.24 

(0.68 -0.77) 

(1.09 -1.33) 

(1.09 -1.56) 

Former (any length) 

95% CI 

Odds 

Ratio 

1.00 

0.73 1.00 

1.20 

1.31 

(0.86 -1.03) 

(1.13 -1.49) 

(0.74 -1.34) 

95% CI 

Occasional3 

Odds 

Ratio 

1.00 

0.94 1.00 

1.30 

1.00 

Cessation Attempt2 

(0.77 -0.82) 

(0.98 -1.10) 

(1.17 -1.45) 

95% CI 

Odds 

Ratio 

1.00 0.80 

1.00 1.04 

1.30 

(0.78 -0.83) 

(1.00 -1.12) 

(1.15 -1.42) 

Cessation Activity1 

95% CI 

Odds 

Ratio 

1.00 0.80 

1.00 1.06 

1.28

Rest of USA 

Massachusetts 

Survey Year 

California 

Table 2-5 Variable 

1992/3 1995/6 

Region 

51

Smoking and Tobacco Control Monograph No. 12 

Differences between When the results of the 1996 California Tobacco Surveys 

the CPS for California are compared to the 1995/96 CPS data for the state of 

and CTS Data California, some differences in the cessation measures are 

evident. The CPS data estimate that a higher fraction of those who were 

daily smokers 1 year prior to the survey had not made an attempt to quit 

(64.3 ± 2.4 percent, Table 2-3; compared to 53.6 ± 1.4 percent, Table 2-16), 

and the fraction who were former smokers of less than 3 months duration 

was lower in the CPS (2.2 ± 0.7 percent) than in the CTS (4.8 ± 0.7 percent). 

The rates for occasional smoking and for cessation of 3+ months' duration 

are essentially identical. It is unclear whether the differences between these 

two surveys in frequency of these cessation measures relate to the survey 

designs, the populations sampled, or the timing of the surveys. 

Distribution of the Figure 2-9 and Table 2-6 present the current smoking status 

Cessation Measures among those age 25 and older who were daily smokers 1 

in the CTS Data year prior to the survey for the 1996 California Tobacco 

Survey. Because this survey asked occasional smokers about cessation 

attempts in the last year, it is possible to demonstrate that nearly 75 percent 

of those smokers who reported shifting from daily smoking to occasional 

smoking also made a quit attempt in the previous year. This suggests that 

many of these former daily smokers who are current occasional smokers are 

either in process of cessation or in the process of relapsing from a cessation 

attempt. 

Incorporating the cessation attempt information for occasional smokers 

into the cessation attempt measure allows estimation of the frequency of 

cessation attempts for all those who were daily cigarette smokers 1 year 

prior to the survey, including those who had become occasional smokers. 

Using the 1996 CTS data, approximately 45 percent of those who were daily 

smokers 1 year prior to the survey made cessation attempts and almost 10 

percent were successfully quit at the time of the survey. 

Change in Cessation Cessation measures for the California surveys were calbetween 1990 and 1996 culated using the same approach that was utilized for 

the CPS data, as presented in the first section of this chapter. Table 2-6 presents the measures of cessation for the 1990 and 1996 CTS. There is a small 

and not statistically significant decline in the fraction of former daily smokers who have been quit for 3 or more months—consistent with that seen in 

the CPS. However, there is little suggestion from these data of a substantial 

decline in rates of cessation success or cessation attempts in California 

between 1990 and 1996. There is a small increase in the prevalence of occasional smoking between these two surveys, but this difference is probably 

due to a change in the definition of current smoking used in the CTS. 

Current smokers of at least 100 lifetime cigarettes were defined by the question “Do you smoke everyday, some days or not at all?” in the 1996 CTS 

and in the 1990 survey by the question “Do you smoke cigarettes now?” 

followed by “Do you smoke everyday or some days?” for positive answers 

to the first query. Tables 2-15 and 2-16 present the cessation measures for 

California by demographic characteristics for the 1990 and 1996 CTS. 

52

Chapter 2 

Figure 2-9 

California Tobacco Survey 1996: Current Smoking Status among Those who were 

Daily Cigarette Smokers 12 Months Ago, Ages 25 and Older 

Unknown length

Former smoker 3+ months

Former smoker <3 months

Current occasional smoker 

without quit attempt 

in last year

Current occasional smoker 

with quit attempt 

in last year

Current daily smoker 

without quit attempt 

in last year

Current daily smoker 

with quit attempt 

in the last year

Daily 

Smokers

Former 

Smokers

Occasional 

Smokers

3.31

1.27

0.63 4.76

5.03

31.42

53.58

Unknown

Length

Multivariate logistic regression analyses were also performed on the 

1990 and 1996 CTS in order to examine the influence of demographic characteristics and number of cigarettes smoked per day on the measures of 

change, and they are presented as Tables 2-12 and 2-13. In general, the 

results of these analyses were similar to those found when the analyses were 

performed on the CPS data. There was an increased likelihood of cessation 

activity (the change variable in the table) and cessation success with 

increasing levels of education in 1990, but the effect of education was 

markedly reduced or eliminated in the 1996 data. A decreasing likelihood of 

cessation activity, but greater likelihood of cessation success, was evident 

with increasing age in both surveys, although the effect was not statistically 

significant in the 1996 survey. There was also a decline in cessation activity 

with little falloff in cessation success for increasing number of cigarettes 

smoked per day in both surveys. 

In 1990, there was a higher likelihood of cessation activity among 

African-American and Hispanic smokers when compared to Non-Hispanic 

Whites, and Hispanic smokers had a significantly higher likelihood of successful cessation and of being successful for 3 or more months. By 1996, the 

53

Smoking and Tobacco Control Monograph No. 12 Current Smoking Status among Self-Respondents, Age 25 and Older, Identified as Daily Smokers 1 

Year Ago by the 1990 and 1996 

California 

Tobacco Surveys 

Daily Occasional Former 

Quit Unknown Population Sample Quit <3 Quit 3+ Quit 

Without Quit Quit 

Without Quit 

Attempts


%

± CI 

%

± CI 

%

± CI 

%

± CI 

%

± CI 

%

± CI 

%

± CI (N) (n)


Size Size 

Year 1990 32.67 1.72 53.20 1.72 2.64 0.51 0.84 0.32 4.15 0.68 5.56 0.73 0.95 0.50 3,419,535 7,260 

2,894,421 6,211 0.63 0.22 5.03 0.79 4.76 0.66 1.27 0.45 3.31 0.53 53.58 1.40 

Months Duration Attempts Months Attempts Attempts 

31.42 1.28 

TNote: CI = 95% confidence interval. 

able 2-6 

1996 

54

Chapter 2 

cessation activity measure for Hispanic smokers had a lower odds ratio but 

was still statistically significant; however, their likelihood of successful cessation was no longer statistically significantly different from those of NonHispanic White smokers. 

Among African-Americans, the odds ratio for cessation activity (change) 

was statistically significantly higher when compared to Non-Hispanic 

White smokers for both the 1990 and 1996 CTS, but their likelihood of cessation success was significantly lower than for Non-Hispanic Whites in 

1996. It is clear that there has been a decline in cessation activity and cessation success among both African-American and Hispanic smokers in 

California between 1990 and 1996. In 1990, both groups had increased 

rates of cessation activity, and Hispanic smokers had increased rates of cessation success, but by 1996 odds ratios for cessation activity among 

Hispanic smokers had fallen, and the likelihood of cessation success was 

significantly lower among African-Americans when compared to nonHispanic Whites. These analyses control for differences in education and 

income as well as for number of cigarettes smoked per day among the different racial and ethnic groups. When the effects of poverty and low educational attainment are added to the effects of race and ethnicity, the picture 

of cessation for these groups becomes even more bleak. The magnitude of 

the change in California and the absence of similar changes in the CPS data 

suggest that the California Tobacco Control program may have preferentially reached African-American and Hispanic smokers in the early years of the 

program, but the effect appears to have largely disappeared by 1996. 

SMOKING BEHAVIOR A 25-cent per pack tax on cigarettes was implemented in 

IN MASSACHUSETTS: January of 1993 in Massachusetts. A mass media cam1993 TO 1997 paign was launched in October of that year, but most of 

Lois Biener the other interventions associated with the Massachusetts 

Tobacco Control Program were not fully operational until 

well into 1994. Evaluation activities have consisted primarily of populationbased surveys conducted by the Center for Survey Research at the 

University of Massachusetts and an independent evaluation based at Abt 

Associates, which assembles program information from a management 

information system, tobacco consumption information based on tax data, 

and other relevant information that becomes available from a variety of 

sources (such as the Behavioral Risk Factor Survey, the tracking research 

conducted by a market research organization, and independent research 

projects). Assembling data from all of these sources, including the population-based surveys, Abt publishes an annual report each fiscal year describing the impact of the Massachusetts Tobacco Control Program. The most 

recent report covers fiscal year (FY) 1997 and includes data from July 1996 

through June of 1997 (Hamilton, 1998). That report summarizes the data 

relevant to adult smoking behavior in Massachusetts as follows: 

• Cigarette consumption in Massachusetts has fallen by 31 percent 

since 1992, compared with a drop of 8 percent in the rest of the 

United States. 

55

Smoking and Tobacco Control Monograph No. 12 

• Smoking prevalence among adults is declining slowly (from 22.6 

percent in 1993 to 20.6 percent in FY 97), but the difference is 

not statistically significant. 

• The number of cigarettes smoked per day by adult smokers has 

declined significantly from 20 cigarettes per day in 1993 to 16 

per day in FY 97. 

• The rate of cessation and cessation attempts among past-year 

smokers has risen from 1993 to FY 97, but not significantly. 

• Significantly more smokers are considering quitting in the next 

30 days. 

The analyses presented in this paper were undertaken shortly after data 

for the calendar year 1997 became available for analysis, and they cover the 

same variables summarized above (with the exception of tax data on consumption). Whenever possible, analyses have been designed to correspond 

with those being produced from the CPS and include demographic breakdowns to determine whether changes in any particular population group 

are apparent. The CPS analyses usually focus on daily smokers rather than 

both daily and occasional smokers. Because the Massachusetts surveys did 

not question recent quitters on their previous smoking patterns, we cannot 

distinguish between those quitters who were occasional smokers prior to 

quitting in the past year and those who were daily smokers prior to quitting. 

Cross-sectional The baseline Massachusetts Tobacco Survey was a probability 

Surveys of Adults sample of Massachusetts housing units that used randomdigit-dial techniques to contact subjects by telephone. Initial brief interviews were carried out with an adult household informant in 11,463 households. The informant provided information about the other residents of the 

household—the age, gender, ethnic and racial background of all residents, 

and the smoking status of each adult resident. Based on the household enumeration, a representative sample of adults was selected for extended interview. The adult sampling design oversampled smokers and minority-group 

members. Adult interviews were conducted in English, Spanish, and 

Portuguese. Interviewing was conducted between October 1993 and March 

1994, with 70 percent of the interviews completed by January 31, 1994. The 

response rate was 78 percent for the household interviews and 78 percent 

and 75 percent for the eligible adults and teens, respectively. 

Follow-up cross-sectional data are available for adults from the 

Massachusetts Adult Tobacco Survey (MATS), which is an ongoing monthly 

Random Digit Dial survey. Beginning in March 1995, MATS samples 

approximately 225 adults per month. Like the baseline survey, MATS 

includes a screening interview and an extended interview, with one adult 

selected for extended interview from among adults living in the household. 

The annual samples for MATS are about half the size of the baseline, and 

the MATS sample design does not oversample smokers or minority group 

members. Consequently, data on changes among smokers tend to have 

lower statistical power. Detailed information about the methodology of 

these surveys has been published elsewhere (Biener et al., 1994; Biener and 

Roman, 1996). 56

Chapter 2 

Estimates of smoking prevalence are derived from the household screener, who provides information on smoking prevalence for many more adults 

than are interviewed personally. Although much of the information is 

based on proxy report, these reports of current smoking status have been 

determined to correspond with self-report more than 90 percent of the time 

(Biener et al., 1994; Gilpin et al., 1994). 

Progress toward When considering whether progress has been made toward 

smoking cessation smoking cessation in Massachusetts, we examined several 

different self-report indicators from the cross-sectional surveys—changes in 

smoking prevalence over time, changes in rates of successful quitting 

among those who were smoking during the prior year, and changes in rates 

of attempting to quit among the same group. Next we examined changes in 

smoking patterns of current daily smokers—the number of cigarettes being 

smoked each day, the proportion who waited more than 30 minutes after 

waking to light their first cigarette, and the proportion who report intending to quit in the next 30 days. In addition to examining overall statewide 

estimates, we examined these variables for men and women separately and 

for different age, education, ethnic, and income groups. 

RESULTS	 Smoking prevalence as estimated by the screening instruments has declined by about 2 percentage points from Smoking Prevalence 1993 to 1997. The drop is somewhat greater among men 

(23.6 to 20.9 percent) than among women (21.8 to 20.4 percent). 

Consistent declines from year to year can be seen among those in the 25- to 

44-year-old age group, the largest segment of the adult population—overall 

drop, 26.3 to 22.7 percent; men, 27.2 to 24.8 percent; and women, 25.3 to 

20.8 percent. The largest declines can be seen among the least-educated 

groups, those with less than 12 years of education—overall drop, 30.5 to 

24.6 percent; men, 34.1 to 29.8 percent; and women, 26.7 to 20.5 percent. 

None of these changes, however, reach statistical significance. 

Estimates of smoking prevalence derived from the extended interview 

are very similar to those derived from the screener. Although estimates 

diverged a bit during 1995 and 1996, the overall trends are quite consistent 

for all smokers (i.e., both daily and occasional smokers). The prevalence of 

daily smoking dropped by almost 4 percentage points between 1993 and 

1995/96, but increased again in 1997. 

We see very minor declines in smoking prevalence. The drop in the 

poorly educated group, if reliable, may be a result of the price increase or 

the media campaign. 

Cessation Rates Cessation rates were computed as the proportion of past-year 

smokers who reported having quit smoking regularly in the year prior to 

being interviewed. Both daily and occasional smokers are included because 

the MATS did not query quitters about their smoking levels prior to quitting. A quitter is defined as a person who reported having smoked 100 cigarettes in his/her lifetime, currently smokes “not at all,” and quit smoking 

regularly less than 1 year ago. We are unable to distinguish between quitters 

who were abstinent for more than or less than 3 months in 1993 due to difficulties with the dating function on our computer assisted telephone inter57

Smoking and Tobacco Control Monograph No. 12 

viewing program. Therefore, all estimates are for those who reported being 

nonsmokers on the day of the interview. The overall cessation rate 

increased by 2.8 percentage points between 1993 and 1997 (from 8.1 ± 2.6 

percent to 10.9 ± 4.8 percent). The largest increase in cessation rates was 

among the 25- to 44-year-old age group (from 4.1 ± 2.1 percent to 10.0 ± 

6.0 percent), although the group shows a curvilinear rather than a linear 

trend over time. These rates are presented by demographic subgroups in 

Table 2-17. 

Quit Attempts Another indicator of cessation activity is the attempt to quit. 

The variable under examination is the proportion of past-year smokers who 

report having quit smoking for at least 24 hours during the past year. This 

includes those who reported being abstinent at the time of the interview 

(i.e., those who succeeded in quitting). The overall rate is about the same in 

1997 as it was in 1993, although it rose by 5 percentage points in the intervening years. Women show a generally increasing rate of quit attempts. 

Again the 25- to 44-year-old age group shows the greatest improvement in 

quit attempts. These rates are presented by demographic subgroups in 

Table 2-18. 

Intentions to Quit All current smokers were asked whether they were planning 

to quit smoking within the next 30 days. The proportion of all smokers 

who answered “yes” increased from 1993 (28.6 ± 5.2 percent) to 1997 (33.3 

± 6.6 percent). The proportion of daily smokers who reported planning to 

quit in the next 20 days also increased from 23.8 ± 4.9 percent to 29.3 ± 6.6 

percent. These rates are presented by demographic subgroups in Tables 2-18 

and 2-19. 

These data from the Massachusetts surveys are consistent with the data 

from the CPS, which show higher cessation rates for Massachusetts when 

compared to other states. 

SUMMARY Cessation is one of the principal goals of tobacco control programs, both nationally and for individual states. Cessation is a process of 

individual change where many individuals are interested in quitting, a large 

number attempt to change their behavior, and a relatively small number are 

successful in quitting over the long term. 

A cessation attempt is clearly a necessary step on the path to successful 

cessation, but rates of cessation attempts are not necessarily good predictors 

of rates of cessation success. Cessation attempts are substantially lower 

among older smokers and among smokers of higher numbers of cigarettes 

per day, but the likelihood of successful cessation lasting 3 or more months 

is higher among older smokers and changes little between smokers of 5-14 

cigarettes per day and smokers of 25+ cigarettes per day. In contrast, both 

cessation attempts and cessation success are increased with higher levels of 

educational attainment. Many of the differences among racial and ethnic 

groups in cessation are diminished when differences in education, income, 

and number of cigarettes smoked per day are controlled for in the analysis. 

However, African-Americans appear to have lower rates of successful cessation lasting 3 or more months, even when these factors are considered. 

58

Chapter 2 

Between 1993 and 1996, rates of cessation activity declined in the 

United States, as did rates of 3+ month successful cessation. These changes 

are consistent with the observation that per-capita consumption of cigarettes has remained constant for the nation over this period. 

Two states, Massachusetts and California, have conducted large tobacco 

control programs, each with the goal of increasing adult cessation. When 

cessation measures for these states are compared to those for the remaining 

48 states—controlling for differences among the states in age, race/ethnicity, education, income, and number of cigarettes smoked per day—California and Massachusetts have higher rates of both cessation activity and successful cessation. These analyses support an effect of these tobacco control 

programs in creating successful adult cessation. 

59

Chapter 2 

Appendix 1 

Tables 2-7 through 2-20 

Footnotes to Tables 2-10 through 2-14: 

1. Cessation Activity: Includes those who have made a quit attempt, have become 

occasional smokers, or have become former smokers. 

2. Cessation Attempt: Includes those who have made a quit attempt or have 

become former smokers. Occasional smokers are excluded from both the 

numerator and denominator. 

3. Occasional: Includes those who reduced from smoking everyday to smoking 

some days. 

61

Chapter 2 

Table 2-7 

1992/1993 Current Population Survey: Cigarette Prevalence among All Adults, 

18 Years and Older 

Smoking Status Population Sample


Daily Occasional Former Never Size Size


Nation % ± CI % ± CI % ± CI % ± CI (N) (n)


Total 19.61 0.18 4.23 0.09 22.49 0.19 53.67 0.22 185,341,585 275,895 

Male Total 21.86 0.27 4.61 0.14 26.99 0.29 46.54 0.32 88,350,523 127,377 

Female Total 17.57 0.24 3.89 0.12 18.39 0.24 60.16 0.30 96,991,062 148,518 

Age (Years) 

18–24 17.59 0.46 4.96 0.26 6.09 0.29 71.35 0.55 25,314,984 33,537 

25–44 22.98 0.28 5.15 0.15 17.07 0.25 54.79 0.34 81,699,173 119,901 

45–64 21.09 0.36 3.62 0.16 31.66 0.41 43.63 0.44 48,177,432 73,698 

65+ 9.82 0.33 2.10 0.16 36.27 0.53 51.82 0.55 30,149,997 48,759 

Race/Ethnicity 

Non-Hispanic 

White 20.75 0.21 3.73 0.10 25.31 0.22 50.21 0.26 141,799,567 222,163 

Hispanic 12.04 0.67 6.17 0.50 13.30 0.70 68.49 0.96 16,240,415 18,067 

African-Amer. 19.40 0.54 6.17 0.33 13.68 0.47 60.75 0.66 20,574,151 24,492 

Asian/PI 11.09 0.83 3.59 0.49 11.28 0.84 74.05 1.16 5,397,590 8,259 

Native Amer. 31.64 2.71 7.28 1.52 15.76 2.13 45.32 2.91 1,117,516 2,586 

Other 9.94 4.01 4.52 2.78 15.92 4.90 69.62 6.16 212,346 328 

Education (Years) 

<12 24.61 0.45 4.58 0.22 21.37 0.43 49.44 0.53 33,519,656 48,611 

24.19 0.32 4.44 0.15 21.93 0.31 49.44 0.37 67,364,829 101,699 

13–15 18.19 0.34 4.40 0.18 21.88 0.37 55.53 0.44 46,824,878 69,259 

16+ 8.73 0.28 3.33 0.18 25.24 0.43 62.69 0.48 37,632,222 56,326 

Household Income (Dollars) 

<10,000 26.38 0.55 5.42 0.28 15.99 0.45 52.21 0.62 24,210,219 35,730 

10,000-19,999 22.84 0.44 4.69 0.22 21.12 0.43 51.36 0.53 33,448,107 50,259 

20,000-29,999 21.61 0.46 4.23 0.22 22.35 0.46 51.81 0.56 29,875,514 45,054 

30,000-49,999 18.99 0.36 4.05 0.18 23.29 0.39 53.67 0.46 44,519,871 66,724 

50,000-74,999 14.93 0.42 3.74 0.22 25.41 0.52 55.92 0.59 26,511,902 38,987 

75,000 + 10.32 0.45 3.08 0.26 28.03 0.67 58.57 0.74 16,667,077 24,205 

Unknown 17.17 0.72 3.88 0.37 22.64 0.80 56.31 0.95 10,108,895 14,936 

States 

Utah 13.64 1.32 3.26 0.68 16.95 1.44 66.14 1.82 1,179,841 2,952 

California 14.40 0.51 4.54 0.30 20.88 0.59 60.17 0.71 22,249,501 20,809 

District of 

Columbia 15.89 1.62 7.34 1.15 18.27 1.71 58.51 2.18 437,103 2,209 

N. Jersey 16.57 0.72 3.81 0.37 23.40 0.82 56.23 0.96 5,824,375 11,313 

N. York 17.36 0.56 4.16 0.30 22.20 0.62 56.28 0.74 13,380,928 18,356 

N. Dakota 17.43 1.47 4.75 0.83 23.16 1.64 54.66 1.93 443,503 3,805 

Massachusetts 17.74 0.76 3.67 0.37 28.33 0.90 50.26 1.00 4,486,537 10,528 

Arizona 17.91 1.43 4.46 0.77 24.06 1.60 53.56 1.86 2,793,746 2,786 

Maryland 17.99 1.51 5.60 0.91 23.88 1.68 52.53 1.97 3,621,008 2,616 

Hawaii 18.38 1.53 3.79 0.76 20.62 1.60 57.21 1.96 808,387 2,535 

63


12 
Smoking and Tobacco Control Monograph No. 12 

Table 2-7 (continued) 

Smoking Status Population Sample 

Daily Occasional Former Never Size Size 

States % ± CI % ± CI % ± CI % ± CI (N) (n) 

Texas 18.39 0.80 5.06 0.45 20.01 0.82 56.53 1.02 12,556,301 12,459 

Nebraska 18.59 1.45 3.38 0.67 21.10 1.52 56.93 1.84 1,131,857 4,024 

Connecticut 18.63 1.65 3.68 0.80 23.92 1.81 53.78 2.11 2,427,232 2,755 

N. Mexico 18.72 1.50 5.27 0.86 23.82 1.64 52.19 1.92 1,108,244 3,052 

Rhode Island 18.75 1.62 4.45 0.85 27.92 1.86 48.89 2.07 736,986 2,468 

Pennsylvania 19.03 0.76 4.31 0.39 23.35 0.82 53.30 0.96 8,898,952 12,950 

Colorado 19.33 1.61 4.83 0.87 25.56 1.78 50.28 2.04 2,528,960 3,253 

Oregon 19.42 1.60 3.51 0.75 26.99 1.80 50.08 2.03 2,216,870 3,127 

Montana 19.59 1.58 3.94 0.77 24.85 1.72 51.61 1.99 588,805 3,780 

Iowa 19.65 1.53 3.85 0.74 22.01 1.59 54.49 1.91 2,041,504 3,990 

Illinois 19.65 0.81 4.82 0.44 22.02 0.85 53.51 1.02 8,402,459 10,849 

Idaho 19.95 1.49 3.66 0.70 23.02 1.57 53.37 1.86 747,016 3,545 

Delaware 19.95 1.64 3.34 0.74 24.01 1.75 52.70 2.05 509,081 2,236 

Washington 19.96 1.52 4.17 0.76 27.85 1.71 48.01 1.91 3,731,411 3,014 

Florida 20.07 0.72 3.82 0.34 24.39 0.77 51.71 0.90 10,226,811 12,270 

Georgia 20.21 1.53 4.11 0.76 19.85 1.52 55.83 1.89 4,855,056 3,124 

Minnesota 20.46 1.59 4.65 0.83 24.00 1.69 50.89 1.98 3,214,673 3,333 

S. Dakota 20.62 1.50 4.90 0.80 21.86 1.53 52.63 1.85 486,703 4,058 

N. Hampshire 20.67 1.73 4.02 0.84 29.73 1.95 45.58 2.13 816,350 2,244 

Wisconsin 20.79 1.51 5.36 0.84 25.20 1.62 48.66 1.86 3,606,127 4,405 

Virginia 20.86 1.41 4.61 0.73 23.09 1.47 51.44 1.74 4,598,847 3,917 

Kansas 20.90 1.54 3.33 0.68 23.08 1.60 52.70 1.89 1,783,399 3,695 

Wyoming 21.05 1.84 3.77 0.86 23.69 1.92 51.49 2.26 328,343 2,489 

Mississippi 21.20 1.67 4.26 0.83 17.29 1.55 57.25 2.02 1,845,081 4,097 

Louisiana 21.34 1.70 4.03 0.81 21.04 1.69 53.59 2.06 2,950,556 2,825 

S. Carolina 21.98 1.48 3.73 0.68 20.28 1.44 54.01 1.79 2,576,960 3,818 

Vermont 22.15 1.74 4.11 0.83 28.93 1.90 44.80 2.08 424,902 2,240 

Ohio 22.19 0.81 3.77 0.37 22.31 0.81 51.73 0.98 8,005,894 12,426 

Alabama 22.24 1.69 3.50 0.75 21.04 1.66 53.22 2.03 3,027,336 3,765 

N. Carolina 22.88 0.80 4.05 0.38 21.34 0.78 51.73 0.95 4,997,190 11,850 

Michigan 22.99 0.85 4.21 0.41 23.68 0.86 49.11 1.01 6,807,057 11,688 

Missouri 23.07 1.69 3.17 0.70 22.78 1.69 50.98 2.01 3,727,394 3,354 

Oklahoma 23.21 1.65 3.54 0.72 21.70 1.61 51.55 1.96 2,282,823 3,536 

Alaska 23.24 1.62 4.38 0.78 24.69 1.65 47.69 1.92 379,350 3,459 

Indiana 23.79 1.68 4.02 0.78 20.48 1.59 51.71 1.97 4,100,287 3,307 

Nevada 23.83 1.59 4.53 0.77 23.17 1.57 48.46 1.86 991,796 3,003 

Tennesee 24.21 1.60 4.32 0.76 20.05 1.50 51.41 1.87 3,694,775 3,784 

Maine 24.55 1.67 3.96 0.76 27.00 1.73 44.49 1.93 909,532 2,917 

Arkansas 24.98 1.77 3.75 0.78 20.67 1.65 50.60 2.04 1,738,687 3,658 

West Virginia 26.81 1.77 3.44 0.73 20.55 1.62 49.20 2.00 1,369,311 3,719 

Kentucky 29.16 1.79 2.82 0.65 21.01 1.61 47.01 1.97 2,745,738 3,503 

Note: CI = 95% confidence interval. 

64 
Chapter 2 

Table 2-8 

1995/1996 Current Population Survey: Cigarette Prevalence among All Adults, 

18 Years and Older 

Smoking Status Population Sample


Daily Occasional Former Never Size Size


Nation % ± CI % ± CI % ± CI % ± CI (N) (n)


Total 19.05 0.18 4.04 0.09 21.76 0.19 55.16 0.23 191,073,943 233,741 

Male Total 21.19 0.28 4.47 0.14 25.80 0.30 48.54 0.34 91,207,802 107,527 

Female Total 17.09 0.24 3.64 0.12 18.07 0.25 61.20 0.32 99,866,141 126,214 

Age (Years) 

18–24 18.07 0.50 5.31 0.29 5.95 0.31 70.68 0.59 24,553,115 26,448 

25–44 21.97 0.29 4.89 0.15 15.57 0.26 57.58 0.35 82,861,971 99,671 

45–64 20.66 0.36 3.38 0.16 30.12 0.41 45.83 0.45 52,233,863 66,149 

>64 9.43 0.34 1.89 0.16 36.55 0.56 52.13 0.58 31,424,993 41,473 

Race/Ethnicity 

Non-Hispanic 

White 20.46 0.22 3.59 0.10 24.63 0.23 51.32 0.27 143,857,651 185,654 

Hispanic 11.43 0.66 6.02 0.50 12.80 0.70 69.75 0.96 17,862,544 17,130 

African-Amer. 17.61 0.54 5.43 0.32 13.63 0.48 63.34 0.68 21,553,073 21,322 

Asian/PI 10.81 0.80 3.16 0.45 10.88 0.80 75.15 1.11 6,443,983 7,307 

Native Amer. 30.98 2.60 7.39 1.47 16.51 2.09 45.12 2.80 1,356,691 2,328 

Education (Years) 

<12 23.87 0.48 4.28 0.23 20.78 0.46 51.06 0.57 32,521,554 38,561 

24.19 0.34 4.11 0.16 21.49 0.33 50.21 0.40 65,924,580 81,861 

13–15 18.23 0.35 4.44 0.19 21.51 0.37 55.82 0.45 50,560,922 61,512 

16+ 8.24 0.27 3.25 0.18 23.24 0.42 65.27 0.47 42,066,887 51,807 

Household Income (Dollars) 

<10,000 24.97 0.62 5.62 0.33 15.59 0.52 53.81 0.71 20,702,223 25,171 

10,000-19,999 22.99 0.51 4.37 0.25 20.84 0.49 51.81 0.61 28,512,812 35,227 

20,000-29,999 22.21 0.50 4.33 0.25 21.65 0.50 51.80 0.61 28,393,827 35,079 

30,000-49,999 19.79 0.39 3.93 0.19 22.10 0.41 54.18 0.49 43,128,189 53,811 

50,000-74,999 15.59 0.43 3.49 0.22 23.26 0.50 57.66 0.59 29,582,858 36,172 

75,000+ 10.22 0.40 3.29 0.24 25.67 0.58 60.82 0.65 23,940,952 28,067 

Unknown 16.47 0.59 3.32 0.28 22.03 0.65 58.17 0.78 16,813,081 20,214 

States 

Utah 12.03 1.25 3.02 0.66 14.73 1.36 70.23 1.76 1,275,888 3,162 

California 13.54 0.53 4.39 0.32 20.65 0.62 61.43 0.75 22,521,022 17,647 

District of 

Columbia 15.32 1.54 6.93 1.08 18.72 1.66 59.03 2.10 414,451 2,275 

Connecticut 16.02 1.54 3.79 0.80 25.15 1.83 55.04 2.10 2,405,332 2,325 

N. Jersey 16.55 0.84 3.95 0.44 22.30 0.94 57.20 1.11 5,873,687 7,795 

N. York 16.87 0.61 4.00 0.32 20.63 0.66 58.50 0.80 13,404,633 15,075 

Maryland 17.11 1.50 3.97 0.78 23.84 1.69 55.08 1.98 3,713,252 2,631 

Massachusetts 17.13 0.94 3.54 0.46 26.84 1.10 52.49 1.24 4,511,380 6,503 

Nebraska 17.39 1.46 4.08 0.76 18.98 1.51 59.55 1.89 1,162,549 3,273 

Hawaii 17.86 1.61 3.90 0.81 20.21 1.69 58.03 2.07 830,154 2,149 

65


12 
Smoking and Tobacco Control Monograph No. 12 

Table 2-8 (continued) 

Smoking Status Population Sample


Daily Occasional Former Never Size Size


States % ± CI % ± CI % ± CI % ± CI (N) (n)


Colorado 18.10 1.50 4.45 0.80 23.57 1.65 53.88 1.94 2,732,339 3,219 

Texas 18.14 0.77 5.18 0.44 18.73 0.78 57.94 0.99 13,293,119 10,585 

Oregon 18.20 1.53 4.32 0.81 24.76 1.71 52.72 1.98 2,361,048 2,801 

Arizona 18.32 1.44 4.48 0.77 23.14 1.57 54.06 1.85 3,053,062 3,289 

Florida 18.49 0.74 3.75 0.36 23.78 0.81 53.98 0.94 10,721,274 10,714 

Minnesota 18.53 1.52 4.33 0.80 23.70 1.67 53.45 1.95 3,329,386 3,300 

N. Mexico 18.69 1.46 5.26 0.84 22.07 1.55 53.99 1.87 1,192,081 3,130 

S. Dakota 18.69 1.46 4.04 0.74 23.33 1.59 53.94 1.87 504,763 3,382 

Washington 18.95 1.58 4.33 0.82 24.52 1.74 52.20 2.02 3,991,919 2,890 

Idaho 18.99 1.48 3.33 0.68 22.21 1.57 55.47 1.87 824,393 3,290 

Georgia 19.04 1.39 3.75 0.67 18.81 1.38 58.40 1.74 5,229,881 3,942 

N. Dakota 19.08 1.57 4.66 0.84 22.06 1.65 54.20 1.99 447,176 3,218 

Alabama 19.20 1.52 4.01 0.76 19.57 1.53 57.21 1.91 3,114,758 3,173 

Illinois 19.56 0.86 4.11 0.43 21.21 0.89 55.12 1.08 8,571,555 9,553 

Mississippi 19.73 1.55 3.50 0.72 17.86 1.49 58.91 1.92 1,896,081 2,893 

Iowa 19.85 1.56 3.55 0.72 21.11 1.59 55.48 1.94 2,063,388 3,116 

Montana 20.07 1.53 3.86 0.73 27.45 1.70 48.61 1.91 633,417 3,391 

Pennsylvania 20.14 0.83 3.94 0.40 24.53 0.89 51.40 1.04 8,919,897 10,924 

Rhode Island 20.20 1.68 3.57 0.77 26.34 1.84 49.89 2.09 720,021 2,322 

Wisconsin 20.28 1.57 4.76 0.83 23.23 1.65 51.72 1.95 3,690,849 3,499 

N. Hampshire 20.43 1.72 3.24 0.76 29.40 1.95 46.93 2.13 848,541 2,357 

Delaware 21.16 1.67 3.67 0.77 23.00 1.72 52.17 2.04 528,094 2,302 

Alaska 21.16 1.63 4.14 0.79 23.05 1.68 51.64 1.99 395,832 2,252 

Louisiana 21.37 1.56 4.45 0.78 18.57 1.48 55.60 1.89 3,079,727 2,842 

Virginia 21.41 1.50 3.54 0.67 22.95 1.53 52.09 1.82 4,817,098 3,634 

Michigan 21.46 0.93 4.21 0.45 22.55 0.95 51.78 1.13 6,872,437 8,896 

Vermont 21.48 1.72 3.41 0.76 27.35 1.87 47.75 2.09 430,119 2,445 

S. Carolina 21.83 1.60 3.32 0.69 17.94 1.48 56.92 1.91 2,690,982 2,534 

Oklahoma 21.94 1.58 3.59 0.71 20.15 1.53 54.33 1.90 2,330,200 3,591 

Ohio 22.11 0.91 3.96 0.43 22.28 0.91 51.65 1.09 8,117,837 9,516 

Wyoming 22.12 1.72 2.94 0.70 22.13 1.72 52.81 2.07 340,426 3,162 

Kansas 22.12 1.66 3.75 0.76 20.64 1.62 53.49 2.00 1,798,120 3,064 

N. Carolina 22.63 1.07 3.58 0.48 19.90 1.02 53.89 1.28 5,286,952 7,715 

Missouri 22.70 1.64 3.27 0.70 23.06 1.65 50.97 1.96 3,866,274 2,890 

Maine 22.78 1.69 2.96 0.68 27.68 1.80 46.58 2.01 928,793 2,692 

Arkansas 22.95 1.62 3.62 0.72 19.74 1.54 53.68 1.92 1,827,297 3,129 

Tennesse 23.69 1.59 3.52 0.69 22.50 1.56 50.29 1.87 3,916,392 2,889 

Nevada 23.96 1.65 4.13 0.77 21.76 1.59 50.15 1.93 1,154,576 2,455 

W. Virginia 24.62 1.56 3.20 0.64 22.78 1.52 49.39 1.81 1,396,823 3,736 

Indiana 25.17 1.67 3.75 0.73 20.39 1.55 50.69 1.92 4,210,920 3,096 

Kentucky 26.92 1.69 2.76 0.62 21.66 1.57 48.66 1.90 2,833,747 3,078 

Note: CI = 95% confidence interval. 

66 
Chapter 2 

Table 2-9 

1995/1996 Current Population Survey: Prevalence of Former Cigarette Smokers among All 

Adults, 18 Years and Older 

Former Smoker 

% ± CI Quit Ratio 

Total 

by State 

Massachusetts


Connecticut


New Hampshire


California


Montana


Maryland


Rhode Island


Oregon


Vermont


New Jersey


Maine


Florida


Washington


Colorado


Minnesota


South Dakota


Pennsylvania


Arizona


Idaho


New York


Utah


North Dakota


Hawaii


Wisconsin


Delaware


New Mexico


Virginia


Alaska


Iowa


Illinois


Missouri


Nebraska


Wyoming


Michigan


Ohio


21.76 0.19 0.49 

26.84 1.10 0.56 

25.15 1.83 0.56 

29.40 1.95 0.55 

20.65 0.62 0.54 

27.45 1.70 0.53 

23.84 1.69 0.53 

26.34 1.84 0.53 

24.76 1.71 0.52 

27.35 1.87 0.52 

22.30 0.94 0.52 

27.68 1.80 0.52 

23.78 0.81 0.52 

24.52 1.74 0.51 

23.57 1.65 0.51 

23.70 1.67 0.51 

23.33 1.59 0.51 

24.53 0.89 0.50 

23.14 1.57 0.50 

22.21 1.57 0.50 

20.63 0.66 0.50 

14.73 1.36 0.49 

22.06 1.65 0.48 

20.21 1.69 0.48 

23.23 1.65 0.48 

23.00 1.72 0.48 

22.07 1.55 0.48 

22.95 1.53 0.48 

23.05 1.68 0.48 

21.11 1.59 0.47 

21.21 0.89 0.47 

23.06 1.65 0.47 

18.98 1.51 0.47 

22.13 1.72 0.47 

22.55 0.95 0.47 

22.28 0.91 0.46 

67

Smoking and Tobacco Control Monograph No. 12 

Table 2-9 (continued) 

Former Smoker 

% ± CI Quit Ratio 

Alabama


District of Columbia


Tennessee


Georgia


West Virginia


Texas


Kansas


Oklahoma


Nevada


Mississippi


North Carolina


Arkansas


Kentucky


Louisiana


South Carolina


Indiana


19.57 1.53 0.46 

18.72 1.66 0.46 

22.50 1.56 0.45 

18.81 1.38 0.45 

22.78 1.52 0.45 

18.73 0.78 0.45 

20.64 1.62 0.44 

20.15 1.53 0.44 

21.76 1.59 0.44 

17.86 1.49 0.43 

19.90 1.02 0.43 

19.74 1.54 0.43 

21.66 1.57 0.42 

18.57 1.48 0.42 

17.94 1.48 0.42 

20.39 1.55 0.41 

Note: CI = 95% confidence interval. 

68

Chapter 2 

Former (any length) Former, 3+ Months 

1.12 (1.02-1.23) 1.19 (1.08-1.32) 45–64


65+ 0.82 (0.76-0.89) 0.79 (0.73-0.86) 1.21 (1.00-1.47) 1.82 (1.60-2.06) 2.15 (1.86-2.49)


Race/Ethnicity 

Non-Hispanic White 1.00 1.00 1.00 1.00 1.00 Hispanic 1.01 (0.91-1.12) 1.01 (0.91-1.12) 1.04 (0.80-1.36) 1.09 (0.90-1.31) 1.17 (0.94-1.46) African-American
Other 0.98 (0.85-1.12) 0.99 (0.86-1.13) 0.89 (0.61-1.29) 0.67 (0.50-0.89) 0.62 (0.43-0.90)


0.96 (0.81-1.14) 

Education (Years) 

< 12 1.00 1.00 1.00 1.00 1.00 12 1.15 (1.08-1.22) 1.15 (1.08-1.23) 1.09 (0.92-1.30) 1.24 (1.10-1.40) 1.13 (0.99-1.30) 

1.31 (1.12-1.52) 13–15


16+ Years 1.43 (1.32-1.56) 1.40 (1.28-1.52) 1.65 (1.32-2.06) 1.72 (1.49-2.00) 1.51 (1.27-1.80)


Household Income (Dollars) 

<10,000 1.00 1.00 1.00 1.00 1.00 10,000-19,999 1.12 (1.05-1.21) 1.13 (1.05-1.22) 1.01 (0.83-1.23) 1.33 (1.15-1.55) 1.26 (1.05-1.50) 

1.56 (1.31-1.86) 20,000-29,999


30,000-49,999 1.37 (1.28-1.47) 1.40 (1.30-1.50) 1.03 (0.85-1.25) 1.85 (1.60-2.13) 1.77 (1.49-2.10)


2.14 (1.77-2.59) 50,000-74,999


75,000+ 1.67 (1.49-1.87) 1.69 (1.51-1.89) 1.25 (0.94-1.67) 2.16 (1.78-2.62) 2.22 (1.77-2.80)
5–14 0.82 (0.72-0.94) 0.87 (0.76-1.01) 0.61 (0.47-0.80) 0.66 (0.53-0.82) 0.65 (0.50-0.85) 

0.59 (0.46-0.76) 15–24


25+ 0.44 (0.38-0.50) 0.48 (0.42-0.56) 0.24 (0.18-0.32) 0.84 (0.67-1.05) 0.86 (0.66-1.11)


OR 95% CI 

1992/1993 Current Population Survey: Multivariate Logistic Regression Models of Cessation Measures for Adults who were Daily 

1.00 1.00 1.00 1.00 

Cigarettes smoked per day 

1–4 1.00 1.00 1.00 1.00 1.00 

1.05 (0.97-1.14) 1.19 (1.10-1.30) 0.89 (0.77-1.03) 1.41 (1.24-1.60) 1.57 (1.35-1.83) 2.11 (1.79-2.47) 0.58 (0.47-0.72) 

OR 95% CI 

1.21 (1.07-1.36) 0.95 (0.83-1.08) 1.29 (1.08-1.53) 1.44 (1.19-1.74) 0.88 (0.72-1.09) 1.19 (0.95-1.50) 0.38 (0.29-0.49) 

OR 95% CI 

Smokers 1 Year prior to the Survey, Ages 25 and Older 

Cessation Activity1 Cessation Attempt2 Occasional3 

1.00 1.00 1.00 1.00 1.04 (0.99-1.09) 0.89 (0.85-0.94) 1.10 (1.03-1.19) 1.38 (1.29-1.48) 1.31 (1.22-1.41) 1.54 (1.41-1.67) 0.60 (0.52-0.69) 

OR 95% CI 

1–3 See footnotes at beginning of table section for explanation. 

1.05 (1.01-1.10) 0.90 (0.85-0.94) 1.13 (1.05-1.21) 1.40 (1.31-1.50) 1.28 (1.19-1.38) 1.52 (1.39-1.65) 0.56 (0.49-0.64) 

OR 95% CI 

1.00 1.00 

Table 2-10 Variable 

Gender 

Male Female 

Age (Years) 

25–44 

69

Smoking and Tobacco Control Monograph No. 12 Former (any length) Former, 3+ Months 0.97 (0.86-1.09) 45–64
 65+ 0.76 (0.70-0.84) 0.74 (0.67-0.81) 1.14 (0.91-1.44) 1.40 (1.19-1.66) 1.59 (1.31-1.94)
 1.01 (0.89-1.15) Race/Ethnicity Non-Hispanic White 1.00 1.00 1.00 1.00 1.00 Hispanic 0.89 (0.80-1.00) 0.88 (0.79-1.00) 1.03 (0.78-1.37) 0.96 (0.76-1.22) 1.13 (0.86-1.49) African-American
 Other 1.03 (0.90-1.18) 1.03 (0.90-1.19) 1.01 (0.70-1.45) 1.07 (0.82-1.40) 1.06 (0.76-1.48)
 0.73 (0.57-0.92) 

12 1.17 (1.09-1.26) 1.16 (1.08-1.25) 1.22 (0.99-1.50) 1.25 (1.07-1.45) 1.27 (1.06-1.54) 

13–15
16+ 1.42 (1.29-1.57) 1.39 (1.26-1.54) 1.56 (1.20-2.04) 1.77 (1.46-2.14) 1.84 (1.46-2.32)


1.59 (1.31-1.95) 

Household Income (Dollars) 

<10,000 1.00 1.00 1.00 1.00 1.00 10,000-19,999 0.95 (0.88-1.04) 0.97 (0.89-1.06) 0.83 (0.66-1.04) 0.93 (0.77-1.12) 1.08 (0.87-1.35) 

1.02 (0.81-1.28) 20,000-29,999


30,000-49,999 1.07 (0.98-1.16) 1.08 (0.99-1.18) 0.97 (0.77-1.20) 1.13 (0.95-1.34) 1.15 (0.93-1.42)


1.14 (0.90-1.45) 50,000-74,999


75,000+ 1.10 (0.98-1.24) 1.12 (0.99-1.26) 0.98 (0.72-1.34) 1.48 (1.19-1.84) 1.61 (1.24-2.10)


Cigarettes smoked per day 

1–4 1.00 1.00 1.00 1.00 1.00 5–14 0.68 (0.59-0.79) 0.80 (0.68-0.93) 0.38 (0.29-0.48) 0.81 (0.60-1.08) 0.70 (0.50-0.98) 

0.61 (0.44-0.85) 15–24


25+ 0.32 (0.28-0.37) 0.39 (0.34-0.46) 0.12 (0.09-0.16) 0.90 (0.67-1.21) 0.83 (0.59-1.16)


OR 95% CI 

1995/1996 Current Population Survey: Multivariate Logistic Regression Models of Cessation Measures for Adults who were Daily 

1.00 1.00 1.00 1.00 

Education (Years) 

< 12 1.00 1.00 1.00 1.00 1.00 

0.93 (0.84-1.03) 0.97 (0.87-1.08) 

0.67 (0.55-0.82) 1.58 (1.34-1.86) 1.03 (0.86-1.24) 

1.15 (0.95-1.40) 

0.66 (0.50-0.88) 

OR 95% CI 

1.01 (0.89-1.16) 0.86 (0.74-1.01) 

1.30 (1.06-1.58) 1.55 (1.25-1.94) 0.79 (0.63-1.01) 

0.88 (0.68-1.14) 

0.20 (0.15-0.25) 

OR 95% CI 

Smokers 1 

Year prior to the Survey, Ages 25 and Older 

Cessation Activity1 Cessation Attempt2 Occasional3 

1.00 1.00 1.00 1.00 0.96 (0.91-1.01) 0.88 (0.84-0.93) 

1.00 (0.92-1.09) 1.45 (1.34-1.58) 0.98 (0.89-1.07) 

1.08 (0.98-1.20) 

0.55 (0.47-0.64) 

OR 95% CI 

1–3 See footnotes at beginning of table section for explanation. 

0.96 (0.92-1.01) 0.88 (0.83-0.93) 

1.03 (0.95-1.12) 1.48 (1.37-1.60) 0.96 (0.88-1.05) 

1.07 (0.97-1.17) 

0.46 (0.39-0.53) 

OR 95% CI 

1.00 1.00 

Table 2-11 Variable 

Gender 

Male Female 

Age (Years) 

25–44 

70

Chapter 2 

Gender 

Male 1.00 Female 1.00 ( 0.90-1.11 ) 1.00 ( 0.90-1.11 ) 0.86 ( 0.64-1.15 ) 1.23 ( 1.04-1.45 ) 1.41 ( 1.13-1.76 ) 

Age (Years) 

25-44 1.00 45–64 0.75 ( 0.67-0.85 ) 0.75 ( 0.67-0.85 ) 0.95 ( 0.69-1.31 ) 1.21 ( 1.01-1.45 ) 1.47 ( 1.16-1.86 ) 

1.70 ( 1.18-2.45 ) 1.40 ( 1.04-1.88 ) 0.73 ( 0.40-1.31 ) 0.76 ( 0.63-0.91 ) 

1.54 ( 1.09-2.17 ) Hispanic


African-American 2.05 ( 1.66-2.54 ) 1.89 ( 1.52-2.35 ) 2.99 ( 2.00-4.46 ) 1.19 ( 0.86-1.65 ) 1.33 ( 0.89-2.00 )


0.77 ( 0.47-1.29 ) 0.72 ( 0.49-1.07 ) 0.78 ( 0.40-1.55 ) 1.09 ( 0.88-1.35 ) 

1.44 ( 1.03-2.01 ) 12


13–15 1.34 ( 1.14-1.57 ) 1.32 ( 1.12-1.55 ) 1.50 ( 0.97-2.34 ) 1.64 ( 1.24-2.15 ) 1.68 ( 1.17-2.40 )
10,001-20,000
20,001-30,000 1.22 ( 1.01-1.48 ) 1.25 ( 1.02-1.52 ) 0.75 ( 0.44-1.27 ) 1.69 ( 1.19-2.42 ) 1.27 ( 0.83-1.92 )


1.03 ( 0.67-1.59 ) 

30,001-50,000
50,001-75,000 1.38 ( 1.12-1.70 ) 1.39 ( 1.13-1.72 ) 1.02 ( 0.57-1.80 ) 2.12 ( 1.46-3.06 ) 1.29 ( 0.83-2.02 )


1.11 ( 0.74-1.68 ) 

1.85 ( 1.16-2.95 ) 2.35 ( 1.58-3.49 ) 1.44 ( 0.78-2.66 ) 1.13 ( 0.89-1.43 ) 

0.49 ( 0.31-0.77 ) 5–14


15–24 0.41 ( 0.30-0.55 ) 0.46 ( 0.34-0.62 ) 0.22 ( 0.13-0.37 ) 0.38 ( 0.26-0.55 ) 0.34 ( 0.22-0.54 )


0.52 ( 0.32-0.83 ) 0.46 ( 0.31-0.67 ) 0.13 ( 0.07-0.25 ) 0.44 ( 0.32-0.60 ) 1.66 ( 1.11-2.49 ) 1.91 ( 1.41-2.59 ) 1.06 ( 0.61-1.85 ) 1.26 ( 1.05-1.53 ) 

Cessation Activity1 Former (any length) Former 3+ Months 

OR 95% CI OR 95% CI 95% CI 95% CI OR 95% CI OR OR 

1990 California Tobacco Survey: Logistic Regression Models of Cessation for Daily Smokers 12 Months Ago, Ages 25 and Older 

1.69 ( 1.31-2.20 ) 1.28 ( 0.99-1.66 ) 1.48 ( 1.03-2.13 ) 

1.76 ( 1.24-2.48 ) 

0.52 ( 0.36-0.75 ) 

2.02 ( 1.35-3.01 ) 1.08 ( 0.72-1.63 ) 1.20 ( 0.74-1.96 ) 

1.08 ( 0.67-1.76 ) 

0.63 ( 0.39-1.01 ) 

Cessation Attempt2 Occasional3 1.55 ( 1.30-1.84 ) 1.10 ( 0.95-1.27 ) 1.32 ( 1.08-1.61 ) 

1.31 ( 1.08-1.58 ) 

0.78 ( 0.57-1.08 ) 

1–3 See footnotes at beginning of table section for explanation. 

0.74 ( 0.62-0.90 ) 

1.60 ( 1.35-1.90 ) 

1.07 ( 0.87-1.32 ) 

1.10 ( 0.95-1.27 ) 

1.26 ( 1.04-1.51 ) 

1.32 ( 1.09-1.60 ) 

1.30 ( 1.08-1.57 ) 

1.16 ( 0.92-1.46 ) 

0.75 ( 0.55-1.02 ) 

0.39 ( 0.28-0.53 ) 

Race/Ethnicity 

Non-Hispanic White 1.00 

1.00 1.00 1.00 

Household Income (Dollars) Education (YCigarettes Smokd per Day 

ears) 

Table 2-12 Variable 

65+ 

Other 

<12 

16+ 

<10,000 

75,000+ 

1–4 

25 + 

71

Smoking and Tobacco Control Monograph No. 12 Gender Male 1.00 Female 0.96 ( 0.86-1.07 ) 0.94 ( 0.83-1.05 ) 1.26 ( 0.97-1.65 ) 1.23 ( 1.03-1.48 ) 1.17 ( 0.91-1.49 ) Age (Years) 25–44 1.00 45–64 0.65 ( 0.58-0.73 ) 0.65 ( 0.58-0.74 ) 0.83 ( 0.61-1.11 ) 0.78 ( 0.64-0.95 ) 0.97 ( 0.75-1.27 ) 1.43 ( 0.96-2.15 ) 1.25 ( 0.92-1.70 ) 0.88 ( 0.52-1.51 ) 0.62 ( 0.50-0.77 ) Hispanic
 African-American 1.29 ( 1.04-1.60 ) 1.24 ( 0.99-1.55 ) 1.54 ( 1.00-2.35 ) 0.47 ( 0.30-0.75 ) 0.66 ( 0.38-1.15 )
 1.15 ( 0.79-1.66 ) 0.73 ( 0.47-1.15 ) 0.72 ( 0.52-1.00 ) 0.69 ( 0.41-1.17 ) 0.95 ( 0.79-1.15 ) 

12
13–15 0.95 ( 0.80-1.11 ) 0.89 ( 0.75-1.05 ) 1.96 ( 1.31-2.95 ) 1.04 ( 0.79-1.36 ) 1.04 ( 0.72-1.50 )


0.80 ( 0.55-1.15 ) 

1.39 ( 0.93-2.08 ) 1.40 ( 1.03-1.88 ) 1.65 ( 1.02-2.67 ) 1.11 ( 0.91-1.35 ) 

10,001-20,000
20,001-30,000 0.96 ( 0.79-1.17 ) 1.00 ( 0.81-1.22 ) 0.67 ( 0.41-1.09 ) 1.22 ( 0.85-1.74 ) 1.21 ( 0.76-1.93 )


0.98 ( 0.60-1.61 ) 

1.24 ( 0.79-1.93 ) 30,001-50,000


50,001-75,000 1.10 ( 0.89-1.35 ) 1.11 ( 0.90-1.38 ) 0.94 ( 0.59-1.51 ) 1.26 ( 0.87-1.82 ) 1.45 ( 0.90-2.32 )


1.60 ( 0.98-2.62 ) 1.87 ( 1.29-2.71 ) 0.72 ( 0.41-1.26 ) 1.12 ( 0.89-1.41 ) 

0.88 ( 0.49-1.60 ) 5–14


15–24 0.48 ( 0.35-0.66 ) 0.65 ( 0.46-0.90 ) 0.17 ( 0.11-0.26 ) 0.50 ( 0.33-0.77 ) 0.62 ( 0.34-1.13 )


0.83 ( 0.45-1.54 ) 0.67 ( 0.43-1.04 ) 0.11 ( 0.06-0.20 ) 0.54 ( 0.38-0.77 ) 

Cessation Activity1 Former (any length) Former 3+ Months 

OR 95% CI OR 95% CI 95% CI 95% CI OR 95% CI OR OR 

1996 California 

Tobacco Survey: Logistic Regression Models of Cessation for Daily Smokers 12 Months Ago, Ages 25 and Older 

1.12 ( 0.86-1.48 ) 0.76 ( 0.58-1.00 ) 1.23 ( 0.86-1.77 ) 

1.44 ( 1.03-2.01 ) 

0.64 ( 0.42-0.98 ) 

1.68 ( 1.16-2.43 ) 1.08 ( 0.71-1.65 ) 0.87 ( 0.54-1.39 ) 

0.89 ( 0.57-1.38 ) 

0.34 ( 0.22-0.51 ) 

Cessation Attempt2 Occasional3 1.18 ( 0.99-1.40 ) 0.71 ( 0.61-0.84 ) 1.20 ( 0.98-1.48 ) 

1.07 ( 0.88-1.30 ) 

0.99 ( 0.71-1.39 ) 

1–3 See footnotes at beginning of table section for explanation. 

0.63 ( 0.51-0.77 ) 

1.22 ( 1.04-1.46 ) 

0.93 ( 0.77-1.12 ) 

0.73 ( 0.62-0.85 ) 

1.16 ( 0.95-1.40 ) 

1.18 ( 0.96-1.44 ) 

1.05 ( 0.87-1.27 ) 

1.08 ( 0.86-1.35 ) 

0.77 ( 0.56-1.06 ) 

0.40 ( 0.29-0.55 ) 

Race/Ethnicity 

Non-Hispanic White 1.00 

1.00 1.00 1.00 

Education (YHousehold Income (Dollars) Cigarettes Smoked per Day 

ears) 

Table 2-13 

16+ 

<10,000 

75,000+ 

1–4 

25 + 

Variable 

65+ Other 

<12 

72

Chapter 2 

Former 3+ Months 

95% CI 

(0.65-0.76) (1.17-1.49) 

(1.00-1.55) 

(0.98-1.14) (1.03-1.21) 

(1.70-2.14) 

(0.93-1.31) 

(0.76-1.00) 

(0.59-0.97) 

(1.05-1.32) 

(1.23-1.56) 

(1.40-1.86) 

Current Population Survey: Odds Ratios and 95% Confidence Intervals for Measures of Cessation in California and Massachusetts 

Compared to the Remaining States 

OR 

1.00 0.70 1.00 1.32 

1.24 

1.00 1.06 1.00 1.12 

1.91 

1.00 1.10 

0.87 

0.76 

1.00 1.18 

1.38 

1.62 

Former (any length) 

95% CI 

(0.68-0.77) (1.09-1.33) 

(1.09-1.56) 

(0.95-1.07) (1.03-1.17) 

(1.48-1.81) 

(0.87-1.17) 

(0.71-0.90) 

(0.67-0.99) 

(1.13-1.36) 

(1.32-1.61) 

(1.54-1.95) 

OR 

1.00 0.73 1.00 1.20 

1.31 

1.00 1.01 1.00 1.10 

1.63 

1.00 1.01 

0.80 

0.81 

1.00 1.24 

1.46 

1.73 

95% CI 

(0.86-1.03) (1.13-1.49) 

(0.74-1.34) 

(1.03-1.23) (0.82-1.00) 

(1.01-1.36) 

(0.81-1.20) 

(1.13-1.47) 

(0.69-1.17) 

(1.00-1.31) 

(1.27-1.70) 

(1.35-1.90) 

Occasional3 

OR 

1.00 0.94 1.00 1.30 

1.00 

1.00 1.13 1.00 0.91 

1.17 

1.00 0.98 

1.29 

0.90 

1.00 1.14 

1.47 

1.60 

Cessation Attempt2 

95% CI 

(0.77-0.82) (0.98-1.10) 

(1.17-1.45) 

(0.97-1.04) (0.86-0.92) 

(0.72-0.82) 

(0.88-1.03) 

(1.00-1.12) 

(0.91-1.12) 

(1.10-1.21) 

(1.34-1.49) 

(1.31-1.49) 

OR 

1.00 0.80 1.00 1.04 

1.30 

1.00 1.00 1.00 0.89 

0.77 

1.00 0.95 

1.06 

1.01 

1.00 1.16 

1.41 

1.40 

Cessation Activity1 

(0.78-0.83) (1.00-1.12) 

(1.15-1.42) 

(0.98-1.05) (0.86-0.92) 

(0.75-0.85) 

(0.88-1.03) 

(1.03-1.15) 

(0.90-1.10) 

(1.1

(1.36-1.51) 

(1.34-1.52) 

1-1.21) 

95% CI OR 

1.00 0.80 1.00 1.06 

1.28 

1.00 1.01 1.00 0.89 

0.80 

1.00 0.95 

1.09 

1.00 

1.00 1.16 

1.43 

1.43 

Non-Hispanic White 

African-American 

Education (Years) 

Massachusetts 

Race/Ethnicity 

Rest of USA 

Table 2-14 Variable 

Survey Year 

1992/3 1995/6 

Region 

California 

Gender 

Male Female 

Age (Years) 

25–44 45–64 

65+ 

Hispanic 

Other 

< 12 12 

13–15 

16+ 

73

Smoking and Tobacco Control Monograph No. 12 Former (any length) Former 3+ Months 1.18 (1.03-1.36) 10,000-19,999
 20,000-29,999 1.14 (1.07-1.20) 1.16 (1.10-1.23) 0.84 (0.72-0.98) 1.34 (1.19-1.50) 1.33 (1.16-1.53)
 30,000-49,999
 50,000-74,999 1.30 (1.22-1.39) 1.32 (1.24-1.41) 1.04 (0.88-1.23) 1.66 (1.47-1.88) 1.68 (1.45-1.95)
 1.50 (1.31-1.71) 1.95 (1.64-2.32) 0.67 (0.55-0.83) 5–14
 15–24 0.51 (0.46-0.56) 0.58 (0.52-0.64) 0.28 (0.23-0.33) 0.61 (0.52-0.73) 0.60 (0.49-0.74)
 0.86 (0.70-1.06) 0.87 (0.73-1.04) OR 95% CI 1.00 1.00 1.00 1.00 1.16 (1.03-1.30) 1.53 (1.37-1.71) 1.85 (1.60-2.14) 0.71 (0.60-0.85) OR 95% CI 0.93 (0.80-1.08) 1.00 (0.86-1.16) 1.10 (0.89-1.36) 0.48 (0.40-0.57) 0.17 (0.14-0.21) 0.44 (0.40-0.49) 0.38 (0.34-0.42) OR 95% CI 1–3 See footnotes at beginning of table section for explanation. Note: Model also adjusted for gender, race/ethnicity, education, household income, and daily cigarette consumption. 

Table 2-14 (continued) 

Cessation Activity1 Cessation Attempt2 Occasional3 

1.00 1.00 1.00 1.00 1.07 (1.01-1.13) 

1.26 (1.19-1.33) 

1.40 (1.29-1.52) 

0.84 (0.75-0.93) 

OR 95% CI 

1.24 (1.17-1.31) 

1.38 (1.27-1.49) 

0.76 (0.68-0.84) 1.05 (0.99-1.11) 

OR 95% CI 

1.00 1.00 

V

Household Income (Dollars) 

Cigarettes smoked per day 

ariable 

<10,000 

75,000+ 

1–4 

25+ 

74

Chapter 2 

(n) 

750 

632 

373 

235 

121 

20 

933 

634 

938 

721 

830 

Population Sample 

Size 

7,260 4,127 

2,383 

5,879 

2,664 

2,389 

1,274 1,193 

1,841 

1,103 

Size 

(N) 

3,419,535 

1,988,278 

1,091,469 

339,788 

2,423,696 

472,194 

258,685 

170,449 

79,916 

14,595 

852,503 

1,264,846 

824,213 

477,973 

386,961 

487,674 

558,699 

798,429 

462,432 

294,790 

430,550 

Unknown 

CI 

0.5 

0.9 

0.5 

0.9 

0.7 

1.6 

0.1 

1.4 

0.4 

2.1 

0.4 

0.2 

0.4 

1.5 

0.5 

0.2 

2.1 

0.3 

0.3 

0.4 

Duration 

. 

± % 

0.9 

1.1 

0.5 

1.7 

0.9 

1.8 

0.1 

1.0 

0.2 

2.0 

0.6 

0.5 

0.6 

1.8 

0.6 

0.2 

2.1 

0.3 

0.2 

0.6 

. 

1990 California Tobacco Survey: Cessation of Adult Daily Smokers 12 Months Ago, Ages 25 and Older 

Former Smoker 

CI 

0.7 0.8 

1.8 

2.8 

0.8 

3.2 

4.7 

3.3 

2.8 

1.7 

1.4 

1.5 

2.0 

3.1 

1.8 

2.4 

1.1 

2.6 

3.4 

2.0 

Quit 3+ 

Months 

. 

± % 

5.6 4.6 

6.9 

7.2 

5.6 

5.9 

5.7 

6.0 

2.3 

4.0 

5.6 

6.5 

6.5 

4.7 

4.8 

5.8 

5.1 

6.0 

8.4 

5.3 

. 

CI 

0.7 

1.0 

1.1 

1.5 

0.8 

2.2 

2.0 

3.0 

1.0 

1.4 

0.9 

1.4 

1.8 

0.6 

1.7 

1.5 

1.4 

2.6 

2.4 

1.3 

Quit <3 

Months 

. 

± % 

4.2 

4.6 

3.6 

3.3 

4.1 

5.6 

3.5 

4.5 

0.7 

3.0 

3.4 

4.9 

7.0 

1.3 

3.9 

4.0 

5.0 

6.3 

5.5 

2.4 

. 

Without Quit 

CI 

Attempts 

0.3 0.5 

0.6 

1.1 

0.2 

1.8 

1.9 

0.4 

0.8 

0.9 

0.4 

0.7 

0.4 

0.7 

1.5 

0.6 

0.3 

0.5 

0.6 

1.4 

. 

Occasional Smoker 

± % 

0.8 0.9 

0.8 

0.7 

0.4 

2.8 

1.6 

0.2 

0.4 

1.2 

0.6 

1.1 

0.4 

0.6 

1.8 

0.6 

0.4 

0.5 

0.6 

1.7 

. 

CI 

Attempts 

0.5 

0.6 

1.0 

0.9 

0.3 

2.3 

4.0 

1.0 

1.8 

1.5 

0.8 

0.8 

1.1 

2.8 

1.6 

0.9 

1.4 

1.0 

1.3 

1.3 

. 

Quit 

± % 

2.6 

2.9 

2.5 

1.8 

1.8 

4.7 

8.2 

1.5 

2.1 

2.8 

2.4 

3.0 

2.4 

3.8 

2.8 

1.9 

3.0 

2.2 

3.0 

1.9 

. 

Without Quit 

10.0 

Attempts 

CI 

1.7 

2.3 

3.0 

5.0 

1.8 

7.1 

8.1 

9.9 

5.4 

2.3 

2.7 

3.4 

5.2 

5.2 

3.7 

3.3 

4.9 

4.6 

6.2 

. 

± 

Daily Smoker 

53.2 49.8 

57.6 

58.9 

56.9 

41.9 

39.9 

49.4 

57.0 

56.1 

54.4 

49.4 

51.5 

54.4 

51.7 

53.6 

51.1 

51.6 

55.9 

57.1 

% 

. 

10.1 

Attempts 

CI 

1.7 

2.4 

2.4 

4.7 

1.8 

5.9 

8.6 

9.6 

4.4 

2.5 

2.7 

3.4 

5.1 

4.7 

3.6 

2.7 

5.5 

3.7 

5.1 

. 

Household Income (Dollars) 

Quit 

± 

32.7 

36.3 

28.0 

26.5 

Non-Hispanic White 30.4 

37.2 

41.1 

37.4 

37.4 

31.0 

32.9 

34.6 

31.6 

33.3 

34.5 

33.8 

33.3 

33.0 

26.4 

31.1 

% 

. 

Education (Years) 

African-American 

Native American 

TRace/Ethnicity 

10,001-20,000 

20,001-30,000 

30,001-50,000 

50,001-75,000 

able 2-15 

Total 

Age (Years) 25–44 

45–64 

65+ 

Hispanic 

Asian/PI 

Other 

<12 

12 

13–15 

16+ 

≤10,000 

75,000+ 

Unknown 

75

Smoking and Tobacco Control Monograph No. 12 299 

11 

245 

Unknown Population Sample 

Attempts 

%

± CI 

%

± CI 

%

± CI 

%

± CI 

%

± CI 

%

± CI 

%

± CI (N) (n) 

Size Size 

Male Total 32.9 2.1 53.4 2.4 2.7 0.9 0.9 0.5 4.2 1.0 4.6 0.6 1.3 0.9 1,872,737 3,535 

25–44
45–64 26.5 3.4 58.8 4.6 3.2 1.9 0.9 0.9 3.5 1.3 6.3 2.3 0.7 0.9 571,016 1,126


1,137,256 2,110 1,269,736 2,771 

308,363 379 Hispanic


African-American 41.1 12.4 39.9 11.3 10.1 7.6 0.4 0.6 5.0 3.6 3.5 3.8 . . 130,061 173


Asian/PI
Native American . . . . 1.5 2.2 . . 0.6 1.2 1.4 2.8 . . 39,317 53


115,393 148 

<12
12 33.9 3.7 54.9 3.7 2.5 1.5 0.2 0.2 3.4 1.2 4.5 1.3 0.7 0.6 617,688 1,160


505,692 487 

451,212 1,148 13–15


16+ 30.9 3.9 53.9 4.0 2.0 0.9 0.2 0.3 5.9 2.9 6.6 3.0 0.5 0.4 298,145 740


250,518 430 10,001-20,000


20,001-30,000 33.3 4.5 56.8 4.2 1.2 0.9 0.4 0.4 4.2 1.9 4.0 2.0 0.1 0.1 299,922 566


480,032 978 30,001-50,000


50,001-75,000 33.1 6.5 53.1 5.8 1.9 1.4 0.5 0.6 5.6 3.9 5.6 4.0 0.2 0.3 255,706 551


177,145 382 75,000+


Unknown 31.6 7.2 57.7 8.0 2.4 1.9 1.8 2.2 2.6 1.9 3.3 2.1 0.6 0.7 235,051 383


164,465 

9,867 

174,363 2.3 2.9 3.7 3.5 0.9 0.7 0.8 1.0 4.4 3.6 53.6 9.9 

Household Income (Dollars) ≤10,000 34.4 9.2 

1.5 1.5 

1.8 1.3 

1.3 1.3 

2.2 2.3 

1.1 1.4 

3.3 3.6 

0.4 0.4 0.8 0.8 

3.3 3.5 

0.1 0.2 

Months Duration 

Other . . . . . . . . . . . . . . 

Table 2-15 (continued) 

Daily Smoker Occasional Smoker Former Smoker 

3.7 1.0 

5.1 2.9 

4.8 0.9 

4.7 2.2 

4.9 3.5 

2.9 1.4 

5.3 1.7 4.2 2.5 

4.6 1.6 

7.3 3.6 

Quit <3 Quit 3+ Quit 

Without Quit Quit 

Without Quit 

4.6 1.3 

4.1 2.7 

4.1 1.1 

4.7 2.7 

5.9 4.4 

3.5 2.2 

5.1 2.0 5.5 3.2 

4.4 1.5 

5.4 3.7 

Attempts Months 

0.9 0.7 0.3 0.2 1.4 0.4 57.5 2.2 

3.8 2.7 

0.3 0.6 

1.9 1.6 

1.0 1.0 2.2 2.7 

0.5 0.5 

0.2 0.4 

65+ . . 

Attempts Attempts 

2.7 1.0 

0.7 0.9 

5.7 3.3 

1.3 1.3 

3.5 2.1 

2.4 1.4 3.1 3.1 

3.4 2.3 

2.6 1.5 

52.5 14.0 

50.0 3.2 

58.5 7.0 

40.7 7.5 

52.5 7.7 

52.3 3.7 47.3 6.9 

50.2 4.6 

60.0 6.0 

34.0 12.5 

36.5 2.9 

29.8 7.5 

Non-Hispanic White 30.7 2.0 

38.3 6.6 

32.4 6.1 

33.4 3.3 36.9 5.7 

33.7 3.8 

24.4 4.8 

Education (Years) Age (YRace/Ethnicity 

ears) 

76

Chapter 2 

(n) 

451 

253 

200 

87 

68 

9 

446 

534 

389 

508 

627 

863 

552 

339 

447 

Population Sample 

Size 

3,725 2,017 

1,257 

3,108 

1,504 

1,241 

Size 

(N) 

1,546,798 

851,022 

520,453 

175,323 

1,153,960 

163,831 

128,624 

55,056 

40,599 

4,728 

346,811 

647,158 

373,001 

179,828 

212,598 

237,156 

258,777 

318,397 

206,726 

117,645 

195,499 

Unknown 

CI 

0.3 

0.4 

0.2 

1.2 

0.2 

2.0 

0.3 

1.5 

0.7 

0.3 

0.5 

0.4 

0.9 

1.7 

0.4 

0.4 

0.3 

0.7 

0.5 

0.5 

Duration 

. 

± % 

0.5 

0.5 

0.2 

1.5 

0.5 

1.1 

0.1 

0.8 

0.4 

0.2 

0.5 

0.7 

0.8 

1.4 

0.4 

0.4 

0.2 

0.4 

0.4 

0.6 

. 

Former Smoker 

CI 

1.3 1.5 

3.2 

4.3 

1.2 

7.9 

8.6 

7.0 

3.8 

3.7 

2.1 

2.5 

2.7 

4.9 

3.0 

4.6 

2.7 

3.0 

5.4 

3.9 

Quit 3+ 

Months 

. 

± % 

6.7 5.8 

7.5 

9.1 

6.5 

8.3 

8.0 

8.1 

3.2 

5.5 

6.8 

8.0 

6.3 

5.6 

5.4 

7.9 

5.9 

6.5 

10.0 

7.6 

. 

CI 

0.8 

1.4 

1.4 

1.7 

0.9 

4.2 

2.1 

1.8 

1.7 

1.7 

1.3 

1.4 

3.2 

1.0 

1.2 

1.9 

2.2 

3.1 

3.7 

1.3 

Quit <3 

Months 

. 

± % 

4.0 

4.5 

3.8 

2.6 

4.1 

7.2 

2.0 

1.8 

0.9 

2.1 

3.4 

4.5 

8.9 

1.6 

2.2 

3.8 

5.9 

7.1 

5.7 

2.1 

. 

Without Quit 

CI 

Attempts 

0.4 0.5 

0.7 

2.1 

0.4 

1.6 

3.8 

1.5 

0.3 

0.8 

1.0 

1.0 

1.0 

1.6 

1.1 

0.3 

0.8 

1.4 

1.9 

. 

. 

Occasional Smoker 

± % 

0.8 0.8 

0.7 

1.3 

0.6 

1.0 

2.7 

0.7 

0.2 

1.0 

1.1 

0.7 

0.5 

1.2 

0.9 

0.4 

0.4 

1.2 

1.5 

. 

. 

CI 

Attempts 

0.6 

0.9 

1.0 

1.7 

0.6 

2.1 

4.6 

2.0 

2.8 

1.7 

0.8 

1.3 

2.2 

2.7 

1.3 

1.6 

1.1 

1.7 

2.2 

1.0 

. 

Quit 

± % 

2.6 

3.1 

1.7 

2.8 

2.2 

3.0 

6.3 

1.7 

2.6 

1.8 

2.2 

3.8 

3.0 

3.4 

2.4 

2.6 

2.5 

2.7 

3.7 

1.3 

. 

Without Quit 

10.9 

1

16.0 

1.4 

Attempts 

CI 

2.7 

3.1 

3.9 

6.7 

2.6 7.2 

3.6 

3.7 

5.8 

6.4 

6.4 

6.1 

4.4 

6.6 

6.9 

7.8 

. 

. 

Note: CI = 95% confidence interval; “.” = insufficient data. 

± 

Daily Smoker 

52.9 49.5 

56.3 

59.3 

56.1 

44.2 

39.8 

43.0 

61.3 

54.0 

45.8 

47.5 

55.0 

56.3 

49.9 

52.5 

49.8 

49.6 

56.3 

% 

. 

. 

10.9 

14.9 

Attempts 

CI 

2.8 

3.3 

4.1 

5.6 

2.5 

9.7 

6.6 

4.0 

4.0 

5.2 

6.7 

6.0 

6.2 

3.9 

7.0 

5.9 

5.8 

. 

. 

Household Income (Dollars) 

Quit 

± 

32.4 

35.9 

29.7 

23.3 

Non-Hispanic White 30.1 

35.2 

41.0 

44.6 

29.0 

32.1 

36.1 

32.7 

32.5 

32.1 

34.5 

32.8 

33.0 

29.3 

30.6 

% 

. 

. 

Table 2-15 (continued) Education (Years) 

African-American 

Native American 

Female T

Race/Ethnicity 

10,001-20,000 

20,001-30,000 

30,001-50,000 

50,001-75,000 

otal 

Age (Years) 25–44 

45–64 

65+ 

Hispanic 

Asian/PI 

Other 

<12 

12 

13–15 

16+ 

≤10,000 

75,000+ 

Unknown 

77

Smoking and Tobacco Control Monograph No. 12 (n) 

562 

Daily Smoker 

Quit 

Without Quit Quit 

Without Quit Quit <3 Quit 3+ Unknown Population Sample 

Attempts Attempts Attempts Attempts Months Months Duration Size Size 

2,894,421 6,211 

Age (Years) 25–44 35.9 2.0 48.6 2.1 3.5 0.7 1.6 0.7 5.2 0.9 4.8 0.9 0.5 0.2 1,636,213 3,438 

979,379 2,190 45–64


65+ 22.3 3.9 59.3 4.2 3.5 1.6 0.7 0.7 5.8 2.9 7.3 2.9 1.1 1.1 278,833 583


Race/Ethnicity Non-Hispanic White 29.1 1.5 56.4 1.5 2.7 0.5 0.8 0.3 5.1 1.0 5.4 0.9 0.5 0.2 1,941,696 4,661 

Hispanic 35.6 4.5 44.6 4.6 5.7 2.1 2.7 1.7 5.8 2.1 4.9 1.9 0.7 0.7 439,750 648 

218,593 379 African-American


Asian/PI 33.1 6.1 54.7 8.0 2.4 1.8 0.8 1.1 3.5 2.1 4.3 3.1 1.2 1.8 166,128 300


128,263 223 Native American


Other . . . . . . . . . . . . . . 0 0


Education (Years) <12 33.9 3.4 50.9 4.1 2.8 1.1 1.7 1.2 4.8 1.6 4.7 1.7 1.1 0.7 660,951 695 

937,289 2,295 12


13–15 31.5 2.0 52.8 2.4 3.9 0.9 1.7 1.2 5.0 1.5 5.0 1.2 0.2 0.2 811,862 2,033


484,320 1,188 0.5 0.4 7.3 1.9 6.3 1.8 0.7 0.5 4.1 1.3 48.0 4.0 33.0 3.4 

Household Income (Dollars) ≤10,000 32.6 4.4 53.8 4.3 3.2 1.6 2.7 2.3 3.3 1.5 4.1 1.6 0.3 0.5 370,131 621 

34.8 3.9 50.8 4.2 3.6 1.4 0.7 0.8 5.1 2.0 4.5 1.5 0.5 0.5 397,523 784 10,001-20,000 

20,001-30,000
30,001-50,000 30.5 2.8 54.1 2.7 3.2 0.9 1.2 0.8 5.4 1.5 5.1 1.8 0.4 0.5 633,126 1,431


444,746 949 

50,001-75,000
75,000+ 28.6 3.4 53.2 5.3 2.9 1.1 0.6 0.5 7.1 2.6 7.0 2.3 0.5 0.5 330,695 840


437,041 1,024 

(N) 

281,158 1.5 1.0 3.3 1.7 5.1 2.2 1.5 1.7 3.8 1.6 57.2 4.7 27.7 4.3 Unknown 

± CI 

0.6 0.2 

0.7 0.4 

1.2 1.1 

0.8 1.6 

0.7 0.4 

1.0 0.9 

0.5 0.4 

CI % 

1996 California 

Tobacco Survey: Cessation of Adult Daily Smokers 12 Months Ago, Ages 25 and Older 

Occasional Smoker Former Smoker 

5.0 0.8 

4.8 1.3 

3.1 2.1 

4.8 3.4 

4.1 0.9 

4.9 1.5 

6.0 1.9 

%

± ± CI 

4.8 0.7 

3.8 0.8 

1.7 1.3 

3.3 2.2 

3.7 0.9 

4.0 1.4 

3.6 1.5 

CI % 

1.3 0.4 

0.8 0.5 

3.5 3.9 

0.5 0.7 

0.9 0.4 

0.6 0.5 

1.6 0.9 

%

± ± CI 

3.3 0.5 2.9 0.8 

4.7 2.9 

2.7 1.9 

2.8 0.9 

3.2 1.2 

3.4 1.3 

CI % 

53.6 1.4 

60.3 2.1 

44.9 6.6 

54.6 8.5 

59.1 2.5 

54.9 3.7 

51.9 4.5 

%

± ± CI % 

31.4 1.3 

26.6 1.9 

40.8 6.6 

33.3 7.9 

28.7 2.1 

31.5 4.2 

33.1 3.4 

Table 2-16 

Total 

16+ 

78

Chapter 2 

(n) 

236 

412 

172 

211 

118 

0 

377 

997 

660 

255 

355 

453 

716 

561 

479 

285 

Population Sample 

Size 

3,104 1,808 

1,060 

2,191 

1,070 

Size 

(N) 

1,599,132 

938,719 

533,228 

127,184 

1,005,234 

303,944 

105,338 

115,588 

69,026 

0 

389,244 

487,227 

436,514 

286,144 

180,241 

205,949 

242,397 

348,127 

257,188 

202,225 

163,004 

Unknown 

CI 

0.3 

0.4 

0.4 

2.4 

0.4 

0.9 

1.9 

1.1 

0.4 

0.3 

0.5 

0.9 

0.8 

1.5 

0.4 

0.6 

0.6 

1.4 

Duration 

. 

. 

. 

± % 

0.7 

0.6 

0.6 

1.9 

0.7 

0.7 

1.6 

1.5 

0.5 

0.2 

0.6 

0.4 

0.7 

1.2 

0.3 

0.6 

0.5 

1.3 

. 

. 

. 

Former Smoker 

CI 

0.9 1.0 

1.5 

4.6 

1.0 

2.1 

2.1 2.6 

5.3 

1.9 

1.0 

1.5 

2.4 

2.4 

2.2 

2.0 

1.9 

2.2 

2.6 

2.6 

Quit 3+ 

Months 

. 

± % 

4.9 4.2 

4.9 

9.8 

5.3 

4.9 

2.3 3.3 

5.5 

4.9 

3.2 

4.9 

7.5 

4.1 

3.8 

5.2 

4.6 

5.8 

6.5 

3.8 

. 

CI 

0.7 

1.0 

1.2 

3.7 

1.0 

2.4 

1.5 2.4 

3.4 

2.2 

0.9 

1.6 

1.8 

2.4 

2.8 

2.1 

2.2 

1.1 

2.2 

3.1 

Quit <3 

Months 

. 

± % 

4.4 

4.8 

3.4 

6.0 

4.6 

5.4 

1.0 3.7 

3.5 

5.7 

2.8 

4.3 

5.5 

3.8 

4.0 

4.1 

5.1 

2.3 

6.7 

5.1 

. 

Without Quit 

CI 

Attempts 

0.5 0.6 

0.6 

1.1 

0.3 

2.2 

2.4 

1.0 

1.7 

0.5 

0.6 

0.7 

1.6 

1.2 

0.9 

0.5 

1.4 

0.3 

2.7 

. 

. 

Occasional Smoker 

± % 

0.9 1.2 

0.5 

0.5 

0.5 

2.4 

1.8 

0.5 

1.9 

0.6 

0.6 

0.6 

1.3 

0.8 

0.7 

0.5 

1.7 

0.2 

2.0 

. 

. 

CI 

Attempts 

0.7 

0.9 

1.4 

2.0 

0.7 

2.7 

3.7 

2.0 

2.5 

1.7 

1.2 

1.4 

1.9 

2.7 

2.4 

1.6 

1.4 

1.5 

1.6 

2.8 

. 

Quit 

± % 

3.2 

3.3 

3.3 

1.8 

2.3 

6.0 

5.1 

2.3 

2.5 

3.4 

2.7 

3.3 

3.5 

3.2 

3.5 

3.0 

3.3 

2.4 

2.6 

4.5 

. 

Without Quit 

10.6 

Attempts 

CI 

2.1 

2.9 

3.4 

5.8 

2.2 

5.7 

8.6 

8.4 

5.6 

3.3 

3.7 

4.8 

7.2 

5.9 

5.4 

4.0 

4.3 

6.1 

6.6 

. 

± 

Daily Smoker 

53.3 48.5 

59.9 

61.3 

56.3 

44.4 

47.8 

52.9 

58.7 

50.9 

58.9 

51.4 

50.1 

53.8 

49.6 

54.9 

54.7 

50.9 

52.9 

56.5 

% 

. 

Attempts 

CI 

1.7 

2.6 

2.8 

4.5 

2.0 

5.0 

9.3 

7.7 

9.5 

4.3 

2.8 

3.1 

3.8 

6.7 

6.1 

5.2 

3.5 

4.0 

4.8 

5.9 

. 

Household Income (Dollars) 

Quit 

± 

32.6 

37.5 

27.3 

18.8 

Non-Hispanic White 30.3 

36.2 

40.3 

37.8 

29.3 

31.7 

31.2 

35.2 

32.2 

33.4 

37.6 

31.0 

31.5 

36.2 

30.6 

26.8 

% 

. 

Table 2-16 (continued) Education (Years) 

African-American 

Native American 

Male T

Race/Ethnicity 

10,001-20,000 

20,001-30,000 

30,001-50,000 

50,001-75,000 

otal 

Age (Years) 25–44 

45–64 

65+ 

Hispanic 

Asian/PI 

Other 

<12 

12 

13–15 

16+ 

≤10,000 

75,000+ 

Unknown 

79

Smoking and Tobacco Control Monograph No. 12 347 0 

366 

Unknown Population Sample 

Attempts 

%

± CI 

%

± CI 

%

± CI 

%

± CI 

%

± CI 

%

± CI 

%

± CI (N) (n) 

Size Size 

Female Total 30.0 2.1 53.9 2.3 3.5 0.7 1.7 0.7 5.2 1.3 5.2 1.0 0.6 0.3 1,295,293 3,107 

25–44
45–64 25.8 3.0 60.8 2.9 2.5 1.0 1.2 0.8 4.3 1.3 4.7 1.7 0.8 0.8 446,151 1,130


697,492 1,630 936,454 2,470 

Hispanic
African-American 41.3 9.0 42.2 9.3 4.4 3.8 5.0 7.3 2.4 1.8 3.9 2.9 0.9 1.3 113,255 207


135,805 236 

50,540 89 Asian/PI


Native American 38.0 13.2 49.8 15.2 3.0 2.6 0.5 1.1 3.1 3.1 3.9 4.1 1.7 3.4 59,237 105


<12
12 26.1 2.4 59.2 3.4 2.8 1.1 1.2 0.6 4.7 1.6 5.0 1.3 0.9 0.8 450,062 1,225


271,706 318 

375,347 1,036 13 - 15


16+ 34.3 5.8 45.0 5.6 4.9 1.8 0.8 0.8 7.6 3.8 7.1 2.7 0.4 0.7 198,177 528
10,001-20,000
20,001-30,000 32.0 5.1 54.9 4.3 3.4 2.1 0.5 0.5 3.8 1.7 4.6 2.1 0.8 1.1 202,350 496


191,575 429 

285,000 715 30,001-50,000


50,001-75,000 28.5 6.9 53.2 8.0 4.8 1.9 1.6 1.2 5.4 3.3 6.2 2.9 0.3 0.5 179,853 463


75,000+
Unknown 28.9 5.8 58.3 6.6 2.8 2.0 0.8 0.7 5.0 3.1 2.6 1.8 1.6 1.6 118,154 277


128,471 361 

151,649 

0 

189,890 0.3 0.5 4.1 2.3 2.9 1.5 4.1 4.4 3.2 1.9 53.7 5.9 

Household Income (Dollars) ≤10,000 31.8 5.3 

0.4 0.3 

0.6 0.8 

0.2 0.2 

0.8 1.1 

4.0 6.0 

0.5 0.7 

0.2 0.3 0.4 0.7 

0.5 0.9 

0.5 1.1 

Months Duration 

Other . . . . . . . . . . . . . . 

Table 2-16 (continued) 

Daily Smoker Occasional Smoker Former Smoker 

5.6 1.3 

5.3 2.8 

5.4 1.1 

5.0 4.0 

6.6 7.4 

4.3 2.5 

5.2 1.7 5.3 2.3 

5.7 2.9 

7.8 3.8 

Quit <3 Quit 3+ Quit 

Without Quit Quit 

Without Quit 

5.7 1.7 

5.6 3.6 

5.6 1.7 

6.6 4.1 

3.0 3.6 

3.5 2.4 

5.7 2.3 6.3 3.2 

5.8 2.5 

7.9 5.3 

Attempts Months 

2.2 1.3 

0.9 1.0 

1.1 0.5 

3.2 2.8 

2.5 3.7 

1.5 1.5 

2.9 2.3 0.6 0.9 

2.2 1.8 

1.3 1.3 

Attempts Attempts 

3.8 1.0 

4.8 2.6 

3.2 0.6 

5.0 3.1 

2.7 3.9 

2.1 1.6 

4.5 1.3 3.6 1.8 

3.2 1.3 

3.3 1.8 

58.7 18.0 

48.6 3.1 

57.6 7.1 

56.6 2.1 

45.1 7.6 

50.9 6.2 

54.3 3.4 52.0 5.8 

53.2 4.6 

53.8 7.8 

Note: CI = 95% confidence interval; “.” = insufficient data. 

22.4 12.9 

33.7 2.9 

25.2 6.1 

Non-Hispanic White 27.9 2.1 

34.3 7.6 

37.2 6.4 

27.1 2.7 31.8 5.6 

29.4 4.4 

25.4 4.9 

Education (Years) Age (YRace/Ethnicity 

ears) 

65+ 

80

Chapter 2 

Table 2-17 

Percentage of Former Smokers among those who Reported Smoking in the Last Year in 

Massachusetts 

OVERALL MTS* 1993 MATS** 1995, 1996 MATS** 1997 

%*** N‡ % N % N 

Total 8.1 ±2.6 1784 10.2 ±3.9 1253 10.9 ±4.8 782 

Gender 

Male 7.0 ±3.8 858 8.6 ±5.1 578 10.7 ±7.0 363 

Female 9.0 ±3.7 926 11.6 ±6.0 675 10.9 ±6.8 419 

Age (Years) 

18 - 24 7.5 ±7.8 255 2.5 ±1.9 156 4.7 ±3.9 98 

25 - 44 4.1 ±2.1 977 13.0 ±6.5 678 10.0 ±6.0 409 

45 - 64 17.9 ±8.5 402 9.8 ±7.6 308 16.7 ±11.1 209 

65+ 7.6 ±9.0 108 12.5 ±12.4 108 1.9 ±2.4 64 

Ethnicity 

Non-Hispanic White 8.2 ±2.9 1346 11.8 ±4.8 1010 11.1 ±5.2 646 

African-American 7.7 ±5.4 145 8.1 ±8.1 85 — 42 

Hispanic 0 ±1.3 131 3.6 ±2.7 81 6.7 ±8.4 52 

Asian/PI — 26 0 ±2.2 11 — 4 

Other 5.9 ±12.1 61 0 ±2.4 15 10.0 ±10.7 17 

Education (Years) 

<12 6.8 ±5.9 288 11.7 ±10.9 193 8.7 ±6.5 113 

12 8.0 ±4.2 693 5.2 ±3.6 493 15.4 ±9.1 323 

13 - 15 7.8 ±5.1 460 10.4 ±8.2 344 8.3 ±7.0 209 

16+ 10.3 ±6.6 299 19.2 ±11.7 206 5.3 ±8.1 130 

Income Level (Dollars) 

<10,000 4.2 ±5.2 221 10.6 ±9.6 154 — 70 

10,000-19,000 10.4 ±9.3 238 6.9 ±9.8 152 2.3 ±1.9 113 

20,000-29,000 6.0 ±5.5 311 6.1 ±5.6 230 4.9 ±6.4 129 

30,000-49,000 11.5 ±6.7 417 7.9 ±7.2 324 11.2 ±9.8 203 

50,000-75,000 8.2 ±5.8 237 21.5 ±14.9 142 — 102 

75,000+ 7.8 ±11.6 91 — 90 1.6 ±2.1 67 

81

Smoking and Tobacco Control Monograph No. 12 

Table 2-17 (continued) 

MALE MTS* 1993 MATS** 1995, 1996 

%*** N‡ % N % N 

MATS** 1997 

Total Men 7 858 8.6 578 10.7 363 

Age (Years) 

18 - 24 12.3 115 2.4 74 2.6 42 

25 - 44 3.4 472 9.9 312 7.8 196 

45 - 64 14 212 10.7 149 17.2 104 

65+ 10 51 15.2 43 10 21 

Ethnicity 

Non-Hispanic White 7.3 628 11.3 452 11.2 296 

African-American 7.4 69 13.3 34 0 19 

Hispanic 0 63 0 38 0 22 

Asian/PI 20 19 0 10 0 2 

Other 0 34 0 9 11.1 11 

Education (Years) 

<12 7.1 154 12.3 101 3.6 57 

12 7 327 4.8 222 15.5 149 

13 - 15 3.3 211 6 149 5.2 85 

16+ 14.7 146 17.3 99 10.6 68 

Income Level (Dollars) 

<10,000 6.5 91 4 48 0 25 

10,000-19,000 6.4 98 2.7 56 2.3 39 

20,000-29,000 1.2 150 8 102 2.8 51 

30,000-49,000 9.6 214 3.1 176 14.1 113 

50,000-75,000 8.1 125 26.1 69 24.2 49 

75,000+ 13.2 54 9.6 55 2.4 46 

82

Chapter 2 

Table 2-17 (continued) 

FEMALE MTS* 1993 MATS** 1995, 1996 

%*** N‡ % N % N 

MATS** 1997 

Total Women 9 926 11.6 675 10.9 419 

Age (Years) 

18 - 24 4.4 140 1.3 82 4.3 56 

25 - 44 4.8 505 15.7 366 12.3 213 

45 - 64 21.1 190 9 159 16.1 105 

65+ 5.6 57 10.3 65 2.3 43 

Ethnicity 

Non-Hispanic White 9 718 12.4 558 11 350 

African-American 8.3 76 9.1 51 33.3 23 

Hispanic 0 68 5.3 43 12.5 30 

Asian/PI 14.3 7 0 1 0 2 

Other 20 27 0 6 0 6 

Education (Years) 

<12 6.3 134 11.1 92 15.8 56 

12 9 366 5.1 271 15.2 174 

13 - 15 12.3 249 14.2 195 10.5 124 

16+ 7.8 153 20.7 107 0 62 

Income Level (Dollars) 

<10,000 4 130 13.3 106 33.3 45 

10,000-19,000 13 140 10.6 96 2.2 74 

20,000-29,000 8.8 161 3.8 128 6.7 78 

30,000-49,000 14.1 203 11.9 148 8.5 90 

50,000-75,000 8.3 112 14 73 20.3 53 

75,000+ 2 37 27.3 35 0 21 

* MTS - Massachusetts Tobacco Survey. 

** MATS - Massachusetts Adult Tobacco Survey. 

*** All % reported are weighted. 

‡ All N’s reported are unweighted. 

83

Smoking and Tobacco Control Monograph No. 12 

Table 2-18 

Quit Attempts among those who Reported Smoking in the Last Year in Massachusetts 

OVERALL MTS* 1993 MATS** 1995, 1996 MATS 1997 

%*** N‡ % N % N 

Total 47.5 ±5.0 1747 52.9 ±6.0 1245 48.2 ±7.5 776 

Gender 

Male 48.6 ±7.5 839 54.4 ±8.6 574 45.6 ±10.2 360 

Female 46.4 ±7.1 908 51.4 ±8.5 671 51.0 ±10.5 416 

Age (Years) 

18 - 24 37.7 ±11.8 251 — 153 — 98 

25 - 44 46.2 ±7.2 959 59.7 ±7.8 673 56.7 ±9.9 404 

45 - 64 59.3 ±9.5 395 50.8 ±12.1 308 39.1 ±12.9 209 

65+ — 104 — 108 — 64 

Ethnicity 

Non-Hispanic White 47.6 ±5.4 1325 50.9 ±6.7 1004 47.5 ±8.0 643 

African-American — 140 — 85 — 41 

Hispanic — 128 — 80 — 51 

Asian/PI — 24 — 11 — 4 

Other — 61 — 14 — 17 

Education (Years) 

<12 53.4 ±14.2 282 58.9 ±15.1 192 — 113 

12 44.6 ±7.6 685 47.4 ±10.8 491 47.7 ±11.8 322 

13 - 15 43.2 ±9.8 449 50.5 ±11.8 341 50.2 ±14.2 206 

16+ 56.8 ±11.1 289 62.0 ±12.7 204 — 128 

Income Level (Dollars) 

<10,000 25.3 ±11.9 220 58.8 ±15.4 153 — 70 

10,000-19,000 52.7 ±13.1 235 36.1 ±16.7 149 — 113 

20,000-29,000 44.0 ±12.6 306 55.8 ±13.0 228 — 128 

30,000-49,000 53.6 ±9.4 413 52.2 ±11.6 323 43.5 ±14.2 202 

50,000-75,000 49.2 ±12.6 236 — 142 — 101 

75,000+ — 84 — 90 — 67 

84

Chapter 2 

Table 2-18 (continued) 

MALE MTS* 1993 MATS** 1995, 1996 

%*** N‡ % N % N 

MATS 1997 

Total Men 48.6 839 54.4 574 45.6 360 

Age (Years) 

18 - 24 38.5 112 47.2 73 57.9 42 

25 - 44 46.6 465 60.7 309 46.9 193 

45 - 64 65.7 206 54.9 149 41.4 104 

65+ 32.3 50 36.4 43 30 21 

Ethnicity 

Non-Hispanic White 49.1 619 51.6 450 44.7 295 

African-American 55 66 46.7 34 81.8 18 

Hispanic 35.3 62 38.9 37 50 21 

Asian/PI 22.2 17 88.2 10 0 2 

Other 54.5 34 90 8 12.5 11 

Education (Years) 

<12 60.3 149 63.2 101 32.1 57 

12 44.7 324 53.4 220 47.9 148 

13 - 15 38.2 204 40 147 35.5 83 

16+ 68.1 143 72.1 99 57.6 68 

Income Level (Dollars) 

<10,000 17.4 91 44 47 50 25 

10,000-19,000 54.5 96 25 55 31 39 

20,000-29,000 50 147 64.4 101 27.8 51 

30,000-49,000 51.2 211 58.3 175 38 113 

50,000-75,000 48.2 124 50 69 62.3 48 

75,000+ 60.9 52 58.9 55 48.2 46 

85

Smoking and Tobacco Control Monograph No. 12 

Table 2-18 (continued) 

FEMALE MTS* 1993 MATS** 1995, 1996 

%*** N‡ % N % N 

MATS 1997 

Total Women 46.4 908 51.4 671 51 416 

Age (Years) 

18 - 24 36.4 139 34.2 80 32.6 56 

25 - 44 45.6 494 58.7 364 65.9 211 

45 - 64 54.9 189 47.2 159 35.5 105 

65+ 48.6 54 46.2 65 38.1 43 

Ethnicity 

Non-Hispanic White 46.2 706 50.3 554 50 348 

African-American 58.3 74 68.2 51 66.7 23 

Hispanic 60 66 50 43 62.5 30 

Asian/PI 16.7 7 0 1 100 2 

Other 66.7 27 14.3 6 100 6 

Education (Years) 

<12 46 133 53.7 91 50 56 

12 44.3 361 41.4 271 48 174 

13 - 15 47.4 245 60.8 194 60.9 123 

16+ 48.4 146 52.3 105 38.4 60 

Income Level (Dollars) 

<10,000 32.7 129 65 106 55.6 45 

10,000-19,000 52.2 139 42.6 94 42.2 74 

20,000-29,000 40.9 159 46.8 127 27.3 77 

30,000-49,000 56.3 202 47.2 148 48.4 89 

50,000-75,000 50.5 112 58.9 73 62.3 53 

75,000+ 45.8 32 59.3 35 42.5 21 

* MTS - Massachusetts Tobacco Survey. 

** MATS - Massachusetts Adult Tobacco Survey. 

*** All % reported are weighted. 

‡ All N’s reported are unweighted. 

86

Chapter 2 

Table 2-19 

Smokers Planning to Quit in the Next 30 Days in Massachusetts 

OVERALL MTS* 1993 MATS** 1995, 1996 MATS 1997 

%*** N‡ % N % N 

Total 28.6 ±5.2 1564 30.7 ±5.9 1107 33.3 ±6.6 684 

Gender 

Male 31.8 ±7.2 763 34.6 ±9.4 505 36.5 ±10.1 317 

Female 25.6 ±6.7 801 26.8 ±7.7 602 30.5 ±9.4 367 

Age (Years) 

18 - 24 18.2 ±9.2 232 25.0 ±14.0 140 13.6 ±9.0 89 

25 - 44 27.8 ±6.2 874 32.1 ±9.1 599 36.2 ±9.9 362 

45 - 64 34.0 ±11.1 328 31.0 ±11.5 271 39.8 ±14.0 182 

65+ — 94 — 94 — 51 

Ethnicity 

Non-Hispanic White 28.6 ±5.7 1181 26.7 ±6.2 891 32.1 ±7.0 564 

African-American 25.0 ±12.1 122 — 73 — 37 

Hispanic — 119 — 72 — 45 

Asian/PI 7.7 ±10.2 21 — 10 — 4 

Other 18.8 ±13.2 58 — 14 — 17 

Education (Years) 

<12 — 254 29.4 ±14.1 168 — 98 

12 23.3 ±6.8 611 32.9 ±10.1 441 30.9 ±11.1 272 

13 - 15 29.6 ±9.6 404 26.8 ±10.0 306 31.1 ±12.8 190 

16+ 30.3 ±10.9 258 27.3 ±12.3 179 39.1 ±13.7 119 

Income Level (Dollars) 

<10,000 — 198 — 136 17.6 ±12.3 58 

10,000-19,000 22.2 ±13.7 220 — 138 — 100 

20,000-29,000 31.1 ±12.5 280 24.5 ±12.4 207 — 116 

30,000-49,000 32.7 ±9.4 360 38.4 ±12.3 286 32.3 ±13.4 179 

50,000-75,000 29.0 ±12.2 210 — 127 — 85 

75,000+ 9.9 ±9.1 77 — 74 — 66 

87

Smoking and Tobacco Control Monograph No. 12 

Table 2-19 (continued) 

MALE MTS* 1993 MATS** 1995, 1996 

%*** N‡ % N % N 

MATS 1997 

Total Men 31.8 763 34.6 505 36.5 317 

Age (Years) 

18 - 24 25.8 106 17.5 67 18.9 41 

25 - 44 30 431 43 274 32.1 171 

45 - 64 38.4 176 37.9 126 49.5 89 

65+ 42.9 43 28.6 38 33.3 16 

Ethnicity 

Non-Hispanic White 32.4 553 31.7 393 34.8 259 

African-American 23.5 58 25 26 72.7 17 

Hispanic 66.7 62 52.8 37 71.4 18 

Asian/PI 14.3 17 88.2 9 0 2 

Other 16.7 33 10.5 8 0 10 

Education (Years) 

<12 41.9 135 37 83 38.5 49 

12 24.3 295 38.2 200 34.2 127 

13 - 15 35.9 183 30.2 132 22.4 77 

16+ 38.5 131 32.9 85 51.3 61 

Income Level (Dollars) 

<10,000 47.6 80 25.7 42 20 23 

10,000-19,000 25 95 41.7 52 29.3 34 

20,000-29,000 24.4 142 26.4 86 61.8 45 

30,000-49,000 37.4 185 48.8 157 28 100 

50,000-75,000 32.9 111 44.6 60 40 41 

75,000+ 9.3 44 27.7 44 29.1 43 

88

Chapter 2 

Table 2-19 (continued) 

FEMALE MTS* 1993 MATS** 1995, 1996 

%*** N‡ % N % N 

MATS 1997 

Total Women 25.6 801 26.8 602 30.5 367 

Age (Years) 

18 - 24 12.8 126 37.3 73 8.9 48 

25 - 44 25.3 443 21.1 325 40.3 191 

45 - 64 30.4 152 26 145 26 93 

65+ 57.6 51 42.9 56 22 35 

Ethnicity 

Non-Hispanic White 25.3 628 22.9 498 29.7 305 

African-American 27.3 64 55 47 75 20 

Hispanic 61.5 57 55.6 35 42.9 27 

Asian/PI 0 4 0 1 0 2 

Other 25 25 16.7 6 0 7 

Education (Years) 

<12 39 119 22.4 85 20 49 

12 22.3 316 27.9 241 26.9 145 

13 - 15 23.5 221 22.6 174 37.5 113 

16+ 24.3 127 23 94 28.1 58 

Income Level (Dollars) 

<10,000 14.9 118 38.5 94 18.2 35 

10,000-19,000 20 125 25.9 86 29.5 66 

20,000-29,000 36 138 22.7 121 12.2 71 

30,000-49,000 26.2 175 28.7 129 36 79 

50,000-75,000 24.7 99 16.3 67 34.5 44 

75,000+ 10.4 33 21.2 30 26.1 23 

* MTS - Massachusetts Tobacco Survey. 

** MATS - Massachusetts Adult Tobacco Survey. 

*** All % reported are weighted. 

‡ All N’s reported are unweighted. 

89

Smoking and Tobacco Control Monograph No. 12 

Table 2-20 

Daily Smokers Planning to Quit in the Next 30 Days in Massachusetts 

OVERALL MTS* 1993 MATS** 1995, 1996 MATS 1997 

%*** N‡ % N % N 

Total 23.8 ±4.9 1307 27.3 ±6.3 916 29.3 ±7.0 586 

Gender 

Male 28.4 ±7.1 636 32.9 ±9.9 418 35.5 ±10.7 274 

Female 19.1 ±6.0 671 22.2 ±8.3 498 23.0 ±9.5 312 

Age (Years) 

18 - 24 10.4 ±6.2 194 — 103 11.4 ±8.3 70 

25 - 44 24.5 ±6.5 718 29.3 ±9.1 501 29.6 ±10.3 306 

45 - 64 27.0 ±10.8 285 24.9 ±11.7 231 37.7 ±14.4 163 

65+ — 84 — 78 — 47 

Ethnicity 

Non-Hispanic White 23.7 ±4.4 1000 23.1 ±6.6 751 27.6 ±7.4 486 

African-American 24.0 ±12.7 98 — 54 — 30 

Hispanic — 96 — 54 — 39 

Asian/PI 7.7 ±8.2 16 — 7 — 2 

Other 14.3 ±13.2 50 — 10 — 13 

Education (Years) 

<12 30.3 ±15.3 227 32.6 ±14.9 147 — 91 

12 20.9 ±7.1 530 26.6 ±9.7 374 25.1 ±10.5 242 

13 - 15 25.7 ±10.2 333 26.5 ±11.2 261 26.3 ±13.1 155 

16+ 23.8 ±11.5 186 18.4 ±12.0 123 38.2 ±16.9 93 

Income Level 

<10,000 — 173 31.7 ±17.3 116 17.6 ±12.3 55 

10,000-19,000 21.5 ±14.5 195 — 108 — 88 

20,000-29,000 23.0 ±10.9 234 22.6 ±14.1 173 — 98 

30,000-49,000 30.2 ±10.3 305 32.5 ±13.0 243 29.5 ±14.1 149 

50,000-75,000 23.8 ±13.3 173 — 105 — 74 

75,000+ 11.9 ±13.0 55 — 57 — 56 

90

Chapter 2 

Table 2-20 (continued) 

MALE MTS* 1993 MATS** 1995, 1996 

%*** N‡ % N % N 

MATS 1997 

Total Men 28.4 636 32.9 418 35.5 274 

Age (Years) 

18 - 24 16 90 16.3 50 15.2 32 

25 - 44 29.3 350 41.4 224 29.9 146 

45 - 64 29.2 148 32 110 49.5 80 

65+ 44.4 42 33.3 34 33.3 16 

Ethnicity 

Non-Hispanic White 29.9 468 30.8 334 33.5 227 

African-American 18.8 46 25 21 77.8 13 

Hispanic 44.4 49 80 26 71.4 16 

Asian/PI 14.3 12 33.3 6 0 0 

Other 16.7 29 10.5 6 0 7 

Education (Years) 

<12 33.3 120 47.5 71 41.7 46 

12 22.3 255 30.1 169 30.3 113 

13 - 15 33.6 149 32.4 114 20 66 

16+ 37.2 96 28.6 60 59.3 46 

Income Level (Dollars) 

<10,000 42.4 71 42.9 35 20 22 

10,000-19,000 23.8 85 30.8 39 38.7 29 

20,000-29,000 18.8 119 27.4 72 57.1 37 

30,000-49,000 36.2 157 38.5 131 27.4 87 

50,000-75,000 25.9 88 41.2 50 40.9 36 

75,000+ 15 30 34 33 24.3 36 

91

Smoking and Tobacco Control Monograph No. 12 

Table 2-20 (continued) 

FEMALE MTS* 1993 MATS** 1995, 1996 

%*** N‡ % N % N 

MATS 1997 

Total Women 19.1 671 22.2 498 23 312 

Age (Years) 

18 - 24 8 104 38.8 53 7.9 38 

25 - 44 18.8 368 19.1 277 28.9 160 

45 - 64 25.5 137 19.4 121 21.1 83 

65+ 39.1 42 24 44 23.1 31 

Ethnicity 

Non-Hispanic White 18 532 17 417 22 259 

African-American 33.3 52 53.8 33 75 17 

Hispanic 70 47 56.3 28 33.3 23 

Asian/PI 0 4 0 1 0 2 

Other 33.3 21 0 4 0 6 

Education (Years) 

<12 27.7 107 19.6 76 20 45 

12 19.4 275 23.6 205 18.7 129 

13 - 15 17 184 19.5 147 30.6 89 

16+ 17.1 90 6.1 63 18.8 47 

Income Level (Dollars) 

<10,000 12.2 102 26.2 81 18.2 33 

10,000-19,000 20 110 24.4 69 28.6 59 

20,000-29,000 26.9 115 17.7 101 14.3 61 

30,000-49,000 20.7 148 27.4 112 31.5 62 

50,000-75,000 22.4 85 15 55 14.6 38 

75,000+ 10 25 5.3 24 17.5 20 

* MTS - Massachusetts Tobacco Survey. 

** MATS - Massachusetts Adult Tobacco Survey. 

*** All % reported are weighted. 

‡ All N’s reported are unweighted. 

92

Chapter 2 

Appendix 2 

CPS Summary of Methods Used in Logistic Regression 

Models for Cessation Monograph 

1. BASIC CESSATION The analysis includes self-respondents from the CPS 1992/93 

MODELS and 1995/96 surveys who are 25 years of age or older. These 

respondents must have a valid current smoking status (daily, 

Population occasional, or former) and must have been daily smokers one 

year ago. In other words, respondents who did not answer whether they 

had smoked at least 100 cigarettes (Question 32*), whether they currently 

smoke (Question 35), and whether they smoked daily 12 months ago 

(Question 61) are excluded from the analysis. Additionally, respondents are 

excluded from the analysis if they are 

• current daily smokers with unknown quit attempts 

(Questions 44 and 45), 

• current occasional and former smokers who have not been daily 

smokers for at least 6 months (Questions 39 and 55), or 

• current former smokers with unknown lengths of quit time 

(Question 59). 

Any respondents who neglected to answer questions that are used as 

covariates are also excluded from the analysis. 

Additionally, each analysis is stratified by region—the nation, 

California, and the nation minus California (N–CA). Below is a summary of 

the number of respondents used for the analyses by region. 

Region Population 1992/93 1995/96 

Nation Respondents to Tobacco Supplement 333,909 289,704 

Self-respondents, age 25+ 205,621 170,313 

Daily smokers of 1 yr (Used in analysis) 38,283 30,609 

Calif Respondents to Tobacco Supplement 25,834 23,019 

Self-respondents, age 25+ 14,767 12,266 

Daily smokers of 1 yr (Used in analysis) 1,972 1,584 

N–CA Respondents to Tobacco Supplement 308,075 266,685 

Self-respondents, age 25+ 190,854 158,047 

Daily smokers of 1 yr (Used in analysis) 36,311 29,025 

* All question numbers refer to the 1992/93 Current Population Survey. 

93 
Smoking and Tobacco Control Monograph No. 12 

Outcomes Five different cessation outcomes are modeled: 

Cessation Those daily smokers of 1 year ago who have either tried 

Activity	 to quit (current daily smokers with quit attempts in the past 

year), have become occasional smokers, or have quit 

altogether (current former smokers). 

Cessation Those daily smokers of 1 year ago, save current occasional 

Attempts	 smokers, who have tried to quit or who have quit. Current 

occasional smokers have been excluded from the analysis of 

this outcome because their attempts to quit are not 

monitored. 

Occasional	 Those daily smokers of 1 year ago who have become 

occasional smokers. 

Former	 Those daily smokers of 1 year ago who have quit 

smoking, regardless of the length of this current quit effort. 

Former Those daily smokers of 1 year ago who quit smoking at 

>3 months least 3 months prior to the survey. 

Weighting for To estimate the standard errors for the odds ratios obtained 

Confidence Interval from the logistic regression analysis, the weight of each surCalculation vey respondent has been recalculated, so the sum of the 

new weights is the original sample size. This reweighting is obtained by 

dividing each respondent’s original weight by the sum of all the original 

weights (wt/∑wt = each respondent’s contribution), this quotient is then 

multiplied by the total sample size. 

Covariates The following covariates are used to model the cessation outcomes: 

Gender Male or Female 

Age Each respondent is classified into one of three age 

categories: 

25 – 44 

45 – 64 

65 + 

Race	 Race and ethnicity are classified into five categories— 

White, Hispanic, African-American, Native American, and 

Other. Each respondent has specified his race and presence 

of Hispanic ethnicity. If the respondent has indicated 

Hispanic ethnicity, he is classified as Hispanic; otherwise, his 

race response is used. For the 1992/93 survey, the category 

“Other” includes Asian/PI, Native American, and Other; 

however, for the 1995/96 survey, this category only includes 

Asian/PI and Native American, since the CPS reclassified 

respondents into one of the other race categories if they 

chose a race of “Other.” 

94

Chapter 2 

Education Respondents are classified into one of four education 

categories: 

<12 Years 

12 Years (with or without a diploma) 

13-15 Years 

16+ Years 

Income	 Respondents are classified by their household income into 

one of six categories: 

<$10,000 

$10,000 – $19,999 

$20,000 – $29,999 

$30,000 – $49,999 

$50,000 – $74,999 

$75,000 + 

Cigarettes Respondents are grouped differently according to their 

smoked per current smoking status. Current occasional and former 

day smokers are classified into categories according to the 

number of cigarettes smoked per day when they were last 

daily smokers—presumably 12 months prior to the survey 

(Questions 41 and 57). Current daily smokers, however, are 

classified according to the number of cigarettes they are 

currently smoking (Question 36). The categories are 

1 – 4 cigarettes per day 

5 – 14 cigarettes per day 

15 – 24 cigarettes per day 

25+ cigarettes per day 

2. CESSATION BY This analysis subsets the population described in #1 by 

DOCTOR’S ADVICE deleting from that population those respondents who have 

unknown information regarding doctor’s advice. 

Population Additionally, since information about doctor’s advice is only 

obtained from current smokers, former smokers have been deleted from this 

analysis. 

Population used in analysis: Current smokers who were daily smokers one 

year ago. 

Region 1992/93 1995/96 

Nation 35,013 28,801 

Calif 1,752 1,467 

N–CA 33,261 27,334 

95

Smoking and Tobacco Control Monograph No. 12 

Outcomes Since only current smokers are used in the analysis, only three cessation 

outcomes are modeled—change, attempts, and occasional. 

Covariates Only one covariate, doctor’s advice, is added to those already listed in 

#1. Each respondent is characterized by one of the following classifications: 

• Saw a doctor and received advice 

• Saw a doctor but didn’t receive advice 

• Didn’t see a doctor 

Questions 47 and 49 are used to characterize respondents. 

3. CESSATION BY DOCTOR’S The population described in #2 has been further 

ADVICE FOR THOSE WHO subset such that those current smokers who were 

SAW A DOCTOR WITHIN daily smokers 1 year ago have been subset to those 

THE LAST YEAR who also saw a doctor within the last year. 

Population Population used in analysis: Those current smokers 

who were daily smokers 1 year ago and saw a doctor within the last year. 

Region 1992/93 1995/96 

Nation 25,155 21,147 

Calif 1,275 1,029 

N–CA 23,880 20,118 

Outcomes The same cessation outcomes listed in #2 are used—change, attempt, 

and occasional. 

Covariates Since all the respondents used in this analysis have seen a doctor in the 

past year, the covariates listed in #2 have been modified to only include 

• Received doctor’s advice 

• Didn’t receive doctor’s advice 

4. WHO SAW A DOCTOR This analysis uses a subset of the population described in 

IN THE PAST YEAR #1. Those respondents whose visits to a doctor within 

the past year are unknown (Question 47) have been Population excluded from this analysis. This population is slightly 

different than the population described in #2 because the population used 

in that analysis also excluded respondents with missing information regarding doctor’s advice. 

Population used in analysis: Daily smokers of 1 year ago with known doctors’ visits. 

Region 1992/93 1995/96 

Nation 35,411 28,829 

Calif 1,800 1,467 

N–CA 33,611 27,362 

96

Chapter 2 

Outcomes The outcome visit to a doctor in the last year is modeled. Question 47 is 

used to indicate doctor’s visit. 

Covariates The same covariates that are used in the basic cessation models 

(described in #1) are used in these models. 

5. RECEIVED DOCTOR’S 

ADVICE The population modeled in this analysis is the same population described in #3 (Cessation by Doctor’s Advice for 

Population those Who Saw a Doctor). 

Outcomes The outcome modeled is “receipt of doctor’s advice.” 

Covariates The same covariates used in the basic cessation models (#1) are used in 

this analysis. 

REFERENCES 

Biener, L., Fowler, F.J. Jr., Roman, A.M. 1993 

Massachusetts Tobacco Survey: Tobacco Use and 

Attitudes at the Start of the Massachusetts Tobacco 

Control Program. Boston: Center for Survey 

Research, University of Massachusetts, 1994. 

Biener, L., Roman, A.M. Technical Report: 1995 

Massachusetts Adult Tobacco Survey. Boston: 

Center for Survey Research, University of 

Massachusetts, 1996. 

Burns, D., Lee, L., Shen, Z., Gilpin, B., Tolley, D., 

Vaughn, J., Shanks, T. Cigarette Smoking 

Behavior in the United States. In: Changes in 

Cigarette-Related Disease Risks and Their 

Implication for Prevention. Smoking and Tobacco 

Control Monograph No. 8. Burns, D., Garfinkel, 

L., Samet, J., (editors). U.S. Department of Health 

and Human Services, National Institutes of 

Health, National Cancer Institute. NIH 

Publication No. 97-4213, 1997. 

Gilpin, E.A., Pierce, J.P., Cavin, S.W., Berry, C.C., 

Evans, N.J., Johnson, M., Bal, D.G. Estimates of 

population smoking prevalence: self-versus 

proxy reports of smoking status. American Journal 

of Public Health, 84(10):1576-1579, 1994. 

Hamilton, W. Independant Evaluation of the 

Massachusetts Tobacco Control Program: Fourth 

Annual Report Cambridge, MA: Abt Associates, 

Inc., 1998. 

Hunt, W.A., Barnett, L.W., Branch, L.G. Relapse 

rates in addiction programs. Journal of Clinical 

Psychology 27(4):455-456, 1971. 

Hymowitz, N., Cummings, K.M., Hyland, A., 

Pechacek, T.F., Hartwell, T.D. Predictors of smoking cessation in a cohort of adult smokers followed for five years. Tobacco Control 6(Suppl 

2):557-562, 1997. 

Pierce, J.P., Gilpin, E.A., Emery, S.L., White, M.M., 

Rosbrook, B., Berry, C.C. Has the California 

tobacco control program reduced smoking? 

Journal of the American Medical Association, 

280(10):893-899, 1998a. 

Pierce, J.P., Gilpin, E.A., Emery, S.L., Farkas, A.J., Zhu, 

S.H., Choi, W.S., Berry, C.C., Distefan, J.M., 

White, M.M., Soroko, S., Navarro, A. Tobacco 

Control in California: Who’s winning the war? La 

Jolla, CA: University of California, San Diego, 

1998b. 

Prochaska, J.O., DiClemente, C.C. Stages and 

processes of self-change in smoking: Toward an 

integrative model of change. Journal of Consulting 

and Clinical Psychology, 59:295–304, 1991. 

U.S. Department of Health and Human Services. The 

Health Consequences of Smoking: Nicotine 

Addiction. A Report of the Surgeon General. U.S. 

Dept. of Health and Human Services, Public 

Health Service, Centers for Disease Control, 

Center for Health Promotion and Education, 

Office on Smoking and Health. DHHS 

Publication No. (CDC) 88-8406, 1988. 

U.S. Department of Health and Human Services. The 

Health Benefits of Smoking Cessation. U.S. Dept of 

Health and Human Services, Public Health 

Service, Centers for Disease Control and 

Prevention, National Center for Chronic Disease 

Prevention and Health Promotion, Office on 

Smoking and Health. DHHS Publication No. 

(CDC) 90-8416, 1990. 

97

Restrictions on Smoking in 

the Workplace 

David M. Burns, Thomas G. Shanks, Jacqueline M. Major, 

Kathryn B. Gower, Donald R. Shopland 

OVERVIEW One of the most dramatic social changes over the past 30 years 

has been the change in attitudes about public smoking and the resultant 

governmental restrictions on where smoking is allowed. Beginning in 1970, 

with then Surgeon General Jesse Steinfeld's warning that environmental 

tobacco smoke (ETS) exposure was likely to cause problems for nonsmokers 

(Steinfeld, 1972), concern about ETS exposure led to 25 years of scientific 

inquiry. This inquiry culminated in a series of comprehensive reviews con

cluding that ETS exposure is a cause of cancer, heart disease, respiratory ill

ness, and a host of other problems (U.S.DHEW, 1972, 1977, 1979; 

U.S.DHHS, 1982 & 1986; NRC, 1986; U.S.EPA, 1992; Cal/EPA, 1997). 

Early reaction to this evidence included efforts to provide separate sec

tions for smokers and nonsmokers in restaurants and workplaces (NCI, 

1993). But with accumulating evidence that ETS exposure was a cause of 

cancer and other serious diseases, complete bans on smoking in workplaces 

and public places became more common. In 1986, only 3 percent of work

ers nationally reported working in a smoke-free workplace (Gerlach, 1997). 

By the 1992/93 Current Population Survey (CPS), the fraction of indoor 

workers reporting a smoke-free workplace had risen to 46.7 percent. Table 

3-1 presents data from the 1995/96 CPS and demonstrates that the fraction 

of workers covered by a 100 percent smoking ban in the workplace has 

risen to 64.3 percent, including more than half (54.1 percent) of all current 

smokers. 

Males and those who were between ages 18 and 24 were less likely to 

work in a smoke-free workplace, as were Hispanic and Native American 

indoor workers (Table 3-1). The likelihood of working in a smoke-free envi

ronment increases dramatically with increasing level of education and fami

ly income. The fraction of workers who work in a smoke-free workplace 

varies across states, from a high of 84 percent in Utah and Maryland to a 

low of 40 percent in Nevada, but only three states (Nevada, Arkansas, and 

Kentucky) have less than 50 percent of their employees working in smokefree areas. 

The increasing proportion of indoor workers who are employed in 

smoke-free workplaces has a direct health benefit for nonsmokers due to 

the decreased exposure to ETS. However, restrictions on where smokers can 

smoke may also influence the behavior of smokers outside of the workplace. Smokers may quit smoking altogether when a policy restricting 

smoking in the workplace is implemented (as opposed to refraining from 

their habit only at work). They may reduce the number of cigarettes that 

99
Smoking and Tobacco Control Monograph No. 12 

2,001 

681 

1995/96 Current Population Survey 

Level of Workplace Smoking Policy Population Sample 

Size Size Smoke Free 

% CI 

% CI 

% CI 

% CI 

% CI (N) (n) 

Total 64.26 0.37 11.21 0.25 9.15 0.22 1.25 0.09 14.13 0.27 84,811,586 80,661 

Smoking Status 

48,086,591 44,818 Never


Current 54.10 0.80 13.27 0.54 12.25 0.52 1.80 0.21 18.59 0.62 20,135,755 19,379


16,589,240 16,464 12.22 0.58 1.29 0.20 9.21 0.51 10.55 0.54 66.73 0.83 

40,089,095 33,103 Male


Female 69.26 0.49 10.47 0.33 7.15 0.28 0.76 0.09 12.36 0.35 44,722,491 47,558


Age (Years) 

18–24 55.92 1.03 13.21 0.70 9.67 0.61 1.05 0.21 20.15 0.83 12,050,968 8,640 25–44
45–64 67.77 0.69 10.07 0.44 8.69 0.41 1.22 0.16 12.25 0.48 23,906,035 24,670


47,056,921 45,350 

Non-Hispanic White
Hispanic 61.13 1.76 10.78 1.12 9.48 1.06 1.23 0.40 17.39 1.37 7,318,120 5,153


63,934,697 65,231 

9,737,977 7,135 African-American


Asian/Pacific Island 67.72 1.89 8.70 1.14 7.62 1.07 1.07 0.42 14.89 1.44 3,218,613 2,461
<12 

Years


12 

Years 55.81 0.68 13.19 0.47 11.15 0.43 1.75 0.18 18.11 0.53 27,250,901 26,273


6,836,863 5,800 

25,668,947 24,387 13–15 

Years


16+ 

Years 76.68 0.61 8.24 0.39 6.30 0.35 0.71 0.12 8.07 0.39 25,054,875 24,201


1,797,662 19.55 2.12 1.07 0.55 6.91 1.36 8.35 1.48 64.12 2.57 

602,179 19.84 3.73 1.48 1.13 10.70 2.89 10.33 2.85 57.65 4.62 

12.92 0.35 16.11 0.42 13.34 0.36 14.03 0.31 

11.76 0.75 

24.53 1.18 13.06 0.48 

Weak None 

Nation: Extent of Official Smoking Policy in the 

Workplace for Self-Respondent Adults Age 18 and Older, 

1.01 0.10 1.80 0.15 1.33 0.12 1.27 0.10 

1.23 0.26 

1.60 0.34 1.17 0.15 

7.83 0.28 

11.38 0.36 

9.33 0.30 9.13 0.26 

9.45 0.68 

12.17 0.90 

9.00 0.41 

Strong Moderate 

10.58 0.32 12.04 0.37 

11.39 0.33 11.13 0.28 

12.96 0.78 

15.41 0.99 10.89 0.44 

67.65 0.48 58.67 0.56 64.61 0.50 64.45 0.43 46.29 1.37 65.88 0.67 64.59 1.11 

Education (Years) 

Native American 

TRace/Ethnicity 

able 3-1 

Nation 

Former 

Gender 

65+ 

100
Chapter 3 1,174 

Table 3-1 (continued) 

Level of Workplace Smoking Policy Population Sample 

Size Size Smoke Free 

% CI % CI % CI % CI % CI (N) (n) 

Household Income (Dollars) 

< 10,000 51.97 1.63 13.24 1.11 10.87 1.02 1.31 0.37 22.60 1.37 4,823,326 4,340 

9,862,918 9,163 10,000–19,999


20,000–29,999 59.56 0.99 12.42 0.66 9.53 0.59 1.58 0.25 16.92 0.76 12,674,069 12,132


22,523,682 22,058 30,000–49,999


50,000–74,999 69.31 0.80 10.08 0.52 8.63 0.49 1.15 0.18 10.83 0.54 17,084,119 16,512
75,000 +
Unknown 63.45 1.53 10.29 0.96 8.74 0.90 1.05 0.32 16.47 1.18 5,108,254 4,781


12,735,217 11,675 

State* 

Utah 84.21 2.21 4.31 1.23 3.17 1.06 0.42 0.39 7.88 1.63 631,295 1,193 

1,893,937 1,038 Maryland


Vermont 79.22 2.72 5.65 1.55 6.51 1.65 0.59 0.51 8.03 1.82 206,509 947


9,258,735 5,376 California


District of Columbia 74.92 3.05 8.64 1.98 7.24 1.82 0.78 0.62 8.42 1.95 186,943 846
Washington
Maine 73.53 3.07 7.92 1.88 10.07 2.09 0.85 0.64 7.64 1.85 383,712 874


1,694,612 972 

New Hampshire
Colorado 72.01 2.80 9.58 1.83 6.33 1.52 0.45 0.42 11.64 2.00 1,313,603 1,312


391,078 845 

Massachusetts
Idaho 71.11 2.93 5.95 1.53 8.89 1.84 0.80 0.58 13.25 2.19 344,273 1,102


2,117,572 2,340 

Rhode Island
Alaska 69.92 2.97 7.81 1.74 8.90 1.85 1.02 0.65 12.35 2.13 183,542 801


326,789 786 

2,707,634 2,741 New Jersey


Minnesota 68.18 2.82 11.01 1.89 8.59 1.70 0.62 0.48 11.59 1.94 1,714,920 1,440


1,122,583 825 Connecticut


Oregon 67.46 3.17 11.94 2.19 9.14 1.95 0.62 0.53 10.84 2.10 1,001,932 965
Delaware
Florida 66.79 1.58 9.12 0.97 8.07 0.92 0.76 0.29 15.26 1.21 4,181,997 3,177


234,877 826 

1,284,546 15.26 2.29 0.84 0.58 9.03 1.82 8.73 1.80 66.13 3.01 Arizona 

19.62 0.91 13.41 0.52 

8.66 0.57 

4.72 1.31 

10.61 0.82 10.34 2.10 10.10 2.10 

11.82 1.30 

13.63 2.36 13.77 1.27 12.23 2.24 14.64 2.40 

Weak None 

1.44 0.27 1.27 0.17 0.97 0.20 

0.36 0.37 

0.70 0.22 1.01 0.69 1.37 0.81 0.58 0.31 1.07 0.71 1.04 0.37 0.66 0.56 0.89 0.64 

10.49 0.70 

9.63 0.45 7.09 0.52 

5.09 1.35 

4.98 0.58 6.78 1.73 5.34 1.57 7.67 1.07 6.46 1.69 8.23 1.01 8.57 1.91 8.46 1.89 

Strong Moderate 

13.67 0.78 

11.82 0.49 

8.15 0.55 

5.75 1.44 

6.82 0.67 8.09 1.88 9.67 2.06 8.38 1.12 7.92 1.86 8.44 1.02 

10.76 2.12 

8.68 1.91 

54.78 1.14 63.87 0.73 75.13 0.87 

84.09 2.26 

76.88 1.12 73.78 3.03 73.51 3.08 71.56 1.82 70.92 3.12 68.51 1.71 67.78 3.20 67.33 3.18 

Nation (continued) 

101
Smoking and Tobacco Control Monograph No. 12 

905 

Table 3-1 (continued) 

Level of Workplace Smoking Policy Population Sample 

Smoke Free 

% CI 

% CI 

% CI 

% CI 

% CI (N) (n) 

Size Size 

418,678 913 New Mexico


Texas 65.56 1.60 10.43 1.03 8.26 0.93 1.48 0.41 14.26 1.18 5,815,729 3,643


5,521,615 4,578 New 

York


Nebraska 63.90 2.92 9.70 1.80 10.46 1.86 0.81 0.54 15.13 2.18 571,872 1,276


Kansas
Virginia 63.09 2.82 12.74 1.95 9.37 1.71 1.22 0.64 13.59 2.01 2,297,995 1,408


862,573 1,218 

South Dakota
Iowa 62.55 3.06 12.27 2.07 8.86 1.79 1.20 0.69 15.12 2.26 967,618 1,208


221,591 1,220 

1,972,344 1,521

Wisconsin
Hawaii 61.89 3.50 15.34 2.60 12.34 2.37 1.04 0.73 9.39 2.10 346,498 640


135,107 1,009

Wyoming
Illinois 61.26 1.71 13.59 1.20 10.57 1.08 1.47 0.42 13.11 1.19 4,047,530 3,523


North Dakota
Pennsylvania 60.38 1.72 12.34 1.16 11.07 1.10 1.35 0.41 14.85 1.25 3,835,329 3,640


188,307 1,119 

West Virginia


South Carolina 59.15 3.08 16.08 2.30 9.74 1.86 1.09 0.65 13.93 2.17 1,257,513 922


457,077 925 231,352 1,029 Montana


Missouri 58.90 3.04 15.15 2.22 10.85 1.92 1.24 0.69 13.86 2.14 1,911,829 1,178
Oklahoma
Ohio 57.07 1.75 13.79 1.22 10.57 1.09 2.15 0.51 16.41 1.31 3,838,168 3,526


982,605 1,248 

Georgia
Louisiana 56.89 3.35 10.77 2.10 10.54 2.08 1.57 0.84 20.24 2.72 1,191,607 844


2,492,669 1,401 

Alabama
North Carolina 55.15 2.08 15.57 1.51 12.16 1.36 1.73 0.54 15.38 1.51 2,449,839 2,779


1,285,003 1,057 

796,440 24.52 2.87 1.40 0.78 7.89 1.80 11.26 2.11 54.92 3.32 Mississippi 

13.54 2.40 

14.45 0.98 14.17 2.24 16.20 2.32 

18.59 2.84 

21.46 2.80 

14.57 2.48 21.34 2.87 16.31 2.41 15.27 2.40 15.03 2.11 16.49 2.11 

Weak None 

0.86 0.65 

0.96 0.27 1.54 0.79 0.83 0.57 

0.90 0.56 1.01 0.73 

1.36 0.79 

1.31 0.80 1.63 0.89 1.55 0.80 0.85 0.52 1.69 0.86 

9.59 2.06 

10.09 0.84 

11.00 2.01 

9.56 1.85 

9.49 1.73 

10.99 2.28 

8.86 1.94 

11.35 2.23 

8.59 1.96 

12.78 2.17 10.37 1.73 12.86 2.23 

Strong Moderate 

10.29 2.13 

9.35 0.81 9.76 1.90 

10.73 1.94 

12.34 1.94 

7.95 1.98 

7.10 1.75 

12.95 2.36 

9.54 2.06 

10.90 2.03 15.22 2.04 14.44 2.34 

65.73 3.33 

65.14 1.33 63.53 3.09 62.68 3.04 

62.24 2.87 61.47 3.55 

61.22 3.32 

59.82 3.45 58.90 3.44 58.46 3.21 57.07 2.81 55.73 3.31 

State* 

102
Chapter 3 

Size 

(n) 

999 

3,294 1,182 

928 

1,046 

902 

Sample Population 

Size 

(N) 

1,738,759 

3,276,689 2,064,806 1,138,267 

791,438 523,649 

CI 

2.41 

1.37 2.36 2.72 2.53 2.34 

None 

18.36 

17.24 18.36 21.12 18.52 16.31 

% CI 

0.88 

0.55 1.02 0.94 1.04 1.26 

Weak 

Level of Workplace Smoking Policy 

2.05 

2.37 2.86 2.05 2.63 4.11 

% CI 

1.83 

1.20 1.94 2.05 2.14 2.42 

Moderate 

9.50 

12.55 

11.45 

10.59 12.34 17.63 

% CI 

2.28 

1.27 2.23 2.47 2.50 2.59 

Strong 

16.02 

14.16 15.89 16.54 18.05 21.04 

% 

3.10 

1.81 3.05 3.33 3.25 3.12 

* Listed in descending order of smoke-free status. 

Note: CI = 95% confidence interval. Source: 1995/96 Current Population Survey. 

Smoke Free 

CI 

54.08 

53.67 51.44 49.69 48.47 40.91 

% 

Table 3-1 (continued) 

State* 

Tennessee 

Michigan Indiana Kentucky Arkansas Nevada 

103
Smoking and Tobacco Control Monograph No. 12 

they smoke per day or may shift from smoking daily to smoking occasional

ly, and smokers who work in smoke-free evvironments may make more quit 

attempts or may be more successful in those quit attempts. Improvement in 

cessation may be an indirect benefit of the current trend toward smoke-free 

workplaces. 

CHANGES IN SMOKING Brownson et al. (1997) recently reviewed much of the 

BEHAVIOR WITH existing evidence on policies to reduce ETS exposure, 

IMPLEMENTATION OF and this chapter will update that evidence and add 

SMOKING RESTRICTIONS analyses conducted using data from the Current 

Population Surveys (CPS) and the California Tobacco Surveys (CTS). 

Changes in workplace smoking rules are often highly visible and are sometimes among the most contested shifts in workplace norms. Employers 

commonly make substantial efforts to inform and involve their workers as 

part of the introduction of these changes, and cessation assistance is fre

quently made available to smoking workers at the time that the changes in 

workplace rules are implemented. When the smoking behaviors of workers 

are followed before and after the implementation of workplace restrictions, 

many, but not all, studies have demonstrated a fall in smoking prevalence 

and increased cessation rates (Brownson et al., 1997). Many of the workplaces examined have been in health care settings (Table 3-2), but similar 

observations are evident in other settings as well (Table 3-3). These experi

ences would suggest that the implementation of smoking restrictions in the 

workplace can trigger smoking cessation attempts among the smokers who 

work there, particularly if cessation assistance is a prominent part of the 

implementation process. 

A similar picture emerges for changes in the number of cigarettes 

smoked per day following the implementation of restrictions on smoking in 

the workplace (Tables 3-2 and 3-3). Modest declines in the number of ciga

rettes smoked per day are evident following implementation of workplace 

smoking restrictions in most of the locations where it has been examined. 

Effects of Working in Changes in smoking behavior are to be expected when 

Smoke-free Workplaces there is a change in workplace restrictions on smoking 

on Smoking Behavior due to the accompanying shift in workplace norms and 

the provision of cessation assistance. However, it is reasonable to expect 

that there may be longer term effects on smoking behavior as well. Smokers 

may smoke fewer cigarettes per day if smoking is prohibited in work loca

tions, smokers may make more attempts to quit due to a shift in the social 

norms about smoking, and smokers who do attempt to quit may be more 

successful because they are less likely to relapse in workplaces that do not 

allow smoking. 

Number of Cigarettes Multiple studies presented in Tables 3-2 and 3-3 observed 

Smoked per Day reductions in number of cigarettes smoked per day that 

persisted for 12-18 months following implementation of a change in smok

ing policy. One study found a decline after 6 months, with a return to prior 

levels of consumption after 18 months (Hudzinski and Sirois, 1994). Emont 

et al. (1992) demonstrated a nonsignificant, but suggestive, relationship 

between level of smoking restriction from state clean-indoor-air laws and 

number of cigarettes smoked per day using data from the 1989 CPS. 

104
Chapter 3 

Quit ratio different between intervention Change in Prevalence –8.5% at 20-month follow-up No significant change No significant change 

–1.2% at 6-month follow-up NA No change 

–4.0% at 13-month follow-up –5.5% at 6-month follow-up –1.5 % at 4-month follow-up 22.5% of smokers quit at 9-month follow-up No increase in quit rate 9% of smokers stated that they quit because of the ban –2.9% at 30-month follow-up NA and comparison 13% at 60 months 

Impact of Smoke-Free Worksites on Cigarette Consumption and Prevalence: Health Care Worksites 

–2.0 cigarettes/day at 4-month follow-up –3.9 cigarettes/day at work at 12-month follow-up 

25% of smokers no longer smoked at work at No ef

–3.5 cigarettes/day at work at 13-month follow-up; –3.3 cigarettes/day at 6-month follow-up 40% of smokers reduced consumption at 4-month –4.5 cigarettes/day at 9-month follow-up –3.1 cigarettes/day at work at 12-month follow-up 57% of smokers reported cutting down Smokers made significant reductions in cigarettes/day at 6 months but returned to prior levels at 18 months 

fect on total daily consumption 

Change in Consumption NA 

No change at 6-month follow-up 12-month follow-up -1.4 cigarettes/day at work 

–1.8 cigarettes/day over 24 hours follow-up NA –1.1 cigarettes/day 

Children’

Psychiatric hospital Representative sample of hospital employees 

s hospital 

Medical center 

Location Hospital HMO Hospital 

Hospital HMO 

Hospital Hospital Hospital Hospital Hospital Hospital 

Andrews, 1983 Rosenstock, 1986 

Hudzinski, 1990 Mullooly

Daughton, 1992 Goldstein, 1992 Hudzinski, 1994 

, 1990 

TStillman, 1990 

able 3-2 

Author Biener, 1989 Becker, 1989 CDC, 1990 Baile, 1991 Stave, 1991 Offard, 1992 Longo, 1996 

105
Smoking and Tobacco Control Monograph No. 12 

vs 341 packs per year with no restrictions worksites vs 20.6% with no restrictions –1.2 cigarettes/ day –2% at 24-months follow-up 

CA Population Survey 296 packs per year in smoke-free worksites Prevalence was 13.7% in smoke-free 

Jeffery, 1994 

20.5 cigarettes/day without restrictions Brenner, 1994 Cross-section of Prevalence lower in workplaces with 

NA 21% of smokers quit at 20-month 

Author Petersen, 1988 Insurance co. –5.6 cigarettes/day at follow-up –1.6% at 12-month follow-up Borland, 1991 –3.1% at 18-month follow-up Brenner, 1992 National random sample –1.8 cigarettes/day in men, Quit ratio of 30% Scott, 1989 Insurance co. 22.5% of smokers decreased consumption –5.1% at 7-month follow-up 

at 7-month follow-up 15 or more cigarettes/day
–7.9 cigarettes/day in smokers of 25 or more –1.0% at 6-month follow-up


Location/
Study Population Change in Consumption Change in Prevalence


cigarettes/day 

Total database 1.00 employed smokers in


companies Product Opinion No restrictions 0.75


–12% reduction in consumption of –3.4% at 6 months 

Lab database followed Designated 0.92 between 1987 and 1991 Smoke-free 1.84* 

-11% Quitting rates: 

Telecommunications co. to 13.2 cigarettes/day with ban 

follow-up 

restrictions 

–5 cigarettes/day on work days vs leisure days NA 

Impact of Smoke-Free 

Worksites on Cigarette Consumption and Prevalence: Other 

Worksites 

Telecommunications co. –3.5 cigarettes/day at 18-month follow-up 

Borland, 1990 

cigarettes/day at 6-month follow-up 

–1.4 cigarettes/day in women 

Phillip Morris, 1992 Cohort of 22,500-28,000 Wakefield, 1992 Representative sample Gottlieb, 1990 Government agency 

Public service 

Diverse workplaces 

Sorensen, 1991 

Telephone co. 

Woodruff, 1993 Table 3-3 

106
Chapter 3 

Change in Prevalence Increased among intervention group 24.7 % to 25.1 % (p 1.0) Decreased among comparison group 27.2 % to 26.7 % (p 0.80) 

(p 0.14), but decreased from 5.5 to 5. 0 among comparison group (p 0.11) 

*According to this document, the quit rate is based only on those smokers who returned questionnaires and should therefore be considered understated. 

comparison group from 1Cigarettes/day in university buildings increased 

1.4 to 12.0 (p 0.002) 

Total cigarettes/day increased in intervention group from 1from 5.5 to 5.7 among intervention group 

1.4 to 11.7 (p 0.06) and in 

Change in Consumption Study Population 

Students and staff Location/ University 

Table 3-3 (continued) Author Etter, 1999 

107
Smoking and Tobacco Control Monograph No. 12 

Analyses of data from a 5-year longitudinal follow-up of 8,271 

employed adult smokers conducted as a part of the COMMIT trial exam

ined the change in number of cigarettes smoked per day as reported by the 

same individuals in two surveys conducted 5 years apart (Glasgow et al., 

1997). Using multiple linear regression techniques, they demonstrated a sta

tistically significant greater reduction in number of cigarettes smoked per 

day over the 5-year period among those who worked in workplaces where 

smoking was restricted to designated areas (OR = -1.17), and an even greater 

reduction for those who worked in workplaces where smoking was banned 

(OR = -2.78). 

An internal tobacco industry study (Heironimus, 1992) of the effects of 

restrictions on smoking in the workplace using a tracking database of smok

ers demonstrated that smokers who work in smoke-free environments con

sumed 11-15 percent fewer cigarettes per day compared to smokers who 

work where there are no restrictions. Lesser restrictions, such as allowing 

smoking only in designated sections, had little effect on consumption. 

Table 3-4 presents analyses of the 1992/93 and 1995/96 CPS for those 

who were daily cigarette smokers 1 year prior to the survey, currently 

smoked some days or every day, were age 25-64, and worked in an indoor 

environment. When smokers who worked in smoke-free workplaces are 

compared to those with lesser or no restrictions, there is a statistically sig

nificant (p < 0.001) shift in the categorical distribution of cigarettes smoked 

per day toward smoking fewer cigarettes per day. 

The CPS did not ask a question on the number of cigarettes smoked per 

day 1 year prior to the survey, and therefore these analyses are limited to 

examination of the cross-sectional distribution of current number of ciga

rettes smoked per day in relation to workplace restrictions on smoking. As a 

result, the analyses in Table 3-4 cannot identify whether the difference in 

number of cigarettes smoked per day by smokers working under different 

workplace smoking restrictions is due to a reduction in number of cigarettes 

smoked per day produced by the workplace restriction or due to workplace 

restrictions being more difficult to implement where there are greater num

bers of heavy smokers. 

The 1990 and 1996 California Tobacco Surveys (CTS) recorded the num

ber of cigarettes smoked per day both at the time of the survey and for 1 

year prior to the survey. Table 3-5 compares the current number of ciga

rettes smoked per day by those current cigarette smokers who work indoors 

with that reported for 1 year prior to the survey, and the results are strati

fied by the level of workplace restrictions on smoking. In the 1990 CTS, 

smokers who worked in workplaces with no restrictions on smoking were 

more likely to report smoking 25 or more cigarettes per day both at the 

time of the survey and for 12 months prior to the survey than were workers 

employed in workplaces where there were at least some restrictions. 

Workers who smoked 25 or more cigarettes per day 1 year prior to the sur

vey were also significantly more likely to report reducing the number of cig

arettes that they currently smoked if they worked in areas where smoking 

was banned than if they worked in areas where there were no restrictions. 

108
Chapter 3 

Table 3-4 

Percentage of Current Smokers who Smoke Various Numbers of Cigarettes per Day among 

Indoor Workers with Different Levels of Restriction on Smoking in the Workplace 

Cigarettes Level of Workplace Smoking Restrictions 

Smoked Work Area: Ban Ban Restricted Restricted No 

per Day Public Area: Ban No Ban Ban Restricted Restrictions 

1992/93 CPS* 

Occasional Smoking


1–4


5–14


15–24


25+


1995/96 CPS** 

Occasional Smoking


1–4


5–14


15–24


25+


3.91 2.85 3.40 2.15 2.25 

2.95 1.97 2.16 0.49 1.76 

28.20 21.49 18.11 16.16 17.84 

48.75 53.21 48.37 40.66 48.75 

16.19 20.48 27.96 40.53 29.41 

3.34 2.48 2.04 3.11 2.13 

2.47 1.39 1.88 0.63 2.37 

27.58 19.71 17.16 15.14 17.72 

50.20 51.49 50.97 40.67 48.14 

16.41 24.93 27.95 40.45 29.64 

* 1992/93 CPS. Chi-Square = 453.3; degrees of freedom = 16; probability < 0.001; N = 14,787; chi-square based on weighted sample normalized to sample size. 

**1995/96 CPS. Chi-square* = 386.8; degrees of freedom = 16; probability < 0.001; N = 12,669; chi-square based on weighted sample normalized to sample size. 

Note: Current smokers were also daily smokers 1 year prior to the survey and between ages 25 and 64 years. 

We also used these CTS data to develop a logistic regression model of 

the effect of working in a workplace where smoking was restricted on the 

likelihood of current daily smokers having reduced the number of cigarettes 

they reported smoking per day during the period between 12 months prior 

to the survey and the time of the survey. Co-variates controlled for in the 

analyses were gender, age, race/ethnicity, education level, family income 

level, and number of cigarettes smoked per day 1 year prior to the survey. 

Current daily smokers who worked in areas where there were some smoking 

restrictions were more likely to have reduced the number of cigarettes 

smoked per day when compared to smokers who worked in areas where 

there were no restrictions (OR = 1.44, 95% CI = 1.06-1.96). The effect for 

current daily smokers working in areas where smoking was banned was 

even more robust (OR = 1.54, 95% CI = 1.10-2.16). Data for the 1996 CTS 

are also presented in Table 3-5, but the small number of smokers who work 

in areas that are not smoke-free (state law requires smoke-free workplaces in 

California) makes meaningful comparison difficult; however, there appears 

to be a similar trend in the 1996 CTS. These data suggest that the trend 

toward a reduction in number of cigarettes smoked per day among workers 

who work where smoking is restricted demonstrated for the CPS data is due 

to the effect of the smoking restrictions on smoking behavior, rather than 

being due to smoking restrictions being easier to implement in workplaces 

where there are fewer heavy smokers. 

These data taken as a whole suggest that a smoke-free workplace policy 

results in a reduction in the number of cigarettes smoked per day by con

tinuing smokers. 

109
Smoking and Tobacco Control Monograph No. 12 Indoor 

Workers: Change in Reported Number of Cigarettes Smoked per Day from 1 

Year Prior to the Survey to 

Time of the Survey by 

Current Daily Smokers, Ages 25–64, Who Smoked Daily 1 

Year Ago—1990 and 1996 California 

Tobacco Surveys 

Level of Cigs. Smoked # Cigarettes Smoked per Day at Time of Survey Population Sample 

Size Size 

(N) (n) 

Total
25+ 88.30 3.05 8.56 2.76 2.76 2.05 0.38 0.62 163,554 369


533,544 1,104 

15–24
5–14 3.33 4.48 9.02 3.67 79.39 7.60 8.27 6.73 112,651 201


239,644 517 

17,695 17 

24.09 3.08 49.86 3.51 22.93 2.89 3.12 1.37 507,500 1,124 

25+
15–24 3.07 1.83 88.78 3.17 7.58 2.52 0.57 0.67 241,848 553


155,672 345 

96,295 204 1.46 2.22 90.00 3.83 8.54 3.79 

. . 6.02 12.37 3.86 8.10 . . 13,685 22 

397,712 986

Total
25+ 76.31 6.20 18.04 5.85 5.39 3.13 0.26 0.50 91,684 251


15–24
5–14 0.26 0.52 2.66 2.36 95.98 2.98 1.09 1.33 104,350 219


190,605 494 

11,073 22 

4.54 2.78 

0.14 0.28 0.45 0.57 

2.88 1.97 0.30 0.48 

% CI % CI 

1–4 . . . . . . 

1–4 . . 

5–14 1–4 

20.33 4.04 

4.62 1.92 6.98 5.08 

31.26 5.25 

9.84 4.56 

4.31 9.32 

45.40 3.72 

90.88 2.69 

1.44 3.19 

18.81 5.48 

46.20 4.61 85.85 5.98 

7.13 15.43 

% CI % CI 

25+ 15–24 

29.73 3.94 

4.36 2.00 

73.76 6.18 

19.66 3.16 

4.01 2.98 

2.75 6.01 

5–14 . . 

before Survey 

Daily 1 

Year 

Total 

1–4 

1996 CTS 

None Some All 

Table 3-5 

Smoking 

Ban 

110
Chapter 3 

Sample 

Size 

(n) 

173 

61 72 38 

2 

144 

37 70 34 

3 

2,343 

434 

1,165 

665 

79 

Population 

Size 

(N) 

84,289 

27,575 33,034 22,176 

1,505 

69,664 15,616 31,231 20,851 

1,967 

1,041,596 

194,965 486,926 319,701 

40,003 

2.76 

4.43 8.42 0.97 0.67 0.45 1.37 

16.50 

CI 

. . . . . . . 

1–4 

1.79 

3.78 4.25 4.21 0.34 0.56 2.50 

81.34 

% 

# Cigarettes Smoked per Day at Time of Survey 

. . . . . . . 

7.96 

2.45 8.19 

15.67 10.60 

11.59 

6.80 2.91 1.84 2.31 2.18 

16.73 

CI 

. . . 

5–14 

27.41 

1.23 9.83 

88.00 36.36 16.09 94.20 35.65 

4.22 

12.69 92.30 15.65 

% 

. . . 

7.38 

12.15 

8.82 

15.67 

9.63 

12.84 

6.80 2.92 4.10 2.48 1.63 1.99 

CI 

. . . 

15–24 

41.21 

13.89 85.50 12.00 39.56 75.49 

5.80 

44.37 16.70 84.88 

4.92 1.55 

% 

. . . 

Note: CI = 95% confidence interval; “ .” = insufficent data. Source: 1990 and 1996 California Tobacco Surveys. 

7.25 

12.31 

4.41 6.60 5.06 2.12 4.54 0.77 0.39 2.89 

CI 

. . . . . 

25+ 

29.60 

84.88 

4.67 

20.30 

4.18 

15.76 78.74 

1.88 0.28 1.46 

% 

. . . . . 

Cigs. Smoked 

before Survey 

Daily 1 Year 

15–24 15–24 15–24 

Table 3-5 (continued) 

T

5–14 5–14 5–14 

otal 

Total Total 25+ 1–4 25+ 1–4 25+ 1–4 

Level of 

Smoking 

None Some All 

Ban 

1996 CTS 

111
Smoking and Tobacco Control Monograph No. 12 

Table 3-6 

Current Smoking Status among Indoor Workers with Different Levels of Restriction on 

Smoking in the Workplace, Age 18+ 

Workplace Percentage of Smokers 

Restrictions Daily Occasional Former Never 

CTS 1996 100% Smoking Ban 12.21 5.23 22.09 58.47 

Some Restrictions 14.76 5.68 23.61 54.09 

No Restrictions 23.62 7.45 21.73 45.53 

CPS 1992/93 100% Smoking Ban 15.33 4.50 21.91 58.26 

Some Restrictions 23.70 4.99 20.03 51.29 

No Restrictions 25.85 4.99 19.10 50.06 

CPS 1995/96 100% Smoking Ban 15.97 4.02 20.31 59.70 

Some Restrictions 25.17 4.83 19.05 50.95 

No Restrictions 26.43 4.80 16.91 51.86 

Source: 1996 California Tobacco Survey; 1992/93 and 1995/96 Current Population Surveys. 

CESSATION Cross-sectional data from California and the CPS demonstrate 

that the prevalence of smoking is substantially lower among workers who 

are employed in smoke-free workplaces. However, the difference in current 

smoking prevalence across workplaces with different levels of smoking 

restrictions is largely due to a higher prevalence of never smokers rather 

than former smokers in those workplaces with greater restrictions (Table 3-

6). This would suggest that the difference in smoking prevalence may be 

due to smokers moving to workplaces where smoking was allowed or 

greater ease in successfully implementing smoke-free workplaces in sites 

where there are fewer smokers rather than an effect of smoking restrictions 

on cessation. 

The effect of smoking restrictions on cessation has been examined 

directly, however, and an effect of restrictions on cessation has been 

demonstrated. Data from a 5-year longitudinal follow-up of 8,271 employed 

adult smokers conducted as a part of the COMMIT trial examined cessation 

attempts and cessation success reported by the same individuals in two sur

veys conducted 5 years apart (Glasgow et al., 1997). Using multiple logistic 

regression techniques, they demonstrated a statistically significant 25 percent greater likelihood of making a cessation attempt over the 5-year period 

among those who worked in workplaces where smoking was banned, and 

workers in these workplaces had a 25 percent greater rate of having successfully quit during the 5-year period as well. 

Emont et al. (1992) demonstrated a statistically significant relationship 

between the level of state clean-indoor-air laws and a higher fraction of ever 

smokers who were former smokers (quit ratio) using data from the 1989 

CPS. An internal tobacco industry study (Heironimus, 1992) of a tracking 

database of smokers suggested that smokers in a smoke-free workplace quit 

at a rate that is 84 percent higher than smokers who work in locations 

where smoking is allowed. Lower levels of smoking restriction had much 

less effect on cessation. 

112
Chapter 3 

Tables 3-7 and 3-8 present the results of multivariate logistic regression 

analyses of several measures of cessation (see Chapter 2) by level of workplace restriction of smoking for the 1992/93 CPS (Table 3-7) and the 

1995/96 CPS (Table 3-8). The cessation measures are estimated for all those 

who were daily smokers 1 year prior to the survey, worked indoors, and 

were between ages 25 and 64 at the time of the survey. The results are controlled for age, gender, race/ethnicity, education and income levels, and 

number of cigarettes smoked per day. A term is also added to the regression 

that represents the average level of workplace restriction for the state in 

which the individual lives. This term is used to control for the influences of 

general environmental restrictions on smoking and of different social 

norms about smoking present in the environment. The intent is to remove 

these influences from an analysis of the effect of the specific level of restric

tion present in the workplace where the individual is employed. The preva

lence of each cessation measure by level of workplace restriction and by 

demographic characteristics of the population is included in Tables 3-9 and 

3-10. 

The 1992/93 CPS (Table 3-7) shows no relationship between working in 

a smoke-free environment and either making a cessation attempt or becom

ing an occasional smoker; however, there is a significant relationship 

between working in a smoke-free area and becoming a former smoker (OR = 

1.18) or having been quit for 3 or more months (OR = 1.39). There is also a 

smaller, but statistically significant, effect of the average level of workplace 

smoking restriction present in the state on being a former smoker of 3+ 

months’ duration, suggesting that there may be an effect of environmental 

norms about smoking as well as a direct effect of the level of restriction 

where the smoker works. 

The 1995/96 CPS (Table 3-8) analyses show similar results, with the 

addition of small effects of a smoke-free workplace on cessation attempts 

and any cessation change. Similar effects are also noted for the average level 

of workplace restriction in the state as a measure of the general environ

mental norms on smoking restrictions. 

These data suggest that there is an effect of restricting smoking in the 

workplace on smoking cessation, with a small increase in the number of 

cessation attempts when a 100-percent ban on smoking is present in the 

workplace. The effect is not evident for lower levels of workplace restric

tion. There is no effect of smoking restrictions in the workplace on becom

ing an occasional smoker, but there is a modest effect of the average level of 

workplace restriction for the state on becoming an occasional smoker. This 

result suggests that the general environmental norms may be more impor

tant for becoming an occasional smoker, and that the effect of individual 

experience with workplace restrictions is on cessation. The principal effect 

of restricting smoking in the workplace appears to be an increase in the suc

cess rate of those smokers who are attempting to quit. The modest effect on 

cessation attempts, with a much larger effect on 3+ month cessation suc

cess, suggests that the effect of a smoke-free workplace may be to prevent 

113
Smoking and Tobacco Control Monograph No. 12 Multivariate Logistic Regression Analyses of Measures of Cessation by Level of 

Workplace Restriction for Those who were Current Daily 

1.39 (1.20 - 1.62) 1.06 (1.01 - 1.10) 1.16 (1.00 - 1.34) 1.01 (0.86 - 1.18) 1.09 (0.76 - 1.57) Hispanic


African-American 1.17 (1.05 - 1.31) 1.16 (1.03 - 1.30) 1.22 (0.91 - 1.63) 0.87 (0.70 - 1.08) 1.07 (0.83 - 1.39)


0.76 (0.46 - 1.25) 

1.32 (0.99 - 1.75) 12


13–15 1.64 (1.46 - 1.85) 1.59 (1.40 - 1.79) 2.36 (1.54 - 3.61) 1.70 (1.33 - 2.17) 1.48 (1.10 - 1.98)


1.77 (1.29 - 2.43) 2.17 (1.67 - 2.82) 3.07 (1.95 - 4.82) 1.58 (1.38 - 1.82) 1.68 (1.46 - 1.92) 16+ 

Smokers 1 

Year prior to the Survey and who 

Worked Indoors, Age 25–64 

Years, 1992/93 Current Population Survey 

Cessation Activity Cessation Attempt Occasional Former (any length) Former, 3+ Months 

Odds


Ratio 95% CI Ratio 95% CI Ratio 95% CI Ratio 95% CI Ratio 95% CI


Odds Odds 

1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.18 (1.04 - 1.33) 1.02 (0.99 - 1.06) 1.05 (0.93 - 1.19) 1.02 (0.90 - 1.16) 1.03 (0.76 - 1.38) 

0.73 (0.49 - 1.10) 

1.57 (1.24 - 1.99) 

1.07 (0.88 - 1.29) 1.05 (0.99 - 1.10) 0.76 (0.61 - 0.94) 1.24 (0.81 - 1.90) 

0.91 (0.52 - 1.60) 

1.74 (1.14 - 2.64) 1.35 (1.11 - 1.63) 

Odds Odds 

1.00 1.00 1.00 1.00 1.00 1.00 

1.00 1.00 

1.00 1.00 1.00 1.00 1.01 (0.94 - 1.09) 1.01 (0.99 - 1.03) 0.98 (0.92 - 1.05) 0.80 (0.75 - 0.86) 0.79 (0.67 - 0.94) 

0.84 (0.68 - 1.04) 

1.33 (1.18 - 1.49) 

1.00 1.00

1.02 1.00 

(0.95 - 1.09) 

1.02 (1.00 - 1.03) 1.00 (0.94 - 1.07) 0.80 (0.74 - 0.85) 0.82 (0.69 - 0.96) 

0.84 (0.68 - 1.03) 

1.36 (1.21 - 1.52) 

Lesser Restrictions 1.00 Same Ban Level 1.00 

1.00 

Non-Hispanic White 1.00 

1.00 

Worksite Level of Ban 

State % Total Ban* Education (Years) 

Total Work Ban State Ban +5% 

TRace/Ethnicity 

able 3-7 

Gender 

Male Female 

Age (Years) 

25–44 45–64 

Other 

< 12 

114
Chapter 3 

(0.91 - 2.02) (1.10 - 2.40) (1.30 - 2.75) (1.42 - 3.1(1.54 - 3.68) (0.35 - 0.76) (0.38 - 0.80) (0.59 - 1.27) 

1) 

Former, 3+ Months 

95% CI 

Odds 

Ratio 

1.00 

1.36 1.63 1.89 2.10 2.38 

1.00 

0.51 0.55 0.86 

(1.05 - 2.00) (1.10 - 2.08) (1.44 - 2.63) (1.44 - 2.71) (1.44 - 2.95) (0.38 - 0.70) (0.35 - 0.64) (0.51 - 0.95) 

Former (any length) 

95% CI 

Odds 

Ratio 

1.00 

1.45 1.51 1.94 1.97 2.06 

1.00 

0.51 0.48 0.69 

(0.61 - 1.48) (0.84 - 1.97) (0.75 - 1.73) (0.87 - 2.10) (0.87 - 2.43) (0.62 - 1.65) (0.36 - 0.96) (0.32 - 0.92) 

95% CI 

Occasional 

Odds 

Ratio 

1.00 

0.95 1.29 1.14 1.36 1.45 

1.00 

1.01 0.59 0.54 

(0.95 - 1.28) (1.16 - 1.56) (1.27 - 1.69) (1.30 - 1.77) (1.50 - 2.19) (0.68 - 1.04) (0.45 - 0.69) (0.38 - 0.59) 

Cessation Attempt 

95% CI 

*Effect of a 5% difference between states of the average ban level for the state. 

Source: 1992/93 Current Population Survey. 

Odds 

Ratio 

1.00 

1.10 1.34 1.47 1.52 1.81 

1.00 

0.84 0.56 0.48 

(0.95 - 1.27) (1.17 - 1.56) (1.27 - 1.67) (1.31 - 1.76) (1.51 - 2.18) (0.69 - 1.04) (0.45 - 0.67) (0.38 - 0.58) 

Cessation Activity 

95% CI 

Odds 

Ratio 

1.00 

1.10 1.35 1.46 1.52 1.82 

1.00 

0.85 0.55 0.47 

TCigarettes Smoked per Day 

able 3-7 (continued) 

Income (Dollars) 

<10,000 

10,000–19,999 20,000–29,999 30,000–49,999 50,000–74,999 75,000+ 

1–4 

5–14 15–24 25+ 

115
Smoking and Tobacco Control Monograph No. 12 Multivariate Logistic Regression Analyses of Measures of Cessation by Level of 

Workplace Restriction for Those who were Current Daily 

1.34 (1.10 - 1.63) 1.03 (0.99 - 1.08) 0.77 (0.64 - 0.93) 0.88 (0.72 - 1.07) 0.88 (0.56 - 1.38) Hispanic


African-American 1.05 (0.92 - 1.19) 1.07 (0.94 - 1.21) 0.85 (0.59 - 1.22) 0.75 (0.56 - 1.00) 0.77 (0.54 - 1.10)


1.16 (0.73 - 1.82) 

12
13–15 1.40 (1.23 - 1.61) 1.36 (1.19 - 1.57) 1.69 (1.13 - 2.52) 1.31 (0.98 - 1.75) 1.30 (0.90 - 1.86)


1.11 (0.78 - 1.58) 1.56 (1.06 - 2.31) 1.47 (1.07 - 2.01) 1.53 (0.97 - 2.41) 1.30 (1.11 - 1.53) 1.33 (1.14 - 1.56) 16+ 

Smokers 1 

Year prior to the Survey and who 

Worked Indoors, Age 25–64 

Years, 1995/96 Current Population Survey 

Cessation Activity Cessation Attempt Occasional Former (any length) Former, 3+ Months 

Odds


Ratio 95% CI Ratio 95% CI Ratio 95% CI Ratio 95% CI Ratio 95% CI


Odds Odds 

1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.21 (1.04 - 1.42) 1.04 (1.01 - 1.08) 0.82 (0.70 - 0.96) 0.81 (0.69 - 0.95) 0.75 (0.51 - 1.10) 1.04 (0.71 - 1.52) 1.00 (0.75 - 1.32) 

1.13 (0.90 - 1.42) 1.06 (1.01 - 1.12) 1.11 (0.89 - 1.39) 0.91 (0.72 - 1.15) 1.08 (0.70 - 1.66) 0.80 (0.45 - 1.42) 1.03 (0.69 - 1.54) 

Odds Odds 

1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.09 (1.00 - 1.18) 1.04 (1.02 - 1.06) 0.89 (0.82 - 0.96) 0.85 (0.78 - 0.92) 0.78 (0.65 - 0.94) 1.16 (0.94 - 1.42) 1.17 (1.02 - 1.33) 

1.09 (1.01 - 1.18) 1.04 (1.02 - 1.06) 0.90 (0.83 - 0.97) 0.85 (0.78 - 0.92) 0.80 (0.67 - 0.96) 1.13 (0.92 - 1.38) 1.17 (1.02 - 1.33) 

Lesser Restrictions 1.00 Same Ban Level 1.00 

1.00 1.00 

Non-Hispanic White 1.00 

1.00 

Worksite Level of Ban 

State % Total Ban* Education (Years) 

Total Work Ban State Ban +5% 

TRace/Ethnicity 

able 3-8 

Gender 

Male Female 

Age (Years) 

25–44 45–64 Other < 12 

116
Chapter 3 

(0.62 - 1.61) (0.60 - 1.53) (0.82 - 1.97) (0.76 - 1.92) (1.14 - 3.00) (0.42 - 1.1(0.31 - 0.82) (0.41 - 1.12) 

1) 

Former, 3+ Months 

95% CI 

Odds 

Ratio 

1.00 1.00 0.96 1.27 1.21 1.85 1.00 0.68 0.51 0.68 

(0.68 - 1.48) (0.68 - 1.44) (0.92 - 1.88) (0.95 - 2.01) (1.22 - 2.71) (0.49 - 1.12) (0.37 - 0.83) (0.46 - 1.08) 

Former (any length) 

95% CI 

Odds 

Ratio 

1.00 1.00 0.99 1.31 1.38 1.82 1.00 0.74 0.55 0.70 

(0.43 - 1.1(0.47 - 1.18) (0.57 - 1.33) (0.53 - 1.33) (0.43 - 1.26) (0.24 - 0.52) (0.13 - 0.28) (0.08 - 0.21) 

1) 

95% CI 

Occasional 

Odds 

Ratio 

1.00 0.69 0.75 0.87 0.84 0.74 1.00 0.35 0.19 0.13 

(0.75 - 1.07) (0.73 - 1.02) (0.85 - 1.18) (0.86 - 1.22) (0.87 - 1.29) (0.70 - 1.14) (0.47 - 0.76) (0.34 - 0.55) 

Cessation Attempt 

95% CI 

*Effect of a 5% difference between states of the average ban level for the state. 

Source: 1995/96 Current Population Survey. 

Odds 

Ratio 

1.00 0.90 0.86 1.00 1.02 1.06 1.00 0.89 0.60 0.43 

(0.74 - 1.04) (0.72 - 1.00) (0.85 - 1.16) (0.85 - 1.20) (0.85 - 1.25) (0.61 - 0.96) (0.40 - 0.62) (0.28 - 0.45) 

Cessation Activity 

95% CI 

Odds 

Ratio 

1.00 0.87 0.85 0.99 1.01 1.03 1.00 0.76 0.50 0.36 

TCigarettes smoked per day 

able 3-8 (continued) 

Income (Dollars) 

<10,000 10,000–19,999 20,000–29,999 30,000–49,999 50,000–74,999 75,000+ 1–4 5–14 15–24 25+ 

117
Smoking and Tobacco Control Monograph No. 12 

relapse after a cessation attempt rather than to increase the number of 

smokers who try to quit. It may well be that if you cannot smoke at work, 

it is more difficult to relapse at work. 

SUMMARY There has been a dramatic increase in the fraction of the working 

population protected by total bans on smoking in the workplace, increasing 

from 3 percent in 1986 to 64 percent in 1996. These restrictions have two 

effects on smokers as they are implemented. They increase the rate at which 

smokers attempt to quit, and they reduce the number of cigarettes smoked 

per day. Once restrictions on smoking in the workplace have been successfully implemented, they continue to have the effect of reducing the num

ber of cigarettes smoked per day, and they increase the success rate of smok

ers who are attempting to quit. There may also be a small effect of increas

ing the frequency with which smokers attempt to quit. 

THE FOLLOWING PAGES CONTAIN 

TABLES 3-9 AND 3-10 

118
Chapter 3 

3,602 

439 

3,829 

Nation: Current Smoking Status among Indoor Worker Self-respondent Adults Who Were Daily Smokers 1 Year Ago, Age 25 and Older, 1992/93 Current Population Survey 

Current Smoking Status 

Population Sample Daily Smokers 

No Quit Attempts w/Quit Attempts Smokers <3 Months 3+ Months Size Size 

Nation
Total 61.29 0.93 27.96 0.86 2.88 0.32 2.84 0.32 5.04 0.42 12,575,808 16,041

(N) (n) 

Ban [Ban]Ban [No Ban] 63.48 2.04 27.01 1.89 2.61 0.68 2.82 0.70 4.08 0.84 2,537,189 3,303

4,661,981 5,916 

Restrict [Ban]Restrict [Restrict] 62.33 6.03 27.24 5.54 1.97 1.73 2.37 1.89 6.09 2.97 295,478 388

2,250,384 2,832 

25–4445–64 64.99 1.65 24.27 1.48 2.34 0.52 2.96 0.58 5.44 0.78 3,842,573 5,018

8,733,235 11,023 

Race/Ethnicity 

Non-Hispanic White 61.76 1.02 27.37 0.93 2.76 0.34 2.99 0.36 5.13 0.46 10,463,533 13,965 HispanicAfrican-American 55.52 3.08 34.31 2.95 3.71 1.17 1.84 0.83 4.63 1.30 1,216,283 1,145

565,382 492 

1,526,453 1,883 <12

12 62.98 1.37 27.14 1.26 2.38 0.43 2.88 0.47 4.61 0.59 5,691,190 7,42813–1516+ 55.07 2.49 29.34 2.28 4.51 1.04 4.04 0.98 7.03 1.28 1,830,843 2,208

3,527,323 4,522 

Cigarettes Smoked per Day 

1–4 49.66 5.97 32.67 5.60 4.77 2.54 4.80 2.55 8.10 3.26 321,024 360 5–1415–24 63.13 1.30 27.46 1.20 2.46 0.42 2.46 0.42 4.49 0.56 6,321,567 8,258

2,948,752 3,594 2,830,777 4.30 0.82 3.16 0.70 2.03 0.57 25.32 1.75 65.19 1.91 

330,610 4.08 2.36 2.04 1.68 3.17 2.08 28.70 5.38 62.01 5.78 

2,984,466 6.43 0.96 3.21 0.69 2.02 0.55 21.14 1.60 67.20 1.84 25+ 

Former Smokers Former Smokers 

6.33 0.76 4.24 0.91 4.86 0.49 4.83 2.62 3.19 0.96 5.48 0.82 4.46 0.81 

% CI 

2.63 0.50 2.92 0.76 2.78 0.38 2.65 1.97 1.36 0.63 2.78 0.59 3.06 0.68 

% CI 

3.50 0.58 3.12 0.78 3.12 0.40 3.21 2.16 1.38 0.64 3.50 0.66 4.46 0.81 

% CI 

Daily Smokers Occasional 

28.62 1.42 31.06 2.09 29.58 1.04 24.74 5.29 22.26 2.28 31.02 1.67 35.41 1.88 

% CI 

Workplace Smoking Rules, listed as: 

Work Area Level [Public Areas Level] 

58.93 1.54 58.66 2.22 59.66 1.12 64.58 5.86 71.82 2.46 57.22 1.78 52.61 1.97 

% CI 

Education (Years) 

No Restricions 

Table 3-9 Age (Years) 

Other 

119
Smoking and Tobacco Control Monograph No. 12 (n) 

225 

Daily Smokers 

No Quit Attempts w/Quit Attempts Smokers <3 Months 3+ Months Size Size 

Population Sample 

949,892 1,214 <10,000 

10,000–19,999 66.52 2.11 25.08 1.94 2.17 0.65 2.54 0.70 3.69 0.84 2,284,478 2,978 

2,523,179 3,285 20,000–29,999

30,000–49,999 59.51 1.67 28.80 1.54 2.75 0.56 3.49 0.62 5.45 0.77 3,962,812 5,06150,000–74,99975,000 + 53.06 3.85 32.28 3.61 3.87 1.49 3.06 1.33 7.74 2.06 767,670 926

2,087,777 2,577 

States 

Alabama 62.08 8.67 29.47 8.15 1.39 2.10 2.80 2.95 4.25 3.61 193,329 203 

AlaskaArizona 61.78 8.16 26.63 7.42 3.83 3.22 1.65 2.14 6.11 4.02 170,232 147

27,314 206 

136,381 240 Arkansas

California 58.20 3.84 27.20 3.46 3.07 1.34 2.64 1.25 8.89 2.21 945,027 705

169,028 190 Colorado

Connecticut 60.82 8.15 27.31 7.44 0.41 1.07 5.01 3.64 6.45 4.10 191,794 181

20,919 87 District of Columbia

Delaware 71.31 7.32 18.37 6.26 2.61 2.58 2.22 2.38 5.50 3.69 40,213 141

639,167 646 Florida

Georgia 57.51 7.82 32.29 7.39 2.39 2.42 3.82 3.03 3.98 3.09 347,525 177

40,394 102 Hawaii

Idaho 60.25 8.08 27.00 7.33 4.48 3.42 2.01 2.32 6.25 4.00 47,008 200IllinoisIndiana 65.78 7.08 24.36 6.40 0.83 1.35 4.76 3.18 4.27 3.02 353,669 240

658,778 710 

158,397 284 Iowa

Kansas 71.98 6.46 19.20 5.67 1.66 1.84 2.41 2.20 4.75 3.06 152,500 288

KentuckyLouisiana 64.51 9.22 27.72 8.62 2.05 2.73 1.01 1.93 4.72 4.08 167,709 138

218,011 218 

(N) % CI % CI % CI % CI 

80,702 3.09 2.51 1.75 1.90 2.67 2.33 28.29 6.52 64.20 6.94 Maine 

Former Smokers Former Smokers 

2.69 1.12 4.59 0.89 6.34 1.14 

3.51 2.92 

4.17 3.23 

7.49 4.60 

5.40 5.07 

3.98 1.56 

2.48 3.05 4.61 1.70 

4.49 3.17 

2.87 2.59 

1.50 0.84 2.19 0.62 3.22 0.83 

0.94 1.53 

3.74 3.07 

2.28 2.61 

1.85 3.02 

1.70 1.03 

1.59 2.45 3.21 1.43 

2.98 2.60 

2.49 2.42 

Table 3-9 (continued) 

Current Smoking Status 

2.25 1.03 3.15 0.74 3.52 0.86 

3.02 2.71 

1.75 2.12 

4.75 3.72 

5.06 4.92 

2.33 1.20 

3.61 3.66 3.12 1.41 

3.02 2.62 

2.01 2.18 

Daily Smokers Occasional 

24.62 2.99 28.43 1.92 28.86 2.12 

28.50 7.15 

21.05 6.59 

24.42 7.51 

26.06 9.84 

28.55 3.60 

30.56 9.04 27.96 3.65 

28.79 6.92 

21.24 6.35 

68.94 3.21 61.64 2.07 58.06 2.31 

64.03 7.61 

69.30 7.46 

61.06 8.53 

61.62 10.91 

63.44 3.84 

61.77 9.54 61.09 3.96 

60.72 7.47 

71.39 7.02 

% CI Nation 

Household Income (Dollars) 

120
Chapter 3 

Daily Smokers 

No Quit Attempts w/Quit Attempts Smokers <3 Months 3+ Months Size Size 

Population Sample 

State 

Maryland 55.26 7.94 29.91 7.31 6.85 4.03 4.94 3.46 3.04 2.74 270,841 169 

(N) (n) 

MassachusettsMichigan 56.46 3.80 33.61 3.62 2.03 1.08 2.28 1.14 5.62 1.77 583,695 833

316,111 602 

271,791 253 Minnesota

Mississippi 62.00 8.90 29.48 8.36 1.57 2.28 2.17 2.67 4.78 3.91 112,968 208

304,815 242 Missouri

Montana 70.42 8.07 18.30 6.83 2.95 2.99 3.46 3.23 4.87 3.81 36,596 221

416,294 812 North Carolina

North Dakota 58.18 8.48 31.22 7.96 5.40 3.88 2.97 2.92 2.24 2.54 27,882 211

74,191 232 Nebraska

Nevada 65.35 6.63 28.40 6.28 0.44 0.93 1.43 1.66 4.37 2.85 87,270 241

61,072 135 New Hampshire

New Jersey 60.71 4.29 28.26 3.96 2.05 1.25 2.38 1.34 6.61 2.18 349,012 545

57,657 139 New Mexico

New York 58.99 3.39 28.14 3.10 3.09 1.19 4.41 1.41 5.38 1.55 772,360 886

669,072 870 Ohio

Oklahoma 59.04 7.74 28.19 7.08 1.74 2.06 4.30 3.19 6.72 3.94 173,599 223

133,926 166 Oregon

Pennsylvania 59.35 3.99 29.93 3.72 2.90 1.36 2.16 1.18 5.66 1.87 618,303 739Rhode IslandSouth Carolina 65.95 6.61 23.90 5.95 2.99 2.38 3.16 2.44 3.99 2.73 209,182 256

50,910 143 

33,751 257 South Dakota

Tennessee 60.83 7.35 30.99 6.96 2.11 2.16 3.76 2.86 2.31 2.26 280,697 241

TexasUtah 69.01 8.77 22.25 7.89 3.37 3.42 0.95 1.84 4.42 3.90 59,725 134

762,515 637 

Former Smokers Former Smokers 

5.99 1.98 5.17 3.34 

4.38 3.19 

2.99 1.25 

5.35 3.62 

5.21 3.85 

4.52 3.88 

5.67 1.73 3.43 3.33 6.70 4.37 

6.85 3.95 

3.46 1.69 

% CI 

4.06 1.64 1.82 2.02 

3.62 2.91 

3.03 1.26 

2.10 2.31 

2.95 2.93 

1.33 2.14 

1.90 1.02 1.53 2.25 3.46 3.19 

1.96 2.16 

2.27 1.38 

% CI 

Table 3-9 (continued) 

Current Smoking Status 

2.75 1.36 5.56 3.46 

3.61 2.91 

2.57 1.16 

1.21 1.76 

4.09 3.43 

2.90 3.14 

2.91 1.26 3.28 3.26 3.21 3.08 

3.91 3.03 

3.02 1.59 

% CI 

Daily Smokers Occasional 

31.99 3.89 28.63 6.81 

25.98 6.84 

24.37 3.15 

33.21 7.58 

24.06 7.40 

23.31 7.90 

27.69 3.35 30.72 8.44 25.34 7.60 

25.41 6.80 

29.49 4.22 

% CI 

55.21 4.14 58.82 7.42 

62.41 7.55 

67.05 3.45 

58.13 7.94 

63.68 8.32 

67.94 8.72 

61.82 3.64 61.03 8.92 61.29 8.51 

61.87 7.59 

61.75 4.50 

% CI 

121
Smoking and Tobacco Control Monograph No. 12 149 Daily Smokers No Quit Attempts w/Quit Attempts Smokers <3 Months 3+ Months Size Size Population Sample (N) (n) State 

Vermont 59.75 7.62 28.89 7.04 3.26 2.76 2.79 2.56 5.30 3.48 37,915 177 

371,310 268

VirginiaWashington 56.37 8.16 29.79 7.52 3.83 3.16 3.12 2.86 6.88 4.16 246,885 176

93,929 210

West Virginia

Wisconsin 60.18 6.90 27.64 6.30 5.87 3.31 2.35 2.14 3.96 2.75 310,824 338

22,609 4.33 3.88 3.13 3.32 2.85 3.18 31.58 8.87 

Former Smokers Former Smokers 

4.34 2.77 

3.23 3.00 

% CI 

3.17 2.38 

0.84 1.54 

% CI 

Table 3-9 (continued) 

Current Smoking Status 

2.36 2.06 

2.79 2.79 

% CI 

Daily Smokers Occasional 

27.19 6.05 

19.33 6.69 

% CI 

62.94 6.57 

73.80 7.45 58.11 9.42 

% CI 

Note: CI = 95% confidence interval. *Source: 1992/93 Current Population Survey. 

Wyoming 

122
Chapter 3 

2,292 

404 

2,971 

Population Sample Daily Smokers 

No Quit Attempts w/Quit Attempts Smokers <3 Months 3+ Months Size Size 

(N) (n) Nation


Total 67.5 0.9 24.2 0.8 2.7 0.3 2.0 0.3 3.6 0.4 13,184,031 13,422

Ban [Ban]Ban [No Ban] 70.8 2.4 22.7 2.2 2.4 0.8 1.6 0.7 2.6 0.8 1,786,388 1,779

7,200,542 7,392 1,679,520 1,720 Restrict [Ban]

Restrict [Restrict] 67.6 6.8 25.5 6.3 3.0 2.5 1.6 1.8 2.3 2.2 245,711 239

8,884,812 8,931 25–44

45–64 70.4 1.6 22.0 1.4 2.4 0.5 1.7 0.4 3.5 0.6 4,299,219 4,491

Race/Ethnicity 

Non-Hispanic White 68.2 1.0 23.4 0.9 2.6 0.3 2.1 0.3 3.7 0.4 10,839,373 11,541 HispanicAfrican-American 63.6 3.1 29.2 2.9 2.9 1.1 1.5 0.8 2.8 1.1 1,277,602 983

641,866 494 

<1212 69.7 1.4 23.7 1.3 2.0 0.4 1.5 0.4 3.1 0.5 5,816,058 6,014

1,537,128 1,473 

13–1516+ 63.6 2.5 24.8 2.3 3.4 1.0 2.7 0.9 5.4 1.2 1,871,281 1,861

3,959,563 4,074 

Cigarettes Smoked per Day 

1–4 52.7 6.2 28.4 5.6 10.9 3.9 2.4 1.9 5.6 2.8 336,446 318 

5–1415–24 68.9 1.3 24.0 1.2 2.1 0.4 1.8 0.4 3.1 0.5 6,689,405 6,885

3,229,042 3,248 

Nation: Current Smoking Status among Indoor Worker Self-respondent Adults who were Daily Smokers 1 Year Ago, Age 25 and Older, 

1995/96 Current Population Survey 

Current Smoking Status 

2,271,869 2.9 0.8 1.6 0.6 2.0 0.7 22.0 2.0 71.5 2.1 

425,189 5.0 2.4 2.1 1.6 2.5 1.7 29.9 5.1 60.5 5.4 

2,929,138 4.0 0.8 2.0 0.6 1.4 0.5 16.6 1.6 76.1 1.8 25+ 

Former Smokers Former Smokers 

% CI 

4.2 0.5 3.4 1.0 3.7 0.5 3.3 2.2 2.6 0.9 3.9 0.7 

4.1 0.8 

% CI 

2.1 0.4 2.6 0.9 2.2 0.4 1.3 1.4 1.6 0.7 2.5 0.6 

2.3 0.6 

% CI 

3.1 0.5 1.9 0.8 2.8 0.4 3.8 2.3 1.9 0.8 3.6 0.7 

4.1 0.8 

Daily Smokers Occasional 

% CI 

25.2 1.2 24.1 2.4 25.2 1.0 23.5 5.2 20.5 2.3 26.0 1.6 

31.0 1.8 

Workplace Smoking Rules, listed as: 

Work Area Level [Public Areas Level] 

% CI 

65.3 1.3 68.0 2.6 66.1 1.1 68.1 5.7 73.4 2.6 63.9 1.7 

58.4 2.0 

Education (Years) 

No Restrictions 

Table 3-10 Age (Years) 

Other 

123
Smoking and Tobacco Control Monograph No. 12 (n) 

163 

Daily Smokers 

No Quit Attempts w/Quit Attempts Smokers <3 Months 3+ Months Size Size 

Population Sample 

890,140 922 <10,000 

10,000–19,999 69.7 2.3 23.8 2.1 2.3 0.7 1.5 0.6 2.8 0.8 2,035,953 2,100 

20,000–29,99930,000–49,999 66.9 1.7 24.4 1.5 2.8 0.6 2.1 0.5 3.9 0.7 4,117,727 4,253

2,563,182 2,637 

50,000–74,99975,000 + 64.5 3.2 23.9 2.8 2.7 1.1 2.7 1.1 6.2 1.6 1,182,091 1,116

2,394,938 2,394 

State 

Alabama 67.4 8.3 28.3 8.0 1.8 2.3 1.2 1.9 1.3 2.0 182,677 161 AlaskaArizona 63.0 7.8 25.9 7.1 2.9 2.7 5.6 3.7 2.7 2.6 197,215 197

31,231 138 

153,177 207 

2.4 1.3 4.9 1.8 964,676 589 

198,247 206 Colorado

Connecticut 67.4 8.9 27.2 8.5 1.6 2.4 1.1 2.0 2.7 3.1 144,552 108

19,597 87 District of Columbia

Delaware 70.0 7.5 18.8 6.4 4.4 3.3 3.5 3.0 3.3 2.9 40,305 149

FloridaGeorgia 73.6 6.7 21.2 6.2 . . 3.0 2.6 2.2 2.2 348,989 212

672,955 539 

45,482 86 Hawaii

Idaho 64.9 8.1 22.2 7.1 5.0 3.7 2.5 2.6 5.4 3.8 50,023 165

648,422 601 Illinois

Indiana 75.3 5.9 19.4 5.4 . . 0.8 1.3 4.4 2.8 405,977 248

168,848 221 Iowa

Kansas 75.6 6.5 18.5 5.9 1.8 2.0 1.5 1.9 2.5 2.4 154,920 228

222,143 197 Kentucky

Louisiana 77.1 7.3 14.1 6.0 2.0 2.4 2.0 2.4 4.8 3.7 182,864 136

(N) % CI % CI % CI % CI 

69,418 3.5 3.0 1.6 2.0 0.8 1.4 27.5 7.3 66.7 7.7 Maine 

Former Smokers Former Smokers 

2.7 1.2 2.8 0.7 

3.8 0.9 

3.9 3.0 

2.7 2.4 5.7 3.7 1.0 2.2 

3.9 1.6 3.6 3.7 

3.4 1.6 3.9 2.9 2.9 2.5 

1.4 0.9 1.6 0.6 

2.7 0.7 

0.6 1.2 

4.1 3.2 1.2 2.4 

2.0 1.2 3.9 3.9 

1.8 1.2 1.4 1.8 1.1 1.6 

Arkansas . . 

Table 3-10 (continued) 

Current Smoking Status 

3.0 1.3 2.5 0.7 

3.0 0.8 

2.1 2.3 

1.9 2.0 

1.6 3.6 4.0 4.0 26.4 62.4 

3.2 2.8 3.0 3.7 

2.4 1.3 2.6 3.2 

2.8 1.4 3.5 2.8 1.3 1.7 

Daily Smokers Occasional 

25.9 3.3 22.9 1.9 

25.0 2.0 30.4 7.2 

20.2 5.9 25.4 7.0 27.6 9.7 

23.3 3.5 21.2 8.1 

23.5 3.7 20.7 6.1 25.5 6.6 

% CI 

67.0 3.6 70.2 2.0 

65.5 2.2 63.0 7.6 

75.2 6.4 61.7 7.8 67.1 10.2 

68.4 3.9 68.7 9.2 

68.6 4.1 70.4 6.9 69.2 7.0 

Nation 

Household Income (Dollars) 

California 

124
Chapter 3 

Daily Smokers 

No Quit Attempts w/Quit Attempts Smokers <3 Months 3+ Months Size Size 

Population Sample 

State 

Maryland 62.4 8.2 27.3 7.5 4.9 3.7 1.6 2.1 3.7 3.2 253,032 146 

(N) (n) 

MassachusettsMichigan 62.6 4.0 29.4 3.8 2.3 1.2 2.1 1.2 3.7 1.6 622,882 649

302,728 350 

274,423 243 Minnesota

Mississippi 65.0 8.0 27.3 7.5 1.1 1.8 3.2 2.9 3.3 3.0 126,519 151

361,678 234 Missouri

Montana 67.4 8.0 27.1 7.5 2.4 2.6 0.5 1.1 2.6 2.7 39,296 183

426,357 507 North Carolina

North Dakota 74.2 7.3 20.4 6.8 1.3 1.9 3.1 2.9 1.0 1.7 31,021 195

83,923 195 Nebraska

Nevada 67.0 7.0 25.6 6.5 3.9 2.9 1.1 1.6 2.4 2.3 95,940 171

72,494 166 New Hampshire

New Jersey 69.2 4.5 21.5 4.0 1.3 1.1 4.0 1.9 4.1 1.9 380,038 395

67,139 154 New Mexico

New York 64.5 3.7 25.8 3.3 3.1 1.3 1.6 1.0 5.0 1.7 742,585 644

707,330 681 Ohio

Oklahoma 68.5 7.0 24.8 6.5 4.1 3.0 1.8 2.0 0.8 1.3 181,739 238

146,569 151 

0.7 0.7 4.7 1.8 669,981 658 

59,114 145 Rhode Island

South Carolina 77.0 6.1 17.2 5.4 2.1 2.1 1.7 1.8 2.1 2.0 237,363 182

36,583 210 South Dakota

Tennessee 72.5 6.4 21.0 5.8 2.7 2.3 1.0 1.4 2.9 2.4 327,339 204

847,183 556 Texas

Utah 68.3 9.1 21.2 8.0 5.9 4.6 1.4 2.3 3.2 3.4 60,579 120

Former Smokers Former Smokers 

% CI 

5.0 2.3 

3.1 2.6 

4.3 2.9 

2.9 1.7 

1.8 2.1 4.0 3.2 

3.6 3.2 

2.6 1.3 

4.9 3.8 

3.4 2.9 

3.9 3.0 

2.6 1.4 

% CI 

3.2 1.9 

3.6 2.8 

1.0 1.4 

2.7 1.6 

3.5 2.9 2.9 2.7 

2.4 2.7 

1.9 1.1 

2.3 2.4 

2.6 2.5 

1.8 1.2 

Oregon . . 

Table 3-10 (continued) 

Current Smoking Status 

% CI 

3.2 1.9 

5.1 3.3 

3.7 2.7 

2.6 1.6 

2.2 2.3 3.3 2.9 

4.5 3.6 

2.7 1.3 

2.0 2.5 

1.5 3.6 3.4 4.0 24.5 Pennsylvania 66.7 

1.6 2.0 

5.1 3.4 

2.6 1.4 

Daily Smokers Occasional 

% CI 

32.7 5.0 

24.7 6.5 

24.9 6.1 

21.1 4.1 

21.8 6.6 31.0 7.5 

24.8 7.6 

19.4 3.3 

20.3 7.1 

31.2 7.5 

26.3 6.8 

25.7 3.9 

% CI 

55.9 5.3 

63.4 7.3 

66.0 6.7 

70.7 4.6 

70.7 7.2 58.8 8.0 

64.7 8.4 

73.4 3.6 

72.8 7.9 

61.5 7.9 

62.1 7.5 

67.3 4.1 

125
Smoking and Tobacco Control Monograph No. 12 203 Daily Smokers No Quit Attempts w/Quit Attempts Smokers <3 Months 3+ Months Size Size Population Sample (N) (n) State 

Vermont 65.8 7.5 27.2 7.1 1.4 1.9 1.4 1.9 4.2 3.2 36,771 176 

VirginiaWashington 59.2 8.8 30.6 8.3 1.4 2.1 3.8 3.4 5.0 3.9 248,779 152

362,169 241 

West Virginia

Wisconsin 65.5 6.5 26.7 6.0 3.6 2.6 1.0 1.3 3.3 2.4 370,648 299

84,774 185 25,339 4.8 3.6 1.0 1.7 1.9 2.3 

Former Smokers Former Smokers 

% CI 

3.7 2.8 

2.9 2.7 

% CI 

2.5 2.3 

1.1 1.7 

Table 3-10 (continued) 

Current Smoking Status 

% CI 

1.6 1.8 

3.3 2.9 

Daily Smokers Occasional 

% CI 

22.8 6.2 

21.9 6.8 21.0 6.9 

Note: CI = 95% confidence interval; “. “ = insufficient data. *Source: 1995/96 Current Population Survey. 

% CI 

69.5 6.8 

70.8 7.4 71.2 7.6

Wyoming 

126
Chapter 3 

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128
Population Impact of Clinician 

Efforts to Reduce Tobacco Use 

Jack F. Hollis 

INTRODUCTION A large fraction of U.S. smokers visit a physician each year, creating an opportunity to alter their smoking behavior. This chapter examines 

1) the proportion of U.S. smokers who are receiving recommended tobacco 

interventions during routine health care visits; 2) whether clinician intervention rates are increasing over time; and 3) what effect physician advice 

is having on cessation activity and success. We use Current Population 

Survey (CPS) data and meta-analyses on the efficacy of clinician interventions to estimate the number of smokers in the United States who quit each 

year as a direct result of current clinician counseling practices and also to 

determine what might be achieved through improved practice patterns. 

Finally, we consider office system strategies that appear necessary to integrate systematic tobacco support into routine care, making progress toward 

the year 2000 goals of reducing tobacco-use prevalence to 15 percent. 

RATIONALE FOR CLINICIAN- The rationale, methods, and outcomes for brief 

DELIVERED TOBACCO tobacco interventions during routine health and 

INTERVENTIONS dental care visits have been widely discussed 

(Lichtenstein et al., 1996a; Fiore et al., 2000; NCI, 1994; Ockene et al., 

1997a; Abrams et al., 1996). Physicians, nurses, dentists, hygienists, pharmacists, and others involved in the routine delivery of health care have the 

opportunity, legitimacy, and professional credibility to motivate and help 

patients quit tobacco use. The vast majority of smokers want to quit on 

their own, without attending specialized intensive programs (Fiore et al., 

1990), and few will act on clinician referrals to groups, even with systematic 

recruitment efforts and convenient free access (Lichtenstein and Hollis, 

1992). 

Evidence-based national clinical guidelines for tobacco intervention in 

routine care have been published (Fiore et al., 2000) that, if widely implemented, would reach a high proportion of all tobacco users on a regular 

basis. Brief cessation advice is easy to deliver, and is both expected and 

appreciated by patients if done in a caring and respectful manner 

(Schauffler et al., 1996). When delivered, brief interventions consistently 

increase quit rates (Fiore et al., 2000; Kottke et al., 1988; Law and Tang, 

1995; Ockene et al., 1997a) and are highly cost-effective in terms of both 

cost per quit and cost per year of life saved (Cromwell et al., 1997; Law and 

Tang, 1995; Warner, 1993). Arguments for involving clinicians in brief 

counseling include the following: 

• Tobacco is the most important cause of preventable disease, 

• Most smokers see physicians (70 percent) and/or dentists (50 percent) each year, 

129

Smoking and Tobacco Control Monograph No. 12 

• Smokers view clinicians as credible and persuasive, 

• Clinic visits represent teachable moments when health concerns 

are salient, 

• Satisfaction is higher among patients receiving tobacco advice 

and support, 

• Meta-analyses show modest, but consistent positive effects of 

physician advice on cessation, and 

• Tobacco interventions are highly cost-effective when compared 

to other medical services. 

While clinicians agree that patients should quit smoking, many clinicians and health system leaders remain unconvinced that significant 

resources should be devoted to implementing recommended interventions 

as a part of routine care. Busy clinicians, pressured to squeeze more and 

more into the typical 10-minute encounter, question whether it makes 

sense to devote 10-30 percent of that time to smoking when only 5-10 percent quit rates can be expected. Health system and medical office managers 

are unsure how to implement tobacco treatment guidelines and question 

whether they are practical and sustainable and whether the impact on cessation rates justifies the effort and costs of implementation. Managers of 

capitated managed care organizations worry that successful ex-smokers will 

switch plans before the plan can realize a return on its investment in tobacco control. Common concerns and barriers include the following: 

• Lack of time, funding, space, and support staff, 

• Reluctance to “badger” patients about an issue of lifestyle choice, 

• Beliefs that intervention benefits are too uncertain or delayed, 

• Inadequate training, confidence, and comfort in discussing 

tobacco issues, 

• Lack of reminders or prompts to cue action, 

• Lack of performance feedback and peer/professional support, and 

• Lack of reimbursement or other incentives for delivering tobacco 

intervention. 

Given these challenges, it is perhaps not surprising that the U.S. healthcare system has been slow to respond to calls for action in addressing tobacco during routine care. The U.S. Public Health Service Agency for 

Healthcare Research and Quality (AHRQ) guidelines powerfully summarized 

the situation by concluding, “it is difficult to identify a condition in the 

United States that presents such a mix of lethality, prevalence, and neglect, 

and for which effective interventions are so readily available” (Fiore et al., 

2000). 

130

Chapter 4 

HOW MANY PATIENTS RECEIVE A goal of Healthy People 2010 is to “increase 

TOBACCO ADVICE AND ASSIS- to at least 75 percent the proportion of the 

TANCE, AND DO THEY QUIT? population of primary care and oral health 

care providers who routinely advise cessation and provide assistance and 

follow-up for all of their tobacco-using patients” (U.S.DHHS, 2000). The 

AHRQ Clinical Practice Guideline recommends that clinicians identify smokers and encourage cessation as a routine part of virtually all medical and 

dental care contacts (Fiore et al., 2000). 

The frequency of physician-delivered advice to quit depends, in part, on 

whom one asks. When physicians are asked how they generally practice, 

the vast majority report that they regularly advise virtually all smokers. 

Patients report much lower rates of advice. The large discrepancies between 

clinician and patient reports are likely due to numerous factors, including 

incomplete patient recall, unclear or unmemorable clinician messages, and 

overreporting by clinicians. For example, Brink et al. (1994) found that 95 

percent of physicians and 65 percent of dentists reported that they advised 

all or most of their smoking patients to quit. Their survey of patients, however, found that only 29 percent of those who had seen a physician and 7 

percent of those who had seen a dentist reported receiving advice. Woller et 

al. (1995) surveyed a stratified random sample of 6,132 patients who had 

visits in one of 45 primary care practices in the upper Midwest. More than 

90 percent of smokers said they were asked about smoking and 84 percent 

recalled advice to quit, but this was over a relatively long 3-year period. 

Only 60 percent received advice on how to quit, however, and only 27 percent said the clinician referred them to a stop-smoking program during the 

3-year period. 

It is possible that surveys understate actual practice because patients fail 

to recall the clinician’s advice, but a recent comparison of smokers’ reports 

of advice and tapes of clinical encounters suggests otherwise. Ward and 

Sanson-Fisher (1996) found that, if anything, smokers tend to over-report 

receipt of clinician advice to quit (sensitivity of 0.92, specificity of 0.82). 

Solberg (1996) notes that patient reports of advice not being delivered were 

quite accurate (negative predictive value of 99 percent) and that advice 

rates in surveys probably portray an overly optimistic picture. Even if recall 

of clinician advice were low, that would simply suggest that clinician interventions need to be more frequent, salient, and memorable. Data from 

physicians’ own post-visit summaries and patients’ post-visit reports are less 

susceptible to recall bias, and yet they confirm that most intervention 

opportunities are wasted. 

As part of the COMMIT trial (Ockene et al., 1997b), a random sample of 

30 physicians in each of 11 treatment and 11 control communities were 

surveyed about office practices. A high percentage of treatment and control 

clinicians (79 percent and 80 percent, respectively) reported that they routinely ask established patients about smoking, and almost all (98 percent 

and 94 percent) reported that they advise smokers to quit “most or all of 

the time.” Relatively few, however, used stickers or other chart markers (28 

percent and 26 percent), set quit dates (22 percent and 14 percent), devel131

Smoking and Tobacco Control Monograph No. 12 

oped cessation plans (38 percent and 37 percent), made referrals (22 percent 

and 22 percent), or arranged follow-up visits for smoker counseling (19 percent and 18 percent). Physicians were more likely to report recommending 

nicotine replacement therapy (NRT) (52 percent and 42 percent) and to 

report recording the results of the encounter in the clinical record (66 percent and 60 percent). In contrast, a survey of 20,347 smokers from these 

communities found that many fewer patients reported receiving advice (42-

56 percent), pamphlets (21-31 percent), or encouragement to use NRT (20-

31 percent). 

Others have queried patients shortly after a specific visit in order to 

minimize recall bias. Heywood et al. (1996) randomly sampled and surveyed 7,160 patients from 230 general practitioners in Australia during 

1989 and 1990 and found that 49 percent received advice during a specific 

recent visit. Advice was more likely to be given to younger smokers, those 

with smoking-related health conditions or other risk factors, and those who 

had been counseled previously. Kottke et al. (1997) surveyed 7,997 randomly selected patients following visits in 44 midwestern clinics and found that 

47 percent of smokers reported receipt of advice at that visit. Hollis et al. 

(1998) surveyed 20,372 patients (76 percent response rate) shortly after 

their routine Family Practice and Internal Medicine visits within a staffmodel HMO. While 59 percent of patients reported receiving advice to quit 

at the visit, few received either self-help (5 percent) or referral (12 percent) 

materials. 

The National Ambulatory Medical Care Survey (NAMCS) provides information on national trends in advice rates at specific visits since 1991 as 

reported by physicians themselves (Thorndike et al., 1998). Between 1991 

and 1995, a random sample of 3,254 U.S. physicians (response rates of 70-

73 percent) completed one-page after-visit reports on all patients seen during assigned 1-week periods. This survey yielded data on 145,716 patient 

visits. Over the 5 years, the proportion of visits at which smoking was 

known (or assessment occurred) remained constant at 67 percent. This was 

also true for new patient visits and for general medical examinations. 

Physicians reported counseling at only 22 percent of visits with known 

smokers. Counseling rates increased from 16 percent in 1991 to a peak of 

29 percent in 1993, and then decreased to 21 percent in 1995. Primary care 

clinicians counseled more than specialists (33 percent versus 15 percent), 

and counseling was more likely at visits for smoking-related conditions (35 

percent) and during general medical exams (37 percent). Counseling was 

less likely for those over age 65 and for those with conditions unrelated to 

smoking. Insurance status was unrelated to counseling rates. NRT was 

reported for about 1 percent of visits, with the number peaking in 1993. 

The Health Plan Employer Data and Information Set (HEDIS 3.0) is a 

measure of the quality of care in participating health plans across the country (NCQA, 1997). As part of the HEDIS 3.0, health plans contracted for 

standardized mailed surveys of random samples of health-plan members. 

The smoking measures include: 

132

Chapter 4 

1. Have you ever smoked at least 100 cigarettes in your entire life? 

2. Do you now smoke every day, some days, or not at all? 

3. How long has it been since you quit smoking cigarettes? 

4. During the past 12 months, how many times have you visited a 

doctor or other health professional in your plan (do not count 

overnight hospital visits)? (This is coded None versus Yes) 

5. On how many of these visits were you advised to quit smoking 

by a doctor or other health professional in your plan? (Those 

responding “one or more” are classified as smokers who have 

received medical advice to quit.) 

Among smokers who had seen a doctor or other health care professional in the health plan within the last year, 61 percent reported that they had 

received cessation advice on one or more occasions in the last year (see 

www.ncqa.org). 

Two ongoing national population surveys provide the best picture of 

how patient perceptions of tobacco advice rates are changing over time 

(Figure 4-1). The first is the National Health Interview Surveys (NHIS), conducted periodically since the early 1970s. During each update, large national probability samples of the smokers in the U.S. population are interviewed 

at home. Response rates typically exceed 85 percent. Using NHIS data, 

Gilpin et al. (1992) reported that the percentage of smokers reporting that a 

physician had ever advised them to quit smoking rose dramatically from 26 

percent in 1974 to 51 percent in 1987. 

For 1991, the CDC (1993) used the NHIS to estimate that, of the 51 million smokers in the United States, 70 percent (36 million) had one or more 

outpatient visits with a physician or other health care professional. Most 

had multiple visits. About 37 percent (12.8 million) of smokers with visits 

reported receiving advice to quit smoking during the previous year, and a 

little more than half (56 percent) reported ever receiving cessation advice. 

Advice in the previous year was more common among those with four or 

more visits (45 percent) compared to those with one visit (28 percent). 

Rates were higher for older, non-Hispanic, and heavier smokers. 

The 1992 NHIS survey asked separately about both physician and dentist visits within the previous year, and whether physicians and dentists had 

offered cessation advice within the previous year (U.S.DHHS, 1992). Among 

smokers who had physician visits (70 percent) in the previous year, 52 percent reported receiving cessation advice from physicians (Tomar et al., 

1996). The sharp increase from the 37 percent rate recorded for 1991 may 

be related to attention surrounding the marketing of NRT products. Among 

smokers with dentist visits (53 percent), about 24 percent reported advice 

from a dentist in the previous year. Those planning to quit within the next 

6 months were also more likely to report having received advice to quit in 

the previous year. Advice was more likely for heavier and older smokers, in 

contrast to the lower rates of counciling for the elderly found in the 

NAMCS. Others have also shown that clinicians are more likely to advise 

heavier smokers (Cummings et al., 1987) and those who are white, older, 

133 
Smoking and Tobacco Control Monograph No. 12 

Figure 4-1 

Percentage of Smokers Reporting Ever Having Received Physician Advice, 

Aged 18 and Over* 

0

10

20

30

40

50

60

70

80

974 986 991 992/93 1995/96

NHIS

26%

NHIS

51%

NHIS

56%

CPS

58%

CPS

62%

Year of Survey

Percentage

* NHIS is the National Health Interview Survey, and CPS is the Tobacco-Use Suppliment of the 

Current Population Survey 

and in poorer health (Hymowitz et al., 1996; CDC, 1993; Frank et al., 1991). 

In summary, it appears that while the proportion of patients reporting they 

had ever been advised increased sharply in the 1980s, progress has been 

slow more recently in spite of increased attention, national guidelines, and 

repeated calls for action. 

A comparable source of national data is the Current Population Survey 

(CPS), which is designed to provide labor force indicators for the U.S. 

Bureau of Labor Statistics. The CPS uses household interviews to gather 

information from a national probability sample derived from census data. 

For both the 1992/93 and 1995/96 CPS, NCI appended a Tobacco Use 

Supplement that included items about physician and dentist visits and 

tobacco advice that were identical to those used in the NHIS survey. We 

present these data here for the first time. 

The determinants of who receives physician advice have two components: first are the determinants of who sees a physician at all, and second, 

of those who see a physician, who receives advice to quit smoking? Among 

daily cigarette smokers age 25 years and older surveyed by the CPS in 

1992/93, 71.3 percent reported visiting a physician in the last year and 50.8 

percent reported visiting a dentist in the last year. In 1995/96, 72.5 percent 

saw a physician and 51.3 percent saw a dentist. Table 4-1 presents the 

results of multivariate regression analyses of the 1992/93 and 1995/96 CPS 

and identifies the demographic and smoking characteristics that predict 

which smokers were likely to visit a physician in the year prior to the sur134 
Chapter 4 

Table 4-1 

CPS 1992/93 and 1995/96—Multivariate Logistic Regressions of Visits to a Physician in the Last 

Year (Current Smokers 25+ Years of Age Who Were Daily Smokers 1 Year Ago) 

1992/93 1995/96 

Variable OR 95% CI OR 95% CI 

Gender 

Male 

Female 

Age (Years) 

25–44 

45–64 

65+ 

Race/Ethnicity 

Non-Hispanic White 

Hispanic 

African-American 

Other 

Education (Years) 

< 12 

12 

13–15 

16+ 

1.00 

2.11 

1.00 

1.19 

2.45 

1.00 

0.84 

1.06 

0.77 

1.00 

1.03 

1.34 

1.20 

Household Income (Dollars) 

<10,000 1.00 

10,000–19,999 0.92 

20,000–29,999 1.15 

30,000–49,999 1.29 

50,000–74,999 1.52 

75,000+ 1.73 

Cigarettes Smoked per Day 

1–4 1.00 

5–14 1.10 

15–24 1.01 

25+ 0.96 

1.00 

(2.01 - 2.21) 2.14 (2.03 - 2.27) 

1.00 

(1.13 - 1.25) 1.34 (1.26 - 1.42) 

(2.21 - 2.71) 2.42 (2.16 - 2.71) 

1.00 

(0.75 - 0.93) 0.68 (0.61 - 0.77) 

(0.98 - 1.15) 0.97 (0.89 - 1.06) 

(0.67 - 0.89) 0.74 (0.64 - 0.86) 

1.00 

(0.97 - 1.10) 1.13 (1.05 - 1.21) 

(1.24 - 1.44) 1.34 (1.24 - 1.46) 

(1.09 - 1.33) 1.37 (1.23 - 1.52) 

1.00 

(0.86 - 0.99) 0.85 (0.78 - 0.93) 

(1.06 - 1.25) 0.92 (0.84 - 1.01) 

(1.19 - 1.39) 1.16 (1.06 - 1.27) 

(1.38 - 1.68) 1.33 (1.20 - 1.48) 

(1.50 - 1.98) 1.41 (1.23 - 1.61) 

1.00 

(0.93 - 1.29) 0.98 (0.82 - 1.17) 

(0.86 - 1.19) 0.89 (0.75 - 1.06) 

(0.81 - 1.13) 0.88 (0.73 - 1.05) 

vey. Female smokers, older smokers, and smokers with higher levels of education and income were more likely to visit a physician, and Hispanic 

smokers were less likely to see a physician, as were smokers of Asian/Pacific 

Islander/Native American and other races. There was no relationship 

between number of cigarettes smoked per day and likelihood of seeing a 

physician. 

The frequency of reporting physician advice to quit smoking in the last 

year among current daily smokers who were also daily smokers 1 year prior 

to the survey and who saw a physician in the last year is presented in Table 

4-2a. In the 1992/93 CPS 54.7 ± 0.8 percent of current daily smokers over 

age 25 reported that they had been advised to quit in the last year. This 

measure is virtually identical to that from the 1992 NHIS estimate of 52 

percent reported above (Tomar et al., 1996). Reported advice rates increased 

slightly (59.2 ± 0.8 percent; Table 4-2b) in 1995/96. Approximately 65.8 ± 

135 
Smoking and Tobacco Control Monograph No. 12 

Table 4-2a 

CPS 1992/93—Who Received Physicians' Advice (Current Smokers 25+ Years of Age Who 

Were Daily Smokers 1 Year Ago and Saw a Physician in the Last Year) 

Advised by Doctor to Quit Smoking 

Current Smokers Who All Current Smokers (Including Those 

Saw Doctor in Last Year Who Did Not See Doctor in Last Year) 

Advised within Pop. Samp. Pop. Samp. 

Last Year Size Size Advised Ever Size Size 

% ± CI (N) (n) % ± CI (N) (n) 

Total 

Gender 

Male 

Female 

Age (Years) 

25–44 

45–64 

65+ 

Race/Ethnicity 

54.7 0.8 19,630,620 25,155 61.5 0.6 27,112,558 34,450 

53.9 1.1 9,381,308 10,761 56.9 0.9 14,338,239 16,382 

55.5 1.0 10,249,312 14,394 66.6 0.9 12,774,319 18,068 

51.4 1.0 11,226,836 14,138 57.7 0.8 16,047,944 20,004 

59.4 1.3 6,338,781 8,195 66.8 1.1 8,620,121 11,086 

58.5 2.3 2,065,003 2,822 67.3 2.0 2,444,493 3,360 

Non-Hispanic White 55.5 0.8 16,165,195 21,639 63.8 0.7 22,112,500 29,502 

Hispanic 51.1 4.9 871,213 764 47.7 4.0 1,354,387 1,172 

African-American 49.9 2.3 2,130,272 2,067 50.9 2.0 2,947,187 2,788 

Asian/PI 60.7 6.7 248,080 330 54.3 5.3 416,868 512 

Native American 53.8 7.5 206,805 342 61.8 6.4 269,919 459 

Other . . 9,055 13 . . 11,697 

Education (Years) 

<12 56.3 1.7 4,088,973 5,077 58.5 1.4 5,867,024 7,181 

12 53.1 1.2 8,465,219 11,087 59.4 1.0 11,918,478 15,506 

13–15 54.5 1.5 4,955,501 6,347 65.0 1.3 6,499,453 8,290 

16+ 58.7 2.3 2,120,927 2,644 68.2 1.9 2,827,603 3,473 

Cigarettes per Day 

1–4 43.3 4.9 467,277 569 46.4 4.2 646,372 743 

5–14 49.8 1.6 4,480,652 5,540 55.8 1.4 5,956,525 7,301 

15–24 54.9 1.1 9,721,488 12,677 62.1 0.9 13,365,158 17,354 

25+ 60.0 1.5 4,961,202 6,369 66.4 1.2 7,144,503 9,052 

Household Income (Dollars) 

<10,000 55.3 1.8 3,396,384 4,303 57.8 1.5 4,783,781 5,979 

10,000–19,999 52.4 1.7 3,980,854 5,282 57.6 1.4 5,848,297 7,630 

20,000–29,999 53.3 1.8 3,685,840 4,740 60.6 1.5 5,134,816 6,566 

30,000–49,999 55.2 1.5 5,047,152 6,472 63.4 1.2 6,843,463 8,735 

50,000–74,999 56.9 2.1 2,464,475 3,076 68.0 1.8 3,179,898 3,940 

75,000 + 58.9 3.2 1,055,915 1,282 69.7 2.7 1,322,303 1,600 

By State 

Alabama 53.3 6.6 352,618 371 59.4 5.6 476,460 498 

Alaska 53.5 6.9 36,363 304 53.6 5.3 60,870 468 

Arizona 54.4 6.6 272,862 247 66.6 5.3 384,055 334 

Arkansas 44.3 6.3 220,617 405 57.0 5.2 321,249 567 

California 56.4 2.9 1,671,505 1,275 62.2 2.4 2,294,715 1,723 

136


17 
Chapter 4 

Table 4-2a (continued) 

Advised by Doctor to Quit Smoking 

Current Smokers Who All Current Smokers (Including Those 

Saw Doctor in Last Year Who Did Not See Doctor in Last Year) 

Advised within Pop. Samp. Pop. Samp. 

Last Year Size Size Advised Ever Size Size 

% ± CI (N) (n) % ± CI (N) (n) 

Colorado 54.8 6.8 280,054 322 63.6 5.7 369,239 420 

Connecticut 64.8 6.6 280,356 264 69.8 5.6 366,233 343 

Delaware 67.5 6.2 59,948 211 70.5 5.2 80,090 284 

District of Columbia 53.7 8.3 37,600 150 57.0 7.3 48,097 190 

Florida


Georgia


Hawaii


Idaho


Illinois


Indiana


Iowa


Kansas


Kentucky


Louisiana


Maine


Maryland


Massachusetts


Michigan


Minnesota


Mississippi


Missouri


Montana


Nebraska


Nevada


New Hampshire


New Jersey


New Mexico


New York


North Carolina


North Dakota


Ohio


Oklahoma


Oregon


Pennsylvania


Rhode Island


South Carolina


South Dakota


Tennessee


Texas


Utah


52.3 3.1 1,080,141 1,101 60.0 2.5 1,512,187 1,515 

57.3 6.3 537,762 278 60.2 5.2 765,068 395 

62.5 6.8 78,484 194 72.0 5.5 102,581 251 

49.7 6.4 78,591 336 58.6 5.2 114,059 486 

54.1 3.6 817,274 898 59.2 3.0 1,169,281 1,266 

54.2 6.3 488,551 337 63.5 5.3 643,568 432 

56.0 6.5 215,431 381 58.7 5.4 307,484 543 

46.6 6.0 214,808 411 58.5 5.2 286,841 541 

48.1 5.7 403,600 406 51.4 4.7 601,593 599 

49.0 6.9 331,114 266 54.1 5.8 457,409 370 

57.9 5.7 128,319 360 65.3 4.6 181,243 503 

62.6 6.3 409,321 256 67.9 5.2 549,267 342 

61.8 3.3 472,564 916 67.9 2.8 620,611 1,194 

56.6 3.1 854,047 1,241 64.4 2.6 1,183,763 1,704 

55.8 6.5 364,871 341 65.6 5.3 489,873 454 

47.3 6.7 213,835 392 53.5 5.6 303,055 545 

55.5 6.3 457,069 370 57.5 5.3 639,137 509 

54.5 6.8 61,175 360 62.9 5.5 87,186 505 

45.2 6.8 101,985 324 56.8 5.7 146,246 454 

52.7 5.9 123,239 342 55.9 4.7 187,585 513 

56.3 7.0 90,836 207 68.7 5.7 123,012 276 

54.5 3.6 511,973 810 63.1 3.0 695,800 1,089 

46.1 6.9 106,412 262 55.9 5.6 157,322 381 

58.4 2.7 1,250,852 1,434 63.9 2.2 1,679,636 1,908 

50.3 3.0 618,572 1,220 56.4 2.6 845,241 1,648 

47.3 6.8 43,955 329 61.1 5.7 60,764 455 

53.8 3.1 960,316 1,267 60.2 2.6 1,349,921 1,762 

51.2 6.1 291,434 387 61.1 5.1 394,828 516 

59.5 7.1 217,078 275 65.4 5.6 319,448 396 

56.2 3.2 972,134 1,167 62.0 2.7 1,317,262 1,573 

58.9 7.0 76,052 216 62.9 5.9 103,363 292 

52.6 5.9 294,520 368 55.8 4.9 418,887 511 

52.8 6.4 50,703 373 64.8 5.2 68,680 507 

52.6 5.7 490,221 426 59.3 4.8 669,209 570 

50.9 3.6 1,229,339 1,039 58.0 3.0 1,761,601 1,481 

50.8 8.2 80,470 186 62.1 6.6 114,801 261 

137

Smoking and Tobacco Control Monograph No. 12 

Table 4-2a (continued) 

Advised by Doctor to Quit Smoking 

Current Smokers Who All Current Smokers (Including Those 

Saw Doctor in Last Year Who Did Not See Doctor in Last Year) 

Advised within Pop. Samp. Pop. Samp. 

Last Year Size Size Advised Ever Size Size 

% ± CI (N) (n) % ± CI (N) (n) 

Vermont 59.7 6.4 53,801 242 64.5 5.3 73,440 324 

Virginia 58.2 5.4 564,504 414 65.7 4.6 738,659 532 

Washington 57.5 6.0 460,778 335 74.2 4.7 576,018 412 

West Virginia 53.5 5.7 204,358 465 57.7 4.8 280,174 636 

Wisconsin 53.5 6.4 379,021 417 63.6 5.1 559,828 611 

Wyoming 58.1 7.2 39,185 257 67.7 5.7 55,621 361 

Note: CI = 95% confidence interval; “.” = insufficient data. 

138

Chapter 4 

Table 4-2b 

CPS 1995/96—Who Received Physicians' Advice (Current Smokers 25+ Years of Age who were 

Daily Smokers 1 Year Ago and Saw a Physician in the Last Year) 

Advised by Doctor to Quit Smoking 

Current Smokers Who All Current Smokers (Including Those 

Saw Doctor in Last Year Who Did Not See Doctor in Last Year) 

Advised within Pop. Samp. Pop. Samp. 

Last Year Size Size Advised Ever Size Size 

% ± CI (N) (n) % ± CI (N) (n) 

Total 

Gender 

Male 

Female 

Age (Years) 

25–44 

45–64 

65+ 

Race/Ethnicity 

59.2 0.8 20,501,925 21,147 65.8 0.6 28,261,736 28,771 

57.7 1.1 9,736,220 8,823 60.6 0.9 14,867,079 13,427 

60.5 1.1 10,765,705 12,324 71.6 0.9 13,394,657 15,344 

55.9 1.1 11,278,521 11,354 62.1 0.9 16,286,194 16,137 

63 1.3 7,174,430 7,468 70.6 1.1 9,521,098 9,854 

63.7 2.4 2,048,974 2,325 71.6 2.1 2,454,444 2,780 

Non-Hispanic White 60.3 0.9 16,869,070 18,124 68.6 0.7 22,876,535 24,441 

Hispanic 53 5.1 922,541 715 48.6 4 1,499,043 1,128 

African-American 53.9 2.5 2,146,619 1,744 55.4 2.1 3,019,621 2,339 

Asian/PI 57.6 6.5 307,782 278 52.4 5.1 512,109 440 

Native American 57.9 7.1 255,914 286 65.2 5.8 354,427 423 

Education (Years) 

<12 59.8 1.8 3,889,887 3,906 61.4 1.5 5,678,909 5,561 

12 58.2 1.2 8,745,200 9,108 64.7 1 12,222,380 12,606 

13–15 59.7 1.5 5,515,483 5,725 69.3 1.2 7,304,957 7,517 

16+ 60.9 2.3 2,351,356 2,408 69.9 1.9 3,055,491 3,087 

Cigarettes per Day 

1–4 46.1 4.9 540,665 534 48.6 4.2 735,301 695 

5–14 54.6 1.6 4,807,801 4,887 60.6 1.4 6,406,319 6,407 

15–24 58.8 1.1 10,077,733 10,499 66.2 0.9 13,916,785 14,326 

25+ 65.8 1.5 5,075,726 5,227 71.4 1.2 7,203,331 7,343 

Household Income (Dollars) 

<10,000 61 2 3,042,358 3,139 62.8 1.7 4,233,242 4,278 

10,000–19,999 58.1 1.8 3,771,029 3,964 62.2 1.5 5,500,596 5,655 

20,000–29,999 57.6 1.8 3,731,948 3,897 63.9 1.5 5,361,238 5,486 

30,000–49,999 58.7 1.5 5,412,723 5,625 66.3 1.3 7,327,333 7,550 

50,000–74,999 60.4 2 2,981,838 3,004 71.8 1.6 3,863,464 3,897 

75,000 + 61.5 2.8 1,562,029 1,518 73.9 2.2 1,975,863 1,905 

By State 

Alabama 56.8 6.4 340,690 305 61.4 5.4 469,368 414 

Alaska 62.7 6.2 46,316 198 65.9 5.1 67,767 287 

Arizona 54.5 6.7 288,696 293 65.3 5.3 418,367 418 

Arkansas 49.9 6.2 214,149 300 60.3 5 321,117 441 

California 61.4 3.1 1,673,921 1,029 66.9 2.5 2,397,307 1,463 

139

Smoking and Tobacco Control Monograph No. 12 

Table 4-2b (continued) 

Advised by Doctor to Quit Smoking 

Current Smokers Who All Current Smokers (Including Those 

Saw Doctor in Last Year Who Did Not See Doctor in Last Year) 

Advised within Pop. Samp. Pop. Samp. 

Last Year Size Size Advised Ever Size Size 

% ± CI (N) (n) % ± CI (N) (n) 

Colorado 62 6.4 295,562 311 69.2 5.3 382,076 393 

Connecticut 66.2 6.6 271,134 200 76.2 5.3 337,897 245 

Delaware 58.7 6.3 66,015 244 64.2 5.4 83,984 309 

District of Columbia 51.1 7.3 43,672 203 66.2 6.3 52,512 239 

Florida


Georgia


Hawaii


Idaho


Illinois


Indiana


Iowa


Kansas


Kentucky


Louisiana


Maine


Maryland


Massachusetts


Michigan


Minnesota


Mississippi


Missouri


Montana


Nebraska


Nevada


New Hampshire


New Jersey


New Mexico


New York


North Carolina


North Dakota


Ohio


Oklahoma


Oregon


Pennsylvania


Rhode Island


South Carolina


South Dakota


Tennessee


Texas


Utah


57.9 3.3 1,066,392 877 61.6 2.7 1,555,314 1,244 

55.5 6.3 496,628 301 59.4 5.2 723,657 428 

64.2 6.9 86,935 163 68.9 5.9 111,134 208 

62.1 6.5 79,583 281 69.4 5.1 115,450 402 

59.1 3.6 944,323 878 63.5 2.9 1,341,309 1,211 

56.1 5.6 601,058 371 64.8 4.7 802,909 494 

57.8 6.3 237,604 312 68 5.2 311,972 408 

55.1 6.3 221,783 331 67.1 5.1 299,636 440 

56.9 5.2 457,874 387 66.7 4.3 605,785 512 

54 6.5 318,972 242 59.9 5.3 465,292 343 

67.2 5.9 116,971 275 74.4 4.6 168,770 394 

64.1 6.5 396,517 235 77.9 5 491,520 290 

66.3 4.1 462,298 538 70.5 3.4 606,617 694 

64 3.4 862,118 906 69.2 2.8 1,150,884 1,196 

59.9 6.4 367,772 328 73.3 5 488,620 430 

50.1 6.7 199,585 238 54.4 5.4 299,663 350 

53.9 6.2 474,933 316 65 4.9 693,826 451 

57.8 6.3 70,104 327 69.2 4.8 104,079 477 

54 6.5 123,342 293 63.2 5.5 163,531 382 

59.5 5.9 143,846 272 57.9 4.8 227,701 414 

70.8 6.1 104,853 240 77.1 4.9 140,290 316 

58.7 4 562,267 601 64.3 3.3 754,241 790 

63.7 6.2 123,751 282 66.2 5.1 174,629 393 

62.2 2.8 1,275,860 1,135 65.8 2.4 1,660,597 1,468 

60 4 656,409 785 65.2 3.3 914,716 1,082 

50.4 7 44,662 279 61.2 5.5 67,502 414 

58.4 3.4 1,023,708 986 65.3 2.8 1,393,787 1,326 

53.4 6 292,183 390 64.6 4.8 409,168 535 

56.8 6.8 240,543 254 70.1 5.4 328,361 343 

62.6 3.2 1,066,331 1,063 68.1 2.7 1,395,358 1,377 

76.4 5.3 98,514 249 75.1 4.9 122,217 306 

54.4 6 336,467 262 60.4 5.1 456,079 352 

52.7 6.6 49,533 285 61.3 5.3 74,318 431 

57.3 5.5 537,979 342 68.2 4.5 716,126 446 

55.4 3.5 1,319,024 897 60.4 2.9 1,916,107 1,269 

56.9 8.2 84,733 169 72.9 6.2 118,589 234 

140

Chapter 4 

Table 4-2b (continued) 

Advised by Doctor to Quit Smoking 

Current Smokers Who All Current Smokers (Including Those 

Saw Doctor in Last Year Who Did Not See Doctor in Last Year) 

Advised within Pop. Samp. Pop. Samp. 

Last Year Size Size Advised Ever Size Size 

% ± CI (N) (n) % ± CI (N) (n) 

Vermont 65 6.1 56,914 274 74.3 4.9 74,293 355 

Virginia 56 5.8 570,775 372 64 4.8 783,004 500 

Washington 62.2 6.7 417,863 261 72.3 5.4 557,968 346 

West Virginia 68.3 5 195,029 417 72.1 4.1 269,846 573 

Wisconsin 58.9 6.2 438,829 358 69.3 4.9 620,298 499 

Wyoming 56.5 6.9 36,903 292 62.3 5.5 56,178 439 

Note: CI = 95% confidence interval. 

0.6 percent of all smokers (including those who had not seen a physician in 

the last year) reported ever being told by a physician to quit smoking in the 

1995/96 CPS. Also in the 1995/96 CPS, Massachusetts was significantly 

higher than the national norm with 66.3 ± 4.1 percent of daily smokers 

over age 25 who had seen a physician in the last year reporting physician 

advice to quit within the last year, an increase from 61.8 ± 3.3 percent in 

1992/93 CPS. However, California was not significantly different from other 

states in either survey. 

Reports of tobacco advice in the previous year from patients seeing dentists also increased, from 21.9 ± 0.7 percent in 1992/93 to 26.5 ± 0.8 percent 

in 1995/96, and the ever-advised rate (including smokers without dental 

visits) rose from 19.4 ± 0.5 percent to 23.0 ± 0.6 percent. 

Multivariate logistic regression analyses of the determinants of who 

received advice to quit smoking among those daily smokers who saw a 

physician in the last year (Table 4-3) reveal that women and older smokers 

were more likely to receive physician advice to quit smoking, as were smokers of higher number of cigarettes per day. African-American smokers were 

less likely to receive physician advice to quit. Level of education and household income did not influence the likelihood of receiving physician advice 

to quit smoking once their effect on likelihood of seeing a physician was 

taken into account by limiting the analyses to those who had visited a 

physician in the last year. 

The CPS did not ask former smokers whether they had received advice 

to quit smoking from a physician in the last year, but the 1996 California 

Tobacco Survey (CTS) did. The characteristics that predicted who would 

receive physician advice to quit were similar in both the CPS and CTS. 

Measures of cessation activity and success were estimated for those who had 

been daily smokers 1 year prior to the survey for the 1996 CTS (Table 4-4). 

Those estimates show 50.0 ± 2.54 percent of those current daily smokers 

who were advised to quit smoking by their physician made an attempt to 

141

Smoking and Tobacco Control Monograph No. 12 

quit, in comparison to 41.2 ± 3.4 percent of those smokers who did not 

report receiving physician advice to quit. However, the percentages of daily 

smokers 1 year prior to the survey who were former smokers, or former 

smokers of 3+ months duration, were almost identical for those who did 

and did not report receiving advice to quit. Table 4-5 presents the results of 

a multivariate logistic regression analysis of the cessation measures from the 

1996 CTS with report of advice to quit by a physician in the last year 

included as a term in the analysis. Daily smokers who received physician 

advice to quit were 1.5 times more likely to make some change in their 

smoking behavior and 1.6 times more likely to make a cessation attempt, 

but they were no more likely to be a former smoker at the time of the survey (OR = 1.0) or to have quit for 3 or more months at the time of the survey (OR = 0.91). These associations may reflect both the benefits of clinician intervention and a tendency for clinicians to raise the issue with more 

motivated patients. Similar results were obtained for a multivariate logistic 

regression of the CPS data controlling for any cessation activity or cessation 

attempts, but no data on cessation success were available because former 

smokers were not asked whether they had received advice to quit. 

The data suggest that physicians are effective motivators for cessation 

activity; but that physician advice alone, at least as it is currently being 

practiced in the United States, does not have a substantive effect on the 

likelihood of population-level cessation success. This observation is in contrast to a substantial number of well-controlled clinical trials of physician 

intervention that have demonstrated a modest effect on long-term smoking 

cessation rates, an effect that was significant both statistically and in terms 

of public health. The difference may reflect the quality of the advice provided in these two settings. In research settings, even minimal intervention 

approaches are provided in a structured way and commonly include components designed to enhance longer term success. In the real-world setting 

surveyed by the CTS, physician intervention may be more frequently limited to simple advice to quit without any offers of assistance or follow-up. 

Even in the absence of an intervention sufficient to influence long-term 

cessation rates, physician advice to quit smoking does increase cessation 

activity by 50 to 60 percent, demonstrating the potential of physician 

advice as a tobacco control intervention channel. The gap represented by 

the absence of an effect on long-term cessation in the CTS data and the 

clear demonstration of a long term-effect in clinical trials define what is 

achievable if the AHRQ clinical practice guidelines were implemented for 

those patients who are currently receiving advice to quit. 

Effects of current practice How many smokers might be influenced to quit 

patterns on cessation rates each year if the clinical practice guidelines were 

in the United States implemented? We assumed that 35 million smokers, 

or 70 percent of the roughly 50 million U.S. smokers, see a physician each 

year, and that 3 percent (Hughes et al., 1992) of these smokers (1,050,000) 

will become long-term quitters each year without clinician intervention. 

We further assumed that 60 percent of smokers seen by clinicians each year 

receive minimal advice (i.e., <3 minutes), and very few receive more extensive intervention and assistance. 

142

Chapter 4 

Table 4-3 

CPS 1992/93 and 1995/96—Multivariate Logistic Regressions of who Received Physicians' 

Advice (Current Smokers 25+ Years of Age who were Daily Smokers 1 Year Ago and Saw a 

Physician in the Last Year) 

1992/93 1995/96 

Variable OR 95% CI OR 95% CI 

Gender 

Male 

Female 

Age (Years) 

25–44 

45–64 

65+ 

Race/Ethnicity 

Non-Hispanic White 

Hispanic 

African-American 

Other 

Education (Years) 

<12 

12 

13–15 

16+ 

1.00 

1.14 

1.00 

1.34 

1.40 

1.00 

0.96 

0.91 

1.18 

1.00 

0.90 

0.96 

1.11 

Household Income (Dollars) 

<10,000 1.00 

10,000–19,999 0.89 

20,000–29,999 0.93 

30,000–49,999 1.00 

50,000–74,999 1.05 

75,000+ 1.05 

Cigarettes Smoked per Day 

1–4 1.00 

5–14 1.33 

15–24 1.65 

25+ 2.04 

1.00 

(1.09 - 1.20) 1.19 (1.13 - 1.26) 

1.00 

(1.27 - 1.42) 1.31 (1.23 - 1.39) 

(1.28 - 1.52) 1.44 (1.31 - 1.59) 

1.00 

(0.85 - 1.09) 0.88 (0.77 - 1.01) 

(0.84 - 0.99) 0.86 (0.78 - 0.94) 

(1.00 - 1.40) 0.99 (0.84 - 1.17) 

1.00 

(0.84 - 0.96) 0.98 (0.90 - 1.06) 

(0.89 - 1.04) 1.06 (0.97 - 1.16) 

(1.00 - 1.23) 1.10 (0.98 - 1.23) 

1.00 

(0.82 - 0.96) 0.87 (0.79 - 0.96) 

(0.85 - 1.01) 0.85 (0.77 - 0.94) 

(0.92 - 1.09) 0.89 (0.81 - 0.98) 

(0.95 - 1.16) 0.94 (0.85 - 1.05) 

(0.92 - 1.20) 0.95 (0.83 - 1.09) 

1.00 

(1.12 - 1.58) 1.43 (1.19 - 1.70) 

(1.39 - 1.95) 1.69 (1.42 - 2.01) 

(1.71 - 2.42) 2.31 (1.93 - 2.77) 

An AHRQ meta-analysis found that minimal advice of 1-3 minutes 

yields a 30 percent increase in the spontaneous quit rate. With current practice patterns (Scenario 1, Table 4-6), we estimate that clinicians are responsible for helping an additional 189,000 smokers quit each year. If clinicians 

delivered minimal advice to 90 percent of the smokers they saw at least 

once over the course of a year (Scenario 2, Table 4-7), they would help an 

additional 283,500 smokers quit, over and above the background cessation 

rate. In Scenario 3 (Table 4-8), we assumed that clinicians (or their staff) 

would advise 90 percent of all smokers they saw at least once per year and 

would provide 10 minutes or more of cessation counseling and/or followup to the half who were considering quitting. Nationally, this would yield 

756,000 clinician-generated long-term quitters each year. Thus, providing 

143 
Smoking and Tobacco Control Monograph No. 12 Size (n) 

819 

CTS 1996—Measures of Cessation Activity and Success among Current and Former Smokers 25+ 

Years of Age who were Daily Smokers 

1 Year ago and Saw a Physician in the Last 

Year 

Former Former 3+ Population Sample 

Not Advised
Advised 50.25 2.53 50.03 2.54 3.34 0.87 10.80 1.39 5.57 1.09 1,022,300 2,286


722,315 1,628 

Total 47.25 1.79 46.38 1.75 4.14 0.81 10.88 1.28 5.78 0.99 1,744,616 3,914 

Male
Female 46.72 2.44 45.56 2.40 4.74 1.05 11.01 1.86 5.99 1.28 894,605 2,193


850,010 1,721 

Age 

25–44 52.07 2.71 50.87 2.71 4.87 1.30 11.08 1.44 5.55 1.13 981,419 2,171 

45–64
65+ 40.49 6.15 39.84 5.82 3.70 2.11 14.16 6.08 7.55 4.35 160,583 341


602,613 1,402 

Race/Ethnicity 

Non-Hispanic White 44.63 2.02 43.87 1.98 3.61 0.59 11.23 1.44 5.88 1.00 1,223,967 3,006 

220,963 356 Hispanic


African-American 54.42 7.23 53.32 7.40 5.98 3.90 5.61 3.28 3.97 3.02 140,871 246


Asian/PI
Native American 53.07 10.65 52.62 10.52 3.42 2.76 8.84 4.65 4.60 3.78 71,373 140


87,442 166 

Education (Years) 

<12 49.59 5.43 48.94 5.49 3.39 1.76 9.77 2.95 4.98 2.20 345,937 379 

12
13–15 47.65 2.59 46.65 2.58 5.34 1.39 10.55 2.50 5.08 1.69 527,748 1,335


547,340 1,381 

Size 

(N) 

323,589 8.94 2.37 15.77 2.49 4.98 1.71 50.93 4.02 51.75 3.98 16+ 

6.08 1.43 

5.56 1.29 

5.69 1.60 

6.47 2.71 

6.60 5.31 

5.10 1.23 

% CI 

Months 

11.00 2.01 

10.75 1.70 

9.70 1.74 

12.22 4.30 

12.89 6.10 

9.02 1.64 

% CI % CI 

Occasional3 Smoker 

5.27 1.56 

3.51 1.02 

3.07 1.06 

6.23 2.96 

3.88 3.12 

2.96 0.99 

41.22 3.39 

47.25 2.85 

40.82 2.80 

49.59 12.23 

41.82 3.07 

52.59 6.11 

% CI % CI 

Any Change1 Attempt2 

43.01 3.41 

47.81 2.80 

41.21 2.76 

53.82 6.12 

51.06 12.69 

42.73 3.19 

Physician's Advice 

Table 4-4 

Variable 

Gender 

144

Chapter 4 

Size 

(n) 

390 491 631 

1,044 

733 625 

122 993 

1,822 

977 

Sample Population 

Size 

(N) 

214,655 243,502 287,691 449,586 309,943 239,237 

54,352 

484,224 782,071 423,967 

CI 

2.10 2.21 1.88 1.63 2.66 2.73 

5.21 

2.02 1.23 1.65 

Former 3+ 

Months 

% 

4.83 5.56 4.32 5.06 7.55 7.69 

8.21 

6.43 5.08 6.02 

1Any Change: Includes those who have made a quit attempt, have become occasional smokers, or have become former smokers. 2Attempt: Includes those who have made a quit attempt or have become former smokers (CTS algorithm). 3Occasional: Includes those who reduced from smoking everyday, to smoking some days. Note: CI = 95% confidence interval. 

CI 

2.87 3.32 2.59 2.30 3.24 3.94 

9.50 

2.38 1.62 1.98 

Former 

Smoker 

8.90 

10.43 

9.37 

10.66 

11.40 

14.72 

17.76 

11.83 

9.68 

1

% 

1.15 

1.91 1.85 1.40 1.51 2.10 1.30 

5.54 

1.79 1.00 0.86 

Occasional3 

CI 

3.44 4.57 3.28 4.36 5.66 2.98 

10.76 

% 

6.27 3.51 2.03 

5.44 5.82 4.61 2.99 5.49 6.43 

10.65 

CI 

4.12 2.25 3.60 

Attempt2 

46.25 50.31 44.20 44.66 48.37 45.79 

57.45 

55.86 44.64 37.35 

% 

5.21 5.87 4.54 2.93 5.63 6.57 

10.38 

4.07 2.25 3.54 

Any Change1 

CI 

47.31 50.46 44.67 45.62 49.96 46.62 

59.83 

57.41 45.32 37.61 

% 

Table 4-4 (continued) 

Household Income 

Cigarettes per Day 

10,001–20,000 21,000–30,000 30,001–50,000 50,001–75,000 

Variable 

≤10,000 

75,000+ 

1–4 

5–14 15–24 25+ 

145

Smoking and Tobacco Control Monograph No. 12 0.91 (0.69 , 1.20) 1.15 (0.87 , 1.52) 45–64
 65+ 0.68 (0.53 , 0.85) 0.68 (0.54 , 0.86) 0.98 (0.54 , 1.78) 1.37 (0.98 , 1.92) 1.49 (0.95 , 2.33)
 1.03 (0.76 , 1.40) 

Hispanic 1.18 (0.96 , 1.46) 1.17 (0.95 , 1.44) 1.55 (0.98 , 2.46) 1.17 (0.84 , 1.61) 1.25 (0.81 , 1.91) African-American
Other 1.08 (0.86 , 1.36) 1.08 (0.86 , 1.36) 0.82 (0.45 , 1.50) 0.92 (0.64 , 1.32) 0.92 (0.57 , 1.50)


0.69 (0.38 , 1.27) 

Education (Years) 

<12 1.00 12 0.77 (0.64 , 0.94) 0.77 (0.63 , 0.93) 0.89 (0.52 , 1.51) 0.89 (0.65 , 1.23) 1.00 (0.65 , 1.54) 

1.00 (0.65 , 1.56) 13–15


16+ 1.10 (0.88 , 1.39) 1.10 (0.88 , 1.39) 1.58 (0.90 , 2.80) 1.57 (1.11 , 2.22) 1.71 (1.08 , 2.72)


OR 95% CI 

CTS 1996—Mulitvariate Logistic Regression Analysis of Measures of Cessation Activity and Success among Current and Former 

Smokers 25+ 

Years of Age who were Daily Smokers 1 

Year Ago and Saw a Physician in the Last 

Year 

Former Former 3+ 

Months 

1.00 (0.81 , 1.23) 

1.07 (0.87 , 1.32) 0.85 (0.68 , 1.07) 0.48 (0.29 , 0.79) 1.09 (0.79 , 1.50) 

OR 95% CI 

Occasional3 Smoker 

0.67 (0.49 , 0.93) 

1.33 (0.95 , 1.85) 0.74 (0.51 , 1.08) 1.35 (0.79 , 2.31) 1.67 (1.01 , 2.75) 

OR 95% CI 

1.60 (1.40 , 1.83) 

0.87 (0.76 , 1.00) 0.70 (0.60 , 0.80) 1.18 (0.92 , 1.51) 0.92 (0.76 , 1.12) 

OR 95% CI 

Any Change1 Attempt2 

1.50 (1.31 , 1.71) 

0.90 (0.78 , 1.02) 0.68 (0.59 , 0.79) 1.18 (0.93 , 1.52) 0.93 (0.77 , 1.14) 

OR 95% CI 

Physician's Advice 

Not Advised 1.00 

1.00 1.00 

Race/Ethnicity 

Non-Hispanic White 1.00 

Table 4-5 Variable 

Advised 

Gender 

Male Female 

Age 

25–44 

146

Chapter 4 

95% CI 

(0.62 , 1.92) (0.47 , 1.50) (0.58 , 1.66) (0.88 , 2.58) (0.78 , 2.43) 

(0.44 , 1.79) (0.34 , 1.38) (0.40 , 1.75) 

Former 3+ 

Months 

OR 

1.10 0.84 0.98 1.51 1.37 

0.89 0.68 0.84 

95% CI 

(0.73 , 1.80) (0.65 , 1.50) (0.75 , 1.63) (0.79 , 1.81) (0.96 , 2.25) 

(0.41 , 1.13) (0.31 , 0.87) (0.37 , 1.07) 

Former 

Smoker 

1.10.99 1.10 1.19 1.47 

0.68 0.52 0.63 

1 

OR 

1Any Change: Includes those who have made a quit attempt, have become occasional smokers, or have become former smokers. 2Attempt: Includes those who have made a quit attempt or have become former smokers (CTS algorithm). 3Occasional: Includes those who reduced from smoking everyday, to smoking some days. 

95% CI 

(0.76 , 2.78) (0.48 , 1.84) (0.73 , 2.48) (0.88 , 3.10) (0.42 , 1.89) 

(0.35 , 1.25) (0.20 , 0.76) (0.12 , 0.58) 

Occasional3 

OR 

1.45 0.94 1.34 1.65 0.89 

0.66 0.39 0.27 

95% CI 

(0.95 , 1.58) (0.72 , 1.18) (0.73 , 1.16) (0.81 , 1.34) (0.74 , 1.28) 

(0.64 , 1.40) (0.42 , 0.91) (0.31 , 0.69) 

Attempt2 

OR 

1.23 0.92 0.92 1.05 0.98 

0.95 0.62 0.46 

95% CI 

(0.92 , 1.53) (0.70 , 1.15) (0.73 , 1.16) (0.84 , 1.38) (0.74 , 1.28) 

(0.62 , 1.36) (0.40 , 0.87) (0.29 , 0.65) 

Any Change1 

1.00 1.19 0.90 0.92 1.07 0.98 

1.00 0.92 0.59 0.44 

Household Income (Dollars) 

OR 

Table 4-5 (continued) Cigarettes per Day 

10,001–20,000 21,000–30,000 30,001–50,000 50,001–75,000 

Variable 

≤10,000 

75,000+ 

1–4 5–14 

15–24 

25+ 

147

Smoking and Tobacco Control Monograph No. 12 

Table 4-6 

Scenario 1: Additional Quitters per Year with a 60% Minimal Advice Rate 

60% receive simple advice to quit 21,000,000 

Effect of minimal advice on probability of cessation 1.3 

Expected quits for those with minimal advice


(21,000,000 x 0.03 x 1.2) 819,000


Expected spontaneous quits without advice


(21,000,000 x 0.03) 630,000


Expected increase in quits due to current practice


(756,000 – 630,00) 189,000


Table 4-7 

Scenario 2: Additional Quitters per Year with a 90% Minimal Advice Rate 

90% receive simple advice to quit 31,500,000 

Effect of minimal advice on probability of cessation 1.3 

Expected quits for those with minimal advice


(31,500,000 x 0.03 x 1.2) 1,228,500


Expected spontaneous quits without advice


(31,500,000 x 0.03) 945,000


Expected increase in quits with 90% advice rate


(1,134,000 – 945,000) 283,500


Table 4-8 

Scenario 3: Additional Quitters per Year with 90% Minimal Advice Plus 10 Minutes of 

Counseling for 50% who Are Planning to Quit 

45% receive simple advice to quit 15,750,000 

Effect of minimal advice on probability of cessation 1.3 

45% receive 10 minutes or more of cessation counseling 15,750,000 

Effect of counseling on probability of cessation 2.3 

Expected quits for those with minimal advice


(15,750,000 x 0.03 x 1.3) 614,250


Expected quits for those with counseling 


(15,750,000 x 0.03 x 2.3) 1,086,750


Total expected quits for advised plus counseled patients 1,701,000


Expected spontaneous quits without advice


(31,500,000 x 0.03) 945,000


Expected increase in clinician-generated quits


(1,701,000 – 945,000) 756,000


148

Chapter 4 

brief cessation assistance to interested patients, rather than just simple 

advice, would increase the number of long-term quitters that can be attributed to clinicians’ efforts from 189,000 per year currently to 756,000 per 

year—a 4-fold increase. 

Implications for While cessation advice rates have increased substantially 

practice and policy over the last 20 years, progress of physicians and dentists 

toward implementing the AHRQ guidelines or toward achieving the 

Healthy People Year 2010 objectives regarding tobacco services remains 

slow. Given multiple contacts with most patients each year, this tobacco 

control channel remains one where the potential effect outweighs the 

achieved effect. Currently, even when smokers are advised to quit, they are 

unlikely to receive meaningful cessation assistance in the form of self-help 

materials, encouragement to set a quit date, follow-up support, or pharmacotherapy; so improvement in the effectiveness of current physician-delivered cessation assistance is likely to be more important than increasing the 

frequency of physician-delivered advice. 

Simply offering minimal, but effective, advice to 90 percent, rather than 

60 percent, of smokers each year would increase the number of cliniciangenerated quitters to 283,500 per year. What would make a far greater difference, however, would be for clinicians and their staff to provide cessation 

assistance to the half of smokers who are considering quitting. Assistance 

goes beyond simple advice. It also includes brief discussion of quitting 

strategies and how to overcome barriers, encouragement to set a quit date, 

referral options, NRT, and follow-up support. Office staff, with the help of 

videos and other tools, can help clinicians offer this type of brief (10 minutes) support within an organized office system. Assistance of this sort, if 

delivered routinely to interested smokers, could increase clinician-generated 

quitters four-fold to 756,000 per year. Implementing this type of intervention should be a high priority for all routine care settings. 

What does it take to Altering the practice patterns of busy clinicians is 

improve tobacco counsel- never easy, but the problems appear to be particularly 

ing during routine care? acute when it comes to tobacco-control efforts. Most 

of the studies showing positive effects on practice patterns and patient quit 

rates have been conducted in smaller groups of willing clinicians who are 

participating in a short-term study. Usually, the researchers provide highquality training, careful monitoring, and often external support (e.g., 

research assistants) that are rarely available in real-world practice. Under 

these relatively ideal conditions, patients do indeed receive more and better 

services, which translates to improved cessation outcomes. As the research 

team leaves, however, or as others disseminate the intervention in new settings, compliance drops dramatically (Kottke et al., 1989; Solberg, 1996; 

Solberg et al., 1996). 

The problem may be that dissemination efforts for proven clinical interventions are inadequate. The most common implementation strategies 

include distributing clinical practice guidelines and offering continuing 

medical education (CME). In isolation, however, these approaches have little lasting effect on tobacco intervention practices or on other clinical 

149

Smoking and Tobacco Control Monograph No. 12 

improvement targets. Changes in practice patterns, if they occur at all, tend 

to fade quickly as initial enthusiasm succumbs to the crush of patient-care 

demands, competing new initiatives, and administrative burdens. 

Realistically, changing routine clinical practice requires both an office 

systems approach to delivering care, and a sustained organizational commitment to maintaining long-term success (Kottke et al., 1990; Elford et al., 

1994; Fiore et al., 1997 & 2000; Hollis et al., 1993; Leininger et al., 1996; 

Lichtenstein et al., 1996a; McAfee et al., 1998; Solberg et al., 1990 & 1997; 

Ockene et al., 1997a). An office systems approach includes the following 

elements: 1) a system for identifying and documenting smokers; 2) clinician 

prompts to deliver advice; 3) a means to provide assistance to smokers 

interested in quitting (e.g., support staff); 4) appropriate training for clinicians and support staff; 5) a convenient way for staff to document the 

delivery of tobacco interventions; 6) clear performance objectives for all 

staff members; and 7) a mechanism for regular performance reporting at 

the individual, team, and organizational levels. Preferably, tobacco intervention quality measures should be tied to annual performance reviews and 

other incentive mechanisms. 

Involving support staff appears essential, both to prompt clinicians to 

advise and to reduce demands on clinicians struggling with 10-minute 

encounters. For example, having staff document smoking status in the 

chart note has been shown to double the rate of smokers reporting that 

they received advice (Fiore et al., 1995). Cohen et al. (1989) found that 

chart reminders increased advice rates from 41 percent to 75 percent and 1-

year patient quit rates from 1.5 percent to 7.9 percent, though maintaining 

staff documentation efforts over time can be challenging (Cummings et al., 

1989). Defining specific roles for support staff (e.g., assessing smoking and 

prompting clinicians), for clinicians (e.g., advising and staging), and for 

nurses (e.g., assisting smokers) nearly doubles the long-term quit rate over 

brief clinician advice alone (Hollis et al., 1993). Telephone outreach systems 

can provide effective assistance and follow-up to patients ready to take 

action on smoking (Lichtenstein et al., 1996b; McAfee et al., 1998). 

Of course, it is much easier to identify the components of a good systems approach than to actually incorporate them into real-world clinical 

settings. Berwick (1992) provides a model for how to conceptualize the clinical quality improvement process, but these ideas have not been systematically applied to tobacco intervention. Organized health care systems, particularly staff-model HMOs, would seem to have both the incentive and the 

tools to achieve systematic and lasting changes in the policies, norms, and 

practices of clinicians. First, they have a vested interest in reducing tobacco 

use and tobacco-related disease in their members and in doing well on 

quality performance measures (e.g., HEDIS 3.0). As patients, employer 

groups, and purchasers intensify calls for action, the incentive for organizational change efforts will also increase. HMOs also have the ability to define 

system-level policies, norms, and targets; to monitor performance; and to 

provide feedback and incentives to staff. Indeed, many health care systems 

are considering or piloting approaches for systematically implementing the 

150 
Chapter 4 

Four A’s—Ask, Advise, Assist, and Arrange. Success will depend on whether 

their organizational change efforts include the following components: 

• Maintainance of a tobacco-services taskforce with high level 

stakeholders 

• Adoption of performance quality targets for the delivery of 

tobacco advice and assistance 

• Creation of an office system with explicit accountabilities for 

staff 

• Development of convenient documentation procedures 

• Measurement of performance and providing feedback to teams 

across the entire organization 

• Recognition of performance and celebration of progress 

The underlying challenge for most preventive interventions, particularly behavioral interventions requiring education and problem solving rather 

than tests, drugs, or surgery, is that they fall outside the traditional medical 

paradigm (Vogt et al., 1998). Overcoming this last barrier will require a reevaluation of the role of clinicians and health care systems. In short, we 

need to move from a health care delivery model, in which we primarily 

diagnose and treat presenting complaints, toward a public health model 

(Greenlick, 1995) with the objective of maintaining optimal health in a 

defined population. 

SUMMARY The frequency with which smokers in the United States report receiving physician advice to quit smoking has increased substantially over the 

last 20 years, and in the 1995/96 CPS, approximately 60 percent of current 

daily smokers reported receiving advice to quit smoking from their physician in the last year. Older smokers and smokers of higher numbers of cigarettes per day are more likely to receive physician advice to quit smoking, 

and African-American smokers are slightly less likely to receive physician 

advice to quit. 

Studies in research settings have demonstrated that minimal interventions by physicians and dentists can increase cessation attempt rates and 

long-term cessation success as well. Data from the most recent CPS suggest 

that physician advice to quit, as it is currently being delivered in the United 

States, increases cessation attempts but does not improve long-term cessation success rates. 

Successful dissemination and implementation of the AHRQ clinical 

practice guidelines could increase the number of smokers who quit by 

increasing the frequency with which smokers are advised to quit, but a 

more effective approach might be to increase the effectiveness of interventions already provided by the physician or dentist. Enhancing the quality of 

the intervention provided, focusing on those smokers who are ready to 

quit, and implementing changes in the care delivery system that promote 

and support physician-based cessation interventions are all methods by 

which physician- and dentist-based cessation interventions can be 

enhanced as a tobacco control channel. 

151

Smoking and Tobacco Control Monograph No. 12 

The substantial effect of physician advice on cessation attempts, with 

minimal or absent effects on long-term cessation rates, also suggests that 

strategies to improve the frequency with which physicians advise their 

patients should be coupled with other tobacco control channels that 

improve cessation success among those who make a quit attempt. Programs 

that link physician advice to quit with telephone counseling or other 

proven cessation modalities may create synergies across these separate 

tobacco-control intervention channels. 

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94(5):266-272, 1995. 

154

Impact of Medications on 

Smoking Cessation 

John R. Hughes, David M. Burns 

OVERVIEW The proven pharmacotherapies for smoking cessation are nicotine 

gum, inhaler, nasal spray, and patch (Hughes, 1996; Hughes et al., 1999) 

and the non-nicotine therapies bupropion (Hughes et al., 1999), and perhaps nortriptyline (Prochazka et al., 1998). All of these methods have been 

shown to double quit rates compared to placebo in several randomized controlled trials (Hughes, 1996). Because the nicotine nasal spray has had limited sales, the inhaler has just been marketed, and nortriptyline has not been 

marketed for cessation, the current analyses will focus on nicotine gum, the 

nicotine patch, and bupropion. Nicotine gum was originally approved in 

the United States as prescription only (Rx) medication in 1984 as a 2 mg 

form, and 4 mg nicotine patches were approved as Rx only in 1993. In 

April 1996, the nicotine gum became available for over-the-counter (OTC) 

sales. Nicotine transdermal patches, which became available as a prescription device in 1992, were approved for OTC sale in 1996. In May of 1997, 

bupropion became available as an Rx-only medication. 

This paper will present two sets of data that estimate the populationbased extent of medication use for smoking cessation. The first data are 

from the 1996 California Tobacco Survey (CTS), a large population-based 

survey of California adults (see Chapter 2). This survey asked all smokers 

over the age of 25 whether they had tried to stop smoking in the last year 

and, if so, whether they had used nicotine gum or patch. The survey was 

conducted from September 1996 through January 1997. Thus, depending 

on when a smoker was surveyed, the gum would have been available OTC 

for 5-10 months prior to the survey, the patches would still have been Rxonly, and bupropion would not have been available yet. 

The second data set is from nationally representative prescription and 

OTC sales data and physician prescribing data obtained in the last 6 

months of 1997 from audits done by, or for, the pharmaceutical companies. 

In this data set, the gum would have been available OTC for 14-20 months, 

two patches would have been available OTC for 10-17 months, and bupropion would have been available Rx-only for 5-10 months. Both sales and 

physician audit allow one to estimate the number of new purchases. 

Writing of this article was supported by a Research Scientist Development Award from the National Institute 

on Drug Abuse (DA 00109). 

155

Smoking and Tobacco Control Monograph No. 12 

To examine population-based efficacy of these medications, this chapter 

will use cessation data among users in the 1996 CTS. In addition, since sales 

data for 1997 do not provide cessation data, we will review Current 

Population Survey (CPS) data (see Chapter 2), meta-analyses (Fiore, 2000) 

and recent scientific studies in prescription (Rx) and over-the-counter 

(OTC) settings (Hughes et al., 1999). 

USE OF MEDICATIONS	 Table 5-1 presents the 1996 CTS data on the use of patch, 

gum, and counseling in various combinations among dif- Nicotine Gum ferent groups. In the 1996 CTS, 45 percent of those over 

and Patch age 25 who were daily smokers 1 year prior to the survey 

reported making a quit attempt that lasted more than 24 hours during the 

prior year. Of those who made a quit attempt, 21 percent reported using 

either patch or gum. Patch and gum use was more common in older, white, 

more educated, and higher income smokers. The 1996 estimates for patch 

and gum use represent a substantial increase from those recorded in a prior 

CTS in 1993, when patch and gum were available only as Rx products. In 

that survey, 47 percent of smokers reported quitting in the prior year, but 

only 10 percent used a patch, and 3 percent used gum (Pierce et al., 1995). 

A different estimate can be derived using national pharmaceutical company sales data. A recent article estimated that in 1997, 5.8 million quit 

attempts were made with OTC gum and patch and 0.5 million were made 

with Rx gum and patch (Gilpin and Pierce, 1994). The number of smokers 

over age 18 nationally was estimated at 47 million in 1995 by the CDC and 

44 million by the CPS (see Chapter 2). If one uses the CDC definition of a 

quit attempt, requiring 24 hours of abstinence, then about 17 million of 

those smokers made a quit attempt in 1995 (see Chapter 2). Assuming that 

the number of smokers and the incidence of quitting have not changed 

between 1995 and 1997 (see Chapter 2), and that smokers do not make 

more than one quit attempt using patch or gum per year, then 36 percent 

of all quits in 1997 involved gum or patch. Since it is likely that smokers 

who are trying to quit may make more than one attempt per year and may 

use patch or gum on one or more of those attempts, it is likely that the 36 

percent figure represents an overestimate of the fraction of quit attempts in 

which patch or gum was utilized. In the 1990 California Tobacco Survey, 

approximately 36 percent of those smokers who made a quit attempt in the 

prior 12 months made more than 1 quit attempt in that 12-month period, 

and some had made as many as 15 attempts each (Gilpin and Pierce, 1994). 

A minimum of 57 percent of the quit attempts occurred among those who 

made more than one attempt. These data would suggest that the ratio 

between the total number of quit attempts and the number of individuals 

who have made a quit attempt in the last year may be approximately 1.5. 

Dividing the number of quit attempts estimated from sales data by this 

ratio would reduce the 36 percent presented above to 24 percent of all quit 

attempts that are accompanied by nicotine patch and gum—a number 

closely matching the estimate from population-based survey data (21 percent; Table 5-1). 

156

Chapter 5


Samp 

Size 

(n) 

2,680 

1,377 

1,303 

1,661 

803 

216 

1,930 

332 

185 

135 

98 

0 

312 

903 

887 

578 

264 

354 

398 

605 

452 

377 

230 

Cessation Methods Reported by Daily Smokers 1 Year prior to the Survey Who Made a Quit Attempt in the Last 12 Months. 1996 CTS* 

Pop 

Size 

(N) 

1,266,663 

707,535 

559,127 

797,986 

365,166 

103,509 

806,518 

224,058 

111,550 

70,309 

54,227 

0 

299,599 

364,834 

359,691 

242,537 

156,924 

187,040 

190,339 

271,517 

200,708 

148,285 

111,848 

0.3 0.5 

0.5 

0.5 

0.4 

0.4 

0.7 

2.3 

0.8 

0.5 

0.9 

1.3 

1.0 

1.1 

0.7 

0.9 

0.7 

0.7 

± CI 

Unknown 

. 

. 

. 

. 

. 

Combination of Aids** 

0.7 0.6 

0.7 

0.9 

0.3 

0.7 

0.4 

2.1 

1.0 

0.5 

1.1 

1.2 

0.7 

0.8 

0.6 

0.7 

0.4 

0.4 

. 

. 

. 

. 

. 

% 

Nic Patch 

1.8 2.3 

2.9 

2.0 

3.5 

7.5 

2.1 

4.0 

4.9 

6.1 

11.1 

4.8 

2.9 

3.2 

4.2 

4.7 

4.5 

4.3 

4.1 

5.0 

5.5 

5.7 

± CI 

or Gum 

. 

21.0 19.2 

23.4 

18.2 

24.1 

32.5 

25.1 

13.2 

11.4 

15.5 

20.7 

15.8 

22.3 

20.4 

26.5 

14.8 

18.2 

14.9 

23.8 

23.9 

29.9 

21.5 

. 

% 

Self-Help 

Materials 

1.3 1.7 

1.9 

1.7 

2.6 

4.8 

1.4 

2.9 

4.1 

3.9 

6.5 

3.0 

2.2 

2.1 

2.7 

3.3 

2.7 

2.9 

2.9 

4.1 

2.8 

4.0 

± CI 

. 

9.3 8.0 

11.0 

9.0 

10.0 

9.1 

9.7 

7.6 

10.7 

5.9 

12.0 

7.2 

9.2 

9.8 

11.3 

6.9 

6.4 

9.7 

10.4 

13.5 

6.9 

9.7 

. 

% 

Counseling 

1.1 1.4 

1.6 

1.2 

2.6 

3.8 

1.1 

3.0 

4.9 

6.4 

4.7 

3.1 

1.9 

1.8 

2.5 

4.0 

3.2 

2.0 

2.6 

3.1 

3.2 

2.5 

± CI 

. 

*Those 25+ years of age who have made a quit attempt in the past year and were daily smokers 1 year ago. 

7.1 5.6 

8.9 

6.0 

9.2 

7.7 

6.8 

6.5 

9.5 

8.0 

7.4 

8.3 

6.0 

6.7 

7.7 

8.3 

6.8 

4.5 

7.6 

8.6 

7.7 

5.2 

. 

% 

0.8 1.0 

1.4 

0.9 

1.5 

5.1 

1.1 

1.8 

2.2 

2.9 

8.3 

2.0 

1.0 

1.0 

2.4 

2.5 

1.8 

1.1 

1.5 

1.7 

3.6 

3.9 

± CI 

Nicotine 

. 

Gum 

3.3 2.7 

3.9 

2.7 

3.6 

6.6 

3.5 

2.5 

2.4 

2.9 

4.6 

3.3 

2.1 

2.8 

5.5 

3.2 

2.6 

1.8 

2.9 

3.3 

5.4 

4.8 

. 

% 

0.8 1.1 

1.2 

0.8 

1.8 

2.8 

1.1 

1.6 

4.1 

2.1 

1.4 

1.5 

1.6 

1.6 

1.9 

1.8 

1.8 

2.2 

2.1 

2.5 

2.9 

± CI 

Nicotine 

. 

. 

Patch 

**Combination includes use of the method alone or with any other method. 

4.6 4.7 

4.4 

3.9 

5.7 

6.3 

6.1 

2.0 

5.7 

1.8 

2.1 

6.1 

5.2 

4.6 

1.8 

3.7 

3.6 

6.0 

5.4 

6.6 

4.4 

. 

. 

% 

Single Aid Only 

± CI 

0.7 1.0 

1.1 

0.9 

1.0 

1.8 

0.7 

1.6 

2.6 

2.4 

2.5 

1.2 

1.0 

1.2 

1.5 

1.5 

1.3 

1.7 

1.3 

2.0 

1.2 

2.3 

Self-Help 

Materials 

. 

2.5 2.4 

2.7 

2.9 

2.0 

1.3 

2.6 

2.0 

3.6 

2.2 

1.3 

1.5 

2.7 

2.6 

3.4 

1.9 

1.9 

3.1 

2.5 

3.6 

1.2 

3.4 

. 

% 

Counseling 

0.7 0.8 

1.1 

0.9 

1.4 

0.8 

0.6 

2.1 

2.9 

4.1 

4.2 

2.5 

0.6 

0.7 

0.8 

2.7 

2.1 

0.7 

1.4 

1.5 

2.4 

0.7 

± CI 

. 

Household Income (Dollars) 

1.7 1.3 

2.2 

1.9 

1.7 

0.4 

1.2 

2.7 

1.8 

2.6 

2.9 

3.8 

1.1 

1.0 

1.0 

3.0 

2.5 

0.6 

1.5 

1.6 

2.3 

0.4 

. 

% 

2.0 2.7 

3.4 

2.1 

4.2 

7.7 

2.2 

4.6 

6.2 

7.7 

13.7 

5.6 

3.1 

3.7 

4.8 

5.3 

4.9 

4.4 

4.4 

5.7 

5.6 

6.4 

± CI 

. 

None 

Education (Years) Race/Ethnicity 

72.3 75.2 

68.5 

74.6 

69.3 

64.3 

NH White 68.4 

80.6 

79.5 

77.9 

72.5 

77.2 

72.0 

71.9 

67.1 

78.2 

76.3 

78.5 

69.7 

66.9 

64.9 

Unknown 71.9 

. 

% 

Total Gender Male 

Female 

Age (Years) 25–44 

45–64 

65+ 

Hispanic 

Afric-Am 

Asian/PI 

Nativ Am 

Table 5-1 

Other 

<12 

13–15 

16+ 

≤10K 

12 10-20K 

20-30K 

30-50K 

50-75K 

>75K 
Smoking and Tobacco Control Monograph No. 12 

The difference in usage rates (14 percent in the 1993 CTS versus 21 percent in the 1996 CTS, versus 24 percent in the 1997 U.S. sales data) could 

be due to several reasons. There is good evidence that the historical trend is 

due to increased recognition of the efficacy of patch and gum and due to 

their increased availability as an OTC item (Shiffman et al., 1997a & b). 

Some smokers may have purchased gum or patch but never actually made a 

quit attempt; however, recent work indicates that 94 percent of OTC nicotine replacement therapy (NRT) use is for cessation purposes (Pillitteri et al., 

1998). 

In summary, it is reasonable to estimate that between one-fifth and 

one-quarter of all quit attempts are accompanied by the use of nicotine 

gum or patch. 

Bupropion Bupropion was not yet available for smoking cessation when the 1996 

CTS was conducted. When the pharmacy sales data were collected in 1997, 

Zyban® (the trade name of bupropion when used for smoking) had only 

been available for smoking cessation for between 1 and 6 months. Use of 

Zyban® appeared to stabilize the last 3 months of these data. Projections for 

a full year based on these last 3 months of pharmacy audits indicate that 

2.4 million quit attempts/year may involve Zyban®. In addition, it is estimated that 15 percent of Wellbutrin® use (the trade name of bupropion for 

depression) is actually for smoking cessation (Glaxo-Wellcome, personal 

communication). Adding these usage measures together results in an estimate of 3.7 million quits/year with bupropion. Using the same value of 1.5 

for the ratio between quit attempts and number of individuals who have 

attempted to quit in the last 12 months would yield an estimate of 14 percent of all quit attempts that involve bupropion. 

Any medication Although no data are available, it is thought that in 1997 there 

was little concomitant use of gum with patch or of bupropion with gum or 

patch. Recent publications suggest that combined use may improve quit 

rates (Hughes et al., 1999; Jorenby et al., 1999). But if we assume that combined use is minimal, then based on pharmacy sales data, the use of any 

medication would be projected to occur in 35-38 percent of all quit 

attempts in 1998, based on assumptions about the number of quit attempts 

stated above. 

EFFICACY/ The 1996 CTS asked those who were daily smokers 1 year prior 

EFFECTIVENESS to the survey whether they had made a quit attempt lasting 

more than 24 hours. Those who had made a quit attempt were Nicotine Gum asked what method or methods they had used (Table 5-1). and Patch: Table 5-2 presents the current smoking status of those who had 

made a quit attempt in the last 12 months by the method of cessation assistance they reported using. Of those who reported using no cessation assistance, 17 ± 2 percent were former smokers at the time of the survey. Of 

those who reported using patch or gum, either alone or in combination 

with other methods, 32 ± 5 percent were former smokers at the time of the 

survey. When the data were analyzed for those who had been quit for 3+ 

months at the time of the survey, results were less impressive (11.2 ± 2.6 

158

Chapter 5 

Table 5-2 

Current Smoking and Cessation Status by Method of Cessation Reported by Those who were 

Daily Smokers 1 Year prior to the Survey and who Made a Quit Attempt in the Last 12 

Months: 1996 CTS* 

Current Smoker w/Quit Attempt Former Smoker of Pop Samp 

Daily Occasional Any Quit Length Size Size 

% CI % CI % CI (N) (n) 

Total 71.79 2.09 7.56 1.21 20.65 1.90 1,266,663 2,680 

Single Aid Only 

None 74.59 2.30 8.35 1.60 17.06 2.20 915,186 1,886 

Counseling Only . . 3.79 5.39 . . 21,538 38 

Self-Help Only 73.04 9.63 6.48 5.66 20.48 8.88 32,124 74 

Patch Only 67.11 8.17 6.49 4.06 26.40 8.04 58,422 142 

Gum Only 57.49 14.99 8.00 6.32 34.52 14.16 41,251 92 

Aids in Combination 

Counseling** 71.81 7.11 3.32 2.55 24.87 7.16 89,356 189 

Self-Help** 69.06 6.22 4.34 3.07 26.60 6.08 117,871 260 

Patch/Gum** 62.62 4.87 5.68 1.76 31.71 4.51 266,595 612 

Unknown . . . . . . 8,549 16 

*Those 25+ years of age who have made a quit attempt in the past year and were daily smokers 1 year ago. 

**Combination includes use of the method alone or with any other method. 

percent for any use of patch or gum versus 9.7 ± 0.7 percent for no methods used). The results for 3+ month cessation were not statistically different, possibly due to the small number of observations. 

In intervention studies, the one community practice Rx study found a 

long-term (6-12 months) quit rate with nicotine gum of 18 percent (Smith 

Kline Beecham, 1995). Across five studies of Rx nicotine patch (Table 5-3), 

quit rates ranged from 5 percent to 11 percent. In OTC settings, two gum 

studies reported long-term quit rates of 13 percent and 15 percent. Six studies of OTC patch reported quit rates from 5 percent to 17 percent with a 

median of 10 percent. Most studies that directly compared patch in Rx and 

OTC settings found similar quit rates (Hughes et al., 1999). 

In summary, a reasonable estimate for a real-world quit rate for OTC 

and Rx gum and patch is 10 percent. Thus, with 6.3 million uses, 630,000 

successful quits/year are estimated to be associated with gum or patch use 

(see Table 5-4). Given that those who choose to use gum or patch are more 

heavily dependent than those who choose to quit on their own (Hughes et 

al., 1997), this estimate may be biased to show smaller gum/patch effects. 

The difference in percentage of quit rates in which patch or gum are used 

between 1993 and 1996 could be because of the Rx barrier to obtaining 

patch or gum that existed in 1993 but did not exist in 1996. 

159

Smoking and Tobacco Control Monograph No. 12 

Table 5-3


Six-Month Quit Rates in Minimal-Contact Studies of Nicotine Gum and Patchesa


OTC Rx Risk Ratio of 

NRT Placebo NRT OTC NRT vs. Placebo 

Nicotine Gum 

Smith Kline Beecham, 1995 15 — 18b — 

Schneider et al., 1983 13 8 30 1.6 

Nicotine Patch 

Hays et al., 1997 9 4 — 2.5 

Alza Corporation, 1996 9 — 7b — 

McNeil Pharmaceuticals, 1996 11 — 12 — 

Leischow et al., 1997 5 — 5 — 

Sonderskov et al., 1997 11 4 — 2.8 

aDue to differences in study design and in data collection, quit rates can be compared within rows but not across rows
 bSurveys, not experimental trials. Because so few returned for CO verification, these are self-reported quit rates. With CO verifica­


tion they are likely to be somewhat lower.


Bupropion There are no community practice Rx studies with bupropion. There is 

one head-to-head comparison of nicotine therapy versus bupropion 

(Jorenby et al., 1999). In this study, bupropion had higher quit rates than a 

nicotine patch (30 percent versus 16 percent). On the other hand, longterm quit rates for bupropion in other studies were similar to those found 

with gum and patch studies. In summary, because there is but one study, 

this paper will assume that the quit rates for real-world bupropion are similar to that for real-world gum and patch—i.e., 10 percent. Thus with 3.7 

million users, 370,000 quits/year are estimated to be associated with bupropion. 

Any medication As discussed above, bupropion and NRT are probably rarely used 

together. Thus, the total number of medication-associated quits projected is 

630,000 + 370,000 = 1.0 million quits for 1998. 

Quits with medications To calculate the proportion of additional successful 

from the CTS quits (not quit attempts) associated with medication, 

one has to make assumptions about the quit rate in those who do not use 

medications to quit. We assume that the 1-year quit rate for those who do 

not use medication is similar to the self-quit rate. This rate has been estimated at 5 percent (Hughes et al., 1992), and the 1996 CTS data (See 

Chapter 2) reports an 11.5 percent quit rate for 3+ months among those 

who were daily smokers one year prior to the survey, which, if converted to 

a 1-year quit rate, would approximate the 5 percent estimated rate. With 

this assumption of a doubling of the success rate with medication, 50 percent of all quits in which medications are used during 1998 are projected to 

be additional quits associated with medication use. 

160

Chapter 5 

0.15–0.50 

7.5%–25% 

1

44.1 

1.5% 

2.0 

Number of smokers over age 18 

Quit attempts in the last year that are 

currently successful for 3 or more months (% of all daily smokers age 25+) (See 

Quit attempts successful for 3+ months 

Number of quit attempts attributable to 

Fraction of all successful quit attempts 

Table 2-2) 

National Estimates 

(1996 CPS Data) 

(millions) 

medication attributable to medication 

Use of, and Cessation with, Most Commonly Used Smoking Cessation Medications* 

Nicotine Gum 

0.15–0.50 

34–38% 15–50% 

Total 

10.0 1.00 

Bupropion 

0.06–0.18 

15–50% 

3.7 

14% 

0.37 

and Patch 

0.10–0.32 

21–24% 15–50% 

6.3 

0.63 

to Medication (% of successful quits where medication is used) 

Successful Quits Associated Excess Quits Attributable to Excess Quits Attributable * See text for basis of calculations. 

(% of all quit attempts) 

Medication (millions) 

Use from Sales Data 

with Use (millions) 

Table 5-4 

Basis 

(millions) 

Use 

161

Smoking and Tobacco Control Monograph No. 12 

AHRQ Analyses A recent meta-analysis of treatment patch or gum performed 

as part of the U.S. Public Health Service Agency for Healthcare Research and 

Quality (AHRQ) Clinical Practice Guideline suggested that there was a doubling of the cessation rate for nicotine patch therapy and a 30 to 80 percent 

increase in cessation with nicotine gum (Fiore, 2000). Data from the 1996 

CTS suggest that patch or gum use was associated with an increased likelihood of being quit at the time of the survey—approximately twice that of 

no therapy (31.7 percent compared to 17.1 percent; Table 5-2)—but the 

likelihood of being quit for 3 or more months was increased by only 15 percent. This population estimate of a 15 percent increase is based on a small 

number of observations and is substantially lower than estimates of larger 

populations studied as part of cessation evaluations. In addition, it is based 

on self-selected groups and, for the reasons discussed above, it probably represents an underestimate of the effect of those medications and is included 

as a lower bound of the likely magnitude of the effect. 

INTERPRETATION Before discussing the significance of the above projections, 

some cautions are needed. First, the projections may actually be underestimates, as they do not include quits from medications other than nicotine 

patch, nicotine gum, and bupropion. On the other hand, the numbers may 

be overestimates, as they assume smokers do not use more than one medication at a time and do not use more than one medication per year. As 

stated above, we do not have any actual data on these two issues. Third, the 

calculations assume that all medication use is for cessation. A recent survey 

found that 94 percent of OTC gum use is, in fact, for cessation (Pillitteri et 

al., 1998). Fourth, these estimates assume that utilization will continue at 

the same rate. Often, medications have an initial period of popularity followed by a decline in use. OTC gum and patch have been available for a 

sufficient period to indicate that sales are now stable. Bupropion has been 

available for less than a year; thus, whether its sales will decline (or alternately, they might still increase) is difficult to know. 

The term “quits associated with medication” has been used to avoid the 

often implicit assumption that the effects of medication are entirely due to 

traditional pharmacological effects. 

Of course, some of these effects are due to placebo effects and other 

non-pharmacological effects, including telephone-based counseling offered 

to smokers trying to quit. The one randomized study of such counseling 

showed that it improved quit rates on its own by a factor of 1.7 (Shiffman 

et al., 1997a & b). However, probably less than 5 percent of medication 

users take advantage of such a program (Smith Kline Beecham, personal 

communication). Thus the contribution of telephone counseling to medication-associated quits is probably small. Another non-pharmacological effect 

is that medication availability may prompt quit attempts. OTC availability 

has made it easier to access medications among smokers who do not have 

to see a physician for such medication. Finally, the pharmaceutical companies have engaged in a large amount of direct-to-consumer advertising, the 

majority of which includes a stop-smoking message and encourages cessation, and the impact of this advertising on cessation activity has not yet 

been examined (Shiffman et al., 1997a & b). 

162

Chapter 5 

Neither did the analyses address whether any medication-associated 

quits are from “stealing” quitters who would have quit via behavior therapy. There are no data on whether this is the case; however, even if it were, 

the effect would be very small given the miniscule utilization of behavior 

therapy (<2 percent of all quits; Smith Kline Beecham, 1995). 

With these caveats in mind, Table 5-4 presents a number of summary 

estimates for the effects of medication. With 44 million smokers and 17 

million making quit attempts each year, and with 11.5 percent of those quit 

attempts lasting at least 3 months, approximately 2 million successful quits 

(for at least a 3-month period) would occur. Drug-use data would suggest 

that 6.3 million uses of patch and gum would occur (some individuals 

would use medications in more than one cessation attempt per year), and 

3.7 million uses of bupropion would occur. Of the total population of daily 

smokers, 21-24 percent of those who make a quit attempt are estimated to 

use patch and gum, and an additional 14 percent are estimated to use 

bupropion. If 10-percent success rates are estimated for use of either medication, then approximately 1 million successful quits would be associated 

with medication. If the attributable fraction for medication use is between 

0.15 and 0.5, then the number of excess quits produced by medication 

would be 150,000 to 500,000, or 7.5 to 25 percent of all successful quits. 

CONCLUSION The major conclusions of these analyses are that medications are 

widely utilized for smoking cessation and make a substantial contribution 

to cessation success in the smoking population. Up to 1 million successful 

quits/year may be accompanied by medication use, and there may be an 

additional 150,000 to 500,000 successful quitters associated with medication use in the United States each year. 

The development of truly effective medications, the decreased professional time necessary with OTC medications, the large increase in availability with OTC access, and the direct-to-consumer advertising for both Rx and 

OTC drugs by the pharmaceutical companies have led to a situation in 

which medications make an important contribution to smoking cessation 

in the United States. 

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Alza Corporation. Nicoderm data summary. Paper 

presented at: meeting of the Nonprescription 

Drug Advisory Committee of the FDA, Bethesda, 

MD, 1996. 

Fiore, M.C., Bailey, W.C., Cohen, S.J., et al. Treating 

Tobacco Use and Dependence: Clinical Practice 

Guideline. Rockville, MD: U.S. Department of 

Health and Human Services, Public Health 

Service, Agency for Healthcare Research and 

Quality, 2000. 

Gilpin, E., Pierce, J.P. Measuring Smoking Cessation: 

problems with recall in the 1990 California 

Tobacco Survey. Cancer Epidemiology, Biomarkers 

& Prevention. 3(7):613-617, 1994. 

Hays, J.T., Croghan, I.T., Offord, K.P., et al. Over-thecounter (OTC) transdermal nicotine patch therapy. Journal of Addictive Diseases 16:136, 1997. 

Hughes, J.R. Pharmacotherapy of nicotine dependence. In: Pharmacological Aspects of Drug 

Dependence: Toward an Integrative Neurobehavioral 

Approach, Handbook of Experimental Pharmacology 

Series. Schuster C.R., Kuhar M.J. (editors) New 

York: Springer-Verlag, 599-626, 1996. 

Hughes, J.R., Giovino, G.A., Klevens, R.M., Fiore, 

M.C. Assessing the generalizability of smoking 

studies. Addiction 92:469-472, 1997. 

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Hughes, J.R., Goldstein, M.G., Hurt, R.D., Shiffman, 

S. Recent advances in the pharmacotherapy of 

smoking. Journal of the American Medical 

Association 281:72-76, 1999. 

Hughes, J.R., Gulliver, S.B., Fenwick, J.W., Cruser, K., 

Valliere, W.A., Pepper, S.L., Shea, P., Solomon, 

L.J., Flynn, B.S. Smoking cessation among selfquitters. Health Psychology 11:331-334, 1992. 

Jorenby, D.E., Leischow, S.J., Nides, M.A., Rennard, 

S.I., Johnston,J.A., Hughes, A.R., Smith, .S., 

Muramoto, M.L., Daughton, D.M, Doan, K., 

Fiore, M.C., Baker, T.B. A controlled trial of sustained-release bupropion, a nicotine patch, or 

both for smoking cessation. The New England 

Journal of Medicine 340: 685-691, 1999. 

Leischow, S.J., Castellini, S., Merikle, E. The efficacy 

of nicotine patch as an over-the-counter medication. Journal of Addictive Disorders 16:140, 1997. 

McNeil Consumer Products Company. Nicotrol data 

summary. Paper presented at: meeting of the 

Nonprescription Drug Advisory Committee of 

the FDA, Bethesda, MD, 1996. 

Pierce, J.P., Gilpin, E., Farkas, A.J. Nicotine patch use 

in the general population: Results from the 

1993 California Tobacco Survey. Journal of the 

National Cancer Institute 87:87-93, 1995. 

Pillitteri, J.L., Hughes, J.R., Callas, P.W. Use of nicotine gum for smoking reduction vs. smoking 

cessation. Presented at Society for Research on 

Nicotine & Tobacco: New Orleans, 1998. 

Prochazka, A.V., Weaver, M.J., Keller, R.T., Fryer, G.E., 

Licari, P.A., Lofaso, D. A randomized trial of nortriptyline for smoking cessation. Archives of 

Internal Medicine 158:2035-2039, 1998. 

Schneider, N.G., Jarvik, M.E., Forsythe, A.B., Read, 

L.L., Elliott, M.L., Schweiger, A. Nicotine gum in 

smoking cessation. Addictive Behavior 8:253-261, 

1983. 

Shiffman, S., Gitchell, J., Strecher, V.J., et al. Realworld efficacy of computer-tailored smoking cessation 

material as a supplement to nicotine replacement. 

Presented at 10th World Conference on Tobacco 

or Health, Beijing, China, 1997a. 

Shiffman, S., Pinney, J.M., Gitchell, J., Burton, S.L., 

Lara, E.A. Public health benefit of over-thecounter nicotine medications. Tobacco Control 

6(4):306-310, 1997b. 

Sonderskov, J., Olsen, J., Sabroe, S., Meillier, L., 

Overvad, K. Nicotine patches in smoking cessation. American Journal of Epidemiology 145:309-

318, 1997. 

Smith Kline Beecham. OTC Nicorette data summary. 

Paper presented at meeting of the 

Nonprescription Drug Advisory Committee of 

the FDA, Bethesda, MD, 1995. 

164

Effect of Cost on Cessation 

Dave Sweanor, David M. Burns, Jacqueline M. Major, 

Christy M. Anderson 

BACKGROUND ON One of the best known principles of economics is that of the 

THE ROLE OF downward sloping demand curve. As the price of a commodiPRICE/TAXATION ty increases, the demand for that commodity will decrease. 

This law of economics can be extremely valuable in population-based 

tobacco control strategies. We can increase tobacco prices through tax policy, thus promoting reduced consumption. 

The pricing of tobacco products is recognized as a key strategy in the 

“comprehensive plans” that health organizations have developed to guide 

tobacco control. The major health and medical organizations in the United 

States identify tax strategy as critical to achieving reductions in tobacco use, 

and the World Health Organization (WHO), in its publication Guidelines for 

Controlling and Monitoring the Tobacco Epidemic (WHO, 1998), lists tobacco 

taxes as a key strategy. It is important to ensure that the accessibility of 

tobacco products reflects the gravity of harm produced by these products. 

One important way of reducing this accessibility is to reduce the affordability of tobacco products by increasing the taxes imposed on them. 

There is a substantial body of evidence, from the United States and elsewhere, demonstrating that a cigarette price increase will lead to a fall in 

overall cigarette consumption, though that fall will be less than proportionate to the increase in price. Much of the evidence on the role of price was 

summarized in the 1992 report of the Surgeon General, Smoking and Health 

in the Americas (U.S.DHHS, 1992), a 1993 summary report of a National 

Cancer Institute Expert Panel (NCI, 1993), and in the report of the Institute 

of Medicine (IOM), Growing Up Tobacco Free (IOM, 1994). In general, these 

analyses of the literature estimate that a 10 percent increase in the price of 

cigarettes will, all other things being equal, result in roughly a 4 percent 

decline in overall consumption (Chaloupka and Warner, 1999). 

Price is also one of the few things tobacco companies acknowledge as 

affecting tobacco consumption. Filings with the Securities and Exchange 

Commission (SEC), and similar bodies in other countries, and reports to 

current or potential shareholders often mention the impact of price on 

sales. For example, the current 10-K filing with the SEC by Philip Morris 

Companies Inc. states (p. 4): 

“In the opinion of PM Inc. and Philip Morris International, 

past increases in excise and similar taxes have had an adverse 

impact on sales of cigarettes. Any future increases, the extent of 

which cannot be predicted, could result in volume declines for the 

cigarette industry, including PM Inc. and Philip Morris 

International...” (Philip Morris, Inc.) 

165

Smoking and Tobacco Control Monograph No. 12 

Recent research has reiterated the importance of price. A review of this 

evidence was carried out by Dr. Frank Chaloupka as a policy analysis paper 

for the Health Science Analysis Project (Chaloupka, 1998), which looked at 

the potential impact on health of the price components of the various 

tobacco-related bills which had recently been introduced in Congress. His 

review of the research leads to the conclusion, “...that substantial sustained 

cigarette tax increases are potentially the most effective means of achieving 

long-run reductions in smoking in all segments of the population.” 

The impact of price is sufficiently strong that it can be demonstrated 

simply by juxtaposing data on price and consumption. As shown in Figures 

6-1 through 6-3, there is a pronounced tendency for per-capita consumption to move in an inverse relationship to real prices. 

OVERVIEW OF Although cigarette smoking is an addiction, even addictive 

RECENT STUDIES behaviors have been shown to have downward sloping 

demand curves. This is an established effect quite independent of tobacco 

price studies. For example, it has been shown in animal experiments that 

there is an inverse relationship between the amount of work required and 

the consumption of an addictive substance (Bickel and DeGrandpre, 1996). 

The idea that decisions about the use of addictive products can be made 

on the basis of a rational decision-making process is encompassed within 

the “rational addiction” model (Becker and Murphy, 1988), which is now 

widely accepted among economists (Chaloupka, 1991; Keeler et al., 1993; 

Becker et al., 1994; Sung et al., 1994). Within this model, present consumption is influenced by past consumption and by the perception of the various costs of anticipated future consumption. Because of the role of past 

consumption in influencing current consumption, measures that reduce 

cigarette use in the present will have an additional effect on longer term 

use. In addition, increases in the perceived future costs of smoking will lead 

to reductions in current smoking. 

There is significant evidence that young people are particularly price 

sensitive, and that this price-sensitivity will be reflected primarily in 

whether they smoke at all (Grossman and Chaloupka, 1997). By reducing 

the overall level of tobacco use within a population cohort, we create a 

strong tendency toward reduced consumption over the longer term. This, 

in part, explains the estimates that the long-term price elasticity is about 

double the short-term effect (Chaloupka, 1991; Becker et al., 1994). This 

effect suggests that a 10 percent price increase could be expected to reduce 

overall cigarette use by about 4 percent in the short term, but by about 8 

percent in the long term. 

In terms of estimating overall population-based cessation, it is important to note that estimates of price responsiveness among smokers measure 

aggregate cigarette consumption. This is a combination of the effects of 

those who quit (or do not start) and those who reduce their consumption. 

A 4 percent decline in consumption does not mean a 4 percent decline in 

smoking prevalence. A recent analysis (Evans and Farrelly, 1996) estimated 

that approximately half of the impact of price on adult smoking is on the 

decision to smoke in the first place. 

166

Chapter 6 

Figure 6-1 Annual per Capita Consumption of Cigarettes and Real Price of Tobacco (per 20 Cigarettes): 

United States, 1954–1994 A C m R T Y Number of Cigarettes Smoked per Capita Annually Price per 20 Cigarettes Sources: The Tax Burden on Tobacco, published by The Tobacco Institute, Washington, DC, vol. 33, 1998 

U.S. Bureau of Labor Statistics, CPI (all items) 

167

Smoking and Tobacco Control Monograph No. 12 

Figure 6-2 

Daily Consumption of Cigarettes (per Capita) and Real Price of Tobacco (per 20 

Cigarettes): Canada, 1950–1994 

4

7

$2

$3

$4

$5

$6

Real Price of Cigarettes (1994 dollars)

Daily Consumption Per Capita

950 959 968 977 986 1994

Year

Cigarettes Consumed Daily

Price per Pack

Notes: 	Data include the highest credible estimate of contraband tobacco. 

Cigarettes include fine-cut tobacco equivalents (1 g) 

Sources: 	Canadian Tobacco Consumption, 1990–1994, Prepared by The Non-Smokers’ Rights Association, 1994 

Statistics Canada, catalogues, 32-022 Monthly, 91-022, vol. 7, no. 3, 91-512 and 91-213 

Linquist Avey MacDonald Baskerville, Inc. “Contraband Estimate 1992—An Update” September 27, 1993 

THE CANADIAN From 1982 to 1991, there were rapid increases in the cost of 

EXPERIENCE cigarettes in Canada, caused primarily by a series of large tax 

increases. The real price of a pack of 20 cigarettes went from about $2.10 to 

about $5.40 (Sweanor et al., 1994). Smuggling of tobacco products—supplied overwhelmingly by Canadian cigarettes shipped to the United 

States—led to a significant contraband market, which began to erode prices 

in 1992 and 1993. In early 1994 there were large tobacco tax reductions, 

bringing the average price of a pack of 20 back to about $3.20. 

There is no doubt that the rapid escalation of tobacco prices in Canada 

was accompanied by significant declines in consumption. In terms of total 

per-capita consumption, the decline among adults from 1982 to 1992 was 

approximately 40 percent, and among 15- to 19-year-olds, the decline was 

roughly 60 percent (Sweanor et al., 1994; Sweanor and Martial, 1994). 

This decline in Canadian per-capita consumption was significantly 

more rapid than that experienced in the United States. Figures compiled by 

the Canadian Tobacco Manufacturers’ Council (CTMC, 1993) show that per 

capita cigarette consumption among those over the age of 15 declined by 

42.4 percent in Canada from 1982 to 1992, compared to a decline of 25.7 

percent in the United States. 

168

Chapter 6 

Figure 6-3 

Real Cigarette Prices and Daily Cigarette Smoking among Canadians: Age 15 to 19 

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

Teen Smoking

979 982 985 988 991 994 1997

$0

$30

$60

$90

$120

$150

$180

$210

$240

$270

$300

Real Tobacco Price Index (1981=100)

Year

Real Tobacco Price Index

Percentage Smoking

Sources: 	Statistics Canada, Labor Force Survey, 1991 

Canadians and Smoking: An Update, Health and Welfare Canada, 1991 

Survey on Smoking in Canada, Cycle 3, 1994 

The Canadian experience also showed that the declines in per capita 

consumption were accompanied by significant declines in prevalence. The 

federal health department (Health Canada, 1991) does periodic polling of 

smoking rates, and these rates show a decline in smoking prevalence from 

39.5 percent in 1981 to 31 percent in 1991. Gallup, who does an annual 

survey, found a decline from 45 percent in 1981 to 33 percent in 1991. By 

far the most comprehensive surveys of smoking behaviors, however, are 

conducted by tobacco companies themselves. Data from Imperial Tobacco, 

a BAT affiliate that controls two-thirds of the Canadian market, show a 

decline in smoking prevalence from 39.4 percent in 1981 to 30.6 percent in 

1991 (Imperial Tobacco, 1989; Imasco, 1993). In all cases, the percentage 

decline in the prevalence of smoking increased significantly during the time 

of rapidly increasing prices (Stephens, 1994). 

The decline in smoking prevalence among 15- to 19-year-olds in 

Canada was more pronounced, as shown in federal government surveys 

(Health Canada, 1991). In 1981, 43.5 percent of 15- to 19-year-olds were 

smoking cigarettes and 39.5 percent were smoking daily. By 1991, only 22 

percent were smoking at all and only 16 percent were smoking daily. 

169

Smoking and Tobacco Control Monograph No. 12 

With the reduction in tobacco prices—a process that began with smuggling and was greatly enhanced by the tax reductions—the trend lines in 

tobacco consumption reversed. The best example of this is, again, data from 

the tobacco industry. RJR’s Canadian subsidiary does monthly polling of 

smoking trends in Canada, and a year ago this information became available for the years 1988 to 1996 (RJR-Macdonald, 1997). The relationship of 

consumption rates with price changes is very strong. Among all adults it 

shows a decline in smoking prevalence from 31.0 percent in 1988 to 26.7 

percent in 1991. There was a further small decline in 1992, coinciding with 

the growth of smuggling, but a slight increase (to 26.9 percent) in 1993 as 

smuggling peaked. The price cuts of 1994 correspond to an increase in 

smoking prevalence to 27.9 percent that year, followed by an increase to 

28.4 percent in 1995 and a slight decrease (to 28.2 percent) in 1996. 

The price effects indicated by the RJR data are even more pronounced 

among 19- to 24-year-olds. The data show a decline in prevalence from 33.4 

percent in 1988 to 28.4 percent in 1992 and 28.3 percent in 1993. With the 

tax cuts, prevalence went to 29.6 percent in 1994 and was 32.3 percent in 

1996. 

EFFECTS OF COST Much of the work examining the role of cigarette cost as a 

ON MEASURES OF tobacco control intervention has centered around using cigaCESSATION rette consumption as the measure of smoking behavior that is 

changing in relation to changes in cost. However, consumption can change 

because smokers quit long term, because smokers reduce the number of cigarettes that they smoke per day, because large numbers of smokers quit for 

brief periods and then relapse, or because fewer adolescents begin to smoke. 

Obviously the public health benefits of these different causes of reductions 

in consumption are vastly different, but few studies have been able to 

examine the effect of changes in cost of cigarettes on cessation due to the 

difficulties in obtaining population-based cessation data around the time of 

a price increase and the difficulty in finding an appropriate comparison 

group. We have utilized the 1992/93 and 1995/96 Current Population 

Surveys (CPS) which provide state-specific smoking prevalence and cessation data to examine the effect of cost on cessation in the United States. 

LONG-TERM The CPS asks all former smokers when they quit smoking, allowSUCCESSFUL ing identification of the calendar year in which they quit. These 

CESSATION data allow estimation of annual successful cessation rates. The 

number of current smokers for each of the years prior to the survey is estimated by adding those who are current smokers at the time of the survey 

and those who have quit between the year in question and the survey year. 

This number forms the denominator of the cessation rate for each calendar 

year. The number of these current smokers who report having quit during 

that year forms the numerator. By restricting the analyses to those who 

have been quit for at least 1 year at the time of the survey, only those who 

are successfully quit for 1 year or more are included in the numerator; and 

the estimates become an annual estimate of long-term (1 year or more) successful cessation for each of the calendar years. Use of 5- and 10-year digit 

preferences in the response to the question on how long ago the former 

170

Chapter 6 

Figure 6-4 

Long-Term Cessation Rates* versus Price of Cigarettes: United States 

1.50

2.00

2.50

3.00

3.50

4.00

4.50

5.00

5.50

Cessation Rate

987 988 989 990 991 992 993 994 1995 80

100

120

140

160

180

200

Price of Cigarettes

Year

Cessation Rates (%) with 95% CI

Price per Package of Cigarettes (cents)

* The at-risk population for each calendar year includes those CPS subjects who reported smoking during that year and 

who responded to the CPS no less than 2 calendar years and no more than 4 calendar years from the year for which the 

rate was calculated. Long-term quits are those that are at least 1 year long. 

smoker quit limits the utility of calendar year quit rate estimates to those 

within 4 years of the survey. But by combining the 1992/93 and 1995/96 

CPS it is possible to get calendar-year, long-term successful cessation rates 

for the period of 1988-1995. 

Figure 6-4 presents these calendar-year, long-term successful cessation 

rates in conjunction with the average sales-weighted cost (Tobacco Institute, 

1998) of a pack of cigarettes for the same years. There is a remarkable concordance between the cost and cessation data, particularly for the fall in 

cost and fall in cessation that occurred between 1992 and 1993 as part of a 

price competition triggered by the discounting of the prices of Marlboro 

and other premium cigarettes. This pattern suggests that at a macro level 

there is a concordance between cost of cigarettes and cessation rates. 

MEASURES OF There is a marked disparity in the cost of cigarettes among differCESSATION ent U.S. states. This disparity is produced by differences in the 

state excise taxes on cigarettes and by differences in the market share of different brands of cigarettes, particularly of generic brands that sell at a steep 

discount to full-price premium brands such as Marlboro. Differences across 

states in cost of cigarettes can be compared to differences in state-specific 

171

Smoking and Tobacco Control Monograph No. 12 

cessation measures (cessation attempt, being a former smoker, being a former smoker for 3+ months (see Chapter 2)) for those who were daily smokers 1 year prior to the CPS. These measures provide state-specific estimates 

of the rates of cessation attempts and cessation success that can be compared to the differences across states in the absolute cost of cigarettes. 

Cost measures were calculated separately for each month of the CPS 

(September, January, and May). The cost measures were the average of the 

annual costs for the 12 months prior to the survey month, with the change 

in cost estimate for the 3+ month cessation analysis excluding the costs for 

the 3 months prior to the survey—i.e., it was an average of 9 months rather 

than 12. An appendix to this chapter contains a more detailed description 

of the methods used in these analyses. 

An analysis of repeated measures for these data were performed and are 

included in the appendix. There are statistically significant effects identified 

for the association between absolute costs of cigarettes and increases in cessation attempts, being a former smoker of any duration, and 3+ month cessation success. The effect of the prior year’s absolute cost on becoming an 

occasional smoker was not statistically significant. Table 6-1 quantifies the 

magnitude of this effect of cost on cessation by expressing the change 

expected in the cessation measures based on various percentage differences 

in the cost of cigarettes. The differences are somewhat dependent on the 

starting point chosen for calculation of the differences in cost and the baseline rate of cessation in the state, but these estimates provide a general 

measure of the magnitude of the effect found in the analysis. For example, 

if the difference in the price per pack of cigarettes between states is from 

$2.00 to $2.30 (a 15 percent difference), the analyses would predict that 

there would be a difference in cessation attempts from 30 percent to 32.1 

percent (a 7.1 percent increase) and a difference in 3+ month cessation rates 

of from 5 percent to 5.4 percent (a 10.6 percent increase). These absolute 

differences may appear small, but they are similar to or larger than the price 

elasticities calculated for the acute effects of cost changes on consumption, 

and they would accumulate over time to have a much larger effect on 

prevalence as described above. These analyses are cross-sectional in nature, 

and it is likely that many of the same environmental factors that allow a 

high excise tax within a state will have an effect on cessation independent 

of their effect on the cost of cigarettes. The association of these other factors with the cost measure will overestimate the independent effect of cost 

on cessation in these analyses. However, these data provide further support 

for an effect of cigarette cost on smoking cessation as one mechanism for 

the reduction in cigarette consumption measures demonstrated following 

increases in excise taxes. 

CAVEATS Many factors must be kept in mind when analyzing the potential 

impact of price policies on population-based cessation. To begin with, economists talk about “real” (i.e., inflation-adjusted) prices. Price increases must 

be sustained, or the impact will be eroded by inflation. 

172

Chapter 6 

Table 6-1 

Predicted Difference in Cessation Measures for Various Differences in the Cost of Cigarettes 

(Estimated from the Relationship across States between the Percentage Difference in Cost and Percentage Difference in Cessation Measures, 

Controlling for the Random Effects of Time and State, CPS 92/93 & 95/96 Combined) 

Difference in Cessation Measures Expressed as a Percentage 

Percentage 

Difference Cessation Former Smokers 

in Cost (%) Attempts* (%) Any Length (%) 3+ Months (%) 

5 2.4 2.6 3.6 

10 4.8 5.2 7.1 

15 7.1 7.7 10.6 

20 9.4 10.1 14.0 

25 11.6 12.5 17.4 

-5 -2.5 -2.7 -3.6 

-10 -5.0 -5.4 -7.3 

*Attempts: Includes those who have made a quit attempt or have become former smokers, excludes occasional smokers. 

For example: A state charges $2.00 for a pack of cigarettes, 30% of its residents made a quit attempt and 5% became former 

smokers. If the price per pack is raised to $2.30 (a 15% increase in cost ), the analysis would predict the reported cessation measures to increase to 32.1% and 5.4%, respectively. 

Price data may not accurately reflect what is actually paid for the product. For instance, “average prices” in the United States often use the price of 

Marlboros as the standard or use a market-weighted average price. Such 

methodologies fail to take into account market segmentation on pricing 

issues. Looking at average prices ignores the role of cheaper cigarettes as a 

way of retaining price-sensitive smokers. 

To examine the effect of price on price-sensitive smokers we need to 

know what prices these people are actually paying. This means knowing 

about not only cheaper cigarette brands, but also about the role of discount 

coupons and the provision of merchandise (such as Marlboro gear) that 

effectively lowers the price paid for the product. 

Most pricing analyses, like most other research on tobacco consumption, are based on examining one variable while holding other variables 

“constant.” This, of course, does not work well in practice, as many other 

factors change over the same time periods that a change in price occurs. 

Studies of price need to consider the following: 

• Disposable income. There is an income elasticity as well as a 

price elasticity. Looking only at prices will miss the overall 

impact of affordability. This is particularly significant when 

looking at relatively small price increases during times of significant disposable income changes. These income changes may be 

particularly significant among adolescents and young adults and 

may dwarf the effects of measured price changes. 

• Promotional activities. The activities of tobacco companies can 

increase the perceived value of tobacco products in the eyes of 

purchasers as a way of combating the effects of higher prices. 

Tobacco companies are quite capable of fighting back against an 

increase in excise tax by increasing promotional activities in 

173 
Smoking and Tobacco Control Monograph No. 12 

order to retain existing users and attract new users. This can 

happen through promotions such as Marlboro gear, Joe Camel, 

and tobacco-product movie placement. 

• Population differences. Populations change over time. Looking 

at the effects of price on smoking rates over time in, say, 

Vancouver or California without taking into account changing 

demographics may simply miss key associations. It may be that 

there is a broad-based change in consumption due to price, but 

this change needs to be distinguished from consumption 

changes due to other factors such as high numbers of nonsmoking immigrants. 

SUMMARY Cost is clearly one of the major public policy tools that can influence smoking behavior. Increases in the cost of cigarettes have been shown 

to reduce cigarette consumption across a wide range of political jurisdictions and time periods. It is estimated that a 10 percent increase in the cost 

of cigarettes can be expected to reduce cigarette consumption by 4 percent, 

for a price elasticity of 0.4. Adolescents appear to be more sensitive to the 

effect of increasing cigarette costs. Data comparing long-term cessation rates 

in the United States with changes in the sales-weighted average cost of cigarettes show a fall in cessation when the cost of cigarettes was reduced 

between 1992 and 1993 as part of a cigarette price competition. 

Comparison of differences in costs across states with differences in cessation 

rates shows a statistically significant association of the absolute cost of cigarettes with both cessation attempts and 3+ month successful cessation. 

Taken as a whole, these data support an effect of cost on both cigarette consumption and smoking cessation. 

174

Chapter 6 

Appendix 

CPS CESSATION MODELS 

WITH COST: SUMMARY 

OF METHODS USED IN 

REPEATED MEASURES 

ANALYSIS 

Population 

The analysis includes cessation measures based on 

respondents of the Current Population Surveys for 

1992/93 and 1995/96, who are 25 years of age or 

older. To be included in the analyses, these respondents must have a valid current smoking status (daily, 

occasional, or former) and must have been daily 

smokers 1 year ago. In other words, respondents who 

did not answer whether they had smoked at least 100 cigarettes (Question 

32), whether they currently smoke (Question 35), and whether they 

smoked daily 12 months ago (Question 61) are excluded from the analysis. 

Additionally, respondents are excluded from the analysis if they are: 

current daily and occasional smokers with unknown quit attempts 

(Questions 44 and 45), 

current occasional and former smokers who have not been daily 

smokers for at least 6 months (Questions 39 and 55), or 

current former smokers with unknown lengths of quit time 

(Question 59). 

Additionally, the cessation measures were calculated for all states (plus D.C.) 

for each survey month ( Sept 92, Jan 93, May 93, Sept 95, Jan 96, and May 

96 ), yielding six repeated measures for each state. 

Below is a summary of the number of respondents used for the cessation 

measures for the CPS for various years. 

Population Sept 92 Jan 93 May 93 Sept 95 Jan 96 May 96 

Respondents to 105,937 105,148 104,920 98,082 87,336 87,811 

Current Population Survey 

Daily Smokers 15,194 15,367 14,255 13,314 11,564 11,516 

12 months ago 

Daily Smokers 13,676 13,830 12,815 12,081 10,473 10,363 

12 months ago, age 25+ 

175

Smoking and Tobacco Control Monograph No. 12 

Outcomes The five different cessation outcomes modeled using the CPS algorithm 

were as follows: 

Change	 Daily smokers 1 year ago who have either tried to quit 

(current daily smokers with quit attempts in the past 

year), have become occasional smokers, or have quit 

altogether (current former smokers). 

Attempts	 Daily smokers 1 year ago, excluding current occasional 

smokers, who have tried to quit or who have quit. 

Current occasional smokers have been excluded from 

the analysis of this outcome since their attempts to quit 

are not monitored on the CPS. 

Occasional	 Daily smokers 1 year ago who have become occasional 

smokers. 

Former	 Daily smokers 1 year ago who have quit smoking, 

regardless of the length of this current quit effort. 

Former, greater Daily smokers 1 year ago who quit smoking at least 3 

than 3 months months prior to the survey. 

Covariates The following fixed effects are used to model the cessation outcomes: 

Time-weighted The price of cigarettes for all states (plus D.C.) was 

Price for Prior obtained from The Tax Burden on Tobacco (Tobacco 

Year’s Absolute Institute, 1998). Each price is the weighted average 

Cost price per package for the calendar year. 

To calculate an appropriate cost measure of time for the 

cessation measures Change, Attempt, and Any Former, 

we weighted the price for each calendar year by the 

number of months in each year that spans the 12-

month period prior to the survey month. 

To calculate an appropriate cost measure of time for the 

cessation measure Formers with at Least 3 Months Quit 

Time, we weighted the price for each calendar year by 

the number of months in each year that spans the 9-

month period 3 months prior to the survey month. 

176

Chapter 6 

The following random effects are used to model the cessation outcomes: 

Month/Year	 A continuous variable that takes into account the length 

of time between the survey months. This variable is 

needed to account for the unequal time intervals in our 

repeated measures analysis. 

Month/Year Code 

September ’92 1 

January ’93 2 

May ’93 3 

September ’95 10 

January ’96 11 

May ’96 12 

State	 A categorical variable that assigns a number to each state 

(plus D.C.). 

Variables State and Month/Year were used as random effects to address the 

issue that observations from the same state are correlated as are observations from the same year.* 

REFERENCES 

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Economic Review 84(3):396–418, 1994. 

Becker, G.S., Murphy, K.M. A Theory of Rational 

Addiction. Journal of Political Economy 

96(4):675–700, 1988. 

Bickel, W.K., DeGrandpre, R.J. Modeling Drug Abuse 

Policy in the Behavioral Economics Laboratory. 

In Advances in Behavioral Economics, Volume 3: 

Substance Use and Abuse L. Green and J.H. Kagel 

(editors). Norwood, NJ: Ablex Publishing 

Corporation, 1996. 

Canadian Tobacco Manufacturers’ Council. Daily 

Consumption of Cigarettes per Capita Canada and 

the United States. Ottawa, Canada: Canadian 

Tobacco Manufacturers’ Council, 1993. 

Chaloupka, F.J. The Impact of Proposed Cigarette Price 

Increases, Policy Analysis No. 9. Health Sciences 

Analysis Project. Washington, D.C.: The 

Advocacy Institute, 1998. 

Chaloupka, F.J., Rational addictive behavior and 

cigarette smoking. Journal of Political Economy 

99(4):966–970, 1991. 

Chaloupka, F.J., Warner, K.E. The Economics of 

Smoking. Working Paper 7047, Cambridge, MA: 

National Bureau of Economic Research, 1999. 

Evans, W.N., Farrelly, M.C. The Compensating 

Behavior of Smokers: Taxes, Tar and Nicotine. 

Manuscript Presented at the Annual Meetings of 

the American Economic Association, 1996. 

Grossman, M., Chaloupka, F.J. Cigarette Taxes: The 

Straw to Break the Camel's Back, Public Health 

Reports 112(4):290–297, 1997. 

Health Canada. Canadians and Smoking: An Update. 

Ottawa, Canada: Health Canada, 1991. 

Hughes, J.R., Gulliver, S.B., Fenwick, J.W., Valliere, 

W.A., Cruser, K. Pepper, S., Shea, P., Solomon, 

L.J., Flynn, B.S. Smoking cessation among selfquitters. Health Psychology 11(5):331–334, 1992. 

Imasco Limited. 1993 Annual Report. Montreal, 

Canada: Imasco Limited, 1993. 

* SAS System for Mixed Models by Littell et al., Chapter 3, pp. 130-132. 

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Imperial Tobacco Limited. The Canadian Tobacco 

Market at a Glance. Montreal, Canada: Imperial 

Tobacco Limited, 1989. 

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Preventing Nicotine Addiction in Children and 

Youths. Lynch, B.S., Bonnie, B.S., Bonnie, R.J. 

(editors). Committee on Preventing Nicotine 

Addiction in Children and Youths, Washington, 

DC: National Academy Press, 1994. 

Keeler, T.E., Hu, T.W., Barnett, P.G., Manning, W.G. 

Taxation, regulation, and addiction: A demand 

function for cigarettes based on time-series evidence. Journal of Health Economics 12(1):1–18, 

1993. 

National Cancer Institute. The Impact of Cigarette 

Excise Taxes on Smoking Among Children and 

Adults: Summary Report of a National Cancer 

Institute Expert Panel. Rockville, Maryland: 

National Cancer Institute, Cancer Control 

Science Program, Division of Cancer Prevention 

and Control, August, 1993. 

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(www.secinfo.com): Accession Number 

0001047469-99-010218. March 18, 1999. 

RJR-Macdonald Inc. RJRMI Smoking Prevalence Data. 

Toronto, Canada: RJR-Macdonald Inc., 1997. 

Stephens, T. Cigarette Purchasing and Smoking in 

Canada, 1965–93. Ottawa, Canada: Heart and 

Stroke Foundation of Canada, 1994. 

Sung, H-Y, Hu, T-W. and Keeler, T.E. Cigarette 

Taxation and Demand: An Empirical Model. 

Contemporary Economic Policy 12(3):91–100, 

1994. 

Sweanor, D.T., Martial, L.R. The Smuggling of Tobacco 

Products: Lessons from Canada. Ottawa, Canada: 

Non-Smokers’ Rights Association/Smoking and 

Health Action Foundation, 1994. 

Sweanor, D.T., Martial, L.R., Dossetor, J.B. The 

Canadian Tobacco Tax Experience: A Case Study. 

Ottawa, Canada: Non-Smokers' Rights 

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Foundation, 1994. 

Tobacco Institute. The Tax Burden on Tobacco. Vol. 33 

Washington, D.C.: The Tobacco Institute, 1998. 

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Surgeon General. Atlanta: U.S. Department of 

Health and Human Services, Public Health 

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Center for Chronic Disease Prevention and 

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Health, 1992. 

World Health Organization. Guidelines for Controlling 

and Monitoring the Tobacco Epidemic. Geneva: 

World Health Organization, 1998. 

178

Self-Help Materials 

Susan J. Curry, Jacqueline M. Major 

INTRODUCTION Population-based approaches to smoking cessation can be 

viewed on the continuum of clinical to public health interventions (Curry, 

1993). At one end, a clinical approach provides intensive, efficacious inter

ventions to smokers who seek help, whereas a public health approach pro

vides lower intensity interventions to a broader spectrum of the population 

(Abrams et al., 1991; Lichtenstein and Glasgow, 1992). Generally, popula

tion-based approaches fall in at the public health end of this continuum. At 

the population level, we often talk about wanting to maximize the impact 

of an intervention. Impact can be defined as the product of an interven

tion’s reach (i.e., the proportion of smokers who are exposed to the inter

vention) and its effectiveness (i.e., the cessation rate associated with the 

intervention). Because of their potential for wide-scale dissemination, selfhelp materials for smoking cessation are an important component of popu

lation-based approaches to smoking cessation. 

We define self-help materials as comprehensive behavioral programs for 

smoking cessation that do not require attendance at treatment sessions (in 

person or via telephone). Such programs can take the form of written materials, computerized programs, or audio-visual programs. Self-help materials 

can be delivered alone or as part of a set of intervention components that 

comprise “minimal interventions.” Examples of minimal intervention packages include self-help materials along with proactive telephone counseling, 

with pharmacotherapy, or with face-to-face treatment sessions. 

There are several intuitively appealing features of self-help materials. As 

noted above, the materials can package components of intensive interven

tions for broad reach into the population. Such materials are relatively low 

cost to disseminate in a variety of settings. Self-help materials can be tai

lored or customized for different target groups, and users of self-help materials can tailor the program recommendations to their own specific needs. 

Self-help materials can be kept and reused for multiple quit attempts. 

Finally, the majority of smokers prefer less intensive self-help approaches 

(Fiore et al., 1990). 

This brief report examines the current state of knowledge regarding the 

rates of use for self-help materials among the general smoking population 

and the impact of self-help materials on smoking cessation attempts and on 

the achievement rates of smoking cessation success. 

179
Smoking and Tobacco Control Monograph No. 12 

UTILIZATION OF SELF- Key national surveys of tobacco use and cessation— 

HELP MATERIALS including the 1986 Adult Use of Tobacco Survey and the 

past and current Behavioral Risk Factor Surveys—do not assess the use of 

self-help materials. Nor did the Fiore et al. (1990) analysis of assisted and 

unassisted methods of cessation include a specific reference to self-help 

materials. The 1986 version of the Cancer Control Supplement to the 

National Health Interview Survey did ask current smokers whether they had 

ever tried to stop smoking by following instructions in a book or pamphlet, 

but these data have not been published (Office on Smoking and Health, 

personal communication, 1998). 

Data on use of self-help materials alone and in combination with other 

interventions (e.g., counseling, nicotine replacement, etc.) are available 

from the 1996 California Tobacco Survey for adults. Among adults age 25 

and older who were daily smokers 12 months prior to the survey and who 

had made a quit attempt in the past 12 months, 2.5 ± 0.7 percent reported 

using self-help materials alone and 9.3 ± 1.3 percent reported using them 

alone or in combination with some other cessation method (Table 7-1). 

These rates of use are higher than for counseling, but lower than the rates 

for nicotine gum or patch, particularly gum or patch used either alone or in 

combination with other methods. There appear to be some differences in 

rates of use by age, with a lower proportion of younger smokers (ages 18-24, 

data not shown) reporting the use of self-help methods, either alone or in 

combination. Female smokers were slightly more likely than males to use 

self-help approaches in combination with other methods, and Asian/Pacific 

Islander smokers were slightly less likely to use self-help approaches. 

Otherwise, there were few differences by age or race/ethnicity. There was a 

modest increase in the use of self-help approaches among higher educated 

and higher income groups (with the exception of those earning $75,000 or 

more). Figure 7-1 shows abstinence rates at the time of the survey for adult 

smokers who reported using either no cessation method or using counsel

ing, patch, gum, or self-help alone or in combination with another method. 

Self-help, patch, and gum, when used in combination with other methods, 

had significantly higher rates of being quit at the time of the survey, but 

the differences in being quit for 3 or more months were not statistically sig

nificant, possibly due to the small number of observations. 

Table 7-2 presents the current smoking or cessation status at the time of 

the survey for those who were daily smokers 1 year prior to the survey and 

who made a cessation attempt. Cessation and smoking status are presented 

by the method used. Although the confidence intervals on these observa

tions are too broad to draw statistically significant interpretations, the frac

tion of those who made a quit attempt and who are still quit at the time of 

the survey among those reporting that they used self-help methods alone is 

only slightly higher than that for those who reported using no method at 

all. The use of gum alone, self-help in combination with counseling or 

patch or gum, and patch or gum in combination with self-help or counsel

ing were all associated with a higher rate of being still quit at the time of 

the survey. There is a suggestion that self-help used in combination with 

patch, gum, or counseling may be more effective than self-help methods 

180
Chapter 7

Samp 

Size 

(n) 

2,680 

1,377 

1,303 

1,661 

803 

216 

1,930 

332 

185 

135 

98 

0 

312 

903 

887 

578 

264 

354 

398 

605 

452 

377 

230 

Pop 

Size 

(N) 

1,266,663 

707,535 

559,127 

797,986 

365,166 

103,509 

806,518 

224,058 

111,550 

70,309 

54,227 

0 

299,599 

364,834 

359,691 

242,537 

156,924 

187,040 

190,339 

271,517 

200,708 

148,285 

111,848 

0.3 0.5 

0.5 

0.5 

0.4 

0.4 

0.7 

2.3 

0.8 

0.5 

0.9 

1.3 

1.0 

1.1 

0.7 

0.9 

0.7 

0.7 

± CI 

Unknown 

. 

. 

. 

. 

. 

Combination of Aids** 

0.7 0.6 

0.7 

0.9 

0.3 

0.7 

0.4 

2.1 

1.0 

0.5 

1.1 

1.2 

0.7 

0.8 

0.6 

0.7 

0.4 

0.4 

. 

. 

. 

. 

. 

% 

Nic Patch 

1.8 2.3 

2.9 

2.0 

3.5 

7.5 

2.1 

4.0 

4.9 

6.1 

11.1 

4.8 

2.9 

3.2 

4.2 

4.7 

4.5 

4.3 

4.1 

5.0 

5.5 

5.7 

± CI 

or Gum 

. 

Aids Used by Those Who Made a Cessation Attempt in the Last Year*—California Tobacco Survey, 1996 

21.0 19.2 

23.4 

18.2 

24.1 

32.5 

25.1 

13.2 

11.4 

15.5 

20.7 

15.8 

22.3 

20.4 

26.5 

14.8 

18.2 

14.9 

23.8 

23.9 

29.9 

21.5 

. 

% 

Self-Help 

Materials 

1.3 1.7 

1.9 

1.7 

2.6 

4.8 

1.4 

2.9 

4.1 

3.9 

6.5 

3.0 

2.2 

2.1 

2.7 

3.3 

2.7 

2.9 

2.9 

4.1 

2.8 

4.0 

± CI 

. 

10.0 

10.7 

12.0 

10.4 

13.5 

9.3 8.0 

11.0 

9.0 

9.1 

9.7 

7.6 

5.9 

7.2 

9.2 

9.8 

11.3 

6.9 

6.4 

9.7 

6.9 

9.7 

. 

% 

Counseling 

1.1 1.4 

1.6 

1.2 

2.6 

3.8 

1.1 

3.0 

4.9 

6.4 

4.7 

3.1 

1.9 

1.8 

2.5 

4.0 

3.2 

2.0 

2.6 

3.1 

3.2 

2.5 

± CI 

. 

*Those 25+ years of age who have made a quit attempt in the past year and were daily smokers 1 year ago. 

7.1 5.6 

8.9 

6.0 

9.2 

7.7 

6.8 

6.5 

9.5 

8.0 

7.4 

8.3 

6.0 

6.7 

7.7 

8.3 

6.8 

4.5 

7.6 

8.6 

7.7 

5.2 

. 

% 

0.8 1.0 

1.4 

0.9 

1.5 

5.1 

1.1 

1.8 

2.2 

2.9 

8.3 

2.0 

1.0 

1.0 

2.4 

2.5 

1.8 

1.1 

1.5 

1.7 

3.6 

3.9 

± CI 

Nicotine 

. 

Gum 

3.3 2.7 

3.9 

2.7 

3.6 

6.6 

3.5 

2.5 

2.4 

2.9 

4.6 

3.3 

2.1 

2.8 

5.5 

3.2 

2.6 

1.8 

2.9 

3.3 

5.4 

4.8 

. 

% 

0.8 1.1 

1.2 

0.8 

1.8 

2.8 

1.1 

1.6 

4.1 

2.1 

1.4 

1.5 

1.6 

1.6 

1.9 

1.8 

1.8 

2.2 

2.1 

2.5 

2.9 

± CI 

Nicotine 

. 

. 

Patch 

**Combination includes use of the method alone or with any other method. 

4.6 4.7 

4.4 

3.9 

5.7 

6.3 

6.1 

2.0 

5.7 

1.8 

2.1 

6.1 

5.2 

4.6 

1.8 

3.7 

3.6 

6.0 

5.4 

6.6 

4.4 

. 

. 

% 

Single Aid Only 

± CI 

0.7 1.0 

1.1 

0.9 

1.0 

1.8 

0.7 

1.6 

2.6 

2.4 

2.5 

1.2 

1.0 

1.2 

1.5 

1.5 

1.3 

1.7 

1.3 

2.0 

1.2 

2.3 

Self-Help 

Materials 

. 

2.5 2.4 

2.7 

2.9 

2.0 

1.3 

2.6 

2.0 

3.6 

2.2 

1.3 

1.5 

2.7 

2.6 

3.4 

1.9 

1.9 

3.1 

2.5 

3.6 

1.2 

3.4 

. 

% 

Counseling 

0.7 0.8 

1.1 

0.9 

1.4 

0.8 

0.6 

2.1 

2.9 

4.1 

4.2 

2.5 

0.6 

0.7 

0.8 

2.7 

2.1 

0.7 

1.4 

1.5 

2.4 

0.7 

± CI 

. 

Household Income (Dollars) 

1.7 1.3 

2.2 

1.9 

1.7 

0.4 

1.2 

2.7 

1.8 

2.6 

2.9 

3.8 

1.1 

1.0 

1.0 

3.0 

2.5 

0.6 

1.5 

1.6 

2.3 

0.4 

. 

% 

2.0 2.7 

3.4 

2.1 

4.2 

7.7 

2.2 

4.6 

6.2 

7.7 

13.7 

5.6 

3.1 

3.7 

4.8 

5.3 

4.9 

4.4 

4.4 

5.7 

5.6 

6.4 

± CI 

. 

None 

Education (Years) Race/Ethnicity 

72.3 75.2 

68.5 

74.6 

69.3 

64.3 

NH White 68.4 

80.6 

79.5 

77.9 

72.5 

77.2 

72.0 

71.9 

67.1 

78.2 

76.3 

78.5 

69.7 

66.9 

64.9 

Unknown 71.9 

. 

% 

Total Gender Male 

Female 

Age (Years) 25–44 

45–64 

65+ 

Hispanic 

Afric-Am 

Asian/PI 

Nativ Am 

Table 7-1 

Other 

<12 

13–15 

16+ 

≤10K 

12 10-20K 

20-30K 

30-50K 

50-75K 

>75K 
Smoking and Tobacco Control Monograph No. 12 

Figure 7-1 

Current Cessation Status at Time of Survey by Method Used among Those Who Were 

Daily Smokers 1 Year prior to the Survey and Who Made a Quit Attempt, Ages 25+, 

1996 CTS 

0

10

15

20

25

30

35

40

Quit 

3+ Months

Quit 

at Survey

Patch/Gum 

Combination

Counseling 

Combination

Self-help 

Combination

None

Cessation Method

Percent Quit

Table 7-2 

Current Smoking and Cessation Status by Method of Cessation Used* 

Current Smoker w/Quit Attempt Former Smoker of Pop Samp 

Daily Occasional Any Quit Length Size Size 

% CI % CI % CI (N) (n) 

Total 71.79 2.09 7.56 1.21 20.65 1.90 1,266,663 2,680 

Single Aid Only 

None 74.59 2.30 8.35 1.60 17.06 2.20 915,186 1,886 

Counseling Only . . 3.79 5.39 . . 21,538 38 

Self-Help Only 73.04 9.63 6.48 5.66 20.48 8.88 32,124 74 

Patch Only 67.11 8.17 6.49 4.06 26.40 8.04 58,422 142 

Gum Only 57.49 14.99 8.00 6.32 34.52 14.16 41,251 92 

Aids in Combination 

Counseling** 71.81 7.11 3.32 2.55 24.87 7.16 89,356 189 

Self-Help** 69.06 6.22 4.34 3.07 26.60 6.08 117,871 260 

Patch/Gum** 62.62 4.87 5.68 1.76 31.71 4.51 266,595 612 

Unknown . . . . . . 8,549 16 

*Those 25+ years of age who have made a quit attempt in the past year and were daily smokers 1 year ago. 

**Combination includes use of the method alone or with any other method. 

Source: California Tobacco Survey, 1996 

182 
Chapter 7 

used alone. In contrast, there is no trend suggesting that the addition of 

self-help or counseling methods improves the percentage of gum users who 

are quit at the time of the survey. These data suggest that, if self-help materials are used, they should be used as one component of a multi-component 

cessation intervention. 

Unpublished data from a study conducted at the Group Health 

Cooperative (Curry et al., 1995) provide some population-based data on uti

lization of self-help materials. In this study, a total of 1,137 smokers were 

identified from a population-based survey of over 5,900 adults (response 

rate 74 percent). Smokers were asked the following question, “Have you 

ever tried self-help quit smoking books, pamphlets or guides?” Overall, 3 

percent indicated that they were currently using one, 28 percent said they 

had used them in the past, and 69 percent said that they had never tried a 

self-help guide. Rates of use differed by gender, with women reporting sig

nificantly more current (4 percent versus 2 percent) and past (32 percent 

versus 24 percent) use than men. 

Population-based estimates of the proportion of smokers who say they 

have used self-help materials do not provide insight into what the smokers 

actually do with the books or guides when they have them. Because selfhelp materials can be easily disseminated, it may be of particular interest to 

examine rates of use and the impact of materials in smokers who voluntari

ly request materials compared to those who receive the materials through 

population-based outreach efforts. A recent publication from our research 

program (McBride et al., 1998) examined the use of self-help materials and 

smoking cessation among proactively recruited and volunteer intervention 

participants. The study used data from two separate randomized trials that 

used the same self-help manual as one of the treatment arms (Curry et al., 

1991 & 1995). As expected, volunteer smokers were significantly more like

ly to read the self-help materials and to complete any activities than were 

nonvolunteer smokers (84 percent versus 33 percent read materials, respec

tively; 49 percent versus 13 percent completed activities, respectively). 

Baseline variables that predicted use of the self-help materials (with use 

defined as reading at least half of the materials and completing any recom

mended activities) for the volunteer smokers were whether participants 

reported any prior quit attempts and a strong desire to quit smoking. Desire 

to quit smoking also predicted use among nonvolunteers, as did higher 

education level. 

McBride and colleagues also tested for associations between using the 

self-help materials and outcomes at a 12-month follow-up. These prospec

tive analyses examined whether reported use of the self-help manual at 3 

months predicted quit attempts or abstinence when assessed at 12 months. 

In both the volunteer and nonvolunteer samples, self-reported use of the 

self-help manual at 3 months was associated with a higher likelihood of 

reporting 24-hour quit attempts at the 12-month follow-up. Use of the 

materials did not predict 12-month prevalent abstinence in either sample. 

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Smoking and Tobacco Control Monograph No. 12 

IMPACT OF SELF-HELP The Cochrane Tobacco Addiction Review Group is comMATERIALS ON pleting a meta-analysis of self-help interventions for 

SMOKING CESSATION smoking cessation (Lancaster and Stead, 1999). They 

examined a total of 39 randomized clinical trials with a minimum of 6 

months of follow-up. The studies were selected if they had at least one arm 

that included a self-help intervention without repeated face-to-face thera

pist contact. The target outcome is long-term abstinence, defined as either 

6-month sustained abstinence or two consecutive point-prevalent absti

nence reports. 

Five hypotheses guided the review: 

• Self-help interventions are better than no treatment. 

• Self-help interventions are equivalent to more intensive behav

ioral interventions and to pharmacotherapy. 

• Different forms of self-help materials (written, audio, video) 

have equivalent effects. 

• Adjuncts such as computer-generated feedback, telephone hotlines, and pharmacotherapy increase effectiveness. 

• Approaches tailored to the individual are more effective than 

nontailored materials. 

Self-help interventions are defined as “any manual or program to be 

used by individuals to assist a quit attempt not aided by health profession

als, counselors, or group support.” The review group also distinguished tai

lored from personalized materials, with tailored materials defined as those 

“...prepared for and targeted at particular groups of smokers (e.g., over 60, 

stage of readiness to change)” and personalized materials defined as those 

“...adapted for characteristics of individual smokers based on questionnaire 

responses.” 

Data were not available to address all of the review hypotheses. Tables 

7-3 and 7-4 summarize the odds ratios and confidence intervals for several 

comparisons related to the self-help versus no self-help hypotheses and to 

the impact of enhancements to self-help. Among the key conclusions from 

the Cochrane analysis are: 

• There is little evidence that self-help materials, used on their 

own, were an effective means of aiding smoking cessation. 

• Tailoring materials to the perceived needs of broadly defined 

groups did not have an effect. 

• Personalizing materials to the individual appeared to have an 

effect. However, there is insufficient evidence regarding the spe

cific elements of personalization that may be important. 

• Increasing the intensity of self-help interventions via telephone 

counseling increases quit rates. 

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Chapter 7 

Table 7-3 

Preliminary Results from Cochrane Tobacco Addiction Review Group Meta-Analysis of SelfHelp versus No Self-Help 

Comparison Peto OR [95% CI] 

Neither group face-to-face (n = 9) 1.05 [0.87-1.26] 

Both groups face-to-face (n = 4) 1.21 [0.97-1.52] 

Both groups face-to-face with advice (n = 10) 0.95 [0.78-1.18] 

Self-help vs. no self-help overall (n = 23) 1.06 [0.94-1.20] 

Table 7-4 

Preliminary Results from Cochrane Tobacco Addiction Review Group Meta-Analysis of 

Enhancements to Self-Help 

Comparison Peto OR [95% CI] 

Additional written materials (n = 4) 1.02 [0.85-1.22] 

Additional video (n = 2) 0.70 [0.38-1.31] 

Tailored versus standard (n = 2) 1.14 [0.71-1.83] 

Personalized versus standard (n = 6) 1.55 [1.16-2.07] 

Additional phone follow-up (n = 6) 1.81 [0.67-1.31] 

Self-help + NRT versus NRT only (n = 2) 0.84 [0.67-1.31] 

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Smoking and Tobacco Control Monograph No. 12 

GENERAL CONCLUSIONS Despite their intuitive appeal and positive results in 

individual studies, meta-analytic results strongly indicate that self-help 

materials for smoking cessation have not demonstrated significant advan

tages over no-treatment control groups. In contrast to the discouraging 

results from comparing self-help to no self-help interventions, there are 

promising effects for minimal intervention programs that include personal

ization of printed intervention messages and for providing self-help materi

als along with supportive telephone counseling. Thus, although self-help 

materials may not significantly increase quit rates when used alone, they 

are so commonly a core component of minimal interventions that have 

been demonstrated to be effective that they may be a necessary component 

of these programs and may be useful for effectively delivering the personal

ized and/or telephone counseling components of minimal interventions. To 

date, however, there are no randomized trials evaluating the impact of selfhelp adjuncts such as personalized feedback or telephone counseling with 

and without comprehensive self-help materials. 

Self-help materials have been evaluated with both volunteer and proac

tively recruited (i.e., nonvolunteer) samples of smokers. As more nonvolun

teer, population-based studies are completed, the evidence suggests that 

simply distributing self-help materials to the general population of smokers 

is unlikely to significantly increase rates of cessation. It is noteworthy that, 

in many of these studies, the intervention group achieved the target quit 

rate (i.e., the proportional outcome used to determine sample size and sta

tistical power). The null results were due to equally impressive quit rates in 

the no-treatment control groups. One interpretation of this pattern is that 

the assessment components of these population-based studies have as large 

an intervention effect as the minimal intervention protocols being evaluat

ed. 

Despite the lack of empirical support for the effect of self-help materi

als, it would be premature to recommend against their further dissemina

tion. The meta-analyses summarized in this report do not address impor

tant questions such as whether health care providers are more likely to 

advise their patients to quit smoking if they have written self-help materials 

to distribute or whether worksites are more likely to adopt and enforce nonsmoking policies if they can make self-help materials available to their 

employees who smoke. Ultimately, we need to examine and appreciate the 

potential value of self-help materials in the broader context of the social 

and organizational components of population-based strategies for smoking 

cessation. 

186
Chapter 7 

REFERENCES


Abrams, D.B., Emmons, K., Niaura, R.D., Goldstein, 

M.G., Sherman, C. Tobacco dependence: An 

integration of individual and public health per

spectives. In The Annual Review of Addictions 

Treatment and Research (Vol. 1), P.E. Nathan, J.W. 

Langenbucher, B.S. McCrady and W. 

Frankenstein (editors). Elmsford, NY: Pergamon 

Press, 1991. 

Curry, S.J. Self-help interventions for smoking cessa

tion. Journal of Consulting and Clinical Psychology 

61: 790–803, 1993. 

Curry, S.J., McBride, C., Grothaus, L.C., Louie, D., 

Wagner, E.H. A randomized trial of self-help 

materials, personalized feedback and telephone 

counseling with non-volunteer smokers. Journal 

of Consulting and Clinical Psychology 

63:1005–1014, 1995. 

Curry, S.J., Wagner, E.H., Grothaus, L.C. Evaluation 

of intrinsic and extrinsic motivation interven

tions with a self-help smoking cessation program. Journal of Consulting and Clinical Psychology 

59:318–324, 1991. 

Fiore, M.C., Novotny, T.F., Pierce, J.P., Giovino, G.A., 

Hatziandreu, E.J., Newcomb, P.A., Surawics, T.S., 

Davis, R.M. Methods used to quit smoking in the 

United States: Do cessation programs help? 

Journal of the American Medical Association 

263:2760–2765, 1990. 

Lancaster, T., Stead, L.F. Self-help interventions for 

smoking cessation (Cochrane Review). In: The 

Cochrane Library, Issue 2, 1999. Oxford: Update 

Software. http://www.update-software.com/ 

ccweb/cochrane/revabstr/ab001118.htm 

Lichtenstein, E., Glasgow, R.E. Smoking cessation: 

What have we learned over the past decade? 

Journal of Consulting and Clinical Psychology 

60:518–527, 1992. 

McBride, C.M., Curry, S.J., Grothaus, L.C., Rosner, 

D., Louie, D., Wagner, E.H. Use of self-help 

materials and smoking cessation among proac

tively recruited and volunteer intervention par

ticipants. American Journal of Health Promotion 

12(5):321–324, 1998. 

187
Telephone Quitlines for 

Smoking Cessation 

Shu-Hong Zhu 

Telephone counseling programs have attracted increasing interest in 

recent years as an alternative system for delivering smoking cessation services. The convenience of telephone counseling encourages program participation, which has been a significant barrier for formal treatment programs 

(Fiore et al., 1991; Lichtenstein and Hollis, 1992). Telephone quitlines can 

also be centralized; for example, one toll-free number can provide most cessation services to smokers in even a large state. This makes it easier and 

more cost-efficient to promote the services in a large public health campaign. 

Telephone counseling can be reactive or proactive. In reactive counseling, the smoker initiates all calls and talks with the counselor about specific 

issues of current concern. In proactive counseling, the counselor calls the 

smoker and provides counseling in a systematic manner, with scheduled 

sessions similar to traditional cessation clinics. Of course, a telephone quitline can be both reactive and proactive, taking calls from smokers who need 

immediate service and following up with those who need more intensive 

treatment. 

We will outline the strengths of telephone quitlines, review the extent 

of their usage, and evaluate the empirical evidence for their efficacy. We 

will also discuss potential uses of the telephone quitline as support for 

physicians’ advice to quit smoking and as an adjuvant for nicotine replacement therapy (NRT). 

THE STRENGTHS OF Compared to traditional cessation clinics or classes, a 

TELEPHONE QUITLINES telephone quitline has several advantages. It reduces 

barriers tied to the logistics of attending cessation classes, including having 

to wait for classes to form, time away from home to attend class, and the 

effort and expense of arranging for transportation and childcare. A quitline 

enables smokers to get help without leaving home and allows them to 

receive counseling at a time convenient for them, thus making the service 

more accessible. This is particularly helpful for those whose mobility is limited or who live in rural or remote areas. One study shows that, when 

offered the choice between group sessions and a telephone quitline, 70 percent of smokers chose the telephone quitline (McAfee et al., 1998). 

The telephone format appeals to those who are reluctant to get help 

face-to-face, especially in group settings. More importantly, it allows the 

counselor to proactively follow up on the smokers, thus addressing the 

problem of high attrition rates (Lichtenstein and Hollis, 1992). A proactive 

calling procedure can significantly reduce dropouts. One study shows that a 

189

Smoking and Tobacco Control Monograph No. 12 

change from reactive counseling to proactive counseling reduced the attrition rate from 65 to 25 percent, which in turn was accompanied by a significant increase in quit rate (Zhu et al., 1998a). 

A principal strength of telephone quitlines, in the context of a population-based smoking cessation, is that they can utilize one centralized operation site to provide multiple services. The centralized service makes it easy 

for the quitline to be promoted in a coordinated public health campaign. It 

is more cost efficient and probably more effective to promote a single telephone number than to promote multiple programs, especially in cases 

where the promotion of cessation programs is fused with a comprehensive 

anti-smoking media campaign. For example, media spots can be tagged 

with the toll-free number of a quitline statewide. 

THE USE OF TELEPHONE Telephone quitlines can have many uses and can take 

QUITLINES many forms, such as: 

• an information resource to distribute cessation materials 

(Anderson et al., 1992; Cummings et al., 1993); 

• a recorded telephone message (Dubren, 1977; Burke, 1993; 

Ossip-Klein et al., 1991 & 1997; Schneider et al., 1995); 

• a relapse prevention mechanism to support those who have finished a cessation program (Colleti and Supnick, 1980; Danaher, 

1977; Lando et al., 1996); 

• a supplement to printed interventions (Prochaska et al., 1993); 

• an adjuvant treatment for nicotine replacement therapy (Lando 

et al., 1997; Shiffman et al., 1997; Zhu et al., 1998b); 

• a component of a preventive medicine program wherein telephone calls are combined with face-to-face interaction with 

clinical staff (DeBusk et al., 1994; Ockene et al., 1994; Taylor et 

al., 1990); or 

• the primary intervention in which the counselor provides individualized telephone counseling to those who are ready to quit 

smoking (Orleans et al., 1991; Zhu et al., 1996a & b). 

One quitline can have several functions, of course, as has been demonstrated in several projects (Wakefield and Miller, 1997; Zhu et al., 1998a). 

In the last 5 years there has been a proliferation of telephone quitline 

services, most of them with a population orientation. Some are statewide 

(Altamore, 1998; Zhu, 1996a & b), some are regional (McCabe and Crone, 

1997; Platt et al., 1997), and some are national quitlines (Peters, 1995; 

Wakefield and Miller, 1997; Zeeman, 1997). The following describes three 

large projects, each with a different emphasis, but all of them using mass 

media to motivate smokers to call. 

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Chapter 8 

National Quitline As part of the National Quit Campaign in Australia, which 

in Australia targeted smokers aged 18-40 years, a quitline number was 

attached to television ads, radio spots, and other promotional materials 

across the nation. One phone number was advertised; but when smokers 

called, they reached different regional call centers. To ensure that most of 

the smokers’ calls were answered, some of the regional centers employed a 

telemarketing service to answer the first call. The main service of the quitline was to provide a self-help quit pack. However, those who requested further service were transferred to counselors (Wakefield and Miller, 1997). 

In the first year of operation, the Quitline received 144,000 calls, representing 4 percent of all Australian smokers of age 18 or older. 

Approximately one-fifth of the callers were within the 18- to 40- year target 

age group. This large volume of smokers’ request for cessation service in a 

limited campaign period challenges the belief that most smokers simply 

will not seek help (Chapman, 1985). Similar success of a coordinated promotion of telephone quitlines has been reported in England, where over 

500,000 calls reached the quitline in 1 year (McCabe and Crone, 1997), and 

in Scotland, where approximately 8 percent of all smokers called the quitline in 1 year (Platt et al., 1997). 

A population-based approach to smoking cessation emphasizes that 

interventions work best when they are combined instead of standing alone 

(Fishbein, 1998). A quitline, when coupled with an aggressive media campaign, may impact more than just those people who call (Ossip-Klein et al., 

1991). The Quitline in Australia, for example, is one component of a comprehensive, nationwide campaign designed to encourage people to quit 

smoking (Wakefield and Miller, 1997). The presence of the Quitline makes 

the campaign complete. A single quitline number was shown repeatedly in 

different media spots, sending a clear message to smokers that if they want 

to quit, help is only a phone call away. 

Quit 4 Life Program The Quit 4 Life Program was a national campaign in 

for Teen Smokers Canada that targeted smokers aged 15–19 years. The campaign encouraged teen smokers to quit smoking by calling an 800-number, 

through which they received a self-help quit kit in the form of a paper or 

compact disc (CD). The program was promoted through mass media and 

was in operation for about 3 years. Between 1993 and 1995, nearly 98,000 

teenage smokers called, representing almost 20 percent of all smokers targeted for this campaign (Peters, 1995). This result is very encouraging, 

given that teenage smokers are known not to attend cessation programs 

(U.S.DHHS, 1994). No counseling was provided through this project, but a 

year-long evaluation shows that 92 percent of those who received the quit 

kit used it, at least to some extent. A pre-post comparison based on selfreport shows that 77 percent reduced the number of cigarettes smoked and 

20 percent achieved a significant period of abstinence as measured by “quitting for 3 months” or “not smoking at both points of evaluation at 6 and 

12 months” (Peters, 1995). 

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Smoking and Tobacco Control Monograph No. 12 

California Smokers’ The California Smokers’ Helpline is a statewide cessation 

Helpline service that began in 1992 and is still in operation. No age 

group has been specifically targeted, although the media spots to which the 

Helpline’s numbers were tagged have been mostly for adults. A major effort 

was made to reach smokers of minority ethnic backgrounds. The Helpline is 

currently also testing a counseling protocol for teen smokers. 

The Helpline takes a stepped-care approach by providing three levels of 

cessation service according to smokers’ readiness to change and their preference for intensity of treatment: 

1) Motivational materials for smokers who are contemplating quitting but not yet ready to take action; 

2) Self-help quit kits for those who are ready to quit but prefer to 

do it themselves with the materials; and 

3) Comprehensive proactive counseling for those who are quitting 

soon and want the counseling. 

In addition, the Helpline provides smokers with a list of local cessation 

programs. It also serves as the primary source of adjuvant behavioral support for smokers who receive free nicotine replacement treatment (NRT) 

paid for by Medi-Cal (California’s version of Medicaid). All Helpline services 

are provided in six languages—English, Spanish, Mandarin, Cantonese, 

Vietnamese, and Korean (Zhu, 1996). 

The California Smokers’ Helpline places emphasis on integrating its 

activities into the comprehensive tobacco control program in California, 

rather than on getting a large number of smokers to call the program 

(although over 80,000 smokers have called the Helpline). The anti-smoking 

media campaign in California is multi-tracked and has evolved over time. 

Media spots for cessation have a relatively small share of the overall campaign budget. Although mass media has been the chief mode of promotion 

for the California Smokers’ Helpline, a major effort is also made to encourage local tobacco education groups to promote the Helpline. In 6 years of 

operation, the media campaigns generated about half of all the Helpline’s 

calls. The rest came from other sources, including referrals from various 

local tobacco control programs, health care providers, and simple word of 

mouth. More recently, with counseling now available for teens, an effort is 

being made to promote the Helpline among school systems statewide. 

EFFICACY OF Telephone counseling has been tested in a variety of settings, with 

TELEPHONE diverse populations including hospital patients (DeBusk et al., 

QUITLINES 1994; Ockene et al., 1994), HMO insurees (Orleans et al., 1991; 

Curry et al., 1995), and smokers in the community at large (Ossip-Klein et 

al., 1991; Zhu et al., 1996a & b). 

Reactive Quitlines There is an inherent difficulty in evaluating the efficacy of a 

reactive telephone quitline because it requires a control group that is not 

aware of the existence of the quitline. Ossip-Klein and her colleagues (1991) 

conducted a large trial on the effect of a reactive telephone quitline. Ten 

rural counties were randomized into two conditions; one group received 

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Chapter 8 

self-help materials only, and the other group received the same materials 

plus an offer to access a telephone hotline. A total of 1,813 smokers were 

recruited into the study and assigned to these two groups—approximately 4 

percent of the total number of smokers in these counties. The quitline condition included a recorded message and a session with a counselor. At the 

end of 12 months, the quitline condition produced higher biochemically 

confirmed quit rates (quit rates for 90+ days are 12.1 percent and 7.6 percent for the two conditions, respectively) than the self-help condition. 

Most subjects in the quitline condition did not actually call: 36 percent 

did call, but only 9 percent spoke with the counselors; the rest of the callers 

listened to the recorded messages. The difference in success between the 

groups cannot be completely attributed to the increased quit rate among 

the 9 percent who spoke with the counselors, suggesting that simply knowing a quitline is available and/or calling to listen to recorded messages 

might be beneficial. One possible explanation is that knowing they could 

call for help if needed may have caused smokers in the quitline condition 

to be more confident about quitting, leading to a greater attempt rate, 

which in turn translated into a greater long-term quit rate. This is conjecture, and no data were available in the study with regard to changes in selfefficacy. However, the attempt rate was greater for the quitline condition. 

Proactive Quitlines A number of randomized trials for proactive telephone 

counseling have been conducted and have produced varying results. The 

studies differed in several major aspects, including the number of counseling sessions (ranging from one to nine sessions), the schedule of these sessions (weekly, monthly, or by relapse probability), and the supervision and 

quality control provided for the counseling. Two features seem to be associated with lack of effect for counseling: one is if the smokers are not voluntary participants; the other is if the telephone counseling is used only as a 

secondary follow-up treatment for subjects who have already gone through 

an intensive cessation treatment. These two types of studies tend to find no 

significant effect for telephone counseling. 

A meta-analysis that combined 13 randomized trials (including all nonsignificant-effect studies) shows proactive counseling to have an effect that 

is statistically significant but modest in size. The combined odds ratios are 

1.34 for short-term effect (95% CI = 1.19-1.51) and 1.20 for long-term effect 

(95% CI = 1.06-1.37) (Lichtenstein et al., 1996). 

Three studies that used proactive telephone counseling as the primary 

intervention method found larger effects. One study recruited hospitalized 

patients with myocardial infarctions (Taylor et al., 1990). At the 12-month 

follow-up, the helpline condition produced a 61 percent cessation rate compared to 32 percent in the control group. Another study recruited HMO 

insurees and found a 21.5 percent cessation rate in the counseling group 

compared to 13.7 percent in the control group at the 18-month follow-up 

(Orleans et al., 1991). 

One study of proactive telephone counseling was conducted in the general population (Zhu et al., 1996a). Smokers were recruited from the general 

community. Two levels of counseling were tested, single session and multi193

Smoking and Tobacco Control Monograph No. 12 

Figure 8-1 

Relapse Curves for Self-Help (SH), Single Counseling (SC), and 

Multiple Counseling (MC) 

0

20

40

60

80

100

Self-Help

Single Counseling

Multiple Counseling

30 60 90 120 150 180 210 240 270 300 330 360

Days after Quitting

Percent Abstinent

Source: Zhu et al., 1996a 

ple session, against a self-help group in a randomized design. Evaluation of 

the effect of a single session is valuable for real-world applications because 

smokers often use the quitline once and then drop out of the process. Thus, 

it is important to examine whether single session counseling can be effective, as budgetary concerns may prevent the quitline staff from continuing 

to call those who drop out of the process. This study also made a major 

effort to document the whole counseling process, both the single and multiple sessions, for the purpose of quality control as well as for future replication (Zhu et al., 1996b). 

Both single and multiple counseling were effective, and there was a 

dose-response relationship between the intensity of treatment and the longterm effect (see Figure 8-1; the 12-month success rates are 14.7 percent, 19.8 

percent, and 26.7 percent for self-help, single counseling, and multiple 

counseling, respectively). A recent evaluation of the California Smokers’ 

Helpline, which used the multiple counseling protocol, replicated the earlier result (26.9 percent in Zhu et al., 1998a). 

194

Chapter 8 

AN AREA FOR SYNERGY: A potential area for synergy among various approachTELEPHONE QUITLINE es to smoking cessation is to use telephone counseling 

AS A SUPPORT FOR as support for physician advice, as an adjuvant treatPHYSICIAN ADVICE AND ment for NRT, or both. Physician advice to quit smokADJUVANT TREATMENT ing is a potentially important population-based 

FOR NRT approach to smoking cessation because most smokers 

see their physicians at least once a year (Hollis, 1998; Ockene, 1987; and see 

Chapter 4). The Agency for Healthcare Research and Quality (AHRQ) guidelines recommend that physicians ask about their patients’ smoking status at 

every visit, advise every smoker to quit, and prescribe NRT for every quit 

attempt in the absence of major medical contraindications. The guidelines 

further suggest that physicians should help their patients formulate a quit 

plan, provide supplementary materials, and schedule a follow-up session to 

be conducted either in person or via telephone (Fiore et al., 2000). 

In practice, however, physicians may prescribe NRT but not provide any 

follow-up counseling for various reasons. They may feel unprepared to provide behavioral counseling (Cummings et al., 1987; Lindsay et al., 1994). Or 

they may think that advising their patients to quit and prescribing NRT are 

sufficient. Even if they wish to counsel their patients on how to quit smoking, time constraints generally limit their ability to do so (Humire and 

Ward, 1998; Thorndyke et al., 1998). Providing follow-up counseling takes 

even more time. These barriers may be part of the reason for differences 

between long-term successful cessation demonstrated in multiple researchbased physician intervention trials and the absence of an effect of physician 

advice to quit on long-term cessation success found in the 1996 California 

Tobacco Survey (See Chapter 4). What physicians can easily do, however, is 

refer their patients out for cessation counseling. 

Telephone counseling is a good referral choice for physicians to use for 

their patients, for two reasons mentioned at the beginning of this paper. 

One is that smokers are more likely to use a telephone quitline than to 

attend face-to-face group sessions (McAfee et al., 1998). The second reason 

is that once smokers enroll in a quitline, the telephone counselor can 

proactively call them for the follow-up sessions to prevent early dropout 

(Zhu, 1996). As the impact of an intervention over a population is a product of how many people enroll and what percentage of them finish the program, the telephone quitline is expected to have a greater overall effect on 

the population in question than face-to-face group sessions. 

When physicians realize that smokers are following up with their referral to cessation programs, their referral behavior will be reinforced. One way 

to help physicians know the outcome of their referrals is to send a progress 

report of the smoking patients back to their providers (with smokers’ permission). This can be accomplished quite easily if the quitline is set up 

within a group health setting. This is indeed the case with the Group 

Health Cooperative (GHC) at Puget Sound, which has developed a systematic approach to using telephone counseling as a support for physician 

advice and as an adjuvant treatment for NRT (Curry et al., 1998; McAfee et 

al., 1998). The quitline services have been an important behavioral treat195

Smoking and Tobacco Control Monograph No. 12 

ment component in the overall smoking cessation program of GHC, as a 

majority of smokers used the telephone quitline when they wanted to 

obtain free NRT. The overall cessation program is credited with contributing 

to the accelerated decline of smoking prevalence within GHC (McAfee et 

al., 1998). 

In fact, a telephone quitline does not have to be within the health care 

system to be useful for that purpose. A study with the California Smokers’ 

Helpline shows that telephone counseling can serve as physician support 

and adjuvant treatment to NRT, even though the Helpline is not officially 

affiliated with any of the physicians who refer their patients to the program. Over 6 years of operation, the Helpline has received calls from over 

14,000 smokers who reported that their health care providers referred them 

to the program. More than 4,000 smokers also obtained NRT free of charge 

for their enrollment in the Helpline. They got free NRT because their health 

plans accepted the Helpline enrollment as a sufficient condition. Some NRT 

users dropped out of the process after they obtained the NRT, while others 

stayed with the program for more follow-up sessions. Those who received 

follow-up sessions are significantly more likely to stay abstinent in the long 

term (Zhu et al., 1998b). These data suggest that telephone counseling is a 

useful adjuvant support for both physician advice and NRT. 

CONCLUSIONS Telephone quitlines are highly accessible forms of cessation service. 

They can also be effective aids for smoking cessation. A centralized telephone quitline is easier to integrate with other population-based approaches to smoking cessation, such as mass media campaigns. The convenience 

and the proactivity associated with the telephone format makes the quitline 

a good adjuvant treatment for physician advice and nicotine replacement 

treatment. 

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Anderson, D.M., Duffy, K., Hallett, C.D., Marcus, 

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198

Mass Media in Support of 

Smoking Cessation 

Robert E. Sparks, Lawrence W. Green 

INTRODUCTION Much of what we have learned about the effect of media can 

be drawn directly from reports on California and Massachusetts cessation 

trends; the COMMIT experience; Current Population Survey trends; and 

specific studies on the combined effects of media on pricing, environmental 

bans, community programs, clinical and self-help interventions. Our objectives are: 1) to summarize key findings in this research regarding media 

effectiveness, and 2) to discuss the implications of these findings for media 

practice in support of smoking cessation. 

The mass media provide an important means for reaching and influencing smokers on a population-wide basis. Properly designed and implemented, media campaigns can be cost-effective and efficient in disseminating 

knowledge and information, realigning attitudes and social norms, and 

advocating for policy changes (Reid, 1996; Burns, 1994; Goldman and 

Glantz, 1998; Wallack and Dorfman, 1996). These roles tend to support 

each other and can have broad (“ripple out”) as well as more selective (“targeted”) social and behavioral consequences, depending on the methods and 

strategies used (mass or segmented; population- or subgroup-focused). 

For all their potential, however, media campaigns have caveats. 

Consumers today are more media-literate and more diverse in their media 

consumption patterns than in past generations. This means that there is no 

single most effective way to appeal to smokers using the media. The 

increased number of television channels, in particular, has led to more fractured and less predictable general audiences. Although this proliferation 

potentially enables better audience segmentation and targeting, it also 

entails greater complexity and possibly greater costs in reaching a large 

group. At the same time, messages within a given media campaign must be 

sensitive to and differentially targeted to differing segments of smokers if 

penetration of these special populations and widespread effects are to occur 

(Goldman and Glantz, 1998). Such segments include members of distinct 

linguistic, geographic, and cultural communities, as well as high-risk 

lifestyle groups and heavily addicted smokers. 

Evidence suggests that media campaigns are most effective at eliciting 

smoking cessation when they are part of a comprehensive program of interventions. It has been recognized that “Changes in media have been associated with major changes in smoking behavior, but only when the rest of 

the social structure actively changed the environment for the smoker. These 

changes act synergistically with media messages, and cessation or behavior 

change occurs” (Burns, 1994). Even with these caveats, mass media cam199

Smoking and Tobacco Control Monograph No. 12 

paigns can be effective in challenging people's everyday understanding of 

smoking and at stimulating positive attitudinal and behavioral changes 

with respect to smoking cessation (Reid, 1996; Flay et al., 1993; Sussman et 

al., 1994; Wallack and Dorfman, 1996). 

Media interventions supporting smoking cessation can be undertaken at 

three levels: to elicit very specific behavioral changes; to affect the determinants of such behavioral changes; and to advocate for policy changes that, 

in turn, can affect more complex behavioral changes. In each case, interventions can have predisposing, enabling, and/or reinforcing effects (Green 

and Kreuter, 1991) with respect to these targeted changes within the context of particular campaign strategies (mass or targeted) and outcome objectives (information, education, motivation, and advocacy). This paper focuses on evaluating media efficacy on the first two of these levels—eliciting 

smoking cessation behavior and influencing attitudes and opinions. The 

third level, media advocacy, is briefly discussed at the end as an extension 

of the process of influencing attitudes and opinions. Two major bodies of 

evidence are reviewed; the California and Massachusetts campaigns are 

reviewed as examples of the best campaign practices, and the Stanford FiveCity Project and COMMIT study are reviewed as the best examples of controlled community trials that used media. 

CALIFORNIA AND These well-documented campaigns were undertaken in 

MASSACHUSETTS California in 1990 (Bal et al., 1990) and in 

ANTISMOKING ADVER- Massachusetts in 1994 (Koh, 1996; Begay, 1997) with 

TISING CAMPAIGNS the dual objectives of discouraging smoking initiation 

and encouraging smoking cessation. Each campaign was accompanied by a 

tax increase on the sale of cigarettes—in 1989 and 1993, respectively— 

amounting to $0.25 per pack (although, when the tax went into effect in 

Massachusetts, the tobacco companies reduced point-of-sale prices to 1992 

pretax levels). 

Goldman and Glantz (1998) have recently analyzed the cost-effectiveness of the two media-led tobacco control campaigns and synthesized findings from the 186 focus groups (involving over 1,500 children and adults) 

that were conducted by advertising agencies to develop the message strategies for California and Massachusetts and also for a campaign in Michigan. 

During 1989-1996, per capita cigarette consumption in California fell 1.93 

packs per year faster than in the rest of the United States, and during 1993-

1996, Massachusetts consumption fell 1.28 packs per year faster. These 

declines were the result of the combined effects of the tobacco control campaigns in the two states and the increase in the cigarette costs resulting 

from the tax increase. However, Massachusetts conducted a more mediaintensive campaign. The average yearly per-capita cost for the media campaign in California was $0.50 (1996 U.S. dollars) and the per-capita cost for 

the Massachusetts campaign was $2.42 (Goldman and Glantz, 1998). 

Based on the focus group results, the most influential advertising messages were those that aggressively addressed tobacco industry duplicity and 

manipulation and the health consequences of secondhand smoke. Focus 

group results suggest that these were effective for both adults and youths, 

200

Chapter 9 

although for different reasons. Adults tended to re-express their guilt at 

being unable to quit smoking as anger towards the tobacco industry's drive 

to profit from a deadly product, whereas youths perceived tobacco industry 

manipulation as being exactly the kind of social control they were rebelling 

against. Secondhand smoke made adults feel responsible for contaminating 

the air of children. For youths, it tended to awaken a “sense of injustice for 

the little guy.” The secondhand smoke theme was effective for both groups 

because it portrayed the child as a “helpless victim” as well as “[making] 

people aware of the effects of their smoking on others” (Goldman and 

Glantz, 1998, p. 775). 

Recent analyses (Biener, 1998) of findings from adult cohort surveys in 

the Massachusetts advertising campaign suggest that the perceived emotional intensity of antismoking advertisements correlates positively with the 

advertisements’ perceived effectiveness. A representative sample of adults (n 

= 1,566) was interviewed by telephone before the nine Massachusetts advertisements were aired on television in 1994 and then again 3 years later. In 

the follow-up survey, cohort recall of the nine advertisements was measured 

(all were 30-second spots), and each advertisement was then rated on a 10-

point effectiveness scale. Correlates of perceived effectiveness were analyzed 

based on the effectiveness measure, viewer characteristics (from the baseline 

and follow-up survey), and advertisement characteristics (established independently by a panel of 15 judges). The findings indicate that humorous 

advertisements are not seen as effective and that spots portraying illness 

resulting from smoking are likely to be perceived as emotionally intense. 

Viewer responses were stratified by smoking status (current smoker, quitter, 

or nonsmoker) for particular advertisements. For example, nonsmokers 

rated the Janet Sackman spot (Tobacco industry is targeting kids) as most 

effective, whereas quitters and smokers rated the Picture on Pack (Quit to 

stay alive for your kids) as most effective. Nevertheless, all three groups 

rated the Circle the date (Pick a date to quit) and Ask the doc (Your doctor 

can help you) as the two least effective advertisements in the campaign. 

Smokers on average were found to be more attentive than nonsmokers to 

anti-tobacco messages. Smokers who were anticipating quitting tended to 

rate advertisements more highly than those not ready to quit. Smokers who 

had attempted but failed to quit rated helpful advertisements more highly. 

It is likely that the tax increase had an effect on campaign results in 

California, but not in Massachusetts. Hu et al. (1995) conducted an econometric analysis of the relative effects of the California tax increase and the 

media campaign on per capita cigarette sales and found that the tax 

increase yielded a higher negative demand elasticity (-0.30) than did the 

media campaign (-0.05). Goldman and Glantz (1998), however, note that 

the Hu et al. study probably underestimated the demand elasticity of the 

media campaign, because their model did not account for the additional 

promotional activities undertaken by the tobacco industry to counter the 

effects of the media campaign (p. 773). The tobacco industry reduced the 

price of cigarettes at approximately the same time that the increase in tax 

occurred in Massachusetts, and therefore the cost effect of the increase in 

tax was blunted. 

201 
Smoking and Tobacco Control Monograph No. 12 

Popham et al. (1993) surveyed adults who had quit smoking during the 

first wave of the California campaign (1990-1991) and found that 6.7 percent of smokers, without being cued, identified campaign advertising as a 

factor in their decision to quit smoking. When directly queried about the 

campaign, 34.3 percent identified the campaign as having influenced their 

decision. This translates into 33,000 and 173,000 former adult smokers in 

California whose decision to quit was influenced to a perceptible degree by 

the antismoking advertising campaign. 

Tables 9-1 and 9-2 present measures of change in smoking behavior for 

the 1990 and 1996 California Tobacco Surveys (CTS) in relation to selfreported recall of media in the last week (1990) and last month (1996) for 

television, radio, newspaper, magazine, and billboard spots. The change in 

smoking behavior measures presented are for those who were current daily 

smokers 1 year prior to the survey and who were age 25 years or older at 

the time of the survey. In general, those who reported recall of media spots 

were more likely to have made a quit attempt in the last 12 months than 

those who did not. These analyses do not establish whether the quit 

attempt was a result of the exposure to the media or whether the recall is 

because of an interest in quitting. Cessation is a process that occurs over 

time and is measured over the prior 12 months in these analyses. Recall of 

the media is measured over the last month or week, and it is unlikely that 

the difference in cessation activity occurred during that period. However, it 

is also likely that recall of the media is a measure that is generalized over a 

longer period of time than that specified in the survey question, raising the 

possibility of a direct effect. 

Figure 9-1 presents cessation attempts for the 1990 and 1996 CTS by the 

number of media channels that the smokers recalled. There is a statistically 

significant increase in cessation with increasing number of channels 

recalled for both survey years. 

The Massachusetts and California campaigns in many respects represent 

the “state of the art” in media methodologies, and their results thus far 

have been quite positive. Several important qualifications need to be made, 

however, about the findings discussed above. Both campaigns are multidimensional and encompass a number of activities and components in addition to media advertising and taxation. California in particular has integrated a variety of additional services and programs into its campaign, including a statewide proactive telephone helpline, targeted interventions for ethnic and linguistic minorities, and various school- and community-based initiatives. It would be a mistake, therefore, to credit the declines in consumption solely to media advertising. The relative rate comparisons of tobacco 

consumption reported by Goldman and Glantz (1998) certainly do not rule 

out other contributing causes, and they do not account for the broader 

social context of change. Comparing a target state's consumption rate with 

the rest of the country is useful as a relative indicator of campaign success, 

but it does not control for ancillary factors that may be contributing to 

both the national and local state rates. Such factors may include a longterm decline in smoking rates nationally (the “secular trend”) or the status 

202 
Chapter 9 

Table 9-1 

Recall of Media in the Last Week* among Current and Former Smokers** 

Current Smokers Former Smoker 

Made Quit No Quit (Any Quit Population Sample 

Attempt Attempt Length) Size Size 

% CI % CI % CI (N) (n) 

Total 35.36 1.71 54.11 1.64 10.53 1.05 3,414,774 7,249 

Television Exposure 

Some 38.27 1.99 52.99 2.05 8.74 1.47 1,491,309 3,294 

None 33.30 2.30 54.51 2.13 12.20 1.66 1,788,553 3,670 

Unknown 30.46 7.28 61.25 8.95 8.28 3.85 134,912 285 

Radio Exposure 

Some 41.62 5.18 49.13 4.67 9.25 2.79 501,934 997 

None 34.21 1.68 54.95 1.54 10.84 1.06 2,686,266 5,751 

Unknown 35.03 6.45 55.27 7.22 9.71 4.42 226,574 501 

Newspaper or Magazine Exposure 

Some 36.99 2.56 51.62 2.48 11.39 2.36 701,727 1,683 

None 34.93 1.88 54.83 1.83 10.24 1.11 2,564,939 5,308 

Unknown 35.08 12.77 53.45 10.16 11.48 7.41 148,108 258 

TV, Radio, Newspaper, or Magazine Exposure 

All 41.40 7.06 49.31 10.45 9.29 7.93 92,430 184 

Some 37.80 1.91 52.55 2.03 9.64 1.43 1,925,111 4,290 

None 31.73 2.48 56.32 2.65 11.95 1.63 1,229,318 2,456 

Unknown 30.54 8.84 58.45 9.94 11.01 6.25 167,915 319 

*The questions differ between the 1990 survey and the 1996 survey: 

1990: Did you see anything in the newspapers or magazines in the last week about the pros or cons of smoking? 

1996: In the last month, have you seen a billboard with a message against smoking? 

**Current or former smokers, 25+ years of age, who were daily smokers 1 year ago. 

Source: 1990 California Tobacco Survey. 

of antismoking activities in other state jurisdictions. Without detracting 

from the success of these two campaigns, it is instructive to compare these 

very positive findings with the more modest results obtained in community 

trials that have used experimental control methods to evaluate campaign 

and intervention performance. 

STANFORD FIVE-CITY The Stanford Five-City Multi-factor Risk Reduction 

PROJECT (FCP) Project (FCP) was a landmark field trial funded in 1978 

to evaluate community-based cardiovascular health education methodologies. The FCP was designed to extend the knowledge and experience gained 

in the Stanford Three-Community Study and to offer a more rigorous basis 

of evaluation by using two treatment cities (Monterey and Salinas) and 

three control cities (Modesto and San Luis Obispo; and Santa Maria for 

morbidity and mortality data only). Initial funding covered 9 years (6-year 

intervention with a 3-year follow-up); however, funding was extended to 18 

total years in 1987 to allow for 4 additional years of education maintenance 

(to 1990) and 6 more years of program surveillance (Fortmann et al., 1995). 

Cardiovascular disease (CVD) risk factors targeted for reduction in the program's multifactorial design included hypertension, elevated plasma cholesterol, smoking, obesity, and sedentary lifestyles (Farquhar et al., 1985 & 

1990). 203

Smoking and Tobacco Control Monograph No. 12 

Table 9-2 

Recall of Media in the Last Month* among Current and Former Smokers** 

Current Smokers Former Smoker 

Made Quit No Quit (Any Quit Population Sample 

Attempt Attempt Length) Size Size 

% CI % CI % CI (N) (n) 

Total 34.80 1.29 54.97 1.42 10.24 1.00 2,888,238 6,203 

Television Exposure 

Some 35.84 1.58 54.68 1.64 9.48 0.97 2,265,114 4,891 

None 32.15 3.69 54.10 4.09 13.75 3.24 463,099 957 

Unknown 27.71 5.89 61.58 6.85 10.71 3.26 160,027 355 

Radio Exposure 

Some 38.35 2.46 51.41 2.31 10.24 1.30 1,329,508 2,882 

None 32.64 1.94 56.67 2.51 10.70 1.75 1,187,535 2,516 

Unknown 29.01 3.73 62.25 4.81 8.75 2.21 371,198 805 

Billboard Exposure 

Some 39.83 1.86 50.61 2.20 9.57 1.30 1,278,612 2,698 

None 30.69 1.92 58.57 2.01 10.74 1.30 1,580,481 3,434 

Unknown 36.99 11.43 . . 12.05 8.61 29,151 71 

TV, Radio, or Billboard Exposure 

All 42.69 3.34 48.07 3.46 9.24 1.56 678,171 1,416 

Some 33.49 1.73 56.63 1.84 9.88 1.11 1,875,742 4,085 

None 27.19 4.40 57.11 4.94 15.69 4.32 224,240 465 

Unknown 24.00 5.73 64.72 6.85 11.28 4.24 110,092 237 

*The questions differ between the 1990 survey and the 1996 survey: 

1990: Did you see anything in the newspapers or magazines in the last week about the pros or cons of smoking? 

1996: In the last month, have you seen a billboard with a message against smoking? 

**Current or former smokers, 25+ years of age, who were daily smokers 1 year ago. 

Source: 1996 California Tobacco Survey. 

The smoking cessation component of FCP was comprehensive, integrated, and multifaceted, and used multiple communications channels and 

message formats to reach a socially diverse audience of smokers (Fortmann 

et al., 1993). Media elements differed somewhat from year to year but typically encompassed television, radio, and print campaigns. In the third education year (1982-1983) for example, a television-based smoking cessation 

program was developed and aired, as were nine 30-second and five 10-second television public service announcements (PSAs) and a radio cessation 

series targeted at younger, blue-collar smokers. Radio and print programs 

were also developed for Spanish-speaking audiences. Knowledge, attitude, 

and behavior goals were set for each year, as were program outcomes. For 

1982-1983, the goal was to motivate 2,000 smokers to quit. Predisposing, 

enabling, and reinforcing factors were emphasized to enhance overall smoking cessation objectives. As noted by the authors, “Attempts were made to 

increase knowledge about the dangers of smoking and the advantages of 

quitting, to alter attitudes about smoking, to increase smokers' confidence 

in their ability to quit, and to encourage smoking prevention, cessation, 

and maintenance. Multiple programs and products were developed to 

achieve these aims” (Fortmann et al., 1993). In addition to the media com204 
Chapter 9 

Figure 9-1 

Percentage of Current Smokers Making a Quit Attempt by Number of Media Modalities 

in Which Smoking Messages were Recalled 

0

10

20

30

40

50

All 

Three

Some of 

the Three

None of 

the Three

990 1996

Survey Year

Percntage Who Made a Quit Attempt

1990: Television, radio, or newspaper/magazine in the last week 

1996: Television, radio, or billboard in the last month 

Source: 1990, 1996 California Tobacco Surveys 

ponent, core program elements included self-help cessation methods 

(broadcast cessation programs and quit kits in English and Spanish), group 

programs, contests and events (Smoker's Challenge, Great American SmokeOut), school-based smoking prevention initiatives, and health professional 

interventions (education for health practitioners). 

An evaluation of smoking rates by Fortmann et al., (1993) after the fifth 

education year showed significant treatment effects for the FCP's cohort 

sample and for the baseline population at follow-up, but showed no significant effects for the independent, cross-sectional samples. The decline in 

cohort smoking rates (factored as a linear slope coefficient) averaged -1.51 

percentage points/year in the two treatment cities, nearly double the -0.78 

percentage points/year averaged in the two control cities (p = 0.007). By 

contrast, the findings for the independent samples reflected little treatment 

effect. The decline in smoking prevalence was similar in treatment and control cities, the changes that occurred were not linear, and cessation rates 

varied within cities between surveys (Op cit., p. 82). Nevertheless, baseline 

smokers in both the cohort and independent samples (identified in the initial 1978-1979 survey) were more likely to quit smoking in the treatment 

205 
Smoking and Tobacco Control Monograph No. 12 

cities than in the control cities (bio-confirmed). In the independent sample, 

22 percent in the treatment condition quit smoking, compared with 18 percent in the control, and the resulting treatment versus control survival 

curves were significantly different (log rank p = 0.04). The smoking survival 

analyses for the cohort sample yielded greater differences with quit rates of 

40 percent of baseline smokers in the treatment condition, compared with 

23 percent in the control condition, and significant survival curve differences (log rank p = 0.006). However, the cohort sample sustained a high 

dropout rate (nearly 50 percent) and when dropouts were re-coded as smokers as a cautionary measure, significance was lost (log rank p = 0.075). 

Predictors of smoking cessation for men were baseline cigarette consumption (number per day) and treatment status, whereas for women only 

baseline cigarette consumption was significant. Education level, intention 

to quit, and alcohol intake were moderately predictive but did not reach 

statistical significance. More importantly, media exposure and knowledge of 

cardiovascular disease both had p values of less than 0.2 and as a result 

were not included in the final predictive model. 

Fortmann et al. (1993) also evaluated the effects of socio-demographic 

characteristics on cessation by cross-tabulating changes in smoking prevalence between the baseline and final cohort surveys with baseline demographic and behavioral characteristics of the sample. These comparisons 

were post hoc, and Fortmann et al. warn that they should be considered 

exploratory. Because of the small number of comparisons in the data set 

and the lack of power to detect differences, no statistical tests were reported. Nevertheless, the stratification of changes in smoking rates that resulted 

is instructive. Treatment effects (measured by net differences in smoking 

rate changes for treatment and control) were much greater for men (-8.6) 

than for women (+0.8), and for Anglos (White/non-Hispanic) (-3.8) than for 

other ethnic groups (approximately half Hispanic) (-2.2), although these 

subgroups had very dissimilar baseline smoking rates. Treatment cities 

demonstrated higher smoking rate declines than controls for all age groups 

and at all education levels, except for the strata with less than a high-school 

education (+0.8). Lighter smokers (two strata—light ≤15 cigarettes/day; 

moderate = 16-24 cigarettes/day) were more likely to quit than heavy smokers (≥25 cigarettes/day) in both the treatment and control conditions. But 

the change in treatment cities was greater than in control cities at all levels, 

particularly for moderate-level smokers (light: -7.9; moderate: -21.3; 

heavy: -8.6). 

A subsequent analysis of smoking rates conducted by Winkleby et al. 

(1996), several years after the Fortmann et al. study, yielded less positive 

treatment effects. Using cross-sectional data from the final survey in 

1989/1990 (conducted 3 years after the main intervention as the last phase 

of the original 9-year design), Winkleby et al. (1996) found that, “smoking 

rates leveled out or increased slightly in treatment cities, while declines in 

the control cities continued” (p. 1,777). Comparing figures for the last year 

of treatment and the final survey (a 3-year period), the net difference in 

percentage of smokers in the treatment cities versus the control cities was 

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+5.8 for men (a change of +3.0 percent in treatment and -2.8 percent in 

control) and +3.8 for women (a change of -0.2 percent in treatment and -

4.0 percent in control). No significant treatment effects were found. 

Winkleby et al. (1996) attribute the erosion of treatment effects partly to 

the secular trends in smoking and partly to antismoking activities in one of 

the control cities, San Luis Obispo, whose smoking trends approximated 

those in the treatment cities. The number of smokers in the combined control-city data reported by Winkleby et al. (1996) fell from 34.3 percent and 

30.3 percent of population at baseline for men and women, respectively, to 

21.6 percent and 15.2 percent in the final survey, 10 years later. 

COMMUNITY INTERVEN- COMMIT was funded by the National Cancer 

TION TRIAL FOR SMOKING Institute (NCI) in 1986 to test the effectiveness of a 

CESSATION (COMMIT) comprehensive, multiyear, community-based smoking control intervention using randomized control conditions (COMMIT 

Research Group, 1996). Results from COMMIT are reported elsewhere in 

this monograph, therefore, only brief mention will be made here of the 

design and findings of the study as they pertain to mass media and smoking cessation. The COMMIT trial was organized in 11 pairs of communities 

that were each matched for size, geographic location (state or province), 

and demographic characteristics. Intervention and comparison communities were randomly assigned from each pair, so treatment/control comparisons would be between like communities. The intervention strategy was 

standardized across communities and was a comprehensive community 

activation approach. Fifty-eight activities were mandated, with only limited 

opportunity for tailoring. Four primary intervention channels were targeted: public education through the media and community events, health care 

provider interventions, work-site interventions, and cessation resources 

development and distribution. The public education component required 

communities to undertake five core activities (COMMIT Research Group, 

1995a; Wallack and Sciandra, 1991): 

• Provide media advocacy training for community board members 

• Implement an initial “kick-off” event 

• Publicize smoking control plans 

• Design and implement “magnet events” (such as local Quit & 

Win contests and local extensions of the Great American 

Smokeout) 

• Publicize activities in other areas (such as self-help materials) 

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COMMIT's main target population was heavy cigarette smokers (>25 

cigarettes/day) aged 25 to 64 years; however, the trial's design was cross-sectional and followed a community-based, mass intervention strategy, not a 

segmented strategy. The primary hypothesis of COMMIT was that, “implementation of a defined intervention protocol [would] result in at least 10 

percent higher quit rates among heavy cigarette smokers in the intervention communities than the quit rate observed in the comparison communities (i.e., 25 percent versus 15 percent)” (COMMIT Research Group, 1996; p. 

1,621). One of the optional activities permitted under the research protocol 

was mass media based cessation campaigns. Intermediate trial goals were 

compatible with media intervention effects and included: 

• Increasing the priority of smoking cessation as a public health 

issue; 

• Increasing the community’s capacity to modify the smoking 

behavior of its residents; 

• Enhancing the influence of existing political and economic factors that discourage smoking in the community; and 

• Increasing societal norms and values that support nonsmoking. 

The COMMIT intervention was carried out over 4 years from January 

1989 to December 1992. Baseline surveying was done from January to May 

1988, followed by annual surveys during the intervention, and a final 

prevalence survey from August 1993 to January 1994 (COMMIT Research 

Group, 1995a). 

The COMMIT trial achieved significant smoking cessation effects 

among light-to-moderate smokers in the cohort sample, but not with heavy 

smokers and not with the independent cross-sectional samples. Average cessation rates (self-reported) for light-to-moderate smokers in the cohort sample were 0.306 for the intervention communities and 0.275 for the comparison communities (p = 0.004). By contrast, the rates for heavy smokers were 

0.180 for intervention and 0.187 for comparison, a nonsignificant difference (p = 0.68). The average quit ratio (an analogous measure to the cohort 

quit rate, see COMMIT Research Group, 1995b, pp. 194-195) for the independent sample was 0.198 for intervention and 0.185 for comparison, a 

nonsignificant difference (p = 0.09) (COMMIT Research Group, 1995b, 

p. 196). 

Average smoking prevalence rates for the target 25- to 64-year-old age 

group (independent sample) declined in the intervention communities 

from 27.6 percent at baseline to 24.1 percent in the final survey (a change 

of -3.5 percent) and from 28.6 percent to 25.4 percent in the comparison 

communities (a change of -3.2 percent), a nonsignificant difference 

(p = 0.36). Heavy smoking prevalence fell from 10.2 percent at baseline to 

7.3 percent at final for intervention (change of -2.9) and from 11.0 percent 

to 8.2 percent for comparison (change of -2.9), also a nonsignificant difference (p = 0.51). 

The COMMIT Research Group evaluated the intervention effects of the 

mandated smoking control activities by measuring smokers' and recent ex208 
Chapter 9 

smokers' “perception of receipt” of these activities, and by comparing these 

findings across the intervention and comparison conditions. Only two of 

the mandated intervention activities achieved significance in the receipt 

indices, and they were significant for both the cohort and independent 

samples. These were events and contests (cohort: p = 0.001; independent: 

p = 0.01) and programs and materials (cohort: p = 0.007; independent: 

p = 0.05). By contrast, media/public relations activities were the least differentiated between the intervention and comparison communities (cohort: 

p = 0.29; independent: p = 0.68). 

The COMMIT Research Group used pair-wise rank correlations of quit 

rate differences and receipt-index differences as a way to evaluate the success of the intervention for changing behavior. The correlation findings 

demonstrate a significant intervention effect for light-to-moderate smokers 

in the cohort group (rank order correlation = 0.75, p = 0.01), but not for the 

heavy smokers (rank order correlation = 0.13, p = 0.71). As noted by the 

COMMIT Research Group (1995a): 

“This suggests that in the light-to-moderate smoker cohort, 

where the COMMIT intervention did produce a behavioral change, 

the magnitude of this intervention effect was related to the magnitude of the difference in awareness of (or participation in) smoking 

control activities.” 

In the independent sample, pair-wise intervention/comparison differences in the summary receipt index (a standardized composite score of all 

eight evaluated smoking control activities of which media/public relations 

was one) were found to correlate significantly with differences in the quit 

ratio (rank order correlation 0.67, p = 0.02), but not with differences in 

changes of smoking prevalence (rank order correlation 0.02, p = 0.96). 

Interaction tests between quitting and socio-demographic variables yielded 

one statistically significant finding that demonstrated an inverse relationship to education level and showed that most of the benefits in the lightto-moderate smoker cohort were seen in the lesser educated subgroup 

(COMMIT Research Group, 1995a, p. 187). 

DISCUSSION The evidence reviewed here supports the observations that a 

comprehensive program of tobacco control interventions supported by 

media campaigns can be effective. Although additional factors were 

undoubtedly at play in the California and Massachusetts experiences, the 

combined demand elasticities resulting from increased taxes and an effective media-led tobacco control intervention in California (versus 

Massachusetts where the tobacco industry lowered point of sale prices) help 

to account at least in part for the higher reported rate of success in smoking 

cessation in that state. Findings from the Stanford FCP and COMMIT are 

less conclusive, although they support the efficacy of integrated interventions. Both trials achieved significant treatment effects, using multifaceted, 

multilevel interventions that combined media campaigns with communitybased programs designed to target smoking cessation. Even though the net 

gains were appreciable, the effects in both trials were mainly restricted to 

light-to-moderate smokers in the cohort groups and did not extend to the 

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independent sample or the population of the more addicted heavy smokers. 

The media awareness findings in the FCP were not significant (p = 0.2), and 

the COMMIT receipt indices for media/public relations activities were the 

least differentiated between the intervention and comparison communities 

(cohort: p = 0.29; independent: p = 0.68). 

A number of researchers have attributed the selective success of the 

Stanford FCP and COMMIT to declining secular trends in smoking and to 

the increased diffusion of health information about smoking, championed 

in part by the popular press (Fortmann et al., 1993; Winkleby, 1994; 

Winkleby et al., 1996; Green, 1997a; COMMIT Research Group, 1995b; 

Susser, 1995). The COMMIT Research Group (1995b) speculated that the 

low receipt indices they found for public education and media coverage 

may reflect the inability of this type of intervention “to affect smoking 

behavior much beyond national secular trends” (p. 199). In particular, they 

noted that the increased coverage of tobacco issues in the media observed 

during the COMMIT trial may have diminished audience receptivity to the 

trial's own publicity, resulting in “little additional effect of the COMMIT 

efforts” (Op cit.). 

The widespread public adoption of healthier lifestyles (including quitting smoking) has followed the classical S-shaped curve of innovation-diffusion theory over the last three decades (Green, 1991; Green, 1997b; Green 

and Richard, 1993; Rogers, 1983). Declines in smoking rates began in the 

United States and Canada in the 1960s, soon after the release of the first 

Surgeon General's report (1964), and the declines have continued to present 

(Burns, 1994; Cunningham, 1996). The diffusion curve that has resulted 

helps to explain a number of the apparent inconsistencies and “failures” in 

the FCP and COMMIT. For example, the diminished success of these trials 

when compared with earlier trials such as North Karelia, Finland and the 

Stanford Three-Community Study, can be explained in part by where they 

have occurred on the diffusion curve. The earliest community trials--North 

Karelia and the Stanford Three-Community Study--led the diffusion curve 

and were therefore more successful at producing treatment effects that were 

ahead of the secular rate of change. Subsequent programs, however, were 

undertaken after the secular rate of change was already in full swing and 

had engaged the steeper component of the curve. In such circumstances, 

when motivation to quit smoking and knowledge about how to quit is 

widespread, it becomes increasingly difficult to outperform the secular rate 

of change in a randomized treatment/control context. 

The momentum of the secular trend in smoking today is likely partly a 

result of the power of the media to communicate to a mass public. It also 

dramatizes the difficulties faced by health promotion initiatives that want 

to “be heard” over the “noise” of extant health information in the media 

system. The secular declines in smoking are largely attributable to the success of prior health education initiatives, however, and this attests to the 

long-term value of education interventions, whether or not they outperform the secular trend. 

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Chapter 9 

A second conclusion to draw from these studies, therefore, is that the 

environmental context of smoking and smoking information is in a state of 

change that appears to be following classic diffusion patterns. This helps to 

explain the rather modest media results of FCP and COMMIT, as just noted, 

and also highlights an emerging need for campaigns to take better account 

of the media environments in which they operate. The successes in 

Massachusetts and California indicate that media planners should exploit 

formative research methods to ensure that campaign messages reinforce 

(and where necessary, lead or correct) social beliefs portrayed in the popular 

media context, so as to build on secular trends. Media advocacy strategies 

as well as social marketing campaigns and community-based interventions 

can all follow this course of action. 

There are also implications for campaign measurement and evaluation. 

In a period of increased social diffusion of health messages, one can expect 

to find more respondent confusion over the authorship of particular health 

messages and more “legitimate” false recognition of campaign messages in 

control populations, because of the apparent similarity of secular and campaign messages (Brown et al., 1990). 

Diffusion theory predicts that at this point on the diffusion curve, motivational appeals are more likely to achieve success with smokers who are 

contemplating quitting than are cognitively oriented, informational appeals 

(although these two strategies are not necessarily incommensurate, as we 

discuss below). This prediction is founded on the premise that a motivational intervention will positively affect the determinants of behavior for a 

majority of adopters. The usefulness of the diffusion approach and the ability of the media to affect the determinants of smoking behavior are both 

supported by the results from the reviewed studies. The finding of Popham 

et al. (1993) that 34.3 percent of surveyed California smokers identified 

campaign advertising as a factor in their decision to quit smoking when 

prompted, and 6.7 percent spontaneously cited media as a factor, suggests 

that the campaign was a significant motivating factor for over a third of the 

smokers in the population. The campaign advertisements were broadly 

positioned to promote negative attitudes about smoking, and as such they 

targeted attitudinal determinants of smoking, although help-line numbers 

and the names of local health organizations were provided. Popham et al.'s 

findings fit well with Biener's (1998) results from Massachusetts—that emotionally tense advertisements were perceived as most effective. As with the 

California campaign, the strength of the advertising messages in 

Massachusetts seems to have been in providing the emotional (motivational) grounds for quitting, not in relaying particular techniques and methods. 

Smokers who had failed at an initial quit attempt, on the other hand, rated 

helpful advertisements more highly. Smokers generally were found to be 

more attentive than nonsmokers to anti-tobacco messages. Smokers who 

were anticipating quitting tended to rate the campaign advertisements 

more highly than those who were not ready to quit. 

Emotive strategies need not necessarily be separate from informational 

and educational strategies. In some cases, the effectiveness of information 

penetration, adoption, and use could be enhanced if it were carried on a 

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message platform that had emotive and motivational appeal. Media messages can serve as a motivational “cue to action” for some smokers, in addition to influencing the context in which the action itself is undertaken. The 

obvious methodological question that results in this context is whether 

media campaigns actually enhance smoking cessation rates, or whether the 

people who quit smoking during a campaign are already motivated to quit 

and would have quit anyway (Flay et al., 1993). Other types of media campaign evaluations often find that after an initial increase in the uptake of a 

recommended behavior, a dip in the rate of uptake appears in the following 

time interval. The number of people not changing in the second time interval is often approximately equal to the number who changed earlier (Green 

and Lewis, 1986). For example, this is the relationship seen in the 3-year 

follow-up study of the Stanford FCP noted above. Winkleby et al. (1996) 

found that “smoking rates leveled out or increased slightly in treatment 

cities, while declines in the control cities continued” (p. 1,777). This “borrowing from the future” response of populations to mass media appeals for 

behavior change makes the media appear to be successful in part by getting 

people to do a little earlier what they would have done later anyway. 

To suggest that people might be “cued” by mass media to take action, 

therefore, draws into question both the manner and level of such “cueing.” 

A study of smoking behavior changes resulting from motivated versus 

habitual (“de facto”) exposure to a television program (Flay et al., 1993) 

found that the strongest predictor for attempting to quit smoking was prior 

motivation to quit. At the same time, however, they also found that people 

did not actively seek out quit information when given the chance. Rather, 

their routine viewing patterns were a better predictor of their exposure to 

televised quit information. Most importantly, however, “de facto” exposure 

to the televised quit program (i.e., as a result of their regular viewing habits) 

resulted in increased 24-hour quitting behavior even after controlling for a 

number of key motivational and demographic factors among the participants. This led Flay et al. to speculate that “readiness to change” can perhaps be more passive than previously theorized and that people can be 

serendipitously cued to action even though they would not have pursued it 

on their own. 

This is a useful way to understand the results seen in the studies 

reviewed for this paper. That is, media interventions can be used to help 

build the supportive conditions (“determinants”) for smoking cessation, 

and to cue specific behavioral changes in individuals who are receptive to 

these cues and ready to change. Flay et al.(1993) conclude that, “particular 

audiences can be successfully targeted and some change brought about 

merely by determining which group views a particular television channel 

most often and knowing that the televised content meets high substantive 

standards” (p. 331). Other work by Sussman et al. (1994) suggests that these 

same conditions can be extended to other media. In particular, they found 

that newspapers had a more pronounced effect, in part because they 

reached the desired demographic group (older smokers) and they had a 

longer shelf life. One difficulty with television programs is that they have 

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no follow-up potential once viewed unless people have taped them. 

Newspaper supplements, by contrast, are long lasting and can be read or 

browsed at people's leisure, as they will. 

In an era of increasing media outlets and modes of communication, the 

selection of appropriate communication channels for reaching general and 

target audiences will tend to become more critical. It may be possible to 

improve campaign efficiency, however, by following a multimodal, multichannel approach and by using messages that are designed to appeal broadly to several target groups. In the Massachusetts and California campaigns, 

messages that aggressively focused on tobacco industry duplicity and 

manipulation and on the health consequences of secondhand smoke were 

successful with both adults and youths (although for different reasons). 

This kind of “message efficiency” (of multiple address) can only be achieved 

through formative research on the targeted populations, as was done (using 

focus groups) in Massachusetts and California. A second kind of “message 

efficiency” (of multifunctionality) is also desirable. As noted in the introduction, media messages supporting smoking cessation can be undertaken 

at three levels: to elicit very specific behavioral changes; to affect the determinants of such behavioral changes; and to advocate for policy changes 

that, in turn, can affect more complex behavioral changes. Multifunctional 

messages target change at several of these levels, for example, by using 

emotive appeals that are designed to alter people’s attitudes towards smoking and at the same time cue smoking cessation behavior. Practically speaking, most campaign messages function at several levels, and even functionally distinct campaign strategies can have cross-functional effects. For example, anti-smoking advertising can serve as a stimulus to policy change, and 

media advocacy programs can result in smoking cessation (as seen in COMMIT). 

Events, such as the Great American Smoke-Out and Quit & Win contests, have value in communications plans because they are inherently 

multi-address and multifunctional. They are also multimodal and attract 

the interest of a broad segment of the population, although actual participation rates tend to be low. Bains et al. (1995) found that contests generally 

recruit only 1 to 2 percent of the target population. Shipley et al. (1995) 

found that participation rates for stop-smoking contests varied from 0.27 

percent to 3.11 percent in the COMMIT trial. Nevertheless, the media attention curried on events typically encompasses both print and broadcast 

media and is potentially far-reaching. Events and contests were the mandated activity with the most significant receipt indices in COMMIT (cohort: 

p = 0.001; independent: p = 0.01), more significant than programs and 

materials (cohort: p = 0.007; independent: p = 0.05). This suggests that the 

events themselves played an important role in distinguishing the COMMIT 

program in the intervention condition. 

As a final observation, maintenance of an antismoking message in the 

mass media is in itself an important role for media campaigns. For the most 

part, the media context (“mediascape”) continues to be populated with positive images of healthy young people smoking, provided through tobacco 

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advertising, sponsorship and movie placements. This context is unlikely to 

change appreciably in the near future. Sparks (1997a,b & c) has shown that 

the rate of tobacco marketing innovation has stayed ahead of the development of tobacco control legislation internationally, such that the tobacco 

manufacturers continue to be able to promote their brands effectively, even 

in countries where tobacco advertising is prohibited. A key point, therefore, 

is that without clear, targeted antismoking messages in the media, the 

media context is essentially tobacco-positive for most smokers and starters. 

The final and overriding message from research, therefore, is that media 

support for smoking cessation should be undertaken in such a way as to 

support long-term goals of correcting social norms as well as short- and 

medium-term goals of eliciting smoking reduction and quitting in those 

who are predisposed to do so. 

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Characteristics of joiners and non-joiners in the 

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1372, 1994. 

Winkleby, M. A., Feldman, H. A., Murray, D.M. Joint 

analysis of three U.S. community intervention 

trials for reduction of cardiovascular disease risk. 

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Winkleby, M.A., Taylor, C.B., Jatulis, D., Fortmann, 

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1173-1779, 1996. 

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of a smoking prevention mass-media program 

using diagnostic and formative research. 

Preventive Medicine 17:531-558, 1988. 

216

Community-Wide Interventions 

for Tobacco Control 

K. Michael Cummings 

INTRODUCTION There are two unique features of community-wide interventions 

that distinguish them from other types of tobacco control strategies. First, 

community interventions attempt to change tobacco use in populations, 

not just in individuals or select target groups (NCI, 1991). Community-wide 

interventions for tobacco control operate on the premise that tobacco use is 

driven by societal attitudes that accept tobacco use and that efforts to 

reduce tobacco use require changing these attitudes. The second unique feature of community-wide interventions is that they are comprehensive in 

nature, involving attempts to intervene through multiple social structures 

in a community (NCI, 1991). This feature of community-wide interventions 

acknowledges the fact that attitudes about tobacco use are shaped by many 

different sources, including one’s family, workplace, educational and health 

care institutions, and the media, just to name a few. 

ARE THESE What evidence is available to support the premise that tobacco 

ASSUMPTIONS use is a socially mediated practice that can be altered by changCORRECT? ing social customs that support the behavior? First, it is a well 

accepted tenet of social psychology that humans are subject to a need to 

conform to the social conventions of the majority (Wrightman, 1977). To 

the extent that individuals perceive their actions as deviant, there will be 

pressure to conform to the dominant public opinion. 

Second, the history of tobacco use in United States seems to mirror 

shifts in public attitudes about smoking, reflecting increasing social sanctions on smoking in the early part of the century and then growing disapproval of smoking as a practice dangerous to the smoker and later to others 

(Warner, 1986). 

Third, even the tobacco industry recognizes that besides nicotine delivery, smoking behavior is mediated by social influences, as evidenced by the 

following explanation offered by a Philip Morris scientist on changing 

trends in teenage smoking prevalence: 

“There is no question but that peer pressure is important in 

influencing the young not to begin smoking. A decade or more ago 

it was a major reason why teenagers began to smoke. Now it is a 

major reason for their not beginning to smoke?” (Philip Morris, Inc, 

1981) 

Because the norms of society are in large part prescribed through public 

sources, such as the media, they are subject to the influences of special 

interest groups. Viewed in this light, tobacco advertising can be thought of 

as an effort to create demand for tobacco products by influencing the pub217

Smoking and Tobacco Control Monograph No. 12 

lic’s perceptions about the benefits of tobacco use. As marketing professor 

Richard Pollay points out: “...to smokers advertising is a reminder and reinforcer, while to the non-smoker it is a temptation and a teacher” (Pollay, 

1995). 

While the mass media has been used to increase the demand for tobacco, it has also been used to discourage the use of tobacco, as evidenced during the Fairness Doctrine period when anti-smoking television commercials 

were aired on a regular basis during prime time and cigarette consumption 

dropped sharply (U.S.DHHS, 1989). Thus, it appears that despite the addictive qualities of tobacco, tobacco use behavior is strongly influenced by the 

social conventions, customs, and norms of society and is subject to changes 

in the social environment. 

DO COMMUNITY-WIDE The scientific literature clearly demonstrates the limitINTERVENTIONS WORK? ed effect of individually focused, single-channel interventions in terms of influencing tobacco use throughout populations 

(U.S.DHHS, 1989; Klausner, 1997). Perhaps with the exception of nicotine 

replacement products, those programs with substantial efficacy, particularly 

clinic-based cessation programs, have not been widely accepted by smokers. 

By offering a comprehensive intervention that operates through multiple 

channels in a community, it is hoped that a synergy will be produced 

whereby the social norms undercutting tobacco will spread throughout the 

population at a faster pace than would otherwise be the case. Communitywide tobacco control interventions often have little to do with providing 

direct services to individual tobacco users, but instead focus attention on 

employers, health providers, politicians, and community leaders who are in 

positions to implement policies that help define the social norms about 

tobacco use in the population at large (NCI, 1991). 

What evidence is there that community-wide tobacco control interventions work? In recent years, we have seen a number of well-conducted, 

large-scale evaluations of community-wide interventions to reduce tobacco 

use. Although a few of these showed a degree of success, for most, the 

effects have been small and certainly less than predicted given the effort 

expended. For example, the Stanford Five-City Project reported a small 

treatment effect on quitting behavior, but no effect on smoking prevalence 

(Fortmann et al., 1993). The Minnesota Heart Health Program reported a 

modest beneficial effect for women in their cross-sectional analysis, but no 

effect in their cohort sample (Leupker et al., 1994). The Pawtucket Heart 

Health Program failed to demonstrate a significant intervention effect for 

smoking in any of their analyses (Carlton et al., 1994). The NCI’s 

Community Intervention Trial for Smoking Cessation (COMMIT) failed to 

affect quit rates among heavy smokers, but did boost quit rates by about 3 

percent among light-to-moderate smokers (COMMIT Research Group, 

1995a & b). Although COMMIT did not achieve the kind of success that 

had been hoped for, the modest increase in quitting observed among lightto-moderate smokers, if achieved nationally, would translate into 1.2 million additional adults stopping smoking (Klausner, 1997). A recent analysis 

of the cost-effectiveness of the COMMIT shows that the intervention com218

Chapter 10 

pares favorably with a number of other common preventive practices and 

many therapeutic interventions as well (Lewit et al., 1998). The finding that 

COMMIT was relatively cost-effective, given its limited effectiveness, 

appears to rest largely on the estimate of its incremental social cost—$167 

per smoker for the 4 years of the trial ($42 per smoker per year) as compared with the costs of other health and medical interventions. 

In evaluating the scientific literature on community interventions for 

tobacco control, one also has to recognize that not all interventions are 

equal. The focus and content of community-wide tobacco control interventions has evolved over the years from an approach a decade ago that was 

primarily designed to provide education and services to individual smokers 

to one that today actively attempts to bring about formal policy changes 

(Klausner, 1997). The focus of activity in most community tobacco programs today is on efforts to enact policies that have the potential to influence every smoker and potential smokers, including regulations on where 

smoking is permitted, taxation of tobacco products, limits on tobacco 

advertising and promotion, dedicated funding for mass-reaching public 

information campaigns, and mainstreaming of cessation advice and treatment by health care providers (Klausner, 1997). The success of a comprehensive, policy-focused approach to tobacco control is seen in the recent 

evaluations of the Massachusetts Tobacco Control program and the NCI’s 

American Stop Smoking Intervention Trial for Cancer Prevention (ASSIST), 

both of which found significant reductions in cigarette consumption associated with program efforts (Harris et al., 1997; Manley et al., 1997). Indeed, 

as Glantz has pointed out, the 7 percent reduction in per-capita cigarette 

consumption attributable to the ASSIST program means that if ASSIST were 

a cigarette brand, it would exceed the market share for all other brands of 

cigarettes sold except Marlboro (Glantz, 1997). 

WHAT LESSONS HAVE The history of the tobacco control movement provides 

WE LEARNED? some useful lessons to ponder as we consider whether 

community interventions are a good investment (Susser, 1995). First, to 

bring about large-scale changes in tobacco consumption, the social norms 

related to tobacco use need to change, and this change takes time. Two 

decades ago, who would have envisioned a smoke-free workplace as the 

accepted norm? The campaign to enact smoke-free policies began with a 

few public health advocates standing alongside those harmed by smoke pollution and gradually grew to include health care institutions, private 

employers, and government regulators. The usual time frame for evaluations of community tobacco control interventions is years when the time 

required to bring about social change may be decades. For example, significant reductions in smoking associated with the North Karelia intervention 

did not become evident for nearly 10 years (Puska et al., 1973 & 1983). 

Second, the measured effects of community-wide interventions is likely 

to be small, but as demonstrated by COMMIT, even a modest percentage 

effect on smoking behavior can translate into a large public health impact 

(Carlton et al., 1994; Lewit et al., 1998; Glantz, 1997). 

219

Smoking and Tobacco Control Monograph No. 12 

Third, community-wide interventions like COMMIT do not seem to 

have much impact on changing the smoking habits of heavy smokers. For 

those who are highly dependent on nicotine, more intensive clinical interventions and/or substitution of less lethal forms of nicotine ingestion may 

be necessary (Warner et al., 1997). 

Fourth, community tobacco control activities change over time, to 

reflect both the current state of scientific knowledge and shifting public 

attitudes about tobacco. Three decades ago, the primary focus of community interventions was educating consumers about the hazards of tobacco. 

Today, the emphasis is on dictating the policies that govern the way that 

tobacco products are designed, used, and marketed (Klausner, 1997). 

Finally, the conventional experimental research paradigm typically used 

to evaluate medical interventions may not be ideally suited to assessing the 

impact of community tobacco control efforts that encompass entire populations and change over time (Klausner, 1997; Susser, 1995). In the COMMIT 

study, over half of the $42.5 million devoted to that project was used for 

evaluation purposes (Lewit et al., 1998). A simpler, more efficient use of 

resources would be to design a surveillance system that would encompass 

the entire population and allow evaluators to compare differences in tobacco use trends over time and between communities. 

SUMMARY Although national and statewide initiatives have important roles to 

play in a comprehensive program to reduce tobacco use, local community 

intervention is where the action is, and represents the heart of the tobacco 

control movement. We would all be smart to live by the old adage, “Think 

global, act local.” Local community intervention, tailored to the unique 

concerns and needs of a community, represents the best hope of speeding 

up the pace of change in the social norms that govern tobacco use. 

It would be a big mistake to abandon community tobacco control 

efforts on the basis of a few disappointing studies. We have much to learn 

about how to bring about population-wide changes in tobacco use. 

Research is now just beginning to help us elucidate the factors that are 

important (Kaufman, 1997). For example, a recent secondary analysis of 

data collected as part of the COMMIT study has shown that community 

variation in tobacco use trends can be accounted for in part by differences 

in cigarette pricing and marketing practices, policies that influence workplace smoking, and policies that influence the cost and accessibility of stop 

smoking therapies (Lewit et al., 1997; Cummings et al., 1997a & 1997b; 

Glasgow et al., 1997). We need to use this knowledge and invest more time 

and energy into learning how to apply this information to the practice of 

community tobacco control. 

220

Chapter 10 

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221

Interaction of Population-Based 

Approaches for Tobacco Control 

Howard A. Fishbein, Jennifer B. Unger, C. Anderson Johnson, Louise Ann Rohrbach, 

Beth Howard-Pitney, Tess Boley Cruz, Clyde Dent, Kim Ammann Howard 

OVERVIEW This paper looks at program effectiveness results from data collected in 

1996 and 1997 during Wave 1 of the Independent Evaluation of California's 

Tobacco Control, Prevention, and Education Program (IEC, 1998). The 

issues discussed in this paper are based on certain assumptions about the 

tobacco-control atmosphere in California. These assumptions are 1) that 

tobacco control programs and activities do not occur in isolation; 2) that 

adults and youths throughout California were exposed to more than one 

tobacco control program or activity; and 3) that the California tobacco control program delivers a consistent anti-tobacco message. Given these 

assumptions, the issue to be explored is whether exposure to multiple 

tobacco-control programs and activities will produce stronger anti-tobacco 

attitudes and beliefs than the effect of exposure to only one program or 

activity. 

BACKGROUND California’s Tobacco Control Program was developed in response to 

voters’ actions in passing Proposition 99—the Tobacco Tax and Health 

Promotion Act of 1988. The Tobacco Control Program (TCP) Model utilizes 

a comprehensive integrated approach for preventing and reducing tobacco 

use. Throughout California, various program interventions are implemented through multiple modalities—i.e., community programs, school programs, and a statewide media and public relations campaign. 

From 1993 to the present, California’s tobacco control efforts have concentrated on three priority areas: 

1. Reducing exposure to environmental tobacco smoke (ETS); 

2. Reducing youth access to tobacco via commercial and social 

sources; and 

3. Countering pro-tobacco influences in the community. 

One of the primary objectives of the comprehensive California program 

is to promote social norms that tobacco use and exposure to ETS are not 

acceptable. 

* Collection of the data described in this article was supported by a contract from the California Department 

of Health Services, Tobacco Control Section (Contract #95-222998). The analyses, interpretations, and conclusions are those of the authors, not the California Department of Health Services. The authors thank Todd 

Rogers, June Flora, and Caroline Schooler for assistance with the research design and interpretation of 

results. 

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Smoking and Tobacco Control Monograph No. 12 

FRAMEWORK The conceptual framework for the evaluation is illustrated in 

FOR OUR STUDY Figure 11-1. The schematic presents a simplified view of the presumed relationships among TCP activities, intermediary outcomes, and ultimate outcomes. It shows that TCP activities are conducted independently 

and interactively through community programs, schools, and the statewide 

media and public relations campaign. Activities are directed towards tobacco-related social norm changes (i.e., intermediary outcomes such as attitudes, beliefs, behaviors, and policies) within three program priority areas: 

(1) reducing youth and adult exposure to environmental tobacco smoke 

(ETS); (2) reducing youth access to tobacco products; and (3) countering 

pro-tobacco influences. In addition, school-based programs are directed 

toward changing tobacco-use mediators such as perceptions and refusal 

skills. 

INDEPENDENT The Independent Evaluation conducted in California was 

EVALUATION designed to assess the effectiveness of tobacco control activities. 

METHODS The primary purpose of the evaluation was to gather information that would be used to provide feedback to help the California 

Department of Health Services and the California Department of Education 

to achieve their objectives. 

As of this writing, the Independent Evaluation is beginning year 4 of a 

5-year effort; it includes three sequential, cross-sectional waves of data collection. The first wave of data—used as the basis for this paper—was conducted from October 1996 to March 1997 and focused on a 2-year period of 

tobacco control activities in California—calendar years 1995 and 1996. 

SAMPLING SCHEMES The sampling scheme for the Independent Evaluation 

sought to find a set of 18 counties that were representative of the entire 

state. Because a major intervention arm of the TCP is the statewide mass 

media, we pre-selected the five counties comprising the largest media markets in the state. We applied a cluster solution approach to the remaining 

53 counties. The analysis was designed to form three clusters (strata) based 

on county population density (population per square mile) and percentage 

of rural area. We randomly selected 13 counties from these 3 strata. These 

13 counties, plus the 5 media market counties, yielded the sample of 18 

counties shown in Figure 11-2. These 18 counties represent 75 percent of 

the state’s population, and data analytic results based on these 18 counties 

are generalized to the entire state. 

The evaluation focused on assessing program implementation, exposure, and outcomes. Measures of program implementation were obtained 

from organizations that sponsored tobacco-control activities. Measures of 

program exposure were obtained from random samples of youths and 

adults in the 18 counties. Outcome measures were focused on intermediary 

outcomes of the tobacco control program, which included individual- and 

community-level indicators. Multiple data collection methods were used, 

including telephone interviews, school-based surveys, written surveys, and 

coding of archival records. 

224

Chapter 11 AEAE L N m O m Aw m A BC m E m A C mm L N m O m A T M C m m E m L ETY A C T L T U M R RUQ U m O m R C m ET E T C P m C m A w M R C m m C mm m Figure 11-1 Conceptual Framework for the Independent Evaluation 

225

Smoking and Tobacco Control Monograph No. 12 

Figure 11-2 

Eighteen Focal Counties 

Media Markets Medium Density 

Fresno Monterey


Los Angeles San Bernardino


Sacremento Shasta


San Diego Yuba


San Francisco


High Density Low Density 

Alameda Lake 

Contra Costa Lassen 

Orange Mono 

San Mateo Plumas 

Santa Clara 

A limitation of the Independent Evaluation approach is that linkages 

between program exposure and outcomes were observed at only one point 

in time—data from Wave 1. We point out that these baseline data provide a 

cross-sectional look at program effectiveness. Given our cross-sectional evaluation design, we are able to observe associations between program exposure and outcomes, but we cannot infer causal relationships. 

DATA COLLECTION Multiple data-collection methods were used to examine proMETHODS gram activities in counties across the state, and individualand community-level outcome indicators in the 18 counties. Information 

on implementation of tobacco control programs and activities was gathered 

from 12 different sources, including Local Lead Agency (LLA) progress 

reports; project director surveys and interviews; teacher surveys; school 

administrator surveys; surveys and interviews with media and public relations campaign contractors; and content analysis of statewide media campaign materials. 

Data on program outcomes were obtained from 11 different sources, 

including adult computer-assisted telephone interviews (n = 6,985); schoolbased youth surveys with students in 5th, 8th, and 10th grades (n = 3,139 

5th-graders, 5,870 8th-graders, and 6,929 10th-graders); telephone surveys 

of opinion leaders in the focal counties; and data on enactment of local 

policy. 

APPROACH Our hypothesis suggests that if the various tobacco control program 

modalities deliver consistent messages, they may reinforce and enhance one 

another. If this occurs, Californians exposed to multiple tobacco control 

program modalities may show even stronger anti-tobacco attitudes and 

beliefs than those exposed to only one program. 

We first looked at the percentage of the populations of interest exposed 

to the different program modalities. Then we explored the differences in 

tobacco-related attitudes and behaviors among those Californians exposed 

226

Chapter 11 

Figure 11-3 

Percentage of Youth Exposed to Different Combinations of TCP Activity 

Media

23%

Community

1%

School

8%

None

7%

Media + School + Community

11%

School + Community

2%

Media + Community

3%

Media + School

45%

to one type of TCP activity with those exposed to more than one TCP activity. For clarity of the results, we define exposure to a tobacco control activity as 1) for community: recall of at least one local community program; 2) 

for media: validated recall of at least one tobacco control program media 

ad; and 3) for schools: recall of at least one in-school lesson or school-wide 

activity. 

RESULTS Ninety-three percent of California 10th-grade youths were exposed to at 

least one modality of the California Tobacco Control Program. 

Most California youths reported exposure to more than one tobacco 

control modality. Figure 11-3 shows the percentage of youths that were 

exposed to different combinations of tobacco control program modalities. 

Only 7 percent of youths were not exposed to any activity. 

Adults Eighty-seven percent of California adults were exposed to at least one 

tobacco control program activity. Figure 11-4 shows the percentage of 

adults who were exposed to tobacco control community and media programs. Over one-third (38 percent) were exposed to both community and 

media programs. 

Exposure to each tobacco control program component was associated 

with tobacco-related knowledge, attitudes, and beliefs, even after accounting for the respondents’ exposure to other tobacco control program components. We evaluated the associations between tobacco control program 

exposure and tobacco-related outcome variables, while controlling for the 

respondents’ level of exposure to other tobacco control program modalities. 

227 
Smoking and Tobacco Control Monograph No. 12 

Figure 11-4 

Percentage of Adults Exposed to Different Combinations of TCS-Funded Programs 

Community

10%

None

13%

Community + Media

38%

Media

39%

These results evaluate how strongly each tobacco control program component (i.e., community programs, media campaign, and school-based programs) would have been associated with outcomes if everyone had received 

an equal level of exposure to the other program modalities. 

Among adults, exposure to community programs was associated with 

anti-tobacco attitudes and behaviors. Adults who reported high levels of 

exposure to TCS community programs were more likely to practice personal 

enforcement and talk about not smoking. These associations were present 

regardless of adults’ exposure to media programs. 

Similarly, among adults, exposure to media programs was associated 

with anti-tobacco attitudes and behaviors. Adults who reported high levels 

of exposure to media programs were more likely to dislike environmental 

tobacco smoke, favor government regulation of tobacco, practice personal 

enforcement, talk about not smoking, and express greater belief in the 

importance of tobacco issues. These associations were present regardless of 

the adults’ exposure to TCP community programs. 

Adults who were exposed to both media and community programs 

tended to support anti-tobacco policies more than did adults who were 

exposed only to media programs or only to community programs (Figure 

11-5). Media programs and community programs had important individual 

associations with support for anti-tobacco policies, but the interaction (or 

combination of the programs) seems to have been most effective. The data 

show that each type of program reinforced or increased the relationship 

between the other type of program and policy attitudes. 

228 
Chapter 11 

Figure 11-5 

Percentage of Adults Who Supported Anti-Tobacco Policies, According to TCSFunded Program Exposure 

0

10

20

30

40

50

60

70

80

Tobacco products should be regulated as a drug by the FDA

Tobacco advertising in stores should be banned

Smoking in outdoor public areas should be restricted

Community Only Media Only Community and Media

57 57 56

50 53

59

65 64 67

TCS-Funded Program Exposure

Percentage Who Said Agree or Strongly Agree

Significant differences at the p = 0.05 level were found when comparing 

results for community only to community and media; and for media only 

compared to community and media. 

We found similar trends for youth exposure and outcomes as we had 

observed for adults. 

10th Grade Youths Among youths, exposure to school programs was associated 

with anti-tobacco attitudes and behaviors. Regardless of their level of exposure to other tobacco control program activities, the following findings distinguished 10th-graders with high level school-based tobacco program 

exposure from their peers who reported lower levels of school program 

exposure: 

• More likely to believe that ETS, youth access to tobacco, and 

pro-tobacco influences are serious problems 

• Higher rates of advocacy actions such as signing petitions, contacting government officials, and attending youth conferences 

• More likely to talk to others about tobacco use 

• More negative attitudes toward the tobacco industry 

229 
Smoking and Tobacco Control Monograph No. 12 

• More positive attitudes toward anti-tobacco policy enforcement 

• More negative perceived consequences of tobacco use 

Among youths, TCP community programs appear to have had a mix of 

positive and negative associations with anti-tobacco attitudes and behaviors, after exposure to school and media programs was taken into account. 

Tenth-grade youths with high community program exposure showed the 

following characteristics relative to those with lower exposure to community programs: 

• More likely to believe that ETS, youth access to tobacco, and 

pro-tobacco influences are serious problems 

• Higher rates of advocacy actions such as signing petitions, contacting government officials, and attending youth conferences 

• More likely to talk to others about tobacco use 

However, somewhat surprisingly, 10th-grade youths with high community program exposure also showed the following negative characteristics 

relative to their peers with lower community program exposure: 

• Fewer perceived negative consequences of use 

• Lower cigarette refusal self-efficacy 

• Higher perceived smoking prevalence among peers 

• More exposure to ETS in the home or car 

We speculate that youths who smoked were perhaps disproportionately 

aware of community events and activities, accounting for many of the negative associations and higher rates of smoking among those exposed to 

community programs. 

Exposure to tobacco control program media programs was associated 

with stronger anti-tobacco attitudes and behaviors among youths. The following results distinguished 10th-grade youths with high media exposure 

from their peers with low media exposure: 

• More negative attitudes toward the tobacco industry 

• More perceived negative consequences of tobacco use 

• Higher cigarette refusal self-efficacy 

Figure 11-6 shows the percentage of 10th-grade youths who participated 

in advocacy actions, such as signing petitions, contacting government officials, and attending youth conferences. Youths who reported exposure to 

more than one type of tobacco control program were more likely to have 

performed these advocacy actions than were youths exposed to only one 

program or to no programs at all. 

In most cases, exposure to multiple programs was better than exposure 

to a single program. All comparisons of results for these three actions following exposure to a single component as compared with exposure to multiple components were significant at p = 0.05, except for the following: 

media versus media and school; community versus media and school; and school 

versus media and school. 

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Chapter 11 

Figure 11-6 Advocacy Actions among Youths, According to TCP Exposure %%%%%% AC m MC mm C mm M MC mm C mm M N E TCP M Percentage of Youth

231

Smoking and Tobacco Control Monograph No. 12 Figure 11-7 Negative Attitudes toward the Tobacco Industry among 

Youth, According to TCP Exposure 

%%%%%%

T m m

T m

M +

+

C mm

+

C mm

M + M +

C mm

C mm M N

E TCP M Percentage Who Agreed

232

Chapter 11 

Figure 11-7 shows the percentage of 10th-grade youths that expressed 

negative attitudes toward the tobacco industry, according to their exposure 

to TCS program modalities. Youths exposed to more than one program 

expressed attitudes toward the tobacco industry that were significantly 

more negative than those of youths exposed to only one program or youths 

not exposed to any programs. 

The trends showed a slight but significant increase in negative attitudes 

toward the tobacco industry among youths exposed to messages from multiple modalities. Significant differences in youth attitudes were found (at p 

= 0.05) when results were observed for comparisons between media versus 

media and school; and school versus media and school. The nonsignificant 

results for negative attitudes toward the tobacco industry may be due to a 

ceiling effect; regardless of program exposure, most students already had 

very negative attitudes about the tobacco industry. 

SUMMARY While exposure to specific tobacco control programs was associated 

with anti-tobacco attitudes and behaviors, exposure to multiple components appeared to be more beneficial than exposure to only one component. This indicates that presenting information through a variety of 

modalities is an important strategy for tobacco control. 

REFERENCES 

Bal, D.G., Kizer, K.W., Felten, P.G., Mozar, H.N., 

Niemwyer, D. Reducing tobacco consumption in 

California. Development of a statewide antitobacco use campaign. Journal of American 

Medical Association 264(12):1570-1574, 1990. 

Independent Evaluation Consortium. Final report of 

the Independent Evaluation of the California 

Tobacco Control Prevention and Education Program: 

Wave I Data, 1996–1997. Rockville, MD: The 

Gallup Organization, 1998. 

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