NIH Publication No. 03-5370

April 2003
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, National Cancer Institute, NIH Publication No. 92-3461, September 1992.

Major Local Tobacco Control Ordinances in the United 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, National Cancer Institute, NIH Publication No. 93-3532, May 1993.

Respiratory Health Effects of Passive Smoking: Lung Cancer and Other Disorders. Smoking and Tobacco Control

Monograph No. 4. Bethesda, MD: U.S. Department of Health and Human Services, Public Health Service,

National Institutes of Health, National Cancer Institute, 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, National Cancer Institute, 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, National Cancer Institute, 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, National Cancer Institute,

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, National Cancer Institute, 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, National

Cancer Institute, 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, Public Health Service, National Institutes of

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

Population Based Smoking Cessation: Proceedings of a Conference on What Works to Influence Cessation in the

General Population. Smoking and Tobacco Control Monograph No. 12. Bethesda, MD: U.S. Department of

Health and Human Services, Public Health Service, National Institutes of Health, National Cancer Institute,

NIH Publication No. 00-4892, November 2000.

Risks Associated with Smoking Cigarettes with Low Machine-Measured Yields of Tar and Nicotine. Smoking and

Tobacco Control Monograph No. 13. Bethesda, MD: U.S. Department of Health and Human Services, Public

Health Service, National Institutes of Health, National Cancer Institute, NIH Publication No. 02-5047,

October 2001.

Changing Adolescent Smoking Prevalence: Where It Is and Why. Smoking and Tobacco Control Monograph No.

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

of Health, National Cancer Institute, NIH Publication No. 02-5086, November 2001.
Preface

The End of An Era

Monograph 15, entitled Those Who Continue to Smoke: Is Achieving

Abstinence Harder and Do We Need to Change Our Interventions?, marks the

end of an era. It is the last of the original series of Smoking and Tobacco

Control Monographs begun in 1991 under the editorial direction of Donald

R. Shopland, former coordinator for the Smoking and Tobacco Control

Program (STCP) at the National Cancer Institute. From the very inception of

the monograph series, the National Cancer Institute has been extremely

fortunate to have had David M. Burns, M.D., professor of family and

preventive medicine at the University of California at San Diego, serve as

senior scientific editor.

The National Cancer Institute honors the significant contributions of

both these men. Mr. Shopland and Dr. Burns have brought keen insight,

knowledge, creativity, and boundless energy and dedication to the

production of the monographs. Much of the success of this first series of

Smoking and Tobacco Control Monographs can be attributed to the vision and

commitment of these two leaders in the tobacco control community. Their

efforts, and those of the hundreds of other contributors to the first 15

volumes, have laid a solid groundwork for future series.

The National Cancer Institute remains strongly committed to producing

and disseminating state-of-the-science smoking and tobacco control

monographs. The new series will draw from the strengths of the first series

and add several new processes and features to improve the breadth, depth,

and policy relevance of the evidence reviewed. One major goal will be to

provide the most objective and thorough syntheses of research to inform

the ongoing efforts of the National Cancer Institute and the extramural

research and tobacco control communities.

Stephen E. Marcus, Ph.D.

Series Editor, Smoking and Tobacco Control Monographs 

Tobacco Control Research Branch

Behavioral Research Program

Division of Cancer Control and Population Sciences

National Cancer Institute

National Institutes of Health

iii

Smoking and Tobacco Control Monograph No. 15
iv

Smoking and Tobacco Control Monograph No. 15
Acknowledgements

Monograph 15 is the result of a set of analyses commissioned and

funded jointly by the National Cancer Institute and the Tobacco Control

Section of the California Department of Health Services. William Ruppert,

M.S., health program specialist, Tobacco Control Section, California

Department of Health Services, Sacramento, CA, was the project officer for

the contract.

The Introduction was written by C. Tracy Orleans, Ph.D., senior scientist

and senior program officer at the Robert Wood Johnson Foundation, based

on her comments at a symposium sponsored by the National Cancer

Institute at the Society for Research on Nicotine and Tobacco (SRNT) Eighth

Annual Meeting held on February 20, 2002, in Savannah, GA. At this

symposium, entitled Hardening the Target: Are Smokers Less Likely to Quit Now

Than in the Past?, authors of several chapters of Monograph 15 participated

in a discussion of the scientific evidence, and Dr. Orleans served as the

discussant. Chapter 2 is based on data available as of February 2002.

The managing editor of Monograph 15 is Richard H. Amacher, project

director, KBM Group Inc., Silver Spring, MD. Stephen E. Marcus, Ph.D.,

completed the editorial direction of the monograph after Mr. Shopland

retired and served as its managing editor after the KBM contract ended.

The editors gratefully acknowledge the many researchers and authors

who made this monograph possible through their numerous hours of

writing and review. Contributors to each chapter are as follows:

Introduction C. Tracy Orleans, Ph.D.

Robert Wood Johnson 

Foundation

Chapter 1 Smokers Who Have Not David M. Burns, M.D.

Quit: Is Cessation More University of California, 

Difficult and Should We San Diego School of 

Change Our Strategies? Medicine

San Diego, CA

Kenneth E. Warner, Ph.D.

School of Public Health

University of Michigan

Ann Arbor, MI 

v

Acknowledgements
Chapter 2 The Case for Hardening John R. Hughes, M.D.

of the Target Departments of Psychiatry, 

Psychology and Family 

Practice

University of Vermont

Burlington, VT

David M. Burns, M.D.

University of California, 

San Diego School of 

Medicine

San Diego, CA

Chapter 3 The Case Against David M. Burns, M.D.

Hardening of the Target University of California,

San Diego School of 

Medicine

San Diego, CA

Chapter 4 Examining a Quarter- Jennifer E. Irvin

Century of Smoking University of South Florida

Cessation Trials: Is the and the

Target Becoming Harder H. Lee Moffitt Cancer 

to Treat? Center and Research 

Institute

Tampa, FL

Thomas H. Brandon, Ph.D.

University of South Florida

and the

H. Lee Moffitt Cancer 

Center and Research 

Institute

Tampa, FL

Chapter 5 Changes in Measures of Andrew Hyland, Ph.D.

Nicotine Dependence Roswell Park Cancer

Using Cross-Sectional Institute

and Longitudinal Data Buffalo, NY

from COMMIT

K. Michael Cummings, 

Ph.D., M.P.H.

Roswell Park Cancer 

Institute

Buffalo, NY

vi

Smoking and Tobacco Control Monograph No. 15
Chapter 6 Changes in Smoking Thomas G. Shanks, M.P.H., 

Habits in the American M.S.

Cancer Society CPS I Tobacco Control Policies

During 12 Years of Project

Follow-Up University of California at

San Diego

San Diego, CA

Christy M. Anderson, B.S.

Tobacco Control Policies 

Project

University of California at 

San Diego

San Diego, CA

Chapter 7 Changes in Number of David M. Burns, M.D.

Cigarettes Smoked per University of California,

Day: Cross-Sectional and San Diego School of 

Birth Cohort Analyses Medicine

Using NHIS San Diego, CA

Jacqueline M. Major, M.S.

Tobacco Control Policies 

Project

University of California at 

San Diego

San Diego, CA

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

M.S.

Tobacco Control Policies 

Project

University of California at 

San Diego

San Diego, CA

Chapter 8 Changes in Cross- David M. Burns, M.D.

Sectional Measures of University of California, 

Cessation, Numbers of San Diego School of 

Cigarettes Smoked per Medicine

Day, and Time to First San Diego, CA

Cigarette—California 

and National Data

vii

Acknowledgements
Jacqueline M. Major, M.S.

Tobacco Control Policies 

Project

University of California at 

San Diego

San Diego, CA

Christy M. Anderson, B.S.

Tobacco Control Policies 

Project

University of California at 

San Diego

San Diego, CA 

Jerry W. Vaughn, B.S.

Tobacco Control Policies 

Project

University of California at 

San Diego

San Diego, CA 

Chapter 9 Hardening of the Carolyn C. Celebucki, Ph.D.

Target: Evidence From Massachusetts Department 

Massachusetts of Public Health

Tobacco Control Program

Boston, MA

University of Rhode Island, 

Department of Psychology

Kingston, RI

Phyllis Brawarsky, M.P.H.

Massachusetts Department 

of Public Health

Bureau of Health Statistics, 

Research and Evaluation

Boston, MA

viii

Smoking and Tobacco Control Monograph No. 15
Reviewers include:

Erik Augustson, Ph.D.

Cancer Prevention Fellow

Division of Cancer Prevention

National Cancer Institute

Bethesda, MD

Gary Giovino, Ph.D.

Department of Cancer Prevention,

Epidemiology and Biostatistics

Roswell Park Cancer Institute

Smoking Control Program

Buffalo, NY

Dorothy K. Hatsukami, Ph.D.

Professor

Department of Psychiatry

University of Minnesota

Minneapolis, MN

Jack Henningfield, Ph.D.

Vice President

Research and Health Policy

Pinney Associates, Inc.

Bethesda, MD

John Hughes, M.D.

University of Vermont

Human Behavioral Pharmacology

Laboratory

Burlington, VT

Lynn T. Kozlowski, Ph.D.

Department of Biobehavioral

Health

The Pennsylvania State University

University Park, PA

Linda L. Pederson, Ph.D.

Centers for Disease Control and

Prevention

Office on Smoking and Health

Atlanta, GA

John Slade

Professor of Medicine

University of Medicine and

Dentistry

Program in Addictions

New Brunswick, NJ

Kenneth Warner

School of Public Health

The University of Michigan

Department of Health Management

and Policy

Ann Arbor, MI

ix

Acknowledgements
x

Smoking and Tobacco Control Monograph No. 15
Contents

Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .iii

Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .v

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

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1

Is the Target Hardening? Are Smokers Less Likely to Quit

Now Than in the Past? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .2

Are We Seeing a Hardening of the Population? Or a Hardening

Of Our Interventions? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4

What Can We Learn From and About Special Populations? How

Can Better Surveillance Help Us to Design Better

Treatments and Dissemination Efforts? . . . . . . . . . . . . . . . . . . . .5

Importance of Widening the Lens—Combining Clinical and

Broader Policy-Based and Public Health Approaches and

Building Consumer Demand . . . . . . . . . . . . . . . . . . . . . . . . . . . .6

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9

Chapter 1: Smokers Who Have Not Quit: Is Cessation More

Difficult and Should We Change Our Strategies? . . . . . . . . . . . .11

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .11

Definition of the Question . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12

Measures of Hardening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14

Have Cessation and Abstinence Rates Fallen Overall? . . . . . . . . . . .16

Have Recent Cessation Rates Fallen Among Populations

That Have Achieved Low Smoking Prevalence? . . . . . . . . . . . . .17

Are Residual Smokers Heavier Smokers or More Addicted? . . . . . . .21

Do Current Smokers Have Higher Comorbidity Than

Smokers Did in Previous Decades? . . . . . . . . . . . . . . . . . . . . . .25

Are Residual Smokers Concentrated in Less Advantaged

Demographic Groups and Those With Less Exposure

To Tobacco Control Interventions? . . . . . . . . . . . . . . . . . . . . . .26

Discussion and Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .27

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .30

Chapter 2: The Case for Hardening of the Target . . . . . . . . . . . . . . . .33

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .33

Why It Is Important to Test the Hardening Hypothesis . . . . . . . . . .35

An Adequate Test of the Hardening Hypothesis Is Needed . . . . . . .36

Dependence May Not Be the Most Relevant Cause of

Any Hardening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .37

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .38

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .38

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Smoking and Tobacco Control Monograph No. 15
Chapter 3: The Case Against Hardening of the Target . . . . . . . . . . . .41

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .41

Effect of Individual Factors on Heavy Smokers . . . . . . . . . . . . . . . . . . . . . . .42

Effect of Environmental Factors on Heavy Smokers . . . . . . . . . . . . .46

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .47

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .48

Chapter 4: Examining a Quarter-Century of Smoking Cessation

Trials: Is the Target Becoming Harder to Treat? . . . . . . . . . . . . . .49

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .49

Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .51

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .54

Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .55

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .59

Chapter 5: Changes in Measures of Nicotine Dependence Using

Cross-Sectional and Longitudinal Data from COMMIT . . . . . . . .61

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .61

Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .61

Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .64

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .64

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .65

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .70

Chapter 6: Changes in Smoking Habits in the American Cancer

Society CPS I During 12 Years of Follow-Up . . . . . . . . . . . . . . . . . .71

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .71

Cancer Prevention Study I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .71

Methods of Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .72

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .73

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .81

Chapter 7: Changes in Number of Cigarettes Smoked per Day:

Cross-Sectional and Birth Cohort Analyses Using NHIS . . . . . . . .83

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .83

Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .84

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .86

Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .95

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

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Smoking and Tobacco Control Monograph No. 15
Chapter 8: Changes in Cross-Sectional Measures of Cessation,

Numbers of Cigarettes Smoked per Day, and Time to

First Cigarette—California and National Data . . . . . . . . . . . . . .101

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .101

Changes in National Cessation Rates and Number of

Cigarettes Smoked per Day . . . . . . . . . . . . . . . . . . . . . . . . . . . .101

Changes in Cessation Rates, Number of Cigarettes Smoked

Per Day, and Time to First Cigarette in California,

1990 to 1999 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .110

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .123

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .125

Chapter 9: Hardening of the Target: Evidence from

Massachusetts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .127

Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .127

Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .130

Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .132

Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .132

Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .141

Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .143

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .143

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Smoking and Tobacco Control Monograph No. 15
Introduction

C. Tracy Orleans

The decline in U.S. smoking prevalence since the publication of the first

Surgeon General’s Report in 1964 has been hailed as one of the greatest

public health accomplishments of the past century (Warner 2001). Fortyfour million Americans—almost half of those who ever smoked—have quit,

and lung cancer death rates have decreased greatly as a result. As a nation,

we’ve launched wide-reaching tobacco control programs in worksites,

schools, communities, and all 50 states, and we’ve witnessed enormous

shifts in social norms, policies, and public attitudes. Growth in clean

indoor-air laws and smoking restrictions have made quit-smoking cues

“persistent and inescapable” (Glynn, Boyd, and Gruman 1990), and new

data shows that tobacco price increases and mass media cessation

campaigns can significantly increase population quit rates (CDC 2001).

Over the last three decades, we have developed effective clinical

treatments—psychosocial and pharmacological—and seen the publication

and update of authoritative practice guidelines recommending evidencebased treatments that, if universally applied, could double our national

annual quit rate in a highly cost-effective way (Cromwell et al. 1997; 

U.S. DHHS 2000). Prospects for preventing and treating tobacco use and

addiction have never been better.

Yet the papers in this monograph, Those Who Continue to Smoke: Is

Achieving Abstinence Harder and Do We Need to Change Our Interventions?,

raise important questions about what it will take to build on the successes

of the last century and, in particular, on the last few decades of research and

practice. While efforts to promote tobacco cessation need to be part of a

much broader national tobacco control strategy that emphasizes prevention,

it is clear that the greatest gains in reducing tobacco-caused morbidity,

mortality, and health care costs in the next 30 to 40 years will come from

helping addicted smokers quit (Orleans 1997). Further declines in adult

smoking are likely to strengthen prevention efforts as well, since adult

smoking is a critical determinant of social norms and a vector for youth

initiation.

In this context, the findings presented in this monograph have

important implications for the next generation of research and practice to

help addicted smokers quit. Specifically, these papers and the findings they

present indicate that helping more smokers quit will require: (1) developing

more powerful treatments that can break through the 25% to 30% quit-rate

ceiling achieved with our best existing treatments; (2) refining, targeting

and tailoring treatments for high-risk populations; (3) greatly improving

surveillance of quitting patterns and determinants; (4) developing combined

1

Introduction
clinical-public health approaches that harness synergies between evidencebased clinical treatments, and macrolevel policy and environmental

cessation strategies; and (5) improving the use of and demand for

treatments that work.

This is the central question addressed in

different ways by each of the papers in this

monograph. Surprisingly, none of the papers

presents compelling evidence that this is the case. But each paper offers

unique insights into what it will take to raise success rates of individually

oriented and population-based approaches.

Burns and Warner (see Chapter 1) approach this question by carefully

operationalizing the hardening construct and then testing the hardening

hypothesis against available national Current Population Survey (CPS) and

National Health Interview Survey (NHIS) data, 1964 to 1999, as well as

against data from the California Tobacco Survey (CTS), 1990 to 1999, and

the Community Intervention Trial for Smoking Cessation (COMMIT). Their

thoughtful paper asks clear questions and gives us mostly clear answers: 

• Is there epidemiological evidence that the nation’s annual quit rate

is falling? No, not at present. 

• Is there epidemiological evidence in the United States for decreased

cessation rates among groups in which more ever-smokers have

quit? No. 

• Is there epidemiological evidence that levels of dependence,

estimated by cigarettes per day or score on the Fagerström Tolerance

Questionnaire (1994), have increased in the United States as

prevalence has decreased? No. 

• Is there epidemiological evidence among current smokers for

increased psychiatric comorbidity among current smokers? The

answer here is uncertain, given the lack of systematic surveillance.

However, new data from the National Co-morbidity Study (Lasser 

et al. 2000) shows that patients with diagnosed psychiatric

disorders—ranging from anxiety disorders, phobias, and dysthymia

to other chemical dependencies to major depressive disorder and

schizophrenia—are twice as likely to smoke and currently consume

approximately 50% of the cigarettes sold in America. However,

Lasser et al. (2000) point out that lifetime quit rates for these

smokers are also fairly respectable (ranging from 27% to 34%

compared with 43% for smokers with no history of mental illness).

And finally, Burns and Warner highlight the growing concentration of

smokers in low socioeconomic status (SES) groups. However, in the absence

of evidence that low-SES smokers are any less likely to quit than those in

higher income groups when offered proven treatments or exposed to

effective cessation policies and environmental influences, it is difficult to

conclude support for the hardening hypothesis from these findings. 

IS THE TARGET HARDENING?

ARE SMOKERS LESS LIKELY TO

QUIT NOW THAN IN THE PAST?

2

Smoking and Tobacco Control Monograph No. 15
Hence Burns and Warner conclude that the hardening hypothesis

should continue to be tested, and evidence that hardening is actually

occurring should be required before it is used as a justification for changing

current tobacco control strategies.

Burns’ and Warner’s paper also raises some important questions about

language. They wisely cite John Slade’s caution about the use of hardening

as a term that could be construed to be demeaning or dismissive of people’s

quit attempts. Moreover, their findings suggest that a better question for

understanding and addressing the challenges of increasing our national quit

rate might be “is the target changing?” Substituting the word “changing” for

“hardening” immediately brings a wider range of solutions into view,

pointing not only toward future treatments that might be more intensive

but also toward those that might be more effective or better tailored,

packaged, promoted, and priced to reach their target populations.

Irvin and Brandon (see Chapter 4) offer another creative and rigorous

approach to testing the hardening hypothesis: reviewing published

cessation trials conducted in the United States to examine whether success

rates have declined. For cognitive-behavioral multicomponent treatments

published between 1977 and 1996, they found significant declines in

reported end-of-treatment, 3-month, and 6-month (but not 12-month)

abstinence rates—with mean 6-month quit rates declining about 10

percentage points, from over 40% to about 30%. Somewhat similar patterns

were observed for trials of nicotine gum (1984 to 1996), transdermal

nicotine (1990 to 2000), and varied placebo treatment conditions 

(1983 to 1999).

However, while they carefully examined and attempted to control for a

range of potentially confounding and mediating variables (e.g., mean age,

years smoked, daily smoking rate, Fagerström Tolerance Questionnaire

scores), Irvin et al. point out that they may have missed key mediating

variables (especially those related to nonspecific treatment effects) and had

limited statistical power to detect mediation effects. In fact, it is quite

possible that early adopters of these treatments (both smokers and

clinicians) brought higher treatment expectations than later adopters, and

that those smokers who were among the first to try each of these treatments

had higher treatment-related self-efficacy based on fewer past, unsuccessful

quit attempts or treatment experiences. Moreover, while these trials were

conducted during periods of significant decline in national adult smoking

prevalence, participants represented a very small subset of all U.S. smokers

who tried to quit. The 1986 Adult Use of Tobacco Survey (AUTS) found, for

instance, that only 30% of smokers tried to quit that year, and that only

10% to 15% of them used any formal treatment (2% to 4% counseling, 

3% to 12% nicotine gum) (Fiore et al. 1990). Hence these published

treatment studies provide limited insight into national quitting patterns and

practices. Irvin and Brandon conclude that they cannot establish that their

findings are consistent with the “population target hardening” theory.

3

Introduction
The clear look we get from Irvin and Brandon (see

Chapter 4) at the performance of the same basic (essentially

unchanged) treatments in published reports dating back 25

years, and over periods of time ranging from 10 to 19 years,

begs a more fundamental question: is it our smokers, or our

treatments, that have hardened? As Shiffman pointed out in his landmark

1993 paper (Shiffman 1993), behavioral intervention quit rates plateaued in

the 1980s after a period of rapid innovation and improvement in the 1970s.

Shiffman concluded in 1993 that behavioral cessation research “was in a

rut” and challenged the field to renewed innovation. A few years later,

Rimer (1997) pointed out that behavioral medicine research in general was

suffering from “a hardening of the theories”—reflecting a growing tendency

to abandon both formal theory testing and new theory development. And

Piasecki and Baker (2001) recently reached a very similar conclusion, noting

that not much had changed since Shiffman’s review and concluding that

“the rut had deepened.”

Each of these reviews makes it clear that we will need to reinvigorate the

science base driving treatment research if we are to develop new clinical

treatments that can break through current 25% to 30% quit-rate ceilings.

This will require new theory and more creative application of existing

theory to expand beyond reliance on the handful of cognitive behavioral

theories and models on which most recent tobacco dependence treatment

research has been based (Orleans 1997). Progress also is likely to come from

examining new combinations of pharmacologic and behavioral treatments,

developing treatments that are biologically and developmentally tailored as

well as environmentally and culturally tailored, and making tobacco

dependence treatments more holistic by addressing related lifestyle risks and

comorbid conditions. A return to the study of how today’s smokers actually

quit and how they use existing treatments could furnish important new

insights.

Innovative transdisciplinary research efforts, like those supported

through the new Tobacco Use Transdisciplinary Research Centers (TUTRCs),

cofunded by the National Cancer Institute, the National Institute on Drug

Abuse, and the Robert Wood Johnson Foundation, are promising incubators

for discovering more powerful approaches to tobacco dependence

treatments and public health cessation strategies. Research that bridges the

clinical and public health domains, connecting the science of individual

behavior change (i.e., individually oriented tobacco dependence treatment)

with the science of population-based cessation (i.e., policies and

environmental influences that promote cessation in organizations,

communities, or larger populations), could be equally transformative—

pointing us not only toward more effective treatments and cessation

interventions but also toward more effective dissemination strategies to

spread their use and application.

ARE WE SEEING A

HARDENING OF THE

POPULATION? OR A

HARDENING OF OUR

INTERVENTIONS?

4

Smoking and Tobacco Control Monograph No. 15
At the 2002 Society for Research on Nicotine and

Tobacco meeting, Gary Giovino presented a

systematic overview of the epidemiology of

quitting in America, based on analysis of trends

from 1965 to the present in several national data

sets (CPS, NHIS, National Household Survey on

Drug Abuse, and Monitoring the Future), which

confirms a slow but continuing rise in our national annual quit ratio for

most adult smoker populations. Trend analyses (national and state) of

cigarettes per day and some-day smoking do not indicate hardening. And,

despite suggestive evidence for a slight increase in indicators of addiction

from 1985 to 1994, trends in measures of dependence do not support the

view that U.S. tobacco control efforts have led to proportionately more

quitting among less dependent smokers or left behind a population of

proportionately more dependent smokers (see also Giovino 1996).

Perhaps most provocative, however, are NHIS data showing much

higher quit ratios for some groups than others. Adults aged 18 to 24 and 

25 to 44 have the highest rates of current smoking prevalence and lowest

quit ratios, while those aged 65 and over and 45 to 64 have the lowest rates

of current smoking prevalence and highest quit ratios. Similarly, smoking

prevalence is highest and quit ratios are lowest among Americans with fewer

than 12 years of education compared with those having a college education

or higher. Similar findings have been reported for racial/ethnic minority

adult populations (e.g., Boyd et al. 1998; Gilpin et al. 2001). These stark

contrasts underscore the need to target and tailor our interventions better to

these high-risk groups.

The contrast most germane to the target-hardening hypothesis is that

between older adults (65 and over) and young adults (aged 18 to 24):

• Older adults represent a population in which the prevalence of

smoking has declined to a very low level (10.6% in 2000) and thus

comprises a group in which the most “hardening” should have

occurred, a group with the greatest potential recalcitrance to

standard treatment approaches. However, with access to in-depth

national surveillance data from the 1986 AUTS (Fiore et al. 1990)—

which clarified how older adults tried to quit, thought about

quitting, what their misconceptions were (e.g., “it’s too late to

quit”), and identified covariates of successful quitting—we were able

to develop population-targeted self-help and primary care

treatments designed specifically for them that produced quit rates as

high, if not higher, than those seen with the same general

approaches in younger populations (e.g., Orleans et al. 1994; Rimer

et al. 1994). A strict target-hardening theory would have predicted

poorer outcomes.

• In contrast, younger adult smokers, with the highest smoking

prevalence (27.9% in 2000), represent the group in which, by

definition, the least hardening has occurred. Yet quit rates with

standard treatment approaches (counseling, pharmacotherapy)

WHAT CAN WE LEARN FROM

AND ABOUT SPECIAL

POPULATIONS? HOW CAN

BETTER SURVEILLANCE

HELP US TO DESIGN BETTER

TREATMENTS AND

DISSEMINATION EFFORTS?

5

Introduction
effective for most adult populations have proven ineffective and

unappealing with these younger smokers (Sussman 2002), likely

reflecting the different determinants of quitting motivation and

success in this population. Unfortunately, given the dearth of

national survey data on youth quitting determinants and practices,

we are handicapped in developing treatments to better assist them.

The interesting contrast in treatment recalcitrance between these two

groups, older and younger smokers, not only challenges the hardening

hypothesis but also points strongly to the need for much better surveillance

of current quitting motives, barriers, and practices among all smoker

populations in the United States. Such survey data could be systematically

used to develop more appealing treatments and more effective methods for

promoting their use in the targeted populations (Boyd et al. 1998). Without

such data, we are working very much in the dark to help more smokers

quit. 

Systematic longitudinal, nationally representative surveys could help us

to engineer more effective treatments and public health cessation strategies

and systematically evaluate impacts of varying public policy and

environmental interventions. Such surveillance is especially critical now,

given the emergence of new so-called reduced-harm tobacco products.

Marketed as safe alternatives to quitting, these products may lure many

would-be quitters away from serious quit attempts and existing treatments.

Monitoring these trends nationally is essential. Improved cessation

surveillance should include a special focus on high-risk populations—

including youth, racial/ethnic minorities, low-SES groups, as well as smokers

with psychiatric comorbidity (Lasser et al. 2000). It is not reasonable to

assume that one size fits all when it comes to motivating and assisting

smokers to quit, and these populations continue to merit special targeting.

To begin to address neglected surveillance needs, the Robert Wood

Johnson Foundation, the Centers for Disease Control and Prevention, and

the National Cancer Institute (NCI) are cofunding a youth cessation panel

study that will, beginning in 2003, longitudinally follow smokers aged 16 to

20 over two years, and the NCI has identified the need for prospective

observational studies of quitting and relapse processes in its 2004 bypass

budget. However, more extensive efforts are needed. Comprehensive

sustained surveillance would provide the compass we now lack to reach the

2010 quitting goals we have set for the nation (U.S. DHHS Healthy People

2010).

Hughes’ paper (see Chapter 2) underscores the need for

broad-spectrum approaches that combine effective

clinical treatments with effective policy and

environmental approaches. The past three decades of

research have given us vital resources, two sets of

evidence-based tobacco intervention guidelines on

which we can draw to find new and better ways to help

addicted smokers quit: (1) clinical practice guidelines for

treating tobacco use and dependence (U.S. DHHS 2000),

IMPORTANCE OF

WIDENING THE LENS—

COMBINING CLINICAL

AND BROADER

POLICY-BASED AND

PUBLIC HEALTH

APPROACHES AND

BUILDING CONSUMER

DEMAND

6

Smoking and Tobacco Control Monograph No. 15
and (2) public health guidelines for policy and macrolevel environmental

strategies that can help spur quitting by changing the larger social and

political contexts in which smokers live and work (e.g., tobacco price

increases, smoking bans and restrictions, mass media campaigns, policies

that reduce smokers’ out-of-pocket treatment costs) (CDC 2001).

Hughes (see Chapter 2) proposes that raising tobacco prices,

cessation-oriented media campaigns, and provider advice may have primary

impacts on smokers’ quitting motivation and attempt rates, while

improving treatment efficacy and access may primarily affect quitting

success rates among those who make attempts. Unfortunately, without

systematic and ongoing cessation surveillance, it is difficult to test these

hypotheses, to assess the differential effects of policy and treatment

advances on our national quitting profile, or to understand the mechanisms

through which these different strategies exert their influence.

As a nation, we have only just begun to understand how to implement

these clinical or public health strategies fully or to capitalize on the synergy

between them. Lessons learned from states with comprehensive tobacco

control policies and programs (e.g., California, Massachusetts, and Oregon)

offer vital clues and inspiration. California provides one of the nation’s

most important laboratories for these kinds of studies (Warner 2000) and

serves as a model for the nation.

Elements of California’s comprehensive 12-year Tobacco Control

Program have included: a statewide smokers’ telephone helpline,

antitobacco media campaigns (including those designed specifically to

motivate quitting and helpline use), local smoking cessation programs,

increases in insurance coverage for nicotine pharmacotherapy, clean indoorair laws, campaigns educating smokers about the dangers of environmental

tobacco smoke, tobacco tax increases and enforcement of youth access laws

(Fichtenberg and Glantz 2000; Gilpin et al. 2001). These initiatives led to a

spontaneous grassroots movement supporting voluntary in-home smoking

bans across the state. In fact, 25% of smokers in California now live in

smokefree homes, and they report higher quit attempts and quit rates

(Gilpin et al. 2001). 

While we know little about which of these statewide program elements,

alone or in combination, was most responsible for California’s rising quit

rates, and even less about the mechanisms of change (e.g., exactly how

in-home smoking bans are helping more smokers quit), we do have

evidence that this comprehensive strategy has worked. From 1989 to 1997,

adult smoking prevalence in California dropped 33% compared with 22% in

the rest of the country. Rates of lung cancer declined 14% (compared with

4% in the rest of the country), and an estimated 33,000 cardiovascular

disease deaths were prevented. Through reduced health care costs, a $3.62

return was estimated for every $1.00 invested (Fichtenberg and Glantz

2000). The NCI monograph Population-Based Smoking Cessation (NCI 2000)

projected that if comprehensive tobacco control programs like California’s

were implemented nationally, quit rates would increase by one-third every

year, creating 500,000 new ex-smokers annually.

7

Introduction
Consistent with the data Burns and Warner (see Chapter 1) present for

declining addiction levels among California smokers over the last decade,

the most recent state survey data (Gilpin et al. 2001) indicate that

California’s lower smoking prevalence has been accompanied by a softening

rather than hardening of the smoker population. The proportion of light

smokers (<15 cigarettes per day) increased from 44% in 1990 to 60% in

1999. Smokers reporting serious past-year quit attempts rose from 49% in

1990 to 62% in 1999. The percentages of attempting quitters who succeeded

(24%) and of so-called “hardcore” smokers who reported never expecting to

quit (10%) were similar in 1990 and 1999.

Finally, California’s results, while very encouraging, also demonstrate

the need to dramatically widen the reach, use, and appeal of effective

treatment services in order to take full advantage of the softening that has

occurred. The proportion of quitters using any formal quitting aids rose

only 4 percentage points, from 18% in 1990 to 22% in 1999, and rates of

physician advice to quit rose only 8 percentage points, from 38% to 46%,

during the same period (Gilpin et al. 2001). These rates may in fact be

higher than (unknown) national rates, but they are not high enough,

especially in underserved low-income and minority populations (Fiore et al.

1990; Gilpin et al. 2001). At the same time that we are investing in research

to discover more powerful clinical treatments and public health cessation

strategies, we could realize a more rapid return on investment from parallel

efforts to improve the reach and appeal of existing treatments and to boost

consumer demand for them (Orleans 2001).

In studies and in situations in which we’ve succeeded in expanding

treatment coverage and reducing smoker out-of-pocket costs, we’ve found

that only a minority of smokers come forward (Curry et al. 1998;

Mordavsky et al. 2002)—evidence that more can be done to market our

treatments effectively or design (or redesign) them for wider use and appeal.

Media campaigns to promote quitting or quitline use, both in general

populations and in smoker subgroups (African-American smokers, HMO

enrollees, and pregnant smokers), have been very successful in getting

smokers to call for help. And those who do call quit at predicted rates (Boyd

et al. 1998; CDC 2001). In fact, media cessation campaigns are

recommended by the Centers for Disease Control and Prevention (CDC) as

an effective cessation strategy (CDC 2001). But, to date, we have invested

relatively little energy and dollars in these media strategies or in other forms

of creative-treatment marketing or packaging to boost consumer demand. 

In contrast, our competition, the tobacco industry, invests over $8 billion a

year marketing cigarettes and tobacco products (FTC 2001).

Going forward, we need to pursue a two-part strategy—striving both to

discover new, more powerful treatments and to get better results from

disseminating the proven, science-based interventions we have developed.

Just as we need transdisciplinary basic biobehavioral research to discover

new quitting approaches, so do we need to bring fresh new perspectives to

bear from business, marketing, product design, economics, communications, even new dissemination science to study how quitters actually use

our best evidence-based treatments, to reinvent and repackage them for

8

Smoking and Tobacco Control Monograph No. 15
greater appeal, use, and efficacy. Even small pilot grants to interdisciplinary

teams might lead to breakthrough product packaging or delivery

improvements that could incorporate what we know to be the most

effective treatment elements, comply with U.S. Public Health Service (PHS),

CDC, and Food and Drug Administration (FDA) guidelines, and prove to be

more widely applicable and cost-effective. These and other disseminationfocused initiatives now being launched or planned by a variety of funders—

including the National Partnership to Help Pregnant Smokers Quit (2002)

and the National Blueprint for Disseminating and Implementing Evidence-Based

Clinical and Community Strategies to Promote Tobacco Use Cessation (AHRQ

2002)—could allow us to more fully harvest the fruits of past intervention

research and capitalize on the unprecedented potential for social and

financial support for smokers’ quitting efforts. 

9

Introduction

REFERENCES

Agency for Health Care Research and Quality.

National Blueprint for Disseminating and

Implementing Evidence-Based Clinical and

Community Strategies to Promote Tobacco Use

Cessation. Washington, DC: Agency for Health

Care Research and Quality, June 2002.

Boyd, N. R., Sutton, C., Orleans, C. T. et al. Quit

today! A targeted communications campaign to

increase use of the Cancer Information Service

by African American smokers. Preventive Medicine

1998;27:S50–S60.

Burns, D. M., Warner, K. E. Smokers who have not

quit: Is cessation more difficult and should we

change our strategies? (Chapter 1 of this

monograph.)

Centers for Disease Control and Prevention. The

guide to community preventive services; State

and local opportunities for tobacco use

reduction. American Journal of Preventive Medicine

2001;20(Suppl 2):8–9.

Cromwell, J., Bartosch, W. J., Fiore, M. C. et al. 

Cost-effectiveness of the clinical practice

recommendations in the AHCPR Guidelines for

Smoking Cessation. Journal of the American

Medical Association 1997;278:1759–766.

Curry, S. J., Grothaus, L. C., McAfee, T. et al. Use

and cost-effectiveness of smoking-cessation

services under four insurance plans in a health

maintenance organization. New England Journal

of Medicine 1998;339:673–79.

Fagerström, K. O. Measuring the degree of

dependence to tobacco smoking with reference

to individualization of treatment. Addictive

Behaviors 1994;19:33–39.

Federal Trade Commission. Federal Trade Commission

Cigarette Report for 1999. Washington, DC:

Federal Trade Commission, 2001.

Fichtenberg, C. M., Glantz, S. Association of the

California tobacco control program with

declines in cigarette consumption and mortality

from heart disease. New England Journal of

Medicine 2000;343:1772–777.

Fiore, M. C., Novotny, T. E., Pierce, J. P. et al.

Methods used to quit smoking in the United

States: Do cessation programs help? Journal of

the American Medical Association

1990;263:2760–765.

Gilpin, E. A., Emery, S. L., Farkas, A. J. et al. The

California Tobacco Control Program: A Decade of

Progress, 1989–1999. La Jolla, CA: University of

California at San Diego, 2001.

Giovino, G. Tobacco control and nicotine

dependence. Tobacco Control 1996;5:1–3.

Glynn, T. J., Boyd, G. M., Gruman, J. Essential

elements of self-help/minimal intervention

strategies for smoking cessation. Health

Education Quarterly 1990;17:329–45.

Hughes, J. R. The case for hardening of the target.

(Chapter 2 of this monograph.)

Irvin, J. E., Brandon, T. Examining a quarter-century

of smoking cessation trials: Is the target

becoming harder to treat? (Chapter 4 of this

monograph.)

Lasser, K., Boyd, J. W., Woolhandler, S. et al.

Smoking and mental illness: A population-based

prevalence study. Journal of the American Medical

Association 2000;284(20):2606–610.

Mordavsky, J. K., Schauffler, H. H., Barker, D. C. 

et al. Coverage of tobacco dependence

treatments for pregnant women under Medicaid

and for children and parents under EPSDT.

American Journal of Public Health, in press.
National Cancer Institute. Population-Based Smoking

Cessation: What Works. Smoking and Tobacco

Control Monograph No. 12, edited by D. Burns, 

D. Shopland. NIH Pub. No. 00-4892. Bethesda,

MD: U.S. Department of Health and Human

Services, National Cancer Institute, 2000.

National Partnership to Help Pregnant Smokers

Quit. National Partnership to Help Pregnant

Smokers Quit: Action Plan. Princeton, NJ: Robert

Wood Johnson Foundation, May 2002.

Orleans, C. T. The challenge of translating research

to practice: Everything I needed to know I

learned from tobacco. Presidential address to

Society of Behavioral Medicine, March 2001, at

Seattle, Washington.

Orleans, C. T. Reducing tobacco harms among older

adults: A critical agenda for tobacco control.

Tobacco Control 1997;6:161–63.

Orleans, C. T., Jepson, C., Resch, N. et al. Quitting

motives and barriers among older smokers: The

1986 Adult Use of Tobacco Survey revisited.

Cancer 1994;74:2055–61.

Piasecki, T. M., Baker, T. Any further progress in

smoking cessation treatment? Nicotine and

Tobacco Research 2001;3:311–23.

Rimer, B. K. Toward an improved behavioral

medicine. Annals of Behavioral Medicine

1997;19:6–10.

Rimer, B. K., Orleans, C. T., Fleisher, L. et al. Does

tailoring matter? The impact of a tailored guide

on ratings and short-term smoking-related

outcomes. Health Education Research

1994;9:69–84.

Shiffman, S. Smoking cessation treatment: Any

progress? Journal of Consulting and Clinical

Psychology 1993;61:718–22.

Sussman, S. Effects of sixty-six adolescent tobacco

use cessation trials and seventeen prospective

studies of self-initiated quitting. Tobacco Induced

Diseases 2002;1:35–81. 

U.S. Department of Health and Human Services,

Healthy People 2010, n.d.,

(http://www.health.gov/healthypeople)

(January 22, 2001).

U.S. Department of Health and Human Services.

Treating Tobacco Use and Dependence.

Washington, DC: U.S. Public Health Service,

June 2000.

Warner, K. E. The need for, and value of, a multilevel approach to disease prevention: The case of

tobacco control. In Promoting Health: Intervention

Strategies for Social and Behavioral Research, edited

by B. D. Smedley and S. L. Syme, 417–50.

Washington, DC: National Academy Press, 2001.

10

Smoking and Tobacco Control Monograph No. 15
Smokers Who Have Not Quit: 

Is Cessation More Difficult and Should

We Change Our Strategies?

David M. Burns, Kenneth E. Warner

In the early 1950s, recognition that cigarette smoking is a cause

of disease led to substantial and sustained efforts to persuade smokers to

quit smoking and to assist them in their attempts to achieve abstinence

(U.S. DHHS 2000). Approximately half of those who have ever smoked have

currently quit smoking (CDC 1999b), demonstrating that successful

smoking cessation is both possible and has been widely achieved. 

Increasing costs of smoking, changing social norms, more successful

cessation methods, and persistent and inescapable messages to quit, coupled

with support for cessation, have all likely contributed to these changes in

smoking behavior (CDC 1999a; U.S. DHHS 2000). However, even in the face

of all of these efforts, 45 million Americans remain cigarette smokers, and

the rate of decline in smoking prevalence appeared to stall during much of

the 1990s (CDC 1999b; see Chapters 7 and 8). Part of this stabilization of

smoking prevalence is due to a recent increase in rates of smoking initiation

among adolescents (Johnston et al. in press), but there also appears to have

been a decline in rates of cessation among adult smokers between the

periods covered by the 1992/93 and 1995/96 Current Population Survey

(CPS) (Burns et al. 2000a). The most recent CPS (1998/99) shows a rise in

rates of cessation back to the levels recorded in the 1992/93 CPS. However,

the slowing in the rate of decline in smoking prevalence and the fall in rates

of cessation in the mid-1990s raise a question whether those smokers who

are left behind by not having quit are substantively different in their ability

to achieve abstinence compared with those who have quit(see Chapter 2;

Warner and Burns in press 2003); that is, does the population of smokers

currently targeted with cessation efforts have more difficulty in achieving

long-term abstinence than previous generations of smokers, are they less

likely to achieve abstinence, and have they become more resistant to

existing interventions?

There are two parts to these questions. First, have those smokers who

could easily quit done so, leaving behind a residual group of smokers who

cannot achieve abstinence, do not want to quit, or have much more

difficulty quitting? Second, are the smokers who remain less likely to be

reached by existing cessation interventions or less likely to respond to

them? The answers to these questions define where programmatic tobacco

control efforts should invest their resources. In particular, fundamental to

planning for the delivery of tobacco control activities is the question

INTRODUCTION

11

Chapter 1
whether we should shift resources away from current comprehensive

tobacco control interventions, with their focus on media, changing social

norms, and implementing public policy changes, and move resources

toward more individualized and intensive cessation assistance. This

monograph takes some initial steps toward answering these questions, with

particular emphasis on the first of them: is there evidence that the residual

population of smokers is having more difficulty achieving successful

abstinence?

The chapter begins with a discussion of how hardening of the smoking

population over time might be defined and what changes in a population of

smokers could lead to the remaining smokers’ having more difficulty

achieving abstinence. We then explore the evidence for trends over time in

the characteristics of smokers that reflect these changes and for trends in

whether they are influencing cessation. Finally, we attempt to integrate

these data to form an understanding of how the population of residual

smokers has changed and what it may mean for tobacco control. While a

definitive conclusion is premature, there is little evidence that cessation

rates are falling due to hardening of the residual smoking population or that

the residual population of smokers has become resistant to cessation or

unresponsive to current tobacco control approaches. 

We use the term hardening in this volume as a convenient shorthand to

describe changes in difficulty of quitting, in measures of smoking behavior

and cessation, in the characteristics of the smoking population, and in the

smoking population’s becoming more resistant to cessation interventions.

There is a reasonable concern that use of this term may be demeaning to

continuing smokers who cannot quit or dismissive of their cessation efforts

(J. Slade, personal communication). That is not the intent of this

monograph. The term is in widespread use as a description of the changing

trends in smoking cessation and therefore, rather than substituting a new

term, it is used here too.

On an abstract level, the question whether, on average, the

population of residual smokers has more personal difficulty

achieving successful abstinence than a population who has already quit can

only be answered in the affirmative. It is logically compelling that those

who have successfully quit must, as a group, have had less difficulty

achieving abstinence than those who, having tried to quit unsuccessfully,

continue to smoke in the face of great pressure not to. These residual

smokers should, as a group, also find achieving abstinence more difficult

than those who have already quit successfully. This greater difficulty in

achieving abstinence, and the lower rate of successful quitting that should

result, could leave behind a population of smokers which is hardening over

time (see Chapter 2). This definition of hardening refers to an increasing

population mean in the difficulty of achieving abstinence among those who

continue to smoke. 

Whether this increasing difficulty in quitting over time lowers actual

abstinence would depend on changes in the availability and effectiveness of

cessation methods, social support for abstinence, and environmental norms

DEFINITION OF

THE QUESTION

12

Smoking and Tobacco Control Monograph No. 15
encouraging cessation. Among the forces influencing cessation rates and

successful abstinence are individual characteristics of the smoker (U.S.

DHHS 1990) and factors in the environment in which smoking takes place

(NCI 2000). Rates of successful cessation in the population of residual

smokers are likely determined by a balance between increases in the

difficulty of achieving abstinence and increases in the forces and resources

promoting cessation. Environmental influences promoting cessation and

supporting abstinence may be increasing over time, thus counterbalancing

the greater individual difficulty in achieving cessation (see Chapter 3). 

This abstract definition of hardening offers little assistance in defining

which characteristics of the smoking population have changed or how we

might adjust our interventions to respond to these changes. To move from

the abstract to the pragmatic, measures and characteristics of the smoking

population associated with difficulty in achieving abstinence need to be

identified. Changes over time in these measures or in characteristics of the

population of residual smokers can then be examined to see how tobacco

control programs can respond. In forcing the discussion of hardening

toward objective and quantitative measures of smokers and their behavior,

we lose the ability to consider difficulty in achieving abstinence as a

qualitative reality. However, these qualitative considerations do little but

lead us back to the compelling logic that those who have not quit must

have more difficulty achieving abstinence than those who are already

abstinent. Objective and quantifiable measures of hardening may lack the

richness of qualitative measures in describing hardening, but they offer an

opportunity to examine changes in the measures over time as a test of

whether hardening is occurring. 

In addition, the changes in personal difficulty of achieving abstinence

occurred over the same interval of time that the changes that motivate and

support cessation also occurred in the general environment. Actions taken

by smokers are the net result of these competing trends. Examining trends

over time in specific smoking actions (cessation attempts and success,

number of cigarettes smoked, and time to first cigarette as a measure of

addiction) quantifies the net effect of the qualitative changes occurring

among smokers and in the environment in which they smoke in order to

determine which is exerting the larger influence on current smokers’

behavior. The implications of these net effects for current tobacco control

programs can then be considered. In choosing quantitative measures to

examine whether hardening is occurring, we are able to define the presence

or absence of net changes in smoking behavior consistent with hardening,

but not whether qualitative differences in the difficulty of successful

cessation are occurring. 

It may be important to differentiate between cessation attempts and

long-term abstinence in considering whether cessation rates are declining in

the residual population of smokers. One can describe reduced cessation as a

decline in quit attempts, a decline in the fraction of quit attempts that

result in long-term abstinence, or a decline in the rate of long-term

abstinence. Individual characteristics of smokers or particular tobacco

13

Chapter 1
control interventions may influence quit attempts without affecting longterm abstinence, and the reverse may be true as well: cessation success may

be influenced without increasing quit attempts. Data on both quit attempts

and cessation success are presented in this monograph. However, as a

general approach, the term hardening is used in this monograph to describe

an effect on the difficulty or probability of achieving long-term abstinence

among smokers, rather than the rate at which smokers try to quit or the

fraction of quit attempts that are successful.

One central measure of hardening is a fall in long-term abstinence

rates for all current smokers as a group. Falling abstinence rates are

perhaps the most direct outcome measure of hardening and, on one level,

are by definition a hardening of the residual smokers. Abstinence rates

suffer from two principal limitations as a measure of hardening, however. 

First, cessation rates have changed over the past several decades (U.S.

DHHS 1990, Burns et al.1997), both rising and falling over time. A decline

in cessation may be due to changes in the external environment (e.g.,

reduction in the price of cigarettes) that may influence cessation activity

and interest, or the decline may be due to the residual population of

smokers having more difficulty achieving abstinence once those who could

easily quit have dropped out of the smoking population. Over a short time

interval, or if global changes in cessation are the only measure used, it may

not be possible to distinguish between temporal trends in cessation activity

and changes in the characteristics of smokers being targeted by tobacco

control efforts, or, if both are occurring, to define their relative

contributions. A short-term rise in global cessation rates due, for example,

to an increase in taxes on cigarettes, may mask or overwhelm the

appearance of hardening among residual smokers. Improved abstinence

rates may also be due to improvements in the effectiveness of cessation

interventions even if the residual smokers have more difficulty, on an

individual level, in achieving cessation. 

A second limitation of using global abstinence rates as a measure of

hardening is that it offers little information as to how that hardening has

occurred or what we might do to respond to it.

An alternative to a global fall in abstinence rates is the possibility that

those demographic groups in which cumulative abstinence has been

higher—for example, in the most highly educated—are now composed of

individuals who are strongly resistant to cessation messages. Those smokers

with greater than a college education who continue to smoke in spite of

strong social disapproval, diminishing locations where they can smoke, and

repetitive information and advice to quit could represent a hardcore, highly

resistant group of smokers; one would expect to see cessation and

abstinence rates fall for that group. If abstinence rates for more educated

smokers fall, the historical gradient in cessation activity and success by level

of education should also diminish. For example, if the higher rates of

abstinence among smokers with a college education means that those left

behind are a more highly resistant group of residual smokers, then the ratio

of cessation rates for smokers with more education compared with those

MEASURES OF

HARDENING

14

Smoking and Tobacco Control Monograph No. 15
smokers with less education would diminish over time, as would the

magnitude of the effect of education as an independent positive predictor of

abstinence. The hallmark of this form of hardening would be diminishing

cessation and abstinence rates among those groups with the lowest smoking

prevalences. 

Countering the trend toward diminishing cessation among the most

highly educated might, potentially, be greater availability of, or these

individuals’ increased willingness to participate in, effective tobacco

interventions. Those individuals with high levels of education who

continue to smoke may also encounter substantially greater negative social

reinforcement for their smoking, and negative social norms may be

increasing more rapidly over time for that group of smokers. However, if the

magnitude of the differential in abstinence by level of education persists for

those with greater education, it is difficult to argue that existing tobacco

control approaches are not working. The same line of reasoning can be

applied to examining trends for other subgroups of the population among

whom smoking prevalence rates have fallen more rapidly than among the

general population.

Hardening can also be conceptualized to mean less intense or lessaddicted smokers have quit, leaving behind a heavier-smoking and more

heavily addicted group of smokers. This conceptualization could be

measured by increases in intensity of smoking or in measures of addiction

among the residual population of smokers. Once again, it would seem to be

logically inescapable that higher rates of cessation success among lighter or

less-addicted smokers must leave behind a population who, on average,

smokes more heavily and is more addicted. However, changes in selfreported number of cigarettes smoked per day are likely to be influenced by

factors other than differential cessation rates across levels of intensity of

smoking. These influences include, among others, restrictions on where

smoking is allowed and increases in the price of cigarettes. Many of these

factors have changed over the past several decades, confounding the use of

temporal trends in intensity of smoking as a measure of hardening. It is also

possible that as smokers age or experience more restrictions on their

smoking behavior, their level of addiction may decline, leading, over time,

to a fall in measures of the strength of addiction. However, if selective

cessation by lighter and less-addicted smokers reduces rates of successful

abstinence among the remaining smokers, some increase in intensity of

smoking or in measures of addiction should be evident over time, or we

should see dramatic declines in abstinence rates among more intense and

addicted smokers. Again, this decline in cessation success could be blunted

if these addicted smokers increasingly use new or more effective tobacco

intervention resources.

A more complex concept of hardening is that residual smokers are not

necessarily more addicted but that they have fewer resources on a personal

level to overcome their addiction or have greater barriers to any behavioral

change. For example, comorbidity with alcohol or drug use, depression, or

other psychiatric illness can make cessation success less likely. If the

15

Chapter 1
smoking population were increasingly concentrated among individuals with

these comorbidities, then it would be a population with much greater

difficulty in quitting.

A final concept of hardening focuses less on the individual smoking

behavior of the smoker and more on where they are concentrated

demographically in the population. Higher rates of successful smoking

cessation among those with greater levels of education, income, and other

characteristics have concentrated the residual smoking population among

the poor and the less educated (U.S. DHHS 1990, 2000). These individuals

may well need more assistance to quit smoking for a variety of reasons, but

they are also the groups that have the least exposure to cessation messages

and assistance. This concept of hardening allows for the possibility that a

fall in cessation rates may not be due to an intrinsically more difficult

target, but rather to a target that is less exposed to existing cessation

interventions and has received less intervention.

This monograph presents evidence for each of these concepts of

hardening in an effort to clarify what is known about changes in the

characteristics of the smoking population over time and their implications

for tobacco control interventions.

The fraction of those who have ever smoked but have

successfully quit increased dramatically over the last halfcentury (U.S. DHHS 2000) to the point at which

approximately one-half of those who have ever smoked are currently former

smokers (CDC 1999b). However, declines in per capita consumption slowed

dramatically during the midpart of the 1990s, and the CPS data show a

decline in cessation attempts and abstinence between the 1992/93 and

1995/96 surveys (see Chapter 8). These observations raise a concern that

those smokers who could easily quit, or who could be influenced by existing

tobacco control approaches to quit, have done so, leaving behind a residual

population of smokers who are more heavily addicted and who need new or

more individualized cessation interventions (see Chapter 2). Both anecdotal

and systematic observations of contemporary smokers participating in

smoking cessation clinical interventions suggest that these smokers are less

successful in achieving long-term abstinence than were smokers in prior

years (Irvin and Brandon 2000; see Chapters 4 and 9).

In contrast, following the price increases that resulted from the Master

Settlement Agreement (MSA), per capita cigarette consumption began

declining (see Chapter 8). Data from the 1998/99 CPS show that cessation

measures (both quit attempts and prevalence of 3-plus–month abstinence

among those who were daily smokers one year prior to the survey) have

returned to the 1992/93 levels (see Chapter 8). This increase in measures of

cessation was evident even before the increase in the price of cigarettes

triggered by the MSA, suggesting that it was at least in part a temporal trend

rather than simply a response to price. Changes in per capita consumption

and measures of cessation in California following a greater increase in price

due to a combination of the MSA plus an increase in the tax on cigarettes

demonstrate that price increases maintain their ability to change smoking

HAVE CESSATION AND

ABSTINENCE RATES

FALLEN OVERALL?

16

Smoking and Tobacco Control Monograph No. 15
behavior (see Chapter 8). The magnitudes of the per capita consumption

changes observed nationally and in California are similar to those predicted

based on changes in the price of cigarettes that occurred in previous

decades, showing that the impact of price as a tobacco control intervention

has not diminished.

These recent observations suggest that the absence of a decline in per

capita consumption and the fall in cessation observed during the mid-1990s

may be due to temporal variations in cessation activity and smoking

behavior rather than the result of hardening of the smoking population.

However, it remains to be demonstrated whether the recent improvements

in per capita consumption and cessation can be sustained by interventions

other than price increases, or whether cessation activity will again fall once

the effect of the price increases dissipates.

Compared with past generations of new smokers, if smokers who began

smoking in recent years are less interested in quitting or less able to achieve

abstinence, then the population of current smokers could be hardening due

to changes in the characteristics of those who initiate smoking rather than

those who quit. However, there is little evidence that the new generation of

young smokers is more heavily addicted or less likely to quit than earlier

generations of smokers. Data from the Monitoring the Future Study

(Johnston, O’Malley, and Bachman 2000) for high school seniors in the

United States show a decline from the late 1970s to the present in the

percentage of adolescent smokers who are daily smokers and who are daily

smokers who smoke 10 or more cigarettes per day.

It seems clear that the residual population of smokers who generated

concerns about hardening by its decline in cessation rates during the mid1990s remains responsive to tobacco control interventions, at least with

respect to increasing price.

Low smoking prevalence rates by geographic area or

by demographic subgroup are achieved, in part, by

increased cessation. Variability in the difficulty of

achieving sustained abstinence among individual

smokers should result in the population of remaining

smokers containing a higher fraction of those who have difficulty quitting,

unless changes in other factors affecting the difficulty of successful cessation

are occurring simultaneously. This trend should occur for subgroups of the

population as well as for the population as a whole. In particular, one might

expect the greatest hardening among those geographic and demographic

subgroups that have a higher fraction of ever-smokers who have quit and

therefore a lower prevalence of current smokers.

Lower smoking prevalence by geographic area is likely to be associated

with increased environmental and social pressure to quit as well as with the

presence of successful tobacco control programs. Individuals who continue

to smoke in those locations do so despite strong pressure to quit. They may

represent a group less interested in cessation or less able to achieve

abstinence than smokers in areas without these influences. Conversely, the

HAVE RECENT CESSATION

RATES FALLEN AMONG

POPULATIONS THAT

HAVE ACHIEVED LOW

SMOKING PREVALENCE?

17

Chapter 1
factors that produced the lower rates of smoking prevalence may influence

cessation strongly enough to overwhelm the increased average difficulty in

quitting among residual smokers. If this were to happen, the increased

motivation and resources available to the smoker to promote cessation

could more than counterbalance the inherently greater difficulty many of

these residual smokers have in achieving abstinence. Thus individual

smokers might have more difficulty quitting on a personal level without

having a reduced likelihood of achieving abstinence.

On an individual level, smokers with higher levels of education and

income may bring greater personal resources to a cessation effort and have

historically had higher rates of cessation (U.S. DHHS 1990, 2000). As the

prevalence of smoking in these groups falls, the negative social

reinforcement for smoking likely increases. Those who continue to smoke

do so in the face of increased social pressure to stop. The larger fraction of

smokers who have quit, and the greater social pressure to quit, make it

likely that the remaining smokers are highly resistant to cessation or have

great difficulty in achieving abstinence. Once again, the converse may also

be true: increases in the external motivation and support for cessation

among these groups may overwhelm the effect of differential quitting by

smokers who can easily do so.

The likelihood that populations with a low prevalence of current

smoking or in which a large fraction of ever-smokers have quit contain

more smokers who are unwilling or unable to quit makes them fertile

ground for examining cessation and abstinence trends for evidence of

hardening. If a true hard core of smokers exists due to biological or

behavioral factors, as opposed to demographic characteristics, then that

hard core should be more evident among populations where smoking

prevalence has fallen the most. Current cessation rates among those groups

in which cessation has been high historically should also fall over time if

the remaining smokers are predominantly hardcore smokers unwilling or

unable to quit. The absence of a fall in cessation over time would suggest

either that the group is not hardening or that changes in environmental

factors are able to counterbalance the hardening at the individual level.

Fagerström and colleagues (1996) reported a correlation between mean

scores on a nicotine dependence scale and the prevalence of cigarette

smoking for six countries, with a lower smoking prevalence being associated

with a higher score on the dependence scale (a higher level of addiction).

They suggest that successful tobacco control efforts may result in higher

dependence among the remaining smokers due to successful quitting by low

dependence smokers. However, as the authors acknowledge, the relationship

weakens considerably when data for both male and female smokers in

Finland are included. (Finnish females have both a low prevalence of

smoking and a low dependence score.) When the data for both sexes

combined are examined, the middle four of the six countries studied show

no obvious relationship between prevalence and dependence score.

18

Smoking and Tobacco Control Monograph No. 15
There is substantial variability in the prevalence of smoking among the

50 states as measured by the 1995/96 CPS. Figure 1-1 presents the statespecific percentage of those who were daily cigarette smokers one year prior

to the survey who made no attempt to quit smoking and who did not

become an occasional smoker prior to the survey (see Chapter 8). These

fractions are paired with state-specific smoking prevalences to generate the

graph in Figure 1-1. 

There is a significant positive association between the absence of

cessation activity and the prevalence of smoking. States with a high

smoking prevalence have high fractions of the population who made no

attempt to quit. Conversely, states with a low smoking prevalence have high

levels of cessation activity. This relationship of greater cessation with lower

smoking prevalence is present when either cessation activity or 

3-plus–month abstinence is examined, and the effect is evident for smoking

prevalence measured as a percentage of the population smoking or as the

fraction of ever-smokers who have quit (see Chapter 8). The effect is

significant even when the state-specific price of cigarettes is included in the

analysis. At least at the level of state-specific data, having achieved a lower

19

Chapter 1 Absence of Cessation (%)

Smoking Prevalence (%)

Y = 0.74 X + 50.50

(Slope P = <.0001)

R = 0.3143 55

60

65

70

75

80

85

14 16 18 20 22 24 26 28 30 00

Figure 1-1

State-Specific Percentage of Smokers Age 25 and Older Who Made No Attempt to

Change Their Smoking Behavior in the Last Year Compared to State-Specific Smoking

Prevalence—1995/96 CPS
smoking prevalence is not accompanied by hardening as measured by

falling cessation rates. This observation does not imply that increased

cessation is produced by a low smoking prevalence, but it does suggest that

changes in environmental factors that occur as smoking prevalence falls,

and which promote cessation at the state level, may more than compensate

for the increase in average level of difficulty in achieving abstinence among

residual smokers.

High educational attainment is correlated with both low smoking

prevalence and high rates of successful abstinence (U.S. DHHS 1990).

Smoking prevalence among those with 16 or more years of education is

11.7% for the 1995/96 CPS and 10.3% for the 1999 California Tobacco

Survey (CTS) (see Chapter 8). The effect of educational level on cessation

activity and abstinence is also evident in multivariate logistic regression

analyses of these data sets in which the odds ratios for cessation activity and

success increase with increasing level of education, controlling for age,

gender, race/ethnicity, income, and number of cigarettes smoked per day

(Tables 8-1 and 8-2). If high rates of abstinence result in a residual

population that is less willing or less able to quit, smokers in the bettereducated segments of the population should become more hardened than

smokers in the less-educated groups over time. One would then expect them

to have fewer cessation attempts and less cessation success over time,

reflected in lower odds ratios with increasing level of education for cessation

attempts and abstinence in sequential surveys. 

Cessation activity and abstinence measures fell between the 1992/93

and 1995/96 CPS. If this decline reflects hardening of the residual

population of smokers, one manifestation might be a decline in the

magnitude of the odds ratios for measures of cessation with increasing level

of education between the two surveys. The odds ratios for the effect of

educational attainment on cessation activity and abstinence did not fall

between the 1992/93 and 1995/96 CPS, even though the rates of cessation

activity and cessation success declined significantly for the total population

between these two surveys. Similarly, in California, where a substantial fall

in smoking prevalence occurred between 1990 and 1999, there was no

decline in the magnitude of the odds ratios comparing the highest and

lowest educational categories for cessation activity or abstinence across the

period of decline in smoking prevalence (see Chapter 8). High education

level is a demographic measure of a population of smokers who has had a

large fraction of the group already quit and in which the residual smokers

have arguably experienced greater social stigma and therefore should be

highly resistant to cessation. Yet there is no evident decline in the strength

of educational attainment as a predictor of the likelihood of attempting to

quit or achieving abstinence. Either the individual smokers who remain

change in ways that make it easier for them to quit (e.g., reduced levels of

addiction) or, over time, there is an increased level of motivation or support

for cessation provided in the environment.

Income, highly correlated with education, is another demographic

characteristic associated with low smoking prevalence. Current smoking

prevalence among those making more than $75,000 per year was 13.2% for

20

Smoking and Tobacco Control Monograph No. 15
the 1995/96 CPS and 13.1% for the 1999 CTS. The magnitude of the

increase in odds ratios with increasing level of income in multivariate

logistic regression analyses is smaller than that for increasing level of

education (see Chapter 8). In contrast with the changes seen for education,

the odds ratios for cessation activity and abstinence among the highest

income group compared with the lowest was smaller for the 1995/96 CPS

than for the 1992/93 CPS. The effect of income on cessation also

diminished across the three CTS surveys (1990 to 1999). These data provide

some support for a diminished response of upper income groups to existing

tobacco control interventions, controlling for education. However, price

increases are one of the interventions occurring during this period, and the

likelihood that price increases may affect smokers in the lower income

groups more heavily makes attribution of these shifts to hardening of the

residual smoking population difficult (Townsend, Roderick, and Cooper

1994). 

In summary, with the exception of the income data, there is little

evidence to suggest that demographic or geographic subgroups with low

smoking prevalences are seeing declines in cessation activity or lower rates

of cessation success consistent with hardening.

More heavily addicted smokers have difficulty achieving

abstinence (U.S. DHHS 1990; see Chapter 2). As less-addicted

smokers quit, the remaining population of smokers should

become composed of smokers who are, on average, more

heavily addicted. While the number of cigarettes smoked per day is not a

precise measure of level of addiction, heavily addicted smokers are on

average also smokers who consume more cigarettes per day (CPD), and there

is a modest correlation between CPD and level of addiction (see Chapter 2). 

Time to first cigarette after waking is a measure incorporated into scales

used to measure level of addiction (Fagerström and Schneider 1989). As a

single question, time to first cigarette is the most powerful predictor of level

of addiction of the questions used in the addiction scales (Kozlowski et al.

1994). 

If less-addicted smokers are more likely to quit, remaining smokers

should smoke more cigarettes per day and be more likely to have their first

cigarette within 30 minutes of waking. If so, trends over time in number of

cigarettes smoked per day and time to first cigarette should be good

measures of whether the population is increasingly composed of more

heavily addicted smokers. Both of these measures, especially CPD, may be

influenced by trends in social norms and environmental restrictions on

smoking. These influences may be large enough to obscure the expected

increase due to the differential cessation success of lighter and less-addicted

smokers. However, trends in these measures could strongly support the

position that the residual population of smokers has hardened.

In a population of current smokers drawn from the American Cancer

Society Cancer Prevention Study I (CPS I) that participated in all of the

follow-up evaluations, heavy smokers were substantially less likely to

ARE RESIDUAL

SMOKERS HEAVIER

SMOKERS OR

MORE ADDICTED?

21

Chapter 1
achieve abstinence (see Chapter 6). This effect is also demonstrated by a

multiple logistic regression of abstinence in the long-term follow-up of a

cohort of smokers in the Community Intervention Trial for Smoking

Cessation (COMMIT) trial (Figure 5-2; see Chapter 5). Other things being

equal, the effect of greater cessation success by smokers of fewer cigarettes

per day should lead to an increase in the average number of cigarettes

smoked per day by the remaining population of smokers, and this effect is

observed among the smokers in the CPS I trial (see Chapter 6). 

There was also an increase in the mean number of cigarettes smoked per

day for the National Health Interview Survey (NHIS) data between 1965 and

1980, extending the period of observation of the CPS I study (1959 to 1972)

(Figure 3-1). However, since that time, the mean number of cigarettes

smoked per day has declined substantially in national data (see Chapter 7).

This decline is also evident over the shorter intervals covered by surveys

conducted in Massachusetts (see Chapter 9) and California (see Chapter 8),

22

Smoking and Tobacco Control Monograph No. 15

Figure 1-2

Average Daily Amount Smoked as a Predictor of Future Cessation, 1988 to 1993*

*Data from the COMMIT Endpoint Cohort, N = 13,415. Adjusted for sex, age, race/ethnicity, income, education, alcohol consumption,

age started smoking, time to first cigarette, use of a noncigarette tobacco product, price category of cigarette smoked, past quit

attempts, desire to quit, and number of other smokers in the household. See Chapter 5.

NOTE: Underlined relative risks are statistically significant at the 5% level. Relative Risk

Cigarettes per Day

0

2

3

25+ 15–24 5–14 <5

1.0

1.2

1.6

2.4
as well as in the cross-sectional surveys conducted at the start and the end

of the COMMIT trial (see Chapter 5).

Rates of successful cessation were also lower in the COMMIT data for

those who reported smoking within the first 30 minutes of waking (Figure

4-1; see Chapter 5). This effect would lead one to expect that there would be

an increase in the fraction of smokers who smoke within the first 30

minutes of waking between the cross-sectional samples of smokers collected

at the start and end of COMMIT. However, the fraction of the smoking

population reporting a time to first cigarette of less than 30 minutes, instead

of increasing, remained constant. 

In the California tobacco surveys (1990 to 1999), the fraction of smokers

reporting smoking within the first 30 minutes of waking increased with

increasing number of cigarettes smoked per day, but the percent reporting

smoking within 30 minutes of waking remained constant for smokers when

23

Chapter 1 Mean Cigarettes per Day

Year

16

17

18

19

20

21

22

23

1960 1965 1970 1975 1980 1985 1990 1995 2000

0

Figure 1-3

Standardized Mean Cigarettes per Day Among Current Smokers

See Chapter 6.
stratified by number of cigarettes smoked per day over the nine-year

interval covered by these surveys (Figure 5-1; see Chapter 8). This absence of

a change in time to first cigarette occurred even though there was a

dramatic decline in the fraction of smokers reporting smoking 15 to 24 and

25-plus CPD over this time period. Massachusetts also reported a similar

stability in the fraction of smokers who smoked within 30 minutes of

waking (see Chapter 9).

In summary, there is little evidence to suggest that there is an increasing

level of addiction of the residual smoking population as measured by

changes over time in either number of cigarettes smoked per day or the

fraction of smokers who smoke within the first 30 minutes of waking. The

validity of self-reported CPD and time to first cigarette as measures of the

level of addiction may decline as the social stigma associated with smoking

increases. In addition, there is likely a real reduction in the number of

24

Smoking and Tobacco Control Monograph No. 15 Relative Risk

Time to First Cigarette (Minutes)

0

2

3

<10 10–30 30–60 60+

1.0

1.2

1.4

1.8

Figure 1-4

Time to First Cigarette as a Predictor of Future Cessation, 1988 to 1993*

*Data from the COMMIT Endpoint Cohort, N = 13,415. Adjusted for the following baseline factors: sex, age, race/ethnicity, income,

education, alcohol consumption, age started smoking, amount smoked, use of a noncigarette tobacco product, price category of

cigarette smoked, past quit attempts, desire to quit, and number of other smokers in the household. See Chapter 5.

NOTE: Underlined relative risks are statistically significant at the 5% level. 
cigarettes smoked per day that has resulted from increasing restrictions on

smoking in the workplace and in public places (Brownson et al. 1997, Burns

et al. 2000b). However, while CPD and time to first cigarette are not direct

measures of the level of addiction in smokers, they are correlated with level

of addiction, and the data do not reflect an increase over time in the

average levels of these measures among residual smokers. 

Smokers with mental illness or codependency on drugs

or alcohol have more difficulty in achieving long-term

abstinence, and one form of hardening could be an

increase in the fraction of residual smokers with these

problems. An association of smoking with mental

illnesses has been demonstrated in a population with a variety of psychiatric

disorders (Black, Zimmerman, and Coryell 1999). An analysis of the

National Comorbidity Study found that 22.5% of respondents with no

DO CURRENT SMOKERS

HAVE HIGHER

COMORBIDITY THAN

SMOKERS DID IN

PREVIOUS DECADES?

25

Chapter 1 Percentage

Cigarettes per Day

0

10

20

30

40

50

60

70

80

90

100

Total 1–4 5–14 15–24 25+

1990

1996

1999

Figure 1-5

Percent of Adult Daily Smokers Age 25 and Older Smoking Their First Cigarette Within

30 Minutes of Waking by Number of Cigarettes Smoked per Day, 1990, 1996, and 1999

California Tobacco Surveys

See Chapter 7.
mental illness smoked, in contrast to 34.8% of those with a history of ever

having mental illness and 41% of those who reported having mental illness

in the last 30 days (Lasser et al. 2000). 

There are limited data on whether the prevalence of mental illness or

codependency on drugs and alcohol is changing among smokers over time.

Data from Massachusetts (see Chapter 9) suggest that this is not happening,

but the time frame for the trend analyses, and the magnitude of the

changes in smoking behavior, do not allow the absence of a change in these

data to be confidently used as evidence that those changes will not emerge

in the future as the prevalence of smoking continues to drop.

In summary, there is evidence that smokers have higher rates of mental

illness and codependence on drugs and alcohol than nonsmokers, factors

that reduce the likelihood of cessation success (Lasser et al. 2000). However,

it is unclear whether this higher prevalence of psychiatric problems is

related to higher rates of smoking initiation among individuals with these

problems, due to their lack of cessation success resulting in a higher fraction

of these individuals among the residual population of smokers, or both.

Over time, the composition of current smokers

has shifted toward smoking being a behavior

both of lower education and income groups as

well as of the racial and ethnic minorities who

are disproportionately represented in these

lower socioeconomic groups (U.S. DHHS 1998,

2000, 2001). The prevalence of smoking also remains higher among bluecollar workers than among white-collar workers (Bang and Kim 2001). These

groups have lower rates of cessation activity and cessation success (Burns et

al. 2000a).

While differences in rates of initiation of smoking play a role in

smoking prevalence differences among lower socioeconomic and some

ethnic groups, lower rates of cessation also make a contribution (U.S. DHHS

1998, 2000). These shifts could be considered hardening of the population

of smokers. However, there is considerable evidence that these groups

respond to existing tobacco control approaches when they reach the

individuals concerned (U.S. DHHS 1998, 2000). This shift in the

composition of the population of current smokers may constitute a

hardening of the smoking population in the sense that the residual

population of smokers is preferentially composed of groups who have

historically had low rates of successful cessation. However, it is not clear

that these low rates of cessation would persist if these segments of the

population had greater access to cessation assistance or more exposure to

cessation messages and interventions. This form of hardening may not

require a shift in existing tobacco control approaches but, rather, better

strategies to reach these populations with tailored, or gender- and cultureappropriate forms of, existing interventions. In addition, the role of price

and other barriers to access among lower-income groups should be further

explored (Evans and Farrelly 1998).

ARE RESIDUAL SMOKERS

CONCENTRATED IN LESS

ADVANTAGED DEMOGRAPHIC

GROUPS AND THOSE WITH

LESS EXPOSURE TO TOBACCO

CONTROL INTERVENTIONS?

26

Smoking and Tobacco Control Monograph No. 15
Logic requires that the current residual population of smokers

must have more difficulty, on an individual and abstract basis,

in achieving abstinence when compared with those who have already quit.

However, trends over time, in measures that should change if the residual

smoking population is having more difficulty achieving abstinence, do not

seem to be occurring. There is little evidence for a trend over time among

continuing smokers toward declining rates of cessation, increasing intensity

of smoking, or increasing level of addiction. The absence of a trend is

evident when all current smokers are examined, and it is also absent for

demographic subgroups that have had the greatest fraction of smokers

successfully quit. Successful cessation by those who smoke fewer cigarettes

per day and who are less addicted has not hardened the current population

of residual smokers, at least as measured by changes over time in number of

cigarettes smoked per day, time to first cigarette after waking, or rates of

attaining successful abstinence.

The absence of increases in measures of smoking intensity or addiction

over time may be partially explained by the influx of new, younger smokers

into the smoking population. These smokers are just starting their smoking

behavior, and it is highly probable that substantial numbers of them will

quit in the future, many with little difficulty. There is little reason to expect

that these new smokers are more powerfully addicted than previous cohorts

of smokers at the same stage of their smoking history. Indeed, the evidence

suggests that there are higher percentages of occasional smokers among

these current generations of new smokers (Gilpin et al. 2001; see Chapter 8),

a behavior change consistent with less rather than more addiction. 

However, the logical paradox that the population of residual smokers

should contain more smokers who cannot quit and are more heavily

addicted—while trends in these measures over time do not show these

shifts—remains to be explained. One potential resolution may be a

recognition that abstinence can be influenced by both characteristics of the

individual smoker (level of addiction or education, for example) and

characteristics of the environment in which that individual smokes

(restrictions where smoking is allowed, for example). Environmental

influences promoting cessation may be increasing over time, and that

increase may help to counterbalance the increased difficulty residual

smokers have in achieving cessation. 

An increasing effect of environmental influences may occur across all

smokers, or environmental influences may interact with individual

characteristics of smokers that make it difficult for them to quit. This

interaction may occur in at least two important ways. First, the very factors

that are likely to make it difficult to quit, such as high levels of smoking

and addiction, may also make the same individual more susceptible to

changes in the environment. For example, a heavy smoker may be more

motivated by an increase in the price of cigarettes than a light smoker for

the simple reason that the increase in the dollar price of maintaining his or

her smoking behavior is greater than it is for the lighter smoker. Similarly,

the difficulty experienced by a highly dependent smoker when a workplace

goes smokefree may be more motivating toward cessation than it is for the

DISCUSSION AND

SUMMARY

27

Chapter 1
less dependent smoker. The repetitive craving for a cigarette when smoking

is not allowed may be more frequent and more difficult to tolerate for the

heavily addicted smoker. In addition, once the heavily addicted smoker

adjusts to the forced abstinence from smoking in the workplace, it may

make it easier to achieve complete abstinence in the rest of his or her

smoking behavior. The potential that changes in specific environmental

tobacco control interventions may differentially affect cessation success in

heavily smoking-dependent populations is an area for future investigation. 

Some evidence of this differential effect of environmental influences is

provided by the 12-year follow-up of the American Cancer Society CPS I (see

Chapter 6). For the first five years of the study, there was a clear and large

differential in rates of abstinence between smokers of different numbers of

cigarettes per day. Heavy smokers were much less likely to be abstinent.

However, for the last follow-up, a seven-year period from 1965 to 1972,

there were much smaller differences. This time period encompassed an

interval (1967 to 1970) when counter-tobacco advertisements were required

in broadcast media by the Federal Communication Commission to balance

the existing cigarette ads. Per capita consumption fell sharply during this

period (Warner 1989) and cessation rates rose (Burns et al. 1997). One

possible explanation for the higher rates of cessation and smaller differences

in abstinence rates among smokers of different numbers of cigarettes during

the last follow-up in CPS I is an effect of the counter-advertising that was

larger for heavy smokers than for light smokers. 

A second and more complex interaction between environmental

influences and intensity of smoking may explain some of the observations

in California and in COMMIT. The self-reported number of cigarettes

smoked per day has fallen over the last decade in California, and restrictions

on where smoking is allowed may have contributed to that decline (Gilpin

et al. 2001). However, the fraction of California smokers smoking their first

cigarette within 30 minutes of waking did not increase over time for

smokers at any level of number of cigarettes smoked per day, as it should

have if heavier smokers, with higher frequencies of smoking within 30

minutes of waking, shifted downward without changing their level of

addiction. One potential explanation for this observation might be the

increase in number of smokers who live in homes where smoking indoors is

not allowed (Gilpin et al. 2001). If a smoker cannot smoke indoors, it may

be more difficult to smoke within 30 minutes of waking. Similarly, if

smokers are required to go for prolonged periods without smoking at work,

both the behavioral and pharmacological reinforcement for smoking may

be diminished and the level of addiction may decline. It is also possible that

smokers are falsely reporting lower rates of smoking within 30 minutes of

waking due to social pressure or are actually less likely to smoke within the

first 30 minutes without changing their actual level of addiction. The

potential for interaction of environmental changes with changes in the

intensity of addiction over time for individual smokers remains largely

unexplored. 

28

Smoking and Tobacco Control Monograph No. 15
Hardening of the smoking population through an increase in the

number of smokers with mental illness or codependency on alcohol or

other drugs is a real possibility, but the limited information on trends in

prevalence of these problems among smokers makes it difficult to ascertain

whether such hardening has occurred.

The residual population of smokers has clearly shifted toward groups

with low levels of income and education, groups that historically have also

had lower rates of cessation. At least part of that shift is likely due to the

reduced rates of cessation present among these groups in the past. 

Given the limited evidence that the residual population of smokers is

hardening as measured by reduced abstinence or changes in correlates of

addiction, and the scant evidence that existing tobacco control approaches

no longer work for these residual smokers, it is clearly premature to suggest

that existing tobacco control interventions are becoming less effective over

time or that environmental and public policy interventions should be

abandoned in favor of more individualized and intensive treatment

interventions. Evidence from California and Massachusetts (Burns et al.

2000a; Gilpin et al. 2001; Biener, Harris, and Hamilton 2000) suggests just

the opposite. Well-funded, comprehensive tobacco control efforts lead to

continued reduction in smoking prevalence and enhanced cessation.

Substantial reductions in the number of residual smokers could be achieved

if these comprehensive tobacco control efforts were replicated in all states

(CDC 1999a). 

A greater understanding of these trends and the reasons for them is

needed, as is a more complete description of the mechanisms by which

individual characteristics and environmental factors interact among smokers

to promote or inhibit cessation. The hypothesis that the population of

current smokers is hardening should continue to be tested as we observe

future trends in smoking behavior. However, evidence that hardening is

actually occurring should be required before it is used as a justification for

changing current tobacco control strategies.

This volume focuses on the evidence for hardening among the residual

smokers and the implications for existing programmatic efforts to change

smoking behavior. Research efforts focus on what might be achieved in the

future. A final and most critical observation is that, while there may be very

limited evidence of hardening among current smokers, almost one-half of

all living people who have ever smoked are still smoking (CDC 1999b). Our

existing tobacco control approaches may not be losing their effectiveness

due to hardening of the smoking population, but the majority of people

who currently try to quit still fail in the attempt. There remains an urgent

need for a broad range of research initiatives to develop newer, different,

more effective, and more widely utilized approaches to help smokers quit.

Recent insights into the biology of addiction, the pharmacology and

chemistry of the brain, genetic and other reasons for variability in response

to nicotine, and to cessation interventions all offer exciting possibilities for

future interventions to supplement rather than replace current tobacco

control strategies.

29

Chapter 1
REFERENCES

Bang, K. M., Kim, J. H. Prevalence of cigarette

smoking by occupation and industry in the

United States. American Journal of Industrial

Medicine 2001;40:233–39.

Biener, L., Harris, J. E., Hamilton, W. Impact of the

tobacco control programme: Population based

trend analysis. British Medical Journal

2000;321:351–54.

Black, D. W., Zimmerman, M., Coryell, W. H.

Cigarette smoking and psychiatric disorder in a

community sample. Annals of Clinical Psychiatry

1999;11(3):129–36.

Brownson, R. C., Eriksen, M. P., Davis, R. M. et al.

Environmental tobacco smoke: Health effects

and policies to reduce exposure. Annual Review

of Public Health 1997;18:163–85.

Burns, D. M., Anderson, C., Johnson, M. et al.

Cessation and cessation measures among adult

daily smokers: National and state-specific data.

In Population-Based Cessation: What Works.

Smoking and Tobacco Control Monograph No. 12,

edited by D. Burns, D. Shopland, 25–97. NIH

Pub. No. 00-4892. Bethesda, MD: U.S.

Department of Health and Human Services,

National Cancer Institute, 2000a.

Burns, D. M., Lee, L., Shen, Z. et al. Cigarette

smoking behavior in the United States. In

Changes in Cigarette-Related Disease Risks and

Their Implication for Prevention and Control.

Smoking and Tobacco Control Monograph No. 8,

edited by D. Burns, L. Garfinkel, J. Samet,

13–112. NIH Pub. No. 97-4213. Bethesda, MD:

U.S. Department of Health and Human Services,

National Cancer Institute, 1997.

Burns, D. M., Shanks, T., Major, J. et al. Restrictions

on smoking in the workplace. In PopulationBased Smoking Cessation: What Works. Smoking

and Tobacco Control Monograph No. 12, edited by

D. Burns, D. Shopland, 99–126. NIH Pub. No.

00-4892. Bethesda, MD: U.S. Department of

Health and Human Services, National Cancer

Institute, 2000b.

Centers for Disease Control and Prevention. Best

Practices for Comprehensive Tobacco Control

Programs. Atlanta, GA: U.S. Department of

Health and Human Services, 1999a.

Centers for Disease Control and Prevention.

Cigarette smoking among adults—United States,

1997. Morbidity and Mortality Weekly Report

1999b;48(43):993–96.

Evans, W. N., Farrelly, M. C. The compensating

behavior of smokers: Taxes, tar, and nicotine.

RAND Journal of Economics 1998;29(3):578–95.

Fagerström, K. O., Kunze, M., Schoberberger, R. et al.

Nicotine dependence versus smoking

prevalence: Comparisons among countries and

categories of smokers. Tobacco Control

1996;5:52–56.

Fagerström, K. O., Schneider, N. G. Measuring

nicotine dependence: A review of the

Fagerström Tolerance Questionnaire. Journal of

Behavioral Medicine 1989;12:159–82.

Gilpin, E. A., Emery, S. L., Farkas, A. J. et al. The

California Tobacco Control Program: A Decade of

Progress, 1989–1999. La Jolla, CA: University of

California at San Diego, 2001.

Irvin, J. E., Brandon, T. H. The increasing

recalcitrance of smokers in clinical trials.

Nicotine and Tobacco Research 2000;2(1):79–84.

Johnston, L. D., O’Malley, P. M., Bachman, J. G.

Cigarette Use and Smokeless Tobacco Use Decline

Substantially Among Teens. Ann Arbor, MI:

University of Michigan News and Information

Services, 2000. Available at

(www.monitoringthefuture.org) (January 16,

2001).

Johnston, L. D., O’Malley, P. M., Bachman, J. G.

Monitoring the Future National Survey Results on

Drug Use, 1975–2000. Vol. 1, Secondary School

Students. NIH Pub. No. 01-4924. Bethesda, MD:

National Institute on Drug Abuse, 2001.

Kozlowski, L. T., Porter, C. Q., Orleans, C. T. et al.

Predicting smoking cessation with self-reported

measures of nicotine dependence: FTQ, FTND,

and HSI. Drug and Alcohol Dependence

1994;34:211–16.

Lasser, K., Boyd, J. W., Woolhandler, S. et al.

Smoking and mental illness: A population-based

prevalence study. Journal of the American Medical

Association 2000:284(20):2606–610.

National Cancer Institute. Population-Based Smoking

Cessation: What Works. Smoking and Tobacco

Control Monograph No. 12, edited by D. Burns, 

D. Shopland, 25–97. NIH Pub. No. 00-4892.

Bethesda, MD: U.S. Department of Health and

Human Services, National Cancer Institute,

2000.

Townsend, J. L., Roderick, P., Cooper, J. Cigarette

smoking by socioeconomic group, sex, and age:

Effects of price, income, and health publicity.

British Medical Journal 1994;309:923–26.

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

Health Benefits of Smoking Cessation. Atlanta, GA:

U.S. Department 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,

1990.

30

Smoking and Tobacco Control Monograph No. 15
U.S. Department of Health and Human Services.

Reducing Tobacco Use: A Report of the Surgeon

General. Atlanta, GA: U.S. Department 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, 2000.

U.S. Department of Health and Human Services.

Tobacco Use Among U.S. Racial/Ethnic Minority

Groups; African Americans, American Indians and

Alaska Natives, Asian Americans and Pacific

Islanders and Hispanics: A Report of the Surgeon

General. Atlanta, GA: U.S. Department 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, 1998.

U.S. Department of Health and Human Services.

Women and Smoking: A Report of the Surgeon

General. Atlanta, GA: U.S. Department 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, 2001.

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

An update. American Journal of Public Health

1989;79(2):144–51. 

Warner, K. E., Burns, D. M. Hardening and the hardcore smoker: Concepts, evidence, and

implications. Nicotine and Tobacco Research, in

press 2003.

31

Chapter 1
32

Smoking and Tobacco Control Monograph No. 15
The Case for Hardening of the Target*

John R. Hughes

Tobacco control efforts increased smoking abstinence up until

1990; however, in the mid-1990s, smoking prevalence rates and the U.S. per

capita consumption leveled off and remained constant (CDC 1999b; Taylor

2001; see Chapter 8). Per capita consumption again declined in 1999

following the Master Settlement Agreement (MSA) and a subsequent

increase in the cost of cigarettes. However, it is unclear whether this decline

is a resumption of the previous trends or a one-time drop due to the

increase in cost (see Chapter 8). The percent of ever-smokers who have quit

(the quit ratio) increased from 1965 to the early 1990s but has changed little

since then (Figure 2-1). 

One explanation for this plateauing is that a selection bias is operating

such that those smokers who found it easy to quit did so, leaving a more

hardcore or hardened group of smokers (Hughes 1993) who had more

difficulty achieving abstinence. The argument for such a selection bias is

that since high dependence predicts low rates of cessation (Fagerström and

Schneider 1989), the inevitable consequence is that, over time, remaining

smokers will be those who are highly dependent. The only way this would

not be true is if those new persons recruited to smoking were the same as

those leaving smoking; i.e., if those recruited were destined to become the

less dependent smokers. What is noteworthy is that the hardening

hypothesis assumes that the level of dependence varies across smokers.

Many politicians, public health advocates, and scientists have acted as if all

smokers are victims of a ubiquitous addiction that occurs completely and

immediately upon smoking initiation. In reality, adult smokers do, in fact,

vary from no dependence to heavy levels of dependence (Giovino et al.

1995).

Two tests of the hardening hypothesis support it. One test involved a

comparison of smoking prevalence and degree of dependence across

European countries (Fagerström et al. 1996). In this study, those countries

with a lower prevalence of smoking had higher nicotine dependence scores

among remaining smokers than did countries with higher rates of smoking.

The other test examined quit rates in published treatment outcome studies

and found that quit rates decreased over time (Irvin and Brandon 2000;

Irvin, Hendricks, and Brandon 2001) (see Chapter 4). 

INTRODUCTION

33

Chapter 2

*Preparation of this article was supported by Senior Scientist Award DA00450 to John Hughes

from the National Institute in Drug Abuse.
Changes in success rates per quit attempt over time have not been

published. Data from the U.S. Current Population Survey (CPS) and the

California Tobacco Survey (CTS) (Burns et al. 2000) was used to calculate the

proportion of quit attempts in the last year that resulted in abstinence of 

3-plus months. The success rate per quit attempt is calculated using the

percent quit 3-plus months in the numerator and the percent who made a

quit attempt in the denominator. This measure does not include either quit

<3 months or occasional smokers, but the results are the same when these

measures are included. This success rate hovers between 13.6% and 16.3%,

with no discernable time trend between 1992 and 1999 for the CPS data. 

In the CTS, success rate per quit remained stable from 1990 to 1996

(17% versus 16%). If the number of quit attempts among those who tried to

quit has increased over time, this would mask a decline in success rates, but

this effect is unlikely to be large enough to mask a meaningful decline. This

evidence does not support a decline in the success rate per quit, but

limitations on the length of time over which the rates are calculated means

that it remains unclear whether success rates per quit attempt have changed

over time.

34

Smoking and Tobacco Control Monograph No. 15

Figure 2-1

Quit Ratio by Calendar Year, 1965–2000 Quit Ratio

Year

0

0.1

0.2

0.3

0.4

0.5

0.6

1960 1965 1970 1975 1980 1985 1990 1995 2000

Percent of ever-smokers who had quit by the time of the survey (quit ratio) over time. Data from the National Health Interview

Survey @ www.cdc.gov/tobacco/research_data/adults_prev/tab_3.htm
The plateauing of smoking prevalence could possibly be due to a decline

in the prevalence of quit attempts. The CPS data reports a decline in the

prevalence of quit attempts in the year prior to the survey from 37% in

1992/93 to 32% in 1995/96 (Burns et al. 2000), but they rose again in

1998/99 (see Chapter 8). In California and Massachusetts where tobacco

control programs were in effect, quit attempts declined slightly in California

(33% in 1990 versus 31% in 1996) and were unchanged in Massachusetts

(48% in 1993 and 1997) (Burns et al. 2000). Once again, a clear trend over

time is not evident.

In this chapter, there are three points to be discussed: (1) why it is

important to continue to test the hardening hypothesis; (2) why one must

distinguish between indirect, inadequate tests of the hypothesis and direct,

adequate tests of the hypothesis; and (3) why, even though this monograph

focuses on dependence, the most important factors in any hardening may

be psychosocial factors. 

To understand the importance of the

hardening hypothesis to tobacco control, it is

helpful to first outline the role of cessation in tobacco control. Tobacco

control has traditionally focused on prevention; e.g., the U.S. Centers for

Disease Control and Prevention (CDC) recommends that only 21% to 33%

of tobacco control money be spent on cessation (CDC 1999a). In the past,

when tobacco control plans have focused on cessation, they have usually

focused on motivating quit attempts and not on providing treatment. 

In contrast, plans for the control of alcoholism or illicit drug use make

providing for treatment a central component (NIDA 1999). In addition,

these plans for controlling alcohol or illicit drug use clearly state that simply

increasing motivation is insufficient; rather, drug-dependent individuals

need treatment and some will need intensive treatment (NIDA 1999).

One of the reasons that tobacco control has avoided treatment is the

myth that treatment is not efficacious and not cost-effective (Hughes

1999b). In terms of efficacy, several meta-analyses have concluded that

many treatments for smoking double quit rates (Hughes 1996). Importantly,

meta-analyses have found that, unlike alcohol dependence treatment, the

efficacy of treatments for smoking cessation is dose-related; i.e., more

intensive treatments do, in fact, result in higher quit rates (Fiore et al.

2000). 

In terms of cost-effectiveness, therapies such as brief advice (with or

without medications), telephone counseling, and over-the-counter (OTC)

medications have all been shown to be cost-effective (Cromwell et al. 1997).

In fact, provision of smoking cessation has been called the gold standard of

cost efficacy as no other treatment in medicine has been able to match it

(Eddy 1992).

A corollary myth among many tobacco control advocates is that even

though cessation treatment may be cost-effective, prevention is more so.

Empirical data to support this belief is lacking. Treatment is likely to be as

cost-effective if not more cost-effective than prevention. If one induces a

WHY IT IS IMPORTANT TO TEST

THE HARDENING HYPOTHESIS

35

Chapter 2
smoker to stop smoking, the benefit of cessation begins within a year,

whereas, if one induces a teenager not to start smoking, the benefit may not

occur for 30 or more years. Economists observe that, due to discounting,

$100 spent to obtain a given benefit next year is much more cost-effective

than $100 spent to obtain the identical benefit 30 years from now (Warner

and Luce 1983). 

In contrast to tobacco control programmatic efforts, research on

smoking behavior has adopted a much broader approach to the problem.

Research efforts have examined clinical treatment as well as prevention and

public policy interventions, and future directions include examining the

interactions of genetic, biologic, psychologic, and sociologic factors in

smoking behavior and resultant disease (NCI 1998, 2001).

Given this background on tobacco control and cessation, now let us

assume the hardening hypothesis gathers sufficient evidence to become

believable. The main implication would be that tobacco control should

focus more on cessation; that is, tobacco control would need to reallocate

program delivery funds from just motivating smokers to quit to actually

providing treatment, including intensive treatment.

The major issue in assessing evidence for or against the

hardening hypothesis is the validity of the measure of

nicotine dependence used. Contrary to what many

believe, there are widely accepted criteria of dependence; i.e., those

recommended by the American Psychiatric Association’s (APA) Diagnostic

and Statistical Manual: Fourth Edition (DSM-IV-R) (APA 2000), and the almost

identical criteria of the World Health Organization’s (WHO) International

Classification of Diseases: 10th Edition (ICD–10) (WHO 1992). These criteria

focus on two aspects: physical dependence (i.e., tolerance and withdrawal)

and psychological dependence (i.e., impaired control over drug use).

Although the DSM/WHO criteria have been widely used in alcohol and

illicit drug dependence research and practice, they have been used in only a

few studies of nicotine dependence (Giovino et al. 1995). Thus data on their

reliability and predictive validity in smokers is limited. 

The most widely used measures of nicotine dependence are the

Fagerström tests, i.e., the Fagerström Tolerance Questionnaire and the newer

Fagerström Test for Nicotine Dependence (Fagerström and Schneider 1989).

These measures combine queries about consumption and some indices of

psychological dependence, and they predict the success of quit attempts and

compensatory smoking (Fagerström and Schneider 1989). The item of the

Fagerström scales that carries the most predictive power is time to the first

cigarette of the morning, and this single item has been shown to have

predictive validity (Kozlowski et al. 1994). 

Cigarettes per day (CPD) is often used as a proxy measure for nicotine

dependence, as evidenced by many of the chapters in this monograph. Such

consumption measures are correlated with the probability of alcohol and

other drug dependencies, but this correlation is much smaller than most

believe (Mendelson and Mello 1985). In fact, it is noteworthy that the

AN ADEQUATE TEST OF

THE HARDENING

HYPOTHESIS IS NEEDED

36

Smoking and Tobacco Control Monograph No. 15
amount of drug consumption is not part of the DSM/WHO criteria for

dependence on any drug. 

One major problem with CPD is that it actually is a nonspecific measure

of the dose of nicotine (and smoke) received by the smoker (e.g., the

correlation between CPD and nicotine levels is usually r <0.50) (Benowitz

1983). This is because the way a smoker smokes a cigarette (number of

puffs, puff volume, for example) is as important as CPD in determining

nicotine consumption. Another problem with CPD is that currently in the

United States many variables other than dependence have large effects on

CPD (Evans, Farrelly, and Montgomery 1999). For example, there may be

many highly dependent smokers who would like to smoke 40 CPD but can

only smoke 15 CPD due to increasing cost and worksite and home

restrictions on smoking. There is some evidence that social policy changes,

such as tax increases, may be accompanied by compensation in the way

individual cigarettes are smoked such that declines in CPD do not produce a

proportional decrease in nicotine intake (Evans and Farrelly 1998), again

suggesting CPD may be an imprecise measure of intake or dependence.

Currently, only Fagerström scores, and perhaps the time to the first

cigarette, are adequately validated measures of nicotine dependence. The

problem is that the majority of data sets one could use to examine the

hardening hypothesis only include CPD. It could be argued that CPD is still

an adequate measure to test the hypothesis because, with large data sets, a

very accurate measure of dependence is not needed, and a measure

somewhat related to dependence would be adequate. However, in reality,

CPD is poorly correlated to nonconsumption measures of dependence. For

example, the correlation between CPD and Fagerström scores (minus CPD)

is only r = 0.33, and the correlation of CPD with the number generated by

the DSM/WHO criteria is only r = 0.23 (Riggs and Hughes 1999). Thus,

when tests of the hardening hypothesis use CPD and give negative results,

one must entertain the real possibility of false negative results due to

measurement error. 

Several variables other than the variable of dependence

predict lower rates of cessation: lower income,

psychological comorbidity, younger age, lower education,

alcohol/drug problems, stress, certain occupations, and

other smokers in the household, for instance (U.S. DHHS 1990). Thus it is

probable that future smokers are more likely to be the poor or those with

minor or major psychological or other problems (Hughes 1999a), and it

may be changes in these factors, not dependence, that account for

hardening. Thus it is important to include these factors, as well as

dependence, when testing the hardening hypothesis. Also, if psychosocial

factors are driving the hardening, then instead of providing treatments

tailored for heavily dependent smokers, we may need to provide treatments

focusing on the special problems of the poor (e.g., improving access to

treatment), on problems with other smokers in the household (e.g., how to

handle a smoking spouse), or on more effective and tailored prevention. 

DEPENDENCE MAY

NOT BE THE MOST

RELEVANT CAUSE

OF ANY HARDENING

37

Chapter 2
Tobacco control advocates should be proud that they have dramatically

changed society’s view of smoking. But every businessman knows that as

the society changes, the characteristics and needs of their clients change. It

would be quite foolish for tobacco control advocates to assume the same is

not true for their clients, i.e., smokers. Thus, in reality, the question is not

whether the target is hardening but rather, how the remaining smokers are

changing and whether they changed enough to necessitate changes in our

tobacco control efforts. We should not rely on imprecise measures of

dependence (e.g., studies using CPD as a measure of dependence) to

prematurely make what has a good chance of being a false negative or false

positive decision. Rather, new studies with good measures of dependence

and those other factors that might be changing over time are needed.

Marketers do this type of “characterizing the changing market” all the time.

Why shouldn’t those in tobacco control do the same?

SUMMARY

38

Smoking and Tobacco Control Monograph No. 15

REFERENCES

American Psychiatric Association. Diagnostic and

Statistical Manual of Mental Disorders, Fourth

Edition, Text Revision: DSM-IV-TR. Washington,

DC: American Psychiatric Association, 2000. 

Benowitz, N. L. The use of biological fluid samples

in assessing tobacco smoke consumption. In

Measurement in the Analyses and Treatment of

Smoking Behavior. NIDA Research Monograph No.

48, edited by J. Grabowski, C. S. Bell, 6–26. NIH

Pub. No. 83-1285. Washington, DC: U.S.

Government Printing Office, 1983.

Burns, D. M., Anderson, C., Johnson, M. et al.

Cessation and cessation measures among adult

daily smokers: National and state-specific data.

In Population-Based Smoking Cessation. Smoking

and Tobacco Monograph No. 12, edited by 

D. Burns, D. Shopland, 25–98. NIH Pub. No. 00-

4892. Bethesda, MD: U.S. Department of Health

and Human Services, National Cancer Institute,

2000.

Centers for Disease Control and Prevention. Best

Practices for Comprehensive Tobacco Control

Programs. Atlanta, GA: U.S. Department of

Health and Human Services, 1999a.

Centers for Disease Control and Prevention.

Cigarette smoking among adults—United States,

1997. Morbidity and Mortality Weekly Report

1999b;48(43):993–96.

Cromwell, J., Bartosch, W. J., Fiore, M. C. et al. 

Cost-effectiveness of the clinical practice

recommendations in the AHCPR Guidelines for

Smoking Cessation. Journal of the American

Medical Association 1997;278:1759–766.

Eddy, D. M. David Eddy ranks the tests. Harvard

Health Letter July 10–11, 1992.

Evans, W. N., Farrelly, M. C. The compensating

behavior of smokers: Taxes, tar, and nicotine.

RAND Journal of Economics 1998;29(13):578–95.

Evans, W. N., Farrelly, M. C., Montgomery, E. Do

workplace smoking bans reduce smoking? The

American Economic Review 1999;89:728–47.

Fagerström, K. O., Kunze, M., Schoberberger, R. et al.

Nicotine dependence versus smoking

prevalence: Comparisons among countries and

categories of smokers. Tobacco Control

1996;5:52–56.

Fagerström, K. O., Schneider, N. G. Measuring

nicotine dependence: A review of the

Fagerström Tolerance Questionnaire. Journal of

Behavioral Medicine 1989;12:159–82.

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 Health Care Policy and

Research, 2000.

Giovino, G. A., Henningfield, J. E., Tomar, S. L. et al.

Epidemiology of tobacco use and dependence.

Epidemiologic Reviews 1995;17:48–65.

Hughes, J. R. Comorbidity and smoking. Nicotine

and Tobacco Research 1999a;1:S149–S152. 

Hughes, J. R. Four beliefs that may impede progress

in the treatment of smoking. Tobacco Control

1999b;8(3):323–26. 

Hughes, J. R. Pharmacotherapy for smoking

cessation: Unvalidated assumptions, anomalies

and suggestions for further research. Journal of

Consulting and Clinical Psychology

1993;61:751–60.
Hughes, J. R. Pharmacotherapy of nicotine

dependence. In Pharmacological Aspects of Drug

Dependence: Toward an Integrative Neurobehavioral

Approach, Handbook of Experimental Pharmacology

Series, edited by C. R. Schuste, M. J. Kuhar,

599–626. New York: Springer-Verlag, 1996.

Irvin, J. E., Brandon, T. H. The increasing

recalcitrance of smokers in clinical trials.

Nicotine and Tobacco Research 2000;2(1):79–84.

Irvin, J. E., Hendricks, P. S., Brandon, T. H. The

increasing recalcitrance of smokers in clinical

trials II: Pharmacotherapy trials. In Proceedings

and On-Site Program, Society for Research on

Nicotine and Tobacco. 7th Annual Meeting,

March 23–25, 2001, at Seattle, WA. 

Kozlowski, L. T., Porter, C. Q., Orleans, C. T. et al.

Predicting smoking cessation with self-reported

measures of nicotine dependence: FTQ, FTND,

and HSI. Drug and Alcohol Dependence

1994;34:211–16.

Mendelson, J. H., Mello, N. K. The Diagnosis and

Treatment of Alcoholism. New York: McGraw-Hill,

1985.

National Cancer Institute. Tobacco Research

Implementation Plan: Priorities for Tobacco Research

Beyond the Year 2000. Bethesda, MD: NCI,

National Institutes of Health, 1998.

National Cancer Institute. The Nation’s Investment in

Cancer Research for Fiscal Year 2003: Plans and

Priorities for Cancer Research. Bethesda, MD: NCI,

National Institutes of Health, 2001.

National Institute on Drug Abuse. Principles of Drug

Addiction Treatment. Bethesda, MD: NIDA,

National Institutes of Health, 1999.

Riggs, R. L., Hughes, J. R. Relationship among three

common measures of nicotine dependence.

Problems of Drug Dependence, 1998: Proceedings

from the 60th Annual Scientific Meeting of the

College on Problems of Drug Dependence, Inc.

NIDA Research Monograph No. 179, 190. NIH

Pub. No. 99-4395. Washington, DC: NIDA,

National Institutes of Health, 1999.

Taylor, H. The power of tobacco addiction. Harris

Interactive, Harris Poll Library, The Harris Poll #1.

February 14, 2001. 

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

Health Benefits of Smoking Cessation: A Report of

the U.S. Surgeon General. Atlanta, GA: U.S.

Department 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,

1990.

Warner, K. E., Luce, B. R. Cost-Benefit and CostEffectiveness Analyses in Health Care: Principles,

Practice, and Potential. Ann Arbor, MI: Health

Administration Press, 1983.

World Health Organization. The ICD–10

Classification of Mental and Behavioral Disorders.

Geneva: World Health Organization, 1992.

39

Chapter 2
40

Smoking and Tobacco Control Monograph No. 15
The Case Against Hardening of the

Target

David M. Burns

One of the most compelling arguments for the hypothesis that

past successful smoking control interventions have left behind a group of

smokers who have more difficulty quitting and are therefore a hardened

target is that of direct logic. Those who have already successfully quit must,

as a group, have less difficulty quitting than those who continue to smoke,

a group that includes substantial numbers of smokers who have failed in

past cessation attempts.

An extension of this logic provides the following argument against

hardening: if smokers who have more difficulty quitting are left behind,

then the residual population of smokers should show an increasing

prevalence of those smokers’ characteristics that predict reduced cessation

activity or failure to maintain abstinence. For example, if smokers of greater

numbers of cigarettes per day (CPD) have more difficulty quitting, then,

over time, as smokers of fewer CPD preferentially quit, the residual

population of smokers should show an increase in the mean number of

cigarettes smoked per day. Because the mean CPD reported in surveys has

fallen rather than risen over the last decade (see Chapter 7), this logic would

argue that the target in not hardening.

Evidence presented throughout this monograph suggests that neither of

these “logical” arguments is compelling. In each case, the single dimension

of change in smoking behavior on which the logic is based does not fully

account for the other changes over time in both smoking behavior and in

the environment in which smoking occurs. Much of this monograph is

devoted to a presentation of evidence on trends over time in various

measures of smoking behavior that have been associated with difficulty in

achieving long-term abstinence. Changes in these measures over time do

not provide a convincing demonstration that cessation of about one-half of

ever-smokers has produced a residual population of smokers which is

increasingly composed of heavier smokers, more-addicted smokers, or

smokers with greater comorbidity. Therefore, even in the presence of the

compelling logic that the smoking population must be hardening, there is

little objective evidence that it is actually occurring. 

The following section addresses the paradox of a logical inevitability

that the target must be hardening when there is little evidence that the

residual population of smokers has actually hardened. The section explains

why leaving behind a population of smokers who have more difficulty

achieving abstinence on an individual level may not translate into lower

rates of successful cessation on a population level.

INTRODUCTION

41

Chapter 3
A comprehensive review of the predictors and

determinants of cessation is beyond the scope of this

section and has been presented elsewhere (U.S. DHHS

1990, 2000, 2001). However, in general terms, the factors influencing

cessation can be divided into those that are characteristics of the individual

and those that are characteristics of the environment in which the smokers

smoke. Individual factors are those most often considered in discussions of

whether the target is hardening, but consideration of changes in both

individual and environmental factors over time is important for examining

whether achieving successful cessation is becoming less likely over time. 

Among the individual factors that might influence cessation are the

strength of the addiction to nicotine, the extent of comorbidity with other

substance dependence disorders or with psychiatric illness, and the personal

resources that the smoker brings to the cessation attempt (Fiore et al. 2000).

Studies of cessation interventions have demonstrated an inverse

relationship between the number of cigarettes smoked per day and the

likelihood of cessation success (U.S. DHHS 1990). However, there has been a

decline rather than an increase over the last two decades in the fraction of

smokers smoking 25 or more cigarettes per day (U.S. DHHS 2001), and the

mean number of cigarettes smoked per day as reported by smokers has

declined as well (see Chapter 7). 

This paradoxical outcome was confirmed in a five-year follow-up of

cigarette smokers conducted as part of the Community Intervention Trial

for Smoking Cessation (COMMIT) evaluation (Hymowitz et al. 1997; see

Chapter 5). In the longitudinal sample of smokers followed for the entire

study, the likelihood of quitting over the five-year interval was much lower

among heavy smokers and among those who reported smoking within the

first 30 minutes after waking. However, cross-sectional surveys performed

over the same five-year interval in the same cities where the longitudinal

study was conducted showed a decline in mean number of cigarettes

smoked per day and no change in the fraction of smokers who reported

smoking within the first 30 minutes of waking. The longitudinal data are

consistent with observations that higher levels of addiction predict lower

rates of cessation (U.S. DHHS 1990), and they present a convincing case that

individual characteristics of smoking behavior, particularly those reflecting

the degree of addiction, define how hard it is for an individual to achieve

long-term abstinence. However, the cross-sectional COMMIT data point to

the paradox of heavy and more-addicted smokers having more difficulty

achieving abstinence without the population of residual smokers being

composed of higher percentages of heavy smokers or smokers who are more

addicted.

Defining a group of individuals at one point in time and following them

for short periods of time examines smokers’ responses to a fixed set of

environmental factors. Over a short period of time, factors that influence

cessation, such as cost, restrictions on where smoking is allowed, and social

norms about smoking, change only modestly. Therefore, the individual

characteristics that define how much difficulty a smoker may have in

quitting will be more powerful in predicting cessation success. Short-term

EFFECT OF

INDIVIDUAL FACTORS

ON HEAVY SMOKERS

42

Smoking and Tobacco Control Monograph No. 15
evaluations have difficulty examining the possibility that changes in

environmental factors that promote cessation may have a greater effect on

heavy smokers than on light smokers. Within a fixed set of environmental

factors, more-addicted smokers will have more difficulty quitting than lessaddicted smokers; but as environmental factors change, it is possible that

the impact of these environmental factors on cessation may be more

powerful on heavier smokers than on lighter smokers.

The discordance between the longitudinal data and the cross-sectional

data in the COMMIT observations cannot be explained by differences in the

duration of observation, since the duration is the same for the longitudinal

and cross-sectional measures. One potential explanation is the possibility

that some of the environmental changes taking place may shift smokers

downward in the amount that they smoke, or in their level of addiction,

and this shift might be more pronounced for heavy smokers or moreaddicted smokers. For example, increased restriction on where smoking is

allowed in California is suggested as one reason for the marked decline in

the percentage of California smokers over the last decade who report

smoking 15 or more cigarettes per day (Brownson et al. 1997; Burns et al.

2000b; Gilpin et al. 2001). 

It is also possible that heavy smokers are currently more likely to shift

downward over time than light smokers are to shift upward. If this trend

occurs, the mean number of cigarettes smoked per day in a population will

shift downward unless current populations of heavy smokers are replaced by

future generations of smokers with equally high numbers of heavy smokers.

If those smokers who initiated smoking in the recent past are less likely to

become heavy smokers than previous generations of smokers because of

restrictions on where smoking is allowed or other factors, then the mean

number of cigarettes smoked per day among all current smokers in crosssectional surveys can fall.

Some evidence on the stability of smoking behavior over a one-year

interval is available from the 1996 California Tobacco Survey (CTS) (Burns 

et al. 2000a) and is presented in Table 3-1. 

The population examined was restricted to those who were daily

smokers one year prior to the survey and were 25 years of age or older. Table

3-1 compares the number of cigarettes respondents reported smoking one

year prior to the survey to the smoking status and amount smoked at the

time of the survey. Among those who reported smoking 5 to 14 or 15 to 24

cigarettes per day one year prior to the survey, 74% reported still smoking

the same number of cigarettes per day at the time of the survey. In contrast,

only 69% of those who smoked 25 or more cigarettes one year prior to the

survey reported smoking the same number of cigarettes per day at the time

of the survey. This difference was statistically significant and suggests that

the likelihood of heavy smokers reducing the number of cigarettes that they

smoked per day over the one-year interval was greater than the likelihood of

lighter smokers changing their smoking behavior in any direction, either

increasing or decreasing it. The data in Table 3-1 are subject to biases

resulting from self-reporting and recall, but they suggest that heavy smokers

43

Chapter 3
may be less stable in their smoking intensity than are lighter smokers, and

this differential instability over time could explain the paradoxical result

observed between the longitudinal and cross-sectional observations made

over the five-year interval of the COMMIT study.

It is possible that smokers who shift downward in the number of

cigarettes they smoke per day remain heavily addicted and retain the same

difficulty quitting that they had when they were smoking a greater number

of cigarettes per day. However, it is also possible that the reduction in the

frequency with which they smoke may modify the strength of their

addiction in ways that facilitate their ability to quit. If this happens, the

shift downward in number of cigarettes smoked per day would be

accompanied by a shift upward in their likelihood of quitting. Changes in

environmental factors over time may modify the strength of addiction for

individual smokers.

The COMMIT data suggest that reducing the number of cigarettes

smoked per day may have some impact on the strength of addiction, at

least for smoking within the first 30 minutes of waking as a measure of

addiction. Smokers who reported smoking within the first 30 minutes of

waking had a lower likelihood of quitting, but, over the five-year interval,

the fraction of smokers who reported smoking within the first 30 minutes of

waking did not increase. This suggests that, as the continuing heavy

smokers reduced the number of cigarettes that they smoked, they may also

have reduced their likelihood of smoking within the first 30 minutes of

waking and possibly reduced their level of addiction.

The discussion above points out that the validity of individual smoking

characteristics for predicting cessation success can coexist with a residual

population of smokers that is not hardened by containing a higher

percentage of smokers with those same characteristics that predict poor

cessation outcomes. The logical imperative that supports an argument that

the population of residual smokers is hardening is driven by the impact of

individual characteristics of smokers on the likelihood of cessation success.

Environmental factors that promote cessation may not affect all smokers

equally, and those same individual characteristics that make a smoker less

likely to quit may make the same smoker more likely to be influenced by

environmental factors. To the extent that environmental factors shift the

behavior of heavy smokers to that of lighter smoking, the behavioral shifts

may improve the likelihood of that smoker successfully quitting. 

It is possible that a differential impact of environmental factors on

heavy smokers could counter the effect of heavy smoking on the likelihood

of cessation success, with the two forces canceling each other out as

environmental influences increase over time. The residual smoking

population may be composed of individuals who are having more difficulty

achieving abstinence, but the impact of environmental factors is also

increasing, creating a circumstance in which the hardened smoker has more

motivation and support for cessation and therefore does not have a lower

likelihood of successful cessation.

44

Smoking and Tobacco Control Monograph No. 15
45

Chapter 3

Table 3-1California 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

Occasional <3 3+

Cigarettes 25+ 15–24 5–14 1–4 Unknown Smoker Months Months Unknown Population SampleSmoked 1 Size Size

Year Ago % ± CI % ± CI % ± CI % ± CI % ± CI % ± CI % ± CI % ± CI % ± CI (N) (n)Overall 18.3 1.1 37.6 1.3 26.0 1.5 2.9 0.5 0.3 0.2 4.6 0.7 4.8 0.7 5.0 0.8 0.4 0.2 2,894,421 6,21125+ 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 1,54215–24 2.7 0.7 74.4 1.6 10.1 1.4 0.8 0.5 0.0 0.0 3.2 0.9 4.2 0.8 4.2 0.9 0.4 0.3 1,266,356 2,8355–14 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 1,5601–4 0.5 1.1 1.1 1.0 12.6 8.1 50.7 11.0 0.4 0.7 18.3 8.2 8.3 5.9 6.8 3.5 1.3 1.6 106,769 203Unknown 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 71NOTE: CI = 95% confidence interval; “. ” = insufficient data.Data source: CTS 1996 (Burns et al. 2000a).
A variety of tobacco control interventions are intended to

influence the environment around the smoker in order to

promote cessation and abstinence (U.S. DHHS 2000).

Increasing the cost of cigarettes, restricting where smoking is

allowed, changing social norms about smoking, and encouraging the

provision of physician advice to quit are all components of tobacco control

programs intended to influence the environment around the smoker in

ways that provide motivation to quit and support abstinence. 

One potential explanation for the paradox of heavier smokers finding it

more difficult to quit without the residual population of smokers containing

an increasing fraction of heavy smokers is that there is a differential effect

of these environmental interventions on cessation success among heavy

smokers. An example is the price increase experienced by a two-pack-perday smoker when the cost of cigarettes is raised to twice that of a one-packper-day smoker. It is not unreasonable to expect that the impact of that

price increase on motivation to change smoking behavior might also be

greater in the two-pack-per-day smoker. At a constant price, heavier smokers

would have more difficulty quitting than light smokers, but when a price

increase is implemented, the change in price may have a more powerful

effect on heavy smokers than on light smokers. During periods when the

cost of cigarettes is changing rapidly, the differences in successful cessation

among smokers of different numbers of cigarettes per day might diminish or

even invert for a period of time, with heavy smokers being more likely to

quit than light smokers.

Over long periods of time, the relationship between intensity of

smoking or level of addiction and difficulty quitting may not be constant.

Rapid changes in environmental factors might alter the gradient of

successful abstinence across number of cigarettes smoked per day, might

eliminate the gradient altogether, or might even invert the gradient for

short periods of time. If the relationship of number of cigarettes smoked per

day with successful abstinence varies substantially over time, this variation

might reduce the impact of CPD-related differences in cessation success on

the mean number of cigarettes smoked by the residual smokers.

A similar differential effect can be postulated for restrictions on where

smokers are allowed to smoke. Bans on smoking in the workplace are likely

to inconvenience heavy smokers and disrupt their pattern of smoking more

than for lighter smokers. It is unclear whether the effect of a smokefree

workplace on smoking cessation is more powerful on heavier smokers than

on lighter smokers, but the possibility of a differential effect is not

unreasonable.

Another area of differential impact on heavy smokers may be the

likelihood of receiving an intervention to promote cessation. Heavy smokers

are more likely than lighter smokers to report having received physician

advice to stop smoking in the last 12 months (Hollis 2000), and they are

more likely to participate in or utilize cessation assistance as well. The

differential provision of proven cessation assistance to heavy smokers may

EFFECT OF

ENVIRONMENTAL

FACTORS ON

HEAVY SMOKERS

46

Smoking and Tobacco Control Monograph No. 15
offer a gain in achieving long-term abstinence that partially offsets their

increased difficulty in quitting.

It is also possible that, as the fraction of smokers and particularly heavy

smokers decline, the negative social pressures on heavy smokers may

increase disproportionately compared with those experienced by lighter

smokers. Pressure to quit from family and friends, plus the frequency of

requests to put out a cigarette or other negative messages from strangers,

may be life experiences that are more intense or more frequent for heavy

smokers.

Not all changes in the environment influence heavy smokers more than

light smokers, as evidenced by the response to the intervention in the

COMMIT study. Light and moderate smokers had increased abstinence rates

in response to the intervention, but heavy smokers did not (COMMIT

1995a,b).

Consideration of hardening of the target must, therefore, involve an

examination of changes in both the population of individuals smoking and

the environment within which smokers smoke. Removal of those individual

smokers who can easily quit from the smoking population may well leave

behind a group of smokers who require more motivation to make a quit

attempt, need more assistance for that attempt to be successful, or find

achieving cessation a greater challenge. If the meaning of hardening is

simply an abstract concept of the difficulty a smoker has in achieving

cessation, then little more than a logical imperative is needed to conclude

that the current population of smokers is hardening. However, if hardening

is intended to mean that the population of smokers is less likely to achieve

cessation, or that existing tobacco control strategies are becoming

ineffective, then evidence of these effects actually occurring over time is

needed before reaching a conclusion that the population of smokers is

hardening. 

Careful consideration of the changing environment around the smoker

and its potential to differentially affect heavier and more-addicted smokers

is needed before the conclusion that the population of smokers must be

hardening can be converted into a judgment both that the population of

smokers has actually hardened and that we need to adjust our tobacco

control approaches to recognize that hardening.

Smoking cessation is influenced both by individual characteristics of

the smoker and by environmental forces that make smoking more

expensive, more difficult, or less rewarding. These external environmental

forces may not influence all smokers equally. Heavy smokers and those who

are more strongly addicted may be more influenced by these environmental

changes than lighter smokers. An increased intensity of environmental

motivation to quit may counterbalance a greater personal difficulty in

quitting among the residual population of smokers. The probability that it is

harder for the residual population of smokers to quit than it was for their

former smoking colleagues does not translate into a probability that they

are less likely to achieve cessation with existing tobacco control approaches

until the level of environmental support for cessation is also considered. If

SUMMARY

47

Chapter 3
difficulty in achieving cessation on an individual level results in a reduced

likelihood of successful cessation over time, then, over time, we should see

an increase in the mean number of cigarettes smoked per day, an increase in

measures of addiction (e.g., time to first cigarette), and a fall in rates of

successful cessation. The absence of convincing trends in these measures

suggests that the population of residual smokers is not “measurably” harder.

48

Smoking and Tobacco Control Monograph No. 15

REFERENCES

Brownson, R. C., Eriksen, M. P., Davis, R. M. et al.

Environmental tobacco smoke: Health effects

and policies to reduce exposure. Annual Review

of Public Health 1997;18:163–85.

Burns, D. M., Anderson, C., Johnson, M. et al.

Cessation and cessation measures among adult

daily smokers: National and state-specific data.

In Population-Based Smoking Cessation: What

Works. Smoking and Tobacco Control Monograph

No. 12, edited by D. Burns, D. Shopland, 25–97.

NIH Pub. No. 00-4892. Bethesda, MD: U.S.

Department of Health and Human Services,

National Cancer Institute, 2000a.

Burns, D. M., Shanks, T., Major, J. et al. Restrictions

on smoking in the workplace. In PopulationBased Smoking Cessation: What Works. Smoking

and Tobacco Control Monograph No. 12, edited by

D. Burns, D. Shopland, 99–126. NIH Pub. No.

00-4892. Bethesda, MD: U.S. Department of

Health and Human Services, National Cancer

Institute, 2000b.

Community Intervention Trial for Smoking

Cessation (COMMIT) Research Group. I. Cohort

results from a four-year community

intervention. American Journal of Public Health

1995a;85:183–92.

Community Intervention Trial for Smoking

Cessation (COMMIT) Research Group. II.

Changes in adult smoking prevalence. American

Journal of Public Health 1995b;85:193–200.

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 Health Care Policy and

Research, 2000.

Gilpin, E. A., Emery, S. L., Farkas, A. J. et al. The

California Tobacco Control Program: A Decade of

Progress, 1989–1999. La Jolla, CA: University of

California at San Diego, 2001.

Hollis, J. F. Population impact of clinician efforts to

reduce tobacco use. In Population-Based Smoking

Cessation: What Works. Smoking and Tobacco

Control Monograph No. 12, edited by D. Burns, 

D. Shopland, 129–53. NIH Pub. No. 00-4892.

Bethesda, MD: U.S. Department of Health and

Human Services, National Cancer Institute,

2000.

Hymowitz, N., Cummings, K. M., Hyland, A. et al.

Predictors of smoking cessation in a cohort of

adult smokers followed for five years. Tobacco

Control 1997;6(Suppl 2):S57–S62.

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

Health Benefits of Smoking Cessation. Atlanta, GA:

U.S. Department 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,

1990.

U.S. Department of Health and Human Services.

Reducing Tobacco Use: A Report of the Surgeon

General. Atlanta, GA: U.S. Department 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. 2000.

U.S. Department of Health and Human Services.

Women and Smoking: A Report of the Surgeon

General. Atlanta, GA: U.S. Department 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, 2001.
Examining a Quarter-Century of

Smoking Cessation Trials: Is the Target

Becoming Harder to Treat?*

Jennifer E. Irvin, Thomas H. Brandon

Are tobacco smokers becoming harder to treat? Anecdotal reports

by smoking-cessation providers would suggest that they are. The notion is

that as the prevalence of smoking in the United States has declined, those

smokers who have not yet quit represent the “hardcore” recalcitrant subset

of the historical smoking population. Between 1974 and 1995, the

prevalence of smoking dropped from 43.1% to 27.0% among men and from

32.1% to 22.6% among women (U.S. Bureau of the Census 1998). This

decline in smoking prevalence can be attributed to factors such as increased

knowledge about the health consequences of smoking, the deleterious

effects of secondhand smoke on nonsmokers, antismoking public health

campaigns, antismoking legislation (e.g., limitations on smoking in public

places), and the availability of relatively effective behavioral and

pharmacological smoking cessation interventions. Moreover, the last two

decades were characterized by a dramatic decline in the social acceptance of

smoking, which has led to increased social pressure to quit smoking. Indeed,

approximately half of all ever-smokers have now quit (U.S. DHHS 1989).

Those who believe that smokers are becoming increasingly recalcitrant

argue that those individuals who continue to smoke or who initiate

smoking, despite the health warnings and the social pressure, are probably

different from those who have already quit; that is, because of selective

quitting and initiation, the current population of smokers is likely to be

comprised of individuals more entrenched in their smoking behavior than

would be found in earlier years. Although this is a frequent clinical

observation, there has been little direct evidence to support this hypothesis,

and the hypothesis is controversial. Based on data that such characteristics

are associated with poorer cessation rates and greater initiation rates,

Hughes (1996) offered indirect evidence that today’s smokers are more likely

to be highly nicotine-dependent and to have comorbid psychiatric and

substance abuse disorders than in the past. Similarly, Fagerström and

colleagues (1996) found that ex-smokers had lower nicotine dependence

levels (when they were smokers) than current smokers, and that the typical

dependence level of smokers in the United States is higher than that found 

INTRODUCTION

49

Chapter 4

*Preparation of this article was supported by National Institute on Drug Abuse grant

DA10484. This study was first reported in Irvin, J. E., and Brandon, T. H. The increasing

recalcitrance of smokers in clinical trials. Nicotine and Tobacco Research 2000;2(1):79–84.
in countries in which smoking is more prevalent. Hughes (1996) also noted

that the prevalence of smoking is declining slowest among the poor and less

educated. Other evidence suggesting that the population of smokers might

be becoming more dependent is that an intensive community-based

tobacco control intervention—the Community Intervention Trial for

Smoking Cessation (COMMIT)—led to increased cessation among light to

moderate smokers but not among heavy smokers (COMMIT 1995). If this

result is representative of other tobacco control efforts, the remaining

population of smokers should be becoming increasingly nicotinedependent. In contrast to this perspective, indirect evidence that the

population of smokers is not changing is provided by epidemiological

evidence that indicates that the average smoking rate (cigarettes per day) in

the population has not changed in recent years. This evidence is presented

in other chapters of this monograph (see Chapters 7 and 8).

If the smoking population has been changing, we would expect that

smoking cessation interventions should have become progressively less

successful at producing abstinence within it. This would be expected

because smokers who are highly nicotine-dependent, of low socioeconomic

status, or who suffer from comorbid psychopathology or substance abuse

tend to have poorer outcomes from clinical interventions. To the degree

that these characteristics have become more common among smokers in

recent years, this should be reflected in declining success rates of smoking

interventions. However, Shiffman (1993) conducted a historical analysis of

outcomes from published smoking cessation interventions and concluded

that cessation rates have been stable since the mid-1970s. It is possible,

though, that the increasing recalcitrance of smokers during this period was

masked by the concurrent development of new and improved smoking

cessation aids that were employed in the published trials. Thus it is

important that the type of intervention be held relatively constant over a

historical analysis for changes in recidivism to be revealed.

For the present analysis, we searched for smoking cessation trials

published between 1975 and 1998. In order to maximize the historical

range available for comparison, it was necessary to examine a treatment

that has remained relatively constant over that time span. Very few

treatments were available throughout this entire historical period. For

example, pharmacotherapies were not available during the early portion of

the period, and aversive therapies (i.e., rapid smoking) had fallen into disuse

by the latter portion of the period. A treatment that did remain relatively

constant was cognitive-behavioral coping skills training, which is defined

below. This treatment was used as the constant treatment, and reported

outcome data was examined based on year of the publication of the

research report. It was hypothesized that we would find a trend in which

end-of-treatment and follow-up abstinence rates have been declining over

the years under study. Such a finding would support the notion that

smokers presenting for treatment over the past quarter-century have become

progressively more difficult to treat, consistent with the hypothesis of a

changing population of smokers.

50

Smoking and Tobacco Control Monograph No. 15
A search of the smoking cessation treatment literature was conducted to

identify all relevant studies. Keyword searches (e.g., smoking cessation,

multicomponent smoking treatment) of the computerized databases 

Psyc Lit, PsycINFO, and MedLine, and manual searches of bibliographies of

smoking cessation reviews (e.g., Glasgow and Lichtenstein 1987;

Lichtenstein and Glasgow 1992; Shiffman 1993; Fiore et al. 1996; Silagy 

et al. 1998), were conducted. We searched for studies published between

1975 and 1998 that met the inclusion criteria. To limit the variability of

treatments compared over this 24-year period, the inclusion criteria were

strictly defined. We limited the analyses to studies that used

multicomponent smoking cessation treatments provided in a group format,

emphasizing the training of cognitive and behavioral coping skills.

Additionally, studies were required to have been conducted in the United

States, and articles must have reported point-prevalence abstinence rates for

at least one of the following time points: end-of-treatment, 3 months, 

6 months, or 1 year post treatment. Treatment approaches that used purely

behavioral techniques (e.g., desensitization, cue exposure, rapid smoking)

were not included. We also excluded studies in which smoking

interventions were provided to special or captive populations, such as

worksite- or hospital-based treatments. Nicotine replacement therapies

became available and dominant during the period under study, so we

included studies both with and without nicotine replacement.

Table 4-1 lists the 23 studies identified by our search of the literature as

meeting inclusion criteria and reporting relevant abstinence rates.

Publication dates of the selected articles ranged from 1977 to 1996. Several

studies compared highly similar interventions, often with the difference

between treatments being the intensity of the intervention or whether

nicotine replacement therapy was used. Because of this, 15 studies provided

more than 1 treatment that met the inclusion criteria. We therefore

conducted two separate sets of analyses. An initial set of analyses was

conducted using only one treatment from each study (n = 23). When more

than one treatment in a study met inclusion criteria, we selected for these

analyses the treatment that most closely fit the prototype of coping skills

training plus nicotine replacement. For example, we selected treatments

that included nicotine replacement over those that did not, yet we were

unlikely to select treatments that included additional elements, such as

spousal involvement. To increase statistical power and to ensure the

inclusion of all appropriate interventions, a second set of analyses was

conducted based on all treatments that met the inclusion criteria (n = 44),

allowing for multiple treatments from a single study. No study contributed

more than four treatments to the analyses. 

METHOD

51

Chapter 4
52

Smoking and Tobacco Control Monograph No. 15 Table 4-1 Studies Included in the Historical Analyses Biochemical Abstinence Rates (%) Study Tx. Condition n NRT Verification End of Tx. 3 Months 6 Months 12 Months Lando, 1977 Broad Spectrum Behavioral Tx. 17 no yes 100 — 76 — Elliott and Denny, 1978 Cognitive-Behavioral Tx. Package 15 yes no 65 — 45 — Lando, 1981 Two-Stage, Intensive Contact Behavioral Tx. 21 no yes 88 63 58 46 Two-Stage, Minimal Contact Behavioral Tx. 12 no yes 60 30 30 17 Three-Stage, Intensive Contact Behavioral Tx. 19 no yes 83 35 22 19 Three-Stage, Minimal Contact Behavioral Tx. 22 no yes 67 52 42 19 Brown et al., 1984 Nicotine Fading + Relapse Prevention 16 no yes — — 25 19 Rabkin et al., 1984 Behavior Modification 34 no yes — — 24 — Hall et al., 1984 6 s. Aversive Smoking + Skills Training 29 no yes 90 — 55 52 30 s. Aversive Smoking + Skills Training 28 no yes 89 — 50 39 Killen et al., 1984 Skills Training + Nicotine Gum 22 yes yes 86 — — — Skills Training Only 20 yes yes 55 — — —

Hall et al., 1985 Intensive Behavioral Tx. + Nicotine Gum 35 yes yes — 73 59 44

Behavioral Tx. Only 36 yes yes — 47 31 28

Lando and McGovern, 1985 Nicotine Fading + Maintenance 32 no yes 62 36 21 19

Oversmoking + Maintenance 32 no yes 62 46 42 46Nicotine Fading/Smoke-holding + Maintenance 32 no yes 85 63 51 44

Davis and Glaros, 1986 Basic Tx. + Relapse Prevention 15 no yes 73 20 7 13

Discussion of Relapse Situations Control 14 no yes 21 29 21 21

McIntyre-Kingsolver et al., 1986 Basic Program 32 no yes 48 36 19 32

Basic Program + Spousal Support 32 no yes 73 42 27 36

Molgienecki et al., 1986 Behavior Modification Clinic 89 no yes — — 20 —

Behavior Modification Clinic + Media Campaign 38 no yes — — 37 —

Hall et al., 1987 Intensive Behavioral Tx. + 2 mg Nicotine Gum 35 yes yes — 43 43 34

Intensive Behavioral Tx. + Placebo Gum 34 yes yes — 35 21 21

Curry et al., 1988 Group-Based Relapse Prevention Tx. ~ 24 no yes 47 28 — 28Stevens and Hollis, 1989 Relapse Prevention 184 no yes — — — 48continued 
53

Chapter 4

Table 4-1 (continued)

Biochemical Abstinence Rates (%)

Study Tx. Condition n NRT Verification End of Tx. 3 Months 6 Months 12 MonthsGoldstein et al., 1989 Behavioral Tx. + Fixed Nicotine Gum Schedule 25 yes yes 52 — 32 —

Behavioral Tx. + Ad lib Nicotine Gum Schedule 24 yes yes 58 — 42 —

Lando et al., 1990 Freedom From Smoking Clinic 331 no yes — 24 24 22

Fresh Start Clinic 363 no yes — 29 27 25Laboratory Clinic 347 no yes — 37 29 29

McGovern and Lando, 1992 Freedom From Smoking Clinic + Nicotine Gum 146 yes yes 86 40 — 35

Freedom From Smoking Clinic Only 127 no yes — 40 — 32

Hill et al., 1993 Behavioral Training Only 22 no yes 46 — — —

Behavioral Training + Nicotine Gum 22 no yes 46 — — —Behavioral Training + Exercise 18 no yes 33 — — —

Cincirpini et al., 1994 Cognitive-Behavioral Tx. + Scheduled Smoking 17 no yes 59 — 53 41Fiore et al., 1994 High Contact Cognitive-Behavioral Tx. + 22 mg

Nicotine Patch 44 yes yes 59 — 34 —High Contact Cognitive-Behavioral Tx. + PlaceboPatch 43 no yes 40 — 21 —

Jorenby et al., 1995 Cognitive-Behavioral Tx. + 22 mg Nicotine Patch 87 yes yes 59 26 — —

Cognitive-Behavioral Tx. + 44 mg Nicotine Patch 80 yes yes 49 25 — —

Cincirpini et al., 1996 Behavior Therapy Only 32 no yes 63 22 22 22

Behavioral Therapy + Patch 32 yes yes 79 48 39 38
Pearson correlations were calculated between year of publication and

abstinence rates for four assessment points ranging from treatment end to

12 months post treatment. Because of differences across studies in the

particular assessment points reported, analyses of the four assessment points

were based on different subsets of the total sample of studies. One-tailed

significance tests were used because the strong a priori directional

hypothesis was that negative correlations would be found.

Table 4-2 displays the results from these two sets of analyses. The

pattern of negative correlations between publication year and abstinence

rates suggests that rates have declined over the 20 years represented by the

sampled studies. The greatest effect was found at the first two assessment

points (end-of-treatment and 3-month follow-up). By 12 months post

treatment, the correlations had disappeared.

We considered several potential moderator variables. First, because

biochemical verification (i.e., breath carbon monoxide, thiocyanate,

cotinine) may have become more commonly used in later studies, the

declining abstinence rates could reflect the use of these more objective

measures of smoking status. However, only 1 of the 23 studies did not use

biochemical verification, and exclusion of this study did not substantively

change the results. Second, nicotine replacement products became available

in the 1980s, so they were more likely to be used in the later studies. Of the

44 total treatments used in the analyses, 11 included nicotine replacement.

Given that nicotine replacement is intended to enhance treatment

outcomes, this possible confound should, if anything, attenuate the effect of

declining abstinence rates over time. Indeed, as seen in Table 4-2,

controlling for nicotine replacement yielded negative partial correlations of

greater magnitude than the corresponding zero-order correlations reported

above. 

Three additional methodological variables were examined: whether or

not an intent-to-treat analysis was used (reported for 20 studies, 41

treatments), time interval used to determine point-prevalence abstinence

(13 studies, 29 treatments), and treatment sample size (all 23 studies and 44

treatments). Additionally, we examined four subject variables that were

reliably reported: gender proportions, mean age (22 studies, 43 treatments),

mean years of smoking (15 studies, 31 treatments), and mean daily smoking

rate (20 studies, 41 treatments). Of these seven variables, three were

significantly correlated with year of publication: mean daily smoking rate 

(r = –0.46, p <0.01), and the highly redundant (r = 0.96) variables of age and

years of smoking (both r’s = 0.67, p <0.001); that is, over the period of

analysis, subjects in the more recent clinical trials tended to be older, have

longer smoking histories, and smoke fewer cigarettes per day. Smoking rate

was not related to any of the four outcome measures, but both age and

years of smoking were negatively correlated with abstinence rates at

treatment end (r = –0.47, p <0.01, and r = –0.40, p <0.05) but not at the later

assessment points. Controlling for mean age reduced the association

between publication year and abstinence rates at the four assessment points

below statistical significance (pr’s = –0.21, –0.27, –0.13, 0.12, respectively).

RESULTS

54

Smoking and Tobacco Control Monograph No. 15
Because of severely restricted statistical power due to the cumulative effects

of missing data, similar analyses could not be performed using years of

smoking or smoking rate as covariates.

Findings indicate a robust downward trend in abstinence rates since

the mid-1970s among multicomponent cognitive-behavioral smoking

cessation interventions, as measured immediately following treatment and

at 3- and 6-month follow-up. These results are consistent with the notion

that the target has been hardening; that is, as more and more smokers quit,

the population of remaining smokers may be changing and becoming

progressively more difficult to treat. Because the prevalence of smoking is

again increasing among adolescents (CDC 1995), it is possible that this

trend will soon reverse.

The declining trend in treatment outcome was not found when oneyear post treatment follow-up was used as the outcome index. Smoking

relapse is no doubt influenced by multiple factors such as personality, level

of nicotine dependence, exposure to cigarettes and other conditioned

stimuli, environmental stressors, and so on. With the passage of time since

quitting, there is greater opportunity for a variety of factors to influence

whether or not an individual relapses. It is therefore not surprising that

abstinence rates at later follow-up points will show weaker relationships

with any single predictor variable—including year of cessation. In addition

to such “noise” affecting the correlations, it is also likely that later

assessment points suffer from greater measurement error due to subject

attrition, repeated quit attempts, and the like. At the very least, however,

DISCUSSION

55

Chapter 4

Table 4-2

Correlations Between Year of Publication and Reported Point-Prevalence Abstinence

Rates at Treatment End and Follow-Up for Three Analyses: (1) Including Only a Single

Treatment per Study, (2) Including All Treatments That Met Inclusion Criteria, and

(3) Partial Correlations Including All Treatments, but Controlling for the Use of

Nicotine Replacement Therapy (NRT)

Assessment Point

End of Treatment 3 Months 6 Months 12 Months

One treatment per study –0.48* –0.55* –0.31 –0.03

(n = 16) (n = 11) (n = 17) (n = 14)

Multiple treatments per study –0.45** –0.32† –0.32* 0.09

(n = 31) (n = 25) (n = 33) (n = 28)

Multiple treatments, controlling for NRT –0.49** –0.44* –0.45** –0.01

(n = 31) (n = 25) (n = 33) (n = 28)

*p <0.05, one-tailed.

**p <0.01.

†p <0.1.
our findings suggest that smokers in clinical trials are relapsing more

quickly than they have in the past, even if the eventual, long-term

outcomes have not changed much over time.

The observed declining trend in successful outcome was particularly

noteworthy given that the average smoking rate (cigarettes per day) among

study participants also declined during the period of analysis. Epidemiological studies tend to find that smoking rate is inversely related to the

probability of smoking cessation (e.g., Hymowitz et al. 1997); that is, lighter

smokers are more likely to quit than heavier smokers. In this study, smoking

rate was unrelated to outcome. This leads us to question the validity of

smoking rate as an index of nicotine dependence. We believe that smoking

rate is an imperfect measure of dependence for two reasons. First, because of

variability in smoking topography (e.g., frequency, strength, and duration of

inhalations), smoking rate is only modestly associated with actual level of

nicotine delivery. Second, factors other than nicotine delivery—such as

vulnerability to negative affect, cognitions, and culture—influence nicotine

dependence (Shadel et al. 2000).

The present findings may initially appear to contradict the conclusions

from Shiffman’s (1993) analysis of historical trends (1957 to 1989) in

treatment outcomes. Shiffman found that treatment outcomes improved

during the early 1970s and remained stagnant thereafter. However, he

acknowledged that the apparent lack of improved outcomes since the mid1970s may have been a product of more heavily addicted smokers being

seen in smoking cessation clinics; that is, improvements in cessation

technology may have been masked by the counterforce of more difficult

clients. The present findings are consistent with this explanation, because

treatment outcomes actually declined when we held treatment constant in

the historical analysis—especially when we controlled for the use of

nicotine replacement therapies.

In drawing conclusions based on this historical analysis, certain

methodological limitations should be considered. First, our findings are

based on only one general type of treatment. It was necessary to select a

prototype treatment that has been in use over the entire time period under

investigation and for which there were enough published studies to conduct

meaningful correlational analyses. Nevertheless, the possibility that the

observed declining success rates are somehow limited to this particular

treatment approach should be addressed. It may be that over time the better

therapists or more motivated clients became attracted to newer treatments,

and they became less likely to participate in the fairly standard treatment

considered in this analysis. Given that nicotine replacement was the major

innovation during the period under study, and that many of the studies

included in our analyses used nicotine replacement, this scenario seems

unlikely. In fact, it is interesting that nicotine replacement, which is

considered an empirically supported treatment (Fiore et al. 1996), was found

to be no more effective than placebo in two recent studies (Jorenby et al.

1999; Joseph and Antonnucio 1999). This suggests that other interventions

may be experiencing a declining efficacy similar to that found in the

56

Smoking and Tobacco Control Monograph No. 15
current study. Nevertheless, historical outcome analyses similar to the

present one should be conducted for other smoking cessation approaches,

and perhaps for the control conditions of clinical trials as well.

An alternative explanation for our findings is that, over time, less

dependent smokers have become more likely to elect treatment options that

do not require attending a formal cessation clinic. In particular, our findings

may have been affected by the recent availability of over-the-counter

nicotine replacement. Thus it is possible that our findings reflect a trend in

which the subset of smokers seen in research clinics has become more

challenging, whereas the general population of smokers has not changed. It

may also be that participant recruitment strategies changed over the period

under study. For example, in recent years there has been greater emphasis

placed on recruiting research samples that are representative of the ethnic,

racial, gender, and socioeconomic diversity of the population at large. Thus

it may be that more recent studies have included a greater proportion of

smokers from subpopulations that have greater difficulty quitting smoking

or maintaining abstinence. 

Unfortunately, most of these descriptive statistics were not reliably

reported, precluding analysis of historical changes in subject characteristics.

Of the subject variables examined, only age, years smoking, and smoking

rate changed over time, with recent studies including older, more

experienced smokers who smoked fewer cigarettes per day. That the

remaining pool of smokers willing to participate in clinical trials may be

becoming older with a longer history of smoking is consistent with a

smoking population who will have more difficulty achieving long-term

abstinence. But the dropping rate of number of cigarettes smoked per day

appears inconsistent with the notion that remaining smokers should be

more nicotine-dependent than in the past. Of course, smoking rate may be

influenced by other historical factors such as increasing restrictions on

smoking at work, the rising cost of cigarettes, and the growing tendency for

smokers to be clustered within lower income groups. Regrettably, other

indices of nicotine dependence, such as the Fagerström Tolerance

Questionnaire (Fagerström 1978), were reported too infrequently to be

analyzed.

Because mean subject age covaried with both publication year and

abstinence rates, when we statistically controlled for subject age, the

associations between publication year and abstinence rates declined to

below statistical significance. There are at least two possible interpretations

of this finding. First, the clinical trials included in the analysis may have—

for some reason unrelated to the hypothesized changing population of

smokers—attracted older, more experienced smokers in the more recent

studies. Because older smokers have more difficulty with cessation, subjects’

age may be a confound that accounts for the observed association between

publication date and outcome. The second interpretation is that subject age,

rather than being a confound, is one of the variables that mediates the

relationship between year and outcome. That is, over the past 24 years, as

fewer adolescents (until recently) began smoking and as the younger, less

57

Chapter 4
experienced smokers may have been the most likely to quit, it is logical that

the age of smokers seeking treatment in clinical trials would have increased.

The latter interpretation is consistent with the hypothesis that smokers

seeking treatment are becoming progressively more recalcitrant, and it is

possible that this trend reflects changes in the general population of

remaining smokers.

As with any analysis of archived publications, the possibility exists that

our findings were influenced by publication bias; that is, studies that did

not find significant differences between conditions are less likely to be

published; therefore, archived publications may be biased toward studies

with significant differences. However, unlike traditional meta-analyses of

effect sizes, our analyses were based upon the absolute magnitude of

abstinence rates for individual treatment conditions. These statistics should

be less susceptible to the problem of publication bias. Moreover, because our

analyses focused on changes over time, publication bias could influence the

findings only if its effect also changed over time.

A final limitation of the present study is the small sample size

necessitated by our desire to hold treatment constant. Even for a fairly

common treatment, the number of published studies that met the inclusion

criteria (i.e., group treatments that were conducted in the United States and

that reported point-prevalence abstinence rates) was small. This may limit

the robustness of our findings. In other words, it is possible that our

findings are sample-dependent. However, we verified that exclusion of any

single data point from the analyses did not appreciably change the results.

Moreover, that the negative trend was found for three different assessment

points (end-of-treatment, 3 months, and 6 months), based on different

subsets of studies, also increases confidence in the robustness of the general

trend.

In summary, with the caveat that unknown third variables (e.g., changes

in study methodology or subject self-selection) may influence the results of

any correlational study, the finding of declining treatment outcomes over

the past quarter-century supports the observation that smokers seeking

cessation help today are more recalcitrant than in the past. That is, the

preliminary answer to the question that began this chapter (are tobacco

smokers becoming harder to treat?) appears to be “yes.” This may very well

reflect the likelihood that today’s smokers are more nicotine-dependent, of

lower socioeconomic status (SES), and more likely to suffer from comorbid

psychopathology and substance abuse, as suggested by Hughes (1996). Or it

may simply reflect a change in the subset of smokers who actively seeks

behavioral treatments rather than a change in the larger population of

smokers. The final answer awaits more direct evidence.

58

Smoking and Tobacco Control Monograph No. 15
REFERENCES

*Brown, R. A., Lichtenstein, E., McIntyre, K. O. et al.

Effects of nicotine fading and relapse prevention

on smoking cessation. Journal of Consulting and

Clinical Psychology 1984;52:307–8.

Centers for Disease Control and Prevention.

Tobacco use and usual source of cigarettes

among high school students—United States.

Morbidity and Mortality Weekly Report

1995;45:588–90.

*Cinciripini, P. M., Cinciripini, L. G., Wallfisch, A. 

et al. Behavior therapy and the transdermal

nicotine patch: Effects of cessation outcome,

affect, and coping. Journal of Consulting and

Clinical Psychology 1996;64:314–23.

*Cinciripini, P. M., Lapitsky, L. G., Wallfisch, A. 

et al. An evaluation of a multicomponent

treatment program involving scheduled

smoking and relapse prevention procedures:

Initial findings. Addictive Behaviors

1994;19:13–22. 

Community Intervention Trial for Smoking

Cessation (COMMIT) Research Group. I. Cohort

results from a four-year community

intervention. American Journal of Public Health

1995;85:183–92.

*Curry, S. J., Marlatt, G. A., Gordon, J. et al. A

comparison of alternative theoretical approaches

to smoking cessation and relapse. Health

Psychology 1998;7:545–56.

*Davis, J. R., Glaros, A. G. Relapse prevention and

smoking cessation. Addictive Behaviors

1986;11:105–14.

*Elliott, C. H., Denny, D. R. A multiple-component

treatment approach to smoking reduction.

Journal of Consulting and Clinical Psychology

1978;46:1330–339.

Fagerström, K. O. Measuring degree of physical

dependence to tobacco smoking with reference

to individualization of treatment. Addictive

Behaviors 1978;3:235–41.

Fagerström, K. O., Kunze, M., Schoberberger, R. et al.

Nicotine dependence versus smoking

prevalence: Comparisons among countries and

categories of smokers. Tobacco Control

1996;5:52–56.

Fiore, M. C., Bailey, W. C., Cohen, S. J. et al. Smoking

Cessation. Clinical Practice Guideline No. 18. NIH

Pub. No. 96-0692. Rockville, MD: U.S.

Department of Health and Human Services,

Public Health Service, Agency for Health Care

Policy and Research, 1996.

*References marked with an asterisk indicate studies included

in the historical analysis.

*Fiore, M. C., Kenford, S. L., Jorenby, D. E. et al. Two

studies of the clinical effectiveness of the

nicotine patch with different counseling

treatments. Chest 1994;105:524–33.

Glasgow, R. E., Lichtenstein, E. Long-term effects of

behavioral smoking cessation interventions.

Behavior Therapy 1987;18:297–324.

*Goldstein, M. G., Niaura, R., Follick, M. J. et al.

Effects of behavioral skills training and schedule

of nicotine gum administration on smoking

cessation. American Journal of Psychiatry

1989;146:56–60.

*Hall, S. M., Rugg, D., Tunstall, C. et al. Preventing

relapse to cigarette smoking by behavioral skill

training. Journal of Consulting and Clinical

Psychology 1984;52:372–82.

*Hall, S. M., Tunstall, C. D., Ginsberg, D. et al.

Nicotine gum and behavioral treatment: A

placebo controlled trial. Journal of Consulting and

Clinical Psychology 1987;55:603–605.

*Hall, S. M., Tunstall, C., Rugg, D. et al. Nicotine

gum and behavioral treatment in smoking

cessation. Journal of Consulting and Clinical

Psychology 1985;53:256–58.

*Hill, R. D., Rigdon, M., Johnson, S. Behavioral

smoking cessation treatment for older chronic

smokers. Behavior Therapy 1993;24:321–29.

Hughes, J. The future of smoking cessation therapy

in the United States. Addiction

1996;91:1797–802. Hymowitz, N., Cummings,

K. M., Hyland, A. et al. Predictors of smoking

cessation in a cohort of adult smokers followed

for five years. Tobacco Control 1997;6(Suppl

2):S57–S62.

Jorenby, D. E., Leischow, S. J., Nides, M. A. et al. A

controlled trial of sustained-release buproprion,

a nicotine patch, or both for smoking cessation.

New England Journal of Medicine

1999;340:685–91.

*Jorenby, D. E., Stevens, S. S., Fiore, M. C. et al.

Journal of the American Medical Association

1995;274:1347–352.

Joseph, A. N., Antonnucio, D. O. Lack of efficacy of

transdermal nicotine in smoking cessation. New

England Journal of Medicine 1999;341:1157–158.

*Killen, J. D., Maccoby, N., Taylor, C. B. Nicotine

gum and self-regulation training in smoking

relapse prevention. Behavior Therapy

1984;15:234–48.

*Lando, H. A. Effects of preparation, experimenter

contact, and a maintained reduction alternative

on a broad-spectrum program for eliminating

smoking. Addictive Behaviors 1981;6:123–33.

*Lando, H. A. Successful treatment of smokers with

a broad-spectrum behavioral approach. Journal of

Consulting and Clinical Psychology

1977;45:361–66.

59

Chapter 4
*Lando, H. A., McGovern, P. G. Nicotine fading as a

nonaversive alternative in a broad-spectrum

treatment for eliminating smoking. Addictive

Behaviors 1985;10:53–161.

*Lando, H. A., McGovern, P. G., Barrios, F. X. et al.

Comparative evaluation of American Cancer

Society and American Lung Association smoking

cessation clinics. American Journal of Public

Health 1990;80:554–59.

Lichtenstein, E., Glasgow, R. E. Smoking cessation:

What have we learned over the past decade?

Journal of Consulting and Clinical Psychology

1992;60:518–27.

*McGovern, P. G., Lando, H. A. An assessment of

nicotine gum as an adjunct to freedom from

smoking cessation clinics. Addictive Behaviors

1992;17:137–47.

*McIntyre-Kingsolver, K., Lichtenstein, E.,

Mermelstein, R. J. Spouse training in a

multicomponent smoking-cessation program.

Behavior Therapy 1986;17:67–74. 

*Mogielnicki, R. P., Nelsin, S., Dulac, J. et al. Journal

of Behavioral Medicine 1986;9:141–61.

*Rabkin, S. W., Boyko, E., Shane, F. et al. A

randomized trial comparing smoking cessation

programs utilizing behaviour modification,

health education or hypnosis. Addictive Behaviors

1984;9:157–73.

Shadel, W. G., Shiffman, S., Niaura, R. et al. Current

models of nicotine dependence: What is known

and what is needed to advance understanding of

tobacco etiology among youth. Drug and Alcohol

Dependence 2000;59(Suppl 1):S9–S21.

Shiffman, S. Smoking cessation treatment: Any

progress? Journal of Consulting and Clinical

Psychology 1993;61:718–22.

Silagy, C., Mant, D., Fowler, G. et al. Nicotine

replacement therapy for smoking cessation

(Cochrane Review). In The Cochrane Library, 3.

Oxford: Update Software, 1998.

*Stevens, V. J., Hollis, J. F. Preventing smoking

relapse using an individually tailored skills

training technique. Journal of Consulting and

Clinical Psychology 1989;57:420–24.

U.S. Bureau of the Census. Statistical Abstract of the

United States: 1998. 118th ed. Washington, DC:

U.S. Bureau of the Census, 1998, 152.

U.S. Department of Health and Human Services.

Reducing the Health Consequences of Smoking: 25

Years of Progress: A Report of the Surgeon General.

Atlanta, GA: U.S. Department 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, 1989.

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Changes in Measures of Nicotine

Dependence Using Cross-Sectional and

Longitudinal Data from COMMIT

Andrew Hyland, K. Michael Cummings

This chapter uses cross-sectional and longitudinal survey data

from the Community Intervention Trial for Smoking Cessation (COMMIT)

to assess changes in measures of nicotine dependence between 1988 and

1993. We examine rates of successful smoking cessation in relation to

different smoking behaviors, specifically the number of cigarettes smoked

per day and the time to first cigarette in the morning (a measure commonly

used to assess addiction).

The COMMIT study was initiated in 1986 and involved

testing a comprehensive community-based smoking control

intervention in 11 matched pairs of communities throughout

the United States and Canada (COMMIT 1991). Table 5-1 shows the names

of the communities that participated in the study along with their

demographic characteristics and smoking prevalence rates. For the purposes

of the trial, a community was broadly defined to include an individual city,

multiple smaller geographically linked cities, and portions of well-defined

metropolitan areas. Within each community pair, one community was

randomly assigned to comprehensive intervention and the other served as a

comparison community. The intervention phase of the trial was completed

in December 1992. Details on the COMMIT intervention and findings from

the trial are published elsewhere (U.S. DHHS 1995; COMMIT 1995a,b).

The first cross-sectional survey was conducted during a

telephone interview implemented between January and May

1988. Details of the survey are published elsewhere (COMMIT

1991). In addition to the cross-sectional component of the survey, current

smokers aged 25 to 64 years were eligible for inclusion in a cohort of

smokers to be followed until 1993. A current smoker was defined as

someone who reported having smoked at least 100 cigarettes in his or her

lifetime and who also reported smoking at the time of interview. 

The 1988 survey was administered in two stages. The first stage involved

identifying representative samples averaging 5,400 households within each

community and gathering information on the age, gender, and smoking

behaviors of all adults within selected households. In the second stage, a

sample of current smokers aged 25 to 64 years was selected for an extended

cross-sectional interview that included questions about current and past

smoking behaviors, brand and type of cigarette usually smoked, interest in

COMMIT Surveys

Cross-Sectional Surveys

METHODS

The COMMIT Study

INTRODUCTION

61

Chapter 5
quitting smoking, alcohol consumption, the presence of other smokers in

the household, and sociodemographic characteristics. The mean response

rate for the household rostering portion of the survey was 84%. Of the

eligible smokers identified from the household rostering, 92% completed

the extended interview. There were 34,443 respondents to the 1988 crosssectional survey with complete smoking status, amount smoked,

demographic categories, and other tobacco-related variables indicated. 

From August 1993 to January 1994, a similar random-digit–dialed

telephone survey was conducted to identify approximately 2,300

households in each COMMIT community. A disproportionate sample of

smokers, ex-smokers, and never-smokers aged 25 to 64 years was selected to

participate in an extended interview to gather information on current and

past smoking status, other tobacco-use patterns, and demographic variables.

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Smoking and Tobacco Control Monograph No. 15

Table 5-1

Characteristics of the 22 Communities Participating in COMMIT

% Adult Smoking

High School Low

State/ Population Graduates Income White

Community Pairs (I/C)* Country (N) (%) (%) (%) 1988 1993

Yonkers (I) NY/USA 63,278 67 40 76 25 22

New Rochelle (C) NY/USA 57,493 68 44 75 25 20

Bellingham (I) WA/USA 65,632 79 49 95 20 18

Longview/Kelso (C) WA/USA 60,424 72 41 96 26 24

Vallejo (I) CA/USA 89,046 73 42 66 26 19

Hayward (C) CA/USA 121,134 69 37 77 25 19

Santa Fe (I) NM/USA 57,572 77 47 80 22 19

Las Cruces (C) NM/USA 53,757 73 55 80 20 17

Paterson (I) NJ/USA 138,317 42 59 52 27 21

Trenton (C) NJ/USA 91,726 49 60 47 29 26

Medford/Ashland (I) OR/USA 58,929 78 51 97 21 20

Albany/Corvallis (C) OR/USA 73,452 83 50 95 18 16

Raleigh (I) NC/USA 163,036 77 40 73 23 20

Greensboro (C) NC/USA 166,824 66 47 64 26 26

Utica (I) NY/USA 85,490 58 58 93 27 24

Binghamton/Johnson City (C) NY/USA 76,418 63 57 96 26 23

Cedar Rapids (I) IA/USA 144,835 78 35 97 22 22

Davenport (C) IA/USA 136,408 75 35 93 26 24

Fitchburg/Leominster (I) MA/USA 75,805 61 49 97 26 23

Lowell (C) MA/USA 92,418 58 52 96 29 26

Brantford (I) Ont/Canada 86,985 46 34 NA 32 30

Peterborough (C) Ont/Canada 84,800 54 36 NA 28 25

*I/C: Within each community pair, one community was randomly assigned to comprehensive intervention (I), and the other served as

a comparison (C) community.
The response rate for the survey was 80%. Data used for this analysis are for

the sample of 13,146 respondents with complete data on tobacco-related

variables. 

A sample of approximately 500 light-to-moderate (<25 cigarettes

per day) and 500 heavy smokers (>25 cigarettes per day) in each community

was taken from the 1988 cross-sectional survey. These individuals comprise

the smoker cohort for COMMIT, were followed until 1993, and reinterviewed using an instrument comparable to the baseline survey. In 1988, the

cohort consisted of 20,417 smokers (10,328 light-to-moderate and 10,019

heavy smokers). By 1993, 13,415 smokers remained, including 3,214 (24%)

former smokers. Persons who were younger, single, and less educated were

more likely to be lost to follow-up over the five-year study period.

A current smoker is defined as someone who reports he or

she has smoked 100 cigarettes in his or her lifetime and answers “yes” to

the question: “Do you smoke cigarettes now?”

A person is classified as a successful quitter if he or she was previously

defined as a current smoker and also reported not smoking any cigarettes in

the 6 months prior to the interview.

Number of cigarettes smoked per day is defined as

the weighted average of amount smoked per weekday and weekend. For

these analyses, this continuous measure is categorized into the following

groups: <5 cigarettes per day, 5 to 14 cigarettes per day, 15 to 24 cigarettes

per day, 25-plus cigarettes per day.

The time to the first cigarette in the morning is based on responses to

the following question: “How soon after you wake up do you have your first

cigarettes?” Response categories were “less than 10 minutes,” “from 10 to 30

minutes,” “from 31 minutes to 1 hour,” “from 61 minutes to 1.5 hours,”

“from 91 minutes to 3 hours,” and “more than 3 hours.” The latter three

categories were collapsed for these analyses to comprise a category of “more

than 60 minutes.”

Tar yields of cigarettes were determined by linking self-reported UPC

code and brand descriptor information provided in the surveys to the 1993

Federal Trade Commission (FTC) report (FTC 1995) on the tar, nicotine, and

carbon monoxide content of varieties of cigarettes for sale in the United

States. These tar yields were used to assign subjects to one of three

categories: ultra-light (0 to 6 mg tar), light (7 to 15 mg tar), and regular

(16-plus mg tar). Self-reported generic brands typically were not able to be

matched to the FTC data; therefore, there is a disproportionate percentage

of missing data in the 1993 survey (28% missing) compared with the 1988

survey (14% missing) because generic use was much more prevalent in 1993

(Cummings et al. 1997).

Measures of Nicotine Dependence

Measures of Smoking Status

Longitudinal Survey

63

Chapter 5
Other Predictor Variables: The following predictor variables were used

for these analyses:

• Gender (male or female)

• Age (25 to 34 years, 35 to 44 years, 45 to 54 years, 55 to 64 years)

• Race/ethnicity (white non-Hispanic, black non-Hispanic, Hispanic,

Asian, American Indian, Canadian, other)

• Gross household income (<$10,000/year, $10,000 to $25,000/year,

$25,001 to $40,000/year, >$40,000/year)

• Education (<12 years, 12 years, 13 to 15 years, 16-plus years)

• Alcohol consumption (daily, 3 to 4 times/week, 1 to 2 times/week, 

1 to 3 times/month, <1 time/month)

• Age started smoking daily (<16 years, 16 to 19 years, >19 years)

• Use of a noncigarette tobacco product (yes or no)

• Price category of cigarette smoked (generics, discount, premium)

• Desire to quit (none, a little, somewhat, a lot)

• Presence of another smoker in the household (yes or no)

Analyses focus on the association between quitting, measures of

dependence, and other factors. Some of these findings have been previously

reported (Hymowitz et al. 1997). Briefly, a logistic regression model was

constructed with successful cessation in 1993 as the outcome, and the

baseline measures of tobacco dependence and other variables outlined

above included as predictors.

Change in the number of cigarettes smoked per day, time to first

cigarette in the morning, and tar level of cigarettes smoked between 1988

and 1993 from the cross-sectional surveys are also reported. Independent

samples t-tests are used to assess the statistical significance of change in

these measures over time. 

Figures 5-1 and 5-2 show the association between amount smoked or

time to first cigarette and future cessation, controlling for a variety of other

potential confounding factors. Lower levels of consumption and longer

duration before smoking in the morning were both significantly predictive

of an increased likelihood of success in stopping smoking.

The percentage of respondents at each level of the measures of

dependence from the two cross-sectional surveys is reported in Figures 5-3

to 5-5. The average amount smoked per day decreased from 20.4 cigarettes

per day in 1988 to 18.7 cigarettes per day in 1993 (p = <0.01), and fewer

smokers fell into the 25-plus cigarettes category (29% in 1988 versus 25% in

1993) (Figure 5-3). Time to first cigarette in the morning remained virtually

unchanged between 1988 and 1993 (Figure 5-4). The reported tar level, per

the FTC method, decreased from 1988 to 1993; in 1988, 52% of subjects

reported smoking a light or ultra-light cigarette, whereas 69% reported the

same in 1993 (p = <0.01) (Figure 5-5).

RESULTS

ANALYSIS

64

Smoking and Tobacco Control Monograph No. 15
Data collected from COMMIT between 1988 and 1993 indicate the

following: (1) smokers who are less dependent (as measured by amount

smoked and time to first cigarette) are more likely to stop smoking in the

future, and (2) population-based surveys in 22 North American

communities indicate that the number of cigarettes smoked per day and the

tar level of cigarettes smoked have decreased, and that the time to first

cigarette has remained constant over this relatively short interval. 

There are many ways to measure tobacco dependence. Three measures

are highlighted in this study: (1) cigarettes smoked per day, (2) time to first

cigarette in the morning, and (3) tar level of cigarettes smoked. 

Although it is recognized that the measures used in this study are crude

measures that are only moderately correlated with a more standard measure

of dependence (i.e., Fagerström Tolerance Questionnaire) (Riggs and Hughes

SUMMARY

65

Chapter 5

Figure 5-1

Average Daily Amount Smoked as a Predictor of Future Cessation, 1988 to 1993*

*Data from the COMMIT Endpoint Cohort, N = 13,415. Adjusted for sex, age, race/ethnicity, income, education, alcohol consumption,

age started smoking, time to first cigarette, use of a noncigarette tobacco product, price category of cigarette smoked, past quit

attempts, desire to quit, and number of other smokers in the household.

NOTE: Underlined relative risks are statistically significant at the 5% level. Relative Risk

Cigarettes per Day

0

2

3

25+ 15–24 5–14 <5

1.0

1.2

1.6

2.4
1998), studies clearly show that some of these measures of dependence are

among the strongest predictors of who makes a cessation attempt and who

succeeds in quitting (Hymowitz et al. 1997; Farkas et al. 1996).

Time to first cigarette in the morning does have predictive validity for

tobacco dependence (Kozlowski, Pillitteri, and Sweeney 1994). The finding

that this measure remained virtually unchanged between 1988 and 1993 in

this study provides little support for the hardening hypothesis. The average

number of cigarettes smoked per day decreased by nearly 10% in this study.

This is likely due to increased restrictions about smoking in the workplace

and public places during the course of the COMMIT study (Glasgow,

Cummings, and Hyland 1997); however, population levels of dependence

have probably remained unchanged as smokers tend to compensate for

their smoking behavior (Evans and Farrelly 1998; Kozlowski et al. 1989,

1994) and still exhibit behaviors consistent with dependence. 

66

Smoking and Tobacco Control Monograph No. 15

Figure 5-2

Time to First Cigarette as a Predictor of Future Cessation, 1988 to 1993* Relative Risk

Time to First Cigarette (Minutes)

0

2

3

<10 10–30 30–60 60+

1.0

1.2

1.4

1.8

*Data from the COMMIT Endpoint Cohort, N = 13,415. Adjusted for the following baseline factors: sex, age, race/ethnicity, income,

education, alcohol consumption, age started smoking, amount smoked, use of a noncigarette tobacco product, price category of

cigarette smoked, past quit attempts, desire to quit, and number of other smokers in the household.

NOTE: Underlined relative risks are statistically significant at the 5% level. 
Three possible alternative explanations are offered that reconcile the

findings from this study and the hardening hypothesis. They are: 

• The population of smokers is dynamic and the characteristics of

smokers have changed over time; however, on balance, the

dependence level of the population has remained constant. For

example, older smokers are more likely to quit than younger

smokers, but younger smokers are less dependent than older

smokers and smoking initiation rates have been increasing until

recently. A dynamic smoking population with a greater percentage

of younger smokers who are less likely to quit and are less addicted

may explain why population cessation rates have not continued to

increase and time to first cigarette has not changed.

67

Chapter 5

Figure 5-3

Average Daily Amount Smoked From the 1988 and 1993 Cross-Sectional COMMIT

Surveys* Percentage

Cigarettes per Day

0

10

20

30

40

50

<5 5–14 15–24 25+

1988

1993

7%

9%

24%

28%

40% 39%

30%

25%

The average daily amount smoked among smokers was 20.4 in 1988 and 18.7 in 1993.

*Among smokers age 25–64. N = 34,443 in 1988 and N = 13,146 in 1993.
• The population has changed with respect to other factors that are

associated with decreased smoking cessation rates, such as lower

incomes, younger age, alcohol consumption, and other factors. Data

from the 1988 and 1993 COMMIT cross-sectional surveys indicates

that the mean age and the frequency of alcohol consumption

remained constant and annual income increased (data not shown),

disputing this explanation. However, a more detailed study of

changes in population-based predictors of smoking cessation over

time is warranted to better address this issue.

• The introduction of readily available treatments for tobacco use,

including the sale of nicotine gum and patches over the counter,

may have shifted the primary source of treatment for tobacco

dependence from the physician to the individual smoker. Persons

who enter clinics today for smoking cessation may be more likely to

be smokers who tried a variety of unsuccessful measures to quit on

their own and are inherently less likely to quit smoking, thus

potentially explaining the observation of decreased clinical cessation

rates.

68

Smoking and Tobacco Control Monograph No. 15

Figure 5-4

Time to First Cigarette in the Morning From the 1988 and 1993 Cross-Sectional

COMMIT Surveys*

*Among smokers age 25–64. N = 34,443 in 1988 and N = 13,146 in 1993. Percentage

Time to First Cigarette (Minutes)

1988

1993

0

10

20

30

40

<10 10–30 30–60 >60

27% 28%

31%

18%

24% 23%

29%

19%
In summary, data from COMMIT do not indicate that the number of

cigarettes smoked per day or time to first cigarette has changed as

population-level measures of tobacco dependence between 1988 and 1993.

The short time period available to measure changes consistent with

hardening may limit the opportunity to observe these changes, and the

measures of dependence used have their limitations; however, the data

available from the COMMIT study do not demonstrate a clear hardening in

the population.

69

Chapter 5

Figure 5-5

Average Tar Level of Cigarettes Smoked From the 1988 and 1993 Cross-Sectional

COMMIT Surveys*

*Among smokers age 25–64. N = 34,443 in 1988 and N = 13,146 in 1993. Percentage

Tar Level (mg)

1988

1993

0

25

50

75

0–6 7–15 16+

31%

8%

11%

44%

59%

48%
REFERENCES 

Community Intervention Trial for Smoking

Cessation (COMMIT) Research Group. Summary

of design and intervention. Journal of the

National Cancer Institute 1991;83:1620–628. 

Community Intervention Trial for Smoking

Cessation (COMMIT) Research Group. I. Cohort

results from a four-year community

intervention. American Journal of Public Health

1995a;85:183–92.

Community Intervention Trial for Smoking

Cessation (COMMIT) Research Group. II.

Changes in adult smoking prevalence. American

Journal of Public Health 1995b;85:193–200.

Cummings, K. M., Hyland, A., Lewit, E. et al. Use of

discount and generic cigarettes by smokers in 20

U.S. communities, 1988 to 1993. Tobacco Control

1997;6(Suppl 2):S25–S30.

Evans, W. N., Farrelly, M. C. The compensating

behavior of smokers: Taxes, tar, and nicotine.

RAND Journal of Economics 1998;29(13):578–95. 

Farkas, A. J., Pierce, J. P., Zhu, S. H. et al.

Dependence versus stages of change models in

predicting smoking cessation. Dependence

1996;91(9):1271–280.

Federal Trade Commission. Tar, Nicotine, and Carbon

Monoxide of the Smoke of 1,107 Varieties of

Domestic Cigarettes. Washington, DC: Federal

Trade Commission, 1995.

Glasgow, R., Cummings, K. M., Hyland, A.

Relationship of worksite smoking policy to

changes in employee tobacco use: Findings from

COMMIT. Tobacco Control 1997;6(Suppl 2):

S44–S48. 

Hymowitz, N., Cummings, K. M., Hyland, A. et al.

Predictors of smoking cessation in a cohort of

adult smokers followed for five years. Tobacco

Control 1997;6(Suppl 2):S57–S62.

Kozlowski, L. T., Heatherton, T. F., Frecker, R. C. 

et al. Self-selected blocking of vents on low-yield

cigarettes. Pharmacology, Biochemistry, and

Behavior 1989;33(4):815–19.

Kozlowski, L. T., Pillitteri, J. L., Sweeney, C. T.

Misuse of “light” cigarettes by means of vent

blocking. Journal of Substance Abuse

1994;6(3):333–36.

Kozlowski, L. T., Porter, C. Q., Orleans, C. T. et al.

Predicting smoking cessation with self-reported

measures of nicotine dependence: FTQ, FTND,

and HSI. Drug and Alcohol Dependence

1994;34:211–16. 

Riggs, R. L., Hughes, J. R. Relationship among three

common measures of nicotine dependence.

Problems of Drug Dependence, 1998: Proceedings

from the 60th Annual Scientific Meeting of the

College on Problems of Drug Dependence, Inc.

NIDA Research Monograph No. 179, 190. NIH

Pub. No. 99-4395. Washington, DC: NIDA,

National Institutes of Health, 1999.

U.S. Department of Health and Human Services.

Community-Based Interventions for Smokers: The

COMMIT Field Experience. NCI Monograph No. 6,

edited by B. Thompson, D. Burns, W. R. Lynn.

NIH Pub. No. 95-4028. Bethesda, MD: U.S.

Department of Health and Human Services,

Public Health Service, National Institutes of

Health, National Cancer Institute, 1995. 

70

Smoking and Tobacco Control Monograph No. 15
Changes in Smoking Habits in the

American Cancer Society CPS I

During 12 Years of Follow-Up

Thomas G. Shanks, Christy M. Anderson

The question whether smokers who continue to smoke after large

numbers of their smoking peers have quit represent a group who has more

difficulty quitting can be examined in studies which provide longitudinal

follow-up of groups of smokers (see Chapter 5). The Cancer Prevention

Study I (CPS I) of the American Cancer Society (Garfinkel 1985) followed

over one million subjects over a 12.75-year period. At baseline and at four

follow-up surveys, subjects provided information about current smoking

habits. Changes in smoking behaviors over time can be examined for

evidence of falling cessation rates among the residual smokers in the

population and trends toward the residual population of smokers being

disproportionately composed of heavy smokers as lighter smokers quit in

larger numbers. The focus of this chapter is on descriptive analyses of the

cessation rates and changing smoking behaviors of current smokers in the

CPS I. 

The data contained in this chapter describe smoking behaviors that are

over 30 years old and the use of cigarettes that are quite different in design

and smoke yield with machine testing. However, the data offer some insight

into the important questions whether the difference in cessation rates by

number of cigarettes smoked per day remains constant across time and

whether enhanced cessation success by lighter smokers leads to an increase

in the fraction of heavier smokers over time.

The CPS I was a major prospective study carried

out by the American Cancer Society (Garfinkel

1985). Over one million individuals were

followed for up to 12.75 years from 1959 to 1972. The baseline survey

included age at initiation of smoking, present cigarette use or age at

cessation, as well as information about health history and other behaviors.

The major outcome variable was mortality by specific cause as indicated on

the death certificate. 

The focus of the present chapter is on white male

subjects who were current cigarette smokers on the baseline questionnaire

in 1959. Subjects who were former smokers at that time or who used other

forms of tobacco along with cigarette smoking were excluded from these

analyses. The baseline data with these restrictions included 174,997 white

male current cigarette smokers. Follow-ups were conducted in 1961, 1963,

Data on Smoking Status

CANCER PREVENTION STUDY I

Description of CPS I Data

INTRODUCTION

71

Chapter 6
1965, and 1972 and included questions about continuing smoking status,

the brand of cigarette smoked, and number of cigarettes smoked each day.

In order to consider changes in smoking habits in a healthy population, the

analyses presented in this chapter are further subset to include only

individuals reporting “good” health at baseline, surviving for the duration

of the study, and responding to questions at each follow-up survey with

answers to the smoking questions. These restrictions reduce the number of

subjects to 50,598 individuals for whom complete data are available, but

they also reduce the biases introduced by smokers quitting when they

develop disease. If subjects in fair or poor health or individuals who died

during the years of follow-up had been included, rates of cessation and level

of daily smoking would be more influenced by factors related to changing

health status.

At baseline and follow-up surveys, smokers were asked

how many cigarettes they smoked each day. Responses were categorized into

levels 1 to 9, 10 to 19, 20, 21 to 39, 40, 40-plus for all survey periods except

the final follow-up, in which the specific number of cigarettes smoked per

day was recorded. For these analyses, levels 40 and 40-plus were combined

and the final follow-up was converted to the same categorical levels as the

earlier surveys. The data categories in the CPS I study do not distinguish

between complete cessation and occasional smoking (not smoking every

day). Thus these cessation rates also include smokers who had shifted to

occasional smoking status.

A database of healthy white male subjects smoking

cigarettes exclusively at baseline and surviving to the end of the 12-year

follow-up period, with smoking questions answered on all follow-up

surveys, was assembled. For age standardization of rates, a fictitious

population was constructed representing the combined age distribution of

subjects across all surveys by five-year age groups. This was accomplished by

averaging the age distribution of the subjects at the time of each of the

surveys. This age distribution standard is given in Table 6-1, with the age

distributions at the beginning of the study (January 1959) and at the last

follow-up (September 1972) also given for comparison. Simple

nonparametric bootstrapping was undertaken (percentile interval method)

with 200 bootstrap resamples, producing the 95% confidence interval

estimates shown. Rates of cessation over a period of time are estimated

using the model of a continuously compounded function, with a resulting

rate of continuous cessation that would produce the cessation totals

observed across the interval, as given by Formula 6.1:

Rate = –ln (1 – dCess)/dTime

in which Rate is the rate of continuous cessation in percent per year; dCess,

the observed proportion of cessation; dTime, the time interval in years.

METHODS OF ANALYSIS

Cigarettes per Day Levels

72

Smoking and Tobacco Control Monograph No. 15
Figure 6-1 shows the cumulative cessation over the 12.75-year

period across the entire group of healthy current cigarette

smokers at baseline, N = 50,598. The cumulative cessation

shown for each follow-up date is the percent of subjects who

reported not smoking at that time; all values are age standardized. Figure 

6-1 reveals a steady rate of increasing cumulative cessation during the

follow-up period. By the end of the 12.75 years of follow-up, 58.0% (57.3%

to 58.6%) (95% confidence intervals) of the group of current smokers at

baseline reported not smoking. 

Using the number of subjects smoking at the beginning and end of each

interval of follow-up and Formula 6.1, we can calculate the annual rate of

cessation during each period of follow-up that would underlie the observed

cumulative cessation totals, with the result shown in Figure 6-2. At the first

follow-up period in September 1961, 9.3% (9.0% to 9.5%) of the original

group of smokers reported not smoking, which converts to an average rate

of 5.6% (5.4% to 5.8%) annual cessation over the interval of 1.75 years.

During the subsequent periods of follow-up, cessation rates of 6.8% (6.6% to

7.0%), 8.6% (8.4% to 8.8%), and 9.6% (9.3% to 9.7%) were estimated from

the number quitting over the interval (shown in Table 6-2 under the

category “Combined”). Since the pool of current smokers declined during

the 12.75-year period as more and more smokers became former smokers,

the rate of cessation among the remaining smokers must increase to

produce the apparent uniform rate of cumulative cessation seen in Figure 

6-1. The bootstrapped confidence intervals shown in Figure 6-2 are

nonoverlapping, which confirms the observation of an increasing rate of

cessation during the years 1959 to 1972 with significant probability.

RESULTS

Rates of Cessation

During Follow-Up

73

Chapter 6

Table 6-1

Fictitious Standard Population Used for Age-Standardization (%)

Age Fictitious Standard Population 1/1959 9/1972

<40 5.0 9.6 0.0

40–44 6.4 9.7 1.1

45–49 16.0 28.7 5.1

50–54 23.9 26.1 7.5

55–59 20.5 14.8 18.5

60–64 14.7 6.9 29.8

65–69 8.1 2.9 20.9

70–74 3.6 0.9 10.4

75–79 1.3 0.2 4.6

>80 0.5 0.0 2.2

Total 100.0 100.0 100.0
Figure 6-3, a variation of Figure 6-1, shows the cumulative

cessation for smokers of different numbers of cigarettes per day

as recorded at the beginning of the study. Cumulative cessation is highest

for the lower CPD levels, with significantly higher cessation for the 1 to 9

CPD group, followed by the 10 to 19 CPD group. This consistent pattern is

sustained by the 20 CPD group, which has slightly higher cumulative

cessation than the groups smoking more than 20 CPD. The highest CPD

groups of 21 to 39 and 40-plus have the lowest rates of cumulative cessation

and are not always distinguishable. Clearly there is a relationship between

the baseline CPD and likelihood of cessation, with the lower CPD levels 

(1 to 9 CPD and 10 to 19 CPD) having higher cumulative levels of cessation.

At the final survey, among the 1 to 9 CPD group at baseline, 72.6% (70.2%

to 74.4%) reported not smoking. The rates for the other CPD groups are

62.5% (60.9% to 64.3%), 56.5% (55.5% to 57.4%), 53.6% (52.3% to 54.8%),

and 54.1% (51.9% to 56.1%) for the initial 10 to 19 CPD, 20 CPD, 21 to 39

CPD, and 40-plus CPD groups, respectively.

Rates of Cessation

by Baseline CPD

74

Smoking and Tobacco Control Monograph No. 15

Figure 6-1

Cumulative Reported Cessation at Successive Follow-Up Surveys, Among

Respondents Who Were Smokers at Start of Survey Percent of Total Cohort

Date of Follow-Up Survey

White Male Healthy Current Smokers

at baseline, complete follow-up data,

and surviving to 1972, N = 50598

Sept.

1961 Sept.1965 Sept.1963 Sept.1972

0

10

20

30

40

50

60

70

95% CI
75

Chapter 6

Table 6-2Within-Interval Annual Rate of Reported Cessation in Successive Follow-Up Intervals. CPD Based on Level Reported atBeginning of Each Period of Follow-Up. Rates Age-StandardizedPeriod Combined 1–9 CPD 10–19 CPD 20 CPD 21–39 CPD 40+ CPD

1 5.6% (5.4–5.8) 13.3% (12.2–14.1) 6.5% (6.1–6.9) 4.8% (4.5–5.1) 4.1% (3.7–4.4) 4.2% (3.7–5.0)2 6.8% (6.6–7.0) 12.4% (11.6–13.4) 8.5% (7.9–8.9) 6.4% (6.1–6.7) 5.6% (5.1–6.0) 4.7% (4.3–5.2)3 8.6% (8.4–8.8) 15.6% (14.5–16.6) 10.9% (10.3–11.6) 8.3% (7.9–8.6) 6.8% (6.4–7.2) 5.8% (5.2–6.3)4 9.6% (9.3–9.7) 12.2% (11.2–13.1) 11.0% (10.4–11.6) 9.4% (9.0–9.7) 8.9% (8.5–9.3) 8.1% (7.6–8.6)
Figure 6-4 presents cessation rates annualized within each follow-up

interval and calculated separately for the different CPD levels. The CPD

levels from which the rates in Figure 6-4 are calculated are based on the

transient CPD levels rather than the baseline categories—i.e., with the CPD

levels for the most recent survey response used in the analysis. This figure

shows that over the 12-year period of the CPS I follow-up, there was a

convergence of quit rates among the different CPD levels. Both initially and

throughout the period of follow-up, cessation rates for the 1 to 9 CPD group

are highest, with rates for the 10 to 19 CPD group also higher than for the

20 cigarette a day and higher smokers but lower than for the 1 to 9 CPD

group. This differential is clear during the first five years of the study, with

rates generally increasing for all CPD levels. During the last seven years,

there is a marked tendency for the quit rates from all groups to converge

toward a mean value. Rates for the lower CPD groups flatten, but rates in

the higher CPD group show an increase during the last seven years of

follow-up. 

76

Smoking and Tobacco Control Monograph No. 15

Figure 6-2

Rate of Reported Cessation at Successive Follow-Up Intervals, Annualized Within

Follow-Up Interval Percent Annual Reported Quits

Date of Follow-Up Survey

White Male Healthy Current Smokers

at baseline, complete follow-up data,

and surviving to 1972, N = 50598

Sept.

1961 Sept.1965 Sept.1963 Sept.1972

0

2

4

6

8

10

12

14

95% CI
Figure 6-5 presents the same data shown in Figure 6-4, but changes the

X axis to the CPD level, connecting the points from each follow-up survey

so that we can see the quit-rate profile across the CPD levels as it changes

during the successive periods of follow-up. With this presentation, the

pattern of generally increasing rates of cessation during the period of the

study as the lines from the successive surveys move upward can be seen.

Within each follow-up period, the quit rates for the lower CPD levels are

higher than for the levels with 20 or more CPD. However, the slope of the

lines decreases for the last seven-year period, showing less of a rate

difference between the CPD levels in the last follow-up period. 

Figure 6-6 shows the mean CPD across all currently smoking

subjects at each survey using the CPD reported at the time of

each follow-up. Since CPD is a categorical variable, mean CPD is calculated

using a CPD value for each subject based on the observed means for each

category at the time of the final follow-up (1972), when actual numbers of

cigarettes smoked each day is recorded. These values are 4.48, 11.97, 20.00,

29.15, and 43.52 for the successive CPD categories. Because CPD data is

categorical, the increasing mean CPD seen for successive surveys is

Mean CPD at

Successive Surveys

77

Chapter 6

Figure 6-3

Cumulative Percent of Smokers Reported Quit for Different Baseline CPD,

Age-Standardized Percent of Cohort

Date of Follow-Up Survey

Sept.

1961 Sept.1965 Sept.1963 Sept.1972

Cigarettes per Day

at start of survey

1–9

10–19

20

21–39

40+

0

10

20

30

40

50

60

70

80

95% CI
equivalent to a decreasing proportion of subjects at the lower CPD levels

compared with the higher CPD levels. This result is consistent with the

results seen in Figures 6-4 and 6-5, showing higher rates of cessation among

the lower CPD levels. Although there is some migration between CPD levels

(results not shown), Figure 6-6 shows that a greater proportion of smokers at

the higher levels of CPD continued to smoke at the end of the 12 years of

follow-up. The successive mean CPD values for the subjects still smoking are

22.0 (21.9 to 22.1) at baseline, increasing successively to 22.3 (22.2 to 22.4),

22.5 (22.4 to 22.6), 22.7 (22.6 to 22.8), and 23.8 (23.6 to 24.1) by the end of

the study.

The mean CPD among remaining smokers increased during the 12

years of follow-up from this study (Figure 6-6). This is consistent with

the view that it is harder for a heavy smoker to quit smoking, so that, over

time, more heavy smokers remain among the current smoking population.

This conclusion is supported by a generally higher rate of cessation for the

lower CPD levels compared with the higher levels. Both of these trends are

consistent with the view that cessation rates are highest for lighter smokers

Discussion

of Results

78

Smoking and Tobacco Control Monograph No. 15

Figure 6-4

Within-Interval Annualized Rate of Reported Quits by CPD Reported at Successive

Surveys, Age-Standardized

Cigarettes per Day

at successive surveys Percent Annual Reported Quits

Date of Follow-Up Survey

Sept.

1961 Sept.1965 Sept.1963 Sept.1972

0

2

4

6

8

10

12

14

16

18

1–9

10–19

20

21–39

40+

95% CI
and that the remaining population of smokers tends to become increasingly

composed of heavier smokers for whom quitting is more difficult or less

frequently undertaken.

The increasing mean CPD among the remaining smokers may be

confounded by compensation in smoking behavior due to the declining

machine-measured nicotine yields of cigarettes during the period of this

study. During the CPS I study, tar and nicotine were declining rapidly in

many brands. Using nicotine estimates for each brand from lab tests from

the period (Miller 1959; Federal Trade Commission 1967–1973) and the

brand reported by each individual, the average nicotine yield for a single

cigarette was 1.83 mg nicotine across these subjects at the beginning of the

study in 1959, but that had declined to 1.29 mg of nicotine at the end of

the study in 1972 for those subjects still smoking. These values are agestandardized using subjects for whom nicotine values were available. If

smokers increase the number of cigarettes smoked in order to compensate

for the declining nicotine yields, the mean CPD increase may reflect

compensation instead of hardening. The increasing CPD seen in this study

79

Chapter 6 

Figure 6-5

Within-Interval Annual Rate of Cessation by Transient CPD as Reported at Successive

Surveys, Age-Standardized

Month/Year of Follow-Up Percent Annual Cessation

Reported CPD Level at Each Follow-Up Survey

1/59–9/61

9/61–9/63

9/63–9/65

9/65–9/72

1–9 10–19 20 21–39 40+

0

2

4

6

8

10

12

14

16

18

95% CI
is consistent with the increasing mean CPD observed in the populationbased National Health Interview Survey (NHIS), whose results are reviewed

in Chapter 7 of this monograph. 

In contrast to this evidence of hardening, there was a generally

increasing rate of cessation across the 12 years of the CPS I study. The thesis

of hardening would suggest that as the smokers for whom quitting is easier

become former smokers, the residual pool of smokers would have decreasing

rates of cessation. Instead, we have cessation rates increasing across all

subjects, from 5.6% annual cessation during the first period of follow-up to

a final rate of 9.6% annual cessation during the final follow-up period.

Moreover, the increase in rates of cessation over the final follow-up period is

most pronounced among the higher CPD groups (Figure 6-4), which shows

a general increase in rates of cessation during the period of the study for the

higher CPD group. 

These seemingly contradictory trends may have resulted from

independent factors in play during this period. Physiological and

psychological factors may make cessation rates higher among lighter, less

dependent smokers, which would lead to a residual smoking population

with higher mean CPD levels and progressively lower rates of cessation. But

80

Smoking and Tobacco Control Monograph No. 15

Figure 6-6

Mean Number of Cigarettes Smoked per Day Across Subjects Still Smoking Mean Cigarettes per Day

Date of Follow-Up Survey

Jan.

1959 Sept.1961 Sept.1963 Sept.1965 Sept.1972

20

21

22

23

24

25

95% CI
across this variation are broad social factors during the period of the CPS I

study (from 1959 to 1972), which may have tended to increase rates of

cessation across all categories. This period was characterized by changes in

the public perception of health risks related to smoking, increased

marketing of filtered cigarettes with health-related advertising messages,

release of the U.S. Surgeon General’s report on smoking and health in 1964

(U.S. DHEW 1964), and the period of counter-advertising on television from

1967 to 1970 (Warner 1977). These social forces served to increase rates of

cessation generally in the population, as observed in the data from this

study. 

We therefore conclude that there is evidence of hardening within the

CPS I data in the differential rates of quitting related to CPD and in the

increasing mean CPD observed during the study. However, there is also

evidence of general trends toward increased rates of cessation across all CPD

categories, which may be related to the effect of changing public

perceptions in modifying rates of cessation.

These observations were made 30 to 40 years ago, during a period when

the cigarette was changing rapidly in design and major tobacco educational

campaigns were being initiated by many groups. They offer little insight

into whether the current generation of smokers is actually becoming more

resistant to cessation, but they do demonstrate that over a 12-year period,

the relationships between number of cigarettes smoked per day and

smoking abstinence can vary, and that variation raises the possibility that

environmental influences may influence heavy smokers more than light

smokers.

81

Chapter 6

REFERENCES

Federal Trade Commission. Report of Tar and Nicotine

Content of the Smoke of 59 Varieties of Cigarettes.

Washington, DC: Federal Trade Commission,

1967. 

Federal Trade Commission. Report of Tar and Nicotine

Content of the Smoke of 126 Varieties of Cigarettes

[for the year 1968]. Washington, DC: Federal

Trade Commission, 1969.

Federal Trade Commission. Report of Tar and Nicotine

Content of the Smoke of 118 Varieties of Cigarettes.

Washington, DC: Federal Trade Commission,

1969.

Federal Trade Commission. Report of Tar and Nicotine

Content of the Smoke of 120 Varieties of Cigarettes.

Washington, DC: Federal Trade Commission,

1970.

Federal Trade Commission. Report of Tar and Nicotine

Content of the Smoke of 130 Varieties of Cigarettes.

Washington, DC: Federal Trade Commission,

1973.

Garfinkel, L. Selection, Follow-up, and Analysis in the

American Cancer Society Prospective Studies. NCI

Monograph No. 67, 49–52. Bethesda, MD: U.S.

Department of Health and Human Services,

National Cancer Institute, 1985.

Miller, L. M., Monahan, J. The search for “safer”

cigarettes. The Reader’s Digest 1959;38:37–45.

U.S. Department of Health, Education, and Welfare.

Smoking and Health: Report of the Advisory

Committee to the Surgeon General of the Public

Health Service. NIH Pub. No. 00-1103. Rockville,

MD: U.S. Department of Health, Education and

Welfare, Public Health Service, 1964.

Warner, K. E. The effect of the anti-smoking

campaign on cigarette consumption. American

Journal of Public Health 1977;67:645–50.
82

Smoking and Tobacco Control Monograph No. 15
Changes in Number of Cigarettes

Smoked per Day: Cross-Sectional and

Birth Cohort Analyses Using NHIS

David M. Burns, Jacqueline M. Major, Thomas G. Shanks

Smoking norms and behaviors have changed slowly and

incompletely despite growing scientific evidence of adverse health effects

and strong efforts to prevent continuance of tobacco use (U.S. DHHS 2000).

Smoking prevalence has remained stable for much of the last decade,

declining at the end with the increase in cost resulting from the Master

Settlement Agreement (Giovino et al. 1995; Shiffman 1993). Data from the

Current Population Survey (CPS) show a nationwide decline in cessation

activity from 1992 to 1996 (NCI 2000). The question raised in this

monograph is whether those smokers who can easily quit have done so,

leaving behind a group of smokers who are more heavily addicted and more

difficult to get to quit (Hughes 1993). Since smoking a high number of

cigarettes per day is one characteristic of strongly addicted smokers, and

since smoking higher numbers of cigarettes per day reduces the likelihood

of successful cessation, one hallmark of a hardening population of smokers

might be an increase over time in the mean number of cigarettes smoked

per day by those smokers who remain current smokers. 

Data from the series of National Health Interview Surveys (NHIS)

conducted periodically since 1965 are used to examine changes in number

of cigarettes smoked per day reported by smokers over the last four decades.

These trends are examined in the cross-sectional surveys for individual

calendar years. Birth cohort analyses are also constructed using data from all

of the surveys combined in order to examine changes in number of

cigarettes smoked per day by cohorts of smokers born during specified

calendar years as they age. A birth cohort is a group of individuals born

during the same calendar years (10 years in these analyses). 

In a single cross-sectional survey, age-specific rates of smoking behaviors

are often used to examine the changes in smoking behavior with age.

However, the rate of ever-smoking is very different for populations of

individuals born during different periods in the last century (Burns et al.

1997). As a result, individuals of different ages in cross-sectional surveys will

have different rates of ever-smoking. Therefore, comparing the current

smoking prevalence in a cross-sectional survey of smokers at age 30 with

those at age 60 (individuals who had a much higher prevalence of smoking

when they were age 30) will underestimate the impact of age on smoking

INTRODUCTION

83

Chapter 7
cessation. A similar concern exists for describing changes in number of

cigarettes smoked per day, since age is also an important correlate of the

number of cigarettes smoked per day.

This chapter describes changes in the number of cigarettes smoked per

day and examines whether there has been a shift over time in the number

of cigarettes smoked per day using both cross-sectional and birth cohort

analyses. 

The National Center for Health Statistics, through the annual National

Health Interview Survey, has collected health information since 1964

from a probability sample of the civilian, noninstitutionalized

population of the United States. With developmentally consistent

methodology from 1965 onward, smoking supplements to the National

Health Interview Survey were undertaken during the following 20 calendar

years: 1965, 1966, 1970, 1974, 1976, 1977, 1979, 1980, 1983, 1985, 1987,

1988, 1990, 1991, 1992, 1993, 1994, 1995, 1997, and 1998. Sampling

methods for these surveys changed over time. Details concerning the survey

methodology are reported elsewhere (U.S. DHHS 1985; U.S. DHHS 1989). 

The NHIS is a cross-sectional survey of the civilian, noninstitutionalized

U.S. population conducted mostly within households. Surveys prior to 1974

included smoking information on all the adult members of a household

collected from a single adult from that household. However, from 1974

onward, smoking information was collected from a randomly selected

member of the household with the survey undertaken by telephone only

when the person was not present during the initial household interview.

The mean response rate for the 1965 to 1991 NHIS was approximately 85%

(U.S. DHHS 1994). The mean response rates for the 1993 to 1995 surveys

were approximately 81% (CDC 1994; CDC 1996; CDC 1997). Survey

weights were included with each data set. The weights were constructed to

account for the probability that an individual is sampled and to adjust for

nonresponse. 

These analyses are confined to adults aged 20 years and older.

Respondents aged 19 years and younger were excluded from the analysis so

that the age range of the sample would be uniform across all survey years.

Two of the surveys, NHIS 1976 and 1977, interviewed only respondents

aged 20 years and older. To be considered a current smoker, respondents

must have smoked at least 100 cigarettes in their lifetime and smoked at the

time of the survey. The sample sizes varied between 769 and 15,067 adult

current smokers who reported number of cigarettes smoked per day. Of the

20 surveys used, 10 (1979, 1980, 1983, and 1991 to 1998) made a

distinction between daily and occasional smokers when reporting number

of cigarettes smoked per day.

Data gathered from the interviews provided information on

demographics including age, gender, race/ethnicity, and month/year of

birth. The number of cigarettes smoked per day (CPD) was obtained as a

continuous measure. For the purpose of cross-sectional prevalence tables,

Measures

METHODS

Data

84

Smoking and Tobacco Control Monograph No. 15
this continuous measure was categorized into the following six groups:

occasional smoker, <1 cigarettes per day, 1 to 4 cigarettes /day, 5 to 14

cigarettes /day, 15 to 24 cigarettes /day, and 25-plus cigarettes per day.

Because not all of the surveys asked about occasional smoking, some

categories were not available in all surveys. The change in definition of

smoking used in the surveys alters the prevalence of smoking reported. In

order to prevent this change in definition from confusing the trends over

time, the tabular presentations of number of cigarettes smoked per day are

shown as a percentage of the entire population as well as a percentage of

current smokers.

The mean CPD was calculated for each survey year after

standardizing each year’s population to the age and race distribution of the

nation as indicated in the 1965 NHIS. The mean CPD for the total

population as well as gender-specific means were calculated. In order to

explore the differences in mean reported number of cigarettes per day

produced by the use of different questions to record smoking intensity, the

gender-specific mean number of cigarettes was calculated both for all

smokers (daily and occasional) and for all daily smokers in the surveys in

which that information was available. Surveys prior to 1991 define current

smokers with the question, “Do you smoke some days, every day, or not at

all?” and later surveys ask, “Do you smoke now?” followed by a question

asking whether the respondent smokes daily or occasionally. 

The cross-sectional change in number of cigarettes smoked per day was

examined by calculating the prevalence of current smokers for six categories

of CPD for each survey year. Because demographics of the population

changed between 1965 and 1998, data from each survey was standardized

according to the age and race distribution as indicated by the 1965 NHIS

using the direct method for weighted prevalence. 

The smoking patterns of heavy smokers are evaluated using 10-year

birth cohorts. For the purpose of this chapter, a heavy smoker is defined as

an individual who smokes 25 or more cigarettes per day. The birth cohort

analyses were restricted to persons born between 1890 and 1969, who were

20 years or older at the time of the survey, and for whom smoking status

could be ascertained. Birth year, which was present for every respondent,

was used to categorize each respondent into one of eight 10-year birth

cohorts (1890 to 1899, 1900 to 1909, 1910 to 1919, 1920 to 1929, 1930 to

1939, 1940 to 1949, 1950 to 1959, and 1960 to 1969). Gender-specific birth

cohort analyses were performed. The percentage of smokers reporting 

25-plus cigarettes per day per birth cohort was calculated for each of the

survey years after adjusting for race. These percentages were plotted by

survey year. A smoothing procedure was then applied to the rates to

minimize the effect of sampling variability. The “Loess” smoother, available

in the statistical software package S-PLUS, is a local regression model that

was set to use a quadratic fit over the span of calendar years (Chambers and

Hastie 1992). The rates were weighted by the denominator sample size at

each specific calendar year. By smoothing, we make the assumption that

changes occurring in the population are continuous. 

Statistical Analyses

85

Chapter 7
The weights of the responses for the above analyses were scaled so that,

after weighting, the number of responses added up to the sample size. The

scaled weight was obtained by dividing each individual’s original weight by

the sum of all the original weights. This quotient was then multiplied by

the total sample size.

The mean number of cigarettes smoked per day reported by

all current smokers, while controlling for age and race, has

changed over time in the NHIS. The mean increased from

1965 to 1980 and then declined significantly through the

late 1990s (Figure 7-1). This trend is evident for both males and females

(Figure 7-2). 

However, much of the decline occurs during the 1990s, and the

definition used to identify a current smoker shifted between the 1990 and

1991 surveys. Participants in the 1965 to 1990 surveys were asked if they

“smoke cigarettes now.” In the 1991 to 1998 surveys, participants were

asked whether they “currently smoke every day, some days, or not at all.”

RESULTS

Average Number of

Cigarettes Per Day

86

Smoking and Tobacco Control Monograph No. 15

Figure 7-1

Mean Number of Cigarettes per Day* for All Current Smokers in Each NHIS Survey

Year

*Average number of cigarettes per day standardized to the age and race distribution of NHIS 1965. Brackets indicate 9% confidence

intervals on the estimates. Mean Cigarettes per Day

Year

10

12

14

16

18

20

22

24

26

1966 1970 1974 1978 1982 1986 1990 1994 1998

95% CI
This change in definition increases the prevalence of current smokers,

largely by increasing the number of individuals who report smoking

occasionally. This increase in occasional smokers would be expected to have

a substantial effect on the mean number of cigarettes smoked since the

mean is calculated across all current smokers, including those who report

smoking only occasionally. 

Tables 7-1 through 7-3 present the percentages of current smokers who

smoke different numbers of cigarettes per day. It is clear from the table that

a substantial proportion of current smokers using the new definition are

classified as occasional smokers, and that fraction has been increasing

during the decade of the 1990s. The current percentage of occasional

smokers is more than twice the percentage estimated in the 1979 to 1983

surveys, but it is not clear whether this difference is due to the difference in

the question used to define current smokers or due to trends over time in

the frequency of occasional smoking. However, there appears to be a trend

toward an increasing percentage of occasional smoking after 1991, and the

87

Chapter 7

Figure 7-2

Mean Number of Cigarettes per Day* for All Current Smokers in Each NHIS Survey

Year

*Average number of cigarettes per day standardized to the age and race distribution of NHIS 1965. Brackets indicate 9% confidence

intervals on the estimates. Mean Cigarettes per Day

Year

10

12

14

16

18

20

22

24

26

1966 1970 1974 1978 1982 1986 1990 1994 1998

Men

Women

95% CI
definition used to classify current smokers was consistent through this series

of NHIS.

In order to minimize the effect both of the change in definition of

current smoking and of the trend toward a higher prevalence of occasional

smoking on the distribution of number of cigarettes smoked per day, we

examine the change in mean number of cigarettes smoked per day among

only those who report smoking every day for the NHIS years in which that

question was asked. Figure 7-3 presents data for male and female smokers.

There is no clear decline over time in number of cigarettes smoked per day

in this figure. Since it is difficult to characterize as hardened smokers those

who do not smoke every day, the group for whom a change over time in

number of cigarettes smoked per day is most relevant as a measure of

hardening is daily smokers.

88

Smoking and Tobacco Control Monograph No. 15

Table 7-1

Cross-Sectional Number of Cigarettes Smoked per Day for Current Smokers by Year

Cigarettes per Day

Occasional < 1 1 to 4 5 to 14 15 to 24 25+

NHIS (%) CI (%) CI (%) CI (%) CI (%) CI (%) CI Population Sample

1965 * * 1.7 0.14 8.4 0.29 24.7 0.46 44.6 0.53 20.6 0.43 47,020,967 34,298

1966 * * 2.1 0.15 7.8 0.28 23.6 0.45 45.1 0.53 21.5 0.43 48,003,483 34,455

1970 * * 0.6 0.09 7.0 0.31 22.6 0.51 42.9 0.59 23.7 0.51 44,567,267 25,706

1974 * * * * 7.1 0.56 22.5 0.91 43.2 1.07 26.5 0.94 46,295,102 8,198

1976 * * * * 7.6 0.59 21.5 0.92 43.8 1.10 25.9 0.96 45,456,439 7,678

1977 * * 0.4 0.14 6.7 0.58 22.0 0.96 43.0 1.13 27.1 1.01 44,616,055 7,272

1979 6.6 0.55 0.3 0.11 5.4 0.50 19.3 0.88 39.6 1.07 27.3 0.96 47,662,861 7,457

1980 6.3 0.81 0.3 0.19 5.4 0.76 18.8 1.32 39.5 1.63 28.4 1.49 48,847,313 3,237

1983 1.6 0.30 0.1 0.08 5.0 0.53 21.3 0.99 44.0 1.18 27.6 1.05 50,319,264 6,652

1985 * * 1.6 0.25 5.7 0.47 22.1 0.83 41.8 0.97 28.1 0.88 48,370,474 9,725

1987 * * 1.7 0.32 5.9 0.60 22.7 1.06 41.8 1.23 27.4 1.10 47,724,640 6,134

1988 * * 1.5 0.22 4.9 0.40 21.9 0.75 43.1 0.88 26.7 0.78 46,944,920 11,936

1990 * * 1.7 0.25 6.9 0.50 24.1 0.83 42.8 0.96 24.2 0.82 44,202,813 10,243

1991 13.3 0.64 * * 2.9 0.32 18.7 0.74 41.7 0.92 22.7 0.77 44,155,778 10,800

1992 14.6 1.27 * * 3.0 0.62 19.5 1.43 39.5 1.72 23.1 1.47 45,969,845 2,994

1993 17.9 1.05 * * 2.5 0.45 19.5 1.10 39.7 1.34 19.7 1.07 43,083,427 4,920

1994 17.0 1.07 * * 2.4 0.44 21.1 1.16 40.2 1.37 18.4 1.06 45,441,782 4,766

1995 18.0 1.18 * * 2.3 0.46 19.9 1.22 38.4 1.47 20.7 1.21 44,468,861 4,064

1997 17.2 0.81 * * 2.7 0.36 21.4 0.88 39.0 1.02 19.2 0.81 45,541,495 8,538

1998 16.9 0.85 * * 3.7 0.44 21.4 0.94 38.9 1.10 18.5 0.86 44,527,060 7,420

*Information not available.

NOTE: Percents are standardized to the age and race distribution of the nation as indicated by NHIS 1965.
The percentage of current smokers who reported

smoking different numbers of cigarettes per day

is presented in Tables 7-1 through 7-3 for each of

the NHIS where the data were available, and the data are presented in the

format in which the data was collected; that is, some of the surveys in

which current smoking was defined by the question “Do you smoke now?”

also asked a question of those who responded “yes” as to whether they

smoke daily or occasionally. The percentage of smokers who reported

smoking 25 or more cigarettes per day increased from the first survey in

1965 and peaked in 1980. Between 1980 and 1990, there was a decline in

the prevalence of heavy smoking, which accelerated with the change in

definition in 1991.

In order to minimize the effects of the change in definition and the

trend toward an increased prevalence of occasional smoking, Tables 7-4

through 7-6 present the data as percentages of the entire population rather

than as percentages of current smokers. The percentage of the entire

Distribution of Number of

Cigarettes Smoked per Day in

the Population 1965 to 1998

89

Chapter 7

Table 7-2

Cross-Sectional Number of Cigarettes Smoked per Day for Male Smokers by Year

Cigarettes per Day

Occasional < 1 1 to 4 5 to 14 15 to 24 25+

NHIS (%) CI (%) CI (%) CI (%) CI (%) CI (%) CI Population Sample

1965 * * 1.4 0.16 6.7 0.35 20.2 0.56 46.3 0.70 25.4 0.61 27,001,634 19,518

1966 * * 1.8 0.18 6.3 0.34 19.5 0.55 46.6 0.70 25.9 0.61 27,538,859 19,661

1970 * * 0.5 0.11 5.9 0.38 18.7 0.64 43.0 0.81 28.0 0.73 24,318,169 13,912

1974 * * * * 6.0 0.72 17.8 1.17 42.9 1.49 32.7 1.40 24,453,968 4,225

1976 * * * * 6.4 0.76 16.9 1.18 44.0 1.54 31.6 1.43 23,489,129 3,950

1977 * * 0.2 0.14 5.4 0.74 17.8 1.26 41.7 1.60 33.7 1.52 22,516,926 3,617

1979 6.7 0.77 0.2 0.14 5.3 0.69 16.2 1.15 38.3 1.49 31.9 1.42 25,323,489 3,776

1980 6.8 1.16 0.3 0.26 4.6 0.97 15.2 1.70 38.8 2.26 32.5 2.16 26,077,192 1,650

1983 1.5 0.42 0.2 0.13 4.1 0.71 17.2 1.34 42.7 1.72 34.0 1.62 26,110,678 3,141

1985 * * 1.3 0.34 5.0 0.65 18.1 1.15 40.7 1.44 34.1 1.37 24,792,850 4,451

1987 * * 1.6 0.49 5.6 0.86 18.8 1.48 40.4 1.82 33.0 1.72 24,629,866 2,778

1988 * * 1.4 0.32 4.0 0.53 19.0 1.04 41.8 1.29 31.8 1.20 24,446,987 5,552

1990 * * 1.6 0.37 6.4 0.71 19.0 1.14 41.9 1.40 30.7 1.29 23,356,894 4,767

1991 12.8 0.94 * * 3.0 0.48 15.0 1.01 40.3 1.35 28.4 1.22 22,977,773 4,987

1992 14.9 1.90 * * 2.6 0.87 14.1 1.89 38.3 2.53 29.8 2.33 23,244,280 1,383

1993 18.9 1.58 * * 2.0 0.60 15.2 1.49 37.8 1.94 25.4 1.70 22,668,556 2,294

1994 17.1 1.60 * * 2.4 0.63 16.5 1.56 39.9 2.01 23.1 1.70 23,971,556 2,210

1995 17.2 1.70 * * 2.2 0.66 15.1 1.60 37.6 2.13 27.0 1.92 23,198,580 1,937

1997 16.8 1.15 * * 2.5 0.49 16.7 1.15 40.1 1.47 23.4 1.24 24,406,479 4,191

1998 17.2 1.24 * * 3.2 0.59 16.5 1.23 38.2 1.56 24.2 1.35 23,388,276 3,629

*Information not available.

NOTE: Percents are standardized to the age and race distribution of the nation as indicated by NHIS 1965.
population who reported smoking 25 or more cigarettes per day also peaked

in 1980 and then declined. There is also a statistically significant decline in

the prevalence of heavy smoking from 1991 through 1998, a period during

which the new definition of current smoking was consistently used. This

trend toward fewer heavy smokers is accompanied by an increase in the

prevalence of smoking 5 to 14 cigarettes per day. 

There is no dramatic shift in the percentage of the population reporting

smoking 25 or more cigarettes per day between the pre-1990 period during

which the old definition was in use and the post-1991 period during which

the new definition was in use. This suggests that the trends in prevalence of

heavy smoking were not influenced by the definition of current smoking

used in the individual NHIS. 

In summary, the cross-sectional evaluation of the NHIS data suggests

that between 1965 and 1980, there was a trend toward an increasing

number of cigarettes smoked per day and a higher prevalence of heavy

smoking. Since that time, however, the prevalence of heavy smoking has

90

Smoking and Tobacco Control Monograph No. 15

Table 7-3

Cross-Sectional Number of Cigarettes Smoked per Day for Female Smokers by Year

Cigarettes per Day

Occasional < 1 1 to 4 5 to 14 15 to 24 25+

NHIS (%) CI (%) CI (%) CI (%) CI (%) CI (%) CI Population Sample

1965 * * 2.1 0.23 10.8 0.50 30.8 0.74 42.2 0.80 14.2 0.56 20,019,333 14,780

1966 * * 2.5 0.25 9.8 0.48 29.0 0.73 43.1 0.80 15.5 0.58 20,464,624 14,794

1970 * * 0.8 0.16 8.5 0.50 27.5 0.80 42.5 0.88 18.5 0.69 20,249,098 11,794

1974 * * * * 8.3 0.87 27.7 1.40 43.6 1.53 19.8 1.22 21,841,134 3,973

1976 * * * * 8.7 0.91 26.2 1.41 43.6 1.58 20.0 1.26 21,967,310 3,728

1977 * * 0.5 0.23 7.9 0.89 26.2 1.44 44.4 1.60 20.3 1.28 22,099,129 3,655

1979 6.7 0.77 0.4 0.18 5.5 0.73 22.9 1.33 41.4 1.53 22.0 1.27 22,339,372 3,681

1980 6.8 1.16 0.3 0.26 6.3 1.20 22.4 2.04 40.3 2.34 23.8 2.00 22,770,121 1,587

1983 1.5 0.42 0.1 0.10 6.0 0.80 25.6 1.45 45.5 1.63 20.8 1.30 24,208,586 3,511

1985 * * 1.9 0.37 6.4 0.67 26.2 1.20 42.8 1.33 22.0 1.09 23,577,624 5,274

1987 * * 1.6 0.43 6.1 0.83 26.8 1.51 43.4 1.67 21.4 1.36 23,094,774 3,356

1988 * * 1.7 0.31 5.8 0.59 25.0 1.07 44.7 1.21 21.2 0.98 22,497,933 6,384

1990 * * 1.8 0.35 7.4 0.71 29.5 1.21 43.8 1.31 17.3 0.99 20,845,919 5,476

1991 12.8 0.94 * * 2.8 0.44 22.7 1.08 43.3 1.26 16.8 0.94 21,178,005 5,813

1992 14.9 1.90 * * 3.5 0.89 25.2 2.11 40.1 2.36 16.6 1.78 22,725,565 1,611

1993 18.9 1.58 * * 3.3 0.68 24.2 1.61 41.5 1.84 13.6 1.26 20,414,871 2,626

1994 17.1 1.60 * * 2.4 0.61 26.3 1.70 40.8 1.87 13.2 1.27 21,470,226 2,556

1995 17.2 1.70 * * 2.4 0.65 25.5 1.83 39.1 2.04 14.2 1.45 21,270,281 2,127

1997 16.8 1.15 * * 3.0 0.53 26.8 1.32 37.8 1.42 14.5 1.01 21,135,016 4,347

1998 17.2 1.24 * * 4.1 0.65 26.6 1.41 39.9 1.54 12.6 1.03 21,138,784 3,791

*Information not available.

NOTE: Percents are standardized to the age and race distribution of the nation as indicated by NHIS 1965.
fallen substantially and has continued to fall through the decade of the

1990s. This fall in heavy smokers is similar in proportion to the fall in

prevalence of daily smoking over this same period, but the accompanying

trend of an increasing prevalence of smoking 5 to 14 cigarettes per day

suggests a general shift toward lighter smoking among daily smokers during

the 1990s. These data do not suggest that the remaining current smokers are

a heavier-smoking population. There is no suggestion that the residual

population of smokers has become hardened over the last 15 years, at least

for number of cigarettes smoked per day as a measure of hardening. 

91

Chapter 7 Mean Cigarettes per Day

Year

10

12

14

16

18

20

22

24

26

1966 1970 1974 1978 1982 1986 1990 1994 1998

Men

Women

95% CI

Figure 7-3

Mean Number of Cigarettes Smoked per Day* Reported by Daily Cigarette Smokers in

Each NHIS Survey Year

*Average number of cigarettes per day standardized to the age and race distribution of NHIS 1965. 

NOTE: Includes only those surveys that distinguished daily from occasional smokers. Brackets indicate 9% confidence intervals on

the estimates.
Since the NHIS records date of birth in all survey

years, it is possible to assemble the smoking

prevalence data by the year in which individuals

were born as opposed to their age at the time of survey. It is then possible to

examine the changes in smoking behavior for repetitive cross-sectional

samples of 10-year birth cohorts of individuals as they advance in age

through the sequential series of the NHIS from 1965 to 1998. Since eversmoking prevalence has varied from 70% to 80% among men born between

the years 1910 and 1929 to 45% or less among those born after 1960 (Burns

et al. 1997), examining changes in smoking behavior by birth cohort gives a

more valid description of the changes in smoking prevalence occurring with

age, and over time, than does cross-sectional data presented as age-specific

analyses.

Birth Cohort Analyses of the

Prevalence of Smoking 25

Or More Cigarettes Per Day

92

Smoking and Tobacco Control Monograph No. 15

Table 7-4

Cross-Sectional Number of Cigarettes Smoked per Day for the Total U.S. Population

by Year

Cigarettes per Day

Occasional < 1 1 to 4 5 to 14 15 to 24 25+

NHIS (%) CI (%) CI (%) CI (%) CI (%) CI (%) CI Population Sample

1965 * * 0.7 0.06 3.6 0.13 10.4 0.21 18.8 0.27 8.7 0.19 111,604,002 81,436

1966 * * 0.9 0.06 3.3 0.12 10.1 0.21 19.3 0.27 9.2 0.20 112,594,597 81,081

1970 * * 0.2 0.04 2.7 0.12 8.6 0.21 16.2 0.27 9.0 0.21 121,729,938 70,136

1974 * * * * 2.7 0.21 8.5 0.37 16.1 0.48 9.9 0.39 125,080,937 22,280

1976 * * * * 2.8 0.22 7.9 0.37 16.1 0.49 9.5 0.39 126,397,470 21,250

1977 * * 0.1 0.05 2.4 0.21 8.0 0.38 15.5 0.50 9.8 0.40 124,968,643 20,440

1979 2.4 0.20 0.1 0.04 1.9 0.18 6.9 0.33 14.1 0.45 9.7 0.38 144,538,295 22,750

1980 2.3 0.29 0.1 0.07 1.9 0.27 6.7 0.50 14.0 0.68 10.1 0.58 147,895,036 9,912

1983 0.5 0.10 0.0 0.03 1.7 0.17 7.0 0.35 14.2 0.47 8.9 0.37 158,654,252 21,420

1985 * * 0.5 0.08 1.8 0.15 6.8 0.28 12.7 0.36 8.5 0.30 160,299,371 31,858

1987 * * 0.5 0.10 1.7 0.18 6.7 0.35 12.4 0.45 8.1 0.36 163,376,109 20,778

1988 * * 0.4 0.06 1.4 0.12 6.3 0.23 12.2 0.31 7.6 0.25 168,456,196 42,439

1990 * * 0.4 0.07 1.8 0.13 6.2 0.24 11.1 0.31 6.3 0.23 172,274,935 39,464

1991 3.4 0.18 * * 0.8 0.08 4.8 0.21 10.8 0.29 5.9 0.22 173,611,554 41,961

1992 3.8 0.36 * * 0.8 0.17 5.3 0.41 10.6 0.55 6.2 0.43 176,871,804 11,564

1993 4.5 0.29 * * 0.6 0.11 4.9 0.30 10.1 0.41 5.0 0.29 179,189,372 20,274

1994 4.4 0.30 * * 0.6 0.11 5.5 0.33 10.5 0.43 4.7 0.29 180,952,643 19,057

1995 4.4 0.32 * * 0.6 0.12 5.0 0.33 9.7 0.44 5.3 0.33 182,986,412 16,736

1997 4.3 0.22 * * 0.7 0.09 5.4 0.24 9.9 0.31 4.8 0.22 186,456,771 34,889

1998 4.2 0.22 * * 0.9 0.11 5.3 0.25 9.6 0.32 4.6 0.22 187,965,272 31,360

*Information not available.

NOTE: Percents are standardized to the age and race distribution of the nation as indicated by NHIS 1965.
Figure 7-4 demonstrates the relationship between number of cigarettes

smoked per day and age. This 10-year birth cohort (born between 1930 and

1939) has been adjusted for race and shows that the number of cigarettes

smoked per day increases with age to midlife and then declines with

advancing age. This pattern is consistent across multiple cohorts and is

therefore not simply a function of calendar-year effects influencing the 1930

to 1939 cohort. 

The percentage of current smokers in the birth cohort smoking 25-plus

cigarettes per day is presented by survey year for males and females in

Figures 7-5/7-6 and 7-6/7-7, respectively. The oldest male cohorts (Figure

7-5) show a steady decline in percentage of heavy smokers, as expected

given their advanced age at the time of the first survey. The more recent

cohorts show a percentage of heavy smoking that increases at younger ages

and then either declines or levels off at a constant percentage. None of the

cohorts shows an increase in the fraction of current male smokers who

smoked 25-plus CPD during the 1990s. 

93

Chapter 7

Table 7-5

Cross-Sectional Number of Cigarettes Smoked per Day for Male Population by Year

Cigarettes per Day

Occasional < 1 1 to 4 5 to 14 15 to 24 25+

NHIS (%) CI (%) CI (%) CI (%) CI (%) CI (%) CI Population Sample

1965 * * 0.7 0.08 3.5 0.18 10.4 0.31 23.9 0.43 13.1 0.34 52,341,553 37,819

1966 * * 0.9 0.10 3.3 0.18 10.2 0.31 24.5 0.43 13.6 0.35 52,524,255 37,560

1970 * * 0.2 0.05 2.6 0.17 8.3 0.30 19.2 0.43 12.5 0.36 56,742,829 32,440

1974 * * * * 2.6 0.32 7.8 0.54 18.6 0.77 14.2 0.68 56,695,042 9,828

1976 * * * * 2.7 0.33 7.1 0.52 18.5 0.78 13.2 0.67 56,683,201 9,499

1977 * * 0.1 0.06 2.2 0.31 7.3 0.54 17.1 0.78 13.8 0.70 55,695,105 9,017

1979 2.7 0.31 0.1 0.05 2.1 0.28 6.5 0.49 15.3 0.70 12.9 0.64 67,932,678 10,214

1980 2.7 0.48 0.1 0.11 1.9 0.40 6.1 0.72 15.6 1.07 13.3 0.98 69,634,859 4,455

1983 0.5 0.15 0.1 0.05 1.5 0.25 6.1 0.51 15.1 0.74 12.1 0.66 74,458,847 9,127

1985 * * 0.4 0.11 1.6 0.22 6.0 0.41 13.4 0.58 11.2 0.53 75,399,614 13,373

1987 * * 0.5 0.16 1.8 0.28 6.1 0.52 13.0 0.71 10.7 0.64 77,044,177 8,580

1988 * * 0.4 0.10 1.2 0.17 5.9 0.36 12.9 0.50 9.9 0.43 79,676,062 17,751

1990 * * 0.5 0.11 1.8 0.21 5.4 0.36 12.0 0.50 8.8 0.42 81,544,750 16,373

1991 3.6 0.28 * * 0.8 0.14 4.2 0.31 11.3 0.47 8.0 0.39 82,230,069 17,510

1992 4.1 0.58 * * 0.7 0.25 4.0 0.57 10.9 0.87 8.3 0.75 83,848,847 4,914

1993 5.3 0.48 * * 0.6 0.17 4.2 0.44 10.4 0.65 7.0 0.53 85,254,203 8,514

1994 4.9 0.49 * * 0.7 0.18 4.7 0.47 11.3 0.69 6.5 0.53 86,223,037 7,992

1995 4.6 0.50 * * 0.6 0.18 4.1 0.47 10.2 0.70 7.3 0.59 87,274,556 7,214

1997 4.7 0.35 * * 0.7 0.14 4.8 0.35 11.2 0.50 6.4 0.38 89,074,914 14,936

1998 4.6 0.36 * * 0.9 0.16 4.5 0.35 10.2 0.50 6.4 0.40 89,850,921 13,682

*Information not available.

NOTE: Percents are standardized to the age and race distribution of the nation as indicated by NHIS 1965.
Data for females (Figures 7-7/7-8) show lower percentages of female

smokers reporting smoking 25-plus cigarettes per day, particularly for the

older cohorts. In more recent cohorts, the percentages are similar to those

for males. There is no suggestion of an increase in the fraction of females

smoking 25-plus CPD during the 1990s. 

Birth cohort analyses of those smoking 25-plus cigarettes per day as a

percentage of the entire population, as distinct from the analyses as a

percentage of all current smokers, were also conducted. These results are not

shown, as they depict progressive declines in the prevalence of heavy

smoking with advancing survey years. These declines sum up the effects of

smoking cessation, excess mortality, and shifts to lower intensity of smoking

with advancing age, and they offer little insight into whether the residual

population of smokers is hardening.

94

Smoking and Tobacco Control Monograph No. 15

Table 7-6

Cross-Sectional Number of Cigarettes Smoked per Day for Female Population by Year

Cigarettes per Day

Occasional < 1 1 to 4 5 to 14 15 to 24 25+

NHIS (%) CI (%) CI (%) CI (%) CI (%) CI (%) CI Population Sample

1965 * * 0.7 0.08 3.6 0.18 10.4 0.29 14.3 0.33 4.8 0.20 59,262,449 43,617

1966 * * 0.9 0.09 3.4 0.17 9.9 0.28 14.7 0.33 5.3 0.21 60,070,342 43,521

1970 * * 0.3 0.05 2.7 0.17 8.9 0.29 13.6 0.35 5.9 0.24 64,987,109 37,696

1974 * * * * 2.7 0.29 9.2 0.51 14.1 0.61 6.3 0.42 68,385,895 12,452

1976 * * * * 2.9 0.30 8.6 0.51 14.1 0.62 6.4 0.44 69,714,270 11,751

1977 * * 0.2 0.07 2.6 0.29 8.6 0.52 14.3 0.64 6.5 0.44 69,273,538 11,423

1979 2.1 0.25 0.1 0.06 1.8 0.23 7.3 0.46 13.0 0.58 6.9 0.43 76,605,617 12,536

1980 1.8 0.35 0.1 0.08 2.0 0.38 7.2 0.69 12.5 0.87 7.2 0.67 78,260,177 5,457

1983 0.5 0.13 0.0 0.03 1.8 0.24 7.8 0.48 13.5 0.60 6.0 0.41 84,195,405 12,293

1985 * * 0.5 0.11 1.9 0.20 7.5 0.38 12.2 0.47 6.1 0.34 84,899,757 18,485

1987 * * 0.5 0.12 1.7 0.23 7.4 0.47 11.9 0.57 5.9 0.41 86,331,932 12,198

1988 * * 0.4 0.08 1.5 0.16 6.6 0.31 11.7 0.39 5.5 0.28 88,780,134 24,688

1990 * * 0.4 0.08 1.8 0.17 6.9 0.33 10.4 0.39 4.1 0.25 90,730,185 23,091

1991 3.2 0.22 * * 0.7 0.11 5.4 0.29 10.4 0.38 4.1 0.24 91,381,485 24,451

1992 3.6 0.45 * * 0.9 0.23 6.4 0.59 10.4 0.71 4.3 0.47 93,022,957 6,650

1993 3.8 0.35 * * 0.7 0.16 5.6 0.41 9.8 0.53 3.2 0.31 93,935,169 11,760

1994 4.0 0.37 * * 0.6 0.15 6.3 0.45 9.8 0.54 3.1 0.32 94,729,606 11,065

1995 4.3 0.41 * * 0.6 0.15 5.8 0.47 9.2 0.57 3.4 0.35 95,711,856 9,522

1997 4.0 0.27 * * 0.7 0.12 6.11 0.33 8.6 0.38 3.2 0.24 97,381,857 19,953

1998 3.7 0.28 * * 0.9 0.14 6.04 0.35 9.0 0.41 2.9 0.24 98,114,351 17,678

*Information not available.

NOTE: Percents are standardized to the age and race distribution of the nation as indicated by NHIS 1965.
This chapter provides analyses of changes in number of cigarettes

smoked per day from the NHIS conducted between 1965 and 1998. There

has been a substantial fall in smoking prevalence over the last 25 years, but

there is no evidence for a rise in the number of cigarettes smoked per day

over the last 15 years in either cross-sectional analyses or in birth cohort

analyses. The mean number of cigarettes smoked per day and the fraction of

smokers who reported smoking 25-plus cigarettes per day appear to have

declined over the last decade, although at least part of this decline is due to

the increasing percentage of occasional smokers recorded in the surveys

conducted since 1991, when the definition of current smoker was changed

to ask specifically about occasional smoking. 

These data are based on the reported number of cigarettes smoked per

day in surveys, and it is possible that changes in the social acceptability of

smoking over the last several decades have led to an increased

underreporting of the number of cigarettes smoked over the last decade

DISCUSSION

95

Chapter 7

Figure 7-4

Effect of Age on Number of Cigarettes Smoked per Day*

*NHIS percentage of male smokers reporting 25+ cigarettes per day (cohort born 1930–39). Percent

Age

0

10

20

30

40

50

60

25 30 35 40 45 50 55 60 65
(Warner 1978). If this underreporting is becoming more extensive, then the

results of the NHIS would underestimate the actual trends in heavy smoking

in the population. These underestimations could artifactually produce the

declines in heavy smoking observed in the NHIS and could even mask an

increase in the prevalence of heavy smoking if they are severe enough.

However, concordance of the trends in per capita consumption with the

trends observed in the NHIS, the increased prevalence of occasional

smoking, and the decline in per capita consumption in California that is

well in excess of the decline in smoking prevalence all suggest that the

observations described in this chapter reflect real changes in smoking

behavior of the U.S. population.

In summary, analyses of the National Heath Interview Surveys neither

demonstrate a rise in the fraction of the population who are heavy smokers

(i.e., smoking 25-plus CPD) nor suggest that cessation among those who

smoke has increased the mean of number of cigarettes smoked per day in

the national adult smoker population. 

96

Smoking and Tobacco Control Monograph No. 15

Figure 7-5

Birth Cohort-Specific Percentage* of Male Smokers Reporting Smoking 25+ Cigarettes

per Day 1965–1995

*Adjusted by race Percent

Survey Year

0

10

20

30

40

50

60

1960 1965 1970 1975 1980 1985 1990 1995

1920–1929

1910–1919

1900–1909

1890–1899
REFERENCES

Burns, D. M., Lee, L., Shen, Z. et al. Cigarette

Smoking Behavior in the United States. In

Changes in Cigarette-Related Disease Risks and

Their Implication for Prevention and Control.

Smoking and Tobacco Control Monograph No. 8,

edited by D. Burns, L. Garfinkel, J. Samet,

13–112. NIH Pub. No. 97–4213. Bethesda, MD:

U.S. Department of Health and Human Services,

National Cancer Institute, 1997.

Centers for Disease Control and Prevention.

Cigarette smoking among adults—United States,

1993. Morbidity and Mortality Weekly Report

1994;43:925–30.

Centers for Disease Control and Prevention.

Cigarette smoking among adults—United States,

1994. Morbidity and Mortality Weekly Report

1996;45:588–90.

Centers for Disease Control and Prevention.

Cigarette smoking among adults—United States,

1995. Morbidity and Mortality Weekly Report

1997;46:1217–220.

Chambers, J. M., Hastie, T. J., eds. Statistical Models

in S. Pacific Grove, CA: Wadsworth and

Brooks/Cole Advanced Books and Software,

1992.

Giovino, G. A., Henningfield, J. E., Tomar, S. L. et al.

Epidemiology of tobacco use and dependence.

Epidemiologic Reviews 1995;17:48–65.

Hughes, J. R. Pharmacotherapy for smoking

cessation: Unvalidated assumptions, anomalies

and suggestions for further research. Journal of

Consulting and Clinical Psychology

1993;61:751–60.

97

Chapter 7

Figure 7-6

Birth Cohort-Specific Percentage* of Male Smokers Reporting Smoking 25+ Cigarettes

per Day 1965–1995

*Adjusted by race Percent

Survey Year

0

10

20

30

40

50

60

1960 1965 1970 1975 1980 1985 1990 1995

1930–1939

1940–1949

1950–1959

1960–1969
National Cancer Institute. Population-Based Smoking

Cessation: What Works. Smoking and Tobacco

Control Monograph No. 12, edited by D. Burns, 

D. Shopland. NIH Pub. No. 00-4892. Bethesda,

MD: U.S. Department of Health and Human

Services, National Cancer Institute, 2000.

Shiffman, S. Smoking cessation treatment: Any

progress? Journal of Consulting and Clinical

Psychology 1993;61:718–22.

U.S. Department of Health and Human Services.

Design and Estimation for the National Health

Interview Survey, 1985–94. Hyattsville, MD:

National Center for Health Statistics, Public

Health Service, 1989.

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

National Health Interview Survey Design, 1973–84,

and Procedures, 1975–83. Hyattsville, MD: U.S.

Department of Health and Human Services,

Public Health Service, 1985.

U.S. Department of Health and Human Services.

Preventing Tobacco Use Among Young People: A

Report of the Surgeon General, 1994. Atlanta, GA:

U.S. Department 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,

1994.

98

Smoking and Tobacco Control Monograph No. 15

Figure 7-7

Birth Cohort-Specific Percentage* of Female Smokers Reporting Smoking 25+

Cigarettes per Day 1965–1995

*Adjusted by race Percent

Survey Year

0

10

20

30

40

50

60

1960 1965 1970 1975 1980 1985 1990 1995

1920–1929

1910–1919

1900–1909

1890–1899
U.S. Department of Health and Human Services.

Reducing Tobacco Use: A Report of the Surgeon

General. Atlanta, GA: 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,

2000.

Warner, K. E. Possible increases in the

underreporting of cigarette consumption. Journal

of the American Statistical Association

1978;73:314–18.

99

Chapter 7

Figure 7-8

Birth Cohort-Specific Percentage* of Female Smokers Reporting Smoking 25+

Cigarettes per Day 1965–1995

*Adjusted by race Percent

Survey Year

0

10

20

30

40

50

60

1960 1965 1970 1975 1980 1985 1990 1995

1930–1939

1940–1949 1950–1959 1960–1969
100

Smoking and Tobacco Control Monograph No. 15
Changes in Cross-Sectional Measures of

Cessation, Numbers of Cigarettes

Smoked per Day, and Time to First

Cigarette—California and National

Data

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

Jerry W. Vaughn

Per capita consumption of cigarettes and smoking prevalence

have been declining since the 1960s (U.S. DHHS 2000), but trends in these

measures ceased to decline and became flat during the mid-1990s. These

observations suggest that smoking cessation rates may also have fallen

because those who could easily quit may have done so and left behind a

more-addicted and hardened target population of smokers.

This chapter presents the decline in national cessation rates observed

between the 1992/93 and 1995/96 Current Population Surveys (CPS) and

explores whether these declines in cessation are accompanied by changes in

smoking behavior or in the pattern of cessation activity consistent with

hardening of the residual smoking population. Data from the 1990, 1996,

and 1999 California Tobacco Surveys (CTS) are also examined. California

has experienced a decline in both per capita consumption and prevalence

over the last decade well in excess of that seen nationally (Gilpin et al.

2001). If a hardened population of residual smokers is developing because

those who could be induced to quit using current tobacco control strategies

have already quit, then it might be most evident in California where the

largest gains in reducing smoking with current tobacco control approaches

have occurred. Changes in cessation, number of cigarettes smoked per day,

and time to first cigarette (a measure of addiction) occurring between 1990

and 1999 in California are explored for evidence of hardening.

One of the clearest measures of change in smoking

behavior is the per capita consumption of cigarettes.

Figure 8-1 presents the U.S. per capita consumption

from 1950 to 2000. It shows a progressive decline

from 1974 through the early 1990s. However, between 1993 and 1996, there

was very little change in per capita consumption, and the total

consumption of cigarettes was also essentially unchanged. This flattening in

the per capita consumption trend is one of the lines of evidence raising

concerns that smokers are becoming unresponsive to existing tobacco

CHANGES IN NATIONAL

CESSATION RATES AND

NUMBER OF CIGARETTES

SMOKED PER DAY

INTRODUCTION

101

Chapter 8
control approaches. However, following the Master Settlement Agreement

(MSA) of the state attorneys general’s litigation against the tobacco

companies in 1998, and the subsequent substantial increase in the cost of

cigarettes, per capita consumption declined steeply. This suggests that, at

least as far as cost as a tobacco control intervention is concerned, the

population of smokers in 1997 remained responsive to environmental

measures previously shown to alter smoking behavior.

CPS data for the years 1992/93, 1995/96, and 1998/99 are used to

examine changes in cessation and number of cigarettes smoked per day in

order to determine whether the per capita consumption changes are

consistent with a hardening of the residual smoking population as cessation

activity fell between the 1992/93 and 1995/96 surveys. The measures of

cessation used for the CPS are based on the changes in smoking behavior

reported during the 12 months prior to the survey, and they allow changes

in the level of cessation activity in the year prior to each survey to be

compared. 

The cessation measures are calculated using the current smoking status

reported by those who were daily smokers one year prior to the survey and

who were age 25 or older at the time of the survey. Those smokers could be

current daily smokers who had not made a quit attempt, current daily

smokers who had made a quit attempt and failed, current occasional

smokers, or former smokers. Former smokers were divided into those who

had quit for less than 3 months and those who had quit for 3 or more

months at the time of the survey. In addition, current daily smokers who

had made a quit attempt and occasional smokers were combined into a

single measure of those who had made a change in their smoking behavior

short of cessation in the prior year. A more detailed description of this

measure is presented elsewhere (Burns et al. 2000).

There was a small but statistically significant decline in the prevalence

of smoking among self-respondents who were age 25 or older between the

1992/93 and 1995/96 CPS. The percentage declined from 20.06 ± 0.28%

daily and 4.26 ± 0.11% occasional smokers in 1992/93 to 19.23 ± 0.23%

daily and 3.99 ± 0.11% occasional smokers in 1995/96. However, the

percentage of the population reporting that they were former smokers did

not increase and actually declined slightly between the two surveys, from

25.99 ± 0.23% to 24.95 ± 0.23%. This suggests that the fall in prevalence

between the two surveys may not be the result of increased cessation. 

The measures of cessation for the surveys are presented in Table 8-1. The

percentage of those who were daily smokers one year prior to the survey

who had not made a quit attempt during that year rose between the

1992/93 CPS and the 1995/96 CPS. The percentage who had quit at the time

of the survey or who had quit for 3 or more months at the time of the

survey fell. Each of these changes was statistically significant, and a multiple

logistic regression analysis demonstrated that the differences across surveys

persisted when gender, age, education, income, and number of cigarettes

smoked per day were entered into the regression (Burns et al. 2000).

102

Smoking and Tobacco Control Monograph No. 15
These data from the CPS are consistent with changes in per capita

consumption over the same period. They suggest that cessation activity and

success fell during the mid-1990s and contributed to the absence of a

decline in consumption during those years. 

Cessation rates vary over time (Burns et al. 1997), both increasing and

decreasing, and it is possible that the decline observed in the 1995/95 CPS

was one of these variations. Data from the 1998/99 CPS show that the

fraction of daily smokers one year prior to the survey who had not made

any change in their cessation behavior fell to 63.17%, a level similar to that

reported in the 1992/93 survey. In addition, the fraction of smokers who

were successfully abstinent at the time of the survey or who had been

abstinent for 3 or more months increased significantly between the 1995/96

and 1998/99 surveys. A rapid increase in cigarette cost occurred due to the

Master Settlement Agreement in November of 1998, and this increase

almost certainly contributed to the increase in cessation activity recorded in

the 1998/99 CPS. However, the 1998/99 data were collected in September

1998, January 1999, and May 1999; and the September 1998 survey was

conducted prior to the settlement and subsequent price increase. Therefore,

cessation behavior reported in the September 1998 survey would represent

103

Chapter 8

Figure 8-1

Per Capita Consumption of Cigarettes in the U.S.A., 1950–2000 Per Capita Consumption (Cigarettes per Year, Age 18+)

Year

0

1000

2000

3000

4000

5000

6000

7000

1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000
104

Smoking and Tobacco Control Monograph No. 15

Table 8-1Current Smoking Status Among Those Who Were Daily Smokers 1 Year Prior to the Survey and Who Were Age 25 or Older;Self-Respondents Only

Daily Smokers Former Smokers

No Quit Attempts Quit Attempts Occasional Quit <3 Months Quit 3+ Months Sample

Survey Years % ±95% CI % ±95% CI % ±95% CI % ±95% CI % ±95% CI Size1992/93

Total 63.59 (0.60) 25.90 (0.63) 3.05 (0,.22) 2.41 (0.19) 5.06 (0.28) 38,283Male 64.54 (0.84) 25.25 (0.82) 2.67 (0.30) 2.56 (0.30) 4.98 (0.44) 18,247Female 62.51 (0.73) 26.63 (0.77) 3.48 (0.30) 2.23 (0.22) 5.14 (0.33) 20,036

1995/96

Total 67.89 (0.63) 23.51 (0.62) 2.93 (0.19) 1.97 (0.18) 3.69 (0.25) 30,606Male 68.37 (0.86) 23.02 (0.83) 2.72 (0.25) 2.11 (0.25) 3.79 (0.33) 14,322Female 67.36 (0.74) 24.05 (0.74) 3.18 (0.29) 1.83 (0.24) 3.58 (0.30) 16,284

1998/99

Total 63.20 (0.60) 25.60 (0.60) 3.40 (0.20) 2.80 (0.20) 5.00 (0.30) 26,989Male 63.40 (0.90) 25.40 (0.80) 3.30 (0.30) 2.90 (0.30) 5.00 (0.40) 12,890

Female 62.90 (1.00) 25.80 (0.90) 3.60 (0.40) 2.70 (0.30) 4.90 (0.40) 14,099TotalSeptember 1998 63.70 (1.10) 26.70 (1.00) 2.90 (0.40) 1.80 (0.30) 4.90 (0.50) 9,614January 1999 62.80 (1.10) 24.10 (1.00) 4.20 (0.40) 4.40 (0.50) 4.50 (0.50) 8,984May 1999 63.20 (1.10) 26.00 (1.00) 3.20 (0.40) 2.10 (0.30) 5.50 (0.50) 8,391

Source: CPS 1992/93, 1995/96, 1998/99.
behavior not influenced by the cost increase, and the cessation measures for

the September 1998 survey show an increase in cessation compared with

the 1995/96 CPS. This suggests that the increased cessation activity observed

between the 1995/96 and 1998/99 CPS occurred prior to, and was the result

of factors other than, the increase in cost following the MSA. 

It is possible that the increase in cessation observed by the 1998/99 CPS

was transient and that cessation rates will fall again in the future. However,

per capita consumption fell substantially during the two years following the

MSA, suggesting that the effects on smoking behavior continued and that,

at least in regard to cost as an intervention, the residual population of

smokers did respond to the temporal changes.

In order to examine whether the decline in cessation rates observed

between the 1992/93 and 1995/96 CPS is consistent with hardening, Table

8-2 presents the shift between the two surveys in self-reported number of

cigarettes smoked per day. In contrast to what might have been expected if

the decline in cessation was the result of hardening of the residual

population of smokers, the fraction of smokers who smoked 25 or more

cigarettes per day did not increase. It declined nonsignificantly from 20.80%

to 20.25%. The percentage of smokers smoking 15 to 24 cigarettes per day

also remained constant. 

Multiple logistic regression analyses were performed independently for

each of the measures of cessation described above in the 1992/93 and

1995/96 CPS with gender, age, race/ethnicity, education, income, and

cigarettes smoked per day (CPD) included in the regression (Tables 8-1 and

8-2) (Burns et al. 2000). The odds ratios for making a cessation attempt

declined with increasing amount smoked in both surveys. The odds ratio for

having successfully quit at the time of the survey also was lower for those

who had smoked 5-plus CPD compared with those who had smoked 1 to 4

CPD, but there was no clear decline in cessation success with increasing

number of cigarettes smoked per day for amounts above 5 CPD. However,

the likelihood of making a cessation attempt and the difficulty in achieving

cessation did not change between the two surveys for those smokers who

smoked 25-plus CPD, at least as measured by the magnitude of the odds

ratios. There was no significant difference between the two surveys in the

odds ratio for making a cessation attempt or for achieving successful

cessation of any duration among those who smoked 25-plus CPD compared

with those who smoked 1 to 4 CPD, suggesting that the decrease in quitting

seen between the 1992/93 and 1995/96 CPS was not greater for heavy

smokers. Thus the proportion of heavy smokers in the population did not

increase as cessation fell, and those smokers who were left behind as heavy

smokers when their peers quit did not appear to have a greater fall between

the two surveys in cessation activity or success than lighter smokers.

An alternate mode of hardening over this period is also examined in the

same multiple logistic regressions (Tables 8-1 and 8-2). If those who

successfully quit leave behind a more resistant population of smokers, then

the fall in cessation rates should be greatest among those demographic

groups in which the most cessation has occurred. In multivariate logistic

105

Chapter 8
106

Smoking and Tobacco Control Monograph No. 15

Table 8-2Number of Cigarettes Smoked per Day Among Current Smokers 25 Years and Older; Self-Respondents Only, National Data

Occasional Cigarettes per Day

Smokers 1–4 5–14 15–24 25+ Sample

Survey Years % ±95% CI % ±95% CI % ±95% CI % ±95% CI % ±95% CI Size1992/93

Total 17.65 (0.45) 2.39 (0.17) 19.19 (0.46) 39.96 (0.58) 20.80 (0.38) 48,915Male 17.41 (0.65) 2.25 (0.27) 15.41 (0.55) 39.06 (0.77) 25.87 (0.58) 22,914Female 17.92 (0.52) 2.55 (0.23) 23.34 (0.64) 40.95 (0.76) 15.24 (0.41) 26,001

1995/96

Total 17.31 (0.42) 2.59 (0.17) 19.77 (0.53) 40.08 (0.64) 20.25 (0.50) 38,817Male 17.30 (0.62) 2.36 (0.24) 15.47 (0.67) 39.89 (0.93) 24.98 (0.74) 17,943

Female 17.33 (0.55) 2.85 (0.25) 24.50 (0.71) 40.28 (0.71) 15.04 (0.51) 20,874

Source: CPS 1992/93 and 1995/96.
regression analyses controlled for age, gender, race/ethnicity, education,

income, and number of cigarettes smoked per day, the magnitude of odds

ratios for cessation activity and for abstinence or abstinence for 3-plus

months at the time of the survey were unchanged between the two survey

periods for those with 16-plus years of education compared with those with

less than 12 years of education. The magnitude of the odds ratio is a

measure of the relative difference in cessation activity or success across the

different educational groups. If successful cessation among higher

educational groups left behind a group of smokers who were more resistant

to cessation, the odds ratios for the highest educational level compared with

the lowest should decline between the two surveys, and it does not.

In contrast, there was a substantial decline between the two surveys in

the odds ratio for the highest income group compared with the lowest for

the measure of cessation activity. There was a substantial, but not

statistically significant, decline in the odds ratio for abstinence of 3 or more

months. These analyses suggest that a disproportionate fall between the two

surveys in cessation activity and successful abstinence did not occur among

the most highly educated smokers, but may have occurred among smokers

in the highest income group.

The relationship between smoking prevalence and cessation activity was

also examined across the 50 states. State-specific data from the 1995/96 CPS

on the percentage of those who were daily smokers one year prior to the

survey who had not had any cessation activity (no cessation attempt and

not becoming an occasional smoker) or who had successfully quit for 3 or

more months at the time of the survey were examined in relation to the

state-specific prevalence of smoking (age 18-plus and age 25-plus). These

cessation measures were also examined in relation to the quit ratio (fraction

of ever-smokers age 18-plus in the state who had quit at the time of the

survey). If the population of residual smokers is hardening, one might

expect to see less cessation activity (higher percentages not making a

cessation attempt) and fewer smokers with 3-plus month successful

abstinence in those states where smoking prevalence is lower or where the

quit ratio is higher. Presumably, the smoking population in these states

might be the most hardened. 

When plotted against either the prevalence of smoking or the quit ratio,

trends across states in the absence of cessation activity and 3-plus month

successful abstinence show linear slopes in the opposite direction from that

expected if the population were hardening. Absence of cessation activity in

the past year decreases (i.e., cessation activity increases) on a state-specific

basis when plotted against decreasing state-specific prevalence of smoking

(age 25-plus, p = <.0001) and increasing quit ratio (p = 0.000024). The

percentage of those who were daily smokers one year prior to the survey

who had quit for 3 or more months increases nonsignificantly as smoking

prevalence declines (p = 0.17) and increases significantly as the quit ratio

increases (p = 0.011).

Since the cost of cigarettes may influence both prevalence and cessation,

Figure 8-2 presents data for the 1995/96 CPS for all of the states in the form

107

Chapter 8
of a weighted regression that includes both state-specific prevalence (age 

25-plus) and total cost of cigarettes (Tobacco Institute 1998) as terms in the

regression. The state-specific prevalence was weighted by size of the sample

for the state. The dependent variable in the analysis is the percentage of

those smokers age 25 and older who were daily smokers one year prior to

the survey and who did not attempt to quit or become an occasional

smoker in the year prior to the survey; that is, smokers who made no

attempt to change their smoking behavior in the year prior to the survey.

This variable is adjusted in the figure for the effect of the state-specific price

of cigarettes. Cessation activity is higher rather than lower in those states

where smoking prevalence rates are the lowest. Similar results are seen for

both the 1992/93 and 1995/96 surveys. 

Table 8-3 presents the various measures of cessation calculated for the

10 states with the highest smoking prevalence compared with the 10 states

with the lowest smoking prevalence. In this analysis as well, cessation

activity and success are lower in states with higher smoking prevalence

compared with states with lower smoking prevalence. 

108

Smoking and Tobacco Control Monograph No. 15

Figure 8-2

State-Specific Percentage of Daily Smokers One Year Prior to the Survey Who Had No

Cessation Activity in the Last Year Compared to State-Specific Smoking Prevalence,

Controlling for Price of Cigarettes—1995/96 CPS (Age 25 and Older) Absence of Cessation, Adjusted for Price (%)

Smoking Prevalence (%)

70

75

80

85

90

95

14 16 18 20 22 24 26 28 30

 R = 0.53

Y = 0.42 X – 0.07 X + 72.82

Where Y = Absence of cessation

X = Prevalence of smoking (P = 0.0076)

X = Price (P = <0.0001)
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Chapter 8

Table 8-3Current Smoking Status Among Smokers Who Were Daily Smokers 1 Year Prior to the Survey (Age 25+) for States WithLowest and Highest Smoking Prevalence; Self-Respondents Only

Daily Smokers Former Smokers

No Quit Attempts Quit Attempts Occasional Quit <3 Months Quit 3+ Months Sample

Survey Years % ±95% CI % ±95% CI % ±95% CI % ±95% CI % ±95% CI Size1992/93

10 states with the lowest

smoking prevalence 61.22 (1.03) 26.92 (1.12) 3.45 (0.42) 2.59 (0.35) 5.81 (0.55) 9,110

Other states 63.66 (0.79) 25.87 (0.88) 3.15 (0.27) 2.37 (0.24) 4.95 (0.39) 22,02510 states with the highest

smoking prevalence 66.76 (1.42) 24.53 (1.10) 2.10 (0.38) 2.28 (0.44) 4.34 (0.46) 7,148

1995/96

10 states with the lowest

smoking prevalence 65.25 (1.21) 24.61 (1.18) 3.52 (0.46) 2.26 (0.44) 4.36 (0.48) 6,575

Other states 67.71 (0.89) 23.95 (0.81) 2.85 (0.28) 1.99 (0.23) 3.50 (0.33) 18,56210 states with the highest

smoking prevalence 71.99 (1.49) 20.70 (1.53) 2.39 (0.50) 1.54 (0.32) 3.37 (0.57) 5,469

Source: CPS 1992/93.
These analyses suggest that cessation behavior, as distinct from personal

difficulty in achieving cessation, may be enhanced as smoking prevalence

falls or in environments where there are fewer smokers. This interpretation

provides some support for the hypothesis that the effect of environmental

forces is magnified as the fraction of smokers in the population falls,

counterbalancing the increased personal difficulty in quitting experienced

by the residual smokers.

In summary, data from the national CPS demonstrate a fall in cessation

activity and success between the 1992/93 and 1995/96 surveys, but

cessation activity increased again in the 1998/99 survey concurrent with an

increase in the cost of cigarettes. There has been little or no shift in the

distribution of number of cigarettes smoked in the population of smokers

between the 1992/93 and 1995/96 surveys, and what shift there has been

may be a trend toward fewer heavy smokers. Neither heavy smokers nor

highly educated smokers show increased difficulty in quitting between the

two surveys, but upper income smokers have less cessation activity and may

have less abstinence in the 1995/96 survey compared with the 1992/93

survey. Comparisons across states show that cessation activity and success

are higher rather than lower in states with lower smoking prevalences, states

that might be expected to have the most-hardened smoking populations. 

In considering all of this information, it is difficult to see any clear

demonstration that the national population has hardened between 1992/93

and 1995/96 as an explanation for the fall in rates of cessation over that

interval. However, the time period examined in these national studies is

short, and this brief interval may limit the power of these analyses to

identify trends consistent with hardening in the population. Alternatively,

hardening may have occurred prior to the 1992/93 CPS and would have

been missed in the 1992/93 versus 1995/96 comparison. However, the

decline in cessation activity and successful abstinence observed between

these two surveys are not accompanied by any clear shift in the

characteristics of the residual smoking population that would suggest

hardening. In order to examine trends over a slightly longer interval during

which a larger change in smoking behavior had occurred, data from

California are examined.

In 1988, California passed an increase in the

tax on cigarettes and devoted a portion of that

tax to funding a comprehensive tobacco

control campaign. That campaign has been

successful in reducing per capita consumption

of cigarettes and smoking prevalence more rapidly in California than in the

rest of the nation (Gilpin et al. 2001). Per capita consumption fell by more

than 50% (Figure 8-3) in California, and the prevalence of smoking fell from

22.8% in 1988 to 17.1% in 2000 (California Tobacco Control Section

Evaluation Web site 2001). 

CHANGES IN CESSATION RATES,

NUMBER OF CIGARETTES

SMOKED PER DAY, AND TIME

TO FIRST CIGARETTE IN

CALIFORNIA, 1990 TO 1999

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Smoking and Tobacco Control Monograph No. 15
Data from the CTS are available for the years 1990 through 1999, and

they are presented to examine the question whether the substantial decline

in smoking behavior observed over this interval resulted in a hardening of

the population of residual smokers in California. The CTS uses a modified

Waksberg random-digit–dialed telephone methodology to obtain random

samples of the California population. Each cross-sectional survey began

with a brief screener interview from which an adult provided smoking status

and demographic information for each member of the household. Based on

the information obtained from the screener interview, adults were randomly

selected to answer an extended interview. The data gathered from the

extended interviews provide information on smoking prevalence, cessation

activity, and number of cigarettes smoked per day for adults (≥25 years of

age) in the calendar years 1990, 1996, and 1999. Base weights for those

interviewed were computed to take into account the design effect on the

probability of selection. Poststratified weights were then used to adjust the

samples to the California population provided by the Census in the years

1990, 1994, and 1999, respectively.

111

Chapter 8

Figure 8-3

Adult Per Capita Cigarette Consumption in California and U.S., Packs per Fiscal Year,

1980/1981–1999/2000 Packs per Person

Year

0

50

100

150

200

80/81 82/83 84/85 86/87 88/89 90/91 92/93 94/95 96/97 98/99

California

U.S.
Table 8-4 presents the cigarette smoking status of those self-respondents

aged 25 and older for the 1990, 1996, and 1999 surveys. The definition of

current smoker changed between the 1990 and 1996 surveys. Ever-smokers

are defined as those who had smoked 100 or more cigarettes in their

lifetime for both surveys. The 1990 survey defined current smokers by

asking whether ever-smokers smoked now, and the 1996 and 1999 surveys

asked whether they currently smoke every day, some days, or not at all. In

these analyses, only the ever-smokers’ responses to the current smoking

question were tabulated. The difference in definition of current smoker

produces a slight increase in the prevalence of current smoking, particularly

for occasional smokers (Gilpin et al. 2001). However, over the interval from

1990 through 1999, the prevalence of daily smoking among Californians

aged 25 and older fell from 17.8% to 13.0%. This decline is large enough to

be beyond that which could be attributed to a change in the definition, and

it is also large enough to expect that some evidence of hardening might be

evident if it was occurring. It should be noted that the decline in prevalence

was accompanied by a rise in never-smoking prevalence and a fall in the

prevalence of former smokers between the 1990 and 1996 surveys. It is not

clear whether these differences are due to the change in definition, other

changes in the survey, or shifts in the population.

Table 8-5 presents the current cessation status for those who were daily

smokers one year prior to the survey. In contrast to the fall in cessation

attempts and activity seen for the nation, cessation attempts and success

held constant between 1990 and 1996 in California. Between 1996 and

1999, cessation attempts and the fraction who had quit for 3 or more

months increased. These cessation measures are presented by demographic

characteristics in Tables 8-3 to 8-5. The surveys for the 1999 CTS were

conducted between August and December of 1999. In November of 1998,

there was a price increase following the Master Settlement Agreement, and

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Smoking and Tobacco Control Monograph No. 15

Table 8-4

California Cigarette Smoking Prevalence, Ages 25 and Older—1990, 1996, 1999

Current Smoker Former Never Population Sample

Daily Occasional Smoker Smoker Size Size

Year % Cl % Cl % Cl % Cl (N) (n)

1990

Total 17.8 0.57 3.3 0.34 30.1 0.96 48.7 1.08 18,248,686 20,718

Male 19.9 1.05 4.0 0.53 35.8 1.49 40.3 1.62 8,887,409 9,680

Female 15.8 0.67 2.7 0.25 24.6 1.21 56.8 1.32 9,361,269 11,038

1996

Total 14.2 0.27 4.1 0.29 27.4 0.62 54.2 0.61 19,829,250 16,117

Male 16.1 0.41 5.0 0.51 32.8 1.00 46.1 1.00 9,633,769 7,769

Female 12.5 0.35 3.3 0.32 22.3 0.73 61.9 0.71 10,195,419 8,348

1999

Total 13.0 0.28 4.7 0.39 27.7 0.56 54.6 0.58 20,538,778 12,518

Male 14.9 0.52 5.9 0.59 32.5 0.85 46.7 1.04 9,926,575 6,104

Female 11.2 0.50 3.7 0.45 23.2 0.69 62.0 0.83 10,612,211 6,414
113

Chapter 8

Table 8-5Current Smoking Status of Californians Age 25 and Older Who Were Daily Smokers 12 Months Prior to the Survey,1990, 1996, and 1999 CTS

Daily Smoker Occasional Smoker Former Smoker Unknown

Quit Without Quit Quit Without Quit Former Former Attempts or Population Sample

Attempts Attempts Attempts Attempts <3 mos >=3 mos Duration Size Size

Year % Cl % Cl % Cl % Cl % Cl % Cl % Cl (N) (n)1990 32.7 1.72 53.2 1.72 2.6 0.51 0.8 0.32 4.2 0.68 5.6 0.73 0.9 0.50 3,419,535 7,2601996 31.4 1.28 53.6 1.40 3.3 0.53 1.3 0.45 4.8 0.66 5.0 0.79 0.6 0.22 2,894,421 6,2111999 35.8 2.09 46.9 2.09 4.5 0.92 1.3 0.67 4.2 0.82 7.1 1.06 0.2 0.15 2,790,004 3,798
114

Smoking and Tobacco Control Monograph No. 15

Table 8-61990 California Tobacco Survey: Multiple Logistic Regression Model of Cessation Measures

Cessation Activity1 Cessation Attempt*2 Occasional3 Former (Any Length) Former (3–12 Months)

Variable OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CIGender

Male 1.00Female 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 1.0045–64 0.75 (0.67, 0.85) 0.75 (0.67, 0.84) 0.95 (0.69, 1.31) 1.21 (1.01, 1.45) 1.47 (1.16, 1.86)65+ 0.74 (0.62, 0.90) 0.74 (0.62, 0.89) 0.73 (0.40, 1.31) 1.40 (1.04, 1.88) 1.70 (1.18, 2.45)

Race/Ethnicity

Non-Hispanic White 1.00Hispanic 1.60 (1.35, 1.90) 1.49 (1.25, 1.76) 2.02 (1.35, 3.01) 1.69 (1.31, 2.20) 1.54 (1.09, 2.17)African-American 2.05 (1.66, 2.54) 2.02 (1.64, 2.50) 2.99 (2.00, 4.46) 1.19 (0.86, 1.65) 1.33 (0.89, 2.00)Other 1.07 (0.87, 1.32) 1.09 (0.88, 1.34) 0.78 (0.40, 1.55) 0.72 (0.49, 1.07) 0.77 (0.47, 1.29)

Education (Years)

<12 1.0012 1.10 (0.95, 1.27) 1.09 (0.94, 1.26) 1.08 (0.72, 1.63) 1.28 (0.99, 1.66) 1.44 (1.03, 2.01)13–15 1.34 (1.14, 1.57) 1.31 (1.11, 1.53) 1.50 (0.97, 2.34) 1.64 (1.24, 2.15) 1.68 (1.17, 2.40)16+ 1.26 (1.04, 1.51) 1.25 (1.03, 1.50) 1.06 (0.61, 1.85) 1.91 (1.41, 2.59) 1.66 (1.11, 2.49)

Household Income

<=$10,000 1.00$10,001–20,000 1.32 (1.09, 1.60) 1.24 (1.02, 1.50) 1.20 (0.74, 1.96) 1.48 (1.03, 2.13) 1.03 (0.67, 1.59)$20,001–30,000 1.22 (1.01, 1.48) 1.20 (0.99, 1.45) 0.75 (0.44, 1.27) 1.69 (1.19, 2.42) 1.27 (0.83, 1.92)$30,001–50,000 1.30 (1.08, 1.57) 1.28 (1.07, 1.55) 1.08 (0.67, 1.76) 1.76 (1.24, 2.48) 1.11 (0.74, 1.68)$50,001–75,000 1.38 (1.12, 1.70) 1.36 (1.10, 1.67) 1.02 (0.57, 1.80) 2.12 (1.46, 3.06) 1.29 (0.83, 2.02)$75,001+ 1.16 (0.92, 1.46) 1.13 (0.89, 1.42) 1.44 (0.78, 2.66) 2.35 (1.58, 3.49) 1.85 (1.16, 2.95)

continued
115

Chapter 8

Table 8-6 (continued)

Cessation Activity1 Cessation Attempt*2 Occasional3 Former (Any Length) Former (3–12 Months)

Variable OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CICigarettes per Day

1 to 4 1.005 to 14 0.75 (0.55, 1.02) 0.73 (0.54, 0.99) 0.63 (0.39, 1.01) 0.52 (0.36, 0.75) 0.49 (0.31, 0.77)15 to 24 0.41 (0.30, 0.55) 0.43 (0.32, 0.57) 0.22 (0.13, 0.37) 0.38 (0.26, 0.55) 0.34 (0.22, 0.54)

25+ 0.39 (0.28, 0.53) 0.40 (0.29, 0.54) 0.13 (0.07, 0.25) 0.46 (0.31, 0.67) 0.52 (0.32, 0.83)

*Cessation Attempts include attempts made by occasional smokers.NOTE: Model adjusted for gender, age, race/ethnicity, education, household income, and number of cigarettes smoked per day. Population includes respondents who reported smoking daily12 months ago, ages 25 and older.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.3Occasional: Includes those who reduced from smoking every day to smoking some days.
in January of 1999, the tax on cigarettes increased in California by $0.50.

Both of these price increases occurred during the one-year period prior to

the survey and may have contributed to the increase in cessation attempts

and 3-plus month cessation success in 1999 compared with prior surveys.

However, it is clear that the measures of cessation increased in California as

the prevalence fell, suggesting that the residual population was not

hardening, at least not to cost as a tobacco control intervention.

Multiple logistic regression analyses were performed for each survey

with age, race/ethnicity, education, income, and number of cigarettes

smoked per day entered into the analyses. The odds ratios from these

analyses are presented in Tables 8-6 through 8-8. As was true for the

analyses of the CPS data, there is no clear trend toward lower cessation

activity or successful abstinence by level of education across the three

California surveys as measured by the odds ratio for the highest education

group compared with the lowest. This suggests that the increased cessation

activity and abstinence experienced by those with higher levels of education

are not diminishing compared with those with less education. This effect is

present even though the higher educational groups have lower smoking

prevalence and higher cumulative cessation, factors that might be expected

to make them the most-hardened population of smokers.

In contrast, the effect of income on cessation success has diminished

over time, and the absence of an effect of income on cessation was also

observed in the national CPS analyses. Income is no longer a statistically

significant predictor of being a former smoker or having successfully quit

for 3 or more months in the 1999 California Tobacco Survey. This trend

may have been influenced by the increase in the cost of cigarettes in the

year prior to the 1999 survey, but it appears that the trend may have been

present in the 1996 survey as well, although the differences between 1990

and 1996 were not statistically significant.

Table 8-9 examines the prevalence of smoking different numbers of

cigarettes for the three California tobacco surveys. The data are presented as

percentages of the population rather than as percentages of smokers in

order to avoid the effect of the change in definition of smoking on overall

smoking prevalence. The change in definition would not be expected to

have a substantive impact on the fraction of the population reporting that

they smoked 25 or more cigarettes, but it does have an effect on the fraction

reporting occasional smoking and hence on the total smoking prevalence.

The percentage of the population who smokes 25 or more cigarettes per day

in California fell by more than 50% between 1990 and 1999, a much greater

proportional reduction than had occurred with either total smoking

prevalence or prevalence of daily smoking. This decline in prevalence of

heavy smoking in California was confirmed using the California-specific

data from the CPS between 1992/93 and 1995/96, during which period

there was no change in the definition used to define current smokers (data

not shown). Clearly, the fall in smoking prevalence in California was not

accompanied by a higher fraction of smokers who were in the heavysmoking categories.

116

Smoking and Tobacco Control Monograph No. 15
Whether the heavy smokers who remain in the California population

have more difficulty quitting than the larger group of heavy smokers in the

prior surveys can be examined using the odds ratios for cessation activity

and abstinence by number of cigarettes smoked per day in the multiple

logistic regression analyses presented in Tables 8-6 through 8-8. There is an

effect of number of cigarettes smoked per day on the likelihood of making a

cessation attempt and on the likelihood of having quit at the time of the

survey. In the 1990 and 1996 surveys, heavy smokers were less likely to

make a cessation attempt than were lighter smokers. In all three surveys,

lower odds ratios with increasing amount smoked were evident for any

smoking success and for 3-plus months of abstinence, but only for the

comparison with those who smoked 1 to 4 CPD one year prior to the

survey. There was no gradient of reduced success with increasing amount

smoked above 5 CPD. 

If the population of heavy smokers has become hardened, the likelihood

of making a cessation attempt or of having successfully quit among those

who smoke 25-plus CPD should fall. This would be manifest as a lower odds

ratio for the 25-plus CPD smokers as the prevalence of heavy smoking falls

in sequential surveys. When the odds ratios for heavy smokers in the three

surveys are compared (Table 8-10), the impact of smoking 25-plus CPD on

the likelihood of cessation attempts has not changed over the nine-year

interval. There are also no changes in the odds ratios for cessation success or

for 3-plus–month abstinence between the 1990 and 1999 surveys. The odds

ratios for the 1996 survey were higher and, statistically, were not

significantly different from the comparison group (1 to 4 CPD). These data

suggest that, even in the face of a more than 50% decline in the fraction of

the population that report smoking 25-plus CPD, those who remain heavy

smokers are not less likely to make a cessation attempt or less likely to be

successful in that attempt. Even in this population of heavy smokers, who

persist in being heavy smokers in spite of the powerful trends toward lower

number of cigarettes smoked per day in California, there is no evidence that

they have fewer quit attempts or less cessation success.

Smoking the first cigarette of the day within 30 minutes of waking is a

measure commonly used in scales of addiction (Fagerström and Schneider

1989), and it is one of the most powerful individual measures used to

predict addiction in these scales (Kozlowski et al. 1994). If addicted smokers

are less likely to try to quit or to remain abstinent, then the fraction of

addicted smokers in the population should increase over time. Among

Californians who were daily cigarette smokers at the time of the survey, the

proportion reporting that they smoked their first cigarette within 30

minutes of waking decreased from 62.5 ± 1.6% in 1990 to 58.6 ± 2.0% in

1999. In order to control for the shift toward reporting fewer cigarettes

smoked per day over this interval, the percentages of smokers reporting

smoking a cigarette within 30 minutes of waking are presented by number

of cigarettes smoked per day for each of the three surveys in Figure 8-4.

Over the nine years covered by the California surveys, and after a 27% fall

in the prevalence of daily smoking and a more than 50% fall in the

prevalence of heavy smoking, there is no change in the percentage of

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Chapter 8
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Smoking and Tobacco Control Monograph No. 15

Table 8-71996 California Tobacco Survey: Multiple Logistic Regression Model of Cessation Measures

Cessation Activity1 Cessation Attempt*2 Occasional3 Former (Any Length) Former (3–12 Months)

Variable OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CIGender

Male 1.00Female 0.96 (0.86, 1.07) 0.93 (0.83, 1.04) 1.26 (0.97, 1.65) 1.23 (1.03, 1.48) 1.17 (0.91, 1.49)

Age (Years)

25–44 1.0045–64 0.65 (0.58, 0.73) 0.67 (0.59, 0.76) 0.83 (0.61, 1.11) 0.78 (0.64, 0.95) 0.97 (0.75, 1.27)65+ 0.63 (0.51, 0.77) 0.64 (0.52, 0.79) 0.88 (0.52, 1.51) 1.25 (0.92, 1.70) 1.43 (0.96, 2.15)

Race/Ethnicity

Non-Hispanic White 1.00Hispanic 1.22 (1.04, 1.46) 1.21 (1.02, 1.44) 1.68 (1.16, 2.43) 1.12 (0.86, 1.48) 1.15 (0.79, 1.66)African-American 1.29 (1.04, 1.60) 1.20 (0.97, 1.49) 1.54 (1.00, 2.35) 0.47 (0.30, 0.75) 0.66 (0.38, 1.15)Other 0.93 (0.77, 1.12) 0.94 (0.78, 1.13) 0.69 (0.41, 1.17) 0.72 (0.52, 1.00) 0.73 (0.47, 1.15)

Education (Years)

<12 1.0012 0.73 (0.62, 0.85) 0.73 (0.63, 0.86) 1.08 (0.71, 1.65) 0.76 (0.58, 1.00) 0.80 (0.55, 1.15)13–15 0.95 (0.80, 1.11) 0.92 (0.78, 1.08) 1.96 (1.31, 2.95) 1.04 (0.79, 1.36) 1.04 (0.72, 1.50)16+ 1.16 (0.95, 1.40) 1.17 (0.97, 1.42) 1.65 (1.02, 2.67) 1.40 (1.03, 1.88) 1.39 (0.93, 2.08)

Household Income

<=$10,000 1.00$10,001–20,000 1.18 (0.96, 1.44) 1.25 (1.02, 1.53) 0.87 (0.54, 1.39) 1.23 (0.86, 1.77) 0.98 (0.60, 1.61)$20,001–30,000 0.96 (0.79, 1.17) 1.04 (0.85, 1.27) 0.67 (0.41, 1.09) 1.22 (0.85, 1.74) 1.21 (0.76, 1.93)$30,001–50,000 1.05 (0.87, 1.27) 1.09 (0.90, 1.32) 0.89 (0.57, 1.38) 1.44 (1.03, 2.01) 1.24 (0.79, 1.93)$50,001–75,000 1.10 (0.89, 1.35) 1.12 (0.91, 1.38) 0.94 (0.59, 1.51) 1.26 (0.87, 1.82) 1.45 (0.90, 2.32)$75,001+ 1.08 (0.86, 1.35) 1.13 (0.91, 1.42) 0.72 (0.41, 1.26) 1.87 (1.29, 2.71) 1.60 (0.98, 2.62)

continued
119

Chapter 8

Table 8-7 (continued)

Cessation Activity1 Cessation Attempt*2 Occasional3 Former (Any Length) Former (3–12 Months)

Variable OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CICigarettes per Day

1 to 4 1.005 to 14 0.77 (0.56, 1.06) 1.05 (0.77, 1.42) 0.34 (0.22, 0.51) 0.64 (0.42, 0.98) 0.88 (0.49, 1.60)15 to 24 0.48 (0.35, 0.66) 0.68 (0.51, 0.92) 0.17 (0.11, 0.26) 0.50 (0.33, 0.77) 0.62 (0.34, 1.13)

25+ 0.40 (0.29, 0.55) 0.57 (0.41, 0.78) 0.11 (0.06, 0.20) 0.67 (0.43, 1.04) 0.83 (0.45, 1.54)

*Cessation Attempts include attempts made by occasional smokers.NOTE: Model adjusted for gender, age, race/ethnicity, education, household income, and number of cigarettes smoked per day. Population includes respondents who reported smoking daily12 months ago, ages 25 and older.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.3Occasional: Includes those who reduced from smoking every day to smoking some days.
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Smoking and Tobacco Control Monograph No. 15

Table 8-81999 California Tobacco Survey: Multiple Logistic Regression Model of Cessation Measures

Cessation Activity1 Cessation Attempt2 Occasional3 Former (Any Length) Former (3–12 Months)

Variable OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CIGender

Male 1.00Female 0.86 (0.74, 0.99) 0.87 (0.75, 1.00) 1.09 (0.79, 1.49) 0.86 (0.69, 1.08) 0.75 (0.57, 1.00)

Age (Years)

25–4445–64 0.63 (0.54, 0.73) 0.62 (0.53, 0.72) 1.10 (0.79, 1.54) 0.81 (0.64, 1.03) 1.04 (0.78, 1.39)65+ 0.63 (0.49, 0.80) 0.60 (0.47, 0.77) 0.95 (0.40, 1.31) 1.27 (0.87, 1.84) 1.47 (0.94, 2.30)

Race/Ethnicity

Non-Hispanic WhiteHispanic 1.11 (0.90, 1.37) 1.08 (0.87, 1.33) 1.15 (0.74, 1.80) 1.41 (1.03, 1.93) 1.25 (0.85, 1.85)African-American 1.68 (1.25, 2.26) 1.68 (1.26, 2.25) 1.49 (0.89, 2.49) 1.29 (0.85, 1.96) 0.86 (0.48, 1.54)Other 0.97 (0.77, 1.23) 1.01 (0.80, 1.28) 1.01 (0.61, 1.68) 0.89 (0.61, 1.31) 0.89 (0.56, 1.41)

Education (Years)

<1212 1.31 (1.07, 1.61) 1.27 (1.04, 1.56) 1.09 (0.69, 1.72) 1.35 (0.96, 1.91) 1.30 (0.86, 1.98)13–15 1.18 (0.95, 1.46) 1.17 (0.95, 1.45) 1.27 (0.78, 2.05) 1.37 (0.96, 1.97) 1.38 (0.89, 2.15)16+ 1.45 (1.13, 1.87) 1.46 (1.13, 1.88) 1.25 (0.71, 2.20) 2.00 (1.35, 2.97) 1.74 (1.07, 2.82)

Household Income

<=$10,000$10,001–20,000 1.24 (0.95, 1.62) 1.19 (0.91, 1.55) 0.73 (0.42, 1.26) 0.90 (0.57, 1.42) 0.80 (0.47, 1.38)$20,001–30,000 1.19 (0.91, 1.56) 1.20 (0.92, 1.56) 0.92 (0.54, 1.56) 1.09 (0.70, 1.69) 1.07 (0.64, 1.79)$30,001–50,000 1.03 (0.80, 1.33) 1.03 (0.80, 1.32) 0.61 (0.35, 1.06) 1.10 (0.72, 1.67) 0.79 (0.47, 1.32)$50,001–75,000 1.12 (0.86, 1.47) 1.15 (0.88, 1.50) 0.49 (0.27, 0.91) 1.22 (0.79, 1.88) 0.94 (0.56, 1.59)$75,001+ 1.14 (0.86, 1.50) 1.16 (0.87, 1.53) 0.54 (0.29, 1.00) 1.42 (0.91, 2.22) 1.22 (0.72, 2.06)

continued
121

Chapter 8

Table 8-8 continued

Cessation Activity1 Cessation Attempt2 Occasional3 Former (Any Length) Former (3–12 Months)

Variable OR 95% CI OR 95% CI OR 95% CI OR 95% CI OR 95% CICigarettes per Day

1 to 45 to 14 0.54 (0.35, 0.82) 0.76 (0.51, 1.12) 0.40 (0.24, 0.66) 0.53 (0.33, 0.84) 0.46 (0.27, 0.80)15 to 24 0.38 (0.25, 0.58) 0.55 (0.37, 0.81) 0.15 (0.09, 0.26) 0.40 (0.25, 0.64) 0.38 (0.22, 0.66)

25+ 0.35 (0.23, 0.54) 0.51 (0.34, 0.76) 0.11 (0.06, 0.22) 0.58 (0.36, 0.95) 0.51 (0.29, 0.90)

*Cessation Attempts include attempts made by occasional smokers.NOTE: Model adjusted for gender, age, race/ethnicity, education, household income and number of cigarettes smoked per day. Population includes respondents who reported smoking daily12 months ago, ages 25 and older.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.3Occasional: Includes those who reduced from smoking everyday, to smoking some days.
122

Smoking and Tobacco Control Monograph No. 15

Table 8-9

Percentage of the California Population Age 25 and Older Who Smoke Different

Numbers of Cigarettes per Day

Daily,

Occasional* 1–4 5–14 15–24 25+ Unknown Amount

Year % CI % CI % CI % CI % CI % Cl

1990 3.3 0.34 0.6 0.14 4.7 0.29 7.9 0.33 4.4 0.33 0.2 0.07

1996 4.1 0.29 0.7 0.09 4.7 0.26 6.0 0.22 2.8 0.19 0.1 0.04

1999 4.7 0.39 0.7 0.14 4.5 0.29 5.6 0.34 2.1 0.16 0.1 0.03

*Change in definition of current smoker 1990–96.

Table 8-10

Multivariate Logistic Regression Models of Cessation Activity and Current Cessation

Status for Adult Smokers Who Were Current Daily Smokers One Year Prior to the

Survey and Who Were Age 25 or Older at the Time of the Survey, 1990,1996, and 1999

California Tobacco Surveys

Cessation Activity1* Former* Former 3+*

Cigarettes/Day OR 95% CI OR 95% CI OR 95% CI

1990

1–4 1.00

5–14 0.75 (0.55, 1.02) 0.52 (0.36, 0.75) 0.49 (0.31, 0.77)

15–24 0.41 (0.30, 0.55) 0.38 (0.26, 0.55) 0.34 (0.22, 0.54)

25+ 0.39 (0.28, 0.53) 0.46 (0.31, 0.67) 0.52 (0.32, 0.83)

1996

1–4 1.00

5–14 0.77 (0.56, 1.06) 0.64 (0.42, 0.98) 0.88 (0.49, 1.60)

15–24 0.48 (0.35, 0.66) 0.50 (0.33, 0.77) 0.62 (0.34, 1.13)

25+ 0.40 (0.29, 0.55) 0.67 (0.43, 1.04) 0.83 (0.45, 1.54)

1999

1–4 1.00

5–14 0.54 (0.35-0.82) 0.53 (0.33-0.84) 0.46 (0.27-0.80)

15–24 0.38 (0.25-0.58) 0.40 (0.25-0.64) 0.38 (0.22-0.66)

25+ 0.35 (0.23-0.54) 0.58 (0.36-0.95) 0.51 (0.29-0.90)

1

Cessation activity: Includes those who have made a quit attempt, have become occasional smokers, or have become former

smokers.

*Also adjusted for gender, age, race/ethnicity, education, and household income.
smokers, stratified by amount smoked, who reports smoking the first

cigarette within 30 minutes of waking. 

Data from the national CPS conducted in 1992/93, 1995/96, and

1998/99, and from three California surveys conducted in 1990, 1996, and

1999, are examined for evidence that the residual population of smokers

represents a hardened group, more addicted and less likely to be successful

in cessation. National rates of cessation attempts declined between 1992/93

and 1995/96, but appear to have increased again in 1998/99. The fall in

rates between 1992/93 and 1995/96 was not accompanied by an increased

fraction of the population reporting that they smoked more than 25

cigarettes per day, and there was no decline in the odds ratios for cessation

attempts and success among those with higher educational attainment

between the two surveys. There was a decline in the odds ratios for those

with higher income levels.

SUMMARY

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Figure 8-4

Percentage of Adult Daily Smokers Age 25 and Older Smoking Their First Cigarette

Within 30 Minutes of Waking by Number of Cigarettes Smoked per Day, 1990, 1996,

and 1999, California Tobacco Surveys Percentage

Cigarettes per Day

0

10

20

30

40

50

60

70

80

90

100

Total 1-4 5-14 15-24 25+

1990

1996

1999

95% CI
In California, where cessation rates did not decline between 1990 and

1996 and where there has been a large fall in the prevalence of smoking,

particularly heavy smoking, there has been no increase in the fraction of

smokers who report smoking more than 25 cigarettes per day or in the

percentage of smokers who smoke the first cigarette within 30 minutes of

waking. The odds ratios for cessation activity and success for higher levels of

education have not declined between 1990 and 1999, which suggests that

the group with the highest level of cessation success is continuing to enjoy

undiminished higher levels of cessation success. This effect was not seen for

those with higher levels of income.

These data do not provide compelling evidence that the residual

population of smokers either nationally or in California is becoming

hardened or is less likely to successfully quit smoking. It is possible to argue

that the absence of evidence for hardening is due to the lack of a measure

that adequately quantifies the difficulty an individual smoker has in

achieving cessation. However, the measures used do gauge self-reported

cessation behavior and success, and an increasing difficulty in quitting on a

personal level may be less important for purposes of tobacco control if it is

not accompanied by a diminished likelihood of cessation activity or

cessation success.

The evidence presented also suggests that the residual population of

smokers in California is not composed of a larger fraction of heavily

addicted smokers, at least for number of cigarettes smoked per day and time

to first cigarette as measures of addiction. One reasonable interpretation of

these observations is that comprehensive tobacco control campaigns, such

as that conducted in California, produce environmental changes that affect

heavy smokers and addicted smokers more powerfully than less dependent

smokers. This differential impact may counterbalance the greater personal

difficulty in achieving cessation experienced by those who have thus far

been unable to quit. It is also possible that those environmental changes

that lead to reductions in number of cigarettes smoked per day may also

reduce the strength of the addiction among those smokers who manage to

reduce the number of cigarettes that they smoke. In this way, the changing

environment could make it personally easier for the smoker to quit instead

of the residual population of smokers having more difficulty quitting.

124

Smoking and Tobacco Control Monograph No. 15
125

Chapter 8

REFERENCES

Burns, D. M., Anderson, C., Johnson, M. et al.

Cessation and cessation measures among adult

daily smokers: National and state-specific data.

In Population-Based Smoking Cessation: What

Works. Smoking and Tobacco Control Monograph

No. 12, edited by D. Burns, D. Shopland, 25–97.

NIH Pub. No. 00-4892. Bethesda, MD: U.S.

Department of Health and Human Services,

National Cancer Institute, 2000.

Burns, D. M., Lee, L., Shen, Z. et al. Cigarette

smoking behavior in the United States. In

Changes in Cigarette-Related Disease Risks and

Their Implication for Prevention and Control.

Smoking and Tobacco Control Monograph No. 8,

edited by D. Burns, L. Garfinkel, J. Samet,

13–112. NIH Pub. No. 97-4213. Bethesda, MD:

U.S. Department of Health and Human Services,

National Cancer Institute, 1997.

California Tobacco Control Section Evaluation.

2001. (http://www.dhs.ca.gov/ps/cdic/ccb/

TCS/documents/PR4-01graphs3.pdf).

Fagerström, K. O., Schneider, N. G. Measuring

nicotine dependence: A review of the

Fagerström Tolerance Questionnaire. Journal of

Behavioral Medicine 1989;12:159–82.

Gilpin, E. A., Emery, S. L., Farkas, A. J. et al. The

California Tobacco Control Program: A Decade of

Progress, 1989–1999. La Jolla, CA: University of

California at San Diego, 2001.

Kozlowski, L. T., Porter, C. Q., Orleans, C. T. et al.

Predicting smoking cessation with self-reported

measures of nicotine dependence: FTQ, FTND,

and HSI. Drug and Alcohol Dependence

1994;34:211–16.

Tobacco Institute. The Tax Burden on Tobacco.

Washington, DC: The Tobacco Institute, 1998.

U.S. Department of Health and Human Services.

Reducing Tobacco Use: A Report of the Surgeon

General. Atlanta, GA: U.S. Department 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, 2000.
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Smoking and Tobacco Control Monograph No. 15
Hardening of the Target:

Evidence From Massachusetts

Carolyn C. Celebucki

For the greater part of the past two decades, adult cigarette

smoking prevalence (defined as having smoked at least 100 cigarettes and

smoked in the past month) has been steadily declining in the

Commonwealth of Massachusetts and in the rest of the nation (Biener,

Harris, and Hamilton 2000; CDC 1996; CDC 1999b). Since the beginning of

the Massachusetts Tobacco Control Program (MTCP) in 1993/94, the

smoking prevalence decline in Massachusetts is close to 2.5 times the

national rate (minus California, which initiated a large tobacco control

program in 1989) (Biener, Harris, and Hamilton 2000; Hamilton and Norton

2000; Hamilton, Norton, and Weintraub, 2001). Furthermore, when

controlling for race/ethnicity, gender, and education level, Massachusetts

has experienced significant declines since 1990 in smoking prevalence,

while the rest of the nation, minus California, has not (Weintraub and

Hamilton 2001). 

Massachusetts’ per capita consumption of cigarettes by adults (18-plus)

is also declining. Since the start of the MTCP, it is declining at greater than

3.5 times the rate of decline of the rest of the nation, minus California

(Biener, Harris, and Hamilton 2000). There is evidence that much of the

early decline in adult smoking occurred among the more educated, more

affluent population (U.S. DHHS 2000; Emery et al. 2000). This chapter

examines changes in the characteristics of current smokers in Massachusetts

from 1986 to 1999 and, where possible, compares their trends over time to

those of current nonsmokers. 

A commonly voiced opinion is that smokers are harder to treat or

harder to reach now than a few years ago. With an estimated 340,000 fewer

smokers in Massachusetts since 1986, logic posits that the “easy quits”

would have occurred early in the process, leaving the target population of

remaining smokers more hardened—i.e., less able physically or

psychologically and/or less motivated to successfully quit as measured by

number of quit attempts and intent to quit. These smokers might then be

more nicotine-dependent as measured by time to first cigarette, number of

cigarettes smoked per day, and use of a pack a day or greater. If they have

tried to quit and failed, they may be more discouraged in their ability to

quit successfully, less likely to continue to make quit attempts, and more

adamant about remaining smokers. If earlier trends continued, they may

also be less educated, less affluent, and perhaps less likely to have access to

services. 

BACKGROUND

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Chapter 9
Support for the premise of a hardening of the target is provided by an

analysis of published studies of clinical treatment outcomes that controlled

for type of services offered and revealed a significant linear trend toward less

positive short-term cessation success since the 1980s (see Chapter 4). The

author acknowledges that long-term quit success did not decline and posits

environmental factors as a probable explanation. Over time, the participants

in the studies that were part of the meta-analysis were also significantly

more likely to be older, and when age was controlled in the analysis, the

significant decrease in quit success was no longer evident. 

In Massachusetts, anecdotal information from cessation providers and

quantitative data from the Smoker’s Quitline (Prout, Martinez, and Ballas

2001) provide limited support for this premise in that smokers in treatment

services are smoking their first cigarette sooner upon awakening in 1999

than in 1994. There is evidence from demographic data collected through

the Management Information Systems (MIS) that smokers using the

Quitline counseling services, although not those using local cessation

counseling, are also significantly older now than in 1994, with a mean age

of 34.7 in 1993 and 39.2 in 2001. Abt Associates Inc. and Emery and

colleagues (Abt Associates 2000, 2001; Emery et al. 2000) found age to be

predictive of hardening in smokers. However, smokers in treatment are not

smoking more cigarettes per day now than in 1994 (Prout, Martinez, and

Ballas 2001; Hamilton and Norton 2000).

Data from national sources (see Chapters 7 and 8) do not support the

thesis of a hardened target in the general population of current smokers in

that smokers in states with lower rates of prevalence are not reporting

higher numbers of cigarettes smoked (one proxy for dependence) over time.

It is possible that current smokers in Massachusetts are not becoming more

hardened and that the comprehensive public health model of changing

social norms, while reducing access and providing treatment services, is still

adequate to the task of reducing the morbidity and mortality associated

with tobacco use. 

An alternative hypothesis posits that the kinds of initiatives undertaken

in Massachusetts (Hamilton and Norton 2000; Biener, Harris, and Hamilton

2000; CDC 1999a; Connolly and Robbins 1999; DiFranza, Celebucki, and

Mowery 2001; Kozlowski et al. 2000; Bartosch and Pope 1999) and

California (Gilpin et al. 2001; Pierce et al. 1998b) differentially affect the

hardened core. From a health perspective, a tax increase differentially

benefits those with higher marginal costs (relatively less disposable income,

higher costs, or higher consumption) (CDC 1996; Chaloupka and Pacula

1999; Harris and Chan 1999; Wakefield and Chaloupka 2000). The increased

social cost of smoking, like increased financial cost, may also differentially

affect those with higher marginal costs—i.e., those who consume the most

relative to their restricted opportunity or increased costs of smoking (Siegal,

Biener, and Rigotti 1999; Wakefield et al. 2000). For example, a pack-per-day

or greater smoker whose workplace becomes smokefree may have to quit

smoking totally, or drastically reduce the number of cigarettes smoked,

while one who smokes a few cigarettes may be able to accommodate

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Smoking and Tobacco Control Monograph No. 15
changing environmental constraints without altering consumption. Healthrelated symptoms that drive the smoker to quit or seek medical support may

also be more likely to occur in this group, and physicians are known to

intervene more often with smokers who are older, smoke more cigarettes,

and have poorer health (Gilpin et al. 1993). Unfortunately, attrition (earlier

death or disability) should also differentially affect this group as moreaddicted smokers with longer smoking histories, presumably higher

exposure to tobacco toxicity, and perhaps adjuvant unhealthy conditions

(problem drinking, poor mental health, increased limitations) die sooner.

This could leave the general population of remaining smokers less hardened

in the long term. 

If smokers who are less likely to be impacted by the increased “costs” of

smoking, less likely to be exposed to interventions, less able to access

services, or less successful with services offered increase over time as a

proportion of the general population, then a hardening of the target could

occur in the short term. For example, current smokers could become less

affected by some policy initiatives over time; i.e., they could be less exposed

or less responsive to the MTCP motivational/educational media campaign,

not be working in employment covered by a smoking restriction, not have

seen a physician, or not be covered by health insurance. Emery et al. (2000)

describe the hardcore smoker in California (5.6% of current smokers in

1996) as more likely to be white, male, older, living without children in the

home, feeling no family pressure to quit, educated at no higher level than

high school, and earning $30,000 or less. Additionally, current smokers

could be more likely to have other problems that make it more difficult to

quit or easier to relapse, such as poor mental health (Lasser, Boyd, and

Woolhandler 2000), physical disabilities (Brawarsky et al. 2002), limitations

from these illnesses, or alcohol or drug problems. Furthermore, these

conditions may also make it less likely that they would be affected by some

of the MTCP’s policy initiatives—e.g., work in a smokefree workplace.

The MTCP has always funded program components that address

cessation as well as prevention of tobacco use, and the reduction of

environmental tobacco smoke (ETS) exposure (Begay and Glantz 1997;

Hamilton and Norton 2001). Access to free, on-demand telephone

counseling services and free or sliding-scale community-based cessation

groups has been a component of the program since its inception, as has

outreach to harder-to-reach populations. A more complete discussion of

MTCP tobacco treatment services can be found elsewhere (Hamilton and

Norton 2000). Even as total funding decreased, tobacco treatment services

were maintained at a fairly consistent percentage of overall funding

(Hamilton and Norton 2001). It is also probable that the increased use of

nicotine replacement products due to over-the-counter availability has

benefited the more-addicted smoker (Biener, personal communication).

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Chapter 9
The change in smoking variables in the general population in

Massachusetts would not provide evidence of a hardened target; that

is, over time, current smokers would not be smoking more, smoking

sooner upon awakening, attempting less quitting, or less inclined to quit.

Similarly, it was expected that trends over time for smokers would not be

toward becoming less educated, earning less money, less likely to be

working for wages, less likely to have health insurance, less likely to have

checkups, or more likely to have poor physical or emotional health, limited

activities, or alcohol problems, or that the trends for these measures would

not be worse for smokers than for nonsmokers. While differences between

smokers and nonsmokers in these variables were anticipated, we did not

expect the trends for these two groups to diverge over time. We

hypothesized that the general population of current smokers would actually

be less nicotine-dependent, more motivated to quit, and more likely to have

had a medical checkup in the past year due in part to the MTCP. 

The data used for this chapter were collected through the

Massachusetts Behavioral Risk Factor Surveillance System (BRFSS) from 1986

to 1999. The BRFSS is an annual, state-based, random-digit–dialed

household telephone survey of health-related behaviors and conditions

among adults 18 years of age and older that is conducted by all states in

cooperation with the Centers for Disease Control and Prevention (CDC).

Tobacco-use questions were first asked in 1986. The MTCP has augmented

the BRFSS since 1994 with additional tobacco-related items and increased

sample sizes. Topics and questions can vary from year to year.

During this reporting period, the Massachusetts BRFSS used a listassisted methodology to sample households, and interviews were conducted

with one randomly selected adult from each contacted household. The

annual interview completion rate among contacted households ranged from

54% to 83%; the annual number of completed interviews ranged from 1,105

to 5,024. Completion rates were lower and the number of completed

interviews higher in the later years. Characteristics of the BRFSS are

described in detail elsewhere (CDC 1996). 

“Current” smoking status is defined by two questions. In all

years, all respondents were asked whether they smoked 100

cigarettes in their lifetime. From 1986 to 1995, those who

responded “yes” were asked whether they now smoke cigarettes.

In the 1996 to 1999 surveys, those who responded “yes” were asked

whether they now smoke cigarettes every day, some days, or not at all.

“Current smokers” are those adults who smoked 100 cigarettes in their

lifetime and now smoke (1986 to 1995) or now smoke every day or some

days (1996 to 1999). “Nonsmokers” are either those who did not smoke 100

cigarettes in their lifetime or those who smoked 100 cigarettes in their

lifetime but do not now smoke. In 1994 and 1995, all smokers were asked,

“On how many of the past 30 days did you smoke cigarettes?” “Daily

smokers” are those who reported that they smoked 30 of the past 30 days in

1994 and 1995 and those who reported smoking every day for the 1996 to

1999 surveys. 

Measures

Tobacco Use and

Cessation Variables

Instruments

METHODS

Hypothesis

130

Smoking and Tobacco Control Monograph No. 15
From 1986 to 1999, all current smokers were asked about the number of

cigarettes they smoked per day. From 1991 to 1993, all current smokers were

asked if they quit smoking for one day or longer in the past year, and,

between 1994 and 1999, daily smokers were asked the same question. In

1995 and from 1997 to 1999, nondaily smokers were asked whether or not

they intentionally quit smoking for one day or longer in the past year.

“Quit attempt” for daily and nondaily smokers combined, is reported for

1991 to 1993, 1995, and 1997 to 1999. From 1994 to 1999, all current

smokers were asked whether or not they intended to quit in the next 30

days, whether or not they were thinking about quitting in the next 6

months, and how long after waking they smoked their first cigarette. “No

intent to quit” is defined as no intent to quit in the next 30 days and not

thinking about quitting in the next 6 months.

During the years 1986 to 1999, respondents provided

information on age, educational attainment, employment status, and

income. “Less than high school” was defined as never attending school or

completing a grade no higher than grade 11. “College graduate” was defined

as completing 4 years or more of college. “Unable to work” was added as a

separate response category to the employment status question in 1993.

Therefore, “out of work/unable to work” is reported only for 1993 to 1999,

while “employed for wages” is recorded since 1986 as one of the categorical

responses, with “self-employed,” “retired,” and “out of work” as the other

possible choices.

From 1992 to 1999, adults were asked about their health status. They

were asked whether, in general, their health was excellent, very good, good,

fair, or poor. In addition, during 1993 to 1999, adults were asked about their

physical and mental health and whether they were limited in usual

activities due to poor mental or physical health in the past month. “Poor

mental health” was defined as having 14 or more days in the past month

during which mental health was not good. “Activity limitation” was defined

as having 14 or more days in the past month during which poor physical or

mental health kept respondents from doing their usual activities. 

Respondents were also asked about health care access. From 1991 to

1999, they were asked whether they had “any kind of health care coverage

including health insurance, prepaid plans such as HMOs, or government

plans such as Medicare.” From 1987 to 1999, adults were asked how long it

had been since they visited a doctor for a routine checkup. “No checkup in

last year” was defined as those who did not answer “within the past year”;

that is, they answered “within past 2 years,” “ 5 years,” “more than 5 years,”

or “never.”

Questions about alcohol use were asked in 1986 to 1993 and in 1995,

1997, and 1999. “Problem drinking” was defined as consuming 5 or more

drinks on any one occasion in the past month or consuming 60 or more

drinks in the past month. 

Alcohol Use

Health Care

Health Status

Demographic Variables

131

Chapter 9
Because BRFSS data are weighted to account for differential probability

of selection and to partially adjust for nonresponse, SUDAAN was used to

calculate p values that took into account the survey sampling scheme and

weighting of the data (Shah, Barnwell, and Bieler 1996). Similarly, logistic

regression was employed rather than chi-square for the trend test as the

latter is not available in SUDAAN. Data for current rather than daily

smokers were selected for analyses, because seven additional years could

then be included. “Employed for wages” rather than “out of work/unable to

work” is the preferred variable for the same reason.

Logistic regression models assessed trends over time in demographic,

health status, health care access, and alcohol use characteristics for both

current smokers and nonsmokers, and compared the trends of the two

groups. We modeled the log odds of various characteristics (i.e., college

graduate, fair/poor health, etc.). The independent variables were current

smoking status, year, and an interaction term of current smoking status and

year. The “year” term was used to test for trends for current smokers and

nonsmokers in the following manner: In testing the trend for smokers,

smokers were coded as 1 and nonsmokers as 0; coding was reversed when

testing trends for nonsmokers, with nonsmokers coded as 1 and smokers as

0. The significance of the interaction term was used to test the difference in

trends between smokers and nonsmokers. Similarly, linear regression was

used with the same independent variables to assess trends over time in the

continuous variable mean age.

Logistic regression models were also used to test trends over time in

smoking characteristics among smokers. We modeled the log odds of

smoking characteristics (i.e., quit attempt, less than 30 minutes to first

cigarette after waking, greater than a pack a day). The independent variable

was year. In addition, a linear regression model was used to test the trend in

the mean number of cigarettes smoked per day. 

A total of 1,105 interviews were completed in 1986; 1,422 in 1987; 1,425

in 1988; 1,221 in 1989; 1,296 in 1990; 1,424 in 1991; 1,825 in 1992; 1,857

in 1993; 3,288 in 1994; 3,311 in 1995; 3,041 in 1996; 3,725 in 1997; 4,944

in 1998; and 5,024 in 1999. Table 9-1 depicts current smoking prevalence

and smoking behaviors by year and by gender. Also displayed by year and

by gender are the distributions of current smokers (Table 9-1) and current

nonsmokers (Table 9-2) by education group, income level, employed for

wages, out of work/unable to work, no health insurance, no checkup in past

year, and the percentages of each with alcohol problems, poor mental

health, fair/poor health, or those whose activities are limited by poor

mental or physical health. Mean age is also recorded. 

RESULTS

ANALYSIS

132

Smoking and Tobacco Control Monograph No. 15
133

Chapter 9

Table 9-1Prevalence of Current Smoking by Year and Gender and the Distribution of Current Smokers by Year and Gender AcrossDemographic, Health-Related, and Tobacco-Dependence Characteristics,1986–1999

Prevalence of Current Smoking

Year 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999Current Smoker 27.9 27.6 27 23.7 24.1 22.9 23.5 21.1 22.3 22.7 22.7 20.5 21.1 19.3Men 28.6 27.3 27.1 22 26.7 22.7 25.9 20.7 23.9 24.1 23.3 21 21.2 19.5Women 27.2 27.9 26.8 25.1 21.8 23.1 21.2 21.4 20.7 21.5 22.2 20.2 21 19.1

Distribution of Current Smokers by Year and Gender Across Demographic Characteristics

Current Smokers

Education: All

<HS 20.9 17.1 21.1 18.2 18.3 16.4 14.6 15.1 14.9 13.6 17.3 12.5 13.4 13.8HS grad 37.6 39.1 39.3 38.9 41.8 43.9 42.6 41.3 39.6 37.7 38.4 38.5 40.9 37.8Some college 21.9 23.7 24 24.1 22.6 23.6 22 23.6 26.8 31.1 27.6 29 29.7 26.9College grad 19.5 20.1 15.6 18.7 18.3 16.1 20.8 20 18.7 17.6 16.7 20 15.9 21.6

Education: Men

<HS 26.5 19.9 22.9 16.3 19.9 19.5 17.2 18.1 13.4 15.1 22.2 11.6 14 15HS grad 34.8 34.5 41.8 40.9 37.7 43 41 41 40 31.7 36.1 41.9 43.1 37Some college 16.8 21.7 19.2 20.3 22.1 16.6 22.1 19.4 25 33.1 23.3 27.4 26.5 27.1College grad 21.9 23.9 16.1 22.5 20.3 20.8 19.7 21.5 21.7 20.1 18.4 19 16.4 20.9

Education: Women

<HS 15.8 14.7 19.6 19.6 16.7 13.8 11.8 12.4 16.5 12.1 12.7 13.4 12.9 12.7HS grad 40.2 43.2 37.1 37.5 44.1 44.6 44.3 41.5 39.2 43.7 40.6 35.2 38.9 38.5Some college 26.7 25.4 28.3 27.1 23.1 29.6 21.8 27.3 28.6 29.1 31.6 30.5 32.7 26.7College grad 17.3 16.7 15.1 15.8 16.1 12 22.1 18.8 15.7 15 15.1 20.9 15.5 22.1

Income: All

<$25,000 50.7 45.1 41 41.3 43.5 49.3 49 39.1 38.5 36.4 32.8 30.6 32.9 31.2$25,000–34,999 16 15.3 20 16.2 15.3 17.5 13.7 18 24.9 15.2 22.4 16.2 18.3 16.1$35,000–49,999 16.7 16.9 13 17 18.2 15.9 19.4 17.5 16.5 18.7 20.7 21.5 23.4 19.9$50,000+ 16.5 22.7 25 25.6 22.9 17.3 17.8 25.3 20.1 29.7 24.1 31.7 25.3 32.8

Income: Men

<$25,000 49.5 46.5 37.7 37.7 35.3 38.2 42.2 39.4 33.1 27.9 26.7 32.6 29.2 30.7$25,000–34,999 15.7 16.4 18.1 17.5 19.2 19.7 16 17.8 26.7 14.9 23.2 12.6 16.7 15.4$35,000–49,999 21.1 14.7 13.3 20.1 23.5 23 23.3 18.2 19.2 21.4 22.4 23.6 23.1 17.4$50,000+ 13.7 22.4 30.8 24.7 22 19.1 18.5 24.6 21.1 35.9 27.6 31.2 31 36.3

continued
134

Smoking and Tobacco Control Monograph No. 15

Table 9-1 (continued)

Distribution of Current Smokers by Year and Gender Across Demographic Characteristics (continued)

Year 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999Income: Women

<$25,000 51.7 44.7 43.6 44 52.9 58.9 56.9 38.9 44.5 44.5 38.5 28.6 36.5 31.6$25–34,999 16.6 12.9 21.5 15.2 10.9 15.8 11.1 18.1 22.9 15.5 21.6 19.5 19.9 16.9$35–49,999 12.8 19.3 14.7 14.6 12 9.7 15 17 13.5 16.2 19.1 19.6 23.7 22.2$50,000+ 18.9 23.1 20.1 26.3 24.2 15.6 17 26 19 23.9 20.8 32.2 19.9 29.3

Percentage of Current Smokers with Various Health-Related and Tobacco-Dependence Characteristics by Year and Gender

Current Smokers

Empl. for Wages

All 67.1 67.3 60.5 61 54.3 62.9 63.1 60.4 61 57 59.1 62.2 70 61.6Men 68.9 72.4 63 66.5 60.6 68.2 59.7 61.5 64 61.5 61.2 66.3 71.7 62.1Women 65.4 62.9 58.2 56.8 47.7 57.9 67 59.5 58 52.4 57.1 58.4 68.4 61.1

Out of Work/Unable to Work (18–64)

All 15.5 11.1 13.7 14.4 15.1 9.7 11.9Men 13.8 10.4 12 13.5 14.2 10.3 12.5Women 17 11.7 15.5 15.3 16 9.1 11.4

No Health Insurance (18–64)

All 18.1 19.4 21.7 18.6 18.7 20.9 16.6 18.2 13.3Men 25.6 21.6 26.1 20.1 18.7 24.6 19.7 21.2 17.1Women 10.9 16.9 17.6 17 18.8 17.1 13.7 11.4 9.8

No Checkup in Last Year

All 32.5 36.4 37.4 38.2 37.3 28 37.9 37.1 38.9 34.1 33.9 31.1 26.7Men 37.7 44.7 41.8 43.1 47.1 34.3 44.5 44.2 50.1 40.5 42.9 44.2 35.7Women 28.1 29 34.1 32.9 29 23.2 32 31 27.7 28.1 25.7 19.1 18.4

Fair/Poor Health

All 10.3 13.4 13.7 13.8 13.6 13 12.2 17.6Men 11.8 14.4 9.4 15.1 12.8 14 13.1 17

Women 8.7 12.5 18.2 12.4 14.3 12.1 11.4 18.2

Poor Mental Health: 14+ Days in Last Month

All 16.9 17.5 16.8 16.8 15.8 13 13.1Men 16.5 12.4 14.5 12.7 16.8 11.3 10.4Women 17.3 22.7 18.9 20.8 14.9 14.6 15.5

Activities Limited by Poor Physical or Mental Health: 14+ Days in Last Month

All 7 8.3 7.4 8.1 8.2 5.9 11

Men 7.3 8.6 7.9 7.1 8.9 6.8 8.4Women 6.7 7.9 6.8 9.1 7.5 5.2 11.6

continued
135

Chapter 9

Table 9-1 (continued)

Percentage of Current Smokers with Various Health-Related and Tobacco-Dependence Characteristics by Year and Gender (continued)

Year 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999Alcohol Problem (Binge or Chronic Drinker)

All 37.9 32.9 32.2 28.2 30.1 32.4 31.1 29.4 27.6 35.9 34.3Men 55.1 48.8 42.9 46 37 45.4 43 39.6 35.6 49.7 43.2Women 22.1 19.3 22.8 14.4 22.8 21.2 17.7 20.7 19.7 23.2 26

Quit Attempt

All 55.1 53.8 60.5 59.7 58.9 57.3 63.5Men 53 49.1 66.8 63.8 59.7 55.7 64.2Women 56.7 59.3 54.9 55.5 58.2 58.7 62.9

Plan to Quit in Next 30 Days

All 30.1 29.5 30.1 38.8 41.9 37.9Men 29.9 33.5 30.8 38.2 44.5 40.8Women 30.2 25.5 29.4 37.6 39.5 38.7

Time to First Cigarette <= 30 Minutes

All 49.7 49.9 53.4 51 55.5 53.5Men 51.3 54.2 57.5 51.5 62.4 53.1Women 48 45.5 49.4 50.5 49.1 53.9

Mean Number Cigarettes Smoked per Day*

All 20.3 18.7 19.4 20.1 19.3 19.2 18.7 16.7 15.9 17.4 16.6 15.6 16.2 15.4Men 22.6 20.1 21.9 23 20.7 21.3 20.3 17.5 16.9 19.2 18.5 16.2 18.7 17.3Women 18.4 17.6 17.2 17.9 17.8 17.4 17 15.9 14.8 15.6 14.7 14.9 13.9 13.6

Smoke More Than 1 Pack per Day*

All 26.7 22.9 24.2 26.3 24.5 23.1 23.3 16.8 16.2 17.5 17.2 17.2 18.8 15.7Men 32.3 25.3 30.7 37.6 30.5 31.7 26.3 19.7 19.5 20.8 22.2 17 24 21Women 21.7 20.9 18.5 17.7 18 15.7 19.9 14.2 12.7 14.2 12.5 17.4 14 11

No Intent to Quit Smoking

All 28 26.8 28 26.1 24.6 27.2Men 31.6 24.4 28.2 26.8 24.6 25.9Women 24.1 29.1 27.8 25.5 24.7 28.3

Age (Mean Age)

All 39.9 40.5 39.8 40.9 40.4 39.8 39.3 39.5 40.9 40.6 42.1 39.7 38.8 41.6Men 39.2 40.2 39.7 39.1 40.4 38.5 38.7 38.4 41.9 39 40.8 38.8 38.5 41.5

Women 40.6 40.6 40.1 42.2 40.4 41 39.9 40.4 39.8 42.1 43.4 40.6 39.1 41.7

* Includes some day and every day smokers. There was a change in questions and response categories in 1994. From 1986–1993, “On the average, about how many cigarettes a day doyou now smoke?” was asked of daily and nondaily smokers. “Don’t smoke regularly” was a response category. Therefore, the number of cigarettes smoked per day for “don’t smoke regularly”

is not included above for 1986–1993. Starting in 1994, daily smokers were asked the same question and nondaily smokers were asked, “On the average, when you smoked during the past30 days, about how many cigarettes did you smoke a day?” There was no response category “don’t smoke regularly.” Also, there was a change in coding in 1994. Up to 1993, the maximumnumber of cigarettes smoked per day was 87. In 1994, that number changed to 76. Therefore, for 1986–1993, if number of cigarettes >76, number of cigarettes was set to 76.
136

Smoking and Tobacco Control Monograph No. 15

Table 9-2Distribution of Nonsmokers by Year and Gender for Demographic and Health-Related Characteristics, 1986–1999

Distribution of Nonsmokers Across Demographic Characteristics

Year 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999Not Current SmokersEducation: All

<HS 12.5 14.9 10.2 13.8 11.7 13.1 9.8 10.3 10.1 9.6 11.1 7.6 6.5 7.4HS grad 29.4 27.2 29 25.5 30 27.8 28.4 25.3 27.2 25.7 24.6 27 28.3 28Some college 25.4 25 25.8 25.8 23.8 24.8 22.4 25.7 25 23.7 25.1 26.4 25.5 24.5College grad 32.7 32.9 35.1 34.9 34.5 34.3 39.4 38.6 37.7 41 39.1 39 39.6 40.1

Education: Men

<HS 12.6 13.9 8 13.3 10.8 15.3 9.4 9.3 8.7 9.3 10.7 7.3 6.8 7HS grad 24.6 24.6 26.3 22.9 29.4 22.1 27.3 24.8 26.2 23.7 23.3 25.7 26.7 27.3Some college 23.5 22.2 28.6 23 23.6 24.9 20.1 23.7 24.4 20.6 22.1 25.5 23.7 22.6College grad 39.3 39.3 37.1 40.8 36.2 37.7 43.1 42.2 40.7 46.5 44 41.5 42.9 43.1

Education: Women

<HS 12.5 15.8 12 14.3 12.4 11.2 10.1 11.3 11.3 10 11.5 7.9 6.3 7.7HS grad 33.5 29.5 31.4 27.9 30.5 32.8 29.3 25.8 28 27.5 25.8 28.1 29.8 28.7Some college 27 27.5 23.3 28.3 24 24.8 24.3 27.6 25.5 26.4 27.8 27.2 27.2 26.1College grad 27.1 27.3 33.3 29.6 33.1 31.3 36.3 25.3 35.1 36.2 34.9 36.8 36.7 37.4

Income: All

<$25,000 41.9 39.3 34.3 36 30.3 34.9 31.4 32.2 31.8 26.2 25.3 24.1 22.9 19.3$25,000–34,999 20.7 15.8 19.9 15.9 16.4 14.3 15.5 13.6 14.4 15 15.2 15.5 12.9 12.5$35,000–49,999 15.7 19 18.2 17.2 21 18.9 19 17.7 19.5 18.2 17.5 20.6 19.7 17.2$50,000+ 21.6 25.8 27.6 30.9 32.3 31.9 34.1 36.5 34.3 40.5 42 39.9 44.4 51.1

Income: Men

<$25,000 35.2 32.5 28.1 31.3 25 31.1 25.2 28.6 26.3 22.7 21.4 20.9 17.6 15.6$25,000–34,999 22.3 19.2 23.9 14.7 18.9 14.2 18 13.4 15.5 16.4 15 13 14.1 12.9$35,000–49,999 17.4 22.7 18.1 17.6 21.5 21.1 19.8 20.5 21.3 17.5 17.3 20.4 19.9 16.7$50,000+ 25.1 25.5 29.9 36.4 34.6 33.6 37 37.5 36.9 43.4 46.3 45.7 48.4 54.8

Income: Women

<$25,000 47.7 45.5 40 40.4 34.7 38.3 36.6 35.5 36.7 29.5 28.9 27.2 28.2 22.9$25,000–34,999 19.5 12.7 16.1 17 14.3 14.4 13.4 13.8 13.4 13.8 15.3 17.8 11.8 12$35,000–49,999 14.3 15.7 18.4 16.8 20.6 16.8 18.3 15.2 17.9 18.9 17.8 20.8 19.5 17.7$50,000+ 18.5 26.1 25.5 25.8 30.3 30.5 31.7 35.5 32 37.9 38.1 34.2 40.4 47.4

continued
137

Chapter 9

Table 9-2 (continued)

Percentage of Nonsmokers With Various Health-Related Characteristics

Year 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999Not Current SmokersEmpl. for Wages

All 55.2 59.4 56.3 51.4 56.6 52.9 54 56.9 58.5 57 58.9 58.4 59.2 57.3Men 65.6 69.5 61.5 55.8 65.7 55.3 62.1 64 65.3 62.3 65.5 64.7 65.7 61.7Women 46.2 50.6 51.7 47.6 49.3 50.7 47.1 50.4 52.8 52.5 53.1 52.9 53.3 53.3

Out of Work/Unable to Work (18–64)

All 7.5 6.5 6.2 6.3 6 5.8 6.5Men 6.7 6.4 5.7 6.5 6.3 4.5 6.5Women 8.3 6.5 6.5 6.1 5.8 7.5 6.6

No Health Insurance (18–64)

All 8.6 8.3 6.9 10 10 10.8 8.7 7.8 7Men 8.2 10 7.8 11.5 10.7 12.1 10.4 8.5 8Women 9 6.8 6 8.6 9.4 9.6 7.1 7.2 6

No Checkup in Last Year

All 36.3 30.3 31 30 27.9 25.2 24.2 26.9 27.1 27.3 20.9 20.2 20.3Men 47.7 39.1 41.6 40.7 33.3 29.2 30.8 33.8 36.1 36.8 28.5 26.9 26.9Women 26.3 22.8 21.5 21.4 23.1 21.9 18.3 21.1 19.3 18.9 14.2 14.3 14.4

Fair/Poor Health

All 8.3 9.3 10.6 11.7 12.2 11.5 9.7 10.1Men 6.9 9.1 9.7 11.4 11.4 11.2 8.7 10.5Women 9.4 9.4 11.3 12 12.9 11.8 10.5 9.8

Poor Mental Health: 14+ Days in Last Month

All 7.6 9.2 8.1 8.1 7.5 7 6.5Men 5.2 8.2 6.5 6 6.7 5.2 6.4Women 9.8 10.1 9.6 9.9 8.2 8.6 6.6

Activities Limited by Poor Physical or Mental Health: 14+ days in last month

All 4.3 4.8 4.7 3.9 4.9 4.5 4.9Men 4.2 5.7 3.6 3.7 5.1 3.8 5.5Women 4.4 4 5.7 4.1 4.7 5.1 4.3

Alcohol Problem (Binge or Chronic Drinker)

All 21.3 18.2 15.2 19.4 16 17 17.4 17.7 15.6 14.9 14.6Men 29.9 30.7 24.3 31.7 28.5 26.5 25.7 28.3 26.5 23.1 22.7Women 13.9 7.2 7.2 8.2 5.9 8.8 10.4 8.1 6.3 7.6 7.4

Age (Mean Age)

All 45.4 45 44.5 44.7 45.7 45.9 45 44.9 44.8 45.7 45.2 46 46.1 46.5Men 43.6 42.8 42.6 43.2 44.1 44.4 43.5 43.1 42.8 44.5 44 44.5 44.6 45

Women 46.9 46.9 46.1 46.1 47 47.1 46.3 46.5 46.5 46.8 46.3 47.4 47.6 47.9
138

Smoking and Tobacco Control Monograph No. 15

Table 9-3Results of Regression Analyses for Trends Over Time and Differences in Trends in Various Characteristics of Smokers and Nonsmokers

Comparison of

Smokers Nonsmokers Smokers to Nonsmokers Difference in Trend

Logistic Regression

p value

p value

p value

Variable Years Trend (Trend) Trend (Trend) (Difference in Trend)Less Than High School 1986–99

All Decrease 0.0001 Decrease <.0001 0.0808Men Decrease 0.0020 Decrease <.0001 0.6103Women Decrease 0.0200 Decrease <.0001 0.0410 Nonsmokers, > dec

College Graduate 1986–99

All Increase 0.7988 Increase <.0001 0.0314 Nonsmokers, > incMen Decrease 0.3036 Increase 0.0082 0.0368Women Increase 0.1336 Increase <.0001 0.3978

Out of Work(age 18–64) 1993–99

All Increase 0.0026 Increase 0.0042 0.6533Men Increase 0.0800 Increase 0.0200 0.8976Women Increase 0.0089 Increase 0.0617 0.4316

Employed for Wages 1986–99

All Increase 0.6066 Increase 0.0065 0.3691Men Decrease 0.7856 Increase 0.6352 0.6353Women Increase 0.3197 Increase 0.0009 0.4474

High Income 1986–99

All Increase <.0001 Increase <.0001 0.0001 Nonsmokers, > incMen Increase <.0001 Increase <.0001 0.0684 Nonsmokers, > incWomen Increase 0.0431 Increase 0.0020 0.0003 Nonsmokers, > inc

Low Income 1986–99

All Decrease <.0001 Decrease <.0001 0.0959Men Decrease <.0001 Decrease <.0001 0.2769Women Decrease <.0001 Decrease <.0001 0.2259

continued
139

Chapter 9

Table 9-3 (continued)

Comparison of

Smokers Nonsmokers Smokers to Nonsmokers Difference in Trend

Logistic Regression

p value p value p value

Variable Years Trend (Trend) Trend (Trend) (Difference in Trend)No Health Insurance(age 18–64) 1991–99

All Decrease 0.0056 Decrease 0.0633 0.2706Men Decrease 0.1418 Decrease 0.2689 0.2193Women Decrease 0.0109 Decrease 0.1074 0.0466 Smokers, > dec

Fair/Poor Health 1992–99

All Increase 0.0557 Increase 0.5885 0.1603Men Increase 0.1298 Increase 0.3365 0.4114Women Decrease 0.2419 Decrease 0.8557 0.2648

No Checkup inPast Year 1987–99

All Decrease 0.0025 Decrease <.0001 0.0006 Nonsmokers, > decMen Decrease 0.7203 Decrease <.0001 0.0001 Nonsmokers, > decWomen Decrease <.0001 Decrease <.0001 0.3804

Poor Mental Health 1993–99

All Decrease 0.0082 Decrease 0.0044 0.6496Men Decrease 0.1645 Decrease 0.4323 0.5080Women Decrease 0.0175 Decrease 0.0009 0.8389

Activities Limited 1993–99

All Increase 0.5250 Increase 0.6869 0.7590Men Decrease 0.8841 Increase 0.6873 0.7212Women Increase 0.2813 Increase 0.8856 0.3904

Alcohol Problem

All Increase 0.6384 Decrease 0.0001 0.0089Men Decrease 0.3087 Decrease 0.0003 0.2668Women Increase 0.0636 Decrease 0.0596 0.0085

Linear RegressionAge

All Increase 0.0012 Increase 0.0230 0.1765Men Increase 0.0072 Increase 0.0605 0.2676Women Increase 0.0420 Increase 0.1528 0.3925
Changes in trends over time were tested for the prevalence of a variety

of demographic, health status, and health care characteristics, for current

smokers as compared with the rest of the population (not current smokers),

overall, and by gender. For smokers, change over time in tobacco use and

cessation variables was also tested; i.e., mean number of cigarettes smoked

per day, smoking over one pack per day, smoking within 30 minutes of

waking, past-year quit attempts, intention to quit in next 30 days, and not

thinking about quitting within the next 6 months. Table 9-3 depicts the p

values associated with the trends over time for smokers and nonsmokers

and the difference in trends. Table 9-4 depicts the p values associated with

the trends in tobacco use and cessation variables. 

140

Smoking and Tobacco Control Monograph No. 15

Table 9-4

Results of Linear and Logistic Regressions for Trends Over Time in Various

Behaviors of Smokers

Linear Regression Logistic Regression

Variable Years Change p value Change p value

Current Smoker 1986–99

All Decrease <.0001

Men Decrease <.0001

Women Decrease <.0001

Quit Attempt 1991–93, 1995, 1997–99

All Increase 0.035

Men Increase 0.1511

Women Increase 0.1193

Plan to Quit 1994–99

All Increase <.0001

Men Increase 0.0003

Women Increase <.0001

No Intent to Quit 1994–99

All Decrease 0.5017

Men Decrease 0.3002

Women Increase 0.8712

<=30 Minutes to First

Cigarette 1994–99

All Increase 0.1407

Men Increase 0.464

Women Increase 0.1369

Number of

Cigarettes/Day

All Decrease <.0001

Men Decrease <.0001

Women Decrease <.0001

>1 Pack/Day

All Decrease <.0001

Men Decrease 0.0003

Women Decrease 0.0008
Results indicate no support for a hardening of the target among

current smokers, and on several measures there is evidence of less

tobacco dependence now than in 1986. As noted in Table 9-4, the

percentage of current smokers reporting a past-year quit attempt

and intention to quit smoking within the next 30 days has significantly

increased over time. Similarly, the reported number of cigarettes smoked per

day has decreased as have those reporting smoking greater than a pack (20

cigarettes) per day. Patterns for women and men are similar. 

There was no significant change in the percentage reporting that they

smoke within the first 30 minutes after awakening. But contrary to

prediction, there was a suggestion among women of an increase in this

variable (p = 0.14). There was virtually no change in those who report no

intent to quit within the next 6 months. 

In summary, changes for current smokers are either in the hypothesized

direction of less hardening or are unchanged. No evidence supports a

hardening. Smokers do not appear to be less motivated to quit in terms of

past quitting history, less likely to quit in next 30 days, or less likely to be

thinking about quitting in the next 6 months. 

Table 9-3 displays the results of logistic and linear

regressions for changes over time in various

demographic and health-related characteristics for smokers and

nonsmokers, and it presents the p value of tests for differences in the trends

between smokers and nonsmokers. The proportion of those with less than a

high school education has significantly decreased over time for both

smokers and nonsmokers. The decrease was significantly greater for

nonsmoking women than smoking women. There was an increase in college

graduates over time among nonsmokers, but not among smokers, and the

significant difference between smokers and nonsmokers was largely

attributable to changes among men. The population is aging in

Massachusetts and trends were significant for smokers and nonsmokers, but

there were no significant differences between smokers and nonsmokers. 

Significant decreases were evident over time in the lowest income group,

with comparable increases in the highest income group. Compared with

smokers, the increase in the percent reporting high income was significantly

greater for nonsmokers overall and for nonsmoking women, and was

suggestive for nonsmoking men. There were increases in the percentage of

smokers and nonsmokers who were out of work/unable to work, but no

significant differences between them. 

The percentage reporting no health insurance declined among smokers

(aged 18 to 64), attributable primarily to declines among women, and this

decline was greater for women who smoke as compared with those who do

not. Declines in the percentage of nonsmokers who reported no health

insurance were also suggestive (p = 0.063). The percentage of smokers

reporting no checkup in the past year declined, a decrease again driven

primarily by women, but nonsmokers compared with smokers had a

significantly greater decline overall and for men.

Change in Demographic and

Health-Related Variables

Change in

Tobacco-Use

and Cessation

Variables

141

Chapter 9
There is a suggestion (p = 0.06) that an increased proportion of smokers

reported being in fair or poor health, while there was no discernable trend

among nonsmokers. The difference between smokers and nonsmokers did

not reach significance. Among both smokers and nonsmokers, there were

reported declines in poor mental health and these were significant for

women. However, there was no difference between smokers and

nonsmokers in the trend in this measure. There were no significant trends

in the percent reporting limited activities over time. 

Nonsmokers reported fewer alcohol problems, while smokers did not,

and the difference between the trends for smokers and nonsmokers was

significant. Self-reported alcohol problems decreased significantly among

nonsmoking men, but not among smoking men. The marginal decreases in

self-reported problems with alcohol among nonsmoking women (p = 0.06)

and the marginal increases among smoking women (p = 0.06) resulted in a

significant difference in trends among women.

There is scant evidence that smokers in Massachusetts have become

more hardened. The results generally show that the residual population of

smokers is declining in tobacco dependence and increasing in access to

economic and health resources even with the successful implementation of

the MTCP. Decreases in tobacco dependence are substantiated by declines in

the mean number of cigarettes smoked per day and the percentage of

smokers smoking more than one pack per day. In addition, the percentage

of smokers reporting a quit attempt in the past year or who plan to quit in

the next 30 days increased. The percentage of smokers reporting that they

smoke within the first 30 minutes of waking did not change over time, and

there was no significant change in the percentage reporting no intent to

quit in the next 6 months. Increases in access to resources are documented

by the significant decreases in the percentage of smokers with low

education, low income, no health insurance, no past-year checkup, and

significant increases in those with high income. Smoking women were less

likely over time to have no health insurance, no past-year checkups, and

poor mental health, but were marginally more likely to report alcohol

problems. 

While smokers have made significant gains in education and income

over the 13 years covered in this study, they have not done so to the same

extent as nonsmokers. This divergence is due in part to significantly steeper

trends that favored nonsmokers compared with smokers with respect to

increases in the percentage with college degrees, decreases among women

with less than a high school education, and increases overall and among

both women and men in the percentage reporting high income.

Additionally, directional differences in trends over time among men with

college degrees (nonsignificant decreases among smokers and significant

increases among nonsmokers) resulted in significantly greater increases for

nonsmokers. 

While the increase over time among smokers who reported being out of

work or unable to work is consistent with a harder-to-reach, less advantaged

or more-hardened smoking population, a comparable increase was evident

DISCUSSION

142

Smoking and Tobacco Control Monograph No. 15
among nonsmokers. And since the difference in trends between the two

groups was not significant, it is unlikely that this increase is related solely to

smoking. The percentage of women without health insurance decreased

significantly for smokers but not for nonsmokers, and the difference was

significant. The percentage of the population who did not receive a health

care checkup in the last year declined over time for female smokers, female

nonsmokers, and male nonsmokers, but did not decrease for male smokers.

The difference between smokers and nonsmokers was significant overall and

for men, favoring nonsmokers.

Finally, with respect to health-related variables that could influence

smoking, there were no significant differences over time between smokers

and nonsmokers in the percentage reporting poor mental health or limited

activity. However, smokers were marginally more likely to increase reporting

fair/poor health (p = 0.06) over time. It is likely that age differentially affects

the health status of smokers compared with nonsmokers, and this effect

could account for the marginal increases in reports of fair and poor health

among smokers. There was no significant change in smokers’ reports of

alcohol problems, but alcohol problems among nonsmokers have

significantly declined over time, and the difference between smokers and

nonsmokers over time is significant. This is especially true for women.

In summary, these trends do not suggest that the population of smokers

who remains is more addicted, more resistant to cessation messages, less

likely to attempt cessation, or increasingly composed of those with limited

activities or poor mental health. However, there is concern that, if program

resources are reduced or an economic slowdown diminishes the economic

or educational opportunities presently available, smokers may benefit less

from the tobacco control initiatives because they are not as economically

advantaged as nonsmokers. Should this occur, the target may harden. 

These findings should be interpreted in light of some important

limitations. First, households without telephones have no opportunity to

participate in the survey. Second, BRFSS data are based on self-report and

subject to resultant biases. Respondents may overreport socially acceptable

behaviors and underreport behaviors deemed unacceptable. The response

rate to the BRFSS during the years 1986 to 1999 ranged from 54% to 83%. If

smoking status was different for people who did not respond to the survey,

there could be a bias in the analysis. In addition, many of these

observations were made over a relatively short interval of time when there

was a relatively small change in smoking prevalence. This may limit the

ability to detect trends in mental health and substance abuse behaviors that

result from the difficulty in achieving long-term abstinence by smokers with

these problems.

LIMITATIONS

143

Chapter 9
144

Smoking and Tobacco Control Monograph No. 15

REFERENCES

Abt Associates Inc. Management Information System

for the Massachusetts Department of Public Health.

Cambridge, MA: Abt Associates, 2000.

Abt Associates Inc. Management Information System

for the Massachusetts Department of Public Health.

Cambridge, MA: Abt Associates, 2001.

Bartosch, W. J., Pope, G. C. The economic effect of

smoke-free restaurant policies on restaurant

business in Massachusetts. Journal of Public

Health Management Practice 1999;5(1):53–62.

Begay, M. E., Glantz, S. A. Question 1 tobacco

education expenditures in Massachusetts, USA.

Tobacco Control 1997;6(3):213–18.

Biener, L., Harris, J. E., Hamilton, W. Impact of the

tobacco control programme: Population based

trend analysis. British Medical Journal

2000;321:351–54.

Brawarsky, P., Brooks, D. R., Wilber, N. et al. Tobacco

use among adults with disabilities. Tobacco

Control 2002;11(Suppl 2):ii29–ii33.

Centers for Disease Control and Prevention. The

Behavioral Risk Factor Surveillance System: Survey

Design, Execution and Use. Atlanta, GA: Centers

for Disease Control and Prevention, 1996.

Centers for Disease Control and Prevention. Best

Practices for Comprehensive Tobacco Control

Programs. Atlanta, GA: U.S. Department of

Health and Human Services, 1999a.

Centers for Disease Control and Prevention.

Cigarette smoking among adults—United States,

1997. Morbidity and Mortality Weekly Report

1999b;48(43):993–96.

Centers for Disease Control and Prevention.

Cigarette smoking before and after an excise tax

increase and an antismoking campaign—

Massachusetts, 1990–1996. Morbidity and

Mortality Weekly Report 1996;45(44):966–70.

Chaloupka, F. J., Pacula, R. L. Sex and race

differences in young people’s responsiveness to

price and tobacco control policies. Tobacco

Control 1999;8(4):373–77.

DiFranza, J. R., Celebucki, C. C., Mowery, P. D.

Measuring statewide compliance with tobacco

sales laws: The Massachusetts experience.

American Journal of Public Health

2001;91:1124–125.

Emery, S., Gilpin, E. A., Ake, C. et al. Characterizing

and identifying “hardcore” smokers:

Implications for further reducing smoking

prevalence. American Journal of Public Health

2000;90(3):387–94.

Gilpin, E. A., Emery, S. L., Farkas, A. J. et al. The

California Tobacco Control Program: A Decade of

Progress, 1989–1999. La Jolla, CA: University of

California at San Diego, 2001. 

Gilpin, E. A., Pierce, J. P., Johnson, M. et al.

Physician advice to quit smoking: Results from

1990 California Tobacco Survey. Journal of

General Internal Medicine 1993;8(10):549–53.

Hamilton, W. L., Norton, G. Independent Evaluation

of the Massachusetts Tobacco Control Program.

Sixth Annual Report. Cambridge, MA: Abt

Associates Inc., 2000.

Hamilton, W. L., Norton, G., Weintraub J.

Independent Evaluation of the Massachusetts

Tobacco Control Program. Seventh Annual Report.

Cambridge, MA: Abt Associates Inc., 2001.

Harris, J. E., Chan, S.W. The continuum of

addiction: Cigarette smoking in relation to price

among Americans aged 15–29. Health Economics

1999;8(1):81–86. 

Irvin, J. E., Brandon, T. H. The increasing

recalcitrance of smokers in clinical trials.

Nicotine and Tobacco Research 2000; 2(1):79–84.

Kann, L., Warren, C. W., Harris, W. A. Youth risk

behavior surveillance—United States, 1995.

Morbidity and Mortality Weekly Report

1996;45(4):1–84.

Kozlowski, L. T., Yost, B., Stine, M. M. et al.

Massachusetts’ advertising against light

cigarettes appears to change beliefs and

behavior. American Journal of Preventive Medicine

2000;18(4):339–42.

Lasser, K., Boyd, J. W., Woolhandler, S. et al.

Smoking and mental illness: A population-based

prevalence study. Journal of the American Medical

Association 2000;284(20):2606–610.

Pierce, J. P., Gilpin, E. A., Emery, S. L. et al. Has the

California Tobacco Control Program reduced

smoking? Journal of the American Medical

Association 1998a;280(10):893–99.

Pierce, J. P., Gilpin, E. A., Emery, S. L. et al. Tobacco

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

Evaluation of the Tobacco Control Program,

1989–1996. La Jolla, CA: University of California

at San Diego, 1998b.

Prout, M. N., Martinez, O., Ballas, L. et al. Who uses

the smoker’s quitline in Massachusetts? Tobacco

Control 2002;11(Suppl 2):ii74–ii75.

Rigotti, N. A., Regan, S., Majchrzak, N. E. et al.

Tobacco use by Massachusetts public college

students, 1999. Tobacco Control 2002;

11(Suppl 2):ii20–ii24.

Shah, B. V., Barnwell, B. V., Bieler, G. S. SUDAAN

Users Manual and Software, Release 7.0. Research

Triangle Park, NC: Research Triangle Institute,

1996.

Siegal, M., Biener, L., Rigotti, N. A. The effect of

local tobacco sales laws on adolescent smoking

initiation. Preventive Medicine 1999;29(5):334–42.
145

Chapter 9

U.S. Department of Health and Human Services.

Reducing Tobacco Use: A Report of the Surgeon

General. Atlanta, GA: U.S. Department 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, 2000.

Wakefield, M. A., Chaloupka, F. J. Effectiveness of

comprehensive tobacco control programmes in

reducing teenage smoking in the USA. Tobacco

Control 2000;9(1):24–32.

Wakefield, M. A., Chaloupka, F. J., Kaufman, N. J. 

et al. Effects of restrictions on smoking at home,

at school, and in public places on teenage

smoking: Cross-sectional study. British Medical

Journal 2000;321(7257):333–37. 

Weintraub, J. M., Hamilton, W. L. Trends in

prevalence of current smoking, Massachusetts

and the United States, 1990–1999. Tobacco

Control 2002;11(Suppl 2):ii8–ii13.