RESPIRATORY HEALTH EFFECTS
 

OF PASSIVE SMOKING:
 

LUNG CANCER AND OTHER DISORDERS
 

EPA/600/6-90/006F 

December 1992 

Major funding for this report has been provided by the Indoor Air Division,
 

Office of Atmospheric and Indoor Air Programs
 

Office of Health and Environmental Assessment
 

Office of Research and Development
 

U.S. Environmental Protection Agency
 

Washington, D.C.
 
DISCLAIMER 

This document has been reviewed in accordance with U.S. Environmental Protection Agency policy 

and approved for publication. Mention of trade names or commercial products does not constitute 

endorsement or recommendation for use. 

ii 
CONTENTS 

Tables ........................................................................... viii
 

Figures .......................................................................... xiii
 

Foreword ........................................................................ xv
 

Preface .......................................................................... xvi
 

Authors, Contributors, and Reviewers ................................................. xvii
 

1. SUMMARY AND CONCLUSIONS ............................................... 1-1
 

1.1. MAJOR CONCLUSIONS ................................................... 1-1
 

1.2. BACKGROUND ...................................................... . . .. 1-2 
 

1.3. PRIMARY FINDINGS ..................................................... 1-4
 

1.3.1.	 ETS and Lung Cancer ................................................ 1-6
 

1.3.1.1. Hazard Identification ........................................ 1-6
 

1.3.1.2. Estimation of Population Risk ................................. 1-11
 

1.3.2. ETS and Noncancer Respiratory Disorders ............................... 1-12
 

2. INTRODUCTION .............................................................. 2-1
 

2.1. FINDINGS OF PREVIOUS REVIEWS ........................................ 2-2
 

2.2.	 DEVELOPMENT OF EPA REPORT .......................................... 2-5
 

2.2.1. Scope ............................................................. 2-5
 

2.2.2. Use of EPA's Guidelines .............................................. 2-6
 

2.2.3. Contents of This Report .............................................. 2-8
 

3. ESTIMATION OF ENVIRONMENTAL TOBACCO SMOKE EXPOSURE ............... 3-1
 

3.1. INTRODUCTION ......................................................... 3-1
 

3.2. PHYSICAL AND CHEMICAL PROPERTIES .................................. 3-2
 

3.3. ASSESSING ETS EXPOSURE .............................................. 3-10
 

3.3.1.	 Environmental Concentrations of ETS ................................... 3-12
 

3.3.1.1. Markers for Environmental Tobacco Smoke ...................... 3-18
 

3.3.1.2. Measured Exposures to ETS-Associated Nicotine and RSP ......... 3-22
 

3.3.2. Biomarkers of ETS Exposure .......................................... 3-40
 

3.3.3. Questionnaires for Assessing ETS Exposures ............................. 3-48
 

3.4. SUMMARY .............................................................. 3-51 
 

4.	 HAZARD IDENTIFICATION I: LUNG CANCER IN ACTIVE SMOKERS,
 

LONG-TERM ANIMAL BIOASSAYS, AND GENOTOXICITY STUDIES ............... 4-1
 

iii 
CONTENTS (continued) 

4.1. INTRODUCTION ......................................................... 4-1
 

4.2.	 LUNG CANCER IN ACTIVE SMOKERS ..................................... 4-2
 

4.2.1. Time Trends ....................................................... 4-2
 

4.2.2. Dose-Response Relationships .......................................... 4-5
 

4.2.3. Histological Types of Lung Cancer and Associations With Smoking ........... 4-10
 

4.2.4. Proportion of Risk Attributable to Active Smoking ......................... 4-23
 

4.3.	 LIFETIME ANIMAL STUDIES .............................................. 4-23
 

4.3.1. Inhalation Studies ................................................... 4-25
 

4.3.2. Intrapulmonary Implantations of Cigarette Smoke Condensates ............... 4-25
 

4.3.3. Mouse Skin Painting of Cigarette Smoke Condensates ...................... 4-26
 

4.4. GENOTOXICITY ......................................................... 4-27
 

4.5. SUMMARY AND CONCLUSIONS .......................................... 4-27
 

5.	 HAZARD IDENTIFICATION II: INTERPRETATION OF EPIDEMIOLOGIC
 

STUDIES ON ENVIRONMENTAL TOBACCO SMOKE AND LUNG CANCER .......... 5-1
 

5.1. INTRODUCTION ......................................................... 5-1
 

5.2.	 RELATIVE RISKS USED IN STATISTICAL INFERENCE ....................... 5-15
 

5.2.1. Selection of Relative Risks ............................................ 5-15
 

5.2.2. Downward Adjustment to Relative Risk for Smoker
 

Misclassification Bias ................................................ 5-22
 

5.3.	 STATISTICAL INFERENCE ................................................ 5-25
 

5.3.1. Introduction ........................................................ 5-25
 

5.3.2. Analysis of Data by Study and Country .................................. 5-31
 

5.3.2.1. Tests for Association ........................................ 5-31
 

5.3.2.2. Confidence Intervals ........................................ 5-34
 

5.3.3	 Analysis of Data by Exposure Level .................................... 5-36
 

5.3.3.1. Introduction ............................................... 5-36
 

5.3.3.2. Analysis of High-Exposure Data ............................... 5-37
 

5.3.3.3. Tests for Trend ............................................. 5-40
 

5.3.4. Conclusions ........................................................ 5-45
 

5.4.	 STUDY RESULTS ON FACTORS THAT MAY AFFECT
 

LUNG CANCER RISK ..................................................... 5-48 
 

5.4.1. Introduction ........................................................ 5-48
 

5.4.2. History of Lung Disease .............................................. 5-51
 

5.4.3. Family History of Lung Disease ........................................ 5-53
 

5.4.4. Heat Sources for Cooking or Heating .................................... 5-53
 

5.4.5. Cooking With Oil ................................................... 5-54
 

5.4.6. Occupation ........................................................ 5-54
 

5.4.7. Dietary Factors ..................................................... 5-55
 

5.4.8. Summary on Potential Modifying Factors ................................ 5-60
 

5.5. ANALYSIS BY TIER AND COUNTRY ....................................... 5-60
 

5.6. CONCLUSIONS FOR HAZARD IDENTIFICATION ............................ 5-63
 

5.6.1. Criteria for Causality ................................................. 5-63
 

iv
 
CONTENTS (continued) 

5.6.2. Assessment of Causality .............................................. 5-67
 

5.6.3. Conclusion ......................................................... 5-68
 

6. POPULATION RISK OF LUNG CANCER FROM PASSIVE SMOKING ................ 6-1
 

6.1. INTRODUCTION ......................................................... 6-1
 

6.2.	 PRIOR APPROACHES TO ESTIMATION OF POPULATION RISK ............... 6-1
 

6.2.1. Examples Using Epidemiologic Data .................................... 6-2
 

6.2.2. Examples Based on Cigarette-Equivalents ................................ 6-5
 

6.3.	 THIS REPORT'S ESTIMATES OF LUNG CANCER MORTALITY
 

ATTRIBUTABLE TO ETS IN THE UNITED STATES ........................... 6-8
 

6.3.1. Introduction and Background .......................................... 6-8
 

6.3.2. Parameters and Formulae for Attributable Risk ............................ 6-10
 

6.3.3. U.S. Lung Cancer Mortality Estimates Based on Results of
 

Combined Estimates from 11 U.S. Studies ............................... 6-16
 

6.3.3.1. U.S. Lung Cancer Mortality Estimates for Female
 

Never-Smokers ............................................. 6-16
 

6.3.3.2. U.S. Lung Cancer Mortality Estimates for Male
 

Never-Smokers ............................................. 6-17
 

6.3.3.3. U.S. Lung Cancer Mortality Estimates for Long-Term
 

(5+ Years) Former Smokers .................................. 6-20
 

6.3.4. U.S. Lung Cancer Mortality Estimates Based on Results of the 
 

Fontham et al. (1991) Study (FONT) .................................... 6-21
 

6.3.5. Sensitivity to Parameter Values ........................................ 6-27
 

6.4. SUMMARY AND CONCLUSIONS ON POPULATION RISK ..................... 6-29
 

7.	 PASSIVE SMOKING AND RESPIRATORY DISORDERS
 

OTHER THAN CANCER ....................................................... 7-1
 

7.1. INTRODUCTION ......................................................... 7-1
 

7.2.	 BIOLOGICAL MECHANISMS .............................................. 7-2
 

7.2.1. Plausibility ......................................................... 7-2
 

7.2.2. Effects of Exposure In Utero and During the First
 

Months of Life ..................................................... 7-3
 

7.2.3. Long-Term Significance of Early Effects on
 

Airway Function .................................................... 7-6
 

7.2.4. Exposure to ETS and Bronchial Hyperresponsiveness ...................... 7-7
 

7.2.5. ETS Exposure and Atopy ............................................. 7-9
 

7.3.	 EFFECT OF PASSIVE SMOKING ON ACUTE RESPIRATORY
 

ILLNESSES IN CHILDREN ................................................. 7-10
 

7.3.1. Recent Studies on Acute Lower Respiratory Illnesses ....................... 7-11
 

7.3.2. Summary and Discussion of Acute Respiratory Illnesses .................... 7-20
 

7.4.	 PASSIVE SMOKING AND ACUTE AND CHRONIC
 

MIDDLE EAR DISEASES .................................................. 7-21
 

7.4.1. Recent Studies on Acute and Chronic Middle Ear Diseases .................. 7-22
 

v 
CONTENTS (continued) 

7.4.2. Summary and Discussion of Middle Ear Diseases .......................... 7-28
 

7.5.	 EFFECT OF PASSIVE SMOKING ON COUGH, PHLEGM,
 

AND WHEEZING ......................................................... 7-32
 

7.5.1. Recent Studies on the Effect of Passive Smoking on Cough,
 

Phlegm, and Wheezing ............................................... 7-32
 

7.5.2. Summary and Discussion on Cough, Phlegm, and
 

Wheezing .......................................................... 7-41
 

7.6. EFFECT OF PASSIVE SMOKING ON ASTHMA ............................... 7-45
 

7.6.1. Recent Studies on the Effect of Passive Smoking on
 

Asthma in Children .................................................. 7-46
 

7.6.2. Summary and Discussion on Asthma .................................... 7-53
 

7.7. ETS EXPOSURE AND SUDDEN INFANT DEATH SYNDROME ................. 7-54
 

7.8. PASSIVE SMOKING AND LUNG FUNCTION IN CHILDREN ................... 7-60
 

7.8.1. Recent Studies on Passive Smoking and Lung Function
 

in Children ......................................................... 7-60
 

7.8.2. Summary and Discussion on Pulmonary Function
 

in Children ......................................................... 7-68
 

7.9.	 PASSIVE SMOKING AND RESPIRATORY SYMPTOMS AND
 

LUNG FUNCTION IN ADULTS ............................................. 7-69
 

7.9.1. Recent Studies on Passive Smoking and Adult Respiratory
 

Symptoms and Lung Function ......................................... 7-70
 

7.9.2. Summary and Discussion on Respiratory Symptoms and
 

Lung Function in Adults .............................................. 7-74
 

8.	 ASSESSMENT OF INCREASED RISK FOR RESPIRATORY ILLNESSES IN
 

CHILDREN FROM ENVIRONMENTAL TOBACCO SMOKE ......................... 8-1
 

8.1. POSSIBLE ROLE OF CONFOUNDING ....................................... 8-1
 

8.2.	 MISCLASSIFICATION OF EXPOSED AND UNEXPOSED SUBJECTS ............ 8-2
 

8.2.1. Effect of Active Smoking in Children .................................... 8-2
 

8.2.2. Misreporting and Background Exposure ................................. 8-3
 

8.3. ADJUSTMENT FOR BACKGROUND EXPOSURE ............................. 8-4
 

8.4.	 ASSESSMENT OF RISK ................................................... 8-8
 

8.4.1. Asthma ........................................................... 8-8
 

8.4.2. Lower Respiratory Illness ............................................. 8-12
 

8.4.3. Sudden Infant Death Syndrome ........................................ 8-13
 

8.5. CONCLUSIONS .......................................................... 8-13
 

ADDENDUM: PERTINENT NEW STUDIES .......................................... ADD-1
 

APPENDIX A:	 REVIEWS AND TIER ASSIGNMENTS FOR EPIDEMIOLOGIC
 

STUDIES OF ETS AND LUNG CANCER ............................. A-1
 

APPENDIX B:	 METHOD FOR CORRECTING RELATIVE RISK FOR
 

SMOKER MISCLASSIFICATION .................................... B-1
 

vi 
CONTENTS (continued) 

APPENDIX C:	 LUNG CANCER MORTALITY RATES ATTRIBUTABLE TO
 

SPOUSAL ETS IN INDIVIDUAL EPIDEMIOLOGIC STUDIES ........... C-1
 

APPENDIX D: STATISTICAL FORMULAE ........................................ D-1
 

SELECTED BIBLIOGRAPHY ...................................................... R-1 
 

vii 
TABLES
 

3-1	 Distribution of constituents in fresh, undiluted mainstream smoke and
 

diluted sidestream smoke from nonfilter cigarettes ................................. 3-5
 

3-2 Example sidestream cigarette smoke deliveries .................................... 3-8
 

3-3 Tobacco-specific N-nitrosamines in indoor air (ng/m3) .............................. 3-17
 

3-4	 Weekly average concentrations of each measure of exposure by parental
 

smoking status in the cross-sectional study, Minnesota, 1989 ........................ 3-36
 

3-5	 Studies measuring personal exposure to airborne nicotine associated
 

with ETS for nonsmokers ..................................................... 3-37
 

3-6	 Studies measuring personal exposure to particulate matter associated
 

with ETS for nonsmokers ..................................................... 3-38
 

3-7	 Approximate relations of nicotine as the parameter between
 

nonsmokers, passive smokers, and active smokers ................................. 3-43
 

4-1	 Main characteristics of major cohort studies on the
 

relationship between smoking and cancer ........................................ 4-6
 

4-2 Lung cancer mortality ratios--prospective studies .................................. 4-8
 

4-3	 Lung cancer mortality ratios for men and women, by current
 

number of cigarettes smoked per day--prospective studies ........................... 4-9
 

4-4	 Relationship between risk of lung cancer and duration of smoking in
 

men, based on available information from cohort studies ............................ 4-11
 

4-5	 Lung cancer mortality ratios for males, by age of
 

smoking initiation--prospective studies .......................................... 4-12
 

4-6	 Relationship between risk of lung cancer and number of years
 

since stopping smoking, in men, based on available information
 

from cohort studies .......................................................... 4-13
 

4-7	 Relative risks of lung cancer in some large cohort studies among
 

men smoking cigarettes and other types of tobacco ................................. 4-15
 

4-8	 Age-adjusted lung cancer mortality ratios for males and females,
 

by tar and nicotine (T/N) in cigarettes smoked .................................... 4-17
 

4-9	 Relative risk for lung cancer by type of cigarette smoked (filter vs.
 

nonfilter), in men, based on cohort and case-control studies .......................... 4-17
 

viii
 
TABLES (continued) 

4-10	 Main results of studies dealing with the relationship between
 

smoking and different histological types of lung cancer ............................. 4-18
 

4-11 Lung cancer deaths attributable to tobacco smoking in certain countries ................ 4-24
 

5-1	 Epidemiologic studies on ETS and lung cancer in this report and
 

tier ranking ................................................................ 5-4
 

5-2 Studies by location, time, size, and ETS exposure ................................. 5-6
 

5-3 Case-control studies of ETS: characteristics ..................................... 5-8
 

5-4 Diagnosis, confirmation, and exclusion of lung cancer cases ......................... 5-12
 

5-5	 Estimated relative risk of lung cancer from spousal ETS
 

by epidemiologic study (crude and adjusted for cofactors) ........................... 5-16
 

5-6	 Effect of statistical adjustments for cofactors on risk estimates
 

for passive smoking ......................................................... 5-20
 

5-7	 Alternative estimates of lung cancer relative risks associated
 

with active and passive smoking ............................................... 5-23
 

5-8 Estimated correction for smoker misclassification ................................. 5-26
 

5-9	 Statistical measures by individual study and pooled by country,
 

corrected for smoker misclassification ........................................... 5-28
 

5-10 Statistical measures for highest exposure categories only ............................ 5-39
 

5-11 Exposure response trends for females ........................................... 5-41
 

5-12 Reported p-values of trend tests for ETS exposure by study ......................... 5-44
 

5-13 P-values of tests for effect and for trend by individual study ......................... 5-46
 

5-14 Other risk-related factors for lung cancer evaluated in selected studies ................. 5-52
 

5-15 Dietary effects in passive smoking studies of lung cancer in females ................... 5-57
 

5-16 Classification of studies by tier ................................................ 5-62
 

5-17 Summary data interpretation by tiers within country ................................ 5-64
 

ix 
TABLES (continued) 

6-1	 Definition and estimates of relative risk of lung cancer for 11 U.S. studies
 

combined for various exposure sources and baselines; population parameter
 

definitions and estimates used to calculate U.S. population-attributable
 

risk estimates for ETS ....................................................... 6-11
 

6-2	 Estimated female lung cancer mortality by attributable sources
 

for United States, 1985, using the pooled relative risk estimate
 

from 11 U.S. studies ......................................................... 6-18
 

6-3	 Female and male lung cancer mortality estimates by attributable
 

ETS sources for United States, 1985, using 11 U.S. studies
 

(never-smokers and former smokers who have quit 5+ years) ........................ 6-22
 

6-4	 Female lung cancer mortality estimates by attributable sources
 

for United States, 1985, using both the relative risk estimates
 

and Z values from the Fontham et al. (1991) study ................................. 6-24
 

6-5	 Female and male lung cancer mortality estimates by attributable
 

ETS sources for United States, 1985, using the Fontham et al. (1991) study
 

(never-smokers and former smokers who have quit 5+ years) ........................ 6-25
 

6-6	 Effect of single parameter changes on lung cancer mortality due to
 

ETS in never-smokers and former smokers who have quit 5+ years ................... 6-28
 

7-1	 Studies on respiratory illness referenced in the Surgeon General's
 

and National Research Council's reports of 1986 .................................. 7-11
 

7-2	 Recent epidemiologic studies of effects of passive smoking on
 

acute lower respiratory tract illnesses (LRIs) ..................................... 7-12
 

7-3	 Studies on middle ear diseases referenced in the Surgeon
 

General's report of 1986 ...................................................... 7-22
 

7-4	 Recent epidemiologic studies of effects of passive smoking on
 

acute and chronic middle ear diseases ........................................... 7-23
 

7-5	 Studies on chronic respiratory symptoms referenced in the Surgeon
 

General's and National Research Council's reports of 1986 .......................... 7-31
 

7-6	 Recent epidemiologic studies of effects of passive smoking on
 

cough, phlegm, and wheezing ................................................. 7-32
 

7-7	 Recent epidemiologic studies of effects of passive smoking on
 

asthma in childhood ......................................................... 7-45
 

x 
TABLES (continued) 

7-8	 Epidemiologic studies of effects of passive smoking on
 

incidence of sudden infant death syndrome (SIDS) ................................. 7-53
 

7-9	 Studies on pulmonary function referenced in the Surgeon General's
 

and National Research Council's reports of 1986 .................................. 7-58
 

7-10	 Recent epidemiologic studies on the effects of passive smoking
 

on lung function in children ................................................... 7-59
 

7-11	 Recent epidemiologic studies on the effects of passive smoking
 

on adult respiratory symptoms and lung function .................................. 7-65
 

8-1	 Adjusted relative risks for "exposed children." Adjusted or background
 

exposure based on body cotinine ratios between "exposed" and "unexposed"
 

and equation 8-1 ............................................................ 8-8
 

8-2	 Behavior variations in adjusted relative risks from equation 8-1 when the
 

observed relative risks and Z ratios are close together .............................. 8-9
 

8-3	 Range of estimates of adjusted relative risk and attributable
 

risk for asthma induction in children based on both threshold
 

and nonthreshold models ..................................................... 8-11
 

A-1 Study scores for tier assignments ............................................... A-8
 

A-2 Total scores and tier assignment ............................................... A-18
 

B-1	 Observed ratios of occasional smokers to current smokers
 

(based on cotinine studies) .................................................... B-4
 

B-2	 Examples, using five U.S. studies, of differences in smoker misclassification
 

bias between EPA estimates and those of P.N. Lee regarding passive smoking
 

relative risks for females ..................................................... B-5
 

B-3 Misclassification of female current smokers ...................................... B-7
 

B-4	 Misclassification of female former smokers reported as never-smokers
 

based on discordant answers .................................................. B-11
 

B-5 Misclassification of female lung cancer cases ..................................... B-12
 

B-6	 Deletions from the "never" columns in Tables B-13 and B-16 and
 

corrected elements .......................................................... B-13
 

B-7	 Notation for distribution of reported female lung cancer cases and
 

controls by husband's smoking status ........................................... B-15
 

xi
 
TABLES (continued) 

B-8 Notation for distribution of subjects by observed and true smoking status .............. B-15
 

B-9	 Observed ratios of female former smokers to ever-smokers in the U.S., U.K.,
 

and Swedish studies: populations or controls (numbers or percentage) ................. B-16
 

B-10	 Notation for observed lung cancer relative risks for exposed (k=1) and
 

nonexposed (k=0) wives by the wife's smoking status, using average
 

never-smoking wives RR(a)0 as the reference category .............................. B-18
 

B-11	 Prevalences and estimates of lung cancer risk associated with active
 

and passive smoking ......................................................... B-19
 

B-12	 Observed ratios of current smoker lung cancer risk to ever-smoker
 

risk for females ............................................................. B-23
 

B-13 Observed smoking prevalence among the controls--Correa example ................... B-26
 

B-14 Observed relative risks--Correa example ......................................... B-27
 

B-15 Crude case table, prevalence of cases by smoking status--Correa example .............. B-27
 

B-16	 Normalized case table, prevalence of cases by smoking status--
 

Correa example ............................................................. B-27
 

B-17	 Distribution of subjects by observed and true smoking status for wives
 

in Correa example .......................................................... B-28
 

C-1 Female lung cancer mortality from all causes in case-control studies ................... C-2
 

C-2	 Parameter values used to partition female lung cancer mortality
 

into component sources ...................................................... C-4
 

C-3 Female lung cancer mortality rates by attributable source ........................... C-6
 

C-4	 Lung cancer mortality rates of female ever-smokers (ES) and never-smokers (NS) 
 

by exposure status .......................................................... C-8
 

xii 
FIGURES
 

3-1	 Diagram for calculating the RSP mass from ETS emitted into any 

occupied space as a function of the smoking rate and removal rate (N) ................. 3-14 

3-2	 Diagram to calculate the ETS-associated RSP mass concentration in g/m3 

in a space as a function of total mass of ETS-generated RSP emitted in mg 

(determined from Figure 3-1) and the volume of a space ............................ 3-15 

3-3	 Range of average indoor concentrations for notable ETS contaminants associated 

with smoking occupancy of different indoor environments ........................... 3-16 

3-4	 Mean, standard deviation, and maximum and minimum nicotine values measured 

in different indoor environments with smoking occupancy ........................... 3-23 

3-5	 Mean, standard deviation, and maximum and minimum concentrations 

of RSP mass measured in different indoor environments for smoking and 

nonsmoking occupancy ...................................................... 3-26 

3-6	 Weeklong RSP mass and nicotine measurements in 96 residences 

with a mixture of sources. .................................................... 3-27 

3-7	 Range of average nicotine concentrations and range of maximum 

and minimum values measured by different indoor environments 

for smoking occupancy from studies shown in Figure 3-4 ........................... 3-28 

3-8	 Range of average RSP mass concentrations and range of maximum 

and minimum values measured by different indoor environments 

for smoking occupancy from studies shown in Figure 3-5 ........................... 3-29 

3-9	 Cumulative frequency distribution and arithmetic means of vapor-phase 

nicotine levels over a 1-week period in the main living area in residences 

in Onondaga and Suffolk Counties in New York State between January and 

April 1986 ................................................................ 3-31 

3-10	 Cumulative frequency distribution and arithmetic means of RSP mass levels by 

vapor-phase nicotine levels measured over a 1-week period in the main living 

area in residences in Onondaga and Suffolk Counties in New York State between 

January and April 1986 ...................................................... 3-31 

3-11 Monthly mean RSP mass concentrations in six U.S. cities ........................... 3-32 

3-12a	 Week-long nicotine concentrations measured in the main living area of 

96 residences versus the number of questionnaire-reported cigarettes smoked 

during the air-sampling period ................................................. 3-33 

xiii 
FIGURES (continued) 

3-12b	 Week-long RSP mass concentrations measured in the main living area
 

of 96 residences versus the number of questionnaire-reported cigarettes
 

smoked during the air-sampling period .......................................... 3-34
 

3-13	 Cumulative frequency distribution of RSP mass concentrations from
 

central site ambient and personal monitoring of smoke-exposed and
 

nonsmoke-exposed individuals ................................................ 3-39
 

3-14 Average cotinine t1⁄2 by age groups .............................................. 3-41
 

3-15	 Distribution of individual concentrations of urinary cotinine by degree
 

of self-reported exposure to ETS ............................................... 3-44
 

3-16	 Urinary cotinine concentrations by number of reported exposures to 
 

tobacco smoke in the past 4 days among 663 nonsmokers, Buffalo,
 

New York, 1986 ............................................................ 3-45
 

3-17	 Average cotinine/creatinine levels for subgroups of nonsmoking
 

women defined by sampling categories of exposure or by
 

self-reporting exposure to ETS from different sources during
 

the 4 days preceding collection of the urine sample ................................. 3-47
 

4-1	 Age-adjusted cancer death rates for selected sites, males,
 

United States, 1930-1986 .................................................... 4-3
 

4-2	 Age-adjusted cancer death rates for selected sites, females,
 

United States, 1930-1986 .................................................... 4-4
 

4-3	 Relative risk of lung cancer in ex-smokers, by number of years
 

quit, women, Cancer Prevention Study II ......................................... 4-14
 

5-1 Test statistics for hypothesis RR = 1, all studies ................................... 5-32
 

5-2 Test statistics for hypothesis RR = 1, USA only ................................... 5-32
 

5-3 Test statistics for hypothesis RR = 1, by country .................................. 5-33
 

5-4 Test statistics for hypothesis RR = 1, tiers 1-3 only ................................ 5-33
 

5-5 90% confidence intervals, by country ........................................... 5-35
 

5-6 90% confidence intervals, by country, tiers 1-3 only ................................ 5-35
 

xiv 
FOREWORD 1/19/93
 

xv
 
PREFACE 

This assessment of the respiratory health effects associated with passive smoking has been prepared 

by the Human Health Assessment Group, Office of Health and Environmental Assessment, Office of Research 

and Development, which is responsible for the report's scientific accuracy and conclusions. The assessment 

was prepared at the request of the Indoor Air Division, Office of Atmospheric and Indoor Air Programs, Office 

of Air and Radiation, which defined the assessment's scope and provided funding. 

The report has been developed under the authority of Title IV of Superfund (The Radon Gas and 

Indoor Air Quality Research Act of 1986) to provide information and guidance on the potential hazards of 

indoor air pollutants. 

Two drafts of this report were made available for public review and comments, the first in June 1990 

(reviewed by the Agency's Science Advisory Board [SAB] in December 1990) and a significantly revised draft 

in May 1992 (reviewed by the SAB in July 1992). This report reflects the comments received from those 

reviews. 

A comprehensive search of the scientific literature for this report is complete through September 1991. 

In addition, pertinent studies published through July 1992 have been included in the analysis in response to 

recommendations made by reviewers. 

Due to both resource and time constraints, the scope of this report has been limited to an analysis of 

respiratory effects, primarily lung cancer in nonsmoking adults and noncancer respiratory illnesses in children, 

with emphasis on the epidemiologic data. Further, because two thorough reviews on passive smoking were 

completed in 1986 (by the U.S. Surgeon General and the National Research Council), this document provides a 

summary of those reports with a more comprehensive analysis of the literature appearing subsequent to those 

reports and an integration of the results. 

xvi 
AUTHORS, CONTRIBUTORS, AND REVIEWERS 

This document was prepared by the Office of Health and Environmental Assessment (OHEA) within 

the Office of Research and Development, with major contract funding provided by the Indoor Air Division 

within the Office of Air and Radiation's Office of Atmospheric and Indoor Air Programs. Steven P. Bayard1 

was the OHEA project manager with overall responsibility for the contents of this report and its conclusions. 

Other OHEA staff members responsible for the scientific content of sections of this document are Jennifer 

Jinot1 and Aparna M. Koppikar.1 Jennifer Jinot and Steven Bayard were the scientific editors. 

AUTHORS 

Major portions of this revised report were prepared by ICF Incorporated, Fairfax, Virginia, under EPA 

Contract No. 68-00-0102. While OHEA staff provided technical editing and incorporated reviewers' 

comments into each chapter in an attempt to develop a comprehensive and consistent document, the following 

people were the primary authors: 

Chapter 1: Steven P. Bayard
 

Chapter 2: Jennifer Jinot
 

Chapter 3: Brian P. Leaderer2
 

Chapter 4: Jennifer Jinot
 

Chapters 5/6: Kenneth G. Brown3
 

Chapter 7: Fernando D. Martinez4
 

Chapter 8: Fernando D. Martinez and Steven P. Bayard
 

Appendix A: Kenneth G. Brown, Neal R. Simonsen,3 and A. Judson Wells3
 

Appendix B: A. Judson Wells
 

Appendix C: Kenneth G. Brown
 

Appendix D: Kenneth G. Brown and Neal R. Simonsen
 

1

Human Health Assessment Group, Office of Health and Environmental Assessment, U.S. EPA, 

Washington, DC 20460. 

2

J.B. Pierce Foundation Laboratory, Department of Epidemiology and Public Health, Yale 

University School of Medicine, New Haven, CT 06520. Subcontractor to ICF, Inc. 

3

Kenneth G. Brown, Inc., P.O. Box 16608, Chapel Hill, NC 27516. Subcontractor to ICF, Inc. 

4

Division of Respiratory Sciences, University of Arizona Medical Center, Tucson, AZ 85724. 

Subcontractor to ICF, Inc. 

xvii 
CONTRIBUTORS 

Numerous persons have provided helpful discussions or responded to requests for preprints, data, and 

other material relevant to this report. The authors are grateful to W.J. Blot, N. Britten, R.C. Brownson, P.A. 

Buffler, T.L. Butler, D.B. Coultas, K.M. Cummings, J. Fleiss, E.T.H. Fontham, Y.T. Gao, L. Garfinkel, S. 

Glantz, N.J. Haley, T. Hirayama, D.J. Hole, C. Humble, G.C. Kabat, J.C. Kleinman, G.J. Knight, L.C. Koo, M. 

Layard, M.D. Lebowitz, P.N. Lee, P. Macaskill, G.E. Palomaki, J.P. Pierce, J. Repace, H. Shimizu, W.F. 

Stewart, D. Trichopoulos, R.W. Wilson, and A. Wu-Williams. 

REVIEWERS 

This final report was preceded by two earlier drafts: an External Review Draft (EPA/600/6-90/006A) 

published in May 1990, and an SAB Review Draft (EPA/600/6-90/006B) published in May 1992. The 

External Review Draft was released for public review and comment on June 25, 1990, and was subsequently 

reviewed by the EPA Science Advisory Board (SAB) on December 4 and 5, 1990. The SAB Review Draft 

incorporated many of the public comments and especially the valuable advice presented in the SAB's April 19, 

1991, report to the Agency. In addition, many reviewers both within and outside the Agency provided 

assistance at various internal review stages. 

The second Review Draft also was reviewed by the SAB on July 21 and 22, 1992, which provided its 

report to the Agency on November 20, 1992. The authors wish to thank all those who sought to improve the 

quality of this report with their comments and are particularly grateful to the SAB for its advice. 

The following members of the SAB's Indoor Air Quality and Total Human Exposure Committee 

(IAQTHEC) participated in the reviews of the two Review Drafts. 

Chairman 

Dr. Morton Lippmann, Professor, Institute of Environmental Medicine, New York University 

Medical Center, Tuxedo, NY 10987 

Vice Chairman 

Dr. Jan A.J. Stolwijk, Professor, School of Medicine, Department of Epidemiology and Public 

Health, Yale University, 60 College Street, New Haven, CT 06510 

Members of the IAQTHEC 

Dr. Joan Daisey, Senior Scientist, Indoor Environment Program, Lawrence Berkeley Laboratory, 

One Cyclotron Road, Berkeley, CA 94720 

xviii 
Dr. Timothy Larson, Environmental Science and Engineering Program, Department of Civil 

Engineering, University of Washington, Seattle, WA 98195 (1992 review only) 

Dr. Victor G. Laties, Professor of Toxicology, Environmental Health Science Center, Box EHSC, 

University of Rochester School of Medicine, Rochester, NY 14642 

Dr. Paul Lioz, Department of Environmental and Community Medicine, Robert Wood Johnson 

School of Medicine, Piscataway, NJ 08854 (1992 review only) 

Dr. Jonathan M. Samet, Professor of Medicine, Department of Medicine, University of New 

Mexico School of Medicine, and New Mexico Tumor Registry, 900 Camino De Salud, NE, 

Albuquerque, NM 87131 

Dr. Jerome J. Wesolowski, Chief, Air and Industrial Hygiene Laboratory, California Department 

of Health, Berkeley, CA 94704 

Dr. James E. Woods, Jr., Professor of Building Construction, College of Architecture and Urban 

Studies, 117 Burress Hall, Virginia Polytechnic Institute and State University, Blacksburg, VA 

24061-0156 

Consultants to the IAQTHEC 

Dr. Neal L. Benowitz, Professor of Medicine, Chief, Division of Clinical Pharmacology and 

Experimental Therapeutics, University of California-San Francisco, Building 30, Fifth Floor, 

San Francisco General Hospital, 1001 Potrero Avenue, San Francisco, CA 94110 

Dr. William J. Blot, National Cancer Institute, 9000 Rockville Pike, Bethesda, MD 20892 (Federal 

Liaison to the Committee) 

Dr. David Burns, Associate Professor of Medicine, Department of Medicine, University of 

California, San Diego Medical Center, 225 Dickenson Street, San Diego, CA 92103-1990 

Dr. Delbert Eatough, Professor of Chemistry, Brigham Young University, Provo, UT 84602 

Dr. S. Katharine Hammond, Associate Professor, Environmental Health Sciences Program, 

Department of Family and Community Medicine, University of Massachusetts Medical School, 

55 Lake Avenue, North, Worcester, MA 06155 

Dr. Geoffrey Kabat, Senior Epidemiologist, American Health Foundation, 320 East 43rd Street, 

New York, NY 10017 

Dr. Michael D. Lebowitz, Professor of Internal Medicine, University of Arizona College of 

Medicine, Division of Respiratory Sciences, Tucson, AZ 85724 

Dr. Howard Rockette, Professor of Biostatistics, School of Public Health, 318 Parran Hall, 

University of Pittsburgh, Pittsburgh, PA 15261 

xix 
Dr. Scott T. Weiss, Channing Laboratory, Harvard University School of Medicine, 

Boston, MA 02115 

Acknowledgments 

The authors would like to acknowledge the contributions of several people who have made this report 

and the previous two drafts possible. Foremost is Robert Axelrad, Chief of the Indoor Air Division, Office of 

Air and Radiation, who provided the foresight, funding, and perseverance that made this effort possible. We 

also would like to thank the following people: 

Individuals from the Office of Health and Environmental Assessment's Technical Information
 

Staff who were responsible for the overall quality, coordination, organization, printing, and
 

distribution of these reports: Linda Bailey-Becht, Terri Konoza, Marie Pfaff, Michele Ranere,
 

and Judy Theisen. Also, Karen Sandidge from the Human Health Assessment Group for the
 

typing support that she provided.
 

Staff from R.O.W. Sciences, Inc., under the direction of Kay Marshall, who were responsible for
 

editing, word processing, and proofreading the final report.
 

Robert Flaak, Assistant Staff Director of the SAB, whose efforts and professionalism in
 

organizing and coordinating the two SAB reviews led to an improved and more useful product.
 

xx 
1. SUMMARY AND CONCLUSIONS 

1.1. MAJOR CONCLUSIONS 

Based on the weight of the available scientific evidence, the U.S. Environmental 

Protection Agency (EPA) has concluded that the widespread exposure to environmental tobacco 

smoke (ETS) in the United States presents a serious and substantial public health impact. 

In adults: 

ETS is a human lung carcinogen, responsible for approximately 3,000 lung 

cancer deaths annually in U.S. nonsmokers. 

In children: 

ETS exposure is causally associated with an increased risk of lower respiratory 

tract infections (LRIs) such as bronchitis and pneumonia. This report estimates 

that 150,000 to 300,000 cases annually in infants and young children up to 18 

months of age are attributable to ETS. 

ETS exposure is causally associated with increased prevalence of fluid in the middle 

ear, symptoms of upper respiratory tract irritation, and a small but significant 

reduction in lung function. 

ETS exposure is causally associated with additional episodes and increased 

severity of symptoms in children with asthma. This report estimates that 200,000 

to 1,000,000 asthmatic children have their condition worsened by exposure to 

ETS. 

ETS exposure is a risk factor for new cases of asthma in children who have not 

previously displayed symptoms. 

1-1 
1.2. BACKGROUND 

Tobacco smoking has long been recognized (e.g., U.S. Department of Health, Education, and Welfare [U.S. 

DHEW], 1964) as a major cause of mortality and morbidity, responsible for an estimated 434,000 deaths per year in 

the United States (Centers for Disease Control [CDC], 1991a).  Tobacco use is known to cause cancer at various sites, 

in particular the lung (U.S. Department of Health and Human Services [U.S. DHHS], 1982; International Agency for 

Research on Cancer [IARC], 1986).  Smoking can also cause respiratory diseases (U.S. DHHS, 1984, 1989) and is a 

major risk factor for heart disease (U.S. DHHS, 1983).  In recent years, there has been concern that nonsmokers may 

also be at risk for some of these health effects as a result of their exposure ("passive smoking") to the tobacco smoke 

that occurs in various environments occupied by smokers.  Although this ETS is dilute compared with the mainstream 

smoke (MS) inhaled by active smokers, it is chemically similar, containing many of the same carcinogenic and toxic 

agents. 

In 1986, the National Research Council (NRC) and the Surgeon General of the U.S. Public Health Service 

independently assessed the health effects of exposure to ETS (NRC, 1986; 

U.S. DHHS, 1986).  Both of the 1986 reports conclude that ETS can cause lung cancer in adult nonsmokers and that 

children of parents who smoke have increased frequency of respiratory symptoms and acute lower respiratory tract 

infections, as well as evidence of reduced lung function. 

More recent epidemiologic studies of the potential associations between ETS and lung cancer in nonsmoking 

adults and between ETS and noncancer respiratory effects more than double the size of the database available for 

analysis from that of the 1986 reports.  This EPA report critically reviews the current database on the respiratory 

health effects of passive smoking; these data are utilized to develop a hazard identification for ETS and to make 

quantitative estimates of the public health impacts of ETS for lung cancer and various other respiratory diseases. 

The weight-of-evidence analysis for the lung cancer hazard identification is developed in accordance with 

U.S. EPA's Guidelines for Carcinogen Risk Assessment (U.S. EPA, 1986a) and established principles for evaluating 

epidemiologic studies.  The analysis considers animal bioassays and genotoxicity studies, as well as biological 

measurements of human uptake of tobacco smoke components and epidemiologic data on active and passive smoking. 

The availability of abundant and consistent human data, especially human data at actual environmental levels of 

exposure to the specific agent (mixture) of concern, allows a hazard identification to be made with a high degree of 

certainty.  The conclusive evidence of the dose-related lung carcinogenicity of MS in active smokers (Chapter 4), 

coupled with information on the chemical similarities of MS and ETS and evidence of ETS uptake in nonsmokers 

(Chapter 3), is sufficient by itself to establish ETS as a known human lung carcinogen, or "Group A" carcinogen 

under U.S. EPA's carcinogen classification system.  In addition, this document concludes that the overall results of 30 

epidemiologic studies on lung cancer and passive smoking (Chapter 5), using spousal smoking as a surrogate of ETS 

exposure for female never-smokers, similarly justify a Group A classification. 

The weight-of-evidence analyses for the noncancer respiratory effects are based primarily on a review of 

epidemiologic studies (Chapter 7).  Most of the endpoints examined are respiratory disorders in children, where 

1-2 
parental smoking is used as a surrogate of ETS exposure.  For the noncancer respiratory effects in nonsmoking adults, 

most studies used spousal smoking as an exposure surrogate.  A causal association was concluded to exist for a 

number of respiratory disorders where there was sufficient consistent evidence for a biologically plausible association 

with ETS that could not be explained by bias, confounding, or chance.  The fact that the database consists of human 

evidence from actual environmental exposure levels gives a high degree of confidence in this conclusion.  Where 

there was suggestive but inconclusive evidence of causality, as was the case for asthma induction in children, ETS was 

concluded to be a risk factor for that endpoint.  Where data were inconsistent or inadequate for evaluation of an 

association, as for acute upper respiratory tract infections and acute middle ear infections in children, no conclusions 

were drawn. 

This report also has attempted to provide estimates of the extent of the public health impact, where 

appropriate, in terms of numbers of ETS-attributable cases in nonsmoking subpopulations.  Unlike for qualitative 

hazard identification assessments, where information from many sources adds to the confidence in a weight-ofevidence conclusion, for quantitative risk assessments, the usefulness of studies usually depends on how closely the 

study population resembles nonsmoking segments of the general population.  For lung cancer estimates among U.S. 

nonsmokers, the substantial epidemiology database of ETS and lung cancer among U.S. female never-smokers was 

considered to provide the most appropriate information.  From these U.S. epidemiology studies, a pooled relative risk 

estimate was calculated and used in the derivation of the population risk estimates.  The large number of studies 

available, the generally consistent results, and the condition of actual environmental levels of exposure increase the 

confidence in these estimates.  Even under these circumstances, however, uncertainties remain, such as in the use of 

questionnaires and current biomarker measurements to estimate past exposure, assumptions of exposure-response 

linearity, and extrapolation to male never-smokers and to ex-smokers.  Still, given the strength of the evidence for the 

lung carcinogenicity of tobacco smoke and the extensive human database from actual environmental exposure levels, 

fewer assumptions are necessary than is usual in EPA quantitative risk assessments, and confidence in these estimates 

is rated medium to high. 

Population estimates of ETS health impacts are also made for certain noncancer respiratory endpoints in 

children, specifically lower respiratory tract infections (i.e., pneumonia, bronchitis, and bronchiolitis) and episodes 

and severity of attacks of asthma.  Estimates of ETS-attributable cases of LRI in infants and young children are 

thought to have a high degree of confidence because of the consistent study findings and the appropriateness of 

parental smoking as a surrogate measure of exposure in very young children.  Estimates of the number of asthmatic 

children whose condition is aggravated by exposure to ETS are less certain than those for LRIs because of different 

measures of outcome in various studies and because of increased extraparental exposure to ETS in older children. 

Estimates of the number of new cases of asthma in previously asymptomatic children also have less confidence 

because at this time the weight of evidence for asthma induction, while suggestive of a causal association, is not 

conclusive. 

1-3 
Most of the ETS population impact estimates are presented in terms of ranges, which are thought to reflect 

reasonable assumptions about the estimates of parameters and variables required for the extrapolation models.  The 

validity of the ranges is also dependent on the appropriateness of the extrapolation models themselves. 

While this report focuses only on the respiratory health effects of passive smoking, there also may be other 

health effects of concern.  Recent analyses of more than a dozen epidemiology and toxicology studies (e.g., Steenland, 

1992; National Institute for Occupational Safety and Health [NIOSH], 1991) suggest that ETS exposure may be a risk 

factor for cardiovascular disease.  In addition, a few studies in the literature link ETS exposure to cancers of other 

sites; at this time, that database appears inadequate for any conclusion.  This report does not develop an analysis of 

either the nonrespiratory cancer or the heart disease data and takes no position on whether ETS is a risk factor for 

these diseases.  If it is, the total public health impact from ETS will be greater than that discussed here. 

1.3. PRIMARY FINDINGS 

A.  Lung Cancer in Nonsmoking Adults 

1. 	 Passive smoking is causally associated with lung cancer in adults, and ETS, by the total weight of 

evidence, belongs in the category of compounds classified by EPA as Group A (known human) 

carcinogens. 

2. 	 Approximately 3,000 lung cancer deaths per year among nonsmokers (never-smokers and former 

smokers) of both sexes are estimated to be attributable to ETS in the United States.  While there 

are statistical and modeling uncertainties in this estimate, and the true number may be higher or 

lower, the assumptions used in this analysis would tend to underestimate the actual population 

risk.  The overall confidence in this estimate is medium to high. 

B.  Noncancer Respiratory Diseases and Disorders 

1.  Exposure of children to ETS from parental smoking is causally associated with: 

a. 	 increased prevalence of respiratory symptoms of irritation (cough, sputum, and 

wheeze), 

b.  increased prevalence of middle ear effusion (a sign of middle ear disease), and 

c. 	 a small but statistically significant reduction in lung function as tested by objective 

measures of lung capacity. 

2. 	 ETS exposure of young children and particularly infants from parental (and especially mother's) 

smoking is causally associated with an increased risk of LRIs (pneumonia, bronchitis, and 

bronchiolitis).  This report estimates that exposure to ETS contributes 150,000 to 300,000 LRIs 

annually in infants and children less than 18 months of age, resulting in 7,500 to 15,000 

hospitalizations.  The confidence in the estimates of LRIs is high.  Increased risks for LRIs 

continue, but are lower in magnitude, for children until about age 3; however, no estimates are 

derived for children over 18 months. 

1-4 
3. 	 a.  Exposure to ETS is causally associated with additional episodes and increased severity of 

asthma in children who already have the disease.  This report estimates that ETS exposure 

exacerbates symptoms in approximately 20% of this country's 2 million to 5 million 

asthmatic children and is a major aggravating factor in approximately 10%. 

b. 	 In addition, the epidemiologic evidence is suggestive but not conclusive that ETS exposure 

increases the number of new cases of asthma in children who have not previously exhibited 

symptoms.  Based on this evidence and the known ETS effects on both the immune system 

and lungs (e.g., atopy and airway hyperresponsiveness), this report concludes that ETS is a 

risk factor for the induction of asthma in previously asymptomatic children.  Data suggest 

that relatively high levels of exposure are required to induce new cases of asthma in 

children.  This report calculates that previously asymptomatic children exposed to ETS 

from mothers who smoke at least 10  cigarettes per day will exhibit an estimated 8,000 to 

26,000 new cases of asthma annually.  The confidence in this range is medium and is 

dependent on the conclusion that ETS is a risk factor for asthma induction. 

4.  Passive smoking has subtle but significant effects on the respiratory health of nonsmoking adults, 

including coughing, phlegm production, chest discomfort, and reduced lung function. 

This report also has reviewed data on the relationship of maternal smoking and sudden infant death 

syndrome (SIDS), which is thought to involve some unknown respiratory pathogenesis.  The report concludes that 

while there is strong evidence that infants whose mothers smoke are at an increased risk of dying from SIDS, 

available studies do not allow us to differentiate whether and to what extent this increase is related to in utero versus 

postnatal exposure to tobacco smoke products.  Consequently, this report is unable to assert whether or not ETS 

exposure by itself is a risk factor for SIDS independent of smoking during pregnancy.  Regarding an association 

of parental smoking with either upper respiratory tract infections (colds and sore throats) or acute middle ear 

infections in children, this report finds the evidence inconclusive. 

1.3.1. ETS and Lung Cancer 

1.3.1.1. Hazard Identification 

The Surgeon General (U.S. DHHS, 1989) estimated that smoking was responsible for more than one of 

every six deaths in the United States and that it accounted for about 90% of the lung cancer deaths in males and about 

80% in females in 1985.  Smokers, however, are not the only ones exposed to tobacco smoke.  The sidestream smoke 

(SS) emitted from a smoldering cigarette between puffs (the main component of ETS) has been documented to 

contain virtually all of the same carcinogenic compounds (known and suspected human and animal carcinogens) that 

have been identified in the mainstream smoke (MS) inhaled by smokers (Chapter 3).  Exposure concentrations of 

these carcinogens to passive smokers are variable but much lower than for active smokers.  An excess cancer risk 

from passive smoking, however, is biologically plausible. 

1-5 
Based on the firmly established causal association of lung cancer with active smoking with a dose-response 

relationship down to low doses (Chapter 4), passive smoking is considered likely to affect the lung similarly.  The 

widespread presence of ETS in both home and workplace and its absorption by nonsmokers in the general population 

have been well documented by air sampling and by body measurement of biomarkers such as nicotine and cotinine 

(Chapter 3).  This raises the question of whether any direct evidence exists for the relationship between ETS exposure 

and lung cancer in the general population and what its implications may be for public health.  This report addresses 

that question by reviewing and analyzing the evidence from 30 epidemiologic studies of effects from normally 

occurring environmental levels of ETS (Chapter 5).  Because there is widespread exposure and it is difficult to 

construct a truly unexposed subgroup of the general population, these studies attempt to compare individuals with 

higher ETS exposure to those with lower exposures.  Typically, female never-smokers who are married to a smoker 

are compared with female never-smokers who are married to a nonsmoker.  Some studies also consider ETS exposure 

of other subjects (i.e., male never-smokers and long-term former smokers of either sex) and from other sources (e.g., 

workplace and home exposure during childhood), but these studies are fewer and represent fewer cases, and they are 

generally excluded from the analysis presented here.  Use of the female never-smoker studies provides the largest, 

most homogeneous database for analysis to determine whether an ETS effect on lung cancer is present.  This report 

assumes that the results for female never-smokers are generalizable to all nonsmokers. 

Given that ETS exposures are at actual environmental levels and that the comparison groups are both 

exposed to appreciable background (i.e., nonspousal) ETS, any excess risk for lung cancer from exposure to spousal 

smoke would be expected to be small.  Furthermore, the risk of lung cancer is relatively low in nonsmokers, and most 

studies have a small sample size, resulting in a very low statistical power (probability of detecting a real effect if it 

exists).  Besides small sample size and low incremental exposures, other problems inherent in several of the studies 

may also limit their ability to detect a possible effect.  Therefore, this report examines the data in several different 

ways.  After downward adjustment of the relative risks for smoker misclassification bias, the studies are individually 

assessed for strength of association, both for the overall data and for the highest exposure group when exposure-level 

data are available, and for exposure-response trend.  Then the study results are pooled by country using statistical 

techniques for combining data, including both positive and nonpositive results, to increase the ability to determine 

whether or not there is an association between ETS and lung cancer.  Finally, in addition to the previous statistical 

analyses that weight the studies only by size, regardless of design and conduct, the studies are qualitatively evaluated 

for potential confounding, bias, and likely utility to provide information about any lung carcinogenicity of ETS. 

Based on these qualitative considerations, the studies are categorized into one of four tiers and then statistically 

analyzed successively by tier. 

Results from all of the analyses described above strongly support a causal association between lung cancer 

ETS exposure.  The overall proportion (9/30) of individual studies found to show an association between lung cancer 

-4 and spousal ETS exposure at all levels combined is unlikely to occur by chance (p < 10  ).  When the analysis focuses 

on higher levels of spousal exposure, every one of the 17 studies with exposure-level data shows increased risk in the 

1-6 
highest exposure group; 9 of these are significant at the p < 0.05 level, despite most having low power, another result 

-7 highly unlikely to occur by chance (p < 10  ).  Similarly, the proportion (10/14; 


p < 10-9) showing a statistically significant exposure-response trend is highly supportive of a causal association. 


Combined results by country showed statistically significant associations for Greece 

(2 studies), Hong Kong (4 studies), Japan (5 studies), and the United States (11 studies), and in that order of strength 

of relative risk.  Pooled results of the four Western European studies (three countries) actually showed a slightly 

stronger association than that of the United States, but it was not statistically significant, probably due to the smaller 

sample size.  The combined results of the Chinese studies do not show an association between ETS and lung cancer; 

however, two of the four Chinese studies were designed mainly to determine the lung cancer effects of high levels of 

other indoor air pollutants indigenous to those areas, which would obscure a smaller ETS effect.  These two Chinese 

studies do, however, provide very strong evidence on the lung carcinogenicity of these other indoor air pollutants, 

which contain many of the same components as ETS.  When results are combined only for the other two Chinese 

studies, they demonstrate a statistically significant association for ETS and lung cancer. 

The heterogeneity of observed relative risk estimates among countries could result from several factors.  For 

example, the observed differences may reflect true differences in lung cancer rates for never-smokers, in ETS 

exposure levels from nonspousal sources, or in related lifestyle characteristics in different countries.  For the time 

period in which ETS exposure was of interest for these studies, spousal smoking is considered to be a better surrogate 

for ETS exposure in more "traditional" societies, such as Japan and Greece, than in the United States.  In the United 

States, other sources of ETS exposure (e.g., work and public places) are generally higher, which obscures the effects 

of spousal smoking and may explain the lower relative risks observed in the United States.  Nevertheless, despite 

observed differences between countries, all showed evidence of increased risk. 

Based on these analyses and following the U.S. EPA's Guidelines for Carcinogen Risk Assessment (U.S. 

EPA, 1986a), EPA concludes that environmental tobacco smoke is a Group A (known human) carcinogen.  This 

conclusion is based on a total weight of evidence, principally: 

Biological plausibility.  ETS is taken up by the lungs, and components are distributed throughout the 


body.  The presence of the same carcinogens in ETS and MS, along with the established causal 


relationship between lung cancer and active smoking with the dose-response relationships exhibited 


down to low doses, establishes the plausibility that ETS is also a lung carcinogen. 


Supporting evidence from animal bioassays and genotoxicity experiments.  The carcinogenicity of 


tobacco smoke has been demonstrated in lifetime inhalation studies in the hamster, intrapulmonary 


implantations in the rat, and skin painting in the mouse.  There are no lifetime animal inhalation studies 


of ETS; however, the carcinogenicity of SS condensates has been shown in intrapulmonary 


implantations and skin painting experiments.  Positive results of genotoxicity testing for both MS and 


ETS provide corroborative evidence for their carcinogenic potential. 


1-7 
Consistency of response.  All 4 of the cohort studies and 20 of the 26 case-control studies observed a 


higher risk of lung cancer among the female never-smokers classified as ever exposed to any level of 


spousal ETS.  Furthermore, every one of the 17 studies with response categorized by exposure level 


demonstrated increased risk for the highest exposure group.  When assessment was restricted to the 19 


studies judged to be of higher utility based on study design, execution, and analysis (Appendix A), 17 


observed higher risks, and 6 of these increases were statistically significant, despite most having low 


statistical power.  Evaluation of the total study evidence from several perspectives leads to the 


conclusion that the observed association between ETS exposure and increased lung cancer occurrence 


is not attributable to chance. 


Broad-based evidence.  These 30 studies provide data from 8 different countries, employ a wide variety 


of study designs and protocols, and are conducted by many different research teams.  Results from all 


countries, with the possible exception of two areas of China where high levels of other indoor air lung 


carcinogens were present, show small to modest increases in lung cancer associated with spousal ETS 


exposure.  No alternative explanatory variables for the observed association between ETS and lung 


cancer have been indicated that would be broadly applicable across studies. 


Upward trend in exposure-response.  Both the largest of the cohort studies--the Japanese study of 


Hirayama with 200 lung cancer cases--and the largest of the case-control studies--the U.S. study by 


Fontham and associates (1991) with 420 lung cancer cases and two sets of controls--demonstrate a 


strong exposure-related statistical association between passive smoking and lung cancer.  This upward 


trend is well supported by the preponderance of epidemiology studies.  Of the 14 studies that provide 


sufficient data for a trend test by exposure level, 10 were statistically significant despite most having 


low statistical power. 


Detectable association at environmental exposure levels.  Within the population of married women who 


are lifelong nonsmokers, the excess lung cancer risk from exposure to their smoking husbands' ETS is 


large enough to be observed, even for all levels of their spousal exposure combined.  Carcinogenic 


responses are usually detectable only in high-exposure circumstances, such as occupational settings, or 


in experimental animals receiving very high  doses.  In addition, effects are harder to observe when 


there is substantial background exposure in the comparison groups, as is the case here. 


Effects remain after adjustment for potential upward bias.  Current and ex-smokers may be misreported 


as never-smokers, thus inflating the apparent cancer risk for ETS exposure.  The evidence remains 


statistically significant and conclusive, however, after adjustments for smoker misclassification.  For the 


United States, the summary estimate of relative risk from nine case-control plus two cohort studies is 


1.19 (90% confidence interval [C.I.] = 1.04, 1.35; p < 0.05) after adjustment for smoker 


misclassification.  For Greece, 2.00 (1.42, 2.83), Hong Kong, 1.61 (1.25, 2.06), and Japan, 1.44 (1.13, 


1-8 
1.85), the estimated relative risks are higher than those of the United States and more highly significant 


after adjusting for the potential bias. 


Strong associations for highest exposure groups.  Examining the groups with the highest exposure 


levels increases the ability to detect an effect, if it exists.  Nine of the sixteen studies worldwide for 


which there are sufficient exposure-level data are statistically significant for the highest exposure 


group, despite most having low statistical power.  The overall pooled estimate of 1.81 for the highest 


exposure groups is highly statistically significant (90% C.I. = 1.60, 2.05; p < 10-6).  For the United 


States, the overall pooled estimate of 1.38 (seven studies, corrected for smoker misclassification bias) is 


also highly statistically significant (90% C.I. = 1.13, 1.70; p = 0.005). 


Confounding cannot explain the association.  The broad-based evidence for an association found by 


independent investigators across several countries, as well as the positive exposure-response trends 


observed in most of the studies that analyzed for them, make any single confounder highly unlikely as 


an explanation for the results.  In addition, this report examined potential confounding factors (history 


of lung disease, home heat sources, diet, occupation) and concluded that none of these factors could 


account for the observed association between lung cancer and ETS. 


1.3.1.2. Estimation of Population Risk 

The individual risk of lung cancer from exposure to ETS does not have to be very large to translate into a 

significant health hazard to the U.S. population because of the large number of smokers and the widespread presence 

of ETS.  Current smokers comprise approximately 26% of the U.S. adult population and consume more than one-half 

trillion cigarettes annually (1.5 packs per day, on average), causing nearly universal exposure to at least some ETS. 

As a biomarker of tobacco smoke uptake, cotinine, a metabolite of the tobacco-specific compound nicotine, is 

detectable in the blood, saliva, and urine of persons recently exposed to tobacco smoke.  Cotinine has typically been 

detected in 50% to 75% of reported nonsmokers tested (50% equates to 63 million U.S. nonsmokers age 18 or older). 

The best estimate of approximately 3,000 lung cancer deaths per year in U.S. nonsmokers age 35 and over 

attributable to ETS (Chapter 6) is based on data pooled from all 11 U.S. epidemiologic studies of never-smoking 

women married to smoking spouses.  Use of U.S. studies should increase the confidence in these estimates.  Some 

mathematical modeling is required to adjust for expected bias from misclassification of smoking status and to account 

for ETS exposure from sources other than spousal smoking.  The overall relative risk estimate of 1.19 for the 

United States, already adjusted for smoker misclassification bias, becomes 1.59 after adjusting for background ETS 

sources (1.34 for nonspousal exposures only).  Assumptions are also needed to relate responses in female neversmokers to those in male never-smokers and ex-smokers of both sexes, and to estimate the proportion of the 

nonsmoking population exposed to various levels of ETS.  Overall, however, the assumptions necessary for 

estimating risk add far less uncertainty than other EPA quantitative assessments.  This is because the extrapolation for 

1-9 
ETS is based on a large database of human studies, all at levels actually expected to be encountered by much of the 

U.S. population. 

The components of the 3,000 lung cancer deaths figure include approximately 1,500 female never-smokers, 

500 male never-smokers, and 1,000 former smokers of both sexes.  More females are estimated to be affected because 

there are more female than male nonsmokers.  These component estimates have varying degrees of confidence; the 

estimate of 1,500 deaths for female never-smokers has the highest confidence because of the extensive database.  The 

estimate of 500 for male never-smokers is less certain because it is based on the female never-smoker response and is 

thought to be low because males are generally subject to higher background ETS exposures than females.  Adjustment 

for this higher background exposure would lead to higher risk estimates.  The estimate of 1,000 lung cancer deaths for 

former smokers of both sexes is considered to have the lowest confidence, and the assumptions used are thought to 

make this estimate low as well. 

Workplace ETS levels are generally comparable with home ETS levels, and studies using body cotinine 

measures as biomarkers demonstrate that nonspousal exposures to ETS are often greater than exposure from spousal 

smoking.  Thus, this report presents an alternative breakdown of the estimated 3,000 ETS-attributable lung cancer 

deaths between spousal and nonspousal exposures.  By extension of the results from spousal smoking studies, coupled 

with biological measurements of exposure, more lung cancer deaths are estimated to be attributable to ETS from 

combined nonspousal exposures--2,200 of both sexes--than from spousal exposure--800 of both sexes.  This spouseversus-other-sources partitioning depends on current exposure estimates that may or may not be applicable to the 

exposure period of interest.  Thus, this breakdown contains this element of uncertainty in addition to those discussed 

above with respect to the previous breakdown. 

An alternative analysis, based on the large Fontham et al. (1991) study, which is the only study that provides 

biomarker estimates of both relative risk and ETS exposure, yields population risk point estimates of 2,700 and 3,600. 

These population risk estimates are highly consistent with the estimate of 3,000 based on the combined U.S. studies. 

While there is statistical variance around all of the parameters used in the quantitative assessment, the two 

largest areas of uncertainty are probably associated with the relative risk estimate for spousal ETS exposure and the 

parameter estimate for the background ETS exposure adjustment.  A sensitivity analysis that independently varies 

these two estimates yields population risk estimates as low as 400 and as high as 7,000.  These extremes, however, are 

considered unlikely; the more probable range is narrower, and the generally conservative assumptions employed 

suggest that the actual population risk number may be greater than 3,000.  Overall, considering the multitude, 

consistency, and quality of all these studies, the weight-of-evidence conclusion that ETS is a known human lung 

carcinogen, and the limited amount of extrapolation necessary, the confidence in the estimate of approximately 3,000 

lung cancer deaths is medium to high. 

1-10 
1.3.2. ETS and Noncancer Respiratory Disorders 

Exposure to ETS from parental smoking has been previously linked with increased respiratory disorders in 

children, particularly in infants.  Several studies have confirmed the exposure and uptake of ETS in children by 

assaying saliva, serum, or urine for cotinine.  These cotinine concentrations were highly correlated with smoking 

(especially by the mother) in the child's presence.  Nine to twelve million American children under 5 years of age, or 

one-half to two-thirds of all children in this age group, may be exposed to cigarette smoke in the home (American 

Academy of Pediatrics, 1986; Overpeck and Moss, 1991). 

With regard to the noncancer respiratory effects of passive smoking, this report focuses on epidemiologic 

evidence appearing since the two major reports of 1986 (NRC and U.S. DHHS) that bears on the potential association 

of parental smoking with detrimental respiratory effects in their children.  These effects include symptoms of 

respiratory irritation (cough, sputum production, or wheeze); acute diseases of the lower respiratory tract (pneumonia, 

bronchitis, and bronchiolitis); acute middle ear infections and indications of chronic middle ear infections 

(predominantly middle ear effusion); reduced lung function (from forced expiratory volume and flow-rate 

measurements); incidence and prevalence of asthma and exacerbation of symptoms in asthmatics; and acute upper 

respiratory tract infections (colds and sore throats).  The more than 50 recently published studies reviewed here 

essentially corroborate the previous conclusions of the 1986 reports of the NRC and Surgeon General regarding 

respiratory symptoms, respiratory illnesses, and pulmonary function, and they strengthen support for those 

conclusions by the additional weight of evidence (Chapter 7).  For example, new data on middle ear effusion 

strengthen previous evidence to warrant the stronger conclusion in this report of a causal association with parental 

smoking.  Furthermore, recent studies establish associations between parental smoking and increased incidence of 

childhood asthma.  Additional research also supports the hypotheses that in utero exposure to mother's smoke and 

postnatal exposure to ETS alter lung function and structure, increase bronchial responsiveness, and enhance the 

process of allergic sensitization, changes that are known to predispose children to early respiratory illness.  Early 

respiratory illness can lead to long-term pulmonary effects (reduced lung function and increased risk of chronic 

obstructive lung disease). 

This report also summarizes the evidence for an association between parental smoking and SIDS, which was 

not addressed in the 1986 reports of the NRC or Surgeon General.  SIDS is the most common cause of death in 

infants ages 1 month to 1 year.  The cause (or causes) of SIDS is unknown; however, it is widely believed that some 

form of respiratory pathogenesis is generally involved.  The current evidence strongly suggests that infants whose 

mothers smoke are at an increased risk of dying of SIDS, independent of other known risk factors for SIDS, including 

low birthweight and low gestational age, which are specifically associated with active smoking during pregnancy. 

However, available studies do not allow this report to conclude whether that increased risk is related to in utero versus 

postnatal exposure to tobacco smoke products, or to both. 

The 1986 reports of the NRC and Surgeon General conclude that both the prevalence of respiratory 

symptoms of irritation and the incidence of lower respiratory tract infections are higher in children of smoking 

1-11 
parents.  In the 18 studies of respiratory symptoms subsequent to the 2 reports, increased symptoms (cough, phlegm 

production, and wheezing) were observed in a range of ages from birth to midteens, particularly in infants and 

preschool children.  In addition to the studies on symptoms of respiratory irritation, 10 new studies have addressed the 

topic of parental smoking and acute lower respiratory tract illness in children, and 9 have reported statistically 

significant associations.  The cumulative evidence is conclusive that parental smoking, especially the mother's, causes 

an increased incidence of respiratory illnesses from birth up to the first 18 months to 3 years of life, particularly for 

bronchitis, bronchiolitis, and pneumonia.  Overall, the evidence confirms and strengthens the previous conclusions of 

the NRC and Surgeon General. 

Recent studies also solidify the evidence for the conclusion of a causal association between parental smoking 

and increased middle ear effusion in young children.  Middle ear effusion is the most common reason for 

hospitalization of young children for an operation. 

At the time of the Surgeon General's report on passive smoking (U.S. DHHS, 1986), data were sufficient to 

conclude only that maternal smoking may influence the severity of asthma in children.  The recent studies reviewed 

here strengthen and confirm these exacerbation effects.  The new evidence is also conclusive that ETS exposure 

increases the number of episodes of asthma in children who already have the disease.  In addition, the evidence is 

suggestive that ETS exposure increases the number of new cases of asthma in children who have not previously 

exhibited symptoms, although the results are statistically significant only with children whose mothers smoke 10 or 

more cigarettes per day.  While the evidence for new cases of asthma itself is not conclusive of a causal association, 

the consistently strong association of ETS both with increased frequency and severity of the asthmatic symptoms and 

with the established ETS effects on the immune system and airway hyperresponsiveness lead to the conclusion that 

ETS is a risk factor for induction of asthma in previously asymptomatic children. 

Regarding the effects of passive smoking on lung function in children, the 1986 NRC and Surgeon General 

reports both conclude that children of parents who smoke have small decreases in tests of pulmonary output function 

of both the larger and smaller air passages when compared with the children of nonsmokers.  As noted in the NRC 

report, if ETS exposure is the cause of the observed decrease in lung function, the effect could be due to the direct 

action of agents in ETS or an indirect consequence of increased occurrence of acute respiratory illness related to ETS. 

Results from eight studies on ETS and lung function in children that have appeared since those reports add 

some additional confirmatory evidence suggesting a causal rather than an indirect relationship.  For the population as 

a whole, the reductions are small relative to the interindividual variability of each lung function parameter.  However, 

groups of particularly susceptible or heavily exposed children have shown larger decrements.  The studies reviewed 

suggest that a continuum of exposures to tobacco products starting in fetal life may contribute to the decrements in 

lung function found in older children.  Exposure to tobacco smoke products inhaled by the mother during pregnancy 

may contribute significantly to these changes, but there is strong evidence indicating that postnatal exposure to ETS is 

an important part of the causal pathway. 

1-12 
With respect to lung function effects in adults exposed to ETS, the 1986 NRC and Surgeon General reports 

found the data at that time inconclusive, due to high interindividual variability and the existence of a large number of 

other risk factors, but compatible with subtle deficits in lung function.  Recent studies confirm the association of 

passive smoking with small reductions in lung function.  Furthermore, new evidence also has emerged suggesting a 

subtle association between exposure to ETS and increased respiratory symptoms in adults. 

Some evidence suggests that the incidence of acute upper respiratory tract illnesses and acute middle ear 

infections may be more common in children exposed to ETS.  However, several studies failed to find any effect.  In 

addition, the possible role of confounding factors, the lack of studies showing clear dose-response relationships, and 

the absence of a plausible biological mechanism preclude more definitive conclusions. 

In reviewing the available evidence indicating an association (or lack thereof) between ETS exposure and the 

different noncancer respiratory disorders analyzed in this report, the possible role of several potential confounding 

factors was considered.  These include other indoor air pollutants; socioeconomic status; effect of parental symptoms; 

and characteristics of the exposed child, such as low birthweight or active smoking.  No single or combined 

confounding factors can explain the observed respiratory effects of passive smoking in children. 

For diseases for which ETS has been either causally associated (LRIs) or indicated as a risk factor (asthma 

cases in previously asymptomatic children), estimates of population-attributable risk can be calculated.  A population 

risk assessment (Chapter 8) provides a probable range of estimates that 8,000 to 26,000 cases of childhood asthma per 

year are attributable to ETS exposure from mothers who smoke 10 or more cigarettes per day.  The confidence in this 

range of estimates is medium and is dependent on the suggestive evidence of the database.  While the data show an 

effect only for children of these heavily smoking mothers, additional cases due to lesser ETS exposure also are a 

possibility.  If the effect of this lesser exposure is considered, the range of estimates of new cases presented above 

increases to 13,000 to 60,000.  Furthermore, this report estimates that the additional public health impact of ETS on 

asthmatic children includes more than 200,000 children whose symptoms are significantly aggravated and as many as 

1,000,000 children who are affected to some degree. 

This report estimates that ETS exposure contributes 150,000 to 300,000 cases annually of lower respiratory 

tract illness in infants and children younger than 18 months of age and that 7,500 to 15,000 of these will require 

hospitalization.  The strong evidence linking ETS exposure to increased incidence of bronchitis, bronchiolitis, and 

pneumonia in young children gives these estimates a high degree of confidence.  There is also evidence suggesting a 

smaller ETS effect on children between the ages of 18 months and 3 years, but no additional estimates have been 

computed for this age group.  Whether or not these illnesses result in death has not been addressed here. 

In the United States, more than 5,000 infants die of SIDS annually.  It is the major cause of death in infants 

between the ages of 1 month and 1 year, and the linkage with maternal smoking is well established.  The Surgeon 

General and the World Health Organization estimate that more than 700 U.S. infant deaths per year from SIDS are 

attributable to maternal smoking (CDC, 1991a, 1992b).  However, this report concludes that at present there is not 

1-13 
enough direct evidence supporting the contribution of ETS exposure to declare it a risk factor or to estimate its 

population impact on SIDS. 

1-14 

2. INTRODUCTION 

An estimated 434,000 deaths per year in the United States, or more than one of every six deaths, are 

attributable to tobacco use, in particular cigarette smoking (CDC, 1991a; figures for 1988).  Approximately 

112,000 of these smoking-related deaths are from lung cancer, accounting for an estimated 87% of U.S. lung cancer 

mortality (U.S. DHHS, 1989).  Cigarette smoking is also causally related to cancer at various other sites, such as the 

bladder, renal pelvis, pancreas, and upper respiratory and digestive tracts (IARC, 1986).  Roughly 30,000 deaths per 

year from cancers at these sites are attributable to smoking (CDC, 1991a).  Furthermore, smoking is the major cause 

of chronic obstructive pulmonary disease (COPD), which includes emphysema, and is thought to be responsible for 

approximately 61,000 COPD deaths yearly, or about 82% of COPD deaths 

(U.S. DHHS, 1989).  Tobacco use is also a major risk factor for cardiovascular diseases, the leading cause of death in 

the United States.  It is estimated that each year 156,000 heart disease deaths and 26,000 deaths from stroke are 

attributable to smoking (CDC, 1991a).  In addition to this substantial mortality, the association of smoking with these 

conditions also involves significant morbidity. 

Smoking also is a risk factor for various respiratory infections, such as influenza, bronchitis, and pneumonia. 

An estimated 20,000 influenza and pneumonia deaths per year are attributable to smoking (CDC, 1991a).  Smokers 

also suffer from lung function impairment and numerous other respiratory symptoms, such as cough, phlegm 

production, wheezing, and shortness of breath.  In addition, smokers are at increased risk for a variety of other 

conditions, including pregnancy complications and ulcers. 

Although the exact mechanisms and tobacco smoke components associated with these health effects are not 

known with certainty, more than 40 known or suspected human carcinogens have been identified in tobacco smoke. 

These include, for example, benzene, nickel, polonium-210, 2-napthylamine, 4-aminobiphenyl, formaldehyde, 

various N-nitrosamines, benz[a]anthracene, and benzo[a]pyrene.  Many other toxic agents, such as carbon monoxide, 

nitrogen oxides, ammonia, and hydrogen cyanide, are also found in tobacco smoke. 

Smokers, however, are not the only ones at risk from exposure to these tobacco smoke toxicants.  In utero 

exposure from maternal smoking during pregnancy is known to be associated with low birthweight and increased risk 

of fetal and infant death (U.S. DHHS, 1989).  Furthermore, nonsmokers might be at risk for smoking-associated 

health effects from "passive smoking," or exposure to environmental tobacco smoke (ETS). 

When a cigarette is smoked, approximately one-half of the smoke generated is sidestream smoke (SS) 

emitted from the smoldering cigarette between puffs.  This SS contains essentially all of the same carcinogenic and 

toxic agents that have been identified in the mainstream smoke (MS) inhaled by the smoker (see Chapter 3).  SS and 

exhaled MS are the major components of ETS.  Environmental monitoring and measurements of biomarkers for ETS 

in the biological fluids of nonsmokers demonstrate that ETS constituents can be found at elevated levels in indoor 

environments where smoking occurs and that these constituents are inhaled and absorbed by nonsmokers (see Chapter 

3). 

2-1 
Twenty-six percent of the U.S. adult population (CDC, 1992b), or about 50 million Americans, are smokers, 

and so virtually all Americans are likely to be exposed to some amount of ETS in the home, at work, or in public 

places.  Measurements of biomarkers for ETS in nonsmokers confirm that nearly all Americans are exposed to ETS 

(see Chapter 3). 

In view of the high levels of mortality and morbidity associated with smoking, the chemical similarity 

between ETS and MS, and the considerable likelihood for exposure of nonsmokers to ETS, passive smoking is 

potentially a substantial public health concern.  The objectives of this report are to assess the risk to nonsmokers for 

respiratory health effects from exposure to ETS (hazard identification) and to estimate the population impact 

(quantitative population risk assessment) of any such ETS-attributable respiratory effects. 

2.1. FINDINGS OF PREVIOUS REVIEWS 

The first epidemiologic results associating passive smoking with lung cancer appeared in the early 1980's. 

Since then, two major comprehensive reviews of the health effects of passive smoking and several less extensive ones 

have been published.  One of the major reviews was conducted by the National Research Council (NRC) in 1986.  At 

the request of two Federal agencies, the U.S. Environmental Protection Agency and the U.S. Department of Health 

and Human Services, the NRC formed a committee on passive smoking to evaluate the methods for assessing 

exposure to ETS and to review the literature on all of the potential health consequences of exposure.  The committee's 

report (NRC, 1986) addresses the issue of lung cancer risk in considerable detail and includes summary analyses from 

10 case-control studies and 3 cohort (prospective) studies.  The report concludes that "considering the evidence as a 

whole, exposure to ETS increases the incidence of lung cancer in nonsmokers."  Combining the data from all the 

studies, the committee calculated an overall observed relative risk estimate of 1.34 (95% C.I. = 

1.18, 1.53). 

The NRC committee was concerned about potential bias in the study results caused by current and former 

smokers incorrectly self-reported as lifelong nonsmokers (never-smokers).  Using plausible assumptions for 

misreported smoking habits, the committee determined that smoker misclassification cannot account for all of the 

increased risk observed in the epidemiologic studies.  Furthermore, the upward bias on the relative risk of lung cancer 

caused by smoker misclassification is counterbalanced by the downward bias from background ETS exposure to the 

supposedly unexposed group.  Correcting for smoker misclassification and background ETS exposure, the committee 

calculated an overall adjusted relative risk estimate of 1.42 (range of 

1.24 to 1.61) for lung cancer in nonsmokers from exposure to ETS from spousal smoking plus background sources. 

The NRC committee also found evidence for noncancer respiratory effects in children exposed to ETS.  It 

recommended that "in view of the weight of the scientific evidence that ETS exposure in children increases the 

frequency of pulmonary symptoms and respiratory infections, it is prudent to eliminate smoking and resultant ETS 

from the environments of small children."  Furthermore, the committee concluded that "household exposure to ETS is 

linked with increased rates of chronic ear infections and middle ear effusions in young children."  The NRC report 

2-2 
also notes that "evidence has accumulated indicating that nonsmoking pregnant women exposed to ETS on a daily 

basis for several hours are at increased risk for producing low-birthweight babies, through mechanisms which are, as 

yet, unknown." 

The second major review, the Surgeon General's report on the health consequences of passive smoking, also 

appeared in 1986 (U.S. DHHS, 1986).  This review covers ETS chemistry, exposure, and various health effects, 

primarily lung cancer and childhood respiratory diseases.  On the subject of lung cancer, the report concludes: 

The absence of a threshold for respiratory carcinogenesis in active smoking, the presence of the 

same carcinogens in mainstream and sidestream smoke, the demonstrated uptake of tobacco smoke 

constituents by involuntary smokers, and the demonstration of an increased lung cancer risk in 

some populations with exposures to ETS leads to the conclusion that involuntary smoking is a cause 

of lung cancer. 

With respect to respiratory disorders in children, the Surgeon General's report determined that "the children of parents 

who smoke, compared with the children of nonsmoking parents, have an increased frequency of respiratory 

infections, increased respiratory symptoms, and slightly smaller rates of increase in lung function as the lung 

matures." 

In 1987, a committee of the International Agency for Research on Cancer (IARC) issued a report on methods 

of analysis and exposure measurement related to passive smoking (IARC, 1987a).  The committee reviewed the 

physicochemical properties of ETS, the toxicological basis for lung cancer, and methods of assessing and monitoring 

exposure to ETS.  The report borrows the summary statement on passive smoking from a previous IARC document 

that dealt mainly with tobacco smoking (IARC, 1986).  The working group that produced the 1986 report had found 

that the epidemiologic evidence then available on passive smoking was compatible with either the presence or the 

absence of a lung cancer risk; however, based on other considerations related to biological plausibility, it concluded 

that passive smoking gives rise to some risk of cancer.  Specifically, the 1986 IARC report states: 

Knowledge of the nature of sidestream and mainstream smoke, of the materials absorbed during 

"passive smoking," and of the quantitative relationships between dose and effect that are commonly 

observed from exposure to carcinogens . . . leads to the conclusion that passive smoking gives rise 

to some risk of lung cancer. 

More recently, the Working Group on Passive Smoking, an independent international panel of scientists 

supported in part by RJR Reynolds Nabisco, reported the findings of its comprehensive "best-evidence synthesis" of 

over 2,900 articles on the health effects of passive smoking (Spitzer et al., 1990).  The group concluded that "the 

weight of evidence is compatible with a positive association between residential exposure to environmental tobacco 

smoke (primarily from spousal smoking) and the risk of lung cancer."  It also found "strong evidence that children 

exposed in the home to environmental tobacco smoke have higher rates of hospitalization (50% to 100%) for severe 

respiratory illness" and that the "evidence strongly supports a relationship between exposure to environmental tobacco 

smoke and asthma among children."  In addition, the working group reported that there is evidence for associations 

between home ETS exposure and many chronic and acute respiratory illnesses, as well as small decreases in 

2-3 
physiologic measures of respiratory function, in both children and adults.  Evidence demonstrating an increased 

prevalence of otitis media (inflammation of the middle ear) in children exposed to ETS at home was also noted.  With 

respect to in utero exposure, the group concluded that active maternal smoking is associated with reduced birthweight 

and with increased infant mortality. 

A recent review of the health effects associated with adult workplace exposure to ETS conducted by the 

National Institute for Occupational Safety and Health (NIOSH, 1991) determined that "the collective weight of 

evidence (i.e., that from the Surgeon General's reports, the similarities in composition of MS and ETS, and the recent 

epidemiologic studies) is sufficient to conclude that ETS poses an increased risk of lung cancer and possibly heart 

disease to occupationally exposed workers."  Furthermore: 

Although these data were not gathered in an occupational setting, ETS meets the criteria of the 

Occupational Safety and Health Administration (OSHA) for classification as a potential 

occupational carcinogen [Title 29 of the Code of Federal Regulations, Part 1990].  NIOSH therefore 

recommends that exposures be reduced to the lowest feasible concentration. 

The classification of "potential occupational carcinogen" is NIOSH's category of strongest evidence for 

carcinogenicity. 

2.2. DEVELOPMENT OF EPA REPORT 

2.2.1. Scope 

Due to the serious health concerns that have arisen regarding ETS, a virtually ubiquitous indoor air 

pollutant, and the wealth of new information that has become available since the extensive 1986 reviews, the EPA has 

performed its own analytical hazard identification and population risk assessment for the respiratory health effects of 

passive smoking, based on a critical review of the data currently available, with an emphasis on the abundant 

epidemiologic evidence.  The number of lung cancer studies analyzed in this document is more than double the 

number reviewed in 1986 (31 vs. 13), with a total of about 3,000 lung cancer cases in female nonsmokers now 

reported in case-control studies and almost 300,000 female nonsmokers followed by cohort studies.  Furthermore, the 

database on passive smoking and respiratory disorders in children contains more than 50 new studies, including 9 

additional studies on acute lower respiratory tract illnesses, 10 on acute and chronic middle ear diseases, 18 on 

respiratory symptoms, 10 on asthma, and 8 on lung function.  This report also discusses six recent studies of the 

effects of passive smoking on adult respiratory symptoms and lung function.  Finally, eight studies of maternal 

smoking and sudden infant death syndrome (SIDS), which was not addressed in the NRC report or the Surgeon 

General's report, are reviewed.  (Although the cause of SIDS is unknown, the most widely accepted hypotheses 

suggest that some form of respiratory pathogenesis is usually involved.) 

First, this report reviews information on the nature of ETS and human exposures.  Then, in accordance with 

the Guidelines for Carcinogen Risk Assessment (U.S. EPA, 1986a), it critically analyzes human, animal, and 

genotoxicity data to establish the weight of evidence for the hazard identification of ETS as a human lung carcinogen 

2-4 
and to characterize the U.S. population risk.  Similarly, it reviews studies of passive smoking and noncancer 

respiratory disorders, particularly in children, and provides both hazard identification and population risk estimates 

for some of these effects. 

While this report restricts analysis to ETS-associated respiratory effects because of time and resource 

considerations, several recent studies have also linked passive smoking with an increased risk of heart disease or 

cancers at sites other than the lung.  For cancers of other sites, the available evidence is quite limited (e.g., Hirayama, 

1984; Sandler et al., 1985), but three recent analyses, examining over 15 epidemiologic studies and various supporting 

mechanistic studies, suggest that ETS is an important risk factor for heart disease, accounting for as many as 35,000 to 

40,000 deaths annually (Wells, 1988; Glantz and Parmley, 1991; Steenland, 1992).  This report takes no position on 

ETS and heart disease. 

Other health effects of active smoking may also have passive smoking correlates of public health concern. 

Maternal smoking during pregnancy, for example, is known to affect fetal development.  Studies on passive smoking 

during pregnancy are far fewer but have demonstrated an apparent association with low birthweight (e.g., Martin and 

Bracken, 1986).  Furthermore, passive exposure to tobacco smoke products both in utero (during pregnancy) and 

postnatally (after birth) may result in other nonrespiratory developmental effects in children--for example, decrements 

in neurological development (Makin et al., 1991).  Again, this report takes no position on these potential 

nonrespiratory effects. 

2.2.2. Use of EPA's Guidelines 

The lung cancer hazard identification and risk characterization for ETS are conducted in accordance with the 

EPA's Guidelines for Carcinogen Risk Assessment (U.S. EPA, 1986a).  In fact, tobacco smoke is a mixture of more 

than 4,000 compounds and could be evaluated according to the Guidelines for the Health Risk Assessment of 

Chemical Mixtures (U.S. EPA, 1986b).  Such a highly complex mixture, however, is not easily characterized with 

respect to chemical composition, levels of exposure, and toxicity of constituents.  Furthermore, the effects and 

mechanisms of interactions among chemicals are insufficiently understood. 

The Guidelines for the Health Risk Assessment of Chemical Mixtures acknowledges these inherent 

uncertainties and recommends various assessment approaches, depending on the nature and quality of the data.  When 

adequate data are available on health effects and exposure for the actual mixture of concern, as is the case with both 

MS and ETS, the preferred approach, according to the mixtures guidelines, is to adopt the procedures used for single 

compounds described by the Guidelines for Carcinogen Risk Assessment, as is done here.  The EPA also has used this 

strategy for assessments of diesel exhausts, PCBs, and unleaded gasoline.  The compilation of health effects and 

exposure information for all the mixture components of interest is considered optional.  In the case of tobacco smoke, 

compiling this information would be highly impractical due to the large number of components and the highly 

complex and changing nature of this mixture.  It is also considered unnecessary, given the abundant epidemiologic 

data on ETS and lung cancer. 

2-5 
The Guidelines for Carcinogen Risk Assessment provide a general framework for the analysis of 

carcinogenic risk, while permitting "sufficient flexibility to accommodate new knowledge and new assessment 

methods as they emerge" (U.S. EPA, 1986a).  According to the guidelines, a qualitative risk assessment, or hazard 

identification, is performed by evaluating all of the relevant data to determine if a compound has carcinogenic 

potential.  Then, a dose-response assessment is made by using mathematical models to extrapolate from high 

experimental or occupational exposures, where risks are usually detected, to lower environmental exposure levels. 

Finally, the dose-response assessment and an exposure assessment are integrated into a risk characterization, 

providing risk estimates for exposed populations.  The risk characterization also describes the assumptions and 

uncertainties in the estimate. 

The enormous databases on active and passive smoking provide more than sufficient human evidence on 

which to base a hazard identification of ETS.  The use of human evidence eliminates the uncertainties that normally 

arise when one has to base hazard identification on the results of high-dose animal experiments.  Furthermore, the 

epidemiologic data on passive smoking provide direct evidence from environmental exposure levels, obviating the 

need for a dose- response extrapolation from high to low doses.  These low-level environmental exposures, however, 

are associated with low relative risks that can only be detected in well-designed studies of sufficiently large size.  For 

this reason, new assessment methods are used to categorize studies on the basis of quality criteria and to combine 

studies to increase the statistical power.  Combining studies also provides a means for incorporating both positive and 

nonpositive study results into the statistical analysis. 

As an alternative to using actual epidemiologic data on ETS, an ETS risk assessment could have used 

"cigarette-equivalents" to correlate ETS exposure with lung cancer risk based on dose-response models from active 

smoking.  This would have involved using measures such as cotinine or respirable suspended particles to compare 

smoke uptake between smokers and 

ETS-exposed nonsmokers in order to equate passive smoking to the active smoking of some quantity of a cigarette(s). 

Then the carcinogenic response associated with that exposure level would be estimated from extrapolation models 

based on the dose-response relationships observed for active smoking.  This procedure was not used for several 

reasons.  Although MS and ETS are qualitatively similar with respect to chemical composition (i.e., they contain most, 

if not all, of the same toxicants and carcinogens), the absolute and proportional quantities of the components, as well 

as their physical state, can differ substantially.  Many tobacco smoke compounds partition preferentially into the MS 

component of smoke emissions; others, however, such as certain highly carcinogenic N-nitrosamines, are 

preferentially produced at lower temperatures and appear in much greater amounts in the ETS fraction.  In addition, 

active and passive smokers have different breathing patterns, and particles in ETS are smaller than those in MS. 

Therefore, the distribution and deposition of smoke constituents in the respiratory tracts of active and passive smokers 

will not be identical.  Furthermore, it is not known which of the chemicals in tobacco smoke are responsible for its 

carcinogenicity.  Clearly, the comparison of a small number of biomarker measures cannot adequately quantify 

differential distributions of unknown carcinogenic compounds. 

2-6 
Another area of uncertainty in the "cigarette-equivalents" approach relates to potential metabolic differences 

between active and passive smokers.  Active smoking is known to induce chemical- and drug-metabolizing enzymes 

in various tissues to levels that significantly exceed those found in nonsmokers.  Thus, the dose-response relationships 

for tobacco smoke-associated health effects are likely to be nonlinear.  In fact, evidence suggests that a linear doseresponse extrapolation might underestimate the risk of adverse health effects from low doses of tobacco smoke 

(Remmer, 1987).  Because of these uncertainties, the data from active smoking are more appropriate for qualitative 

hazard identification than for quantitative dose-response assessment.  Furthermore, at least for lung cancer and other 

respiratory effects, we have substantial epidemiologic data from actual exposure of nonsmokers to environmental 

levels of genuine ETS, which constitute a superior database from which to derive quantitative risk estimates for 

passive smoking, without the need for low-dose extrapolation. 

2.2.3. Contents of This Report 

ETS is chemically similar to MS, containing most, if not all, of the same toxicants and known or suspected 

human carcinogens.  A major difference, however, is that ETS is rapidly diluted into the environment, and 

consequently, passive smokers are exposed to much lower concentrations of these agents than are active smokers. 

Therefore, in assessing potential health risks attributable to ETS, it is important to be able to measure ETS levels in the 

many environments where it is found and to quantify actual human ETS exposure.  The physical and chemical nature 

of ETS and issues related to human exposure are discussed in Chapter 3.  The use of marker compounds and various 

methods for assessing ambient ETS concentrations, as well as the use of biomarkers and questionnaires to determine 

human exposure, is described.  Furthermore, measurements of ETS components in various indoor environments and 

of ETS constituents and their metabolites in nonsmokers are presented, providing evidence of actual nonsmoker 

exposure and uptake. 

Chapter 4 reviews the major evidence that conclusively establishes that the tobacco smoke inhaled from 

active smoking is a human lung carcinogen.  Unequivocal dose-response relationships exist between tobacco smoking 

and lung cancer, with no evidence of a threshold level of exposure.  Supporting evidence for the carcinogenicity of 

tobacco smoke from animal bioassays and genotoxicity experiments is also summarized, including data from the 

limited animal and mutagenicity studies pertaining specifically to ETS or SS. 

The chemical similarity between MS and ETS and the measurable uptake of ETS constituents by nonsmokers 

(Chapter 3), as well as the causal dose-related association between tobacco smoking and lung cancer in humans, 

extending to the lowest observed doses, and the corroborative evidence for the carcinogenicity of both MS and ETS 

provided by animal bioassays and genotoxicity studies (Chapter 4), clearly establish the biological plausibility that 

ETS is also a human lung carcinogen.  In fact, this evidence is sufficient in its own right to establish the weight of 

evidence for ETS as a Group A (known human) carcinogen under EPA guidelines. 

In addition to the evidence of human carcinogenicity from high exposures to tobacco smoke from active 

smoking, there are now more than 30 epidemiologic studies investigating lung cancer in nonsmokers exposed to 

2-7 
actual ambient levels of ETS.  The majority of these studies examine never-smoking women, with spousal smoking 

used as a surrogate for ETS exposure.  Female exposure from spousal smoking is considered to be the single 

surrogate measure that is the most stable and best represents ETS exposure.  Spousal smoking is, however, a crude 

surrogate, subject to exposure misclassification in both directions, since it actually constitutes only a varying portion 

of total exposure. 

For the purposes of the hazard identification analysis in Chapter 5, which is based primarily on the 

epidemiologic studies of ETS, this document extensively and critically evaluates 31 epidemiologic studies from 8 

different countries, including 11 studies from the United States (Appendix A).  More than half of these studies have 

appeared since the NRC and Surgeon General's reviews were issued in 1986.  Two U.S. studies are of particular 

interest.  The recently published five-center study of Fontham et al. (1991) is a well-designed and well-conducted 

case-control study with 429 never-smoking female lung cancer cases and two separate sets of controls.  This is the 

largest case-control study to date, and it has a high statistical power to detect the small increases in lung cancer risk 

that might be expected from ambient exposures.  Furthermore, the Fontham et al. study is the only lung cancer study 

that also measured urinary cotinine levels as a biomarker of exposure.  Another large U.S. case-control study was the 

recent study by Janerich et al. (1990), with 191 cases.  Both of these studies were supported by the National Cancer 

Institute. 

In evaluating epidemiologic studies, potential sources of bias and confounding also must be addressed. 

Smoker misclassification of current and former smokers as never-smokers is the one identified source of systematic 

upward bias to the relative risk estimates.  Therefore, prior to the analyses of the epidemiologic data that are 

conducted in Chapters 5 and 6, the relative risk estimates from each study are adjusted for smoker misclassification 

using the methodology described in Appendix B.  Other potential sources of bias and confounding are discussed in 

Chapter 5. 

Chapter 5 quantitatively and qualitatively analyzes the epidemiologic data to determine the weight of 

evidence for the hazard identification of ETS.  First, the individual studies are statistically assessed using tests for 

effect (i.e., association between lung cancer and ETS) and tests for exposure-response trend.  In addition, the highexposure data are analyzed alone to help minimize the effects of exposure misclassification resulting from the use of 

spousal smoking as a surrogate for ETS exposure.  Various combining analyses also are performed to examine and 

compare the epidemiologic results for separate countries.  Then several potential confounders and modifying factors 

are evaluated to determine if they affect the results.  Finally, the studies are analyzed based on qualitative criteria.  The 

studies are categorized into four tiers according to the utility of the study in terms of its likely ability to detect a 

possible effect, using specific criteria for evaluating the design and conduct as described in Appendix A.  These tiers 

are integrated one at a time into statistical analyses, as an alternative method for evaluating the epidemiologic data that 

also takes into account qualitative considerations.  Chapter 5 concludes with an overall weight-of-evidence 

determination for lung cancer based on the analyses in Chapters 3, 4, and 5. 

2-8 
In Chapter 6, the population risk for U.S. nonsmokers is characterized by estimating the annual number of 

lung cancer deaths that are attributable to exposure from all sources of ETS.  The overall relative risk estimate from 11 

U.S. epidemiological studies of passive smoking and lung cancer in female never-smokers is adjusted upward, based 

on body cotinine measurements from different U.S. population studies, to correct for the systematic downward bias 

caused by background exposure to ETS from sources other than spousal smoke.  Additional assumptions are used to 

extend the results from female never-smokers to male never-smokers and long-term former smokers of both sexes. 

Separate estimates are calculated for background (workplace and other nonhome exposures) and spousal (home) 

exposures, as well as for female and male never-smokers and former smokers.  An alternative analysis of the 

population risk is performed based solely on the Fontham et al. (1991) study, the only study that provides exposurelevel measurements.  Chapter 6 also discusses the sources of uncertainty and sensitivity in the lung cancer estimates. 

The final two chapters address passive smoking and noncancer respiratory disorders.  Both the NRC and 

Surgeon General's reports concluded that children exposed to ETS from parental smoking are at greater risk for 

various respiratory illnesses and symptoms.  This report confirms and extends those conclusions with analyses of 

more recent studies.  New evidence for an association between ETS and middle ear effusion, and for a role of ETS in 

the cause as well as the prevalence and severity of childhood asthma, is reviewed.  In addition, the evidence for an 

association between maternal smoking and SIDS is examined. 

Chapter 7 reviews and analyzes epidemiologic studies of passive smoking and noncancer respiratory 

disorders, mainly in children.  Possible biological mechanisms, additional risk factors and modifiers, and the potential 

long-term significance of early effects on lung function are discussed.  Then, the evidence indicating relationships 

between childhood exposure to ETS and acute respiratory illnesses, middle ear disease, chronic respiratory symptoms, 

asthma, and lung function impairment, as well as between maternal smoking and SIDS, is evaluated. 

Passive smoking as a risk factor for noncancer respiratory health effects in adults is also analyzed in Chapter 

7.  The NRC and Surgeon General's reports concluded that adults exposed to ETS may exhibit small deficits in lung 

function but noted that it is difficult to determine the extent to which ETS impairs respiration because so many other 

factors can similarly affect lung function.  More recent evidence and new statistical techniques allow the 

demonstration of subtle effects of ETS on lung function and respiratory health in adults. 

Chapter 8 discusses potential confounding factors and possible sources of bias in the ETS studies that might 

affect the conclusions of Chapter 7.  Chapter 8 also describes methodological and data considerations that limit 

quantitative estimation of noncancer respiratory health effects attributable to ETS exposure.  Finally, the chapter 

develops population impact assessments for ETS-attributable childhood asthma and for infant/toddler bronchitis and 

pneumonia.  Acute respiratory illnesses are one of the leading causes of morbidity and mortality during infancy and 

early childhood, and an estimated 2 to 5 million children under age 18 are afflicted with asthma.  Therefore, even 

small increases in individual risk for these illnesses can result in a substantial public health impact. 

2-9 
3. ESTIMATION OF ENVIRONMENTAL TOBACCO SMOKE EXPOSURE 

3.1. INTRODUCTION 

Environmental tobacco smoke (ETS) is composed of exhaled mainstream 

smoke (MS) from the smoker, sidestream smoke (SS) emitted from the 

smoldering tobacco between puffs, contaminants emitted into the air during the 

puff, and contaminants that diffuse through the cigarette paper and mouth end 

between puffs (NRC, 1986; U.S. DHHS, 1986; Guerin et al., 1992). These 

emissions contain both vapor phase and particulate contaminants. SS is the 

major component of ETS, contributing nearly all of the vapor phase constituents 

and over half of the particulate matter. 

Overall, ETS is a complex mix of over 4,000 compounds. This mix 

contains many known or suspected human carcinogens and toxic agents. The 

information necessary to evaluate human exposures to each of the compounds of 

human health interest in ETS does not exist. 

Recognizing that it is impractical to characterize the many individual 

compounds that make up ETS and to then assess exposures to those compounds, 

this chapter focuses on the characterization of the complex ETS contaminant mix 

and exposure to it by nonsmokers. Available data on the physical and chemical 

properties of sidestream and mainstream smoke are compared to assess the 

potential for the release of known or suspected human carcinogens and toxic 

agents into indoor environments where human exposures occur. The available 

published data are reviewed to determine whether ETS constituents exist in 

elevated levels in various indoor environments where smoking occurs and 

whether human exposures ensue. Particular attention is focused upon 

environmental and biological marker compounds that serve as proxies for the 

complex ETS mix and the compounds of human health interest. 

The available biomarker data for ETS clearly show that levels of ETS 

contaminants encountered indoors by nonsmokers are of sufficient magnitude to 

be absorbed and to result in measurable doses. Chapters 6 and 8 and Appendix 

B use such biomarker data for estimating relative residential and nonresidential 

ETS exposures in calculating the associated risks for lung cancer and various 

noncancer respiratory effects. 

Epidemiologic studies relating exposure to ETS with lung cancer (Chapter 

5) and respiratory disorders other than cancer (Chapter 7) frequently rely on 

questionnaires to assess level of exposure. This chapter reviews the limited 

number of studies that have attempted to validate questionnaires with objective 

measures of exposure. All of these are population surveys and not 

epidemiologic disease studies. The few studies that compare body cotinine 

levels with childhood respiratory disease occurrences are discussed in Chapters 7 

and 8. 

3-1 
This chapter concludes that (1) MS, SS, and ETS are chemically similar 

and contain a number of known or suspected human carcinogens and toxic 

compounds; (2) marker compounds for ETS are measurable in a variety of 

indoor environments; (3) exposure to ETS is extensive; and (4) there is a 

measurable uptake of ETS by nonsmokers. 

3.2. PHYSICAL AND CHEMICAL PROPERTIES 

Over the past several years, there have been a number of reviews of the 

physical and chemical properties of mainstream and sidestream cigarette smoke 

(NRC, 1986; U.S. DHHS, 1986; Guerin et al., 1992). A particularly detailed 

review is contained in the recent book by Guerin et al. (1992). This section 

summarizes the findings of these reviews to identify the similarities and 

differences in mainstream and sidestream emissions and to establish that known 

and suspected human carcinogens and toxic agents are released into occupied 

spaces from tobacco combustion. Data contained in these reviews, as well as 

recently published material, are also presented to document that sidestream 

emissions of notable air contaminants result in measurable increases of these 

contaminants in indoor locations where individuals spend time. 

The physical and chemical characterization of MS air contaminant 

emissions from cigarettes, cigars, or pipes is derived from laboratory-based 

studies that have typically utilized standardized testing protocols (FTC, 1990; 

Guerin et al., 1992). The data available are primarily for tobacco combustion in 

cigarettes and provide a substantial database on the nature of MS. These 

protocols employ smoking machines, set puff volumes and frequencies, and 

standardized air contaminant collection protocols (small chambers, Cambridge 

filters, chamber air flow rates, etc.). Existing standardized protocols reflect 

conditions representative of human smoking practices of over 30 years ago for 

nonfiltered cigarettes and may not reflect current human smoking parameters for 

today's filtered low-tar cigarettes (NRC, 1986; U.S. DHHS, 1986; Guerin et al., 

1992). It has been suggested that current standardized protocols, particularly for 

filter cigarettes, may underestimate MS deliveries (Guerin et al., 1992). MS air 

contaminant emission rates determined in these studies using standardized 

protocols can be affected by a number of factors, such as puff volume, air 

dilution rate, paper porosity, filter ventilation air flow around the cigarette, and 

moisture content of the tobacco. Actual smoking habits of individuals can also 

dramatically alter the MS deliveries. Variability in any of the factors can affect 

the nature and quantity of the MS emissions. 

Standardized testing protocols for assessing the physical and chemical 

nature of SS emissions from cigarette smoke do not exist, and data on SS are not 

as extensive as those for MS emissions. Protocols used for the generation and 

collection of SS emissions typically use standardized MS protocols (smoking 

machines, puff volumes, etc.) with modifications in the test devices (use of small 

3-2 
chambers) that allow for the simultaneous collection of SS emissions for analysis 

(Dube and Green, 1982; McRae, 1990; Rickert et al., 1984). 

The protocols for the collection of SS emissions are such that results can 

be directly compared to MS emissions and thus provide valuable insights into 

the physical and chemical nature of ETS. It should be noted, however, that the 

SS emissions collected under these protocols may be somewhat different from 

ETS emissions. ETS also contains exhaled MS, which has not yet been 

characterized. Exhaled MS can contribute from 15% to 43% of the particulate 

matter in ETS, though little of the gas phase contaminants (Baker and Proctor, 

1990). In addition, SS samples are not collected under conditions where the 

emissions are diluted and "aged," as is ETS. The aging and dilution of the SS 

emissions can produce changes in phase distribution of the contaminants. 

Results of laboratory evaluations have indicated substantial similarities 

and some differences between MS and SS emissions from cigarettes (NRC, 

1986; U.S. DHHS, 1986; Guerin et al., 1992). Differences in SS and MS 

emissions are due to differences in the temperature of combustion of the tobacco, 

Ph, and degree of dilution with air, which is accompanied by a corresponding 

rapid decrease in temperature. SS is generated at a lower temperature 

(approximately 600°C between puffs vs. 800-900°C for MS during puffs) and at 

a higher Ph (6.7-7.5 vs. 6.0-6.7) than MS. Being slightly more alkaline, SS 

contains more ammonia, is depleted of acids, contains greater quantities of 

organic bases, and contains less hydrogen cyanide than MS. Differences in MS 

and SS are also ascribable to differences in the oxygen concentration (16% in 

MS vs. 2% in SS). SS contaminants are generated in a more reducing 

environment than those in MS, which will affect the distribution of some 

compounds--nitrosamines, for example, are present in greater concentrations in 

SS than in MS. 

SS is rapidly diluted in air, which results in a SS particle size distribution 

smaller than that for MS and in the potential for changes in phase distribution for 

several constituents. Nicotine, for example, while predominantly in the particle 

phase in MS, is found predominantly in the gas phase in ETS (Eudy et al., 1985). 

The shift to gas phase is due to the rapid dilution in SS. SS particle size is 

typically in the range of 0.01-1.0 μm, while MS particle size is 0.1-1.0 μm. The 

SS size distribution shifts to small sizes with increasing dilution (NRC, 1986; 

U.S. DHHS, 1986; Guerin et al., 1992; Ingebrethsen and Sears, 1985). The 

differences in size distribution for MS and SS particles, as well as the different 

breathing patterns of smokers and nonsmokers, have implications for deposition 

of the produced particle contaminants in various regions of the respiratory tract. 

Estimates of from 47% to more than 90% deposition for MS and of 10% 

deposition for SS have been reported (U.S. DHHS, 1986). 

Despite quantitative differences and potential differences in phase 

distributions, the air contaminants emitted in MS and SS are qualitatively very 

3-3 
similar in their chemical composition because they are produced by the same 

process. Over 4,000 compounds have been identified in laboratory-based studies 

of MS (Dube and Green, 1982; Roberts, 1988). In a 1986 IARC monograph 

evaluating the carcinogenic risk of tobacco smoke to humans (IARC, 1986), 42 

individual MS components were identified as carcinogenic in bioassays with 

laboratory animals, with many of these either known or suspected human 

carcinogens. Many additional compounds in MS have been identified as toxic 

compounds. Although SS emissions have not been chemically characterized as 

completely as MS emissions, many of the compounds found in MS emissions, 

including a host of carcinogenic agents, are found in SS emissions (NRC, 1986; 

U.S. DHHS, 1986; Guerin et al., 1992; Dube and Green, 1982; Roberts, 1988) 

and at emission rates considerably higher than for MS. 

Part of the data available from studies of MS and SS emissions is shown in 

Table 3-1 (extracted from NRC, 1986). These data are for nonfilter cigarettes 

and represent a summary of data from several sources. It is immediately obvious 

from Table 3-1 that SS and MS contain many of the same notable air 

contaminants, including several known or suspected human toxic and 

carcinogenic agents, and that SS emissions are often considerably higher than 

MS emissions. For the compounds shown in Table 3-1, all of the five known 

human carcinogens, nine probable human carcinogens, and three animal 

carcinogens are emitted at higher levels in SS than in MS, several by an order of 

magnitude or more. For example, N-nitrosodimethylamine, a potent animal 

carcinogen, is emitted in quantities 20 to 100 times higher in SS than in MS. 

Table 3-1 similarly shows that several toxic compounds found in MS are also 

found in SS (carbon monoxide, ammonia, nitrogen oxides, nicotine, acrolein, 

acetone, etc.). Again, for many of these compounds, SS emissions are higher 

than MS emissions--in some cases by an order of magnitude or higher. 

The SS/MS emission ratios shown in Table 3-1 can be highly variable and 

potentially misleading because, as noted earlier, a number of factors can have a 

substantial impact on MS emissions. A filtered cigarette, for example, can 

substantially reduce MS of total mass well below that shown in Table 3-1, thus 

resulting in a much higher SS/MS ratio. A number of recent studies (Adams et 

al., 1987; Guerin, 1987; Higgins et al., 1987; Chortyk and Schlotzhauer, 1989; 

Browne et al., 1980; Guerin et al., 1992) indicate that, quantitatively, SS 

emissions show little variability as a function of a number of variables (puff 

volume, filter vs. nonfilter cigarette, and filter ventilation). The lack of 

substantial variability in SS emissions is related to the fact that sidestream 

emissions are primarily related to the weight of tobacco and paper consumed 

during the smoldering period, with little influence exerted by cigarette design 

(Guerin et al., 1992). 

3-4 
Table 3-1. Distribution of constituents in fresh, undiluted mainstream smoke and 

diluted sidestream smoke from nonfilter cigarettes1 

Constituent Amount in MS Range in SS/MS 

Vapor phase:2 

Carbon monoxide 

Carbon dioxide 

Carbonyl sulfide 

Benzene3 

Toluene 

Formaldehyde4 

Acrolein 

Acetone 

Pyridine 

3-Methylpyridine 

3-Vinylpyridine 

Hydrogen cyanide 

Hydrazine4 

Ammonia 

Methylamine 

Dimethylamine 

Nitrogen oxides 

N-Nitrosodimethylamine4 

N-Nitrosodiethylamine4 

N-Nitrosopyrrolidine4 

Formic acid 

Acetic acid 

MethCyl chloride 

1,3-Butadiene4,6 

10-23 mg 

20-40 mg 

12-42 :g 

12-48 :g 

100-200 :g 

70-100 :g 

60-100 :g 

100-250 :g 

16-40 :g 

12-36 :g 

11-30 :g 

400-500 :g 

32 ng 

50-130 :g 

11.5-28.7 :g 

7.8-10 :g 

100-600 :g 

10-40 ng 

ND-25 ng 

6-30 ng 

210-490 :g 

330-810 :g 

150-600 :g 

69.2 :g 

2.5-4.7 

8-11 

0.03-0.13 

5-10 

5.6-8.3 

0.1--50 

8-15 

2-5 

6.5-20 

3-13 

20-40 

0.1-0.25 

3 

3.7-5.1 

4.2-6.4 

3.7-5.1 

4-10 

20-100 

<40 

6-30 

1.4-1.6 

1.9-3.6 

1.7-3.3 

3-6 

(continued on the following page) 

3-5 
Table 3-1. (continued) 

Constituent Amount in 

MS 

Range in SS/MS 

Particulate phase:2 

PCDDs and PCDFs10 2 

Particulate matter7
 15-40 mg 1.3-1.9 

Nicotine
 1-2.5 mg 2.6-3.3 

Anatabine
 2-20 :g <0.1-0.5 

Phenol
 60-140 :g 1.6-3.0 

Catechol
 100-360 :g 0.6-0.9 

Hydroquinone
 110-300 :g 0.7-0.9 

Aniline4
 360 ng 30 

2-Toluidine
 160 ng 19 

2-Naphthylamine3
 1.7 ng 30 

4-Aminobiphenyl3
 4.6 ng 31 

Benz[a]anthracene5
 20-70 ng 2-4 

Benzo[a]pyrene4
 20-40 ng 2.5-3.5 

Cholesterol
 22 :g 0.9 

(-Butyrolactone5
 10-22 :g 3.6-5.0 

Quinoline
 0.5-2 :g 3-11 

Harman8
 1.7-3.1 :g 0.7-1.7 

N-Nitrosonornicotine5
 200-3,000 ng 0.5-3 

NNK9
 100-1,000 ng 1-4 

N-Nitrosodiethanolamine4
 20-70 ng 1.2 

Cadmium4
 110 ng 7.2 

Nickel3
 20-80 ng 13-30 

Zinc
 60 ng 6.7 

Polonium-2103
 0.04-0.1 pCi 1.0-4.0 

Benzoic acid
 14-28 :g 0.67-0.95 

Lactic acid
 63-174 :g 0.5-0.7 

Glycolic acid
 37-126 :g 0.6-0.95 

Succinic acid
 110-140 :g 0.43-0.62 

1 pg 

(continued on the following page) 

3-6 
Table 3-1. (continued) 

1

Data in this table come from the NRC report (1986), except where noted, which

compiled data

from Elliot and Rowe, 1975; Schmeltz et al., 1979; Hoffman et al., 1983; Klus 

and Kuhn, 1982; 

Sakuma et al., 1983, 1984a, 1984b; and Hiller et al., 1982. Full references are 

given in NRC,

1986. Diluted SS is collected with airflow of 25 mL/s, which is passed over the

burning cone; as

presented in the NRC report on passive smoking (1986).

2

Separation into vapor and particulate phases reflects conditions prevailing in

MS and does not 

necessarily imply same separation in SS.

3

Known human carcinogen, according to U.S. EPA or IARC.

4

Probable human carcinogen, according to U.S. EPA or IARC.

5

Animal carcinogen (Vainio et al., 1985).

6

Data from Brunnemann et al., 1990. 

PCDDs = polychlorinated dibenzo-p-dioxins;

PCDFs = polychlorinated dibenzofurans.

7

Contains di- and polycyclic aromatic hydrocarbons, some of which are known

animal 

carcinogens.

8

1-methyl-9H-pyrido[3,4-b]-indole. 9

NNK = 4-(N-methyl-N-nitrosamino)-1-(3-pyridyl)-1-butanone. 10Data from Löfroth and Zebühr, 1992. Amount is given as International Toxic

Equivalent Factor

(I-TEF). 

More recent summary data on SS emission rates from filtered test 

cigarettes and commercial cigarettes for many compounds of human health 

interest are presented by Guerin et al. (1992) and shown, with modifications, in 

Table 3-2. Much of the data in Table 3-2 is extracted from detailed data 

presented in an R.J. Reynolds (1988) report. Table 3-2, like Table 3-1, 

documents that appreciable quantities of important air contaminants are emitted 

into the air from SS emissions resulting from tobacco combustion. The table 

demonstrates that SS emissions are reasonably similar across different brands of 

cigarettes, varying by only a factor of 2-3. So, while MS emissions can vary 

considerably (Table 3-1), SS emissions are relatively constant (Table 3-2). 

In summary, the available data indicate that tobacco combustion results in 

the emission of a large number of known toxic compounds and that many of 

these will be released at rates that are higher in SS than in MS. Emphasis in 

characterizing SS emissions has been placed upon those carcinogens and toxic 

compounds found in MS. Although not all of the SS emissions have been 

characterized, the available data showing SS to be enriched in many of the same 

carcinogens and toxic agents found in MS lead to the conclusion that ETS will 

contain the same hazardous compounds. This conclusion provides the basis for 

the toxicological comparison of these complex mixtures in Chapter 4. The 

enrichment of several known or suspected carcinogens in SS relative to MS 

suggests that the SS contaminant mix may be even more carcinogenic than the 

MS mix, per unit tobacco burned. 

3-7 
Table 3-2. Example sidestream cigarette smoke deliveries1 

Constituent Kentucky reference2 Commercial 

Milligrams per cigarette 

Condensate
 

Total particulate matter
 

Nicotine
 

Carbon monoxide
 

Carbon dioxide
 

Nitrogen oxides
 

Ammonia
 

Formaldehyde
 

Acetaldehyde
 

Acrolein
 

Propionaldehyde
 

Benzene
 

Toluene
 

Styrene
 

Pyrrole
 

Pyridine
 

3-Vinylpyridine
 

3-Hydroxypyridine
 

Limonene
 

Neophytadiene
 

Isoprene
 

nC27-nC33
 

Acetonitrile
 

Acrylonitrile 

16.9 

5.6 

54 

474 

0.9 

9.1 

0.7 

4.2 

1.3, 1.4 

0.9 

0.3, 0.4, 0.7 

0.8, 1.3 

0.4 

0.3 

0.3 

2.5, 6.1 

0.2-0.8 

1.0, 0.83 

0.2 

36-67 

16-36, 20-23 

5.7-11.2, 2.7-6.1 

41-67 

0.7-1.0 

0.3-0.5 

0.8-1.1 

<0.1-0.4 

0.1-0.2 

4.4-6.5 

(continued on the following page) 

3-8 
Table 3-2. (continued) 

Constituent Kentucky reference2 Commercial 

Micrograms per cigarette 

Hydrogen cyanide
 

Phenol
 

o-Cresol
 

m + p-Cresol
 

Catechol
 

Hydroquinone
 

Naphthalene
 

Phenanthrene
 

Anthracene
 

Fluoranthene
 

Pyrene
 

Benz[a]anthracene
 

Benzo[a]pyrene
 

NNN4
 

NNK4
 

NAT4
 

NAB4
 

DMNA4
 

EMNA4
 

DENA4
 

NPYR4
 

2-Naphthylamine
 

4-Aminobiphenyl
 

Nickel
 

Cadmium
 

Lead
 

53, 173 

0.2 

0.1 

0.2 

0.4 

0.1 

<0.1 

0.3 

0.2 

44-371 

24-98 

59-299 

46-189 

26-256 

53-177 

2.4 

0.7 

0.7 

0.5 

0.2 

0.1 

1.7 

0.4 

0.7-1.0 

<0.1 

<0.1-0.1 

0.2-0.4 

<0.1-15 

<0.1-0.25 

Chromium 

(continued on the following page) 

3-9 
Table 3-2. (continued) 

1

Table reprinted from Guerin et al. 1992, who compiled data from Browne et al.,

1990; 

Brunnemann et al., 1977, 1978, and 1990; Chortyk and Schlotzhauer, 1989;

Grimmer et al., 1987; 

Guerin, 1991; Higgins et al., 1987; Johnson et al., 1973; O'Neill et al., 1987;

R.J. Reynolds, 1988;

Rickert et al., 1984; Sakuma et al., 1983, 1984a, 1984b; and Norman et al., 

1983. Full references 

are given in Guerin et al., 1992.

2

Filter 1R4F unless otherwise specified.

3

Nonfilter 1R1. 

4

N-nitrosonornicotine (NNN), 4-methylnitrosoamino-1-(3-pyridinyl)-1-butanone

(NNK),

N-nitrosoanatabine (NAT), N-nitrosoanabasine (NAB), dimethylnitrosamine

(DMNA),

ethylmethylnitrosamine (EMNA), diethylnitrosamine (DENA), Nnitrosopyrrolidine (NPYR).

5

Calculated from NRC, 1986, SS/MS ratio. 

The mouse skin painting bioassays of organic extracts of MS and SS reviewed in 

Chapter 4 add support to the suggestion that SS is a more potent carcinogen than 

MS. Furthermore, the incomplete chemical characterization of SS emissions 

means that there may be additional, as yet unidentified compounds in SS of 

human health interest. 

Detailed chemical characterizations of ETS emissions under conditions 

more typical of actual smoking conditions (e.g., using smokers rather than 

smoking machines) are limited. As a result, the impact on ETS of factors such 

as the rapid dilution of SS emissions, adsorption and remission of contaminants, 

and exhaled MS is not well understood. Several studies conducted in chambers 

or controlled environments and using smokers (e.g., Benner et al., 1989; Duc and 

Huynh, 1989; Leaderer and Hammond, 1991; R.J. Reynolds, 1988; NRC, 1986; 

U.S. DHHS, 1986; Guerin et al., 1992) have characterized some of the ETS 

components (total mass, carbon monoxide, nicotine and other selected 

compounds, including known carcinogenic and toxic substances). These studies 

indicate that many of the contaminants of interest in SS are measurable in ETS 

(NRC, 1986; U.S. DHHS, 1986; Guerin et al., 1992) and that several SS 

contaminants (e.g., total mass, carbon monoxide, nicotine) are easily measurable 

in ETS. It is not known how the MS and SS air contaminant emission data for 

specific compounds, generated by the standardized testing protocols utilized, 

compare to data gathered under conditions more representative of actual 

smoking in occupied spaces. 

3.3. ASSESSING ETS EXPOSURE 

In the course of a typical day, an individual spends varying amounts of 

time in a variety of environments (residences, industrial and nonindustrial 

workplaces, automobiles, public access buildings, outdoors, etc.). While in these 

different environments, individuals are exposed to a broad and complex 

3-10 
spectrum of organic and inorganic chemicals in gaseous and particle forms, as 

well as a range of viable particles. 

ETS is a major source of indoor air contamination because of the large, 

though decreasing, number of smokers in the population and the quantity and 

quality of the contaminants emitted into the environment from tobacco 

combustion (NRC, 1981, 1986). In a 1990 self-reported smoking survey of a 

representative sample of the U.S. civilian, noninstitutionalized population, it was 

reported that 50.1% (89.9 million) of the adult population were ever-smokers 

and 25.5% were current smokers (CDC, 1992). The reported average number of 

cigarettes smoked per day was 19.1, with 22.9% of smokers reporting smoking 

25 or more cigarettes per day. From 1965 through 1985, the overall smoking 

prevalence among U.S. adults declined 0.5% annually, with a 1.1% annual 

decline between 1987 and 1990. 

In another recent survey (CDC, 1991b), 40.3% (46 million) of employed 

adults (> 18 years old) in 1988 (who reported that their workplace was not in 

their home) worked in locations where smoking was allowed in designated or 

other areas. Of the nonsmokers (79.2 million), 36.5% (28.5 million) worked at 

places that permitted smoking in designated (if any) and other areas. Of these 

nonsmokers, 59.2% (16.9 million) reported that exposure to ETS in their 

workplace caused them discomfort. The survey highlighted the importance of 

the workplace as a major source of ETS exposure in addition to the home. 

The available data on ETS exposure to children in the home are limited. 

However, based on the 1988 National Health Interview Survey on Child Health, 

42% of children 5 years of age and under are estimated to live in households 

with current smokers (Overpeck and Moss, 1991). The home environment is 

clearly an important source of ETS exposure for children. 

Nationally based survey data needed to make direct estimates of the 

frequency, magnitude, and duration of ETS exposure for nonsmoking adults and 

children and the different indoor environments in which those exposures occur 

are not available. The survey data available, however, do indicate that due to the 

ubiquitous nature of ETS in indoor environments, some unintentional inhalation 

of ETS by nonsmokers is unavoidable. 

The combustion of tobacco results in the emission of a particularly 

complex array of air contaminants into indoor microenvironments. Data on the 

chemical composition of mainstream and sidestream cigarette emissions as well 

as measurements in indoor spaces where smoking occurs indicate that exposure 

to ETS will result in exposure to toxic and carcinogenic agents (Section 3.2). 

The nature of the ETS contaminant mix and eventual human exposure is the 

product of the interaction of several interrelated factors associated with the 

source, transport, chemical transformation, dispersal, removal, and remission 

from surfaces, as well as human activities. Efforts to determine adverse health 

effects of ETS must address the issue of exposure to a complex mixture, which 

can occur in a number of environments. Assessing exposure to ETS, as with any 

3-11 
complex air contaminant mix, is inherently complicated in epidemiologic studies 

(Leaderer et al., 1992). 

Because of the many potentially toxic agents in ETS and the various 

possible toxicological endpoints of interest, it is neither feasible nor desirable to 

focus on any one contaminant. Rather, the focus is on gathering information on 

marker or proxy compounds or other indicators of ETS exposure. In assessing 

these exposures, both direct and indirect methods can be employed. Direct 

methods include personal monitoring and measurement of biological markers. 

Indirect methods employ models to estimate exposures. The modeling approach 

generally makes use of stationary monitoring and questionnaire data. 

Stationary monitoring is used to measure concentrations of air 

contaminants in different environments. These measured concentrations are then 

combined with time-activity patterns (time budgets) to determine the average 

exposure of an individual as the sum of the concentrations in each environment 

weighed by the time spent in that environment. Monitoring of contaminants 

might also be supplemented with the monitoring of factors in the environment 

that affect the contaminant levels measured (meteorological variables, primary 

compounds, ventilation, etc.). Measurement of these factors, in a carefully 

chosen set of conditions, can lead to models that predict concentrations in the 

absence of measured concentrations and provide a means of assessing the impact 

of efforts to reduce or eliminate exposures. Questionnaires are used to determine 

time-activity patterns of individuals, to provide a simple categorization of 

potential exposure, and to obtain information on the properties of the 

environment affecting the measured levels (number of smokers, amounts 

smoked, etc.). 

ETS exposure measurements, whether conducted to support 

epidemiological studies or to determine the extent of exposure in nonsmoking 

individuals, have typically employed air monitoring of indoor spaces, personal 

monitoring, and questionnaires. Modeling of ETS exposures, while useful in 

estimating, from measured data, the level of exposure in a variety of indoor 

spaces under varying conditions, is beyond the scope of this report. 

3.3.1. Environmental Concentrations of ETS 

The SS emission data discussed in Section 3.2 and shown in Tables 3-1 

and 3-2 clearly indicate that tobacco combustion will result in the release of 

thousands of air contaminants into the environments in which smoking occurs. 

The concentrations of the known and unidentified contaminants in the ETS 

complex mix in an enclosed space can exhibit a pronounced spatial and temporal 

distribution. The concentration is the result of a complex interaction of several 

important variables, including (1) the generation rate of the contaminant(s) from 

the tobacco (including both SS and exhaled MS emissions), (2) location in the 

space that smoking occurs, (3) the rate of tobacco consumption, (4) the 

ventilation or infiltration rate, (5) the concentration of the contaminant(s) in the 

3-12 
ventilation or infiltration air, (6) air mixing in the space, (7) removal of 

contaminants by surfaces or chemical reactions, (8) re-emission of contaminants 

by surfaces, and (9) the effectiveness of any air cleaners that may be present. 

Additional considerations relate to the location at which contaminant 

measurements are made, the time of sample collection, the duration of sampling, 

and method of sampling. 

Variations in any one of the above factors related to introduction, 

dispersal, and removal of ETS contaminants can have a marked impact on the 

resultant indoor ETS constituent concentrations. Any one of these parameters 

can vary by an order of magnitude or more. For example, infiltration rates in 

residences can range from 0.1 to over 2.0 air changes per hour, and house 

volumes can range from 100 to over 700 m3

 (Grimsrud et al., 1982; Grot and 

Clark, 1979; Billick et al., 1988; Koutrakis et al., 1992). Smoking rates and 

mixing within and between rooms can also show considerable variability. The 

potential impact on indoor ETS-related respirable suspended particle (RSP) mass 

concentrations due to variations in these parameters is demonstrated in Figures 

3-1 and 3-2 (these figures were taken directly from Figures 5-4 and 5-5 in NRC, 

1986). Figures 3-1 and 3-2 are based on the mass balance model for ETS (NRC, 

1986) for a typical range of input parameters encountered in indoor spaces. 

These figures demonstrate that ETS-generated RSP concentrations in indoor 

environments can range from less than 20 μg/m3 to over 1 mg/m3 depending 

upon the location and conditions of smoking. 

Numerous field studies in "natural" environments have been conducted to 

assess the contribution of smoking occupancy to indoor air quality. These 

studies, summarized in a number of reviews (e.g., NRC, 1986; U.S. DHHS, 

1986; Guerin et al., 1992), have measured several ETS-related contaminants of 

human health concern (e.g., particle mass, carbon monoxide, benzene, nicotine, 

polycyclic aromatic hydrocarbons, N-nitrosamines), in a number of enclosed 

environments (e.g., residential, office, transportation) and under a variety of 

smoking and ventilation rates. These studies demonstrate that (1) many of the 

contaminants of health interest found in SS are also found in ETS; (2) ETS 

contaminants are found above background level in a wide range of indoor 

environments in which smoking occurs; and (3) the concentrations of ETS 

contaminants indoors can be highly variable. These findings can be 

demonstrated for selected ETS-related compounds presented in Figure 3-3 and in 

Table 3-3. 

Figure 3-3 principally utilizes data summaries presented in reviews of 

indoor measurements of ETS-related compounds in a variety of indoor spaces 

(NRC, 1986; U.S. DHHS, 1986; and particularly Guerin et al., 1992). Only the 

range of average concentrations measured in different environments is shown. 

3-13 
Figure 3-1. Diagram for calculating the respirable suspended particle mass (RSP) from ETS

emitted into any occupied space as a function of the smoking rate and removal rate (N). The 

removal rate is equal to the sum of the ventilation or infiltration rate (n v) and the removal rate by 

surfaces (n8) times the mixing factor. The calculated ETS-related RSP mass determined from this 

figure serves as an input to Figure 3-2 to determine the ETS-related RSP mass concentration in 

any space in μg/m3

. Smoking rates (diagonal lines) are given as cigarettes smoked per hour. 

Mixing is determined as a fraction, and nv and n8 are in air changes per hour (ach). All three 

parameters have to be estimated or measured. Calculations were made using the equilibrium form 

of the mass-balance equation and assume a fixed emission rate of 26 mg/m3

 of RSP. 

Shaded area shows the range of RSP emissions that could be expected for a residence with one 

smoker smoking at a rate of either 1 or 2 cigarettes per hour for the range of mixing, ventilation, 

and removal rates occurring in residences under steady-state conditions. 

Source: NRC, 1986. 

3-14 
Figure 3-2. Diagram to calculate the ETS-associated respirable suspended particle mass (RSP) 

concentration in μg/rn3

 in a space as a function of total mass of ETS-generated RSP emitted in mg 

(determined from Figure 3-1) and the volume of a space (diagonal lines). The concentrations 

shown assume a background level of zero in the space. The particle concentrations shown are 

estimates during smoking occupancy. The dashed horizontal lines (A, B, C, and D) refer to

National Ambient Air Quality Standards (health-related) for total suspended particulates 

established by the U.S. Environmental Protection Agency. A is the annual geometric mean. B is 

the 24-hour value not to be exceeded more than once a year. C is the 24-hour air pollution 

emergency level. D is the 24-hour significant harm level. Shaded area shows the range of 

concentrations expected (from Figure 3-1) for a range of typical volumes of U.S. residences and 

rooms in these residences. 

Source: NRC, 1986. 

3-15 
Range of Average Indoor Concentrations of Noteable ETS Contaminants 

Associated with Smoking Occupancy 

Figure 3-3. Range of average indoor concentrations for notable ETS contaminants associated with 

smoking occupancy for different indoor environments.Ranges of averages are principally from

tables presented in Guerin et al. (1992), although other sources were used (NRC, 1986; U.S. 

DHHS, 1986; Turk et al., 1987). Background levels are subtracted. Maximum recorded values are 

typically orders of magnitude higher than averages shown. 

3-16 
Table 3-3. Tobacco-specific N-nitrosamines in indoor air (ng/m3

)

1 

Site 

Approx. 

# of 

cigarette 

s 

smoked 

Collectio 

n 

time 

(hours) 

Flow 

rate 

(liters 

/

min.) 

Tobacco-specific 

N-nitrosamines 

NNN2 NAT2 

NNK2 

Bar I 25-35 3 3.2 22.8 9.2 23.8 

Bar II 10-15 3 3.2 8.3 6.2 9.6 

Bar III 10-15 3 3.2 4.3 3.7 11.3 

Restaurant3 25-30 6 2.15 1.8 1.5 1.4 

Restaurant3 40-50 8 2.1 ND ND 3.3 

Car4 13 3.3 2.15 5.7 9.5 29.3 

Train I 50-60 5.5 3.3 ND ND 4.9 

Train II 50-60 6 3.3 ND ND 5.2 

Office 25 6.5 3.3 ND ND 26.1 

Smoker's Home 30 3.5 3.3 ND ND 1.9 

1

Data corrected for recovery.
 2

NNN = NNN-N-nitrosonornicotine; NAT = NAT-N-nitrosoanataline;
 

NNK = NNK-4-methylInitrosoamino-1-(3 pyridinyl)-1-butanone.
 3

Smoking section.
 4

Windows partially open.
 

ND = not detected (in some cases due to chromatographic interference).
 

Source: Brunnemann et al., 1992.
 

Maximum values, which can range up to two or more orders of magnitude above
 

the averages, are not shown in Figure 3-3. Background levels for nonsmoking
 

conditions have been subtracted. When smoking occurs, concentrations of total
 

polycyclic aromatic hydrocarbons, benzo[a]pyrene, benzene, formaldehyde,
 

toluene, and carbon monoxide will be elevated above background levels in a
 

variety of indoor environments. Figures 3-7 and 3-8 present a similar summary
 

with the same conclusions for two other ETS-related contaminants--respirable
 

suspended particle mass and nicotine.
 

N-nitrosamines are important constituents of SS because they are 

considered to be carcinogenic, because they are emitted in much larger quantities 

in SS than in MS (Table 3-1), and because tobacco combustion is the only 

identified air source in the nonoccupational indoor environment. Guerin et al. 

(1992) reviewed the available data on indoor levels of N-nitrosamines related to 

smoking occupancy. They concluded that levels associated with smoking can 

range from less than detectable to as high as 100 ng/m3

 for nitrosodimethylamine 

(NDMA) under conditions of heavy smoking. A more typical range of 

concentrations of NDMA were < 10-40 ng/m3. In a recent paper, Brunnemann et 

al. (1992) demonstrated that exposure to tobacco specific N-nitrosamines can 

3-17 
occur in a variety of indoor spaces under a range of smoking conditions (Table 

3-3). 

The potential for high exposures of nonsmokers to carcinogenic 

components found enriched in SS can be demonstrated in the case of 4-

aminobiphenyl (4-ABP). Tables 3-1 and 3-2 show 4-ABP emissions in SS to be 

approximately 30 times higher than in MS (100-200 μg/cig). Despite the fact 

that SS emissions of 4-ABP are diluted rapidly in the indoor environment, 

presumably resulting in considerably less exposure than to smokers, 4-ABP Hb 

adduct levels in nonsmokers have been found to be 10% to 20% of those in 

smokers (see Section 3.3.2). 

There are important circumstances where concentrations of ETS-related 

contaminants in indoor spaces may considerably underestimate potential levels 

of exposure. These circumstances occur when the SS emissions or exhaled MS 

emissions are in direct proximity to a nonsmoker (e.g., an infant held by a 

smoking mother or father, or when a nonsmoker is directly downwind of the 

plume of a smoldering cigarette). While there are no measurements to assess the 

impact on the nonsmoker's exposure under these conditions, it is an important 

exposure and will be much higher than would be predicted from existing 

environmental measurements of more diluted SS and exhaled MS emissions. 

The data discussed above represent concentrations measured in selected 

indoor environments and indicate that exposure will occur for individuals in 

those spaces. Estimating the actual level of exposure (concentration × time) 

requires knowledge of the actual time spent in those environments. 

3.3.1.1. Markers for Environmental Tobacco Smoke 

Although ETS is a major source of indoor air contaminants, the actual 

contribution of ETS to indoor air is difficult to assess due to the background 

levels of many contaminants contributed from a variety of other indoor and 

outdoor sources. Relatively few of the individual constituents of the ETS mix 

have been identified and characterized. In addition, little is known about the role 

of individual ETS constituents in eliciting the adverse health and nuisance 

effects observed. However, the issue is not how to fully characterize the 

exposure to each ETS-related contaminant, but rather how to obtain accurate 

quantitative measures of exposure to the entire ETS mixture. The measurement 

of all components in ETS is not feasible, practical, or even desirable due to 

limitations in knowledge of the mixture components related to the effects of 

interest, as well as the feasibility and cost of sampling. It is necessary then to 

identify a marker (also referred to as a tracer, proxy, indicator, or surrogate) for 

ETS that will, when measured, accurately represent the frequency, duration, and 

magnitude of exposure to ETS. These markers can be chemicals measured in the 

air, biomarkers, models, or simple questionnaires. 

There are important issues related to the measurement of a given marker 

compound to represent exposure to ETS. Ideally, an air contaminant marker for 

3-18 
ETS should (1) vary with source strength, (2) be unique to the source, (3) be 

easily detected in air at low concentrations, (4) be similar in emission rates for a 

variety of tobacco products, (5) occur in a consistent ratio in air to other ETS 

components in the complex mix, and (6) be easily, accurately, and cost 

effectively measured (Leaderer, 1990). The marker can be a specific compound 

(e.g., nicotine) or much less specific (e.g., respirable suspended particle mass). 

These criteria for selecting a suitable marker compound are the ideal criteria. In 

practice, no single contaminant or class of contaminants has been identified that 

would meet all the criteria. Selection of a suitable marker for ETS is reduced to 

satisfying as many of the criteria for judging a marker as is practical. In using a 

marker, it is important to state clearly the role of the marker and to note its 

limitations. 

A number of marker or proxy compounds have been used to represent 

ETS concentrations in both field and chamber studies. Nicotine, carbon 

monoxide, 3-ethenylpyridine, nitrogen dioxide, pyridine, aldehydes, nitrous acid, 

acrolein, benzene, toluene, myosmine, and several other compounds have been 

used or suggested for use as markers or proxies for the vapor phase constituents 

of ETS (NRC, 1986; U.S. DHHS, 1986; Hammond et al., 1987; Eatough et al., 

1986; Löfroth et al., 1989; Leaderer and Hammond, 1991; Guerin et al., 1992). 

Tobacco-specific nitrosamines, particle phase nicotine and cotinine, solanesol, 

polonium-210, benzo[a]pyrene, potassium, chromium, and respirable suspended 

particle mass (RSP--particle mass < 2.5 μm) are among the air contaminants 

used or suggested for use as markers for particle phase constituents of ETS 

(NRC, 1986; U.S. DHHS, 1986; Leaderer and Hammond, 1991; Benner et al., 

1989; Hammond et al., 1987; Rickert, 1984; Guerin et al., 1992). All the 

markers employed to date have some problems associated with their use. For 

example, carbon monoxide, nitrogen oxides, benzene, and RSP have many 

indoor and outdoor sources other than the combustion of tobacco, while other 

compounds such as nitrosamines and benzo[a]pyrene are sufficiently difficult to 

measure (e.g., concentrations in smoking environments are low and the cost of 

collection and analysis of samples is high) that their use is very limited. 

At the present time, vapor phase nicotine and respirable suspended 

particulate matter are widely and most commonly used as markers of the 

presence and concentration of ETS for a variety of reasons associated with their 

ease of measurement, existing knowledge of their emission rates from tobacco 

combustion, and their relationship to other ETS contaminants. 

Vapor phase nicotine, the dominant form of nicotine in ETS (Eudy et al., 

1985; NRC, 1986; U.S. DHHS, 1986; Hammond et al., 1987; Eatough et al., 

1986; Guerin et al., 1992) accounts for approximately 95% of the nicotine in 

ETS and is a good marker air contaminant for ETS. It is specific to tobacco 

combustion and is emitted in large quantities in ETS (NRC, 1981, 1986; U.S. 

DHHS, 1986; Rickert et al., 1984; Eatough et al., 1990; Guerin et al., 1992). 

Chamber measurements have shown that nicotine concentrations vary with 

3-19 
source strength (Rickert et al., 1984; Hammond et al., 1987; Hammond and 

Leaderer, 1987; Leaderer and Hammond, 1991) and show little variability 

among brands of cigarettes, despite variations in MS emissions (Rickert et al., 

1984; Leaderer and Hammond, 1991). Field studies have shown that weekly 

nicotine concentrations are highly correlated with the number of cigarettes 

smoked (Hammond et al., 1987; Mumford et al., 1989; Thompson et al., 1989; 

Leaderer and Hammond, 1991). One large field study (Leaderer and Hammond, 

1991) showed that weekly nicotine concentrations were strongly correlated with 

measured RSP levels, as well as with reported number of cigarettes smoked. In 

this study, the slope of the regression line was 10.8 (standard error of ± 0.72), 

similar to the RSP/nicotine level seen in chamber studies. Also, the RSP 

intercept was equal to background levels in homes without smoking (17.9 μg/m3 

± 1.63) (Leaderer et al., 1990). A comparable study by Miesner et al. (1989) of 

particulate matter and nicotine in workplaces found a similar ratio between RSP 

and nicotine. The utility of nicotine as an ETS marker is enhanced by the fact 

that recent advances in air sampling have resulted in the development of a 

variety of validated and inexpensive passive and active monitoring methods for 

measuring nicotine in indoor air environments and for personal monitoring 

(Hammond et al., 1987; Hammond and Leaderer, 1987; Eatough et al., 1989a; 

Koutrakis et al., 1989; Muramatsu et al., 1984; Oldaker and Conrad, 1987). 

Nicotine is also an attractive marker for the complex ETS air contaminant 

mix because it and its metabolites, principally cotinine, can serve as biomarkers 

of ETS exposure. Nicotine and cotinine have long served as markers for active 

smoking. Over the past several years, measurements of nicotine and cotinine in 

blood, urine, and saliva have been used extensively as reasonably sensitive 

biomarkers indicative of exposure to ETS (see Section 3.3.2). 

Nicotine is, however, not an ideal ETS marker. One of the potential 

drawbacks is that vapor-phase nicotine has a high affinity for indoor surfaces. 

The high adsorption rate of nicotine could decrease its concentration relative to 

other ETS constituents, particularly ETS-associated particle mass (Eudy et al., 

1986; Rickert et al., 1990; Eatough et al., 1989b). This relative decrease in 

concentration could lead to an underestimation of ETS exposures. The ratio of 

nicotine to RSP and possibly other ETS constituents would be expected to be 

most dynamic as the ETS contaminant mix ages (Eatough et al., 1989a). An 

additional potential problem is that nicotine may be re-emitted from interior 

surfaces, resulting in measurable concentrations in the absence of active 

smoking. There have, however, been a number of field studies (see above and 

Figures 3-4 and 3-7) where nicotine has been used successfully as an ETS 

marker. These studies would indicate that the uncertainties associated with 

nicotine in typical indoor environments under normally encountered smoking 

rates are relatively small. Levels of nicotine in smoking environments have been 

measured over several orders of magnitude (Figures 3-4 and 3-7), suggesting 

that the uncertainty associated with its high adsorption rate is small compared to 

3-20 
the concentration range. It should also be noted that other gas phase ETS 

contaminants may exhibit adsorption and reemission properties similar to that of 

nicotine. Use of nicotine or any other ETS marker must consider the limitations 

associated with its use. 

The combustion of tobacco results in substantial emissions of RSP. One 

small chamber study using a smoking machine found the average particle 

emission rate for 15 Canadian cigarettes to be 24.1 mg/cigarette with a range of 

15.8-36.0 mg/cigarette (Rickert et al., 1984). A large chamber study using 

smokers reported an average particle emission rate of 17.1 mg for 12 brands of 

American cigarettes (Leaderer and Hammond, 1991). This study noted that 

emission rates among brands are similar. Included in the RSP are a number of 

compounds of direct health concern, e.g., many of the polycyclic aromatic 

hydrocarbons and tobacco-specific N-nitrosamines (NRC, 1986; U.S. DHHS, 

1986; Guerin et al., 1992; Tables 3-1 and 3-3, Figure 3-3). There are a number 

of accepted methods to measure personal RSP exposures and concentrations in 

indoor environments (Ogden et al., 1990). The available methods permit the 

accurate measurement of RSP for sampling times ranging from seconds to 

several days. 

Numerous studies of personal exposures to RSP and of RSP levels in 

indoor environments have shown elevated levels of RSP in environments where 

smoking was reported (NRC, 1986; U.S. DHHS, 1986; Guerin et al., 1992; 

Leaderer and Hammond, 1991; Turk et al., 1987). One study found a strong 

correlation between weekly residential RSP levels and reported number of 

cigarettes smoked (Leaderer and Hammond, 1991). At low smoking and high 

ventilation rates, however, it may be difficult to separate out the ETS-associated 

RSP in a background of RSP from other indoor sources (e.g., kerosene heaters) 

or even from outdoor sources. In using RSP as a marker for ETS, it is important 

to account for the background RSP level related to other sources before 

ascertaining the contribution from ETS. Efforts to model ETS exposures for the 

purpose of assessing risks and the impact of various mitigation measures have 

often focused on predicting ETS-associated RSP concentrations (e.g., Repace 

and Lowrey, 1980). 

3.3.1.2. Measured Exposures to ETS-Associated Nicotine and RSP
 

3.3.1.2.1. Measurements using stationary monitors. In the past several years, numerous studies
 

have been conducted in a variety of indoor environments to determine the impact
 

of tobacco combustion on levels of nicotine and RSP. These studies have
 

employed a variety of protocols that used a diversity of air sampling techniques
 

(passive, active, continuous integrative, etc.), sampled over highly varying
 

timeframes (from minutes to several days), and collected highly variable
 

information on factors affecting the measured concentrations (number of
 

cigarettes smoked, volume of building, ventilation rates, etc.). In an attempt to
 

present an overall view of the contribution of ETS to indoor air quality, only the
 

3-21 
summary results of the measured concentrations of ETS-associated nicotine and 

RSP will be discussed here. Several reviews of the studies evaluating the impact 

of ETS on indoor RSP levels have been conducted over the past few years, and a 

number of recent reports have discussed measured indoor levels of nicotine (e.g., 

NRC, 1986; U.S. DHHS, 1986; Guerin et al., 1992; Leaderer and Hammond, 

1991). Only the indoor levels measured are discussed and summarized. In order 

to assess exposures, the time in contact with the concentrations would have to be 

estimated or measured. The reader is referred to those reports and to the 

individual study reports to acquire more detailed information. 

Measured nicotine concentrations in various indoor environments where 

smoking was noted are summarized in Figure 3-4. The mean concentration, 

standard deviation, and the maximum and minimum values recorded are 

presented. Also given in Figure 3-4 are the number of locations in which the 

measurements were taken and the references in which the data were reported. 

Elevated nicotine levels were measured in all microenvironments in which 

smoking was reported. Measured nicotine levels, as would be expected, were 

highly variable, covering several orders of magnitude. 

The home and workplace may represent the most important environments 

for exposure to ETS because of the amount of time individuals spend there. For 

the five studies reporting residential levels, average nicotine concentrations in 

homes where smoking occurs ranged from less than 1 μg/m3

 (Leaderer and 

Hammond, 1991) to over 14 μg/m3 (Muramatsu et al., 1984). For two of the 

studies (Leaderer and Hammond, 1991; Marbury et al., 1990) nicotine 

concentrations represent weekly averages. Actual concentrations in the homes 

during nonsleeping occupancy (i.e., while smoking would be occurring) would 

be considerably higher than the levels presented in the table (a factor of 3 or 

more higher). Workplace nicotine also demonstrated a wide range of 

concentrations, from near zero to over 33 μg/m3. In other environments, nicotine 

concentrations also demonstrated considerable variability. It is important to note 

that short-term concentrations (on the order of minutes) are likely to show 

considerably more variability, resulting in considerably higher short-term peak 

exposures. 

3-22 
Figure 3-4. Mean, standard deviation, and maximum and minimum nicotine values measured in different indoor environments with 

smoking occupancy. References from which observations are reported and the number of environments monitored are also given. 
REFERENCES FOR FIGURES 3-4 AND 3-5 

Figure 3-4
 

1. Leaderer and Hammond, 1991
 1. 

2. Mumford et al., 1989
 2. 

3. Marbury et al., 1990
 3. 

4. Muramatsu et al., 1984
 4. 

5. Coultas et al., 1990b 5. 

6. Weber and Fischer, 1980
 6. 

7. Vaughan and Hammond, 1990
 7. 

8. Leaderer, 1989
 8. 

9. Miesner et al., 1989
 9. 

10. Hinds and First, 1975
 10. 

11. Oldaker et al., 1990
 11. 

12. Coghlin et al., 1989
 12. 

13. Badre et al., 1978
 13. 

14. Higgins, 1987
 14. 

15. Nagda et al., 1990
 15. 

16. Eatough et al., 1990
 16. 

17. Mattson et al., 1989
 17. 

18. Harmsden and Effenberger, 1957
 18. 

19. Cano et al., 1970
 19. 

20. 

21. 

22. 

23. 

24. 

25. 

26. 

27. 

3-24
 

Figure 3-5
 

Brunekreef and Boleij, 1982
 

Hawthorne et al., 1984
 Moschandreas, 1981
 

Nitschke et al., 1985
 

Parker et al., 1984
 Spengler et al., 1981
 Spengler et al., 1985
 

Leaderer et al., 1990
 Lebret et al., 1990
 

Coultas et al., 1990b 

Turk et al., 1987
 

Weber and Fischer, 1980
 

Sterling and Sterling, 1983
 Nelson et al., 1982
 

Quant et al., 1982
 Repace and Lowery, 1980
 

Repace and Lowery, 1982
 

Leaderer, 1989
 First, 1984
 Oldaker et al., 1990
 

Ishizu, 1980
 Husgafvel-Pursiainen et al., 1986
 Eatough et al., 1990
 

Neal et al., 1978
 

Nagda et al., 1990
 U.S. Department of 
 

Transportation, 1971
 

Elliot and Rowe, 1975
 
A substantial number of studies examining the impact of tobacco combustion on 

concentrations of RSP in various indoor environments have been reported. 

Many of these studies have reported outdoor RSP concentrations and indoor RSP 

levels without smoking as well as concentrations when smoking occurs. These 

studies are summarized in Figure 3-5. Outdoor and indoor RSP levels for each 

of the studies as well as the smoking-associated RSP measurements are shown. 

The sampling time for the presented data ranged from one minute to over several 

days. A major portion of the data is for the residential indoor environment. 

Where smoking is reported, RSP levels are considerably higher than RSP levels 

outdoors or indoors without smoking. RSP levels associated with smoking, like 

those for nicotine, demonstrated considerable variability ranging from a few 

μg/m3

 to over 1 mg/m3. Workplace RSP levels associated with smoking 

occupancy are comparable to residential RSP levels. 

In one large residential study, both ETS-associated nicotine and RSP 

levels were found to be highly correlated (r = 0.84; p < 10-5) with reported 

number of cigarettes smoked (Leaderer and Hammond, 1991). This study found 

that, consistent with chamber data, measured nicotine concentrations predicted 

the contribution to residential RSP levels from tobacco combustion (Figure 3-6). 

The data in Figure 3-6 might be used to estimate the RSP levels associated with 

tobacco combustion from the nicotine levels shown in Figure 3-4. The 

predictive equation, along with the standard errors, is given in the figure and 

figure legend. In a study of the impact of smoking on residential levels of RSP 

and nicotine and of urinary cotinine levels in nonsmoking occupants involving 

10 homes, a correlation of 0.54 between residential levels of RSP and nicotine 

was found (Coultas et al., 1990b). 

Indoor levels of nicotine and RSP associated with the combustion of 

tobacco are a function of several factors related to the generation, dispersal, and 

removal of ETS in enclosed environments (see Section 3.3.1). Thus, measured 

levels of these air contaminants indicate a wide range of concentrations (Figures 

3-1 and 3-2). Figures 3-7 and 3-8 present a summary of the range of nicotine 

and ETS-associated particle concentrations measured by type of environment. 

The figures present the range of average values reported for each study and the 

minimum and maximum values reported. Only studies reporting sampling times 

over 4 hours were included in the residential and office summaries in Figures 3-7 

and 3-8, because the averaging time is more likely to represent the exposures 

associated with occupancy time (this included most of the studies for residential 

spaces shown in Figures 3-4 and 3-5). Since occupancy time in other 

environments (e.g., restaurants) is likely to be much shorter, averaging times on 

the order of minutes or greater were considered for the other indoor 

environments presented in the figures. 

3-25 
Figure 3-5. Mean, standard. deviations, and maximum and minimum concentrations of respirable suspended particle mass (RSP) 

measured in different indoor environments for smoking and nonsmoking occupancy. Also shown are outdoor concentrations.

References from which observations are reported and the number of environments monitored are also given. 
Figure 3-6. Week-long respirable suspended particle mass (RSP) and nicotine measurements in 96 

residences with a mixture of sources. Numbers 1-9 refer to the number of observations at the 

same concentration. 

Source: Leaderer and Hammond, 1991. 

3-27 
Figure 3-7. Range of average nicotine concentrations and range of maximum and minimum 

values measured by different indoor environments for smoking occupancy from studies shown in 

Figure 3-4. Only those studies with sampling times of 4 hours or greater are included in the 

residential and office indoor environment summaries. 

3-28 
Figure 3-8. Range of average respirable suspended particle mass (RSP) concentrations and range 

of maximum and minimum values measured by different indoor environments for smoking 

occupancy from studies shown in Figure 3-5. RSP values represent the contribution to 

background levels without smoking. Background levels were determined by subtracting reported 

indoor concentrations without smoking. Only those studies with sampling times of 4 hours or 

greater are included in the residential and office indoor environment summaries. 

3-29 
Indoor particulate levels associated with smoking occupancy (Figure 3-8) were 

calculated by subtracting particle levels for nonsmoking occupancy (presented in 

the studies) from the smoking occupancy levels. Thus, the increase in particle 

mass concentrations associated with ETS is presented in Figure 3-8. Indoor RSP 

levels in residences without smokers are typically in the range of 10-25 μg/m3

, 

while background office levels are somewhat lower (Figure 3-5). 

The summary nicotine data (Figure 3-7) suggest that average nicotine 

values in residences with smoking occupancy will range from 2 to approximately 

10 μg/m3

, with high values up to 14 μg/m3 and low values down to 0.1 μg/m3. 

Offices with smoking occupancy show a range of average nicotine 

concentrations similar to that of residences, but with considerably higher 

maximum values. The data from other indoor spaces suggest considerable 

variability, particularly in the range of maximum values. The cumulative 

distribution of weekly nicotine measured in one study (Leaderer and Hammond, 

1991) for a sample of 96 homes, with the levels for smoking occupancy 

emphasized, is shown in Figure 3-9. 

Particle mass concentrations in smoker-occupied residences show average 

increases of from 18 to 95 μg/m3

, while the individual increases can be as high as 

560 μg/m3

 or as low as 5 μg/m3 (Figure 3-8). Figure 3-10 (Leaderer and 

Hammond, 1991) highlights the distribution of weekly RSP concentrations for 

residences with smoking occupancy. In that study, smoking residences had RSP 

concentrations approximately 29 μg/m3

 higher than nonsmoking homes. 

Concentrations in offices with smoking occupancy will be on average about the 

same as those in residences. Interestingly, in a large and possibly the most 

comprehensive study of particle mass concentrations associated with smoking 

and nonsmoking sites in office buildings (Turk et al., 1987), the geometric mean 

concentration for RSP in 32 smoking sites was 44 μg/m3 while the geometric 

mean for 35 nonsmoking sites was 15 μg/m3. The difference of 29 μg/m3 is the 

same as that found for smoking and nonsmoking residences (Figure 3-10). 

Restaurants, transportation, and other indoor spaces with smoking occupancy 

will result in a considerably wider range of average, minimum, and maximum 

increases in particle concentrations than the residential or office environments. 

As noted earlier, indoor air contaminant concentrations are the result of 

the interaction of a number of factors related to the generation, dispersal, and 

elimination of the contaminants. Source use is no doubt the most important 

factor. Few studies have measured contaminant concentrations as a function of 

the smoking rate in residences or offices, but some data are available. One study 

estimated an average weekly contribution to residential RSP of 2-5 μg/m3

 per 

cigarette (Leaderer et al., 1990), while another study estimated that a pack-a-day 

smoker would add 20 μg/m3

 to residential levels (Spengler et al., 1981). Coultas 

et al. (1990b) estimated that one or more smokers in a home added 

approximately 17 μg/m3 to the residential RSP level. 

3-30 
Figure 3-9. Cumulative frequency distribution and arithmetic means of vapor-phase nicotine

levels measured over a 1 -week period in the main living area in residences in Onondaga and 

Suffolk Counties in New York State between January and April 1986. 

Source: Leaderer and Hammond, 1991. 

Figure 3-10. Cumulative frequency distribution and arithmetic means of respirable suspended 

particle mass levels by vapor-phase nicotine levels measured over a l-week period in the main

living area in residences in Onondaga and Suffolk Counties in New York State between January 

and April 1986. 

Source: Leaderer and Hammond, 1991. 

3-31 
that one or more smokers in a home added approximately 17 μg/m3

 to the residential RSP level. 

Variations in residential RSP levels as a function of the number of smokers and over a period of 

several months are demonstrated in Figure 3-11 (Spengler et al., 1981). An association between 

the reported number of cigarettes and weekly residential nicotine and RSP levels for a sample of 

96 homes (Leaderer and Hammond, 1991) is shown in Figure 3-12a and 3-12b. Smoking clearly 

increases indoor concentrations of both nicotine and particle mass, and residential levels of both 

nicotine and particle mass increase with increasing levels of smoking. Since nicotine and particle 

mass are proxies for the complex ETS contaminant mix, other ETS air contaminants, including the 

toxic and carcinogenic contaminants, should, similarly, be elevated with smoking occupancy. This 

elevation for selected contaminants is shown in Figure 3-3 and Table 3-3, and for a wider range 

of contaminants in other publications (NRC, 1986; U.S. DHHS, 1986; Guerin et al., 1992; Turk et 

al., 1987; Brunnemann et al., 1992). 

Children have been identified as a particularly sensitive group at health risk from exposure 

to ETS in the residential indoor environment (NRC, 1986; U.S. DHHS, 1986). One study has 

measured smokingstatus of the parents and weekly nicotine concentrations in the activity rooms 

and bedrooms of 48 children under the age of 2 years (Marbury et al., 1990). The results, shown 

Figure 3-11. Monthly mean respirable suspended particle mass (RSP) concentrations in six U.S. 

cities. 

Source: Spengler et al., 1981. 

3-32 
Figure 3-12a. Week-long nicotine concentrations measured in the main living area of 96 

residences versus the number of questionnaire-reported cigarettes smoked during the air-sampling

period. Numbers 1-9 refer to the number of observations at the same concentrations. Closed 

circles indicate that cigar or pipe smoking was reported in the houses, with each cigar or pipe 

smoked set equal to a cigarette. Data from residences in Onondaga and Suffolk Counties in New 

York State between January and April 1986. For panel (a), the standard errors for the intercept 

and slope are 0.014 and 0.002, respectively. For panel (b), the standard errors for the intercept 

and slope are 2.1 and 0.03, respectively. 

Source: Leaderer and Hammond, 1991. 

3-33 
Figure 3-12b. Week-long respirable suspended particle mass (RSP) concentrations measured in 

the main living area of 96 residences versus the number of questionnaire-reported cigarettes 

smoked during the air-sampling period. Numbers 1-9 refer to the number of observations at the 

same concentrations. Closed circles indicate that cigar or pipe smoking was reported in the 

houses, with each cigar or pipe smoked set equal to a cigarette. Data from residences in Onondaga 

and Suffolk Counties in New York State between January and April 1986. For panel (a), the 

standard errors for the intercept and slope are 0.014 and 0.002, respectively. For panel (b), the 

standard errors for the intercept and slope are 2.1 and 0.03, respectively. 

Source: Leaderer and Hammond, 1991. 

3-34 
The results, shown n Table 3-4, indicate that activity and bedroom 

concentrations of nicotine in the children's homes increase with the number of 

cigarettes reported smoked in the home by parents. Concentrations also 

increased with the number of reported smokers in the household. Correlation 

coefficients over 0.7 were calculated between nicotine concentrations and 

number of cigarettes smoked. Exposure of children to ETS is covered in greater 

detail in Chapter 8. 

It is important to note that while measurements of nicotine and ETSassociated RSP are good indicators of the contribution of ETS to air contaminant 

levels in indoor environments, their measurement does not directly constitute a 

measure of total exposure. The concentrations measured in all indoor 

environments have to be combined with time-activity patterns in order to 

determine average exposure of an individual as the sum of the concentrations in 

each environment weighted by the time spent in that environment. Both the 

home and the work environment (those without policies restricting smoking) 

have highly variable ETS concentrations, with the ranges largely overlapping. 

Which environment is most important in determining total exposure will vary 

with individual circumstances (e.g., a person who lives in a nonsmoking home 

but works in an office with smokers will receive most ETS exposure at work, but 

for those exposed both at home and at work, the home may be more important 

because, over the course of a week, more time is generally spent at home). 

An additional issue to be considered is how well the general indoor 

concentrations represent exposures of individuals who may be directly exposed 

to the SS plume of ETS. Small children, particularly infants, held by smoking 

parents may receive exposures considerably higher than those predicted from 

concentrations reported for indoor spaces. Special consideration must be given 

to these significant subpopulations. 

3.3.1.2.2. Personal monitors. Personal monitoring allows for a direct integrated measure 

of an individual's exposure. Personal air monitoring employs samplers (worn by 

individuals) that record the integrated concentration of a contaminant to which 

individuals are exposed in the course of their normal activity for time periods of 

several hours to several days. The monitors can be active (employing pumps to 

collect and concentrate the air contaminant) or passive (working on the principal 

of diffusion). As with biomarkers, personal monitoring provides an integrated 

measure of exposure to air contaminants across a number of environments where 

an individual spends time but does not provide direct information on 

concentrations of the air contaminant of interest in individual environments or 

on the level of exposure in each environment unless samples are taken in only 

one environment or are changed with each change of environment. 

3-35 
Table 3-4. Weekly average concentrations of each measure of exposure by parental

smoking status in the cross-sectional study, Minnesota, 1989 

Smoking status 

Nonsmokers Light 

smokers 

Father 

only 

Mother 

only 

Both 

parents 

Number of subjects 23 4 8 6 7 

5.32 

Total cigarettes 0.9 28.8 68.6 58.8 227.6 

(no./week) 

Activity room nicotine 0.15 0.32 2.45 5.50 12.11 

(μg/m3) 

Bedroom nicotine (μg/m3

) - 0.30 1.21 2.66 

Supplemental information (air monitoring of spaces, time-activity patterns, etc.) 

is needed to determine the contribution of each microenvironment to total 

exposure. 

Relatively few studies have measured personal exposures to ETSassociated nicotine and RSP for nonsmoking individuals. The few reported 

studies of personal exposure to nicotine are summarized in Table 3-5. Personal 

exposures associated with specific indoor environments are presented. Indoor 

environments include the nonindustrial workplace, homes, restaurants, public 

buildings, and transportation-related indoor spaces. Table 3-5 highlights the 

wide range of indoor environments in which ETS exposures take place and the 

wide range of personal exposures encountered in those environments. It is 

important to note, however, that relatively few observations are available and 

that observations for nonworkplace nicotine exposures are dominated by the 

Japanese data (Muramatsu), which may not be representative of personal 

exposures in the United States. Because the data are limited, specific 

conclusions about the contribution of different indoor environments to personal 

nicotine exposures associated with passive smoking cannot be drawn. The data 

do indicate, however, that a wide range of exposures to ETS takes place in a 

variety of indoor environments where smoking is permitted. The data also 

indicate that occupational and residential environments are important sources of 

exposure to ETS because of the levels encountered, which are comparable, and 

the amount of time individuals spend in them. 

Studies of personal exposure to RSP of nonsmoking individuals that have 

attempted to stratify the collected data by ETS exposure are shown in Table 3-6. 

Three of the five studies represent exposures integrated over several different 

microenvironments (residential, public buildings, occupational, etc.), while two 

studies report exposures for the workplace only. 

3-36 
Table 3-5. Studies measuring personal exposure to airborne nicotine associated

with ETS for nonsmokers 

Nicotine, :g/m3 

Study Setting Subject N X(±SD) Range Commen 

ts 

Mattson 

et al., 

1989 

Airplane Attendant 

s 

16 4.7 (±4.0) 0.1-

10.5 

4 attendants on 

4 flights 

Railroad 

Workplace 

Office
 Laboratory
 

Conference
 room
 Home
 Hospital
 

lobby
 Hotel lobby
 Restaurant
 Transportatio
 

n
 

Office
 

Home
 

Restaurant
 Car
 

Public
 

transportation
 

Schenker 

et al., 

1990 

Coultas 

et al., 

1990a 

Muramat 

su 

et al., 

1984 

Muramat 

su 

et al., 

1984 

Clerks 

Nonindus 

-trial 

Volunteer 

s 

Volunteer 

s 

40 6.9	 Samples

collected 

over 

work 

shifts 

15 20.4 

(±20.6) 

10 21.1 Calculate 

8 5.8 d from 

5 38.7 data 

3 

1 

11.2 

3.0 

presented 

4 11.2 

15 26.0 

22 21.7 

3 6.9 

7 7.0 

15 28.2 

7 40.0 

1 11.4 

Calculate 

d from 

data 

presented 

3-37 
Table 3-6. Studies measuring personal exposure to particulate matter associated with ETS for nonsmokers 

Number of subjects Particle mass, :g/m3 Particle 

Study Setting Total No ETS exp. ETS exp. X (±SD) Range 

Spengleret al., 1981 

24-hr. 45 NR NR 

day 

Spengleret al., 1985 

24-hr. 

day 

101 NR 

NR 

NR NR NR 

28 

73 NR 

Sexton et al., 1984 

24-hr. 

day 

48 NR 

31.7 

NR NR NR 

NR 

NR 50.1 

Coultas et al., Workplace 15 

1990a 1 

14 

63.9±41.5 

4.0 

68.2±39.5 

4.0-145.8 

14.7-145.8 

Schenker et al., 1990 

Workplace 86 

3-38 

1Calculated by authors from the regression line. 2Calculated from data presented, after the method of Leaderer and Hammond (1991). 3Calculated from nicotine exposure, after the method of Leaderer and Hammond (1991).NR = not reported.
buildings, occupational, etc.), while two studies report exposures for the workplace only. 

Individuals reporting exposure to ETS have substantially higher integrated exposures to RSP than 

those reporting no exposure. Passive smoke exposure resulted in increases in personal RSP 

exposures of 18-64 μg/m3. It is difficult to assess the ETS contribution to personal RSP levels for 

each indoor environment for the 24-hour RSP personal exposures. The contribution of each 

indoor environment must be substantially higher than the 24-hour averages presented, because 

exposures presumably did not occur during sleeping hours or in all microenvironments. Table 3-6 

demonstrates that the contribution of ETS-related RSP in the work environment to personal 

exposure is important and variable. 

The most extensive study of personal exposure to RSP clearly demonstrates the impact on 

RSP levels from ETS (Spengler et al., 1985). In this study, outdoor, indoor, and personal 24-hour 

concentrations of RSP (particle diameter< 3.5 μm) were obtained for a sample of 101 nonsmoking 

individuals. Of the 101 nonsmokers, 28 persons reported some exposure to ETS in either the home 

or workplace, while 73 reported no ETS exposure. The cumulative frequency distributions of RSP 

for the ETS-exposed and non-ETS-exposed individuals and measured outdoor levels are shown in 

Figure 3-13. Those reporting ETS exposure had mean personal RSP levels 28 μg/m3

 higher than 

those reporting no ETS exposure (Table 3-6). A larger variation in RSP concentrations was also 

seen for those reporting ETS exposure. 

Figure 3-13. Cumulative frequency distribution of respirable suspended particle mass (RSP) 

concentrations from central site ambient and personal monitoring of smoke-exposed and 

nonsmoke-exposed individuals. 

Source: Spengler et al., 1985. 

3-39 
3.3.2. Biomarkers of ETS Exposure 

Biomarkers of exposure are actually measures of dose or uptake and hence 

indicators that an exposure has taken place. Biomarkers, within the context of 

assessing exposure to air contaminants, refer to cellular, biochemical, or 

molecular measures obtained from biological media such as human tissues, cells, 

or fluids that are indicative of human exposure to air contaminants (NRC and 

Committee on Biological Markers, 1986; NRC, 1986; Hulka et al., 1990). The 

relationship between the biomarker and exposure, however, is complex and 

varies as a function of several factors, including environmental factors and the 

uptake, distribution, metabolism, and site and mode of action of the compound 

or compounds of interest. 

Ideally, a biomarker of exposure for a specific air contaminant should be 

chemically specific, have a long half-life in the body, be detectable in trace 

quantities with high precision, be measurable in samples easily collected by 

noninvasive techniques, be inexpensive to assay, be either the agent associated 

with the effects or strongly associated with the agent of interest, and be 

quantitatively relatable to a prior exposure regimen. Ideal biomarkers for air 

contaminants, like markers for complex mixtures, do not exist. 

Numerous biomarkers have been proposed as indicators for ETS (e.g., 

thiocyanate, carboxyhemoglobin, nicotine and cotinine, N-nitrosoproline, 

aromatic amines, protein or DNA adducts) (NRC, 1986; U.S. DHHS, 1986). 

While these biomarkers demonstrate that an exposure has taken place, they may 

not be directly related to the potential for developing the adverse effect under 

study (i.e., not the contaminant directly implicated in the effect of interest), they 

can show considerable variability from individual to individual, and they 

represent only fairly recent exposure (potentially inadequate for chronic 

outcomes). Furthermore, some of these markers may not be specific to ETS 

exposure (e.g., carboxyhemoglobin) while others (e.g., thiocyanate) may not be 

sensitive enough for ETS exposures. 

Nicotine and its metabolite, cotinine, in the saliva, blood, and urine are 

widely used as biomarkers of active smoking and exposure to ETS and are 

valuable in determining total or integrated short-term dose to ETS across all 

environments (NRC, 1986; U.S. DHHS, 1986). Nicotine and cotinine are 

specific to tobacco and are accurately measured by gas chromatography, 

radioimmunoassay, or high pressure liquid chromatography in concentrations 

down to 1 ng/mL. Nicotine has a half-life of about 2 hours in the blood and is 

metabolized to cotinine and excreted in the urine. The short half-life of nicotine 

makes it a better indicator of very recent exposures than of integrated exposure. 

Cotinine in saliva, blood, and urine is the most widely accepted biomarker 

for integrated exposure to active smoking or ETS (NRC, 1986; U.S. DHHS, 

1986). Cotinine is the major metabolite of nicotine, is specific to tobacco, and 

has a longer half-life for elimination from the body. The elimination half-life in 

smokers is approximately 20 hours (range of 10 to 37 hours), but it is typically 

3-40 
metabolite of nicotine, is specific to tobacco, and has a longer half-life for elimination from the 

body. The elimination half-life in smokers is approximately 20 hours (range of 10 to 37 hours), 

but it is typically longer in nonsmokers with ETS exposure, particularly in children (Figure 3-14) 

(Collier et al., 1990; Elliot and Rowe, 1975; Goldstein et al., 1987; Etzel et al., 1985; Greenberg et 

al., 1984). The half-life of cotinine makes it a good indicator of integrated ETS exposure over the 

previous day or two. Laboratory studies of nonsmokers exposed to acute high levels of ETS over 

varying times have shown significant uptake of nicotine by the nonsmokers and increases in their 

cotinine levels (NRC, 1986; U.S. DHHS, 1986; Hoffman et al., 1984; Russell and Feyerabend, 

1975). 

Cotinine, however, is not an ideal biomarker for ETS, and caution in its use has been 

suggested (Idle, 1990). Cotinine is only one of the metabolites of nicotine (trans-3'-

hydroxycotinine has recently been identified as the major metabolite [Neurath et al., 1988]), and it 

shows considerable intersubject variability in controlled nicotine exposure studies (Idle, 1990). 

The assumption that nicotine is specific to tobacco has recently been questioned (Idle, 1990; 

Sheen, 1988; Castro and Monji, 1986; Davis et al., 1991). Plant sources other than tobacco, 

primarily from the Solanaceae family, which are common dietary components have been suggested 

as sources (e.g., eggplant, tomato, and green pepper). It has been suggested that nicotine in food 

is a natural defense against bacteria, fungi, insects, and animals (Ames, 1983). 

Figure 3-14. Average cotinine 1⁄2t by age groups. 

Source: Collier et al., 1990. 

3-41 
"cotinine levels in true nonsmokers reflect far more the nicotine in inhaled 

ambient tobacco smoke than they do nicotine in tea." 

In the most detailed evaluation of nicotine in food, Davis et al. (1991) 

measured nicotine in a number of teas and foods. They found nicotine levels 

ranging from less than detectable to 285 ng/g wet weight. The authors 

calculated that with consuming average quantities of tomatoes, potatoes, 

cauliflower, and black tea, the average contribution to urinary cotinine levels 

would be 0.6 ng/mL. High consumption of the foods and tea might result in a 

maximum urinary cotinine level of 6.2 ng/mL. The average contribution of 

dietary nicotine intake to urinary cotinine levels might be expected to be below 1 

ng/mL and somewhat higher under conditions of high consumption of nicotinecontaining foods. 

Several population-based studies examined cotinine levels in smokers, 

nonsmokers reporting passive smoke exposure, and nonsmokers reporting no 

passive smoke exposure (NRC, 1986; U.S. DHHS, 1986; Greenberg et al., 1984; 

Wald et al., 1984; Wald and Ritchie, 1984; Jarvis et al., 1985; Coultas et al., 

1987; Riboli et al., 1990; Cummings et al., 1990; Tunstall-Pedoe et al., 1991). 

These studies found that exposure to ETS is highly prevalent even among those 

living with a nonsmoker (e.g., Cummings et al., 1990). Saliva, serum, and urine 

cotinine levels in ETS-exposed nonsmokers are generally higher than those in 

nonsmokers reporting no ETS exposure, and levels of cotinine are considerably 

higher in smokers than those in nonsmokers passively exposed (e.g., Table 3-7). 

Cotinine levels in nonsmokers exposed to ETS are approximately 1% of the 

levels in active smokers. Cotinine levels of nonsmokers have been found to 

increase with self-reported ETS exposure (e.g., Figures 3-15 and 3-16). 

In a 10-country study of ETS exposure of 1,369 nonsmoking women 

(Riboli et al., 1990), average urinary levels of cotinine/creatinine by country 

ranged from approximately 2.5 ng/mg for Shanghai to approximately 14 ng/mg 

for Trieste. Eighty percent of those sampled had a detectable level of cotinine. 

Statistically significant differences were observed between centers with lowest 

values observed in Honolulu, Shanghai, and Chandigarh and the highest values 

in Trieste, Los Angeles, and Athens. This study also found an increase in 

cotinine/creatinine levels from the group of women reporting no ETS exposure 

either at home or work (lowest exposure) to the group reporting ETS exposure 

both at home and at work, the highest exposure group (Figure 3-17). The group 

of women reporting ETS exposure only at home had cotinine/creatinine levels 

approximately 60% of those who reported exposure both at home and at work. 

Urinary cotinine levels also were found to increase with the number of 

questionnaire-reported ETS exposures in a group of 663 never-smokers and exsmokers (Cummings et al., 1990). In that study, 76% of the subjects reported 

passive smoke exposure in the 4-day period preceding the sampling. Of the total 

sample, 91% had detectable cotinine levels. 

3-42 
Table 3-7. Approximate relations of nicotine as the parameter between nonsmokers, passive smokers, and active smokers 

Nonsmokers without ETS exposure

(N = 46) 

Nonsmokers with ETS exposure

(N = 54) 

Nicotine/cotinine Mean value % of active smokers' 

value 

Mean value % of active smokers' 

value 

Nicotine (ng/mL):

in plasma 

in saliva in urine 

1.0 3.8 3.9 

7.0 0.6 0.2 

0.8 5.5 

12.11 

5.5 0.8 0.7 

Cotinine (ng/mL):

in plasma 

in saliva in urine 

0.8 0.7 1.6 

0.3 0.2 0.1 

2.01 

2.52 7.72 

0.7 0.8 0.6 

3-43 1Differences between nonsmokers exposed to ETS compared with nonsmokers without exposure: p < 0.01. 2Differences between nonsmokers exposed to ETS compared with nonsmokers without exposure: p < 0.001. 

Source: Jarvis, 1987. 
Figure 3-15. Distribution of individual concentrations of urinary cotinine by degree of selfreported exposure to ETS. Horizontal bars indicate median values. 

Source: Jarvis and Russell, 1985. 

3-44 
Figure 3-16. Urinary cotinine concentrations by number of reported exposures to tobacco smoke 

in the past 4 days among 663 nonsmokers, Buffalo, New York, 1986. 

Source: Cummings et al., 1990. 

3-45 
Among the 76% reporting ETS exposure, 28% reported exposure at work, 27% 

at home, 16% in restaurants, 11% at social gatherings, 10% in a car or airplane, 

and 8% in public buildings. Cotinine levels in this study were also found to vary 

by month, with the winter months being associated with higher levels and 

corresponding to higher reported exposures. 

Cotinine values in smokers and nonsmokers measured in both the 

laboratory or field setting show considerable variability due to individual 

differences in the uptake, distribution, metabolism, and elimination of nicotine. 

Another issue to be considered in interpreting the field data is that exposure 

status is determined by respondent self-reporting. This can lead to a 

misclassification error, which tends to reduce the differences in cotinine levels 

measured in the ETS-exposed versus non-ETS-exposed groups and to increase 

the variability in the levels within any exposure category. Within the exposed 

group, this misclassification error could either increase or decrease the average 

cotinine levels measured. 

It is important to recognize that nicotine and cotinine are actually proxy 

biomarkers. They may not be the active agents in eliciting the adverse effect 

under study but merely indicative of the level of passive smoke exposure. Using 

these measures to estimate cigarette equivalents or determine equivalent active 

smoking exposure could result in over- or underestimating exposure to 

individual or classes of compounds that may be more directly related to the 

health or nuisance effect of concern. Use of different biomarker proxies (e.g., 

protein adducts) could result in estimates of much larger cigarette equivalent 

doses. 

Nevertheless, nicotine and cotinine levels in ETS-exposed nonsmokers 

measured in laboratory and field studies have been used to estimate cigarette 

equivalent exposures and to equate ETS exposures with active smoker exposures 

(NRC, 1986; U.S. DHHS, 1986; Jarvis, 1989). On an equivalent cigarette basis, 

an upper-bound estimate of nicotine dose of 2.5 mg/day for a passive smoke 

exposure has been proposed (Jarvis, 1989). This would translate into the 

equivalent of about one-fifth of a cigarette per day or about 0.7% of the average 

smoker's dose of nicotine (cigarette equivalent dose of other toxins or 

carcinogens would be different--see above). Comparisons of cotinine values in 

ETS-exposed nonsmokers with those measured in smokers ranged from 0.1% to 

2%. One analysis proposed that, on average, nonsmokers' cotinine levels are 

0.5%-0.7% of those found in cigarette smokers (Jarvis, 1989). It should be noted 

that these estimations are based on a number of assumptions that may not hold 

(e.g., the half-life of nicotine and cotinine in smokers and nonsmokers being the 

same). 

3-46 
Figure 3-17. Average cotinine/creatinine levels for subgroups of nonsmoking women defined by 

sampling categories of exposure or by self-reporting exposure to ETS from different sources 

during the 4 days preceding collection of the urine sample. 

Source: Riboli et al., 1990. 

3-47
 One of the protein adducts used as a biomarker of active and passive 

smoking is the 4-aminobiphenyl adduct of hemoglobin. One advantage of 

hemoglobin adducts is that their half-life is quite long and they will persist 

through the life of a red blood cell, which is approximately 120 days. Therefore, 

levels of 4-ABP-Hb adducts reflect exposures over the past several weeks, rather 

than the day or two of exposure integration reflected by cotinine measurements. 

Tobacco smoke is the primary environmental source of 4-aminobiphenyl 

(its use in the dye industry was discontinued decades ago), and smokers have 

between 5 and 8 times as much 4-ABP-Hb adducts as nonsmokers (Hammond et 

al., 1990; Perera et al., 1987; Maclure et al., 1989). That nonsmokers appear to 

have approximately 10-20% the adduct level as smokers may at first appear to be 

contradictory to the urinary cotinine ratios of about 1%, but in fact both results 

are quite consistent with our knowledge of the emissions of various 

contaminants in mainstream and sidestream smoke. Approximately twice as 

much nicotine is emitted in sidestream as in mainstream smoke, but about 31 

times as much 4-ABP is emitted in SS as in MS. Thus, compared to MS, SS is 

15 times more enriched in 4-ABP than in nicotine. Similarly, the ratio of 

biomarkers in those exposed to ETS compared with smokers is roughly 15 times 

greater for the biomarker 4-ABP-Hb adducts than for the biomarker cotinine, a 

metabolite of nicotine. 

The above discussions indicate that the cigarette equivalent dose of those 

exposed to ETS varies with the compound, so that a passive smoker may receive 

1% as much nicotine as an active smoker but 15% as much 4-ABP. These 

examples demonstrate the importance of careful interpretation of biomarkers in 

estimating doses. 

3.3.3. Questionnaires for Assessing ETS Exposures 

Questionnaires are the most commonly used method to assess exposure to 

ETS in both retrospective and prospective studies of acute and chronic effects. 

They are the least expensive method to obtain ETS exposure information for 

large populations. They can be used to provide a simple categorization of ETS 

exposure, to determine time-activity patterns of individuals (e.g., how much time 

is spent in environments where smoking occurs), and to acquire information on 

the factors or properties of the environment affecting ETS concentrations (e.g., 

number of cigarettes smoked, size of indoor environments, subjective evaluation 

of level of smokiness). The time-activity pattern information is combined with 

measured or estimated concentrations of ETS in each environment to provide an 

estimate of total exposure. Information on the factors affecting ETS 

concentrations is used to model or predict ETS levels in those environments. 

Questionnaires are used most extensively to provide a simple 

categorization of potential ETS exposure (e.g., do you live with a smoker?, are 

you exposed to ETS at your place of work?, how many hours a week are you 

exposed to ETS?) and to obtain information on possible confounders (e.g., 

3-48 
occupational history, socioeconomic status). When used simply to determine a 

dichotomous exposure (ETS-exposed vs. unexposed), any misclassification tends 

to bias measures of association toward the null. Thus, any effect that may be 

present will be underestimated or even may not be detectable. If there are more 

than two exposure categories (e.g, light, medium, or heavy exposure), the 

intermediate categories of exposure may be biased either away from or toward 

the null. Misclassification errors may arise from respondents' (1) lack of 

knowledge, (2) biased recall, (3) memory failure, and (4) intentional alteration of 

information. Additionally, there are investigator-based sources of 

misclassification. Errors may arise if semiquantitative levels are incorrectly 

imputed to answers; e.g., even if house exposures are higher than occupational 

exposures on average, for any given individual the ranking may well be reversed 

from that of the average. 

In using questionnaires to assess exposure categories to ETS, to determine 

time-activity patterns, and to acquire information on the factors affecting 

concentrations, it is important to minimize the uncertainty associated with the 

estimate and to characterize the direction and magnitude of the error. 

Unlike for active smoking assessment, standardized questionnaires for 

assessing ETS exposures in prospective or retrospective studies of acute or 

chronic health or nuisance effects do not exist. Lebowitz et al. (1989) reported 

on an effort to develop a standardized questionnaire to assess ETS exposure in 

various indoor environments. This questionnaire, however, has not yet been 

validated. Questionnaires used to assess ETS exposure typically have been 

developed for specific studies and have not been validated for general use. 

There is no "gold standard" with which to validate the questionnaires. Various 

strategies, however, have been used to assess the validity of diverse types of 

questionnaires used to assess ETS exposure. Efforts to validate questionnaires 

have used survey data, air monitoring of nicotine in various microenvironments, 

and nicotine or cotinine in body fluid samples. 

A recent study (Leaderer and Hammond, 1991) of 96 homes using a 

questionnaire to assess residential smoking and a passive nicotine air monitor 

found that 13% of the residences reporting no smoking had measurable levels of 

nicotine while 28% of the residences reporting smoking had nondetectable levels 

of nicotine. A good level of agreement between questionnaire-reported number 

of cigarettes smoked and residential levels of ETS-related RSP and nicotine was 

observed in this study (Figures 3-12a and 3-12b). 

Studies (Marbury et al., 1990; Coghlin et al., 1989; Coultas et al., 1987, 

1990a, 1990b; Riboli et al., 1990; Cummings et al., 1990) comparing various 

measures of ETS exposure (location of exposure, intensity of exposure, duration 

of exposure, number of cigarettes smoked, etc.) with cotinine levels measured in 

physiological fluids generally meet with only moderate success (explained 

variations on the order of 40% or less). The largest such study (Riboli et al., 

1990) was a collaborative effort conducted in 10 countries; correlations in the 

3-49 
range of 0.3 to 0.51 (p < 0.01) were found between urinary cotinine levels and 

various measures of exposure derived from questionnaire data. Using cotinine 

as a biomarker of exposure, studies indicated that a substantial percentage of 

those reporting no ETS exposure by questionnaire do have measurable exposure. 

Differences in the uptake, metabolism, and excretion of nicotine among 

individuals make it difficult to use this measure as a "gold standard" in 

validating questionnaires. Also, the recent exposure (previous 1-2 days) that is 

measured by cotinine may differ from usual exposure. 

In a study involving 10 homes with 20 nonsmoking and 11 homes with 

smoking residents, the variability of four markers of ETS exposure 

(questionnaires, cotinine in saliva and urine, respirable suspended particle mass 

in air, and nicotine in air) was assessed (Coultas et al., 1990b). Questionnairereported exposures explained less than 10% of the variability in air 

concentrations of suspended particle mass and nicotine, 8% of the variability in 

urinary cotinine, and 23% of the variability in saliva cotinine. The authors 

concluded that multiple exposure assessment measurement tools were needed to 

assess ETS exposure in the home. 

In one effort to develop a validated questionnaire (Coghlin et al., 1989), 

53 subjects were asked detailed questions about their exposures to ETS, 

including location of exposures, number of smokers, ventilation characteristics, 

number of hours exposed, proximity of smokers, and intensity of ETS. They then 

wore a passive sampler for nicotine for 7 days and recorded the same 

information regarding each exposure episode in daily diaries. Formulae were 

developed to score the exposures on both the questionnaire and the diary, and 

these scores were then correlated to the average nicotine concentrations 

measured over the 7-day period. Excellent correlation was found (r2

 = 0.83 for 

the questionnaire and 0.90 for the diary). However, the simple questions that 

have been used most frequently in epidemiologic studies, such as whether a 

subject lived with a smoker or the number of hours the subject was exposed, 

were not nearly as well correlated with the measured exposures. These results 

indicate that reliable questionnaires can be developed, but that those used in 

most studies in the past will lead to some random misclassification of exposure, 

and, hence, underestimation of any effect that may be present. 

More recently, epidemiologic studies of acute and chronic respiratory 

effects in children associated with ETS exposure have utilized questionnaires in 

combination with measurements of cotinine levels in physiologic fluids (Ehrlich 

et al., 1992; Reese et al., 1992; Etzel et al., 1992). The studies provide more of a 

direct link between questionnaire-assessed exposures and objective measures of 

exposure and disease. Such studies, discussed in Chapter 8, not only provide a 

means of validating questionnaires but also provide data to establish validation 

of the risk models used in Chapter 8. 

ETS exposures take place across a number of environments, with an 

individual's total exposure being a function of the amount of time spent in each 

3-50 
environment and the concentration in that environment. Questionnaires need to 

assess exposures across indoor environments. Personal air monitoring provides 

a method to validate ETS exposure assessment questionnaires and to assess the 

contribution of each environment to total current exposure. 

Personal air monitoring and cotinine measurements in combination with 

questionnaires have highlighted the importance of obtaining information on 

spouses' smoking status, smoking at home, smoking at work, smoking in various 

other indoor environments (social settings, vehicles, public places, etc.), amount 

of time in environments where smoking occurs, and the intensity of the exposure 

(Marbury et al., 1990; Coghlin et al., 1989; Coultas et al., 1987, 1990a, 1990b; 

Riboli et al., 1990; Cummings et al., 1990). 

3.4. SUMMARY 

ETS is a major source of indoor air contaminants. The ubiquitous nature 

of ETS in indoor environments indicates that some unintentional inhalation of 

ETS by nonsmokers is virtually unavoidable. ETS is a dynamic complex 

mixture of over 4,000 chemicals found in both vapor and particle phases. Efforts 

to characterize the physical and chemical properties of SS emissions, the 

principal component of ETS, have found that: (1) MS and SS emissions are 

qualitatively very similar in their chemical composition, containing many of the 

same carcinogenic and toxic compounds, (2) several of these compounds, 

including five known human carcinogens, nine probable human carcinogens, 

three animal carcinogens, and several toxic agents, are emitted at higher levels in 

SS than MS smoke (sometimes by an order of magnitude or more); (3) SS 

emissions of these notable air contaminants demonstrate little variability among 

brands of cigarettes. The enrichment of several known or suspected carcinogens 

in SS relative to MS smoke suggests that the SS contaminant mix may be even 

more carcinogenic than the MS mix, per unit of tobacco burned. 

Sidestream emissions, while enriched in several notable air contaminants, 

are quickly diluted into the environment where ETS exposures take place. Air 

sampling conducted in a variety of indoor environments has shown that 

nonsmoker exposure to ETS-related toxic and carcinogenic substances will occur 

in indoor spaces where there is smoking occupancy. Individuals close to 

smokers (e.g., an infant in a smoking parent's arms) may be directly exposed to 

the plume of SS or exhaled MS, and thus be more heavily exposed than indoor 

measurements from stationary air monitors might indicate. 

Given the complex nature of ETS, it is necessary to identify marker or 

proxy compounds that when measured will allow for the quantification of 

exposure to ETS. Vapor phase nicotine and respirable suspended particle mass 

are two such markers that are suitable indicators of exposure to ETS. Nicotine 

and RSP have been measured in personal monitoring studies and in studies of a 

variety of indoor environments. The results of these studies clearly demonstrate 

that reported exposure to ETS, even under the conditions of low frequency, 

3-51 
duration, and magnitude, will result in RSP and nicotine values above 

background. These studies indicate that ETS exposures take place in a wide 

range of environments (residences, workplaces, restaurants, airplanes, etc.,) 

where smoking occurs. Indoor levels of RSP and vapor phase nicotine have 

been shown to vary in a linear fashion with reported tobacco consumption. 

Nicotine levels measured indoors have ranged from less than 1 μg/m3

 to over 500 

μg/m3, while RSP levels have ranged from less than 5 μg/m3 to over 1 mg/m3. 

Nicotine exposures greater than 100 μg/m3 are exceedingly rare; most 

environments measured have ranged from less than 0.3 (smoke free) to 30 μg/m3

; 

bars and smoking sections of planes may reach 50-75 μg/m3. Thus, the normal 

range of ETS exposures is approximately 100-fold: 0.3 to 30 μg/m3

 for nicotine 

and from 5 to 500 μg/m3

 for RSP. 

In residences with smoking occupancy, average daily or weekly nicotine 

values might typically range from less than 1 to 10 μg/m3, varying principally as 

a function of number of smokers or number of cigarettes smoked. Average daily 

or weekly residential concentrations of ETS-associated RSP could be expected 

to increase from 18 to 95 μg/m3 (added to background levels) in homes where 

smoking occurs. Like nicotine, ETS-associated RSP increases with increased 

smoking. Average levels of nicotine and RSP in offices with smoking 

occupancy are roughly comparable to those in homes. 

Cotinine in saliva, blood, and urine, while not an ideal biomarker, is the 

most widely accepted biomarker of ETS exposure. Cotinine is an excellent 

indicator that ETS exposure has taken place. It also establishes the link between 

exposure and uptake. Studies show that cotinine levels correlate with levels of 

ETS exposure. The available data also indicate that as many as 80% of 

nonsmokers are exposed to ETS and that there is variability in average exposure 

levels among nonsmokers in different geographical regions. 

Although average cotinine levels are a useful indicator of relative doses of 

ETS among different groups of nonsmokers, the ratio of cotinine levels in 

nonsmokers versus smokers may not be indicative of the exposure ratio for the 

active agents in ETS and MS responsible for the adverse effects. For example, 

while comparisons of cotinine levels in smokers and nonsmokers have led to 

estimates that ETS-exposed nonsmokers receive from 0.1 to 0.7% of the dose of 

nicotine of an average smoker, ETS-exposed nonsmokers may receive 10-20% 

of the dose of 4-ABP that smokers inhale. 

Questionnaires are the most commonly used method to assess exposure to 

ETS in both retrospective and prospective studies of acute and chronic effects. 

They have been used not only to establish simple categories of ETS exposure but 

also to obtain information on activity patterns of exposed individuals and on 

environmental factors affecting concentrations in different indoor environments. 

No standardized or validated questionnaires have yet been developed for 

assessing ETS exposure. A number of studies have compared questionnaire 

responses to measured air concentrations of nicotine and RSP and to cotinine 

3-52 
levels. These efforts have indicated that a significant percentage of individuals 

reporting no exposure had actually been exposed. In general, questionnaires had 

moderate success in assessing exposure status and level of exposure. 

Misclassification errors must be addressed when using questionnaires to assess 

ETS exposure. 

In summary, ETS represents an important source of toxic and carcinogenic 

indoor air contaminants. The available data suggest that exposure to ETS is 

widespread, with a wide range of exposure levels. 

3-53 
4. 	HAZARD IDENTIFICATION I: LUNG CANCER IN ACTIVE SMOKERS, 

LONG-TERM ANIMAL BIOASSAYS, AND GENOTOXICITY STUDIES 

4.1. INTRODUCTION 

Numerous epidemiologic studies have conclusively established that the tobacco smoke inhaled from active 

smoking is a human lung carcinogen (U.S. DHHS, 1982; IARC, 1986).  A clear dose-response relationship exists 

between lung cancer and amount of exposure, without any evidence of a threshold level.  It is, therefore, reasonable to 

theorize that exposure to environmental tobacco smoke (ETS) might also increase the risk of lung cancer in both 

smokers and nonsmokers. 

As documented in the previous chapter, the chemical compositions of mainstream smoke (MS) and ETS are 

qualitatively similar, and both contain numerous known or suspected human carcinogens.  In fact, ETS contains 

essentially all of the same carcinogens identified in MS, and many of these appear in greater amounts in sidestream 

smoke (SS), the primary component of ETS, than in MS, per unit tobacco burned (Table 3-1).  In addition, both MS 

and SS have been shown to be carcinogenic in animal bioassays (Wynder and Hoffman, 1967; Grimmer et al., 1988), 

and MS, SS, and ETS have all been found to be genotoxic in in vitro systems (IARC, 1986).  Furthermore, as the 

previous chapter also describes, exposure assessments of indoor air and measurements of nicotine and cotinine levels 

in nonsmokers confirm that passive smokers are exposed to and absorb appreciable amounts of ETS that might result 

in elevated lung cancer risk. 

This chapter reviews the major evidence for the lung carcinogenicity of tobacco smoke derived from human 

studies of active smoking and the key supporting evidence from animal bioassays and in vitro experiments.  The 

evidence from the few animal and mutagenicity studies pertaining specifically to ETS is also presented.  The majority 

of this information has already been well documented by the U.S. Department of Health and Human Services (U.S. 

DHHS) (1982) and the International Agency for Research on Cancer (IARC) (1986).  The current discussion mainly 

extracts and summarizes some of the important issues and principal studies described in those comprehensive reports. 

In view of the abundant and consistent human evidence establishing the carcinogenic potential of active 

smoking to the lung, the bulk of this chapter focuses on the human data.  Although EPA's carcinogen risk assessment 

guidelines (U.S. EPA, 1986a) suggest an extensive review of all evidence pertaining to carcinogenicity, we believe 

that the large quantity of human cancer studies on both MS and ETS provide the most appropriate database from 

which to evaluate the lung cancer potential of ETS.  Thus, the animal evidence and genotoxicity results are given only 

limited attention here.  Similarly, a discussion of the mutagenicity data for individual smoke components would be 

superfluous in the context of the overwhelming evidence from other, more pertinent sources and is not included. 

Extensive reviews of these data can be found in the U.S. DHHS (1982) and IARC (1986) publications.  Claxton et al. 

(1989) provide an assessment of the genotoxicity of various ETS constituents. 

4-1 
Studies of active smoking in human populations from many countries provide direct and incontrovertible 

evidence for a dose-related, causal association between cigarette smoking and lung cancer.  This evidence includes 

time trends in lung cancer mortality rates associated with increasing cigarette consumption, high relative risks for lung 

cancer mortality in smokers of both sexes observed consistently in numerous independent retrospective and 

prospective studies, and dose-response relationships demonstrated with respect to smoking intensity and duration and 

for all four major histological types of lung cancer. 

4.2.1. Time Trends 

While the overall cancer death rate in the United States has been fairly stable since 1950, the lung cancer 

death rate has increased drastically for both males and females (Figures 4-1 and 4-2).  Age-adjusted lung cancer 

mortality rates in men have increased from 11 per 100,000 in 1940 to 73 per 100,000 in 1982, leveling slightly to 74 

per 100,000 in 1987 (Garfinkel and Silverberg, 1991).  In women, lung cancer mortality rates have risen from 6 per 

100,000 in the early 1960's to 28 per 100,000 in 1987 (Garfinkel and Silverberg, 1991). 

The striking time trends and sex differences seen in lung cancer mortality rates correlate with historical 

smoking patterns.  Increases in lung cancer death rates parallel increases in cigarette consumption with a roughly 20-

year lag time, accounting for the latency period for the development of smoking-induced lung cancer.  Males started 

smoking cigarettes in large numbers during the years around World War I, whereas females did not begin smoking in 

appreciable numbers until World War II.  Cigarette consumption per capita (based on the total population age 18 and 

older) in the United States rose from 1,085 in 1925 to a high of 4,148 in 1973.  In the past two decades, cigarette 

consumption has decreased to 2,888 in 1989 (Garfinkel and Silverberg, 1991).  This decline correlates with the 

leveling off of lung cancer mortality rates in recent years. 

4-2 
Figure 4-1. Age-adjusted cancer death rates* for selected sites, males, United States, 1930-1986.

*Adjusted to the age distribution of the 1970 U.S. census population.

Source: U.S. DHHS, 1989.

4-3 
Figure 4-2. Age-adjusted cancer death rates* for selected sites, females, United States, 1930-

1986. 

*Adjusted to the age distribution of the 1970 U.S. census population. 

Source: U.S. DHHS, 1989. 

4-4 
4.2.2. Dose-Response Relationships 

More than 50 independent retrospective studies have consistently found a dose-related association between 

smoking and lung cancer (U.S. DHHS, 1982).  Eight major prospective studies from five countries corroborate this 

association: 

American Cancer Society (ACS) Nine-State Study (white males) (Hammond and Horn, 1958a,b)


Canadian War Veterans Study (Best et al., 1961; Lossing et al., 1966)


British Doctors Study (Doll and Hill, 1964a,b; Doll and Peto, 1976; Doll et al., 1980)


American Cancer Society 25-State Study (Hammond, 1966; Hammond and Seidman, 1980)


U.S. Veterans Study (Kahn, 1966; Rogot and Murray, 1980)


California Labor Union Study (Weir and Dunn, 1970)


Swedish Study (sample of census population) (Cederlöf et al., 1975)


Japanese Study (total population of 29 health districts) (Hirayama, 1967, 1975a,b, 1977, 1978, 1982,


1985).


Details of the designs of these studies are summarized in Table 4-1.  These eight studies together represent 

more than 17 million person-years and more than 330,000 deaths.  Lung cancer mortality ratios from the prospective 

studies are presented in Table 4-2.  Combining the data from the prospective studies results in a lung cancer mortality 

ratio of about 10 for male cigarette smokers compared with nonsmokers.  (Note that these lung cancer mortality ratios 

underestimate the relative risk of lung cancer to smokers compared with a non-tobacco-smoke-related background 

risk to nonsmokers [see Chapter 6], given the causal association between ETS exposure and lung cancer in 

nonsmokers documented in this report.) 

This strong association between smoking and lung cancer is further enhanced by very strong and consistent 

dose-response relationships.  A gradient of increasing risk for lung cancer mortality with increasing numbers of 

cigarettes smoked per day was established in every one of the prospective studies (Table 4-3).  Lung cancer mortality 

ratios for male smokers who smoked more than 20 cigarettes daily were generally 15 to 25 times greater than those 

for nonsmokers.  Marked increases in lung cancer mortality ratios were also seen in all the lowest dose categories. 

Males who smoked fewer than 10 cigarettes per day had lung cancer mortality ratios 3 to 10 times greater than those 

for nonsmokers.  There is no evidence of a threshold level for the development of smoking-induced lung cancer in 

any of the studies. 

Dose-response relationships with respect to the duration of smoking also have been well established.  From 

the British male physicians study, Peto and Doll (1984) calculated that the 

4-5 
Table 4-1.  Main characteristics of major cohort studies on the relationship between smoking and cancer 

Study enrollment followup respondents)  deaths mortality 

Year of population for (proportion of  and no. of followup for 

Sample size; Source of 

initial samples; information on  Duration of 

in brackets, smoking  followup Completeness of 

ACS 1952 204,547 men Self-administered  44 months 98.9% 

9-state [187,783] questionnaire  11,870 deaths 

study 

Canadian 1955-1956 207,397 Self-administered  6 years NA 

veterans subjects questionnaire  9,491 deaths 

study (aged 30+) (57% respondents)  in men; 

[92,000]  1,794 deaths 

in women 

British 1951 34,440 men Self-administered  20 years 99.7% 

doctors (aged 20+) questionnaire  10,072 deaths 

study (69% respondents) 

6,194 women Self-administered  22 years 99% 

(aged 20+) questionnaire  1,094 deaths 

(60% respondents) 

ACS 1959-1960 1,078,894 subjects, Self-administered  4.5 + 5 years 97.4% in women 

25-state first followup: questionnaire  26,448 deaths 97.9% in men 

study 440,558 men,  in men; in first 

U.S. 1954 293,958 men Self-administered  16 years ascertainment of 

veterans (aged 31-84) questionnaire  107,563 deaths vital status; 97.6% 

study  [248,046] (85% respondents) of death 

562,671 women  16,773 deaths followup 

(aged 35-84);  in women 

second followup: 

358,422 men, 

483,519 women 

Almost 100% 

certificates 

retrieved 

California 1954-1957 68,153 men Self-administered  5-8 years NA 

study (aged 35-64) questionnaire  4,706 deaths 

(continued on the following page) 

Swedish study 1963 27,342 men, 27,732 Self-administered  10 years NA 

women (aged 18-69) questionnaire (89%  5,655 deaths 

respondents)  (2,968 

autopsies) 

4-6 
Table 4-1. (continued) 

Study enrollment followup respondents)  deaths mortality 

Year of population for (proportion of  and no. of followup for 

Sample size; Source of 

initial samples; information on  Duration of 

in brackets, smoking  followup Completeness of 

Japanese 

study 1965 122,261 men, Interview  16 years Total 

142,857 women (95% of population  51,422 deaths 

(aged 40+) in area) 

NA = not available. 

Source:  IARC, 1986. 

4-7

Table 4-2.  Lung cancer mortality ratios--prospective studies 

Population  Size of deaths Nonsmokers smokers 

Number Cigarette 

British 34,000 males 441 1.00 14.0 

doctors study  6,194 females 27 1.00 5.0 

Swedish 27,000 males 55 7.0 

study 28,000 females 8 4.5 

1.00 

1.00 

Japanese 122,000 males 940 3.76 

study 143,000 females 304 2.03 

1.00 

1.00 

ACS 25-state 358,000 males 2,018 8.53 

study 483,000 females 439 3.58 

1.00 

1.00 

U.S. veterans study 290,000 males 3,126 11.28 1.00 

Canadian 78,000 males 331 14.2 

veterans study 1.00 

ACS 9-state 188,000 males 448 10.73 

study 1.00 

California males 68,000 males 368 7.61 

in 9 occupations 1.00 

Source:  U.S. DHHS, 1982. 

4-8

--

Table 4-3.  Lung cancer mortality ratios for men and women, by current number of cigarettes smoked per day-­

prospective studies 

Men 

Population smoked per day ratios smoked per day  ratios 

Cigarettes Mortality Cigarettes Mortality 

ACS 25-state Nonsmoker 1.00 Nonsmoker 1.00 

study 1-9 4.62 1-9 1.30 

10-19 8.62 10-19 2.40 

20-39 14.69 20-39 4.90 

40+  18.71  40+ 7.50 

British Nonsmoker 1.00 Nonsmoker 1.00 

doctors 1-14 7.80  1-14 1.28 

study 15-24 12.70 15-24 6.41 

25+  25.10  25+ 29.71 

Swedish study Nonsmoker 1.00 Nonsmoker 1.00 

1-7 2.30 1-7 1.80 

8-15 8.80  8-15 11.30 

16+ 13.70  16+ 

Japanese study Nonsmoker 1.00 Nonsmoker 1.00 

(all ages) 1-19 3.49 <20 1.90 

20-39 5.69 20-29 4.20 

40+ 6.45 

U.S. veterans Nonsmoker 1.00 

study 1-9  3.89 

10-20  9.63 

21-39  16.70 

40 23.70 

ACS 9-state Nonsmoker 1.00 

study 1-9  8.00 

10-20  10.50 

20+ 23.40 

Canadian  Nonsmoker 1.00 

veterans study 1-9  9.50 

10-20  15.80 

20+ 17.30 

California  Nonsmoker 1.00 

males about 1⁄2 pk 3.72 

in 9 about 1 pk 9.05 

occupations  about 11⁄2 pk 9.56 

Women 

Source:  U.S. DHHS, 1982. 

4-9

excess annual incidence rates of lung cancer after 45, 30, and 15 years of cigarette smoking were in the approximate 

ratio of 100:20:1 to each other.  The California and Swedish studies also demonstrated an increasing risk of lung 

cancer in men with longer smoking duration (Table 4-4). 

Four of the prospective studies examined lung cancer mortality in males by age at initiation of smoking and 

found increasing risk with younger age (Table 4-5).  Some of the studies also investigated smoking cessation in men 

and observed a decrease in lung cancer risk with increasing number of years since quitting smoking (Table 4-6).  The 

Cancer Prevention Study II, a study of 1,200,000 people in all 50 states, reveals a similar trend for women who quit 

smoking (Figure 4-3).  The occurrence of higher lung cancer mortality ratios in the groups with only a few years since 

cessation as compared with current smokers (Table 4-6 and Figure 4-3) is attributable to the inclusion of recent exsmokers who were forced to stop smoking because they already had smoking-related symptoms or illness (U.S. 

DHHS, 1990a).  The increased lung cancer risks seen in people who started smoking at a younger age and the 

decreased risks seen with time since smoking cessation suggest both initiation and promotion capabilities of tobacco 

smoke components. 

Additional dose-response relationships have been derived from consideration of the types of tobacco 

products used.  Pipe and cigar smokers, who inhale less deeply than cigarette smokers, have lower risks of lung cancer 

than cigarette smokers (Table 4-7).  Furthermore, the American Cancer Society 25-state study found decreased risks 

for lung cancer in males and females who smoked cigarettes with lower tar and nicotine content compared with those 

who smoked cigarettes with higher tar and nicotine content (Table 4-8), although these decreased risks are still 

substantially higher than the risk to nonsmokers.  Similarly, it has been established that smokers of filtered cigarettes 

have relatively lower lung cancer risks than smokers of nonfiltered cigarettes (Table 4-9).  Filters reduce the amount 

of tars, and hence a portion of the carcinogenic agents, in the MS inhaled by the smoker.  Passive smokers, however, 

do not share in any benefit derived from cigarette filters (see Chapter 3) and may, in fact, be exposed to greater 

amounts of ETS if smokers of filtered cigarettes smoke a greater number of cigarettes to compensate for any reduction 

in nicotine uptake resulting from the filters (U.S. DHHS, 1986). 

4.2.3. Histological Types of Lung Cancer and Associations With Smoking 

A number of epidemiologic studies have also examined the association between various histological types of 

lung cancer and smoking.  The results of some of these investigations are summarized in Table 4-10.  Problems in 

interpreting the results of such studies include differences in the nomenclature, criteria, and verification of tumor 

classification; inadequacy of some specimens; and the small size of many of the patient groups, resulting in unstable 

risk 

4-10 
Table 4-4.  Relationship between risk of lung cancer and duration of smoking in men, based on available information 

from cohort studies 

Reference (years) deaths) (%) 

Duration of smoking (no. of observed excess death rate 

Standardized 

mortality ratio Approximate annual 

1 

Weir and Dunn 1-9 1.13 0.002 (0.001) 

(1970) 10-19 6.45 0.09  (0.05) 

20+ 8.66 0.12  (0.08) 

Nonsmokers 1.0 0 

Cederlöf et al. 1-29 1.8 (5) 0.01 (0.008) 

(1975) >30 7.4 (23) 0.1  (0.06) 

Nonsmokers 1.0 (7) 0 

The mortality ratio among nonsmokers was assumed to be 15.6 per 100,000 per year, as in the 

American Cancer Society 25-state study.  Figures in parentheses were computed by the IARC 

working group, applying the British doctors' mortality rate among nonsmokers (10.0/100,000 

per year). 

Source:  IARC, 1986. 

4-11 

1 
Table 4-5.  Lung cancer mortality ratios for males, by age of smoking initiation--prospective studies 

Study in years ratio 

Age of 

smoking initiation Mortality 

ACS 25-state  Nonsmoker  1.00 

study 25+  4.08 

20-24 10.08 

15-19 19.69 

Under 15 16.77 

Japanese Nonsmoker  1.00 

study 25+  2.87 

20-24  3.85 

Under 20  4.44 

U.S. veterans study Nonsmoker  1.00 

25+  5.20 

20-24  9.50 

15-19 14.40 

Under 15 18.70 

Swedish  Nonsmoker  1.00 

study 19+  6.50 

17-18  9.80 

Under 16  6.40 

Source:  U.S. DHHS, 1982. 

4-12

Table 4-6.  Relationship between risk of lung cancer and number of years since stopping smoking, in men, based on 

available information from cohort studies 

Reference stopping smoking (no. of observed deaths) 

No. of years since  Mortality ratio 

ACS 1-19 cig./day 

25-state study Current smokers 6.5 (80) 

(Hammond, 1966) <1 7.2 (3) 

1-4 4.6 (5) 

5-9 1.0 (1) 

10+ 0.4 (1) 

Nonsmokers 1.0 (32) 

20+ cig./day 

Current smokers 13.7 (351) 

<1 19.1 (33) 

1-4 12.0 (33) 

5-9 7.2 (32) 

10+ 1.1 (5) 

Nonsmokers 1.0 (32) 

Swedish study <10 6.1 (12) 

(Cederlöf et al., >10 1.1 (3) 

1975) Nonsmokers 1.0 (7) 

British doctors Current smokers 15.8 (123) 

study (Doll and Peto, 1-4 16.0 (15) 

1976) 5-9 5.9 (12) 

10-14 5.3 (9) 

15+ 2.0 (7) 

Nonsmokers 1.0 (7) 

Rogot and Murray (1980) Current smokers 11.3 (2,609) 

<5 18.8 (47) 

5-9 7.5 (86) 

10-14 5.0 (100) 

15-19 5.0 (115) 

20+ 2.1 (123) 

Nonsmokers 1.0 NA 

NA = not available. 

Source:  IARC, 1986. 

4-13 
Figure 4-3. Relative risk of lung cancer in ex-smokers, by number of years quit, women, Cancer 

Prevention Study II. 

Source: Garfinkel and Silverberg, 1991. 

4-14
Table 4-7.  Relative risks of lung cancer in some large cohort studies among men smoking cigarettes and other types 

of tobacco 

Relative Death rate No. of cases 

Study Smoking category risk per 100,000 

ACS 9-state Never smoked  1.0 12.8 15 

study Occasionally only  1.5 19.2 8 1 

Cigarettes only  9.9 27.2 249 

Cigars only  1.0 13.1 7 

Pipes only  3.0 38.5 18 

Cigarettes + other  7.6 97.7 148 

Cigars + pipes  0.6 7.3 3 

Canadian Nonsmokers  1.0 7 

veterans Cigarettes only  14.9 325 

study Cigars only  2.9 2 

Pipe only  4.4 18 

Ex-smokers  6.1 18 

ACS 25-state Never smoked  1.0  12 49 

study Cigarettes only  9.2  111 719 1 

Cigars only  1.9  22 23 

Pipes only  2.2  27 21 

Cigarettes + other  7.4  89 336 

Cigars + pipes  0.9  11 11 

Swedish study Nonsmokers  1.0 7 1 

Cigarettes only  7.0 28 

Cigarettes + pipe  10.9 27 

Pipe only  7.1 31 

Cigars only  9.2 6 

Ex-smokers  6.1 12 

(continued on the following page) 

4-15

Table 4-7.  (continued) 

Relative Death rate No. of cases 

Study Smoking category risk per 100,000 

British doctors Nonsmokers 1.0  10 

study Current smokers 10.4 104 

Cigarettes only 14.0 140 

Pipes and/or cigars only 5.8  58 

Cigarettes + other 8.2  82 

Ex-smokers 4.3  43 

U.S. veterans Nonsmokers 1.0 

study Cigarettes 11.3 1 

Cigarettes only 12.1 

Cigars only 1.7 

Pipes only 2.1 

Ex-cigarette smokers 4.0 

2,609 

1,095 

41 

32 

517 

Norwegian Nonsmokers 1.0 7 

study Cigarettes 9.7 88 1 

Cigarettes only 9.5 70 

Pipes or cigars only 2.6 12 

Ex-smokers 2.8 11 

Figures given in original report. 

Source:  IARC, 1986. 

4-16


1 
Table 4-8.  Age-adjusted lung cancer mortality ratios for males and females, by tar and nicotine (T/N) in cigarettes 

smoked 

Males Females 

High T/N 1.00 1.00 1 

Medium T/N 0.95 0.79 

Low T/N 0.81 0.60 

The mortality rate for the category with highest risk was made 1.00 so that the relative reductions 

in risk with the use of lower T/N cigarettes could be visualized. 

Source:  U.S. DHHS, 1982. 

Table 4-9.  Relative risk for lung cancer by type of cigarette smoked (filter vs. nonfilter), in men, based on cohort and 

case-control studies 

Reference Type of study Relative risk 

Hawthorne and Cohort  0.8 

Fry (1978) 

Rimington (1981) Cohort  0.7 

Bross and Gibson (1968) Case-control  0.6 

Wynder et al. (1970) Case-control  0.6 

Dean et al. (1977) Case-control  0.5 

Source:  IARC, 1986. 

4-17 

1 
Table 4-10.  Main results of studies dealing with the relationship between smoking and different histological types of lung cancer 

4-18 

Reference Histological type Results Comments 

Doll et al. Sex No. of Relative risk Nonsmokers,  No. 

(1957) cases 1.0 (RR)  observed 

Amount of tobacco smoked (g) 

<5 5-14 15-24 25+ 

Kreyberg I M 829 4.7 10.6 14.3 25.4 3 

F 32 1.0 1.7 8.3  16 

Kreyberg II M 38 0.5 0.8 1.2 1.1 2 

F 8 1.1 2.3 4.1 5 

Hammond and  Nonsmokers, 

Horn (1958b)  Relative risk  1.0.  Only regular 

no. of packs/day  smokers considered 

<1⁄2  1⁄2-1  1+ 

Adenocarcinoma 2.0 2.5 7.0 

Other types  16.3 25.5 88.0 

Doll and Hill Death rate per 1,000 Men only 

(1964a) Amount of tobacco smoked (g) 

Ex-smokers 1-14 15-24  25+ 

Squamous-cell 

carcinoma  0.09 0.22  0.33  0.45 

Small-cell and 

anaplastic 

carcinoma  0.05 0.10  0.20  0.38 

Adenocarcinoma  0.03 0.03  0.12  0.07 

(continued on the following page) 
Table 4-10.  (continued) 

Reference Histological type Results Comments 

Haenszel and Standardized mortality ratio Women only; 

Taeuber standardized 

(1964) mortality ratio; 

total group, 

1.00 

Never- Ex­ cigarrette ________________ 

smokers Smokers smokers  <1 pack/day  >1 pack/day 

Occasional Regular cigarette smokers 

Adenocarcinoma 0.78 0.35 2.46 1.17 7.50 

Squamous-cell and 

undifferentiated 

carcinoma 0.59 0.52 1.15 2.19 8.58 

Hanbury  Women only 

(1964) 

No. of cases (%) 

"Heavy" and "medium" smokers Nonsmokers and 

"remainder" 

Small-cell 

carcinoma 18 (47) 21 (34) 

Undifferentiated 

carcinoma 9 (24) 14 (23) 

Squamous-cell 

carcinoma 9 (24) 12 (19) 

Adenocarcinoma 2 (5) 15 (24) 

4-19 

(continued on the following page) 
Table 4-10.  (continued) 

Reference Histological type Results Comments 

Vincent  Number of cigarettes smoked/day Women 

et al. (1965) only 

Total no. 

of cases None  1-20  21-40  41+  Unknown 

No.  %  No.  %  No.  %  No.  %  No.  % 

Squamous-cell carcinoma 19 10  53  3  16  2  10  2  10  2  10 

Small-cell carcinoma 17 2  12  7  41  6  35  2  12  0  0 

Adenocarcinoma 64 51  80  6  9  4  6  0  0  3  5 

Undifferentiated 22 12  54  4  18  6  27  0  0  0  0 

Others  41 32  78  8 20  1 2 0 0 0 0 

163 107  66  28  17  19  12  4  2  5  3 

Wynder et Sex  No. (%) Heavy = 41+ cigarettes/day 

al. (1970) 

Cigarette  Heavy 

smokers  smokers 

Kreyberg I  M 191 (91.0)  59 (29.9) 

F  24 (80.0)  3 (12.0) 

Kreyberg II  M  61 (82.4)  9 (14.1) 

F  21 (58.3)  1  (4.8) 

Controls  M 199 (47.4)  26  (9.8) 

F  53 (40.2)  3  (5.4) 

4-20 

(continued on the following page) 
Table 4-10.  (continued) 

Reference Histological type Results Comments 

Deaner and Pack- Number of 

Trummer years  tumors  Smokers 

(1970) Undifferentiated carcinoma  40  40  40 (100%) 

Adenocarcinoma  12  19  13 ( 68%) 

Squamous-cell carcinoma  52  9  9 (100%) 

Weiss et al. Death rate per 1,000 man-years of 

(1972) observation (adjusted for age and race) 

No. of cigarettes/day 

1-10  10-19  20+ 

Squamous-cell carcinoma 

Well differentiated  - 0.8  2.1 

Poorly differentiated  0.7  0.4  1.0 

Small-cell carcinoma  - 0.3  0.7 

Adenocarcinoma  - 0.6  1.0 

Vincent et al.  No. of cigarettes smoked/day 

(1977)  0  1-20  21-40  41+  Other 

Squamous-cell carcinoma 

Adenocarcinoma 

Small-cell carcinoma 

Large-cell carcinoma 

Bronchiolo-alveolar 

carcinoma 

Mixed 

Other 

14  219  110  120  16 

28  101  66  53  7 

4  103  62  56  6 

2  40  32  33  0 

6  20  9  6  0 

0  9  5  5  0 

6  30  19  17  4 

4-21 

(continued on the following page) 
Table 4-10.  (continued) 

Reference Histological type Results Comments 

Chan et al.  Smoking category (kg tobacco smoked during lifetime)  Women only 

(1979)  <100  100-199  >200 

Non- Manufac- Manufac- Manufacsmokers  tured  All  tured  All  tured  All 

Squamous-cell and 

small-cell carcinomas 1.0  3.6  3.4  3.7  4.2  2.6  4.1 

Adenocarcinoma 1.0  1.9  1.4  1.4  1.8  1.6  1.7 

Joly  Relative risk by duration of smoking (years)  Nonsmokers, 1.0 

et al. 

(1983)  Men  Women 

1-29  30-39 40-49  50+  1-29  30-39  40-49  50+ 

Squamous-cell 

carcinoma 15.0  15.9  39.5  42.2  4.4  9.4  31.4  51.9 

Adenocarcinoma 2.0  3.2  5.3  5.7  2.1  2.7  4.7  4.0 

Undifferentiated 

carcinoma 26.0  26.4  40.7  50.0  3.9  15.6  20.6  28.3 

Poorly differentiated 

carcinoma 6.4  7.7  10.8  10.2  3.2  7.8  5.6  13.1 

4-22 

Source:  IARC, 1986. 
estimates, particularly in women.  There are four major histological types of lung cancer:  squamous-cell carcinoma, 

small-cell carcinoma, adenocarcinoma, and large-cell undifferentiated carcinoma.  Sometimes two broad categories--

Kreyberg Group I, containing squamous-cell and small-cell carcinomas, and Kreyberg Group II, containing all other 

epithelial lung cancers, including adenocarcinomas and large-cell undifferentiated carcinomas--are used for 

classification.  The majority of the studies demonstrate an increase in the risk for lung cancer with increasing amount 

smoked for all four major histological groups in both males and females.  The slope of the gradient for 

adenocarcinomas, however, is shallower than the slopes for the other types. 

4.2.4. Proportion of Risk Attributable to Active Smoking 

Table 4-11 presents data on the proportion of lung cancer deaths attributable to smoking in various countries. 

Differences by sex and between countries largely correlate with differences in the proportion of smokers within these 

populations and the duration and intensity of cigarette usage.  In the early 1960s, 50% of U.S. men and 30% of U.S. 

women smoked, although these proportions have been declining in recent years (Garfinkel and Silverberg, 1991). 

In the United States, deaths from lung cancer currently represent one-quarter of all cancer deaths.  The 

American Cancer Society predicted there would be 143,000 lung cancer deaths in 1991 (Garfinkel and Silverberg, 

1991).  Over 85% of this lung cancer mortality is estimated to be attributable to tobacco smoking.  In other words, the 

overwhelming majority of lung cancer deaths, which are a significant portion of all cancer deaths, result from 

smoking.  The strong association between smoking and lung cancer and the dose-response relationships, with effects 

observable at low doses and no evidence of a threshold, make it highly plausible that passive smoking also causes 

lung cancer in humans. 

4.3. LIFETIME ANIMAL STUDIES 

The human evidence for the carcinogenicity of tobacco smoke is corroborated in experimental animal 

bioassays.  The main animal evidence is obtained from inhalation studies in the hamster, intrapulmonary implantations 

in the rat, and skin painting in the mouse.  There are no lifetime animal inhalation studies of ETS; however, the 

carcinogenicity of SS condensates has been demonstrated in intrapulmonary implantations and skin painting 

experiments. 

Negative responses in short-term animal studies (e.g., 60 to 90 days) are not reliable indicators of the 

carcinogenic potential of a compound because of the long latency period for cancer development.  Long-term animal 

studies at or near the maximum tolerated dose level are used to ensure an adequate power for the detection of 

carcinogenic activity (U.S. EPA, 1986a). 

4-23 
Table 4-11.  Lung cancer deaths attributable to tobacco smoking in certain countries 

Crude rate in 

persons aged 35+ 

Country Year deaths nonsmokers Observed  smokers AC  AP 

No. of deaths in In non- 1 

Expected 

2 3 4 

Canada 

Men 1978 6,435 556 142.8 11.8 5,762 0.9 

Women 1978 1,681 487 34.0 9.9 1,194 0.71 

England and Wales 

Men 1981 26,297 1,576 228.5 13.3 24,720 0.94 

Women 1981  8,430 1,663 63.3 12.4 6,767 0.80 

Japan 

Men 1981 16,638 2,868 64.8 10.7 13,184 0.83 

Women 1981  6,161 2,593 21.0 8.9 3,568 0.58 

Sweden 

Men 1981 1,777 301 85.0 14.0 1,476 0.83 

Women 1981  654 281 28.0 12.3 373 0.57 

USA 

Men 1979 72,803 5,778 166.7 12.7 67,024 0.92 

Women 1979 25,648 5,736 50.0 11.1 19,912 0.78 

1
From the Global Epidemiological Surveillance and Health Situation Assessment data bank of

 WHO. 

2
Calculated by IARC, 1986.  Slightly overestimates number of expected deaths. 3
AC, number of cases attributable to smoking.

4
AP, proportion of cases attributable to smoking.

Source:  IARC, 1986. 

4-24 
4.3.1. Inhalation Studies 

Although evidence of the carcinogenicity of cigarette smoke originated in humans, attempts were made to 

develop an inhalation model for smoking in experimental animals in order  to study the carcinogenicity of various 

tobacco products.  Such inhalation studies are difficult to conduct, however, because laboratory animals are reluctant 

to inhale cigarette smoke and will adopt shallow breathing patterns in response to aerosols and irritants.  Furthermore, 

rodents are obligatory nose-breathers, and the anatomy and physiology of the respiratory tract and the biochemistry of 

the lung differ between rodents and humans.  Because of these distinctions, laboratory animals and humans are likely 

to have different deposition and exposure patterns for the various cigarette smoke components in the respiratory 

system.  For example, rodents have extensive and complex nasal turbinates where significant particle deposition could 

occur, decreasing exposure to the lung. 

The Syrian golden hamster has been the most useful animal inhalation model found so far for studying 

smoking-induced carcinogenesis.  It is more tolerant of tobacco smoke than mice and rats and is relatively resistant to 

respiratory infections.  The hamster also has a low background incidence of spontaneous pulmonary tumors and is, in 

fact, refractory to the induction of lung cancers by known carcinogenic agents.  The inhalation of tobacco smoke by 

the hamster does, however, induce carcinomas of the larynx.  In one study (Dontenwill et al., 1973), three groups of 

80 male and 80 female Syrian golden hamsters were exposed for 10 minutes to air-diluted cigarette smoke (1:15) 

once, twice, or three times daily, 5 days per week, for their lifetimes.  Preinvasive carcinomas of the upper larynx 

were detected in 11.3%, 30%, and 30.6% of the animals, respectively, and invasive carcinomas were found in 0.6%, 

10.6%, and 6.9%, respectively.  No laryngeal tumors were observed in control animals.  In another experiment, 

exposure for 59 to 80 weeks to an 11% or 22% cigarette smoke aerosol twice daily for 12 minutes resulted in 

laryngeal carcinomas in 3 of 44 and 27 of 57 animals, respectively, providing some evidence of a dose-response 

relationship for the induction of carcinoma of the larynx by cigarette smoke (Bernfeld et al., 1979).  Bernfeld et al. 

suggest that the greater deposition of tar per unit of surface area in the larynx compared to the lung may explain the 

high yield of laryngeal cancers and lack of lung tumors in this animal model. 

4.3.2. Intrapulmonary Implantations of Cigarette Smoke Condensates 

Because of the difficulties with inhalation studies of cigarette smoke, some in vivo studies examine the 

carcinogenicity of cigarette smoke condensate (CSC) collected from smoking machines.  CSC assays may not, 

however, reveal all of the carcinogenic activity of actual cigarette smoke, because these condensates lack most of the 

volatile and semivolatile components of whole smoke.  In lifetime rat studies, intrapulmonary implants of MS 

condensate in a lipid vehicle cause a dose-dependent increase in the incidence of lung carcinomas (Stanton et al., 

1972; Dagle et al., 1978). 

SS condensates have also demonstrated carcinogenicity when implanted into rat lungs (Grimmer et al., 

1988).  SS emitted by a smoking machine was separated into condensate fractions containing the semivolatiles, the 

polycyclic aromatic hydrocarbon (PAH)-free particulates and the PAHs with two or three rings, or the PAHs with 

4-25 
four or more rings.  These fractions were implanted into female Osborne-Mendel rats, following the procedure of 

Stanton et al. (1972), at a dose level of one cigarette per animal.  At the end of the lifetime study, none of the 35 rats in 

each of the untreated control, vehicle control, or semivolatile-exposed groups had lung carcinomas.  In the group 

exposed to the fraction containing PAH-free particulates and PAHs with 2 or 3 rings, there was 1 lung carcinoma in 

35 animals.  In the group exposed to the fraction comprising PAHs with 4 or more rings, there were 5 lung 

carcinomas in 35 rats.  An additional group that was exposed to a dose of 0.03 mg benzo[a]pyrene (BaP) per rat 

exhibited 3 lung carcinomas in 35 animals.  The condensate fraction containing BaP and the other PAHs with four or 

more rings from the SS generated by a single cigarette contains about 100 ng of BaP.  Assuming a linear, 

nonsynergistic dose-response relationship, this would suggest that less than 1% of the total carcinogenicity of that 

condensate fraction can be attributed to the BaP present in the smoke. 

4.3.3. Mouse Skin Painting of Cigarette Smoke Condensates 

In addition, numerous studies have shown that when MS condensate suspended in acetone is chronically 

applied to mouse skin, significant numbers of the mice develop papillomas or carcinomas at the site of application 

(e.g., Wynder et al., 1957; Davies and Day, 1969).  Mouse skin studies have also demonstrated that MS condensate 

has both tumor-initiating and tumor-promoting capabilities (Hoffman and Wynder, 1971). 

One mouse skin painting study examined the carcinogenicity of SS condensate (Wynder and Hoffman, 

1967).  Cigarette tar from SS deposited on the funnel of a smoking machine was suspended in acetone and 

administered to mouse skin.  Fourteen of thirty mice developed skin papillomas, and 3 of 30 developed carcinomas. 

In a parallel assay in the same study, a suspension of MS condensate applied to deliver a comparable amount of 

condensate to the skin of 100 mice yielded benign skin tumors in 24 and malignant tumors in 6 of the mice.  This 

suggests that the condensate of SS has greater mouse skin tumorigenicity per unit weight than that of MS. 

4.4. GENOTOXICITY 

Supportive evidence for the carcinogenicity of tobacco smoke is provided by the demonstration of 

genotoxicity in numerous short-term assays.  Extensive reviews of these studies can be found in IARC (1986) and 

DeMarini (1983); only the highlights are presented here.  A few studies deal with whole smoke, but most examine 

CSC.  Tobacco smoke is genotoxic in virtually every in vitro system tested, providing overwhelming supportive 

evidence for its carcinogenic potential. 

In Salmonella typhimurium, for example, Basrur et al. (1978) found that both whole MS and MS 

condensates from various types of tobacco were mutagenic in the presence of a metabolic activating system.  SS (Ong 

et al., 1984) and extracts of ETS collected from indoor air (Löfroth et al., 1983; Alfheim and Ramdahl, 1984; Lewtas 

et al., 1987; Ling et al., 1987; Löfroth et al., 1988) also exhibit mutagenic activity in this bacterium.  Claxton et al. 

(1989) found that SS accounted for approximately 60% of the total S. typhimurium mutagenicity per cigarette--40% 

4-26 
from the SS particulates and 20% from the semivolatiles.  The highly volatile fraction, from either MS or SS, was not 

mutagenic. 

Similarly, cigarette smoke produced mitotic gene conversion, reverse mutation, and reciprocal mitotic 

recombination in fungi (Gairola, 1982).  In addition, CSC's induce mutations, sister chromatid exchanges, and cell 

transformation in various mammalian cells in culture.  Putnam et al. (1985) demonstrated dose-dependent increases in 

sister chromatid exchange frequencies in bone-marrow cells of mice exposed to cigarette smoke for 2 weeks. 

4.5. SUMMARY AND CONCLUSIONS 

Lung cancer mortality rates have increased dramatically over the past 60 years in males, and, more recently, 

in females, with increasing cigarette consumption.  High relative risks for lung cancer, associated with the number of 

cigarettes smoked per day, have been demonstrated in countless studies, with no evidence of a threshold level of 

exposure.  Active smoking induces all four major histological types of human lung cancer--squamous-cell 

carcinomas, small-cell carcinomas, large-cell carcinomas, and adenocarcinomas--all in a dose-related manner.  Doseresponse relationships have also been established with respect to duration of smoking.  Furthermore, lung cancer risk 

increases with the younger the age at initiation of smoking and decreases with the longer the time since cessation of 

smoking.  These latter trends, coupled with evidence from mouse skin painting studies, suggest that tobacco smoke 

has both tumor-initiating and tumor-promoting capabilities. 

Inhalation studies in hamsters confirm that MS is carcinogenic to the respiratory tract.  In addition, mouse 

skin painting experiments and intrapulmonary implantations in rats have demonstrated the carcinogenicity of 

condensates from both MS and SS (the primary component of ETS), with SS condensate having a greater potency 

than MS condensate in mouse skin painting studies.  Numerous genotoxicity tests contribute supporting evidence for 

the carcinogenic potential of MS and SS smoke and smoke condensates.  The mutagenicity of ETS and its extracts has 

also been established.  One study found that SS accounted for 60% of the total mutagenicity per cigarette. 

As discussed in Chapter 3, MS and ETS are qualitatively similar in composition, and both contain numerous 

known or suspected human carcinogens.  ETS constituents include essentially all of the same carcinogens found in 

MS, and many of these appear in greater amounts in SS, and hence, in ETS, than in MS, per unit of tobacco burned. 

This quantitative comparison is consistent with the observation noted above that SS condensates apparently have even 

greater carcinogenic potential than MS condensates. 

The unequivocal causal association between tobacco smoking and lung cancer in humans with dose-response 

relationships extending down to the lowest exposure categories, as well as the corroborative evidence of the 

carcinogenicity of both MS and ETS provided by animal bioassays and in vitro studies and the chemical similarity 

between MS and ETS (Chapter 3), clearly establish the plausibility that ETS is also a human lung carcinogen.  In 

addition, biomarker studies verify that passive smoking results in detectable uptake of tobacco smoke constituents by 

nonsmokers, affirming that ETS exposure is a public health concern (Chapter 3). 

4-27 
In fact, these observations are sufficient in their own right to establish the carcinogenicity of ETS to humans. 

According to EPA's Guidelines for Carcinogen Risk Assessment (U.S. EPA, 1986a), a Group A (known human) 

carcinogen designation is used "when there is sufficient evidence from epidemiologic studies to support a causal 

association between exposure to the agents and cancer."  The Guidelines establish "three criteria (that) must be met 

before a causal association can be inferred between exposure and cancer in humans: 

1. There is no identified bias that could explain the association. 

2. The possibility of confounding has been considered and ruled out as explaining the association. 

3. The association is unlikely to be due to chance." 

Given the strong dose-related associations, with high relative risks consistently observed across numerous 

independent studies from several countries, and the biological plausibility provided by ancillary evidence of the 

genotoxicity and animal carcinogenicity of MS and by knowledge of the existence of many specific carcinogenic 

components within MS, confounding, bias, and chance can all be ruled out as possible explanations for the observed 

association between active smoking and lung cancer.  Therefore, under the EPA carcinogen classification system, MS 

would be categorized as a Group A (known human) carcinogen.  Furthermore, the extensive chemical and 

toxicological similarities between SS and MS, detailed in Sections 3.2, 4.3, and 4.4, strongly infer that SS is also 

capable of causing lung cancer in humans, as was documented for MS in Section 4.2.  Thus, under EPA's carcinogen 

classification system, SS also belongs in Group A.  Finally, because ETS is composed of SS and exhaled MS, and 

because ETS is known to be inhaled and absorbed into the body (Section 3.3.2), ETS would similarly be categorized 

as a Group A carcinogen. 

In addition, there exists a vast body of epidemiologic data dealing specifically with lung cancer and exposure 

to ETS.  These data should also be examined in the interest of weighing all the available evidence, as recommended 

by EPA's carcinogen risk assessment guidelines (U.S. EPA, 1986a), both for hazard identification and exposureresponse assessment.  The rapid dilution of both SS and exhaled MS into the environment and changing phase 

distributions of ETS components over time raise some questions about the carcinogenic potential of ETS under actual 

environmental exposure conditions.  Furthermore, while MS and ETS may be qualitatively comparable, active 

smoking data do not constitute a good basis for quantitative estimation of the health effects of passive smoking 

because the relative uptake and deposition between active and passive smokers of the agent(s) responsible for these 

effects are not known (see Chapters 2 and 6).  Provided the epidemiologic studies are of sufficient power and 

adequate study design, this database can offer unique information on the actual lung cancer risk to nonsmokers from 

exposure to true ambient levels of ETS.  The epidemiologic evidence for the human lung carcinogenicity associated 

specifically with ETS is the subject of Chapter 5.  These epidemiologic data are then used as the basis for the 

calculation of population risk estimates for lung cancer from passive smoking in Chapter 6. 

4-28 
5. HAZARD IDENTIFICATION II: INTERPRETATION OF EPIDEMIOLOGIC 

STUDIES ON ENVIRONMENTAL TOBACCO SMOKE AND LUNG CANCER 

5.1. INTRODUCTION 

The Centers for Disease Control attributed 434,000 U.S. deaths in 1988 to smoking (CDC, 

1991a). Major disease groups related to smoking mortality include lung cancer, chronic 

obstructive pulmonary disease, coronary heart disease, and stroke, with smoking accountable for 

an estimated 87%, 82%, 21%, and 18% of total deaths, respectively. Lung cancer alone accounted 

for about 25% to 30% of the total smoking mortality, with some 100,000 deaths. The agestandardized annual lung cancer mortality rates for 1985 are estimated at 12 per 100,000 for 

females and 15 per 100,000 for males who never smoked but 130 per 100,000 for female cigarette 

smokers and 268 per 100,000 for male cigarette smokers, a relative risk of 10.8 and 17.4, 

respectively (Garfinkel and Silverberg, 1991). 

Chapter 4 discusses the biological plausibility that passive smoking also may be a risk 

factor for lung cancer because of the qualitative similarity of the chemical constituency of 

sidestream smoke, the principal source of environmental tobacco smoke (ETS), and mainstream 

smoke taken in during the act of “puffing” on a cigarette, and because of the apparent 

nonthreshold nature of the dose-response relationship observed between active smoking and lung 

cancer. Although the relative risk of lung cancer from passive smoking would undoubtedly be 

much smaller than that for active smoking, the ubiquity of ETS exposure (Chapter 3) makes 

potential health risks worth investigating. 

This chapter analyzes the data from the large number of epidemiologic studies on ETS and 

lung cancer that contain data on the effects of ETS on never-smoking women. Although some of 

the studies involve male nonsmokers and former smokers of both sexes, the female never-smokers 

comprise the large majority of the database--more than 3,000 cases and 6,000 controls in the 27 

case-control studies and almost 300,000 female never-smokers followed in the 4 cohort studies. 

Whenever study data are separated by sex and smoking status, women never-smoker results are 

used. The use of a more homogeneous group allows more confidence in the results of combined 

study analyses. All of the studies used provide data on adult home exposure to ETS. Some also 

provide information on childhood and/or workplace exposure, but there is far less information on 

these exposures; therefore, in order to develop one large database for analysis, only the female 

exposures from spousal smoking are considered. The exposure surrogate used is a report of the 

husband’s smoking status. Wherever a measure of the amount of exposure to husband’s smoking is 

available, additional analyses are performed to examine effects in the highest exposure groups 

(Section 5.3.3.2) and dose-response relationships (Section 5.3.3.3). Virtually all of the 31 studies 

5-1 
available classify never-smoking women as “exposed” or “unexposed” to ETS based on self- or 

proxy-reported smoking in the subject’s environment, usually according to whether or not a 

woman is married to a smoker. In addition, 17 studies provide sufficient information for highest 

exposure group and exposure-response analyses. Other analyses of the data include adjusting for 

the potential upward bias of smoker misclassification (Section 5.2.2); examining confounders, 

effect modifiers, and sources of potential bias (Section 5.4); and pooling qualitatively higher 

ranked studies (Section 5.5). It is hoped that by analyzing the data in several different ways, a 

clear picture will emerge (Section 5.6). 

Throughout this chapter, one-tailed tests of significance (p = 0.05) are used, which 

increases the statistical ability (power) to detect an effect. The 90% confidence intervals used for 

the analyses performed are consistent with the use of the one-tailed test. The justification for this 

usage is based on the a priori hypothesis (from the plausibility of a lung cancer effect documented 

in Chapters 3 and 4) that a positive association exists between exposure to ETS and lung cancer. 

Epidemiologic evidence of an association between passive smoking and lung cancer first 

appeared 10 years ago in a prospective cohort study in Japan (Hirayama, 1981a) and a case-control 

study in Greece (Trichopoulos et al., 1983). Both studies concluded that the lung cancer incidence 

and mortality in nonsmoking women was higher for women married to smokers than for those 

married to nonsmokers. Although there are other sources of exposure to ETS, particularly outside 

the home, the assumption is that women married to smokers are exposed to more tobacco smoke, 

on average, than women married to nonsmokers. These two studies, particularly the cohort study 

from Japan, evoked considerable critical response. They also aroused the interest of public health 

epidemiologists, who initiated additional studies. 

At the request of two Federal agencies-­the U.S. Environmental Protection Agency

(Office of Air and Radiation) and the U.S. Department of Health and Human Services (Office of 

Smoking and Health)--the National Research Council (NRC) formed a committee on passive 

smoking to evaluate the methods for assessing exposure to ETS and to review the literature on the 

health consequences. The committee’s report (NRC, 1986) addresses the issue of lung cancer risk 

in considerable detail and includes summary analyses of the evidence from 10 case-control and 3 

cohort (prospective) studies. It concludes, “Considering the evidence as a whole, exposure to ETS 

increases the incidence of lung cancer in nonsmokers.” 

The NRC committee was particularly concerned about the potential bias in the study 

results caused by the fact that current and former smokers may have incorrectly reported 

themselves as lifelong nonsmokers (never-smokers). Using reasonable assumptions for 

misreported smoking habits, the committee determined that a plausible range for the true relative 

5-2 
risk is 1.15 to 1.35, with 1.25 the most likely value. When these relative risks also are corrected 

for background exposure to ETS to make the risk relative to a baseline of zero ETS exposure, the 

resultant estimate is 1.42, with a plausible range of 1.24 to 1.61. 

Two other major reports on passive smoking have appeared: the Surgeon General’s report 

on the health consequences of passive smoking (U.S. DHHS, 1986) and the report on methods of 

analysis and exposure measurement related to passive smoking by the International Agency for 

Research on Cancer (IARC, 1987a). The Surgeon General’s report concludes: 

The absence of a threshold for respiratory carcinogenesis in active smoking, the 

presence of the same carcinogens in mainstream and sidestream smoke, the 

demonstrated uptake of tobacco smoke constituents by involuntary smokers, and 

the demonstration of an increased lung cancer risk in some populations with 

exposures to ETS lead to the conclusion that involuntary smoking is a cause of lung 

cancer. 

The IARC committee emphasized issues related to the physicochemical properties of ETS, 

the toxicological basis for lung cancer, and methods of assessing and monitoring exposure to ETS. 

Included in the 1987 IARC report is a citation from the summary statement on passive smoking of 

a previous IARC report that the epidemiologic evidence available at that time (1985) was 

compatible with either the presence or absence of lung cancer risk. Based on other considerations 

related to biological plausibility, however, it concludes that passive smoking gives rise to some risk 

of cancer. Specifically, the report (IARC, 1986) states: 

Knowledge of the nature of sidestream and mainstream smoke, of the materials 

absorbed during “passive smoking,” and of the quantitative relationships between 

dose and effect that are commonly observed from exposure to carcinogens . . . 

leads to the conclusion that passive smoking gives rise to some risk of cancer. 

In the years since those reports, the number of studies available for analysis has more than 

doubled. There are now 31 epidemiologic studies available from eight different countries, listed 

in Table 5-1. Twenty-seven studies employ case-control designs, denoted by the first four letters 

of the first author’s name for convenient reference, and four are prospective cohort studies, 

distinguished by the designation “(Coh).” Six case-control studies, FONT (USA), JANE (USA), 

KALA (Greece), LIU (China), SOBU (Japan), and WUWI (China), have been published as 

recently as 1990. The small cohort study from Scotland (Gillis et al., 1984) has been updated and 

is now included under the name HOLE(Coh); another small cohort study on Seventh-Day 

Adventists in the United States, an unpublished dissertation, is included as BUTL(Coh). The 

abstracts for a second case-control study by Kabat and Wynder and a new one by Stockwell and 

colleagues are included in Section A.4, but insufficient information is available to include their 

results. 

5-3 
Table 5-1. Epidemiologic studies on ETS and lung cancer in this report and tier ranking 

Study Tier1 Country Within country References 

AKIB 

BROW 

BUFF 

CHAN 

CORR 

FONT 

GAO 

GARF 

GENG 

HUMB 

INOU 

JANE 

KABA 

KALA 

KATA2 

KOO 

LAMT 

LAMW 

LEE 

LIU 

PERS 

SHIM 

SOBU 

SVEN 

2 

3 

3 

4 

2 

1 

3 

2 

4 

2 

4 

2 

2 

1 

1 

2 

Japan 

United States 

United States 

Hong Kong 

United States 

United States 

China 

United States 

China 

United States 

Japan 

United States 

United States 

Greece 

Japan 

Hong Kong 

Hong Kong 

Hong Kong 

England 

China 

Sweden 

Japan 

Japan 

Sweden 

Hiroshima 

Colorado 

Texas 

Louisiana 

Five metro areas 

Shanghai 

New Jersey, Ohio 

Tianjin 

New Mexico 

Kanajawa 

New York 

New York 

Athens 

Xuanwei 

Nagoya 

Osaka 

Stockholm 

Akiba et al. (1986) 

Brownson et al. (1987) 

Buffler et al. (1984) 

Chan and Fung (1982) 

Correa et al. (1983) 

Fontham et al. (1991) 

Gao et al. (1987) 

Garfinkel et al. (1985) 

Geng et al. (1988) 

Humble et al. (1987) 

Inoue and Hirayama (1988) 

Janerich et al. (1990) 

Kabat and Wynder (1984) 

Kalandidi et al. (1990) 

Katada et al. (1988) 

Koo et al. (1987) 

Lam et al. (1987) 

Lam (1985) 

Lee et al. (1986) 

Liu et al. (1991) 

Pershagen et al. (1987) 

Shimizu et al. (1988) 

Sobue (1990) 

Svenson et al. (1989) 

(continued on the following page)

5-4
Study Country Within country References

Table 5-1. (continued) 

Study Tier Country Within country References 

TRIC 3 Greece Athens Trichopoulos et al.

(1981, 1983) 

WU 2 

WUWI 4 

BUTL(Coh) 2 

GARF(Coh) 3 

HIRA(Coh) 2 

HOLE(Coh) 1 

United States 

China 

United States 

United States 

Japan 

Scotland 

California 

California 

Paisley Renfrew 

Wu et al. (1985) 

Wu-Williams and 

Samet (1990) 

Butler (1988) 

Garfinkel (1981) 

Hirayama (1984) 

Hole et al. (1989) 

1

Tier rankings refer to this report’s ratings of studies for utility of studying the association of ETS

and lung cancer, where “1” is highest (see Section 5.5 and Section A.3).

2

KATA has no tier number because the odds ratio cannot be calculated. 

Because of coincidental timing, the 1986 reports of the Surgeon General and the NRC 

review approximately the same epidemiologic studies. More specifically, the NRC report includes 

nine of the studies shown in Table 5-1: AKIB, CHAN, CORR, GARF, KABA, KOO, LEE, 

PERS, and TRIC; WU was available but not included because the crude data were not reported. 

(Crude data consist of the number of exposed and unexposed subjects among lung cancer cases 

and controls, where a subject is typically classified as exposed to ETS if married to a smoker.) 

The NRC also excluded an earlier version of the KOO study and the studies by Knoth et al. (1983) 

(no reference population was given), Miller (1984) (did not report on lung cancers separately), and 

Sandler et al. (1985) (included very few lung cancers). Aside from WU, these studies also are 

omitted from this report for the same reasons. 

Tables 5-2 and 5-3 provide an overview of some descriptive features of the individual 

ETS studies included in this report. The studies are grouped by country in Table 5-2, which 

indicates the time period of data collection in each study, sample size, and prevalence of ETS 

exposure for each study. The geographical distribution of the current epidemiologic evidence is 

diverse. By country, the number of studies and its percentage of the total number of studies over 

all countries is as follows: China (4, 13%), England (1, 3%), Greece (2, 6%), Hong Kong (4, 13%), 

Japan (6, 19%), Scotland (1, 3%), Sweden (2, 6%), and United States (11, 35%). (One of the 

5-5 
Table 5-2. Studies by location, time, size, and ETS exposure 

Country Study 

Accrual1 Size2 ETS exposure (%)3 

period Cases Controls Cases Controls 

Greece KALA 1987-89 90 116 71 60 

Greece TRIC 1978-80 40 149 73 52 

Hong Kong CHAN 1976-77 84 139 60 53 

Hong Kong KOO 1981-83 86 136 59 49 

Hong Kong LAMT 1983-86 199 335 58 45 

Hong Kong LAMW 1981-84 604 1444 624 444 

Japan AKIB 1971-80 

Japan HIRA(Coh) 1965-81 

Japan INOU 1973-83 

Japan SHIM 1982-85 

Japan SOBU 1986-88 

94 270 

---- 91,540 ----

22 47 

90 163 

144 731 

19 47 

41 196 

---- 9,2075 ----

22 133 

420 7806 

134 402 

---- 176,739 ----

20 162 

191 191 

24 25 

298 628 

78 70 

----- 76 -----

82 64 

58 56 

56 54 

USA BROW 1979-82 

USA BUFF 1976-80 

USA BUTL(Coh) 1976-82 

USA CORR 1979-82 

USA FONT 1985-88 

USA GARF 1971-81 

USA GARF(Coh) 1959 - 72 

USA HUMB 1980-84 

USA JANE 1982-84 

USA KABA 1961-80 

USA WU 1981-82 

21 

80 

64 

70 

67 

15 

84 

----- 345 -----

46 

636 

61 

----- 72 -----

75 56 

*7 

607 

54 60 

* * 

W. Europe 

Scotland 

England 

HOLE(Coh) 1972-85 ---- 1,784 ---- ----- 73 -----

LEE 1979-82 32 66 69 68 

(continued on the following page)

5-6
Table 5-2. (continued) 

Country Study 

Accrual1 

period 

Size2 ETS exposure (%)3 

Cases Controls Cases Controls 

W. Europe 

(continued) 

Sweden 

Sweden 

China 

China 

China 

China 

PERS 1961-80 67 * 49 * 

SVEN 1983-85 34 174 71 66 

GAO 1984-86 246 375 77 74 

GENG 1983 54 93 63 44 

LIU 1985-86 54 202 83 87 

WUWI 1985-87 417 602 49 55 

1

Time during which cases occurred.

2

Number of subjects included in ETS analyses; where numbers differ for spousal smoking and 

other exposures, those for spousal smoking are given.

3

Spousal smoking unless otherwise noted.

4

Adenocarcinoma only. Data for all cell types were available only for general passive smoke 

exposure, which showed 77% of 75 cases and 56% of 144 controls exposed.

5

Figure pertains to “spouse pairs” cohort, which is of principal interest regarding ETS; a subgroup 

of this cohort comprised the “ASHMOG” cohort.

6

Figure is for population controls; study also included 351 colon cancer controls (66% exposed).

7

ORs but no exposure prevalences are presented for spousal smoking in the source. The value 

shown for controls is taken from KABA, as closest to JANE in time and location; no exposure 

percentage is assumed for cases.

8

Adenocarcinoma only. Analyses for other cell types included smokers while adjusting for 

smoking status. 

*Data not available. 

5-7
Table 5-3. Case-control studies of ETS: characteristics 

Study 

Percentage 

proxy 

response

1 

Ca Co 

Female age2 

Ca Co 

Source of 

controls 

Matched 

variables 

ETS 

sample 

matched 

AKIB 90 

BROW 69 

BUFF 82 

CHAN * 

CORR 

FONT 

GAO 

GARF 

GENG 

HUMB 

INOU 

JANE 

* 

34 

0 

88 

0 

* 

* 

3310 

88 

39 

76 

* 

* 

0-108 

* 

* 

0 

* 

* 

3310 

70.2 * 

35-95 * 

66.3 68.2 

30-79 30-79 

39-70 39-70 

* * 

20-79 20-79 

35-69 35-69 

40 40 

65 65 

85 85 

* 

67.110 

* 

68.110 

Atomic bomb 

survivor 

population 

Cancer cases4 

Cancer cases6 

Orthopedic 

patients 

Hospital 

patients7 

Cancer cases; 

general 

population 

General 

population 

Cancer cases9 

* 

General 

population 

Cerebrovascular disease 

deaths 

New York Age, sex, 

State Dept. of county, 

Motor smoking 

Vehicles history 

Age, sex, 

residence, 

vital status, 

med. subject3 

Age, sex 

Age, sex 

Matched but 

variables 

unspecified 

Age (± 5), 

sex, race 

Age, (for 

cancer 

controls) race 

Age (± 5) No5 

Age (± 5),

hospital 

Age (± 2), 

sex, race, 

marital status 

Age (± 10), 

sex, ethnicity 

Age, year 

of death 

(± 2.5), 

district 

No 

No5 

No5 

No5 

No5 

Yes 

Yes 

No5 

No5 

No5 

Yes 

(continued on the following page) 

5-8
Table 5-3. (continued) 

Study 

Percentage 

Proxy 

response

1 Female age2 

ETS 

Source of Matched sample 

Ca Ca Co controls variables matched 

KABA 0 0 61.6 53.9 Patients11 

KALA 0 35 

KATA 0 * 

KOO 0 

0 35 

0 67.8 

0 * * 

Orthopedic 

patients 

Noncancer 

patients 

“Healthy”12 

LAMT 0 * “Healthy”13 

LAMW * 

0 * 

* 67.5 66 

LEE 3815 38 35-74 35-74 

Hospitalized 

orthopedic 

patients 

Patients16 

LIU 0 0 52 52 

PERS *18 * * 19 

0 59 

35-81 

General 

population? 

*20 

SHIM 58 

35-81 

SOBU 

SVEN 

0 60 

0 66.3 

56 Patients 

General 

population 

Age (± 5), 

sex, race, 

hospital 

Sex 

Age (± 2), 

sex 

Age (± 5),

residence, 

housing 

Age (± 5),

residence 

Age, socioeconomic 

status, 

residence14 

Age, sex, 

hospital 

location, time 

of interview 

Age (± 2),

sex, village 

Age (± 1), 

sex 

Age (± 1),

hospital, 

admission 

date 

None 

Age 

Yes 

Yes 

Yes 

No5 

No5 

No5 

No5,17 

Yes 

Yes 

Yes 

No 

No5 

Co 

(continued on the following page) 

5-9
Table 5-3. (continued) 

Percentage 

proxy 

response

1 

Study 

Female age2 

Source of 

Ca controls 

Matched 

variables 

ETS 

sample 

matched 

TRIC 0 0 62.8 

WU 0 0 <76 

WUWI 0 0 55.922 

62.3 Hospitalized Age, No5 

orthopedic occupation, 

patients education” 

<76 Neighbor- Age (± 5), No5 

hood13 sex, race 

55.422 General Sex, age

23 No5 

population 

Ca Co Co 

1

“Ca” and “Co” stand for “cases” and “controls,” respectively.

2

Single values are the average or median. Paired values are the range.

3

Participation in RERF biennial medical examination program.

4

Persons with cancers of bone marrow or colon in Colorado Control Cancer Registry.

5

Not matched on personal smoking status (e.g., smoker/nonsmoker).

6

Population-based and decedent comparison subjects selected from state and Federal records.

7

Assorted ailments.

8

0% for general population and 10% for colon cancer controls.

9

Colorectal cancer.

10Includes males and females and long-term ex-smokers. 11Diseases not related to smoking. 12Selected from a healthy population. 13Living in neighborhood of matched case. 14“Similar” but not actually matched. 15Applies only to the 143 patients in the followup study. 16Excluding lung cancer, chronic bronchitis, ischemic heart disease, and stroke. 170ngoing studymodified for passive smoking.

18No overall percentages given. 19Two control groups: 15 to 65 and 35 to 85 for both cases and controls in groups 1 and 2,

respectively. 20Two control groups were randomly chosen from the cohort under study. 21Patients in the same or adjacent wards with other diseases. 22Entire study population, including smokers. 23Frequency matched by 5-year age group to age distribution of cases reported in study area

2 years prior to initiation of study.

*Data not available.

5-10
studies from Japan, KATA, does not appear in most of the tables because the odds ratio cannot be 

calculated.) The studies differ by size, however, which has to be taken into account in analysis. 

There are two large cohort studies, GARF(Coh) and HIRA(Coh), conducted in the United States 

and Japan, respectively, and two very small ones, BUTL(Coh) and HOLE(Coh), from the United 

States and Scotland, respectively. There are two exceptionally large case-control studies--FONT 

and WUWI of the United States and China; the first was designed specifically to, assess the 

association between ETS and lung cancer, whereas the second has broader exploratory objectives. 

The accrual periods of the case-control studies are typically 2 to 4 years in length 

(exceptions with longer periods are AKIB [9 years], INOU [10 years], GARF [10 years], KABA 

[19 years], and PERS [9 years]) and occur between the early 1970s and late 1980s (exceptions are 

KABA [1961-1980] and PERS [1961-1980]). The two large cohort studies were conducted 

relatively early (GARF(Coh), 1959-72; HIRA(Coh), 1965-81). Differences in study duration or 

accrual period should not be consequential for hazard identification, which is the topic addressed 

in this chapter, but both factors affect the estimation of population risk (Chapter 6). Earlier study 

results are more uncertain for projection of current risk, and parameter values used for modeling 

are more uncertain when based on extended study periods. Table 5-2 also demonstrates 

variability across studies in the percentages of cases and controls classified as exposed to ETS. For 

example, at the extremes for U.S. studies alone, BUFF and BROW classify 84% and 15% of 

controls as exposed to ETS, respectively. Statistical variability and differences across 

subpopulations sampled are partially explanatory, but a major factor is differences between 

researchers’ criteria for classification of subjects as exposed to ETS. This issue affects study 

comparability and observed values of relative risks, which affect both hazard identification and 

characterization of population risk. 

Another example of a study feature of broad consequences in both case-control and cohort 

studies is the method of diagnosis or confirmation of lung cancer and exclusion of secondary lung 

cancers in subjects classified as having lung cancer, as shown in Table 5-4. Accurate 

classification of subjects vis-a-vis the presence or absence of primary lung cancer is essential to 

the validity of results; inaccurate classification can reduce the chance of detecting a positive 

association between ETS exposure and lung cancer, if it exists, by biasing the observed relative 

risk toward unity. (Note: “Relative risk” is used to mean the estimate of the true [but unknown] 

relative risk. For case-control studies, the estimate used is the odds ratio. For editorial 

convenience, “relative risk” is used for both case-control and cohort studies.) 

The large majority of the studies (27 of 31 total) are of the case-control type, which are 

subject to more potential sources of bias than the cohort studies (see discussion in Section 5.4.1). 

5-11 
Table 5-4. Diagnosis, confirmation, and exclusion of lung cancer cases 

Diagnosis/Confirmation (%)1 

Study Histology Cytology 

Radio./ Other/ 

clinical unspec. 

Excluded 

secondary 

LC2 

AKIB3 

BROW 

BUFF3,4 

CHAN3,4 

CORR3 

FONT 

GAO3,5 

GARF5 

GENG3 

HUMB6,7 

INOU 

JANE3 

KABA 

KALA 

KATA 

KOO 

LAMT 

LAMW 

LEE 

LIU8 

PERS 

SHIM 

SOBU 

SVEN3 

TRIC3 

WU 

WUWI3 

BUTL(Coh)9 

GARF(Coh) 

53 

82 

97 

100 

43 

100 

85 

* 

99 

100 

48 

100 

94 

* 

83 

100 

100 

70 

28 

100 

42 

* 

4 

100 

100 

38 

83 

* 

38 14 

100 

100 

* 

17 

16 

29 

37 

32 

100 

* 

43 0 

18 

3 

19 10 

4 11 

17 

* * 

1 

6 

* 

83 

35 

26 

* 

Y 

Y 

Y 

N 

Y 

Y 

Y 

Y 

N 

Y 

N 

Y 

Y 

Y 

N 

Y 

Y 

Y 

N 

N 

Y 

Y 

Y 

Y 

N 

Y 

Y 

Y 

N 

(continued on the following page)

5-12
1

2

3

4

5

6

7

Table 5-4. (continued) 

Diagnosis/Confirmation 1 

Study 

HIRA(Coh) 

HOLE(Coh)10 

Histology 

* 

* 

Cytology 

* 

* 

Excluded 

Radio./ Other/ secondary clinical unspec. LC2 

* N 

* N 

(%)

Figures apply to confirmation of original diagnosis when conducted. 

Y (for “yes”) if specifically indicated; otherwise, N (for “no”). 

Not restricted to never-smokers (contains former smokers or ever-smokers). 

Inconsistency in article. May be 100% histology. 

Diagnostic information was reviewed for study. 

Includes males. 

Available histologic specimens (17 cases) reviewed by pathologists. Poor agreement between 

review diagnoses and original cancer registry diagnoses (8 of 17 cases). Only reviewed cases, 

however, are presented in article.

8

Includes male ever- and never-smokers and one female ever-smoker (control).

9

Includes one former smoker. 

10Death certificate diagnosis checked against Scottish cancer registry records. 

*Data not available. 

To continue the overview depicting some basic similarities and differences between studies that 

may affect analysis of their results, some additional characteristics of the case-control studies 

alone are summarized in Table 5-3. The percentage of proxy response is high for some studies, 

but there is little basis for assessing the direction or magnitude of potential bias from this source. 

The age range of subjects differs across studies, but there is insufficient information on age 

distributions within studies to evaluate the effect of age or to adjust for differences between 

studies. The source of control subjects is a potential source of bias in some studies. 

The table heading “ETS sample matched” refers to whether design matching applies to the 

ETS subjects (the never-smokers used for ETS/lung cancer analysis). As indicated under 

“matched variables,” controls are virtually always matched (or at least similar) to cases on age and 

usually on several other variables as well that the researcher suspects may affect comparability of 

cases and controls. The matching often refers to a larger data set than the ETS subjects only, 

however, because many studies included smokers and investigated a number of issues in addition 

to whether passive smoking is associated with lung cancer. When the data on ETS subjects are 

5-13 
extracted from the larger data set, matching is not retained unless smoking status was one of the 

matching variables. 

Although matching is commonly used as a method to reduce potential confounding, 

effective techniques also may be implemented during analysis of the data (e.g., the use of 

poststratification or logistic regression adjustment for unmatched, stratified, or frequencymatched samples). Use of a method of analysis that adjusts for known or suspected confounders 

and factors that may interact with ETS exposure to affect risk of lung cancer is particularly 

important for studies that are not designated as “ETS sample matched” in Table 5-3. Even with 

matched data, a method of analysis that controls for confounding, such as the use of matched 

pairs or regression techniques, is preferable. In fact, Breslow and Day (1980, p. 32) describe the 

main purpose of matching in a case-control study as permitting use of efficient analytical methods 

to control confounding by the factors used for matching. 

The analysis for hazard identification in this report follows two approaches. The first 

approach (Section 5.3) treats all studies equally, i.e., statistical methods are applied to all studies 

without regard to differences in study utility for the task of hazard identification. Differences in 

study size, of course, are taken into account by the statistical methods. Statistical inference 

includes estimation, with confidence intervals, and hypothesis testing for an effect (an increased 

relative risk in ETS-exposed subjects) and for an upward trend (an increase in relative risk as 

some measure of ETS exposure increases). The second approach (Section 5.5) is motivated by the 

heterogeneity of the study evidence, as described above.Study size aside, some studies have 

higher utility than others for assessing questions related to ETS and lung cancer and thus should 

be given more weight. To implement this extended data interpretation, all studies are first 

reviewed individually for sources of bias and confounding that might affect interpretation of 

results for assessing ETS and lung cancer and then assigned a tier number from 1 to 4 accordingly. 

Tier 1 contains those studies of greatest utility for investigating a potential association between 

ETS and lung cancer. Other studies are assigned to Tiers 2, 3, and 4 as confidence in their utility 

diminishes. (Note: Study utility does not mean study quality. Utility is evaluated with respect to 

the research objectives of this report, while the objectives of individual studies often differ.) 

Pooled estimates of relative risk by country are then recalculated by tiers, beginning with the 

studies of highest utility (Tier 1) and adding studies from Tiers 2, 3, and 4 successively to see 

what effect a judgment of utility has on the overall outcome in each country. The criteria used in 

evaluating studies and the procedure for assigning them to tiers are described in Appendix A, 

which also contains the individual study reviews. 

5-14
The selection of the most appropriate relative risk estimate to be used from each study is 

addressed in Section 5.2.1. In Section 5.2.2, each chosen relative risk estimate is adjusted 

downward to account for bias expected from some smokers misrepresenting themselves as 

nonsmokers. This topic has been a contentious issue in the literature for several years, with claims 

that this one source of systematic upward bias may account entirely for the excess risk observed in 

epidemiologic studies. Recent detailed investigation of this topic by Wells and Stewart 

(unpublished) make that claim unlikely (Appendix B). They found that a reasonable correction 

for bias, calculated on a study-by-study basis, is positive but small. Following this methodology, 

this report makes reductions in the relative risk estimates at the outset for each study individually 

before statistical inference or pooling estimates from studies of the same country. This is in 

contrast to the NRC report (1986), which makes the same downward adjustment to all studies 

(applied to an overall estimate of relative risk obtained after pooling all study estimates). 

The estimates adjusted for smoker misclassification bias are the basis for statistical 

inference in Sections 5.3 (without regard to tier classification) and 5.5 (analysis by tier 

classification). Section 5.4 reviews the study results on potential modifying factors. Conclusions 

are then drawn for hazard identification (i.e., whether ETS is causally associated with increased 

lung cancer mortality) based on the total weight of evidence. Chapter 6 of this report addresses 

the upward adjustment on the U.S. relative risk estimate for background ETS exposures and the 

U.S. population risk of lung cancer from ETS. 

5.2. RELATIVE RISKS USED IN STATISTICAL INFERENCE 

5.2.1. Selection of Relative Risks 

Two considerations largely affect the choice of relative risk (RR): (1) whether other 

relevant cofactors are taken into account (namely, potential confounders and risk modifiers that 

may be correlated with ETS exposure), and (2) the source and place of ETS exposure used. The 

alternatives (not yet adjusted for smoker misclassification) are shown by study in Tables 5-5 and 

5-6, with the ones selected for analysis in this report in boldface type. Table 5-5 lists the RRs 

and their confidence intervals, along with explanatory footnotes, and Table 5-6 provides 

information on source and place of exposure and on the adjusted analysis. Because most studies 

include spousal smoking, and interstudy comparisons may be useful, spousal smoking was the 

preferred ETS surrogate in all except for LAMW and SOBU. In LAMW, spousal smoking data are 

limited to cases with adenocarcinoma; in SOBU, the data for cohabitants are separate from data 

for spousal smoking, and much of the ETS exposure appears to result from the cohabitants. Only 

data for broader exposure to ETS than spousal smoking alone were collected in BUFF, CHAN, 

SVEN, and HOLE(Coh). 

5-15 
Table 5-5. Estimated relative risk of lung cancer from spousal ETS by epidemiologic study 

(crude and adjusted for cofactors) 

Never-smokers 

Case-control Crude RR1,2 Adj. RR1,2,3 

AKIB 

BROW 

BUFF 

CHAN 

CORR 

FONT9 

GAO 

GARF 

GENG 

HIRA13 

HUMB 

INOU 

JANE 

1.52 

(0.96, 2.41) 

1.524 

(0.49, 4.79)

1.824,5 

(0.45, 7.36)6 

0.817 

(0.39, 1.66) 

0.755 

(0.48, 1.19) 

2.078 

(0.94, 4.52) 

1.37 

(1.10, 1.69)

1.21 

(0.94, 1.56)

1.32 

(1.08, 1.61) 

1.19 

(0.87, 1.63) 

1.31 

(0.93, 1.85) 

2.16 

(1.21, 3.84) 

1.5310 

(1.10, 2.13) 

2.34 

(0.96, 5.69) 

2.5514 

(0.90, 7.20) 

0.86 

(0.57, 1.29) 

1.5 

(1.0, 2.5) 

* 

1.684,5 

(0.39, 6.90)6 

* 

* 

* 

1.29 

(1.03, 1.62)

1.28 

(0.98, 1.66) 

* 

1.3410,11 

1.7012 

(0.98, 2.94)6 

* 

1.6410 

* 

2.2 

(0.9, 5.5) 

2.5410,15 

* 

0.93/0.4416 

(continued on the following page) 

5-16
Table 5-5. (continued) 

Never-smokers 

Case-control Crude RR1,2 Adj. RR1,2,3 

KABA17 0.79 * 

(0.30, 2.04) 

KALA 1.6218 1.92 

(0.99, 2.65) (1.02, 3.59)6 

1.41 * 

(0.78, 2.55) 

KATA * 19 * 

KOO 1.55 1.64 

(0.98, 2.44) 

LAMT 1.65 * 

(1.22, 2.22) 

LAMW 2.5120 * 

(1.49, 4.23) 

LEE 1.03 0.75/1.6021 

(0.48, 2.20) 

LIU 0.74 0.77 

(0.37, 1.48) (0.35, 1.68) 

PERS 1.28 1.2 

(0.82, 1.98) (0.7, 2.1)6 

SHIM 1.0822 * 

(0.70, 1.68) 

SOBU 1.0618 1.1318 

(0.79, 1.44) (0.78, 1.63)6 

1.77 1.57 

(1.29, 2.43) (1.07, 2.31)6 

SVEN 1.265 1.45 

(0.65, 2.48) 

TRIC 2.0823 * 

(1.31, 3.29) 

WU 1.4124 1.2 

(0.63, 3.15) (0.6, 2.5)6 

WUWI 0.79 0.7 

(0.64, 0.98) 

(continued on the following page) 

5-17
Table 5-5. (continued) 

Never-smokers 

Case-control Crude RR1,2 Adj. RR1,2,3 

I 

BUTL(Coh) 2.4525 2.02 

(0.48, 8.56)6 

GARF(Coh) * 1.1710 

(0.85, 1.61)6 

HIRA(Coh) 

HOLE(Coh)26 

1.38 1.61 

(1.03, 1.87) * 

2.27 1.99 

(0.40, 12.7) (0.24, 16.7)6 

1

Parentheses contain 90% confidence limits, unless noted otherwise. When not represented in the 

original studies, the crude ORs and their confidence limits were calculated (or verified) by the 

reviewers wherever possible. Boldface indicates values used for analysis in text of this report. 

Odds ratios are shown for case-control studies; relative risks are shown for cohort studies.

2

0Rs for never-smokers apply to exposure from spousal smoking, unless indicated otherwise.

3

Calculated by a statistical method that adjusts for other factors (see Table 5-3), but not 

corrected for smoker misclassification. 

4

Adenocarcinoma only. Data for crude OR values communicated from author (Brownson).

5

Exposure at home and/or at work.

6

95% confidence interval. 

7

Exposure to regularly smoking household member(s). Differs slightly from published value of 

0.78, wherein 0.5 was added to all exposure cells.

8

Excludes bronchioalveolar carcinoma. Crude OR with bronchioalveolar carcinoma included is 

reported to be 1.77, but raw data for calculation of confidence interval are not provided.

9

The first, second, and third entries are calculated for population controls, colon cancer controls,

and both control groups combined, respectively. For adenocarcinoma alone, the corresponding

ORs, both crude and adjusted, are higher by 0.15-0.18.

10Composite measure formed from categorical data at different exposure levels. 11For GAO, data are given as (number of years lived with a smoker, adjusted odds ratio [OR]):

(<20, 1.0), (20-29, l.l), (30-39, 1.3), (40+, 1.7).

12Estimate for husband smoking 20 cig./day. 13Case-control study nested in the cohort study of Hirayama. OR for ever-smokers is taken from

cohort study. This case-control study is not counted in any summary results where HIRA(Coh)

is included.

140R reported in study is 2.25, in contrast to the value shown that was reconstructed from the

confidence intervals reported in the study; no reply to inquiry addressed to author had been

received by press time.

15For INOU, data are given as (number of cig./day smoked by husband, adj. OR): (<19, 1.58), 

(20+, 3.09).

16From subject responses/from proxy responses. 

(continued on the following page) 

5-18 
Table 5-5. (continued) 

17For second KABA study (see addendum in study description of KABA in Appendix A), 

preliminary unpublished data and analysis based on ETS exposure in adulthood indicate 68% of 

never-smokers are exposed and OR = 0.90 (90% C.I. = 0.51, 1.58), not dissimilar from the table 

entry shown.

18For the first value, “ETS-exposed” means the spouse smokes; for the second value, “ETSexposed” means a member of the household other than the spouse smokes.

19OR is not defined because number of unexposed subjects is zero for cases or controls. 20Table entry is for exposure to smoking spouse, cohabitants, and/or coworkers; includes lung 

cancers of all cell types. OR for spousal smoking alone is for adenocarcinoma only: 2.01 (90% 

C.I. = 1.20, 3.37). 21From subject responses/from spouse responses. 22From crude data, estimated to be: exposed cases 52, exposed controls 91, unexposed cases 38, 

unexposed controls 72. 23Known adenocarcinomas and alveolar carcinomas were excluded, but histological diagnosis was 

not available for many cases. Data are from Trichopoulos et al. (1983). 24Raw data for WU are from Table 11 of Surgeon General’s report (U.S. DHHS, 1986). Data 

apply to adenocarcinoma only.

25RR is based on person-years of exposure to spousal smoking.“Prevalence” in those units is 20%. 

26RR values under never-smoker are for lung cancer mortality. For lung cancer incidence, crude 

RR is 1.51 (90% C.I. = 0.41, 5.48) and adjusted RR is 1.39 (95% C.I. = 0.29, 6.61). 

*Data not available. 

5-19
1 Table 5-6. Effect of statistical adjustments for cofactors on risk estimates for passive smoking

Case-control Exposure Crude Adj. Adjustment Adj. 

study Source2

 Place3 RR4 RR4 factor(s)5 technique6 

AKIB 

BROW 

BUFF 

CHAN 

CORR 

FONT 

GAO 

GARF 

GENG 

HIRA 

HUMB 

INOU 

JANE 

KABA 

KALA 

KOO 

LAMT 

Sp 

Sp

A 

Co 

A 

Sp 

M(C) 

Sp

Sp 

Sp

A 

Sp 

Sp 

Sp

Sp 

Sp 

Sp 

Sp

A(C) 

Sp 

Sp 

OC 

Sp

Co 

Sp 

A 

A 

P 

H 

A 

A 

A 

A 

A 

A 

A 

H 

A 

A 

A 

A 

A 

A 

H 

A 

A 

H 

A 

H 

A 

1.52 1.5 A,L,O,V LR 

1.52 * * * 

1.82 1.68 A,I,O LR 

0.81 

0.75 

2.077 

1.667 

1.378 

1.219 

1.19 

* 

* * 

* * 

* 

1.367 

1.298 

1.289 

1.3410 

0.9 

1.31 

2.16 

1.5310 

1.53 

2.34 

2.55 

0.86 

* 

1.70 

* 

* 

Sm 

A,E,I,L,R 

A,E,I,LR 

A,E

A 

A,SES,H,Yd 

* 

1.6410 

1.50 

2.2 

2.5410 

0.93/0.4411 

1.09/2.0712 

* 

A,F,Oh,

F 

A,R 

A 

0.79 

A,L,R 

A,R 

* 

* 

* 

* 

R 

LR 

LR 

R 

LR 

R 

* 

S 

S 

R 

S 

M,S 

* 

1.62 1.92 A,E,Ir LR 

1.41 * * * 

1.55 1.64 A,E,B,Yc LR 

1.34 1.68 A,E,B,Yc LR 

1.65 * * * 

(continued on thefollowing page) 

5-20
Table 5-6. (continued) 

Case-control Exposure Crude Adj. Adjustment Adj. 

study Source2 Place3

 RR4 RR4 factor(s)5 technique6 

LAMW 

LEE 

1.00] 

0.8710 

LIU 

PERS 

SHIM 

SOBU 

SVEN 

TRIC 

WU 

WUWI 

BUTL (Coh) 

GARF (Coh) 

HIRA (Coh) 

HOLE (Coh) 

Sp

A 

Sp 

Co 

Co 

Sp 

Sp 

Sp 

Sp

OC 

A 

Sp 

Sp 

Sp

Co 

Sp 

Sp 

Sp 

Co 

* 

* 

A 

H 

A 

A 

A 

H 

A 

A 

H,W 

A 

A 

P 

P 

A 

A 

A 

A 

2.0113 

2.5114 

1.315 

0.75 

[1.03 

0.80 

0.74 

1.28 

1.28 

1.08 

1.06 

1.77 

1.1/1.816 

(1.26) 

2.08 

1.4117 

* 

* 

* 

* 

1.6015 

0.75 

A 

0.77 

1.2 

1.4710 

* 

A S 

C LR 

A,V M 

A S 

* * 

1.13 

1.57 

1.2/2.116 

(1.4) 

* 

A,E 

A,E 

A 

* 

1.2 A,L 

As 

0.79 

0.78 

2.45 

* 

0.7 A,E,L 

0.7 A,E,L 

2.02 A 

1.27/1.1018 

1.17 

1.37/1.0418 

A 

A,E,L,R,Oh 

1.38 1.61 Ah 

2.27 1.99 A,SES 

* 

* 

S 

* 

M 

LR 

LR 

LR 

S 

S 

S 

S 

S 

1

Values used for inference in this report are shown in boldface.

2

Source: A = anyone; (C) = childhood; Co = cohabitant(s); M = mother; OC = cohabitant(s) other

than spouse; Sp = spouse.

3

Place: A = anywhere; H = home/household; P = proximity of subjects; W = workplace.

4

OR for case-control studies; RR for cohort studies.

(continued on the following page) 

5-21 
Table 5-6. (continued) 

5

Adjustment factors: A= age of subject; Ah = age of husband; As = age started smoking; B = 

number of live births; C = cooking habits; E = education; F = fish consumption; H = hospital; I = 

income; Ir = interviewer; L = location; O = occupation of subject; Oh = occupation of husband; 

R = racial or ethnic group; SES = socioeconomic status; Sm = active smoking; V = vital status; 

Yc = years since exposure ceased; Yd = year of diagnosis.

6

LR = logistic regression; R = regression; M = matched analysis; S = stratified.

7

Bronchioalveolar carcinoma excluded. Spousal smoking OR = 1.77 with bronchioalveolar 

carcinoma excluded; no corresponding value reported for maternal smoking.

8

Population controls, all cell types (crude and adjusted ORs for adenocarcinoma alone are 1.52 

and 1.47, respectively).

9

Colon cancer controls, all cell types (crude and adjusted ORs for adenocarcinoma alone are 1.35 

and 1.44, respectively).

10Composite measure formed from categorical data at different exposure levels. 11Cases and controls matched on A, L, and N; first value is from subject; second value is from 

121-24 smoker-years/ 25 smoker-years. 13Adenocarcinoma only. 

proxy sources. 

14All cell types. 15First value is for smoking information provided by patient’s spouse; second value is for 

information provided by patient herself; third value (in brackets) utilizes available data from 

either source with subject classified as exposed if either source so indicates.

16Exposed at home but not at work or vice versa/exposed both at home and at work followed by 

weighted average of exposed strata.

17Crude OR from Table 11 of Surgeon General’s report (U.S. DHHS 1986); note that adjusted OR 

18Spouse smokes 1-20 cig. per day/spouse smokes 

from WU is not restricted to never-smokers and analysis includes only adenocarcinoma. 

20 cig. per day. The composite RR is 1.17. 

*Data not available. 

After exposure source and place are taken into account in the choice of RR values in 

Table 5-6, an adjusted RR is considered preferable to a crude RR unless the study review in 

Section A.4 indicates a problem with the adjustment procedure. Of the 31 studies, 20 provide 

both an adjusted and crude RR, where the “adjusted estimate” is based on the author’s use of a 

statistical procedure that takes potential confounding factors into account, usually by stratification 

or logistic regression. Based on the decision rule just described, our choice of RR is the smaller 

of the crude and adjusted values in 14 of the 20 studies providing both estimates. In several 

studies, RR values in addition to those shown in Table 5-6 might be considered (see Table 5-7). 

They were not found to be the best choices, however, for comparison between studies. 

5.2.2. Downward Adjustment to Relative Risk for Smoker Misclassification Bias 

There is ample evidence that some percentage of smokers, which differs for current and 

former smokers, misrepresent themselves as never-smokers (sometimes the wording of a 

5-22 
Table 5-7. Alternative estimates of lung cancer relative risks associated with active and passive 

smoking 

Study 

Active/ Controls Alternative Comparison 

passive ETS exposure exp. (%) estimate estimate1 

BUFF2 Passive 

FONT3 Passive 

Household members 

regularly smoking for 33+ 

years 

Spousal smoking, 

all types 

HUMB7

 Passive Spousal cigarette smoking7 57 

KOO8 Passive Home and/or workplace 

exposure over lifetime8 

PERS9 Active N.A.10 

SHIM1 2 Passive Total household ETS 

exposure

12 

BUTL Active 

(Coh) 

HIRA1 4 Active 

(Coh) 

HOLE1 5 Active 

(Coh) 

N.A.10 

N.A.10 

N.A.10 

71 Crude OR 0.95 

(0.38, 2.40) 

0.81 

63 

66 

64 

64 

3711 

77 

Crude OR 1.524 

(1.19, 1.96) 

Adj. OR 1.47 

Crude OR 1.356 

(1.02, 1.80) 

Adj. OR 1.44 

Crude OR 1.476 

(1.15, 1.87) 

No adj. OR 

Crude OR 1.8 

(0.6, 5.4) 

adj. OR 1.7 

Crude OR 1.36 

(0.83, 2.21) 

Adj. OR 1.86 

Crude OR 4.2 

Crude OR 1.36 

1.37 

1.29 

1.21 

1.28 

1.32 

* 

2.3 

2.2 

1.34 

1.64 

* 

1.08 

1411 Adj. RR 4.013 * 

4411 Adj. RR 3.79 2.67 

5611 Adj. RR 4.2 * 

1

Nearest equivalent from Tables 5-5 or 5-6.

2

Values in Tables 5-5 and 5-6 include household smoking for any duration. Lung cancer may

have a long latency period, however, so the extended exposure may be of interest.

3

As in Table 5-5 except for adenocarcinoma alone.

4

Population controls only.

5

Colon cancer controls only.

6

Control groups combined.

7

Values in Tables 5-5 and 5-6 include spousal smoking of cigars and pipes.

8

Value in Table 5-6 is for household cohabitant smoke exposure during adulthood.

(continued on the following page) 

5-23 
Table 5-7. (continued) 

9

Estimate is based on papers by Cederlöf et al. (1975) and Floderus et al. (1988) describing larger 

populations on which Pershagen study was based. 10Not applicable because alternative estimate is for active smoking. 11Percentage ever-smokers. 12Composite estimate from crude ORs for exposure from husband, parents, and father-in-law. 

Values in Tables 5-5 and 5-6 consider only spousal smoke exposure.

13Rough estimate based on data in Fraser et al. (1991). The prevalence of female ever-smoking is 

estimated from KALA and TRIC studies, which were conducted in similar conservative 

societies. 

14Compares active smokers with never-smokers unexposed to ETS, thus providing a reference 

group more truly unexposed to tobacco smoke.The value in Table 5-5 is the more conventional 

comparison of ever-smokers with never-smokers, regardless of passive smoking status.

15Estimate is from adjusted RR for both sexes combined with assumption that female RR is 75% 

of male RR. 

*Data not available. 

questionnaire may not be explicit enough to distinguish former smokers from never-smokers) (see 

Appendix B). It has been argued that the resultant misclassification of some smokers as 

nonsmokers produces an upward bias in the observed relative risk for lung cancer from ETS 

exposure (i.e., the observed RR is too large). The essence of the supporting argument is based on 

smoking concordance between husband and wife-­a smoker is more likely than a nonsmoker to

have been married to a smoker. Consequently, the smoker misclassified as a nonsmoker is more

likely to be in the ETS-exposed classification as well. Because smoking causes lung cancer, a

misclassified smoker has a greater chance of being a lung cancer case than a nonsmoker. The net

effect is that an observed association between ETS exposure and lung cancer among people who

claim to be never-smokers may be partially explainable by current or former active smoking by

some subjects.

The potential for bias due to misreported smoking habits appears to have been noted first 

by Lee (see discussion in Lehnert, 1984), and he emphasizes it in several articles (e.g., Lee, 1986, 

1987a,b). In Lee, 1987b, it is argued that smoker misclassification may explain the entire excess 

lung cancer risk observed in self-reported never-smokers in epidemiologic studies. Lee’s 

estimates of bias due to smoker misclassification appear to be overstated, however, for reasons 

discussed in Appendix B. 

The NRC report on ETS (1986) devotes considerable attention to the type of adjustment 

for smoker misclassification bias. It follows the construct of Wald and coworkers, as described in 

Wald et al., 1986; Wald was the author of this section in the 1986 NRC report. An illustrative 

diagram for the implicit true relative risk of lung cancer from exposure to ETS in women from 

5-24 
spousal smoking is shown in Figure 2 of Wald et al. (1986). A similar example is in Table 12-5 of 

the NRC report. 

Both Lee’s and Wald’s work adjust an overall relative risk estimate, pooled over several 

studies, downward, rather than address each individual study, with its own peculiarities, 

separately. Furthermore, statistical analysis over the studies as a whole is conducted first, and 

then an adjustment is made to the overall relative risk estimate. The recent work of Wells and 

Stewart (Appendix B) on this subject makes an adjustment to each individual study separately. 

Consequently, the pertinent adjustment factors that vary by study and type of society can be 

tailored to each study and then applied to the observed data before any statistical analysis. The 

latter procedure is applied in this report. 

The methodology to adjust for bias due to smoker misclassification and the details of its 

application to the ETS studies are provided in Appendix B. The results of the adjustment and 

estimate of bias are given in Table 5-8. In general, the biases are low in East Asia, or in any 

traditional society such as Greece, where female smoking prevalence is low and the female smoker 

risk is low. Some of the calculated biases are slightly less than unity when carried to three decimal 

places. This may result from the assumption in the calculations that there is no passive smoking 

effect on current smokers. 

5.3. STATISTICAL INFERENCE 

5.3.1. Introduction 

Table 5-9 lists the values of several statistical measures for the effect of spousal smoking 

by study (see boldface entries in Table 5-6 for details). Their meanings will be described before 

proceeding to interpretation of the data, even though the concepts discussed may be familiar to 

most readers. The p-values refer to a test for effect and a test for trend. In the former, the null 

hypothesis of no association (referred to as “no effect” of ETS exposure on lung cancer risk) is 

tested against the alternative of a positive association.The test for trend applies to a null 

hypothesis of no association between RR and exposure level against the alternative of a positive 

association. When data are available on more than two levels of intensity or duration of ETS 

exposure, typically in terms of the husband’s smoking habit (e.g., cig./day or years of smoking), 

then a test for trend is a useful supplement in testing for an effect, as well as indicating whether a 

dose-response relationship is likely. 

The entries under “power” in Table 5-9 are calculated for the study’s ability to detect a 

true relative risk of 1.5 and a decision rule to reject the null hypothesis of no effect when p < 0.05 

(see DuPont and Plummer [I990] for methods to calculate power). The power is the estimated 

probability that the null hypothesis would be rejected if the true relative risk is 1.5 (i.e., that the 
Table 5-8. Estimated correction for smoker misclassification 

Case 

control 

Uncorrected2 

(1) 

Never-smokers RR1 

Corrected3 

(2) 

Bias4 Ever-smokers 

(l)/(2) OR used5 

AKIB 

BROW 

BUFF 

CHAN 

CORR 

FONT 

GAO 

GARF 

GENG 

HIRA 

HUMB 

INOU 

JANE 

KABA 

KALA 

KATA 

KOO 

LAMT 

1.52 1.50 

(0.49, 4.79) (0.48, 4.72) 

0.81 0.68 

(0.39, 1.66) (0.32, 1.41) 

0.75 0.74 

(0.48, 1.19) (0.47, 1.17) 

2.07 1.89 

(0.94, 4.52) (0.85, 4.14) 

1.29 1.28 

(1.03, 1.62) (1.03, 1.60) 

1.19 

(0.87, 1.63) 

1.31 

(0.93, 1.85) 

1.27 

(0.91, 1.79) 

2.16 

(1.21, 3.84) 

1.53 

(1.10, 2.13) 

2.2 

(0.9, 5.5) 

1.52 

(1.10, 2.12) 

2.00 

(0.83, 4.97) 

2.55 

(0.90, 7.20) 

0.86 

(0.57, 1.29) 

0.79 

(0.30, 2.04) 

0.79 

(0.52, 1.17) 

0.73 

(0.27, 1.89) 

1.92 

(1.13, 3.23) 

* * 

1.55 

(0.98, 2.44) 

1.65 

(1.21, 2.21) 

1.54 

(0.98, 2.43) 

1.64 

(1.21, 2.21) 

1.5 

(1.0, 2.5) 

1.00 

1.01 

1.20 

1.01 

1.10 

1.01 

1.00 

1.03 

1.00 

(0.995) 

1.01 

1.10 

1.00 

(0.996) 

1.09 

1.08 

1.00 

* 

1.01 

1.01 

2.38 

4.30 

7.06 

3.48 

12.40 

8.0 

2.54 

6.0 

2.77 

3.20 

16.3 

1.66 

8.0 

5.90 

3.32 

* 

2.77 

3.77 

(continued on the following page) 

5-26
Table 5-8. (continued) 

Case 

control 

Uncorrected2 

(1) 

Never-smokers RR1 

Corrected3 

(2) 

Bias4 Ever-smokers 

(1)/(2) OR used5 

LAMW 

LEE 

LIU 

PERS 

SHIM 

SOBU 

SVEN 

TRIG 

1.03 1.01 

(0.48, 2.20) (0.47, 2.15) 

1.2 

(0.7, 2.1)6 

1.08 

(0.70, 1.68) 

1.26 

(0.65, 2.48) 

WU 

WUWI 

BUTL 

(Coh) 

GARF 

(Coh) 

HIRA 

(Coh) 

HOLE 

(Coh) 

1.41 

(0.63, 3.15) 

0.79 

(0.64, 0.98) 

2.027 

(0.48, 8.56)6 

1.177 

(0.85, 1.61)6 . 

1.38 

(1.03, 1.87) 

1.997 

(0.24, 16.7)6 

2.51 

(1.49, 4.23) 

0.77 

(0.35, 1.68) 

1.57 

(1.13, 2.15) 

2.08 

(1.31, 3.29) 

1.17 

(0.75, 1.87) 

1.07 

(0.7, 1.67) 

1.20 

(0.63, 2.36) 

1.32 

(0.59, 2.93) 

0.78 

(0.63, 0.96) 

2.01 

(0.61, 6.73) 

1.16 

(0.89, 1.52) 

1.37 

(1.02, 1.86) 

1.97 

(0.34, 11.67) 

1.00 

(0.996) 

1.02 

1.00 

1.03 

1.01 

1.00 

1.05 

1.00 

1.07 

1.01 

1.00 

1.01 

1.01 

1.01 

4.12 

4.61 

* 

4.2 

2.8 

2.81 

6.00 

2.81 

4.38 

2.24 

4.0 

3.58 

3.20 

4.2 

1

OR for case-control studies. RR for cohort studies. 2

Adjusted OR in Table 5-5 i’s used unless the confidence interval is unknown or the study review

(Appendix A) is critical of the method(s) used. 3

Corrected (2) (estimate and confidence interval) equals uncorrected (I) times ratio[(2)/(l)]. All 

corrected 95% confidence intervals have been converted to 90% confidenceintervals. 4

Values shown are the lower of (calculated ratio, 1). Calculated ratios less than 1 are shown in

parentheses. 5

The crude OR for ever-smokers in Table 5-5 is used in the calculations for the corrected value 

(Appendix B), when available. Ever-smoker ORs for GARF, JANE, PERS, and SHIM are

approximated from the data of other studies for suitable location and time period. The eversmoker ORs for BUTL(Coh) and (LEE) are based on data in Fraser et al. (1991) and Alderson et

al. 1985),. respectively. 6

95 % confidence interval. 7

Adjusted RR value in Table 5-5. 

5-27 
Table 5-9. Statistical measures by individual study and pooled by country, corrected for smoker 

misclassification1 

Location Study 

Relative 

weight2 

(%) Power3 

P-value 

Effect4

 Trend5 RR6 

Confidence 

interval 

90% 

Greece KALA 43 

Greece TRIC 57 

Greece ALL 5 

HK 

HK 

HK 

HK 

HK 

CHAN 

KOO 

LAMT 

LAMW 

ALL 

20 

20 

45 

15 

14 

Japan 

Japan 

AKIB 

HIRA 

(Coh) 

15 0.42 

35 0.75 

Japan INOU 3 

Japan SHIM 16 

Japan SOBU 30 

Japan ALL 19 

USA 

USA 

USA 

BROW 

BUFF 

BUTL 

(Coh) 

USA 

USA 

USA 

CORR 

FONT8 

GARF 

1 

3 

1 

3 

35 

15 

0.39 

0.45 

0.43 

0.43 

0.73 

0.39 

0.17 

0.377 

0.66 

0.15 

0.17 

0.18 

0.22 

0.93 

0.607 

0.02 0.04 1.92 (1.13, 3.23) 

<0.01 <0.0l 2.08 (1.31, 3.29) 

<0.01 2.01 (1.42, 2.84) 

>0.5 * 0.74 (0.47, 1.17) 

0.06 0.16 1.54 (0.98, 2.43) 

<0.01 <0.01 1.64 (1.21, 2.21) 

<0.01 * 2.51 (1.49, 4.23) 

<0.01 1.48 (1.21, 1.81) 

0.05 0.03 

0.04 <0.01 

0.07 <0.03 

0.38 * 

0.01 * 

<0.01 

1.50 (1.00, 2.50) 

1.37 (1.02, 1.86) 

2.55 (0.90, 7.20) 

1.07 (0.70, 1.67) 

1.57 (1.13, 2.15) 

1.41 (1.18, 1.69) 

0.28 * 

>0.5 * 

0.17 * 

0.10 0.01 

0.03 0.04 

0.12 <0.02 

1.50 (0.48, 4.72) 

0.68 (0.32, 1.41) 

2.01 (0.61, 6.73) 

1.89 (0.85, 4.14) 

1.28 (1.03, 1.60) 

1.27 (0.91, 1.79) 

(continued on the following page)

5-28
Table 5-9. (continued) 

Location Study 

Relative 

weight2 

(%) Power3 

P-value 

Effect4

 Trend5 R R6 

Confidence 

interval 

90% 

USA 

USA 

USA 

USA 

USA 

USA 

GARF 

(Coh) 

HUMB 

JANE 

KABA 

WU 

ALL 

25 

2 

10 

2 

3 

34 

Scotland HOLE 

(Coh) 

100 

Eng./Wales LEE 100 

Sweden PERS 68 

Sweden SVEN 32 

W. Europe ALL 5 

China GAO 28 

China GENG 8 

China LIU 4 

China WUWI 60 

China ALL 22 

0.92 0.18 

0.20 

0.447 

0.177 

0.21 

0.09 0.26 

0.20 

0.457 

0.24 

0.66 

0.32 

0.18 

0.897 

0.10 

>0.5 

>0.5 

0.29 

0.02 

0.50 

0.27 

0.31 

0.22 

0.18 

0.01 

>0.5 

>0.5 

>0.5 

* 1.16 (0.89, 1.52) 

* 2.00 (0.83, 4.97) 

* 0.79 (0.52, 1.17) 

* 0.73 (0.27, 1.89) 

* 1.32 (0.59, 2.93) 

1.19 (1.04, 1.35) 

* 1.97 (0.34, 11.67) 

* 1.01 (0.47, 2.15) 

0.12 1.17 (0.75, 1.87) 

* 1.20 (0.63, 2.36) 

1.17 (0.84, 1.62) 

0.29 1.19 (0.87, 1.62) 

<0.05 2.16 (1.21, 3.84) 

* 0.77 (0.35, 1.68) 

* 0.78 (0.63, 0.96) 

0.95 (0.81, 1.12) 

1

Misclassification is discussed in Section 5.2.2 and Appendix B.

2

A study’s relative weight (wt) is l/var (log(OR)), divided by the sum of those terms for all studies

included, times 100 (to express as a percentage).

3

A priori probability of significant (p < 0.05) test of effect when true relative risk is 1.5. 4

0ne-sided p-value for test of RR = 1 versus RR > 1.

5

P-value for upward trend. P-values from studies reporting only the significance level for trend were

halved to reflect a one-sided alternative, i.e., upward trend.

6

Adjusted for smoker misclassification. OR used for case-control studies; RR for cohort studies.

7

Calculated for matched study design.

8

For population control group only, all cases. 

*Data not available; ns = not significant. 

5-29 
correct decision would result; the power would be larger if the true relative risk exceeds 1.5). If 

the estimates of power for the U.S. studies in Table 5-9 are used for illustration, it can be seen 

that the estimated probability that a study wouldfail to detect a true relative risk of 1.5 (equal to 

1 - Power, the probability of a Type II error [discussed in the next paragraph] when the true 

relative risk is 1.5) is as follows: FONT, 0.07; GARF(Coh), 0.08; GARF, 0.40; JANE, 0.56; 

BUFF, 0.83; CORR, 0.78; WU, 0.79; HUMB, 0.80; KABA, 0.83; BUTL(Coh), 0.82; and BROW, 

0.85. Thus, 7 of the 11 U.S. studies have only about a 20% chance of detecting a true relative risk 

as low as 1.5 when taken alone. Sources of bias effectively alter the power in the same direction 

as the bias (e.g., a downward bias in RR decreases the power). Of the potential sources of bias 

discussed by study in Section A.4, the predominant direction of influence on the observed RR, 

when identifiable, appears to be in the direction of unity, thus affecting power adversely. The 

RRs already have been reduced to adjust for smoker misclassification, the only systematic source 

of upward bias that has been established. 

Studies of all sizes, large and small, are equally likely to make a false conclusion if ETS is 

not associated with lung cancer risk (Type I error). However, smaller studies are less likely to 

detect a real association when there is one (Type II error). This imbalance comes from using the 

significance level of the test statistic to determine whether to reject the null hypothesis. If the 

decision rule is to reject the hypothesis when the p-value is smaller than some prescribed value 

(e.g., 0.05), then the Type I error rate is 0.05, but the Type II error rate increases as study size 

decreases. When a study with low power fails to reject the null hypothesis of no effect, it is not 

very informative because that outcome may be nearly as likely when the null hypothesis is false as 

when it is true. When detection of a small relative risk is consequential, pooling informational 

content of suitably chosen studies empowers the application of statistical methods. 

The heading in Table 5-9 that remains to be addressed is “relative weight,” to be referred 

to simply as “weight.” When the estimates of relative risk from selected studies are combined, as 

for studies within the same country as shown in the table, the logarithms of the RRs are weighted 

inversely proportional to their variances (see Appendix D and footnote 2 of Table 5-9). These 

relative weights are expressed as percentages summing to 100 for each country in Table 5-9. 

Study weight and power are positively associated, which is explained by the significant role of 

study size to both. Consequently, studies weighted most heavily (because the standard errors of 

the RRs are low) also tend to be the ones with the highest power (most likely to detect an effect 

when present). 

5-30
5.3.2. Analysis of Data by Study and Country 

5.3.2.1 Tests for Association 

The p-values of the test statistics for the hypothesis of no effect (i.e., RR = 1) are shown 

in Table 5-9. Values of the test statistics (the standardized log odds ratio; see Appendix D) are 

plotted in Figure 5-1. Also shown in Figure 5-1 for reference are the points on the horizontal 

axis corresponding to p-values of 0.5, 0.2, 0.1, 0.05, 0.01, and 0.001. For example, the area under 

the curve to the right of the vertical line labeled p = 0.01 is 0.01 (1%), so it is apparent from 

Figure 5-1 that three studies had significance levels p < 0.01 (more specifically, 0.001 < p < 0.01). 

The size of the symbol (inverted triangle) used for a study is proportional in area to the relative 

weight of that individual study, but of current interest is the location and not the size of the 

symbol. If the null hypothesis is true, then the plotted values wouldarise from a standard normal 

distribution, shown in the figure (points to the left of zero indicate that the RR is less than 1, and 

points to the right of zero indicate that RR is greater than 1). If the points lie more toward the 

right side of the normal curve than would be likely to occur by chance alone, then the hypothesis 

of no effect is rejected in favor of a positive association between ETS exposure and lung cancer. 

If one constructs five intervals of equal probability (i.e., intervals of equal area under the standard 

normal curve), the expected number of observations in each interval is six (these five intervals are 

not shown on Figure 5-1). The observed numbers in these intervals, however, from left to right 

are 3, 3, 1, 7, and 16, an outcome that is significant at p < 0.005, by the chi-square goodness-offit test. At the points on the standard normal curve corresponding to p-values 0.5, 0.4, 0.3, 0.2, 

0.1, and 0.05, the probability that a number of outcomes as large as that actually observed would 

occur by chance is less than 0.005 at all points. Consequently, the hypothesis of no effect is 

rejected on statistical grounds, and that conclusion is not attributable to a few extreme outcomes 

that might be aberrant in some way. 

Figure 5-2 displays the U.S. studies alone (see Appendix D for calculation of the test 

statistics). Figure 5-3 corresponds to Figure 5-1 except that the test statistics for the hypothesis 

of no effect (i.e., RR = 1) for the significance levels shown apply to a single overall estimate of 

RR for each country, formed by statistically pooling the outcomes from the studies within each 

country. The areas of the symbols for countries are also in proportion to statistical weight as 

given in Table 5-9. It is implicitly assumed that studies within a country, and the subpopulations 

sampled, are sufficiently homogeneous to warrant combining their statistical results into a single 

estimate for the country (see Greenland [1987] for a discussion of applications of meta-analysis to 

epidemiology). The calculational method employed weights the observed RR from each study 

within a country inversely proportional to its estimated variance (see Appendix D). The relative 

5-31 
TESTS OF THE HYPOTHESIS THAT RR = 1 

BY STUDY 

Figure 5-1. Test statistics for hypothesis RR = 1, all studies. 

TESTS OF THE HYPOTHESIS THAT RR = 1 

USA 

Figure 5-2. Test statistics for hypothesis RR = 1, USA only.

5-32
TESTS OF THE HYPOTHESIS THAT RR = 1 

BY COUNTRY 

Figure 5-3. Test statistics for hypothesisRR = 1, by country. 

TESTS OF THE HYPOTHESIS THAT RR = 1 

BY COUNTRY (STUDIES IN TIERS 1 - 3 ONLY) 

Figure 5-4. Test statistics for hypothesisRR = 1, tiers 1-3 only.

5-33
study weights are shown in Table 5-9. Each symbol in Figures 5-1, 5-2, 5-3, and 5-4 has been 

scaled so that its area is proportional to the weight of the outcome represented, relative to all other 

outcomes shown in the same figure. 

Greece, Hong Kong, and Japan, which together comprise a total weight of 39%, areeach 

statistically significant at p < 0.01 against the null hypothesis of no increase in relative risk 

(RR = 1). When the United States is included, the total weight is 73%, andeach of the four 

countries is significant at p < 0.02. The four studies combined into the group called Western 

Europe are not large. Together they represent 5% of the total weight, and their combined odds 

ratio (1.17) is slightly above 1 but not statistically significant (p = 0.21). In contrast, China is 

weighted quite high (22%), the p-value is large (0.66), and the odds ratio is less than 1 (0.95), 

strongly indicating no evidence of an increase in RR due to ETS. This is largely because China is 

very heavily influenced by WUWI (relative weight of 60% of China), which is a very large casecontrol study. However, this apparent inconsistency in WUWI may be due to the presence of 

indoor smoke from cooking and heating, which may mask any effect from passive smoking. A 

similar but more extreme situation is found in LIU, conducted in a locale where indoor heating 

with smoky coal (an established risk factor for lung cancer) and inadequate venting are common. 

Both WUWI and LIU were conducted primarily to assess the hazardous potential of these 

pollutants. The indoor environments of the populations sampled in WUWI and LIU make 

detection of any carcinogenic hazard from ETS unlikely, and thus render these studies to be of 

little value for that purpose (see discussions of WUWI and LIU in Section A.4). Without WUWI or 

LIU, the combined results of the two remaining studies in China, GAO and GENG, are 

significant at p = 0.03. 

Such qualitative considerations about the likely utility of a study to detect an ETS effect, 

if one exists, are taken into account in Section 5.5. In that section, studies are ranked into one of 

four tiers based on their likely utility. Studies such as WUWI and LIU would be placed into Tier 

4, the grouping with the least likelihood of providing useful information on the effects of ETS. 

Figure 5-4 is similar to Figure 5-3 displaying the distribution of test statistics for the pooled 

estimates by country, but includes only the studies in Tiers 1, 2, and 3; it is shown here for 

comparison purposes (see Section 5.5 for a detailed discussion of the analysis based on tiers). 

5.3.2.2. Confidence Intervals 

Confidence intervals for relative risk are displayed by study and by country in Table 5-9 

(see Appendix D for method of calculation). The 90% confidence intervals by country are 

illustrated in Figure 5-5. (Note: 90% confidence intervals are used for correspondence to a right5-34 
9O% CONFIDENCE INTERVALS FOR RR 

BY COUNTRY 

Figure 5-5. 90% confidence intervals, by country. 

90% CONFIDENCE INTERVALS FOR RR 

BY COUNTRY (STUDIES IN TIERS 1 -3 ONLY) 

Figure 5-6. 90% confidence intervals, by country, tiers 1-3 only.

5-35
tailed test of the hypothesis of no effect at a 5% level of significance.) The area of the symbol 

(solid circle) locating the point estimate of relative risk within the confidence interval is 

proportional to study weight. Symbol size is used as a device to draw attention to the shorter 

confidence intervals, which tend to be based on more data than the longer ones. The confidence 

intervals for countries jointly labeled as Western Europe are in Table 5-9, except for Sweden 

which contains two studies, PERS and SVEN. For those two studies combined, the odds ratio 

(OR) is 1.19 (90% C.I. = 0.81, 1.74). The confidence intervals for the pooled relative risk 

estimates by country for studies in Tiers 1, 2, and 3 only (see previous paragraph and Section 5.5) 

are displayed in Figure 5-6. 

In descending order, the relative risks in Figure 5-6 are for Greece, Hong Kong, Japan, 

the United States, and Western Europe. (China is being excluded from this summary because it 

contains only one study in Tiers 1-3 [GAO],which is unlikely to be representative of such a vast 

country. The relative risk estimate for that study, 1.19, is similar to the overall relative risks for 

the United States and Western Europe.) The estimated relative risks from exposure to spousal 

smoking differ between countries, with Greece, Hong Kong, and Japan at the high end of the 

scale and the United States and Western Europe at the low end. These differences suggest that 

combining studies from different countries should be done with caution. The relative risks 

pertain only to ETS exposure from spousal smoking, which may be a higher proportion of total 

ETS exposure in some countries than in others. This also emphasizes the importance of taking 

into account exposure and background (nonspousal) ETS, which is considered in the estimation of 

population risk for the United States in Chapter 6. 

5.3.3. Analysis of Data by Exposure Level 

5.3.3.1. Introduction 

In Section 5.3.2, analyses are conducted by individual study and by studies pooled within 

countries, using the dichotomous data on spousal smoking (i.e., any level of spousal smoking 

versus no spousal smoking) as a surrogate for ETS exposure.This section examines the response 

data from all of the studies that provide data analysis by exposure-level categories. Exposure 

level, for these studies, refers to the amount of spousal smoking. In different studies, exposure is 

measured by intensity (e.g., cig./day smoked by the husband), duration (e.g., number of years 

married to a smoker), or a combination of both (e.g., number of pack-years--packs per day 

x years of smoking by the husband). The data are analyzed by calculating RR estimates for the 

highest exposure groups only (Section 5.3.3.2) and then by testing for an upward trend in RR 

across exposure groups within studies as ETS exposure increases (Section 5.3.3.3). 

5-36
An evaluation of the highest exposure group or a test for exposure-related trend may be 

able to detect an association that would be masked in a test for effect using only dichotomous 

data. This masking is especially likely to occur when dealing with a weak association or a crude 

surrogate measure for exposure that is widespread (i.e., greater potential for exposure 

misclassification), both of which are difficulties in studies of ETS and lung cancer. 

As discussed in Chapter 3, ETS is a dilute mixture, and, consequently, any association 

observed between environmental levels of ETS exposure and lung cancer is likely to be weak (i.e., 

have a low RR). Furthermore, questionnaire-based assessment of exposure to ETS is a crude 

indicator of actual lifetime exposure, and spousal smoking is an incomplete surrogate for exposure 

because it does not consider ETS from other sources, such as the workplace. Therefore, exposure 

misclassification in both directions is inevitable. For example, there will be women whose 

husbands do not smoke but who are exposed to substantial levels of ETS from other sources, and 

there will be women whose husbands smoke but who are not actually exposed to appreciable levels 

of ETS. This latter scenario is most likely if the level of spousal smoking is low. Comparing the 

highest exposure group with the “unexposed” group will help reduce the effect of this latter type 

of exposure misclassification bias. 

In addition, the detection of an exposure-response relationship (trend) across exposure 

groups increases support for a causal association by diminishing the likelihood that the results can 

be explained by confounding, because any potential confounder would have to be associated with 

both lung cancer and ETS exposure in a dose-related manner. However, the potential for 

exposure misclassification is compounded when the exposed group is further divided into 

level-of-exposure categories and the sample sizes become small. This is especially problematic in 

small studies. These inherent difficulties with the ETS database tend to diminish the possibility of 

detecting exposure-response relationships. Therefore, the inability to demonstrate an exposureresponse trend is not considered evidence against causality; rather, if a statistically significant 

trend can be detected despite these potential obstacles, it provides evidential support for a causal 

association. 

5.3.3.2. Analysis of High-Exposure Data 

In this section, analyses will be conducted for the highest exposure groups by study and by 

studies pooled within countries. As described in Section 5.3.3.1, analyzing only the data from the 

highest exposure group of each study increases the sensitivity for detecting an association and 

reduces the effects of exposure misclassification. Fractionating the data, however, does decrease 

the power to observe statistical significance. 

5-37 
The results of statistical inference using only data from the highest exposure categories are 

displayed in Table 5-10. As indicated in the table, exposure-level data are available in 17 studies. 

The definitions of highest exposure category, shown next to the study name in the table, vary 

widely between studies. Crude RR estimates adjusted for smoker misclassification (see Section 5.2 

and Appendix B) are used in this section rather than the estimates adjusted for modifying factors 

within the studies, because the latter are available by exposure level for only a limited number of 

studies. 

Several observations are apparent from Table 5-10. First, every one of the 17 individual 

studies shows increased risk at the highest exposure level, even after adjusting for smoker 

misclassification. Second, 9 of the 16 comparisons for which sufficient data are available are 

statistically significant (p 0.05), despite most having very low statistical power. Third, the RR 

estimates pooled within countries are each statistically significant with p 0.02. Although the 

RR estimates within a country are pooled across different definitions of highest exposure, which 

somewhat limits their interpretation and practical value, it is apparent that these RRs are 

considerably higher than the values observed for the dichotomous data (Table 5-9). The RR 

estimates pooled by country vary from a low of 1.38 (p = 0.005) for the United States to a high of 

3.11 (p = 0.02) for Western Europe, which contains only one study. Finally, the overall pooled 

estimate of 1.81 for the highest exposure groups from all 17 studies is highly statistically 

significant (p < 0.000001). 

These results are consistent with the statistical evidence presented in Section 5.3.2 for an 

association between ETS exposure and lung cancer.In fact, increased risks are found for the 

highest exposure groups without exception. Furthermore, the RR estimates pooled within 

countries are all statistically significant and range from 1.38 to 3.11, even after adjustment for 

smoker misclassification. The consistency of these highest exposure results cannot be accounted 

for by chance, and the stronger associations detected for the highest exposure groups across all 

countries further reduce the likelihood that bias or confounding could explain the observed 

relationship between ETS and lung cancer. 

In addition, with the exception of Western Europe, which contains only one low-power 

study in this analysis, the pooled RR estimates from other,more “traditional” countries are all 

appreciably higher than that from the United States. It is likely that these differences are at least 

partially a result of higher background (nonspousal) ETS exposures to the allegedly “unexposed” 

group in the United States. Again, this highlights the importance of accounting for ETS exposures 

from sources other than spousal smoking. An adjustment for background ETS exposures is made 

in Chapter 6, for the estimation of population risk for the United States. 

5-38 
1 Table 5-10. Statistical measures for highest exposure categories only

RR 5,6 Location Study 

Highest Relative 

exposure weight2 

level (%) 

P-value 

Power 3 Effect4 

Confidence 

interval6 

90% 

Greece KALA ( > 41 cig./day) 35 

Greece TRIC ( > 21 cig./day) 65 

Greece All High 8 

Hong Kong KOO ( > 21 cig./day) 36 

Hong Kong LAMT ( > 21 cig./day) 64 

Hong Kong All High 8 

Japan 

Japan 

( > 30 cig./day) 6 0.10 0.13 2.1 (0.7, 2.5) 

( > 20 cig./day) 89 0.13 0.00015 1.91 (1.42, 2.56) 

Japan 

Japan 

AKIB 

HIRA 

(Coh) 

INOU 

All 

( > 20 cig./day) 

High 

4 

22 

United States 

United States 

United States 

United States 

CORR 

FONT 

GARF 

GARF 

(Coh) 

( > 41 pack-yrs) 

( > 80 pack-yrs) 

( > 20 cig./day) 

( > 20 cig./day) 

8 

14 

15 

45 

United States HUMB ( > 21 cig./day) 2 

United States JANE ( > 50 pack-yrs) 8 

United States WU ( > 31 years) 8 8 

United States All High 36 

W. Europe 

W. Europe 

PERS 

All 

( > 16 cig./day) 

High 

100 

2 

China GAO ( > 40 years) 35 

China GENG ( > 20 cig./day) 65 

China All High 24 

All All High 

0.06 

0.11 

0.11 

0.16 

* 

0.06 

* 

0.21 

* 

* 

* 

* 

* 

0.33 

* 

0.16 1.57 (0.74, 3.32) 

0.003 2.55 (1.46, 4.42) 

0.002 2.15 (1.38, 3.35) 

0.36 1.18 (0.58, 2.55) 

0.02 2.05 (1.18, 3.57) 

0.03 1.68 (1.08, 2.62) 

0.05 3.09 (1.0, 11.8) 

<0.00004 1.96 (1.49, 2.60) 

0.005 3.20 (1.53, 6.74) 

0.21 1.327 (0.75, 2.29) 

0.01 2.05 (1.19, 3.49) 

0.33 1.09 (0.81, 1.49) 

0.46 

0.50 

* 

0.005 

0.02 

0.02 

0.02 

<0.00001 

<0.000001 

<0.000001 

1.09 

1.01 

1.87 

1.38 

(0.27, 4.73) 

(0.50, 2.04) 

* 

(1.13, 1.70) 

3.11 (1.18, 7.71) 

3.11 (1.18, 7.71) 

1.7 (1.09, 2.65) 

2.76 (2.02, 3.84) 

2.32 (1.78, 3.03) 

1.81 (1.60, 2.05) 

(continued on the following page) 

5-39
Table 5-10. (continued) 

1

Similar to Table 5-9 except entries apply to highest exposure category only in each study. Only 

studies with data available for categorized measures of exposure are included. Relative risks and 

confidence bounds are corrected for smoker misclassification. 

2

A study’s relative weight (wt) is 1/var (log(OR)), divided by the sum of those terms for all 

studies included, times 100 (to express as a percentage).

3 A priori probability of significant (p < 0.05) test of effect when true relative risk is 1.5. 4

One-sided p-value for test of RR = 1 versus RR > 1.

5

Adjusted for smoker misclassification. OR used for case-control studies; RR for cohort studies.

6

Values may differ from those of Table 5-11, where confidence intervals are shown as they 

appear in the source. In Table 5-11, the RR and confidence interval are not corrected for smoker 

misclassification, as in this table, and most of the confidence intervals are 95% instead of 90%.

7

Value shown is for all cell types with the two control groups combined. For adenocarcinoma 

cases only, the RR is 1.68 with C.I. = 0.81, 3.46.

8

Relative weight assumed to be the same as for CORR, based on the outcome in Table 5-9. 

*Data not available. 

5.3.3.3. Tests for Trend 

In this section, exposure-response data from the studies providing data by exposure level 

are tested for upward trend. An exposure-response relationship provides strong support for a 

causal association (see Section 5.3.3.1). 

Table 5-11 presents the female exposure-response data and trend test results from the 

studies of ETS and lung cancer discussed in this report. The p-values reported in the table are for 

a test of no trend against the one-sided alternative of an upward trend (i.e., increasing RR with 

increasing exposure). (Note: The results for tests of trend are taken from the study reports. 

Unless the report specified that a one-sided alternative was used, the reported p-value was halved 

to reflect the outcome for the one-sided alternative of RR increasing with exposure. Where the 

data are available, the p-values reported by the individual study’s authors have been verified here 

by application of the Mantel, Haenszel test [Mantel, 1963].) 

Wu-Williams and Samet (1990) previously reviewed the exposure-response relationships 

from the epidemiologic studies on ETS then available. They determined that 12 of 15 studies 

were statistically significant for the trend test for at least one exposure measure. The probability 

of this proportion of statistically significant results occurring by chance in this number of studies 

is virtually zero (p < 10-13). Intensity of spousal smoking was the most consistent index of ETS 

exposure for the demonstration of an exposure-response relationship. 

Our assessment of the exposure-response data is similar and provides essentially the same 

results for a slightly different set of studies. Table 5-12 summarizes the p-values of the trend 

5-40 
Table 5-11. Exposure response trends for females 

Study Case Cont. Exposure1 RR2 C.I. 2,3 P-trend4 

AKIB 

(cig./day) 

AKIB 

(years) 

CORR 

(pack-yrs.) 

FONT6 

(years) 

FONT7 

(years) 

FONT6 

(pack-yrs.) 

FONT7 

(pack-yrs.) 

GAO 

(tot. yrs.)8 

GARF 

(cig./day) 

GENG 

(cig./day) 

21 

22 

12 

1.0 

1-19 

20-29 

> 30 

1.3 

1.5 

2.1 

21 

20 

29 

22 

82 

30 

81 

59 

0 1.0 

1-9 2.1 

20-39 1.5 

> 40 1.3 

72 

38 

23 

0 1.00 

1-40 1.18 

> 41 3.52 

* 0 1.00 * 1-15 1.19 * 16-30 1.14 * > 30 1.25 

* * 0 1.00 * * 1-15 1.33 * * 16-30 1.40 * * > 30 1.43 

0<15 

15-39 

40-79 

> 80 

1.00 

0.96 

1.13 

1.25 

1.33 

0<15 

15-39 

40-79 

> 80 

1.00 

1.03 

1.26 

1.49 

1.70 

99 

93 

107 

76 

57 0-19 1.0 

63 20-29 1.1 

78 30-39 1.3 

48 > 40 1.7 

44 

29 

17 

26 

* 

* 

* 

* 

157 

90 

56 

44 

0 

1-9 

10-19 

> 20 

0 

1-9 

10-19 

> 20 

1.00 

1.15 

1.08 

2.11 

1.00 

1.40 

1.97 

2.76 

(0.8, 2.8)5 (0.7, 2.3)5 

(0.7, 2.5)5 

(1.0, 4.3)5 

(0.8, 2.7)5 

(0.7, 2.5)5 

(0.44, 3.20)

(1.45, 8.59) 

(0.88, 1.61)

(0.82, 1.59) 

(0.91, 1.72) 

(0.93, 1.89)

(0.96, 2.05)

(0.99, 2.09) 

(0.72, 1.29)

(0.81, 1.59)

(0.86, 1.81) 

(0.68, 2.58) 

(0.73, 1.46)

(0.85, 1.87) 

(0.98, 2.27)

(0.82, 3.49) 

(0.7, 1.8) 

(1.1, 1.8) 

(1.4, 2.7)

(1.9, 4.1) 

0.03 

0.24 

0.01 

0.07 

0.02 

0.04 

0.01 

0.29 

<0.02 

<0.059 

(continued on the following page)

5-41
Table 5-11. (continued) 

Study Case Cont. Exposure1 RR2 C.I.2,3 P-trend4 

GENG 

(years) 

HUMB 

(cig./day) 

INOU 

(cig./day) 

JANE10 

(pack-yrs.) 

KALA 

(cig./day) 

KALA 

(years) 

KOO 

(cig./day) 

LAMT6 

(cig./day) 

LAMT7 

(cig./day) 

* * 0 1.00

* * <20 1.49

* * 20-39 2.23

* * > 40 3.32 

* * 0 1.0

* * 1-20 1.8

* * > 21 1.2 

* * 0-4 1.00

* * 5-19 1.58 * * > 20 3.09 

* * 0 1.00

* * 1-24 0.71

* * 25-49 0.98

* * > 50 1.10 

26 46 0 1.00 

34 39 1-20 1.54 

22 22 21-40 1.77 

8 9 41+ 1.57 

26 46 

15 21 

15 20 

17 15 

17 16 

1.00 

1.26 

1.33 

2.01 

1.88 

32 

17 

25 

12 

67 

15 

35 

19 

0 

<20 

20-29 

30-39 

> 40 

0 

1-10 

11-20 

> 21 

1.00 

2.33 

1.74 

1.19 

84 183 

22 22 

56 66 

20 21 

1.00 

2.18 

1.85 

2.07 

53 92 

17 12 

37 28 

15 9 

0 

1-10 

11-20 

> 21 

0 

1-10 

11-20 

> 21 

1.00 

2.46 

2.29 

2.89 

(1.15, 1.94) 

(1.54, 3.22) 

(2.11, 5.22) 

(0.6, 5.6)5 

(0.3, 5.2)5 

(0.4, 5.7)5 

(1.0, 11.8)5 

(0.37, 1.35) 

(0.47, 2.05) 

(0.47, 2.56) 

(0.88, 2.70) 

(0.93, 3.35) 

(0.64, 3.85) 

(0.56, 2.87) 

(0.58, 3.03) 

(0.86, 4.67) 

(0.82, 4.33) 

(0.9, 5.9) 

(0.8, 3.8) 

(0.5, 3.0) 

(1.14, 4.15) 

(1.19, 2.87) 

(1.07, 4.03) 

(1.09, 5.54) 

(1.26, 4.16) 

(1.18, 7.07) 

<0.059 

ns 

<0.03 

* 

0.08 

0.04 

0.16 

0.01 

0.01 

(continued on the following page) 

5-42
Table 5-11. (continued) 

Study Case Cont. Exposure1 R R2 C.I.2,3 P-trend4 

PERS11 

(cig./day) 

TRIC12 

(cig./day) 

WU13 

(years 

exposed as 

adult) 

GARF(Coh)

14 

(cig./day) 

HIRA(Coh)

15 

(cig./day) 

34 * 0 1.0 0.12 

26 * 1-15 1.0 (0.6, 1.8) 

7 * > 16 3.2 (1.0, 9.5) 

24 109 0 1.00 

24 56 1-20 1.95 

14 25 > 21 2.55 

* 

* 

* 

65 

39 

49 

37 21,895 

99 44,184 

64 25,461 

* 

* 

* 

* 

* 

* 

0 

1-30 

> 31 

0 

1-19 

> 20 

0 

1-1916 

> 20 

1.0 

1.2 

2.0 

1.00 

1.27 

1.10 

* 

(0.85, 1.89) 

(0.77, 1.61) 

1.00 0.01 

1.41 (1.03, 1.94) 

1.93 (1.35, 2.74) 

0.01 

(1.13, 3.36) 

(1.31, 4.93) 

* 

* 

* 

1

Smoking by spouse unless otherwise specified.

2

See footnote 6 in Table 5-10. 3

Confidence intervals are 95% unless noted otherwise. 4

P-value for upward trend. P-values from studies reporting only the significance level for trend

were halved to reflect a one-sided alternative (i.e., upward trend). Values below 0.01 are shown

as 0.01. 5

90% confidence interval.

6

All histologies.

7

Adenocarcinomas only. 8

Years lived with a smoking husband.

9

Neither crude data nor a test for trend is included in reference articles. The relative risk at each 

exposure category is significant alone, however, at p < 0.05. 10Data are from subject responses in Table 3 of the source. 11Low exposure level is for husband smoking up to 15 cigarettes per day or one pack (50 g) of

pipe tobacco per week, or smoking any amount during less than 30 years of marriage. High

exposure level is for husband smoking more than 15 cigarettes per day or one pack of pipe

tobacco per week during 30 years of marriageor more.

12Data from Trichopoulos et al. (1983),with RRs corrected (personal communication from

Trichopoulos, 1984). 13Years of exposure to spousal smoke plus years of exposure to workplace smoke; adenocarcinomas

only. 14Value under “RR” is mortality ratio of observed to expected lung cancer deaths. Value under

“Case” is number of observed lung cancer deaths. 15Standardized for age of subject (Hirayama, 1984). Values under “case” are numbers of lung

cancer deaths; values under “cont.” are total population. 161ncludes former smokers of any exposure level. 

*Data not available; ns = not significant. 

5-43
1

2

3

4

5

6

1 Table 5-12. Reported p-values of trend tests for ETS exposure by study

Intensity

(cig./day) 

Trend test results 

Duration 

(total years) 

Cumulative

(pack-years)2 

AKIB 0.03 0.24 * 

CORR 

FONT 

GAO 

GARF 

GENG 

HUMB 

INOU 

JANE 

KALA 

KOO 

LAMT 

PERS 

TRIC 

WU 

* 

* 

* 

* 

<0.02 

<0.056 

ns 

<0.03 

* 6 

0.08 

0.16 

<0.01 

<0.014 

0.12 

<0.01 

* 

* 

0.073 

<0.024 

0.29 

* 

<0.055 

* 

* 

* 

0.04 

* 

* 

* 

* 

* 6 

0.01 

0.04 

<0.01 

* 

* 

* 

* 

* 

* 

* 

* 

* 

* 

* 

* 

GARF(Coh) * 6 * * 

HIRA(Coh) <0.01 * * 

Detailed data presented in Table 5-11.

A “pack-year” is equivalent to one pack/day for 1 year.

All cell types.

Adenocarcinoma only.

See footnote 9 in Table 5-11.

Trend results presented without p-values or raw data--see Table 5-11.

*Data not available; ns = not significant.

5-44
tests for the various ETS exposure measures from the studies presented in Table 5-11. The 

exposure measure most commonly used was intensity of spousal smoking. Eight of the twelve 

studies that reported exposure-response data basedon cigarettes per day showed statistical 

significance at the p < 0.05 level for the trend test. Again, the probability of this many 

statistically significant results occurring by chance in this number of studies is negligible 

(p < 10-7). The trend test results for the other exposure measures were consistent, in general, with 

those based on cigarettes per day (three of six studies using total years of exposure were 

significant, as were two of two studies using pack-years). 

Overall, 10 of the 14 studies with sufficient exposure-response data show statistically 

significant trends for one or more exposure measures. No possible confounder has been 

hypothesized that could explain the increasing incidence of lung cancer with increasing exposure 

to ETS in so many independent studies from different countries. 

By country, the number of studies with significant results for upward trend is as follows: 

China, 1 of 2; Greece, 2 of 2; Hong Kong, 1 of 2; Japan, 3 of 3; Sweden, 0 of 1; and United 

States, 3 of 4. Of particular interest, two of the U.S. studies, GARF and CORR, are statistically 

significant for a test of trend, providing evidence for an association between ETS exposure and 

lung cancer even though neither was significant in a test for effect. In both cases, this occurs 

because the data supporting an increase in RR are largely at the highest exposure level. It appears 

that relatively high exposure levels are necessary to observe an effect in the United States, as 

would be expected if spousal smoking is a weaker surrogate for total ETS exposure in this country. 

The U.S. study by Fontham et al. (1991), a well-conducted study and the largest casecontrol study of ETS and lung cancer to date, with the greatest power of all the U.S. studies to 

detect an effect, was statistically significant with a p-value of 0.04 for the trend test with packyears as the exposure measure. When the analysis was restricted to adenocarcinomas (the majority 

of the cases), tests for trend were statistically significant by both years (p = 0.02) and pack-years 

(p = 0.01). 

5.3.4. Conclusions 

Two types of tests have been conducted: (I) a test for effect, wherein subjects must be 

classified as exposed or unexposed to ETS, generally according to whether the husband is a 

smoker or not, and (2) a trend test, for which exposed subjects are further categorized by some 

level of exposure, such as the number of cigarettes smoked per day by the husband, duration of 

smoking, or total number of packs smoked. Results are summarized in Table 5-13, with countries 

in the same order as in Table 5-9. Studies are noted in boldface if the test of effect or the trend 

5-45 
Table 5-13. P-values of tests for effect and for trend by individual study’ 

Country Study Power Test P-value2 

Greece KALA 0.39 

Greece TRIC 0.45 

Hong Kong 

Hong Kong 

CHAN 

KOO 

0.43 

0.43 

Hong Kong LAMT 0.73 

Hong Kong LAMW 0.39 

Japan AKIB 0.42 

Japan HIRA(Coh) 

Japan INOU 

Japan 

Japan 

SHIM 

SOBU 

0.75 

0.17 

0.37 

0.66 

United States BROW 0.15 

United States BUFF 0.17 

United States BUTL(Coh) 0.18 

United States CORR 0.22 

United States FONT 0.93 

United States GARF 0.60 

United States GARF(Coh) 0.92 

Effect 0.02 

Trend 0.04 

Effect <0.01 

Trend <0.01 

Effect >0.50 

Effect 0.06 

Trend 0.16 

Effect <0.01 

Trend <0.01 

Effect <0.01 

Effect 

Trend 

Effect 

Trend 

Effect 

Trend 

Effect 

Effect 

0.05 

0.03 

0.04 

<0.01 

0.07(0.05)3 

0.03 

0.38 

0.01 

Effect 

Effect 

Effect 

Effect 

Trend 

Effect 

Trend 

Effect 

Trend 

Effect 

0.28 

>0.50 

0.17 

0.10(0.005)3 

0.01 

0.034 

0.04 4 

0.12(0.01)3 

<0.02 

0.18 

(continued on the following page)

5-46
Table 5-13. (continued) 

Country Study Power Test P-value2 

United States 

United States 

United States 

United States 

W. Europe 

Scotland 

England 

Sweden 

Sweden 

China 

China 

China 

China 

HUMB 

JANE 

KABA 

WU 

Hole(Coh) 

LEE 

PERS 

SVEN 0.24 

GAO 

GENG 0.32 

LIU 0.18 

WUWI 0.89 

0.20 

0.44 

0.17 

0.21 

0.09 

0.20 

0.45 

0.66 

Effect 

Trend 

Effect 

Effect 

Effect 

0.10 

ns 

>0.50 

>0.50 

0.29 

Effect 0.26 

Effect 0.50 

Effect 0.27(0.02)3 

Trend 0.12 

Effect 0.31 

Effect 

Trend 

Effect 

Trend 

Effect 

Effect 

0.18(0.02)3 

0.29 

0.01 

<0.05 

>0.50 

>0.50 

1

Test for effect--H,: no increase in lung cancer incidence in never-smokers exposed to spousal 

ETS; H,: an increase. Test for trend--He: no increase in lung cancer incidence as exposure to 

spousal ETS increases; HA: an increase. P-values less than 0.05 are in boldface. 

2

Smallest p-value is used when there is more than one test for trend; ns = not significant.

3

P-value in parentheses applies to test for effect at highest exposure only (see text).

4

For all cell types. P-values for adenocarcinoma alone were smaller. 

test is significant at 0.05 (one-tailed) or if, as in PERS and GAO, only the odds ratio at the 

highest exposure is significant. In 8 of the 11 studies in Greece, Hong Kong, or Japan, at least 

one of the tests is significant at 0.05. For the United States and Western Europe, 4 of the 15 

studies are significant at 0.05 for at least one test. For the studies within the first group of 

countries (Greece, Hong Kong, and Japan), the median power is 0.43, and only 1 of the 10 studies 

(10%) has power less than 0.25 (INOU). In contrast, the median power for the United States and 

Western Europe together is 0.21, and 10 of the 15 studies (67%) have power less than 0.25. In a 

5-47 
small study, significance is meaningful, but nonsignificance is not very informative because there 

is little chance of detecting an effect when there is one.Consequently, there are several studies in 

the United States-Western Europe group that provide very little information. Two of the four 

studies in China are significant at the 0.05 level for at least one test. The two nonsignificant 

studies in China (LIU and WUWI) are not very informative on ETS for reasons previously 

described (see Section 5.3.2.1). 

For the U.S. and Western Europe studies, 3 of the 5 with power greater than 0.25 are 

shown in boldface (FONT, GARF, and PERS), indicating at least suggestive evidence of an 

association between ETS and lung cancer, compared with only 1 of 10 with power under 0.25 

(CORR). All three of the higher power studies are significant for effect (PERS and GARF are 

significant at the highest exposure only) and two (FONT and GARF) are also significant for 

trend. CORR is significant for trend and for effect at the highest exposure level. Overall, the 

evidence of an association in the United States and Western Europe is strengthened by the tests at 

the highest exposure levels and by the tests for trend. 

To summarize, the results of the several different analyses in this section provide 

substantial evidence that exposure to ETS from spousal smoking is associated with increased lung 

cancer mortality. The evidence is strongest in Greece, Hong Kong, Japan, and the United States. 

The evidence for Western Europe appears similar to that in the United States, but there are far 

fewer studies. (The usefulness of statistical information from studies in China is quite limited, so 

no conclusions are drawn from the studies there.) 

The evidence from the individual studies, without pooling within each country, is also 

conclusive of an association. Adjustment, on an individual study basis, for potential bias due to 

smoker misclassification results in slightly lower relative risk estimates but does not affect the 

overall conclusions. The results based on either the test for effect or the test for trend cannot be 

attributed to chance alone. Tests for effect, tests at the highest exposure levels, and tests for trend 

jointly support the conclusion of an association between ETS and lung cancer in never-smokers. 

5.4. STUDY RESULTS ON FACTORS THAT MAY AFFECT LUNG CANCER RISK 

5.4.1. Introduction 

The possibility of chance accounting for the observed associations between ETS and lung 

cancer has been virtually ruled out by the statistical methods previously applied. Potential sources 

of bias and confounding must still be considered to determine whether they can explain the 

observed increases. While the exposure-response relationships reviewed in Section 5.3.3.3 

generally reduce the likelihood of bias and confounding accounting for the observed associations, 

this section focuses on specific factors that may bias or modify the lung cancer results. 

5-48 
Validity is the most relevant concern for hazard identification. Generalizability of results 

to the national population (depending on “representativeness” of the sample population, treated in 

the text) is important for the characterization of population risk, but no more so than validity. As 

stated by Breslow and Day (1980), “In an analysis, the basic questions to consider are the degree of 

association between risk for disease and the factors under study, the extent to which the observed 

associations may result from bias, confounding and/or chance, and the extent to which they may 

be described as causal.” 

Whereas Section 5.3 examined the epidemiologic data by individual study and by pooling 

results by country, this section considers potential sources of bias and confounding and their 

implications for interpretation of study results. As indicated in the brief review of the meanings 

of bias and confounding at the end of this section, confounding arises from the characteristics of 

the sample population, whereas bias is the result of individual study features involving design, 

data collection, or data analysis. Section 5.4.2 briefly reviews the evidence on non-ETS risk 

factors and modifiers of lung cancer incidence that appears in the 30 epidemiologic studies (not 

counting KATA) reviewed for this report. None of the factors has been established as a 

confounder of ETS, which would require demonstrating that the factor causes lung cancer and is 

correlated with ETS exposure (specifically, spousal smoking to affect the analysis in this report). 

Our objective is to consider the influence of sources of uncertainty on the statistical 

measures summarized in Table 5-13, although there are limitations to such an endeavor. For 

example, not controlling for a factor such as age in the statistical analysis, which should be done 

whether or not the study design is matched on age, may require reanalyzing data not included in 

the study report. Potential sources of bias are just that --potential -- and their actual effect may be 

impossible to evaluate (e.g., selection bias in case-control studies). Although numerous questions 

of interest cannot be answered unequivocally, or even without a measure of subjective judgment, 

it is nevertheless worthwhile to consider issues that may affect interpretation of the quantitative 

results. The issues of concern are largely those of epidemiologic investigations in general that 

motivate the conscientious investigator to implement sound methodology. Statistical uncertainty 

aside, the outcomes of studies that fare well under close examination inspire more confidence and 

thus deserve greater emphasis than those that do poorly. 

Preliminary to the next sections, some relevant notes on epidemiologic concepts are 

excerpted from two IARC volumes entitledStatistical Methods in Cancer Research(Breslow and 

Day, 1980, 1987), dealing with case-control and cohort studies, respectively, which are excellent 

references. In the interest of brevity, an assortment of relevant passages is simply quoted directly 

from several locations in the references (page numbers and quotation marks have been omitted to 

5-49 
improve readability). Some readers may wish to skip to the next section; those interested in a 

more fluid, cogent, and thorough presentation are referred to the references. 

� Bias and confounding. The concepts of bias and confounding are most easily 

understood in the context of cohort studies, and how case-control studies relate to 

them. Confounding is intimately connected to the concept of causality. In a cohort 

study, if some exposure E is associated with disease status, then the incidence of the 

disease varies among the strata defined by different levels of E. If these differences 

in incidence are caused (partially) by some other factor C, then we say that C has 

(partially) confounded the association between E and the disease. If C is not causally 

related to disease, then the differences in incidence cannot be caused by C, thus C 

does not confound the disease/exposure association. 

Confounding in a case-control study has the same basis as in a cohort study . . . and 

cannot normally be removed by appropriate study design alone. An essential part of 

the analysis is an examination of possible confounding effects and how they may be 

controlled. 

Bias in a case-control study, by contrast, [generally] arises from the differences in 

design between case-control and cohort studies. In a cohort study, information is 

obtained on exposures before disease status is determined, and all cases of disease 

arising in a given time period should be ascertained. Information on exposure from 

cases and controls is therefore comparable, and unbiased estimates of the incidence 

rates in the different subpopulations can be constructed. In case-control studies, 

however, information on exposure is normally obtained after disease status is 

established, and the cases and controls represent samples from the total. Biased 

estimates of incidence ratios will result if the selection processes leading to inclusion 

of cases and controls in the study are different (selection bias) or if exposure 

information is not obtained in a comparable manner from the two groups, for 

example, because of differences in response to a questionnaire (recall bias). Bias is 

thus a consequence of the study design, and the design should be directed towards 

eliminating it. The effects of bias are often difficult to control in the analysis, 

although they will sometimes resemble confounding effects and can be treated 

accordingly. 

To summarize, confounding reflects the causal association between variables in the 

population under study, and will manifest itself similarly in both cohort and casecontrol studies. Bias, by contrast, is not a property of the underlying population. It 

results from inadequacies in the design of case-control studies, either in the selection 

of cases or controls or from the manner in which the data are acquired. 

� On prospective cohort studies. One of the advantages of cohort studies over casecontrol studies is that information on exposure is obtained before disease status is 

ascertained. One can therefore have considerable confidence that errors in 

measurement are the same for individuals who become cases of the disease of interest, 

and the remainder of the cohort. The complexities possible in retrospective casecontrol studies because of differences in recall between cases and controls do not 

apply. [Regarding the success of a cohort study, the] follow-up over time . . . is the 

essential feature. . . . The success with which the follow-up is achieved is probably 

the basic measure of the quality of the study. If a substantial proportion of the cohort 

5-50 
is lost to follow-up, the validity of the study’s conclusions is seriously called into 

question. 

� On case-control studies. Despite its practicality, the case-control study is not 

simplistic and it cannot be done well without considerable planning. Indeed, a casecontrol study is perhaps the most challenging to design and conduct in such a way that 

bias is avoided. Our limited understanding of this difficult study design and its many 

subtleties should serve as a warning--these studies must be designed and analyzed 

carefully with a thorough appreciation of their difficulties. This warning should also 

be heeded by the many critics of the case-control design. General criticisms of the 

design itself too often reflect a lack of appreciation of the same complexities which 

make these studies difficult to perform properly. 

The two major areas where a case-control study presents difficulties are in the 

selection of a control group, and in dealing with confounding and interaction as part 

of the analysis. . .these studies are highly susceptible to bias, especially selection bias 

which creates non-comparability between cases and controls. The problem of 

selection bias is the most serious potential problem in case-control studies. . . . Other 

kinds of bias, especially that resulting from non-comparable information from cases 

and controls are also potentially serious; the most common of these is recall . . . bias 

which may result because cases tend to consider more carefully than do controls the 

questions they are asked or because the cases have been considering what might have 

caused their cancer. 

In addition to standard demographic factors (e.g., age) that are usually controlled for in a 

study, a number of other variables have been considered as potential risk factors (including risk 

modifiers) for lung cancer. If a factor increases the risk of lung cancer and its presence is 

correlated with exposure to spousal ETS, then it could be a confounder of ETS if not controlled 

for in a study’s analysis. In general, factors that may affect risk of lung cancer and also may be 

correlated with ETS exposure are of interest as possible explanatory variables. Findings from the 

ETS studies are reviewed for six general categories: (1) personal history of lung disease, 

(2) family history of lung disease, (3) heat sources, (4) cooking with oil, (5) occupation, and 

(6) diet. Table 5-14 provides an overview of results in these categories. Two shortcomings are 

common in the studies where these factors appear: failure to evaluate the correlation of exposure 

to the factor and to ETS, and then to adjust the analysis accordingly; and failure to adjust 

significance levels for multiple comparisons.Multiple tests on the same data increase the chance 

of a false positive (i.e., outcomes appear to be more significant than warranted due to the multiple 

comparisons being made on the same data). 

5.4.2. History of Lung Disease 

Results regarding history of lung disease have been reported in eight of the reviewed ETS 

studies, but with little consistency. Tuberculosis (TB), for example, is significantly associated 

with lung cancer in GAO (OR = 1.7; 95% C.I. = 1.1, 2.4) but not in SHIM (OR = 1.1, no other 

5-51 
Table 5-14. Other risk-related factors for lung cancer evaluated in selected studies 

Category Possible risk factor Mixed outcome No evidence 

Personal or family 

history 

WU (US) 

GENG (Ch) 

LIU (Ch) 

Heat source for 

cooking or heating 

WU (US) 

WUWI (Ch) 

GENG (Ch) 

GAO (Ch) 

LIU (Ch) 

Cooking with oil WUWI (Ch) 

GAO (Ch) 

Diet WU (US) 

ß-carotene 

Occupation WUWI (Ch) 

SHIM (Jap) 

GENG (Ch) 

BUTL (US) 

BUFF (US) 

SHIM (Jap) 

GAO (Ch) 

SOBU (Jap) LAMW (HK) 

KALA (Gr) 

HIRA (Jap) 

SHIM (Jap) 

WUWI (Ch) 

KALA (Gr) 

GAO (Ch)-harmful 

WU (US) 

GAO (Ch) 

statistics), LIU or WU (no ORs provided). Chronic bronchitis, on the other hand, is 

nonsignificant in GAO (OR = 1.2; 95% C.I. =0.8, 1.7), SHIM (OR = 0.8), KABA, and WU, but it 

is highly significant in LIU (OR = 7.37; 95% C.I. = 2.40, 22.66 for females; OR = 7.32; 95% C.I. = 

2.66, 20.18 for males) and mildly so in WUWI (OR = 1.4; 95% C.I. = 1.2, 1.8). (Notably, the 

populations of WUWI, LIU, and GENG were exposed to non-ETS sources of household smoke.) 

Consideration of each lung disease separately, as presented, ignores the effect of multiple 

comparisons described above. For example, GAO looked at five categories of lung disease. If 

that were taken into account, TB would no longer be significant. No discussion of the multiple 

comparisons effect was found in any of the references, which might at least be acknowledged. 

Broadening our focus to examine the relationship of lung cancer to history of lung disease 

in general does little to improve consistency. GENG reports an adjusted OR of 2.12 (95% C.I. = 

1.23, 3.63) for history of lung disease, GAO’s disease-specific findings are consistently positive, 

and WUWI reports three positive associations out of an unknown number assessed. SHIM and 

5-52 
WU, however, consistently found no effect except marginally for silicosis (perhaps better 

construed as an occupational exposure surrogate) in SHIM and for childhood pneumonia in WU. 

LIU found a significant association only for chronic bronchitis and KABA only for pneumonia. 

Interpretation is hampered by the lack of numerical data for factors thatwere not statistically 

significant in KABA, LIU, and WU. Even with such data, however, interpretation is hampered 

by the absence of control for key potential confounders in many of the studies (e.g., age in GENG 

and LIU). Only one study (WV) attempted to control for a history variable (childhood 

pneumonia), which reportedly did not alter the ETS results. The importance of prior lung disease 

as a factor in studies of ETS is thus unclear, but it does not appear to distort results one way or 

the other. 

5.4.3. Family History of Lung Disease 

Only a few of the studies addressed family history of lung disease. GAO found no 

significant association between family history of lung cancer and subjects’ disease status (e.g., 

parental lung cancer OR = 1.1; 95% C.I.= 0.6, 2.3), and positive family histories were very rare 

(e.g., 1.0% among mothers of either cases or controls). In contrast, WUWI reports a significant 

association with history of lung cancer in first-degree relatives (OR = 1.8; 95% C.I. = 1.1, 3.0), 

which occurred in about 4.5% of the cases. The presence of TB in a household member (OR = 1.6; 

95% C.J. = 1.2, 2.1) is also significant, even after adjustment for personal smoking and TB status. 

The rarity of family-linked lung cancer in these populations makes accurate assessment difficult 

and also reduces the potential impact on results of any effect it may have. Its study in populations 

where such cancer is more common would be more appropriate. The household TB outcome may 

be the result of multiple comparisons and/or confounding, particularly in view of the weaker 

(nonsignificant) outcome noted forpersonal TB status. 

5.4.4. Heat Sources for Cooking or Heating 

Household heating and cooking technologies have received considerable attention as 

potential lung cancer risk factors in Asian ETS studies. Most studies have focused on fuel type. 

Kerosene was specifically examined in three studies. All three found positive associations--

CHAN and LAMW for kerosene cooking, and SHIM for kerosene heating--but none of the 

associations were statistically significant, and the SHIM relationship held only for adult and not 

for childhood exposure. Five studies specifically examined coal. GENG evaluated use of coal for 

cooking and found a significant positive association.Use of coal for household cooking or heating 

prior to adulthood is significantly associated with lung cancerin WU’s study of U.S. residents, but 

5-53 
no results for adulthood are mentioned. Recent charcoal stove use showed a positive (OR = 1.7) 

but not significant association in SHIM. Separate analyses of five coal-burning devices and two 

non-coal-burning devices by WUWI found positive although not always significant associations 

for the coal burners. In contrast, SOBU found no association between use of unventilated heating 

devices--including mostly kerosene and coal-fueled types but also some wood and gas burners-­

and lung cancer (OR = 0.94 for use at age 15, 1.09 at age 30, 1.07 at present). Results for wood or 

straw cooking were specifically reported in three studies. SOBU found a significant association 

for use of wood or straw at age 30 (OR = 1.89; 95% C.I. =1.16, 3.06) but only a weak relationship 

at age 15. GAO found no association with current use of wood for cooking (OR = 1.0; 95% C.I. = 

0.6, 1.8), and WUWI mentions that years of household heating with wood, central heating, and 

coal showed nonsignificant trends (negative, negative, and positive, respectively). 

Overall, studies that examined heating and cooking fuels generally found evidence of an 

association with lung cancer for at least one fuel, which was usually but not always statistically 

significant. Such relationships appeared most consistently for use of coal and most prominently in 

WUWI and LIU. Neither study found a significant association between ETS and lung cancer, nor 

did either address whether coal use was associated with ETS exposure. The presence of non-ETS 

sources of smoke within households, however, may effectively mask detection of any effect due to 

ETS (as noted by the authors of WUWI). Evidence of effects of other fuel types and devices is 

more difficult to evaluate, particularly because many studies do not report results for these 

factors, but kerosene-fueled devices seem worthy of further investigation. 

5.4.5. Cooking With Oil 

Cooking with oil was examined by GAO and WUWI, both conducted in China, with 

positive associations for deep-frying (OR ranges of 1.5- 1.9 and 1.2-2.1, respectively, both 

increasing with frequency of cooking with oil). GAO also reports positive findings for stirfrying, boiling (which in this population often entails addition of oil to the water), and smokiness 

during cooking and found that most of these effects seemed specific for users of rapeseed oil. 

These results may apply to other populations where stir-frying and certain other methods of 

cooking with oil are common. Neither study, however, addressed whether use of cooking with oil 

is correlated with ETS exposure. 

5.4.6. Occupation 

Seven studies investigated selected occupational factors, with five reporting positive 

outcomes for one or more occupational variables. The outcomes, however, are somewhat 

inconsistent. SHIM found a strong and significant relationship with occupational metal exposure 

5-54 
(OR = 4.8) and a nonsignificant one with coal, stone, cement, asbestos, or ceramic exposure, while 

WUWI found significant positive relationships for metal smelters (OR = 1.5), occupational coal 

dust (OR = 1.5), and fuel smoke (OR =1.6) exposure. Textile work is positively associated with 

lung cancer in KABA and negatively associated with lung cancer in WUWI. BUFF divided 

occupations into nine categories plus housewife and found eight positive and one negative 

associations relative to housewives, but only one (“clerical”) is significant. GAO, on the other 

hand, found no association with any of six occupational categories, while GENG found a 

significant association for an occupational exposure variable that encompassed textiles, asbestos, 

benzene, and unnamed other substances (OR = 3.1; 95% C.I. = 1.58, 6.02). WU reported “no 

association between any occupation or occupational category,” although there was a nonsignificant 

excess among cooks and beauticians. Finally, BUTL(Coh) found an increased RR for wives whose 

husbands worked in blue collar jobs (> 4; never-smoker). HIRA(Coh) did not present findings for 

husband’s occupation as a risk factor independently but reported that adjustment for this factor 

did not alter the study’s ETS results. Few studies attempted to adjust ETS findings for 

occupational factors--SHIM found only modest effects of such adjustment for occupational metal 

exposure, despite an apparent strong independent effect for this factor, and GENG found only 

minimal effect of occupational exposure on active smoking results but did no adjustment of ETS 

results. Overall, multiple comparisons, other factors (e.g., socioeconomic status, age), and the 

rarity of most specific occupational exposure sources probably account for the inconsistent role of 

occupation in these studies. 

5.4.7. Dietary Factors 

Investigations related to diet have been reported in nine of the ETS studies, with mixed 

outcomes. The fundamental difficulty lies in obtaining accurate individual values for key 

nutrients of interest, such asß-carotene. The relatively modest size of most ETS study 

populations adds further uncertainty in attempts to detect and assess any dietary effect that, if 

present, is likely to be small. In those studies where dietary data were collected and adjusted for 

in the analysis of ETS, diet has had no significant effect. Nevertheless, diet has received attention 

in the literature as a possible explanatory factor in the observed association between ETS exposure 

and lung cancer occurrence (e.g., Koo, 1988; Koo et al., 1988; Sidney et al., 1989; Butler, 1990, 

1991; Marchand et al., 1991); therefore, a more detailed and specific discussion is provided in this 

section. 

Diet is of interest for a potential protective effect against lung cancer. If nonsmokers 

unexposed to passive smoke have a lower incidence of spontaneous (unrelated to tobacco smoke) 

lung cancer incidence due to a protective diet, then the effect would be upward bias in the RR for 

5-55 
ETS. However, for diet to explain fully the significant association of ETS exposure in Greece, 

Hong Kong, Japan, and the United States, which differ by diet as well as other lifestyle 

characteristics, it would need to be shown that in each country: (1) there is a diet protective 

against lung cancer from ETS exposure, (2) diet is inversely associated with ETS exposure, and (3) 

the association is strong enough to produce the observed relationship between ETS and lung 

cancer. Diet may modify the magnitude of any lung cancer risk from ETS (conceivably increase 

or decrease risk, depending on dietary components), but that would not affect whether ETS is a 

lung carcinogen. 

The literature on the effect of diet on lung cancer is not consistent or conclusive, but 

taken altogether there may be a protective effect from a diet high in ß-carotene, vegetables, and 

possibly fruits. Also, there is some evidence that low consumption of these substances may 

correlate with increased ETS exposure, although not necessarily for all study areas. The 

calculations made by Marchand et al. (1991) and Butler (1990, 1991) are largely conjectural, being 

based only on assumed data. Therefore, we examined the passive smoking studies themselves for 

empirical evidence on the effect of diet and whether it may affect ETS results. 

It was found that nine of the studies have data on diet, although only five of them use a 

form of analysis that assesses the impact of diet on the ETS association. None of those five 

studies--CORR, HIRA(Coh), KALA, SHIM, and SVEN--found that diet made a significant 

difference. In the four studies where data on diet were collected but not controlled for in the 

analysis of ETS, three (GAO, KOO, and WUWI) are from East Asia and one (WU) is from the 

United States. Koo (1988),who found strong protective effects for a number of foods, has been 

one of the main proponents of the idea that diet may explain the passive smoking lung cancer 

effect. To our knowledge, however, she has not published a calculation examining that conjecture 

in her own study where data were collected on ETS subjects. In WU, a protective effect of 

ß-carotene was found, but the data include a high percentage of smokers (80% of the cases for 

adenocarcinoma, 86% for squamous cell), and the number of never-smokers is small. In recent 

correspondence concerning the large FONT study, its authors state that “mean daily intake of 

beta-carotene does not significantly differ between study subjects whose spouse smoked and those 

whose spouse never smoked” (Fontham et al., 1992). 

The equivocal state of the literature regarding the effect of diet on lung cancer is also 

apparent in the nine ETS studies that include dietary factors, summarized in Table 5-15. Note 

that GAO found an adverse effect from ß-carotene. HIRA and KOO found opposite effects from 

fish while SHIM found no effect. Fruit was found to be protective by KALA and KOO but 

adverse by SHIM and WUWI. Retinol (based on consumption of eggs and dairy products) was 

found to be protective by KOO but adverse by GAO and WUWI. 

5-56 
Table 5-15. Dietary effects in passive smoking studies of lung cancer in females 

Passive1 

Lung cancer relative risk 

by dietary intake 

quartile, tertile, etc. 

Study Lowest Next Next Highest

CORR2 

GAO 

HIRA4 1.53 

KALA 

RR 

2.07 

1.19 

1.92 

Diet entity Diet entity 

Carotene 

Vitamin A 

Carotene rich 

Retinol rich 

Vitamin A index 

Green-yellow veg. 

Fish 

Meat 

Milk 

Soy paste soup 

ß-carotene 

Vegetables 

Fruits 

Vitamin C 

Retinol 

(preformed) 

No data given 

No data given 

1.0 1.0 1.3 2.03 

1.0 1.1 1.0 1.1 

1.0 1.63 1.2 2.03 

1.05 - 0.866 

1.0 - 1.873 

1.0 - 0.62 

1.0 - 1.30 

1.0 - 0.93 

1.0 - - 1.01 

1.0 - - 1.09 

1.0 - - 0.333 

1.0 - - 0.67 

1.0 - - 1.31 

Remarks 

Never-smokers. Carotene and total vitamin A were 

examined. “Except for gender, age, and study area, 

no confounding was detected.” 

Patterns were similar for smokers and nonsmokers. 

Passive RR was not adjusted for diet, possibly 

because the trends were the opposite of those in the 

literature. 

Never-smokers. Lung cancer risks for wives whose 

husbands were former smokersplus 1-19 cig./day 

smokers and 20+ cig./day smokers relative to neversmokers were 1.50 and 1.79 when adjusted for wives’ 

age (Hirayama, 1984). They ranged from 1.53 to 1.69 

and 1.66 to 1.91 when adjusted for wives’ age, 

husband’s occupation, and each of the various dietary 

factors. 

Never-smokers. Controlled for age, years of 

schooling, interviewer, and total energy intake. No 

confounding was observed between the passive 

smoking effect and the effect of fruits, or between 

that of fruits and that of vegetables. Passive risk 

increased to 2.11 when adjusted for fruit 

consumption. 

(continued on the following page) 
Table 5-15. (continued) 

Passive1 

Study Diet entity 

Lung cancer relative risk 

by dietary intake 

quartile, tertile, etc. 

Lowest Next Next Highest Remarks 

KOO7 1.55 Leafy green veg. 

Carrots 

ß-carotene 

Fresh fruit 

Vitamin C 

Fresh fish 

Smoked/cured 

meat/poultry 

Milk 

Retinol 

1.0 0.49 0.49 

1.0 1.31 0.51 

1.0 0.73 0.73 

1.0 0.81 0.42 

1.0 0.55 0.47 

1.0 0.46 0.35 

1.0 0.82 0.92 

1.0 1.66 0.92 

1.0 0.55 0.42 

Never-smokers. Values are adjusted for age, numbers 

of live births, and schooling. Diet items are selected 

to compare with those in other studies. No calculation 

is shown of confounding effect of diet on the passive 

smoking risk either in Koo et al. (1987), Koo (1988), 

Koo et al. (1988), or Koo (1989). Fresh fruit, vitamin 

C, fresh fish, and retinol showed statistically 

significant trends. 

SHIM 1.08 

SVEN 1.26 

Green-yellow veg. 

Fruit 

Milk 

Fish, pork, or 

lamb 

Chicken 

1.08 0.98 Never-smokers. No dose response was found. No 

1.0 1.2 difference between cases and controls was found 

1.0 1.0 regarding intake of green-yellow vegetables. 

1.0 1.0 

1.0 0.7 

Carrots 1.09 0.710 0.63,11 Adjusted for age, smoking, cumulative Rn exposure 

and municipality. The inclusion of carrot 

consumption in the regression model “had only a 

slight effect on the risk estimates of the other 

exposure variables.” See Svensson (1988). 

RR 

(continued on the following page) 
1

2

3

4

5

6

7

8

9

10

11

Table 5-15. (continued) 

Lung cancer relative risk 

by dietary intake 

quartile, tertile, etc. 

Lowest Next Next Highest Remarks 

Passive1 

Study RR Diet Entity 

WU 1.41 

WUWI 0.79 

ß-carotene 1.0 0.52 0.32 0.403 

Preformed Vit. A 1.0 0.92 0.50 0.83 

Dairy products 

and eggs 1.0 0.82 0.633 0.373 

Vegetables 

high-carotene 

low-carotene 

Fresh fruit 

Animal protein 

1.0 1.1 1.0 0.9 

1.0 1.0 1.0 0.8 

1.0 1.0 1.43 1.53 

1.0 3 1.63 2.33 

For adenocarcinoma. Risks of 0.67, 1.0, and 0.63, 

high calf versus low calf, were observed for ßcarotene, preformed vitamin A, and dairy and eggs 

for squamous cell carcinoma. Adjusted for cigarettes 

smoked per day. No adjustment is shown to the 

passive risk for diet. 

Adjusted for age, education, personal smoking, and 

study area. Eight variables other than smoking were 

thought to have a significant effect on lung cancer 

risk. Diet variables were not included in this list, and 

1.6 no adjustment to the passive risk was made for them. 

From Table 5-5.

As reanalyzed by Dalager et al. (1986).

Statistically significant at the p = 0.05 level.

Case-control study nested in Hirayama’s cohort study, ages 40-69 only (Hirayama, 1989).

Less than daily.

Daily.

From Koo (1988).

Cutoffs various.

Less than once per week.

Once per week.

More than once per week.
In view of the results summarized in Tables 5-14 and 5-15, the actual data of ETS studies 

do not support the suspicion that diet introduces a systematic bias in the ETS results. Indeed, it 

would be difficult to show otherwise. Dietary intake is difficult to assess; dietary habits vary 

within countries and enormously between countries, making it difficult to attribute any effect on 

lung cancer to a particular food group; lifestyle characteristics and consumption of food and 

beverage with possibly an adverse effect may be associated, either positively or negatively, with 

the food group under consideration.It would, of course, be helpful to identify dietary factors 

that may affect lung cancer, positively or negatively, because that information could usefully 

contribute to public health. To affect interpretation of ETS results, however, it would need to be 

established also that consumption of the dietary factor of interest is highly correlated with ETS 

exposure in study populations where ETS exposure is linked with increased incidence of lung 

cancer. 

5.4.8. Summary on Potential Modifying Factors 

In summary, an examination of six non-ETS factors that may affect lung cancer risk finds 

none that explains the association between lung cancer and ETS exposure as observed by 

independent investigators across several countries that vary in social and cultural behavior, diet, 

and other characteristics. On the other hand, the high levels of indoor air pollution from other 

sources (e.g., smoky coal) that occur in some parts of China and show statistical associations with 

lung cancer in the studies of GENG, LIU, and WUWI may mask any ETS effects in those studies. 

5.5. ANALYSIS BY TIER AND COUNTRY 

In this section, attention is directed to properties of individual studies, including potential 

sources of bias, that may affect their utility for the assessment of ETS and lung cancer. Studies 

are assessed based on qualitative as well as statistical evaluation. The studies are qualitatively 

reviewed in Appendix A and categorized into “tiers” within country. Studies are individually 

scored according to items in eight categories.Study scores are then implemented in a numerical 

scheme to classify each study into one of four tiers according to that study’s assessed utility for 

hazard identification of ETS. Tier I studies are those of greatest utility for investigating a 

potential association between ETS and lung cancer. Other studies are assigned to Tiers 2, 3, and 4 

as confidence in their utility diminishes. Tier 4 is reserved for studies we would exclude from 

analysis for ETS, for various reasons specified in the text. In the statistical analysis presented in 

this section, the summary RR for each country is recalculated for studies in Tier I alone and for 

Tiers 1-2, 1-3, and 1-4 (the last category corresponds to the combined analysis shown in 

5-60 
Table 5-9) by country. This exercise provides some idea of the extent to which the summary RR 

for a country depends on the choice of studies. 

The assignment of studies to tiers is shown in Table 5-16. Overall, 5 studies are in the 

highest tier, while 15, 5, and 5 studies are in Tiers 2, 3, and 4, respectively (KATA was not 

assigned to a tier). Studies in Tier 4 are not recommended for the objectives of this report. The 

statistical weight for Tiers 1, 2, and 3 pooled together for each country is shown in Table 5-9 as a 

percentage of the total for corresponding tiers over all countries. Emphasis on studies through 

Tier 2 or through Tier 3 is somewhat arbitrary. Although studies in Tier 1 are judged to be of the

highest utility, exclusive attention to Tier 1 would eliminate considerable epidemiologic data 

because only 16% of the studies are in Tier 1.Excluding Tier 4 leaves the choices to either all 

studies through Tier 2 or through Tier 3. GAO is the only study in China that was not placedin

Tier 4, but there is little basis to assume that this single study from Shanghai should be 

representative of a vast country like China. 

Table 5-17 presents adjusted relative risk estimates, 90% confidence intervals, and 

significance levels (one-sided) from studies pooled by country and by tier. The pooled relative 

risks do not decrease as the results from studies in Tier 2 and Tier 3 are combined with those from 

Tier I, with two exceptions: In the United States, the pooled estimate changes from 1.28 to 1.22 

to 1.19 when Tier 2 and Tier 3 studies are added, respectively, and in Western Europe, the pooled 

estimate changes from 1.21 to 1.17 when Tier 2 studies are added. The pooled estimates for 

studies through Tier 2 are statistically significant at p =0.02 (one-tailed) in Greece, Hong Kong,

Japan, and the United States; Western Europe is the exception (p = 0.22). The same statement

holds with Tier 2 replaced by Tier 3, except that China includes one study at p = 0.18. The

relative risk results from all four Western European studies (RR = 1.17) is virtually the same for

all U.S. studies (RR = 1.19), but with less power that value is not significant for Western Europe.

The similarity of outcomes is also interesting, however, because Western Europe is probably more

similar to the United States than the other countries.

Analysis by tiers provides a methodology for weighting studies according to their utility 

for hazard identification of ETS. It allows one to emphasize those studies thought to provide 

better data for analysis of an ETS effect. The addition of studies of lower utility to the analysis, 

such as inclusion of Tier 3 studies with those from Tiers 1 and 2, has a small effect on the relative 

risk estimate but both increases its statistical significance and narrows its confidence interval. In 

view of that outcome and the results and discussion in Section 5.4, this analysis finds little to 

indicate confounding or bias in studies through Tier 3 (which include all studies in the United 

States). In summary, it is concluded that the association of ETS and lung cancer observed from 

5-61 
Table 5-16. Classification of studies by tier 

Country Study Tier 1 Tier 2 Tier 3 Tier 4 

Greece KALA 

Greece TRIC 

Hong Kong 

Hong Kong 

Hong Kong 

Hong Kong 

KOO 

LAMT 

LAMW 

CHAN 

Japan 

Japan 

Japan 

Japan 

Japan 

AKIB 

HIRA(Coh) 

SHIM 

SOBU 

INOU 

United States 

United States 

United States 

United States 

United States 

United States 

United States 

United States 

United States 

United States 

United States 

FONT 

BUTL(Coh) 

GARF 

HUMB 

JANE 

WU 

BROW 

BUFF 

CORR 

GARF(Coh) 

KABA 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

X 

(continued on the following page) 

5-62
Table 5-16. (continued) 

Country Study Tier I Tier 2 Tier 3 Tier 4 

W. Europe 

Scotland 

Sweden 

Sweden 

England 

China 

China 

China 

China 

HOLE(Coh) 

PERS 

SVEN 

LEE 

X 

X 

X 

X 

GAO X 

GENG X 

LIU X 

WUWI X 

the analysis of 30 epidemiologic studies in eight different countries is not due to chance alone and 

is not attributable to bias or confounding. 

5.6. CONCLUSIONS FOR HAZARD IDENTIFICATION 

5.6.1. Criteria for Causality 

According to EPA’s Guidelines for Carcinogen Risk Assessment(U.S. EPA, 1986a), a 

Group A (known human) carcinogen designation is used “when there is sufficient evidence from 

epidemiologic studies to support a causal association between exposure to the agents and cancer.” 

The Guidelines establish “three criteria [that] must be met before a causal association can be 

inferred between exposure and cancer in humans: 

1. There is no identified bias that could explain the association. 

2. The possibility of confounding has been considered and ruled out as explaining the 

association. 

3. The association is unlikely to be due to chance.” 

As demonstrated in the preceding sections, the overall results observed in the 30 epidemiologic 

studies are not attributable to chance and the association between ETS and lung cancer is not 

explained by bias or confounding. 
---

---

---

--- ---

---

---

---

--- ---

---

--- ---

---

1 Table 5-17. Summary data interpretation by tiers within country

Through 

Tier2 

Relative 

weight3 

(%) Country4 

Studies 

added RR 

Confidence 

interval 

90% 

P-value 

effect 

(1.13, 3.23) 0.02 

(1.13, 3.23) 0.02 

(1.42, 2.84) 0.0005 

(1.42, 2.84) 0.0005 

Greece 

Greece 

Greece 

Greece 

KALA 

TRIC 

Hong Kong KOO 

Hong Kong LAMT 

Hong Kong LAMW 

Hong Kong CHAN 

Japan 

Japan AKIB, HIRA(Coh), 

SHIM, SOBU 

INOU 

1.92 

1.92 

2.01 

2.01 

1.54 

1.61 

1.75 

1.48 

(0.98, 2.43) 0.06 

(1.25, 2.07) 0.0009 

(1.39, 2.19) 0.00002 

(1.21, 1.81) 0.0008 

1.39 (1.16, 1.66) 

1.39 

1.41 

1.28 

1.22 

(1.16, 1.66) 

(1.18, 1.69) 

(1.03, 1.60) 

(1.04, 1.42) 

1.19 

1.19 

1.21 

1.17 

1.17 

1.17 

1.19 

0.95 

(1.04, 1.35) 

(1.04, 1.35) 

(0.79, 1.90) 0.24 

(0.85, 1.64) 0.22 

(0.85, 1.64) 0.22 

(0.85, 1.64) 0.22 

(0.87, 1.62) 0.18 

(0.81, 1.12) 0.70 

4 

6 

16 

14 

FONT 

BUTL(Coh), CORR, GARF, 

HUMB, JANE, KABA, WU 

BROW, BUFF, GARF(Coh) 

30 0.001

23 0.001 

0.0007 

0.03 

0.02 

Japan 

Japan 

United States 

41 United States

43 0.02 

0.02 

United States 

United States 

HOLE(Coh), PERS 

SVEN, LEE 

W. Europe 

W. Europe 

W. Europe 

W. Europe 

China 

China 

China 

China 

9 

7 

0 

7 GAO 

GENG, LIU, WUWI 

(continued on the following page) 
Table 5-17. (continued) 

1

Use of Tiers 1 through 2 or Tiers 1 through 3, both shown in boldface, is recommended. Tier 4 is not recommended. 

2

Each line contains the studies in the previous tiers plus those added.

3

Percentage of total weight by country for Tiers 1 through 2 or 1 through 3.

4

Western Europe consists of England, Scotland, and Sweden. 
Below, the evidence for a causal association between ETS and lung cancer is evaluated 

according to seven specific criteria for causality developed by an EPA workshop to supplement 

the Guidelines (U.S. EPA, 1989). These criteria are similar to the original and classical 

recommendations of Hill (1953, 1965). The seven recommended (but not official) criteria from 

the EPA workshop, which vary between essential and desirable, are listed below (U.S. EPA, 1989). 

A causal interpretation is enhanced for studies to the extent that they meet the 

criteria described below. None of these actually establishes causality; actual proof 

is rarely attainable when dealing with environmental carcinogens. The absence of 

any one or even several of the others does not prevent a causal interpretation. 

Only the first criterion (temporal relationship) is essential to a causal relationship: 

with that exception, none of the criteria should be considered as either necessary or 

sufficient in itself. The first six criteria apply to an individual study. The last 

criterion (coherence) applies to a consideration of all evidence in the entire body of 

knowledge. 

1. Temporal relationship: The disease occurs within a biologically reasonable 

timeframe after the initial exposure to account for the specific health effect. 

2. Consistency When compared to several independent studies of a similar exposure 

in different populations, the study in question demonstrates a similar association 

which persists despite differing circumstances. This usually constitutes strong 

evidence for a causal interpretation (assuming the same bias or confounding is not 

also duplicated across studies). 

3. Strength of association: The greater the estimate of risk and the more precise, the 

more credible the causal association. 

4. Dose-response or biologic gradient: An increase in the measure of effect is 

correlated positively with an increase in the exposure or estimated dose. If present, 

this characteristic should be weighted heavily in considering causality. However, 

the absence of a dose-response relationship should not be construed by itself as 

evidence of a lack of a causal relationship. 

5. Specificity of the association: In the study in question, if a single exposure is 

associated with an excess risk of one or more cancers also found in other studies, it 

increases the likelihood of a causal interpretation. 

6. Biological plausibility: The association makes sense in terms of biological 

knowledge. Information from toxicology, pharmacokinetics, genotoxicity, and in 

vitro studies should be considered. 

7. Coherence: Coherence exists when a cause-and-effect interpretation is in logical 

agreement with what is known about the natural history and biology of the disease. 

A proposed association that conflicted with existing knowledge would have to be 

examined with particular care. (This criterion has been called “collateral evidence” 

previously.) 

5-66
5.6.2. Assessment of Causality 

We consider the extent to which the criteria for causality are satisfied for the ETS studies. 

Regarding temporal relationship, ETS exposure classification is typically based on the marital 

history of a subject, which varies, or on the status at the beginning of a prospective cohort study. 

Very few studies up through Tier 3 considered current exposure status only (see Appendix A), so 

some history of ETS exposure is largely the rule for ETS-exposed subjects. Analysis of data by 

exposure level in Section 5.3.3 indicates increased relative risk with exposure level, which supports 

the temporal relationship. 

If ETS causes lung cancer, then the true relative risk is small for detection by 

epidemiologic standards and may differ between countries as well. However, by considering the 

totality of the evidence, it is determined that the large accumulation of epidemiologic evidence 

from independent sources in different locales and circumstances, under actual exposure 

conditions, is adequate for conclusiveness. Having accounted for variable study size, adjusted for 

a possible systematic spousal bias due to smoker misclassification, and considered potential bias, 

confounding, and other sources of uncertainty on a study-by-study basis, consistency of a 

significant association is clearly evident for the summary statistical measures for Tiers 1 through 2 

and 1 through 3 in Greece, Hong Kong, Japan, and the United States. The combined countries 

from Western Europe are similar in outcome to the United States, although significance is not 

attained. There is too much obscurity and uncertainty attached to the studies in China for 

adequate data interpretation. 

The relative risks for each country are obtained by pooling estimates from the 

epidemiologic studies conducted in the country. Thestrength of association is limited by the true 

value of the relative risk, which is small. Statistical significance is attained, however, for the 

pooled studies of the United States and most other countries.The data were obtained from actual 

conditions of environmental exposure; therefore, imprecision is not increased by extrapolation of 

results from atypically high exposure concentrations, a common situation in risk analysis. 

Additionally, all studies were individually corrected for systematic bias from smoker 

misclassification at the outset, and qualitative characteristics of the studies were carefully 

reviewed to emphasize the results from the studies with higher utility for the objectives of this 

report. The outcome for the United States is heavily influenced by the large National Cancer 

Institute study (FONT) that was specifically designed and executed to avoid methodological 

problems that might undermine the accuracy or precision of the results. 

Of the 14 studies reporting a test for upward trend, 10 are statistically significant at 0.05 

(see Table 5-12) which would occur by chance alone with probability less than 10 -9. This 

5-67 
evidence of dose response is very supportive of a causal interpretation because it would be an 

unlikely result of any operative sources of bias or confounding. 

Specificity does not apply to ETS. Although ETS has been assessed for the same endpoint 

(lung cancer) in all studies, the occurrence of lung cancer is not specific to ETS exposure. Data 

on histological cell type are not conclusive.The study by Fontham and colleagues (1991) suggests 

that adenocarcinoma may be more strongly related to ETS exposure than other cell types. 

Adenocarcinoma, however, does not appear to be etiologically specific to ETS. 

Biomarkers such as cotinine/creatinine levels clearly indicate that ETS is taken up by the 

lungs of nonsmokers (see Chapter 3). The similarity of carcinogens identified in sidestream and 

mainstream smoke, along with the established causal relationship between lung cancer and 

smoking in humans with high relative risks and dose-response relationships in four different lung 

cell types down to low exposure levels, providebiological plausibility that ETS is also a lung 

carcinogen (Chapter 4). In addition, animal models and genotoxicity assays provide corroborating 

evidence for the carcinogenic potential of ETS (Chapter 4). The epidemiologic data provide 

independent empirical verification of the anticipated risk of lung cancer from passive smoking 

and also an estimate of the increased risk of lung cancer to never-smoking women. Thecoherence 

of results from these three approaches and the lack of significant arguments to the contrary 

strongly support causality as an explanation of the observed association between ETS exposure and 

lung cancer. 

5.6.3. Conclusion 

Based on the assessment of all the evidence considered in Chapters 3, 4, and 5 of this 

report and in accordance with the EPAGuidelines and the causality criteria above for 

interpretation of human data, this report concludes that ETS is a Group A human carcinogen, the 

EPA classification “used only when there is sufficient evidence from epidemiologic studies to 

support a causal association between exposure to the agents and cancer” (U.S. EPA, 1986a). 

5-68
6. POPULATION RISK OF LUNG CANCER FROM PASSIVE SMOKING 

6.1. INTRODUCTION 

The preceding chapter addressed the topic of hazard identification and 

concluded that environmental tobacco smoke (ETS) exposure is causally 

associated with lung cancer. If an effect is large enough to detect in 

epidemiologic studies investigating the consequences of ETS exposure at 

common exposure levels, the individual risk associated with exposure is 

considered to be high compared with most environmental contaminants assessed. 

Of course, the number of lung cancer deaths attributable to ETS exposure for a 

whole population, such as the United States, depends on the number of persons 

exposed as well as the individual risk. Studies of cotinine/creatinine 

concentrations in nonsmokers indicate that ETS is virtually ubiquitous. For 

example, in urinary bioassays of 663 nonsmokers, Cummings et al. (1990) found 

that over 90% had detectable levels of cotinine. Among the 161 subjects who 

reported no recent exposure to ETS, the prevalence of detectable cotinine was 

still about 80%. Although the average cotinine level for all those tested may be 

below the average for subjects exposed to spousal ETS, as studied in this report, 

it indicates uptake of ETS to some extent by a large majority of nonsmokers (see 

also Chapter 3). Consequently, exposure to ETS is a public health issue that 

needs to be considered from a national perspective. 

This chapter derives U.S. lung cancer mortality estimates for female and 

male never-smokers and long-term (5+ years) former smokers. Section 6.2 

discusses prior approaches to estimating U.S. population risk. Section 6.3 

presents this report's estimates. First, the parameters and formulae used are 

defined (Section 6.3.2), and then lung cancer mortality estimates are calculated 

from two different data sets and confidence and sources of uncertainty in the 

estimates are discussed. Section 6.3.3 derives estimates based on the combined 

relative risk estimates of the 11 U.S. studies from Chapter 5. Section 6.3.4 bases 

its estimates on the data from the single largest U.S. study, that of Fontham et al. 

(1991). Finally, Section 6.3.5 discusses the sensitivity of the estimates to 

changes in various parameter values. ETS-attributable lung cancer mortality 

rates (LCMR) for each of the individual studies from Chapter 5 are presented in 

Appendix C. 

6.2. PRIOR APPROACHES TO ESTIMATION OF POPULATION RISK 

Several authors have estimated the population risk of lung cancer from 

exposure to ETS. Two approaches have been used almost exclusively. One 

approach analyzes the overall epidemiologic evidence available from casecontrol and cohort studies, as done in this report; the other estimates a doseresponse relationship for ETS exposure extrapolated from active smoking, based 

on "cigarette-equivalents" determined from a surrogate measure of exposure 

6-1 
common to passive and active smoking. A recent review of risk assessment 

methodologies in passive smoking may be found in Repace and Lowrey (1990). 

6.2.1. Examples Using Epidemiologic Data 

The National Research Council report (NRC, 1986) is a good example of 

the epidemiologic approach. An overall estimate of relative risk (RR) of lung 

cancer for never-smokers exposed to both spousal smoking and background ETS 

versus those exposed only to background ETS is obtained by statistical summary 

across all available studies. Two "corrections" are then made to the estimate of 

RR to correct for the two sources of systematic bias. The first correction 

accounts for expected upward bias from former smokers and current smokers 

who may be misclassified as never-smokers; this correction results in a decrease 

in the RR estimate. The second correction is an upward adjustment to the RR 

taking into account the risk from background exposure to ETS (experienced by a 

never-smoker whether married to a smoker or not) to obtain estimates of the 

excess lung cancer risk from all sources of ETS exposure (spousal smoking and 

background ETS) relative to the risk in an ETS-free environment. Population 

risk can then be characterized by estimating the annual number of lung cancer 

deaths among never-smokers attributable to all sources of ETS exposure. This 

calculation requires the final corrected estimates of RR (one for background ETS 

only and one for background plus spousal smoking), the annual number of lung 

cancer deaths (LCDs) from all causes in the population assessed (e.g., neversmokers of age 35 and over), and the proportion of that population exposed to 

spousal smoking. The entire population is assumed to be exposed to some 

average background level of ETS; although, in fact, the population contains 

some individuals with high exposure and others with virtually no exposure. 

The NRC report combines data for female and male never-smokers to 

obtain an overall observed RR estimate of 1.34 (95% confidence interval [C.I.] = 

1.18, 1.53), but this estimate is most heavily influenced by the abundant female 

data. (The female data alone generate a combined RR estimate of 1.32 [95% C.I. 

= 1.18, 1.52], while the male data produce an RR estimate of 1.62 [95% C.I. = 

0.99, 2.64].) To adjust for potential misclassification bias, the NRC uses the 

construct of Wald and coworkers. The technical details of the adjustment are 

contained in Wald et al. (1986) and to a lesser degree in the NRC report. After 

correcting the overall observed RR estimate of 1.34 downward for an expected 

positive (upward) bias from smoker misclassification, the NRC concludes that 

the relative risk is about 1.25, and probably lies between 1.15 and 1.35. 

Correction for background sources (i.e., nonspousal sources of ETS) increases 

the NRC estimate of RR for an "exposed" person (i.e., exposed to ETS from 

spousal smoking) to 1.42 (range of 1.24 to 1.61); the change is due only to 

implicit redefinition of RR to mean risk relative to zero-ETS exposure instead of 

relative to nonspousal sources of ETS. Under this redefinition, the RR for an 

6-2 
"unexposed" person (i.e., unexposed to spousal ETS) versus a truly unexposed 

person (i.e., in a zero-ETS environment) becomes 1.14 (range of 1.08 to 1.21). 

The NRC report further estimates that about 21% of the lung cancers in 

nonsmoking women and 20% in nonsmoking men may be attributable to 

exposure to ETS (NRC, 1986, Appendix C); these estimates, however, are based 

on RRs corrected for background ETS but not for smoker misclassification. 

Applying these percentages to estimates of 6,500 LCDs in never-smoking 

women and 3,000 LCDs in never-smoking men in 1988 (American Cancer 

Society, personal communication), the number attributable to ETS exposure is 

1,365 and 600, respectively, for a total of about 2,000 LCDs among neversmokers of both sexes. 

Robins (NRC, 1986, Appendix D [included in the NRC report but neither 

endorsed nor rejected by the committee]) explores three approaches to 

assessment of lung cancer risk from exposure to ETS, each with attendant 

assumptions clearly stated. A related article by Robins et al. (1989) contains 

most of the same information. Method 1 is based solely on evaluation of the 

epidemiologic data applying two assumptions: (1) correction of relative risk for 

background exposure to ETS independent of age, and (2) the excess relative risk 

in a nonsmoker is proportional to the lifetime dose of ETS. In this method, 

Robins uses a weighted average RR of 1.3. After correcting this RR for 

background ETS exposure, age-adjusted population-attributable risks are 

calculated for females and males separately. Adjusting Robins' results to 6,500 

annual LCDs in female never-smokers and 3,000 LCDs in male never-smokers, 

for comparison purposes, yields estimates of 1,870 female LCDs and 470 male 

LCDs attributable to ETS. Method 2 uses an overall relative risk value based on 

epidemiologic data, but also makes some assumptions to appeal to results of Day 

and Brown (1980) and Brown and Chu (1987) on lung cancer risk in active 

smokers. Again, adjusting Robins' estimates to 6,500 female LCDs and 3,000 

male LCDs, the range of excess LCDs attributable to ETS is 1,650 to 2,990 for 

never-smoking females and 420 to 1,120 for never-smoking males. Method 3 is 

a "cigarette-equivalents" approach and is discussed in Section 6.2.2. 

The Centers for Disease Control (CDC) has published an estimate of 3,825 

(2,495 female and 1,330 male) deaths in nonsmokers from lung cancer 

attributable to passive smoking for the year 1988 (CDC, 1991a), with reference 

to the NRC report of 1986. Those figures are the midrange of values for males 

and females from method 2 of Robins in Appendix D of the NRC report (NRC, 

1986). 

Blot and Fraumeni (1986) published a review and discussion of the 

available epidemiologic studies about the same time that the reports of the 

Surgeon General and NRC appeared. The set of studies considered by Blot and 

Fraumeni are almost identical to those included in the NRC report, except for 

omission of one cohort study (Gillis et al., 1984), and inclusion of Wu et al. 

6-3 
(1985), the case-control study excluded by the NRC because the raw data were 

unpublished. An overall relative risk estimate calculated from the raw data for 

females yields 1.3 (95% C.I. = 1.1, 1.5). When the results are combined for 

high-exposure categories, the overall relative risk estimate is 1.7 (1.4, 2.1). 

Wells (1988) provides a quantitative risk assessment that includes several 

epidemiologic studies subsequent to the NRC and Surgeon General's reports of 

1986 (NRC, 1986; U.S. DHHS, 1986). Like the NRC report, the epidemiologic 

data for both women and men are considered, for which Wells provides separate 

estimates of overall relative risk and attributable risk. Wells calculates an 

overall relative risk of 1.44 (95% C.I. = 1.26, 1.66) for females and 2.1 (1.3, 3.2) 

for males. Following the general approach of Wald et al. (1986), the 

misclassification percentage for ever-smokers is assumed to be 5% (compared to 

7% for Wald et al.). Rates are corrected for background exposure to ETS, except 

in studies from Greece, Japan, and Hong Kong, where the older nonsmoking 

women are assumed to experience very little exposure to ETS outside the home. 

A refinement in the estimation of population-attributable risk is provided by 

adjusting for age at death (which also appears in the calculations of Robins, 

NRC, Appendix D). The calculation of population-attributable risk applies to 

former smokers as well as never-smokers, which is a departure from Wald et al. 

and the NRC report. The annual number of LCDs attributable to ETS in the 

United States is estimated to be 1,232 (females) and 2,499 (males) for a total of 

3,731. About 3,000, however, is thought to be the best current estimate (Wells, 

1988). (In addition to the estimates of ETS-attributable LCDs, Wells uses the 

epidemiological approach to derive estimates of ETS-attributable deaths from 

other cancers--11,000--and from heart disease--32,000.) 

Saracci and Riboli (1989), of the International Agency for Research on 

Cancer (IARC), review the evidence from the 3 cohort studies and 11 of the 

case-control studies (Table 4-1). The authors follow the example of the NRC 

and Wald et al. with respect to the exclusion of studies, and add only one 

additional case-control study (Humble et al., 1987). The overall observed 

relative risk for the studies, 1.35 (95% C.I. = 1.20, 1.53), is about the same as 

that reported by the NRC, 1.34 (1.18, 1.53). It is not reported how the overall 

relative risk was calculated. 

Repace and Lowrey (1985) suggest two methods to quantify lung cancer 

risk associated with ETS. One method is based on epidemiologic data, but, 

unlike the previous examples, Repace and Lowrey use a study comparing 

Seventh-Day Adventists (SDAs) (Phillips et al., 1980a,b) with a 

demographically and educationally matched group of non-SDAs who are also 

never-smokers to obtain estimates of the relative risk of lung cancer mortality, in 

what they describe as a "phenomenological" approach. The SDA/non-SDA 

comparison provides a basis for assessing lung cancer risk from ETS in a 

broader environment, particularly outside the home, than the other epidemiologic 

6-4 
studies. It also serves as an independent source of data and an alternative 

approach for comparison. Information regarding the number of age-specific 

LCDs and person-years at risk for the two cohorts is obtained from the study. 

The basis for comparison of the two groups is the premise that the non-SDA 

cohort is more likely to be exposed to ETS than the SDA group due to 

differences in lifestyle. Relatively few SDAs smoke, so an SDA never-smoker 

is probably less likely to be exposed at home by a smoking spouse, in the 

workplace, or elsewhere, if associations are predominantly with other SDAs. 

One of the virtues of this novel approach is that it contributes to the variety of 

evidence for evaluation and provides a new perspective on the topic. 

Phillips et al. (1980 a,b) reported that the non-SDA cohort experienced an 

average LCMR equal to 2.4 times that of the SDA cohort. Using 1974 U.S. Life 

Tables, Repace and Lowrey calculate the difference in LCMR for the two 

cohorts by 5-year age intervals and then apply this value to an estimated 62 

million never-smokers in the United States in 1979 to obtain the number of 

LCDs attributable to ETS annually. The result, 4,665, corresponds to a risk rate 

of about 7.4 LCDs per 100,000 person-years. In an average lifespan of 75 years, 

that value equates to 5.5 deaths per 1,000 people exposed. The second method 

described by Repace and Lowrey is a "cigarette-equivalents" approach and is 

discussed in Section 6.2.2. 

Wigle et al. (1987) apply the epidemiologic evidence from the SDA/nonSDA study (Phillips et al., 1980a,b) to obtain estimates of the number of LCDs 

in never-smokers due to ETS in the population of Canada. The estimated 

number of deaths from lung cancer attributable to passive smoking is calculated 

separately for males and females, using age-specific population figures for 

Canada and the age-specific rates of death from lung cancer attributable to ETS 

estimated by Repace and Lowrey (1985). A total of 50 to 60 LCDs per year is 

attributed to spousal smoking alone, with 90% of them in women. Overall, 

involuntary exposure to tobacco smoke at home, work, and elsewhere may cause 

about 330 LCDs annually. 

6.2.2. Examples Based on Cigarette-Equivalents 

The cigarette-equivalents approach assumes that the dose-response curve 

for lung cancer risk from active smoking also applies to passive smoking, after 

extrapolation of the curve to lower doses and conversion of ETS exposure into 

an "equivalent" exposure from active smoking, determined from a surrogate 

measure of exposure common to passive and active smoking. Relative cotinine 

concentrations in body fluids (urine, blood, or saliva) of smokers versus 

nonsmokers and tobacco smoke particulates in sidestream smoke (SS) and 

mainstream smoke (MS) have commonly been used for this purpose. The lung 

cancer risk of ETS is assumed to equal the risk from active smoking at the rate 

determined by the cigarette-equivalents. For example, suppose the average 

6-5 
cotinine concentration in exposed never-smokers is 1% of the average value 

found in people who smoke 30 cigarettes per day. The lung cancer risk for a 

smoker of (0.01)30 = 0.3 cigarettes per day is estimated by low-dose 

extrapolation from a dose-response curve for active smoking, and that value is 

used to describe the lung cancer risk for ETS exposure. This general explanation 

describes the nature of the approach; however, authors vary in their constructed 

solutions and level of detail. The basic assumption of cigarette-equivalents 

procedures is that the lung cancer risks in passive and active smokers are 

equivalently indexed by the common measure of exposure to tobacco smoke, 

i.e., a common value of the surrogate measure of exposure in an active and a 

passive smoker would imply the same lung cancer risk in both. This assumption 

may not be tenable, however, as MS and SS differ in the relative composition of 

carcinogens and other components identified in tobacco smoke and in their 

physicochemical properties in general; the lung and systemic distribution of 

chemical agents common to MS and SS are affected by their relative distribution 

between the vapor and particle phases, which differs between MS and SS and 

changes with SS as it ages. Active and passive smoking also differ in 

characteristics of intake; for example, intermittent (possibly deep) puffing in 

contrast to normal (shallow) inhalation, which may affect deposition and 

systemic distribution of various tobacco smoke components as well (see Sections 

3.2 and 3.3.2). 

Several authors have taken issue with the validity of the cigaretteequivalents approach. For example, Hoffmann et al. (1989), in discussing the 

longer clearance times of cotinine from passive smokers than from active 

smokers, conclude that "the differences in the elimination time of cotinine from 

urine preclude a direct extrapolation of cigarette-equivalents to smoke uptake by 

involuntary smokers." A recent consensus report of an IARC panel of experts 

(Saracci, 1989) states, "Lacking knowledge of which substances are responsible 

for the well-established carcinogenic effect of MS, it is impossible to accurately 

gauge the degree of its similarity to ETS in respect to carcinogenic potential." 

The Surgeon General's report devotes a three-page section to the concept of 

cigarette-equivalents, quantitatively demonstrating how they can vary as a 

measure of exposure (U.S. DHHS, 1986). It concludes that "these limitations 

make extrapolation from atmospheric measures to cigarette-equivalents units of 

disease risk a complex and potentially meaningless process." (On a lesser note, 

it has generally been assumed that the dose-response relationship for active 

smokers is reasonably well characterized. Recent literature raises some 

questions on this issue [Moolgavkar et al., 1989; Gaffney and Altshuler, 1988; 

Freedman and Navidi, 1987a,b; Whittemore, 1988].) 

Citing cigarette-equivalents calculated in other sources, Vutuc (1984) 

assumes a range of 0.1 to 1.0 cigarettes per day for ETS exposure. Relative risks 

for nonsmokers are calculated for 10-year age intervals (40 to 80) based on the 

6-6 
reported relationships of dose, time, and lung cancer incidence in Doll and Peto 

(1978). Relative risks for smokers of 0.1 to 1.0 cigarettes per day give a range in 

relative risk from 1.03 to 1.36. The author concludes that "as it applies to 

passive smokers, this range of exposures may be neglected because it has no 

major effect on lung cancer incidence." Vutuc assumes that his figures apply to 

both males and females. If an exposure fraction of 75% is assumed for both 

males and females, the range of relative risks given correspond to a range for 

population-attributable risk. If the number of LCDs among never-smokers in the 

United States in 1988 is about 6,500 females and 3,000 males (personal 

communication from the American Cancer Society), then the number of LCDs in 

never-smokers attributable to ETS is estimated to range from 240 to 2,020 (140 

to 1,380 for females alone). So Vutuc's figures are consistent with several 

hundred excess LCDs among never-smokers in the United States. These 

estimates are from our extension of Vutuc's analysis, however, and are not the 

claim of the author. 

Repace and Lowrey (1985) describe a cigarette-equivalents approach as an 

alternative to their "phenomenological" approach discussed in Section 6.2.1. 

One objective is to provide an assessment of exposure to ETS from all sources 

that is more inclusive and quantitative than might be available from studies 

based on spousal smoking. They consider exposure to ETS both at home and in 

the workplace, using a probability-weighted average of exposure to respirable 

suspended particulates (RSP) in the two environments. Exposure values are 

derived from their basic equilibrium model relating ambient concentration of 

particulates to the number of burning cigarettes per unit volume of air space and 

to the air change rate. From 1982 statistics of lung cancer mortality rates among 

smokers and their own previous estimates of daily tar intake by smokers, the 

authors calculate a lung cancer risk for active smokers of 5.8 × 10-6 LCDs/year 

per mg tar/day per smoker of lung cancer age. The essential assumption linking 

lung cancer risk in passive and active smokers is that inhaled tobacco tar poses 

the same risk to either on a per unit basis. Extrapolation of risk from exposure 

levels for active smokers to values calculated for passive smokers is 

accomplished by assuming that dose-response follows the one-hit model for 

carcinogenesis. An estimated 555 LCDs per year in U.S. nonsmokers (neversmokers and former smokers) are attributed to ETS exposure (for 1980). The 

ratio of total LCDs in 1988 to 1980 is approximately 1.37 (Repace, 1989). With 

that population adjustment factor, the approximate number of LCDs attributable 

to ETS among nonsmokers is closer to 760 for 1988 (including former smokers). 

Method 3 of Robins (NRC, 1986, Appendix D--again, included in the 

NRC report but not specifically endorsed by the committee) extrapolates from 

data on active smoking, along with several assumptions. Applying his results to 

6,500 females and 3,000 males, the range of excess LCDs in never-smokers due 

to ETS is 550 to 2,940 for females and 153 to 1,090 for males. 

6-7 
Russell and coworkers (1986) use data on urinary nicotine concentrations 

in smokers and nonsmokers to estimate exposure and risk from passive smoking. 

The risk of premature death from passive smoking is presumed to be in the same 

ratio to premature death in active smokers as the ratio of concentrations of 

urinary nicotine in passive to active smokers (about 0.007). Calculations are 

made using vital statistics for Great Britain and then extrapolated to the United 

States. The latter estimate, 4,000+ deaths per year due to passive smoking, is for 

all causes of death, not just LCDs. 

Arundel et al. (1987) attributes only five LCDs among female neversmokers to ETS exposure. The corresponding figure for males is seven (both 

figures are adjusted to 6,500 females and 3,000 males). The expected lung 

cancer risk for never-smokers is estimated by downward extrapolation of the 

lung cancer risk per mg of particulate ETS exposure for current smokers. The 

authors' premise is that the lung carcinogenicity of ETS is entirely attributable to 

the particulate phase of ETS, and the consequent risk in passive smoking is 

comparable to active smoking on a per mg basis of particulate ETS retained in 

the lung. If the vapor phase of ETS were also considered, the number of LCDs 

attributable to ETS would likely increase (e.g., see Wells, 1991). 

6.3. THIS REPORT'S ESTIMATES OF LUNG CANCER MORTALITY ATTRIBUTABLE TO ETS IN 

THE UNITED STATES 

6.3.1. Introduction and Background 

This report uses the epidemiologic approach because of the abundance of 

human data from actual environmental exposures. Furthermore, the assumptions 

are fewer and more valid than for the cigarette-equivalents approach. The report 

generally follows the epidemiologic methodology used by the NRC (NRC, 

1986) and others (Section 6.2.1), with three important differences. The first 

difference is that the NRC combined the data on females and males for its 

summary relative risk estimate. This report uses only the data on females 

because there are likely to be true sex-based differences in relative risk due to 

differences in exposure to background ETS and differences in background (i.e., 

non-tobacco-smoke-related) lung cancer risk. Furthermore, the vast majority of 

the data are for females. The second difference is that the NRC combined study 

estimates of relative risk across countries for its summary relative risk estimate; 

this report combines relative risk estimates only within countries, and then bases 

the U.S. population risk assessment on the U.S. estimate only. As discussed in 

Chapter 5, there are apparently true differences in the observed relative risk 

estimates from different countries, which might reflect lifestyle differences, 

differences in background lung cancer rates in females, exposure to other indoor 

air pollutants, and differences in exposure to background levels of ETS. 

Therefore, for the purposes of U.S. population risk assessment, it is appropriate 

to use the U.S. studies; in addition, far more studies are currently available so 

6-8 
there is less need to combine across countries. The third difference is that the 

NRC corrected its overall estimate of relative risk downward for smoker 

misclassification bias. In this report, the individual study estimates are corrected 

for smoker misclassification bias at the outset, i.e., prior to any analysis, using 

the particular parameters appropriate for each separate study (Appendix B). 

The basic NRC model is defined as 

RR(dE) = (1 + Z * $dN)/(1 + $dN) 

where RR(dE) is the relative risk for the group of never-smokers identified as 

"exposed" to spousal ETS (plus background ETS) compared with the group 

identified as "unexposed" (but actually exposed to background ETS); Z is the 

ratio between the operative mean dose level in the exposed group, dE, and the 

mean dose level in the unexposed group, dN; and $ is the amount of increased risk 

per unit dose. The equation is only defined for Z > RR(dE) > 1 (see Section 8.3). 

The method used here is based on several assumptions: (1) that body 

cotinine levels in never-smokers are linearly related to ETS exposure; (2) that 

current ETS exposure is representative of past exposures; and (3) that the excess 

risk of lung cancer in nonsmokers exposed to ETS is linearly related to the dose 

absorbed. 

Estimates of RR(dE) for female never-smokers were derived in Chapter 5, 

where they were corrected for smoker misclassification bias; these are redefined 

in Section 6.3.2 as RR2. The relative risk estimates are then adjusted to be 

applicable to different baseline exposure groups in order to calculate population 

risks for never-smoking women. In order to extend the analyses to female 

former smokers and male never- and former smokers, the relative risks are 

converted to excess or additive risks. The use of additive risks is more 

appropriate for these groups because of the different baseline lung cancer 

mortality rates by sex and smoking status (former vs. never). 

More specifically, estimates of ETS-attributable population mortality are 

calculated from female lung cancer mortality rates, which are themselves derived 

from summary relative risk estimates either from the 11 U.S. studies combined 

(Section 6.3.3) or from the Fontham et al. (1991) study alone (Section 6.3.4), 

along with other parameter estimates from prominent sources (Section 6.3.2). 

The LCMRs in this instance are defined as the number of LCDs in 1985 per 

100,000 of the population at risk. The LCMR in U.S. women under age 35 is 

minuscule, so only persons of age 35 and above are considered at risk. Although 

these LCMRs are expressed as a mortality rate per 100,000 of the population at 

risk, as derived they are applicable only to the entire population at risk and not to 

any fraction thereof that might, for example, have a different average exposure 

or age distribution. 

6-9 
The LCMR for the subpopulation and exposure scenario to which the 

epidemiologic studies apply most directly--never-smoking females exposed to 

spousal ETS--is estimated first. That estimate is then incremented to include 

exposure to nonspousal ETS for all never-smoking females. For the ETSattributable population mortality estimates, these LCMRs are applied to neversmoking males and former smokers at risk, as well as to the females at risk for 

which the rates were specifically derived. The most reliable component of the 

total estimate constructed for the United States is the estimate for the female 

never-smokers exposed to spousal ETS. The other components require 

additional assumptions, which are described. As the number of assumptions 

increases, so does the uncertainty of the estimates. Thus, the total estimate of 

lung cancer risk to U.S. nonsmokers of both sexes is composed of component 

estimates of varying degrees of certainty. 

One might argue that smokers are among those most heavily exposed to 

ETS, since they are in close proximity to sidestream smoke (the main component 

of ETS) from their own cigarettes and are also more likely than never-smokers to 

be exposed to ETS from other smokers. The purpose of this report, however, is 

to address respiratory health risks from ETS exposure in nonsmokers. In current 

smokers, the added risk from passive smoking is relatively insignificant 

compared to the self-inflicted risk from active smoking. 

6.3.2. Parameters and Formulae for Attributable Risk 

Several parameters and formulae are needed to calculate attributable risk. 

These are presented in Table 6-1, with the derivations explained below. 

The size of the target population, in this case the number of women in the 

United States of age 35+ in 1985, is denoted by N, with N = N1 + N2, where N1 = 

the number of ever-smokers and N2 = the number of never-smokers. The total 

number of LCDs from all sources, T, is apportioned into components from four 

attributable sources: (1) non-tobacco-smoke-related causes, the background 

causes that would persist in an environment free of tobacco smoke; (2) 

background ETS, which refers to all ETS exposure other than that from spousal 

smoking; (3) spousal ETS; and (4) ever-smoking. The risk from non-tobaccosmoke-related causes (source 1) is a baseline risk (discussed below) assumed to 

apply equally to the entire target population (never-smokers and ever-smokers 

alike). The ever-smoking component of attributable risk (source 4) refers to the 

incremental risk above the baseline in ever-smokers (this report does not 

partition the incremental risk in ever-smokers further into components due to 

background ETS and spousal ETS, except for long-term [5+ years] former 

smokers). The background ETS component (source 2) is the incremental risk 

above the baseline in all never-smokers from exposure to nonspousal sources of 

ETS. The spousal ETS component (source 3) is the additional incremental risk 

in never-smokers exposed to spousal smoking. 

6-10 
Table 6-1. Definition and estimates of relative risk of lung cancer for 11 U.S. studies combined for various exposure sources and basel

definitions and estimates used to calculate U.S. population-attributable risk estimates for ETS 

DENOMINATOR 

(Baseline) 

NUMERATOR of relative risk 

All persons Never-smokers 

ETS exposure 

Current 

sm

Source of exposure Non-tobacco-smoke 

sources of exposure 

[nt] 

Background ETS 

[nt]+[ETSB] 

Background ETS and

spousal ETS 

[nt]+[ETSB]+[ETSS] 

Activ

[nt]+[E

[nt] 1 RR03 = 1.34 RR02 = 1.591 RR0

[nt]+[ETSB] - - RR2 = 1.192 RR1

[nt]+[ETSB]+[ETSS] - - - RR1 

6-11 

1Basic adjustment for background exposure with Z = 1.75. 2Pooled value from 11 U.S. studies for never-smoking females. 3RR1 = a weighted average of 11.94 for women active smokers (63.4%) and 4.69 for women former smokers

(36.6%) = 9.26.

Definitions and Estimates of Population Parameter Values

N = Total number of women in U.S. (1985) age 35+ = N1 (ever-smokers) + N2 (never-smokers) =

25.7 million + 32.3 million = 58 million. 

P1 = Prevalence (proportion) of female ever smokers age 35+ = 0.443.

P2 = Proportion of NS women exposed to equivalent spousal ETS (plus background ETS) = 0.6.

Z = Ratio of body cotinine levels in (nonsmokers exposed to background ETS plus spousal ETS)

to (nonsmokers exposed to background ETS only) = 1.75.

T = Total LCDs in United States in 1985 among women aged 35+ = 38,000. 
ETS. The spousal ETS component (source 3) is the additional incremental risk 

in never-smokers exposed to spousal smoking. 

The calculational formulae also require values for the parameters P1 

(prevalence of ever-smokers), P2 (proportion of never-smokers exposed to 

spousal smoking), RR1 (average lung cancer risk for ever-smokers relative to the 

average risk for never-smokers in the population), and RR2 (lung cancer risk of 

never-smokers exposed to spousal ETS relative to never-smokers not exposed to 

spousal ETS). Additional parameters (RR11, Z, RR01, RR02, and RR03) are 

introduced or developed below. 

The "baseline" risk is defined as the term in the denominator of a risk 

ratio. For example, in RR1 the baseline risk is the lung cancer risk in a 

population of never-smokers with P2 exposed to spousal ETS and 1 - P2 not 

exposed to spousal ETS. The conversion of RR1 to the same baseline risk as RR2 

(the risk of never-smokers not exposed to spousal ETS but still exposed to nontobacco-smoke-related causes and to background ETS), is given by 

RR11 = RR1(P2RR2 + 1 - P2). 

(6-1) 

To convert relative risks to the baseline risk of lung cancer from non-tobaccosmoke-related causes only (i.e., excluding background ETS in the baseline) 

requires some assumptions. Let RR02 denote the conversion of RR2 to this new 

baseline. It is assumed that: (1) the excess risk of lung cancer from ETS 

exposure is proportional to ETS exposure; and (2) the ratio of ETS exposure 

from spousal smoking plus other sources to exposure from other sources alone, 

denoted by Z, is known and Z > RR2 > 1. (For the values used in this report, this 

relation is true. See also the discussion in Section 8.3.) Under these 

assumptions, RR02 = 1 + $ZdN (from Section 6.3.1), or 

RR02 = (Z - 1)/( Z/RR2 - 1). 

(6-2) 

Determination of a value for Z from data on cotinine concentrations (or 

cotinine/creatinine) is discussed below. The conversion of RR1 to the same zeroETS baseline risk as RR02 follows from multiplying expression (6-1) by 

RR02/RR2, i.e., 

RR01 = RR1(P2RR02 + (1 - P2)RR02/RR2). 

(6-3) 

The terms RR01 and RR02 are the lung cancer risks for ever-smokers and for 

never-smokers exposed to spousal ETS, respectively, relative to the risk for 

6-12 
never-smokers in a zero-ETS environment. The risk of never-smokers not 

exposed to spousal ETS (but exposed to background ETS and nonsmoking 

causes) relative to the zero-ETS baseline risk is 

RR03 = RR02/RR2. (6-4) 

The population-attributable risk of lung cancer in the total population for a 

source (risk factor) is a ratio. The numerators of the ratios for sources of tobacco 

smoke are: 

current/former active smoking in ever-smokers,

P1(RR01 - 1); (6-5)

background ETS plus spousal ETS in never-smokers exposed to

both,

(1 - P1)P2(RR02 - 1); and (6-6)

background ETS in never-smokers not exposed to spousal ETS,

(1 - P1)(1 - P2)(RR02/RR2 - 1). (6-7)

The denominator for each term is their sum plus one, i.e., 

Ex(6-5) + Ex(6-6) + Ex(6-7) + 1 

(6-8) 

where Ex(6-5) refers to expression (6-5), etc. The population-attributable risk 

for remaining causes of lung cancer (non-tobacco-smoke-related background 

causes) is 

1/Ex(6-8). (6-9) 

Multiplying the population-attributable risk for a source by the total 

number of LCDs yields the number of LCDs attributable to that source. An 

alternative and equivalent derivation of the source-attributable LCD estimates 

can be performed by first calculating LCMRs. LCMRs are obtained for each 

source as follows: 

non-tobacco-smoke-related causes: LCMRnt = 105

Ex(6-9)T/N. 

ever-smoking: LCMRnt(RR01 - 1). 

spousal ETS: LCMRnt(RR02 - RR03). 

background ETS: LCMRnt(RR03 - 1). 

Then the number of LCDs attributable to a source is estimated by multiplying 

the LCMR for that source by the total population at risk from that source. 

We now consider parameter values for N, T, P1, P2, RR1, and Z to be used 

with the value 1.19 for RR2, the pooled estimate of RR2 from the 11 U.S. studies 

6-13 
(Table 5-17), for the population risk assessment in Section 6.3.3. The value used 

for RR2 is then changed to 1.28, the estimate from the Fontham et al. (1991) 

study in the United States, and a new value of Z is constructed from the cotinine 

data in that study for the alternative population risk assessment calculations in 

Section 6.3.4. The female population in 1985 of age 18+ years of age is 

approximately 92 million (U.S. DHHS, 1989, Chapter 3). Detailed census data 

by age for 1988 indicate that the proportion of women 35+ years of age in the 

female population of age 18+ is 0.63 (U.S. Bureau of the Census, 1990). 

Applying that proportion to the 1985 population gives approximately 58 million 

women of aged 35+ in 1985, the value used for N. There were approximately 

38,000 female LCDs in the United States in 1985 (U.S. DHHS, 1989), which is 

used as the value for T. 

Using figures from the Bureau of the Census and the 1979/80 National 

Health Interview Survey, Arundel et al. (1987) estimate the number of women of 

age 35+ by smoking status, obtaining a value of 0.443 as the fraction of eversmokers. The National Center for Health Statistics (as reported in U.S. DHHS, 

1989) provides the proportion of the female population by smoking status 

(never, former, current) for 1987. When applied to figures from the Bureau of 

the Census (1990) for the female population by age group available for 1988, the 

same fractional value (0.443) is obtained. These sources suggest that the 

proportion of ever-smokers in the female population has been fairly constant 

between 1980 and 1987, so P1 will be given the value 0.443. Multiplying N by 

P1 gives an estimate of N1 = 25.7 million ever-smokers, leaving N2 = 32.3 million 

never-smokers. 

RR1 applies to ever-smokers, which consist of current and former smokers. 

The relative risks of current and former female smokers of age 35+ for the 

period 1982-1986 are estimated at 11.94 and 4.69, respectively, from data in the 

American Cancer Society's Cancer Prevention Study II (CPS-II; as reported in 

U.S. DHHS, 1989). For 1985, the composition of ever-smokers is 63.4% current 

smokers and 36.6% former smokers (CDC, 1989a). Using those percentages to 

weight the relative risks for ever-smokers and former smokers gives 9.26, which 

will be used as the value of RR1. 

The proportion of never-smokers exposed to spousal ETS in 

epidemiologic studies typically refers to married persons, so we need to consider 

how to treat unmarried persons as well in order to set a value for P2. The 

American Cancer Society's CPS-II (reported in Stellman and Garfinkel, 1986) 

percentages for marital status of all women surveyed (not just never-smokers) 

are: married, 75.3; divorced, 5.1; widowed, 14.6; separated, 0.8; and single, 4.2. 

Our estimates of risk apply to married female never-smokers, which comprise 

about 75% of female never-smokers, so it is necessary to consider exposure to 

ETS in the remaining 25% of unmarried female never-smokers. 

6-14 
Cummings (1990) obtained urinary cotinine levels on a total of 663 selfreported never-smokers and former smokers. The cotinine levels were slightly 

higher in males than in females (9.6 and 8.2 ng/mL, respectively), and slightly 

more than one-half of the subjects were females. The average cotinine level was 

10.7 ng/mL for married subjects if the spouse smoked and 7.6 ng/mL otherwise. 

The average cotinine levels reported by marital status are: married, 8.3 ng/mL; 

never married, 10.3 ng/mL; separated, 11.8 ng/mL; widowed, 10.4 ng/mL; and 

divorced, 9.2 ng/mL. The study, in which 7% of the subjects were of age 18 to 

29, and 47% were of age 60 to 84, does not claim to be representative. 

Nevertheless, the results suggest that in terms of ETS exposure, an unmarried 

never-smoker is probably closer, on average, to a never-smoker married to a 

smoker (an exposed person) than to a never-smoker married to a nonsmoker (an 

unexposed person). This observation is also consistent with the findings of 

Friedman et al. (1983). 

The proportion of never-smoking controls exposed to spousal smoking 

varies among studies in the United States. If we exclude studies of uncertain 

representativeness, the median value for the remaining studies is 0.6. From the 

evidence on ETS exposure to unmarried female never-smokers, it is reasonable 

to assume that their exposure to ETS, on average, is at least as large as the 

average background level plus 60% of the average exposure from spousal 

smoking. For the calculations needed from these figures, this assumption is 

equivalent to treating unmarried and married female never-smokers alike in 

terms of exposure to ETS (i.e., 60% exposed at a level equivalent to spousal 

smoking plus background and 40% exposed at the background level only). 

Consequently, the value P2 = 0.6 is assumed to apply equally to married and 

unmarried female never-smokers. 

The NRC report of 1986 uses Z = 3 for the ratio of ETS exposure from 

spousal smoking plus other sources to ETS exposure from nonspousal sources 

alone. That value was primarily based on data from Wald and Ritchie (1984), 

for men in Great Britain, although Lee (1987b) had reported a value of 3.3 for 

women in Great Britain. The results of Coultas et al. (1987) also were 

considered, wherein a value of 2.35 was observed for saliva cotinine levels in a 

population-based survey of Hispanic subjects in New Mexico. More recent data 

suggest that a lower value of Z may be more accurate for the United States. The 

study of 663 volunteers in Buffalo, New York, reported by Cummings et al. 

(1990), observed a value of 1.55 based on mean urinary cotinine levels among 

married females (n = 225; Cummings, 1990). A study by Wall et al. (1988) 

containing 48 nonsmokers observed a ratio of mean cotinine levels of 1.53. A 

survey of municipal workers at a health fair found a cotinine ratio of 2.48 for the 

112 women surveyed, but the comparison is between women who shared living 

quarters with a smoker and those who did not (Haley et al., 1989). The 10-

country collaborative cotinine study conducted by IARC (Riboli et al., 1990) 

6-15 
collected urinary cotinine samples from nonsmoking women in four groups 

totaling about 100 each--married to a smoker (yes, no) and employed (yes, no)--

including two locations, Los Angeles and New Orleans, in the continental United 

States. The ratios of average cotinine/creatinine concentrations for women 

married to a smoker to women not married to a smoker range from 1.75 to 1.89 

in New Orleans, when the percentage of women employed is assumed to be 

between 25% and 75%. The data from Los Angeles contain an abnormally high 

mean for women who are employed and also married to a smoker (a mean of 

14.6 based on only 13 observations, compared to the other three means for Los 

Angeles of 2.1, 4.5, and 6.6), so only the two means for unemployed women 

(married to a smoker and married to a nonsmoker) were used. The resultant ratio 

of cotinine/creatinine concentrations is 1.45. Data from the Fontham et al. 

(1991) study of lung cancer and ETS exposure in five U.S. cities yield a Z of 2.0 

based on mean urinary cotinine levels in 239 never-smoking women (data 

provided by Dr. Elizabeth Fontham). 

Cotinine data exhibit variability both within and between subjects, as well 

as between studies due to different experimental designs, protocols, and 

geographical locations (see also Chapter 3). Most of the Z values from recent 

U.S. studies range between 1.55 and 2.0. A value of 1.75 for Z appears 

reasonable based on the available U.S. data and will be used in Section 6.3.3 

along with the combined RR estimate from 11 U.S. studies (Chapter 5) to 

calculate ETS-attributable lung cancer mortality estimates. Z = 2.0 and Z = 2.6, 

which are based on median cotinine levels, will be used in Section 6.3.4 for 

alternative calculations of lung cancer mortality based on the results of the 

Fontham et al. (1991) study. The sensitivity of the lung cancer mortality 

estimates to changes in Z and other parameters is discussed in Section 6.3.5. 

6.3.3. U.S. Lung Cancer Mortality Estimates Based on Results of Combined Estimates from 

11 U.S. Studies 

This section calculates ETS-attributable U.S. lung cancer mortality 

estimates based on the combined relative risk estimate (RR2 = 1.19) derived in 

Chapter 5 for the 11 U.S. studies. Alternatively, the estimate from just the 

combined Tier 1 and Tier 2 studies (RR2 = 1.22 from 8 of the 11; see Table 5-17) 

could have been used because these eight studies were assessed as having the 

greater utility in terms of evaluating the lung cancer risks from ETS; however, 

the results would be virtually the same because the relative risk estimates are so 

similar. It was therefore decided to use the data from all the U.S. studies for the 

purposes of the population risk assessment. 

6.3.3.1. U.S. Lung Cancer Mortality Estimates for Female Never-Smokers 

The parameter values presented in Section 6.3.2 are assumed along with 

RR2 = 1.19. For Z = 1.75, RR02 = 1.59 (from expression 6-2, denoted hereafter as 

6-16 
Ex(6-2); see also Table 6-1). Given those parameter values, the formulae in 

Section 6.3.2 yield the estimated lung cancer mortality for U.S. women in 1985 

by smoking status (ever-smoker, never-smoker exposed to spousal ETS, and 

never-smoker not exposed to spousal ETS) and source (non-tobacco-smokerelated causes, background ETS in never-smokers, spousal ETS in neversmokers, and ever-smoking), as displayed in Table 6-2. The LCMR from nontobacco-smoke-related causes (LCMRnt) is estimated to be 9.4 per 100,000 and is 

assumed to apply equally to all persons in the target population, regardless of 

smoking status. The excess LCMR in never-smokers from exposure to 

background ETS is 3.2, with an additional 2.4 if exposed to spousal ETS. The 

excess LCMR in ever-smokers, which includes whatever effect exposure to ETS 

has on ever-smokers as well as the effect from active smoking, is 120.8. 

In rounded figures, 5,470 (14.4%) of the 38,000 LCDs in U.S. women age 

35 and over in 1985 are unrelated to smoking (active or passive). The remaining 

32,530 LCDs (85.6% of the total) are attributable to tobacco smoke: 31,030 in 

25.7 million ever-smokers and 1,500 in 32.3 million never-smokers. These 

1,500 ETS-attributable LCDs in never-smokers account for about one-third of all 

LCDs in female never-smokers. Of the 1,500 LCDs, about 1,030 (69%) are due 

to background ETS, and 470 (31%) are from spousal ETS. In summary, the total 

38,000 LCDs from all causes is due to non-tobacco-smoke-related causes, 5,470 

(14.4%), occurring in ever-smokers and never-smokers; ever-smoking, i.e., the 

effects of past and current active smoking as well as ETS exposure, 31,030 

(81.7%), occurring in ever-smokers; and background ETS, 1,030 (2.7%), and 

spousal ETS, 470 (1.2%), occurring in never-smokers. In other words, eversmoking causes about 81.7% of the lung cancers in women age 35 and over; 

exposure to ETS from all sources accounts for some 3.9%; and causes unrelated 

to tobacco smoke are responsible for the remaining 14.4%. The LCDs in neversmokers attributable to ETS equal about 5% (1,500/31,030) of the total 

attributable to ever-smoking. Part of the mortality attributed to ever-smoking 

here, however, is due to ETS exposure in former smokers, to be taken into 

account in Section 6.3.3.3. 

6.3.3.2. U.S. Lung Cancer Mortality Estimates for Male Never-Smokers 

There are 11 studies worldwide of exposure to ETS and lung cancer in 

males. The studies and their respective relative risks are AKIB, 1.8; BROW, 

2.2; BUFF, 33+ years' exposure, 1.6; CORR, 2.0; HUMB, 4.2; KABA, 1.0; LEE, 

1.3; HIRA(Coh), 2.25; HOLE(Coh), 3.5; plus the data in Kabat (1990), 1.2; and 

Varela (1987, Table 13 scaled down to 50 years of exposure), 1.2. (Data 

6-17 
Table 6-2. Estimated female lung cancer mortality by attributable sources for United States, 1985, using the pooled relative risk estima

Lung cancer mortality2 

(1) (2) (3) (4) (5) 

Smoking status3 Exposed to spousal ETS Number at risk (in millions) Non-tobacco- smoke-related 

causes4 

BackgroundETS 

Spousal ETS Ever-smoki

NS No 12.92 1,220 (3.2) 410 (1.1) 

NS Yes 19.38 1,830 (4.8) 620 (1.6) 470 (1.2) 

ES 25.69 2,420 (6.4) 31,0305 (81

Total 58.00 5,470 (14.4) 1,030 (2.7) 470 (1.2) 31,030 (81.

6-18 

1Percentage of grand total (38,000) in parentheses. 2The nonblank entries in the table are the product of an individual's attributable risk of lung cancer from non-tobaccosmoke-related causes (expression 6-9 (38,000/58,000,000)), the number at risk in column (1), and the following column-specific 

multiples: Col. (2) 1 

Col. (3) RR03 - 1 

Col. (4) RR02 - RR03 

Col. (5) RR01 - 1 3NS = never-smokers; ES = ever-smokers.

4Background sources in the absence of tobacco smoke (i.e., in a zero-ETS environment). 5This figure attributes all lung cancer in ever-smokers above the background non-tobacco-smoke-related rate to ever-smoking. 
for BROW, BUFF, and HUMB were supplied via personal communication from 

Drs. Brownson, Buffler, and Humble.) A weighted average of the passive 

smoking risk (RR2) from these 11 studies is about 1.6. For the seven U.S. 

studies, BROW, BUFF, CORR, HUMB, KABA, Kabat (1990), and Varela 

(1987), the weighted average RR is about 1.4, but this value is heavily weighted 

(about 66%) by the Kabat (1990) and Varela (1987) studies, neither of which 

was used in the analysis of the female data. The combined risk for the five U.S. 

studies not including Kabat (1990) and Varela (1987) is about 1.8, but they are 

all small, low-weight studies. In any case, the observed relative risks for males 

appear to be at least as great as those for females. 

When an attempt is made to correct the observed male risks for smoker 

misclassification, however, using the procedures outlined in Appendix B and the 

community survey-based misclassification factors for males (1.6% for current 

regular smokers, 15% for current occasional smokers, and 5.9% for former 

smokers), it is found that for most of these cohorts, the number of smokers 

misclassified as never-smokers either exceeds the relatively small number of 

observed never-smokers or is so great as to drive the corrected relative risk 

substantially below unity. This implies that the misclassification factors from 

the community surveys are too high to accurately correct the risks in the 

epidemiologic studies. Until better misclassification data on males are available, 

no real sense can be made of the male passive smoking relative risks. 

Given the greater stability of the more extensive database on females, it 

was decided to apply the incremental LCMRs for spousal and nonspousal ETS 

exposure in female never-smokers to male never-smokers. The incremental 

LCMRs were used instead of the relative risk estimates because relative risk 

depends on the background risk of lung cancer (from non-tobacco-related 

causes) as well as the risk from ETS, and background lung cancer risk may differ 

between females and males. From Section 6.3.3.1, the LCMR from spousal ETS 

exposure was 2.4 per 100,000 at risk, and the LCMR from nonspousal ETS 

exposure was 3.2 per 100,000. The 1985 male population age 35 and over is 48 

million (U.S. DHHS, 1989), of whom 27.2% (private communication from Dr. 

Ronald W. Wilson of the U.S. National Center for Health Statistics), or 13.06 

million, were never-smokers. Of these, 24% (Wells, 1988), or 3.13 million, 

were spousally exposed. Applying the female ETS LCMRs, 3.13 million × 

2.4/100,000 = 80 deaths in males from spousal ETS exposure and 13.06 million 

× 3.2/100,000 = 420 deaths from nonspousal exposure, for a total of 500 ETSattributable LCDs among never-smoking males. These estimates based on 

female LCMRs are believed to be conservatively low because males generally 

have higher exposure to background ETS than females. This would lead to 

lower Z values and subsequently higher estimates of deaths attributable to 

background (nonspousal) ETS sources. In conclusion, confidence in these 

6-19 
estimates for male never-smokers is not as high as those for female never-smokers. 

6.3.3.3. U.S. Lung Cancer Mortality Estimates for Long-Term (5+ Years) Former Smokers 

Because the risk of lung cancer from active smoking decreases with the 

number of years since smoking cessation (Section 4.2.2), passive smoking may 

be a significant source of lung cancer risk in long-term former smokers. There 

is, however, a scarcity of data on the relative risks of lung cancer for former 

smokers exposed to ETS. With former smokers, it is unknown how much of the 

observed lung cancer mortality is attributable to non-tobacco-smoke-related 

causes, how much is due to ETS exposure, and how much is accounted for by 

prior smoking. Consequently, neither the observational data on the number of 

lung cancers in the former smokers nor the relative risk data from never-smoking 

females are utilized. Instead, long-term former smokers are assumed to have the 

same LCMR from exposure to ETS as never-smoking females, as was assumed 

above for never-smoking males. In this manner, the lung cancer risk from ETS 

exposure can be calculated as an additional risk, supplemental to any remaining 

risk from previous active smoking. There is some uncertainty in the application 

of this assumption because the additional risk to long-term former smokers from 

ETS exposure may not, in fact, be the same as the risk to never-smokers. For 

example, ETS may have a greater promotional effect on former smokers because 

of their previous exposures to high concentrations of carcinogens from active 

smoking. 

Female ever-smokers comprise about 44.3%, or 25.7 million, of the total 

U.S. female population age 35 and over of 58 million. Long-term (5+ years) 

former smokers comprise about 34% of these ever-smokers (U.S. DHHS, 

1990b), or about 8.7 million women. Using a 2.2 concordance factor for former 

smokers married to ever-smokers versus never-smokers married to neversmokers (see Appendix B), it is estimated that about 77% of the former smokers, 

or about 6.7 million, would be spousally exposed compared with the 60% for the 

never-smokers. Thus, based on the LCMRs derived for female never-smokers, 

the expected number of ETS-attributable LCDs for female long-term former 

smokers would be 6.7 million × 2.40/100,000 = 160 deaths from spousal 

exposure and 8.7 million × 3.20/100,000 = 280 deaths from nonspousal 

exposure, for a total of 440. 

Male ever-smokers comprise 72.8% of the U.S. male population, age 35 

and over, of 48 million, equal to 35 million; of these, about 43% (derived from 

data in U.S. DHHS, 1990b, page 60, Table 5), or about 15 million, are 5+ year 

quitters. Of the never-smoking males, 24% were married to smokers (Section 

6.3.3.2). Again using a 2.2 concordance factor for former smokers, it is 

estimated that 41% of the 15 million former smoking males, or 6.2 million, 

would be married to ever-smokers. Applying the female never-smoker LCMRs 

from Section 6.3.3.1, 6.2 million × 2.40/100,000 = 150 deaths from spousal ETS 

6-20 
exposure and 15 million × 3.20/100,000 = 480 deaths from nonspousal ETS 

exposure for a total of 630 ETS-attributable LCDs among male long-term former 

smokers. 

Table 6-3 displays the resultant estimates for LCDs attributable to 

background ETS and spousal ETS by sex for never-smokers and for former 

smokers who have quit for at least 5 years. The LCMRs for background ETS and 

spousal ETS, assumed to be independent of smoking status and sex, are the same 

as derived in Section 6.3.3.1 for female never-smokers (3.2 and 2.4, 

respectively). Background ETS accounts for about 2,200 (72%) and spousal 

ETS for 860 (28%) of the total due to ETS. Of the 3,060 ETS-attributable 

LCDs, about two-thirds are in females (1,930, 63%) and one-third in males 

(1,130, 37%). More females are estimated to be affected because there are more 

female than male never-smokers. By smoking status, two-thirds are in neversmokers (2,000, 65%) and one-third in former smokers who have quit for at least 

5 years (1,060, 35%). 

The numbers shown in Table 6-3 depend, of course, on the parameter 

values assumed for the calculations. The sensitivity of the totals in Table 6-3 to 

alternative parameter values is addressed in Section 6.3.5. First, however, tables 

equivalent to Tables 6-2 and 6-3 are developed based on the FONT study alone 

for comparison. 

6.3.4. U.S. Lung Cancer Mortality Estimates Based on Results of the Fontham et al. (1991) Study (FONT) 

The estimate of RR2 (1.19), the risk of lung cancer to female neversmokers with spousal ETS exposure relative to the risk for female never-smokers 

without spousal ETS exposure, used in Section 6.3.3, is based on the combined 

outcomes of the 11 U.S. epidemiologic studies from Chapter 5 (see Table 5-17). 

In this section, the quantitative population impact assessment is repeated with 

FONT, the single U.S. study with Tier 1 classification (Section 5.4.4), as the 

source of the estimates of RR2 and Z (constructed from urine cotinine measures), 

with the remaining parameter values left unchanged. While a single study has 

lower power and larger confidence intervals on the relative risk estimate than 

can be obtained by combining the various U.S. studies, using the specific data 

from a single study decreases the uncertainties inherent in combining results 

from studies that are not fully comparable. FONT is the only study of passive smoking and 

lung cancer that collected cotinine measurements, thus providing estimates for RR2 and Z from a single study 

population. The total number of lung cancers attributable to total ETS exposure is 

particularly sensitive to those two parameters (discussed in Section 6.3.5). 

The NCI-funded Fontham et al. study (1991) is a large, well-conducted 

study designed specifically to investigate lung cancer risks from ETS exposure 

(see also the critical review in Appendix A). 

6-21 
Table 6-3. Female and male lung cancer mortality estimates by attributable ETS sources for United States, 1985, using 11 U.S. studies 

former smokers who have quit 5+ years)1 

Lung cancer mortality 

(1) (2) (3) (4) 

Smoking status2 

Sex Exposed to

spousal ETS 

Number at risk 

(in millions) 

BackgroundETS 

SpousalETS 

Total ETS 

NS F No 12.92 410 410 

NS F Yes 19.38 620 470 1,090 NS M No 9.93 320 320 

NS M Yes 3.13 100 80 180 

FS F No 2.0 60 60 

FS F Yes 6.7 210 160 370 

FS M No 8.8 280 280 FS M Yes 6.2 200 150 350 

Total 69.07 2,200 

(71.9) 

860 (28.1) 

3,060 

6-22 

1Percentage of total ETS-attributable lung cancer deaths (3,060) in parentheses. 2NS = never-smokers; FS = former smokers who have quit 5+ years ago. 
It addresses some of the methodological issues that have been of concern in the 

interpretation of results regarding lung cancer and passive smoking: smoker 

misclassification, use of surrogate respondents, potential recall bias, 

histopathology of the lung tumors, and possible confounding by other factors 

(see also Sections 5.3, 5.4.2, and 5.4.3). Cases and controls were drawn from 

five major cities across the United States (Atlanta, New Orleans, Houston, Los 

Angeles, and San Francisco) and, hence, should be fairly representative of the 

general U.S. population, at least of urban areas with moderate climates. 

Furthermore, the results of the study are consistent across the five cities. 

In spite of the care incorporated into the FONT design to avoid smoker 

misclassification bias, some might still exist; thus, the adjusted relative risk of 

1.29 reported in FONT is "corrected" slightly to 1.28 in this report. The 

parameter P2, the proportion of never-smokers exposed to spousal ETS, was 

assigned the value 0.60 in the preceding section. In FONT, the observed 

proportion of spousal-exposed controls is 0.60 (0.66) for spousal use of 

cigarettes only (any type of tobacco) among colon-cancer controls and 0.56 

(0.63) in population controls. Consequently, the previous value of 0.60 is 

retained. Of the 669 FONT population controls, whose current cotinine levels 

are considered the most representative of typical ETS exposure, there were 59 

living with a current smoker and 239 whose spouses never smoked. (The other 

371 were nonsmoking women who either no longer lived with a smoking spouse 

or whose spouse was a former smoker.) The mean cotinine level for neversmoking women with spouses who are current smokers (n = 59) is 15.90 ± 

16.46; the mean level for the other 239 was 7.97 (± 11.03). The ratio is 

15.90/7.97, giving Z = 2.0 (data provided by Dr. Elizabeth Fontham). The 

median is a measure of central tendency that is less sensitive to extremes, so the 

ratio of median cotinine levels is also considered (Z = 11.4/4.4 = 2.6). Results for 

both values of Z are displayed in Tables 6-4 and 6-5, which correspond to Tables 

6-2 and 6-3, respectively, of the previous sections for direct comparison. 

The results of Section 6.3.2 are based on RR2 = 1.19 (combined U.S. study 

results) and Z = 1.75 (from studies on cotinine levels). In this section, RR2 and 

Z are both increased (RR2 to 1.28 and Z to 2.0 and 2.6). Correcting RR2 = 1.28 

for background ETS exposure yields estimates of RR02 = 1.78 (i.e., the relative 

risk from spousal and background ETS) for Z = 2.0, and RR02 = 1.55 for Z = 2.6. 

The relative risk estimate from exposure to background ETS only becomes 

RR03 = 1.39 for Z = 2.0, and RR03 = 1.21 for Z = 2.6. The change in RR2, from 

1.19 to 1.28, increases the estimated number of LCDs from background and 

spousal ETS, whereas increasing Z decreases the figure for background ETS and 

has no effect on the number for spousal ETS (see Tables 6-2 and 6-4). Relative 

to the total ETS-attributable LCD estimate in the last section (3,060), the net 

effect is an increase of 12% to 3,570 at Z = 2.0, and a decrease of 13% to 2,670 

when Z = 2.6. 

6-23 
Table 6-4. Female lung cancer mortality estimates by attributable sources for United States, 1985, using both the relative risk estimate

Fontham et al. (1991) study1 

Lung cancer mortality2 

(1) (2) (3) (4) (5) 

Smoking status3 Exposed to spousal ETS Number at risk 

(in millions) 

Non-tobaccosmoke-related causes4 

BackgroundETS 

SpousalETS 

Ever-smokin

NS No 12.92 1,120 (2.9)

1,280 (3.4) 

440 (1.2)270 (0.7) 

NS Yes 19.38 1,680 (4.4) 1,920 

(5.1) 

660 (1.7) 410 (1.1) 

660 (1.7)660 (1.7) 

ES 25.69 2,230 (5.9)

2,550 (6.7) 

31,2205 (82.

30,9005 (81.

Total 58.00 5,030 (13.2)

5,760 (15.2) 

1,100 (2.9)

680 (1.8) 

660 (1.7)660 (1.7) 

31,220 (82.230,900 (81.3

6-24 

1Percentage of grand total (38,000) in parentheses. Calculations using Z = 2.0 (ratio of mean cotinine levels) are shown in regular 

typeface. Outcomes using Z = 2.6 (ratio of median cotinine levels) are shown in italics. 2See Table 6-2 for formulae for table entries. 

3NS = never-smokers; ES = ever-smokers. 4Baseline lung cancer mortality in the absence of tobacco smoke (i.e., in a zero-ETS environment). 5This figure attributes all lung cancer in ever-smokers above the non-tobacco-smoke-related rate to active smoking. 
Table 6-5. Female and male lung cancer mortality estimates by attributable ETS sources for United States, 1985, using the Fontham et 

smokers and former smokers who have quit 5+ years)1,2 

Lung cancer mortality 

(1) (2) (3) (4

Smokingstatus3 

Sex Exposed to

spousal ETS 

Number at 

risk (in millions) 

BackgroundETS 

SpousalETS 

ToET

NS F No 12.92 440 

270 

NS F Yes 19.38 660 

410 660 660 1

1,

6-25 

NS M No 9.93 340 

210 

NS M Yes 3.13 110 

70 

110 110 

FS F No 2.0 70 

40 

FS F Yes 6.7 230 230 

140 230 

FS 

FS 

M No 8.8 300 

190 

M Yes 6.2 210 210 

130 210 

Total 69.07 2,360 (66.1) 1,210 (33.9)

1,460 (54.7) 1,210 (45.3) 

3,52,6

1Calculations using Z = 2.0 (ratio of mean cotinine levels) are shown in regular typeface. Outcomes using Z = 2.6 (ratio of median cotinine levels) are shown in italics. 2Percentage of total ETS-attributable lung cancer deaths (3,570; 2,670) in parentheses. 3NS = never-smokers; FS = former smokers who have quit 5+ years ago. 
(FONT is the largest study and therefore the dominant influence in the combined 

relative risk from the 11 U.S. studies [RR2 = 1.19], so the outcomes being 

compared here with those in Section 6.3.3 are not independent. Similarly, the Zvalue of 1.75 used with RR2 = 1.19 in the first analysis is subjectively based on 

the outcomes of several U.S. cotinine studies, including the FONT cotinine 

results.) Overall, these two analyses support an estimate in the neighborhood of 

3,000 total lung cancer deaths in never-smokers and former smokers (quitters of 

5+ years) from exposure to ETS in the United States for 1985. 

The 3,000 figure is a composite value from estimates of varying degrees of 

uncertainty. The confidence for the female never-smoker estimates is highest. 

The lung cancer estimates for never-smoking females from exposure to spousal 

ETS (470 to 660; from Tables 6-2 and 6-4) are based on the direct evidence from 

epidemiologic studies and require the fewest assumptions. Adding in a figure 

for exposure to background ETS in never-smoking females (680 to 1,100) is 

subject to the assumptions and other uncertainties attached to the estimate of the 

parameter Z. The relative risk from ETS exposure, which depends on the risk 

from background sources of lung cancer as well as the risk from ETS, may differ 

in females and males. Consequently, the absolute risk (LCMR) in neversmoking females was assumed to apply to never-smoking males, adding 

390 to 560 to the total (80 to 110 for spousal ETS and 280 to 450 for background 

ETS; Tables 6-3 and 6-5). Males, however, are thought to have higher 

background exposures to ETS than females, so this assumption is likely to 

underestimate the ETS-attributable lung cancer mortality in males. 

The confidence in the estimates for former smokers is less than in those 

for never-smokers. These estimates also are probably low because they assume 

that ETS-attributable rates in never-smokers and former smokers are the same. 

Figures for lung cancer mortality from ETS in former smokers, for the same 

categories as never-smokers (i.e., females and males, background and spousal 

ETS), account for an additional 940 to 1,250 (totals of 310 to 440 for spousal 

ETS and 500 to 810 for background ETS, for both sexes). These figures for 

former smokers are summed from appropriate entries in Tables 6-3 and 6-5 

(Tables 6-2 and 6-4 do not make them explicit; they are accounted for in the 

entry for lung cancer attributable to ever-smoking). 

Finally, there is statistical uncertainty in each of the LCD estimates 

resulting from sampling variations around all of the parameter estimates that 

were used in the calculations. It is already apparent that the estimate of total 

lung cancer mortality attributable to ETS is sensitive to the values of Z and RR2. 

Uncertainties associated with the parameter values assumed and the sensitivity 

of the estimated total ETS-attributable LCDs to various parameter values are 

examined next. 

6-26 
6.3.5. Sensitivity to Parameter Values 

The estimates for ETS-attributable lung cancer mortality are clearly 

sensitive to the studies, methodology, and choice of models used, and previous 

methodologies have been presented in Section 6.2. Even for this current model, 

however, estimates will vary with different input values. Specifically, the 

estimates depend on the parameter values assumed for the total number of lung 

cancer deaths from all sources (T), the population size (N), the proportion of 

ever-smokers in the population (P1), the proportion of never-smokers exposed to 

spousal ETS (P2), the risk of ever-smokers relative to never-smokers (RR1), the 

risk of never-smokers exposed to spousal ETS relative to unexposed neversmokers (RR2), and the ratio of ETS exposure from spousal smoking and 

background (i.e., nonspousal) sources to background sources alone (Z). 

The effects of changing several of the parameters is readily discernible. A 

change in T/N produces a proportional change in the same direction for all 

estimates of attributable mortality. A change in P1 creates a proportional change 

in the same direction in all mortality figures for ever-smokers and a change in 

the opposite direction proportional to 1 - P1 in all estimates for never-smokers. 

The parameter values assumed for these three parameters are from the sources 

described in the preceding text and are assumed to be acceptably accurate. The 

value of P2 is assumed to be 0.6, but values between 0.5 and 0.7 are easily 

credible. At either of those extremes, there is a 17% change in the lung cancer 

mortality due to spousal smoking, which only amounts to 80 for the first analysis 

(Table 6-2) and 100 for the second one (Table 6-4). The impact of changing 

RR1, RR2, or Z on the total lung cancer mortality attributable to ETS from the 

first analysis is displayed in Table 6-6 for RR1 from 8 to 11, for RR2 between 

1.04 and 1.35 (extremes of the 90% confidence intervals for the 11 U.S. studies; 

Table 5-17), and for Z in the range 1.5 to 3.0. 

For RR1 in the interval (8,11), the total lung cancer mortality from ETS 

ranges from about 2,600 to 3,500, a 14% change in either direction relative to the 

comparison total of 3,060. The extremes are much greater over the range of 

values considered for RR2 (1.04 to 1.35). At the low end, where the excess 

relative risk from spousal ETS is only 4%, there is a 77% decrease in the total 

lung cancer mortality to 700. The percentage change is roughly equivalent in the 

opposite direction when the excess relative risk is at the maximum value 35%, 

for a total of 5,190. The total is also highly sensitive to the value of Z. A 

decrease of only 0.25 from the comparison value of Z = 1.75 increases the total 

by 36% to 4,160. A 36% decrease in ETS-attributable mortality occurs at Z = 

2.5, leaving a corresponding estimate of 1,950. At Z = 3.0, the total drops 

further to 1,680, a 45% decrease. 

6-27 
Table 6-6. Effect of single parameter changes on lung cancer mortality due to ETS

in never-smokers and former smokers who have quit 5+ years 

LCM due to ETS 

Parameter 

change 

Background1 Spousal2 Total Percentage of

change3 

None4 2,210 850 3,060 0 

Z = 1.50 

1.75 

2.00 

2.25 

2.50 

2.75 

3.00 

RR2 = 1.04 

1.05 

1.10 

1.15 

1.19 

1.20 

1.25 

1.30 

1.35 

RR1 = 8.00 

8.50 

9.00 

9.26 

9.50 

10.00 

10.50 

11.00 

3,310 

2,210 

1,660 

1,320 

1,100 

950 

830 

510 

630 

1,220 

1,780 

2,210 

2,310 

2,820 

3,290 

3,750 

2,510 

2,380 

2,260 

2,210 

2,160 

2,060 

2,020 

1,890 

850 4,160 

850 3,060 

850 2,510 

850 2,170 

850 1,950 

850 1,800 

850 1,680 

190 700 

240 870 

470 1,690 

690 2,470 

850 3,060 

890 3,200 

1,080 3,900 

1,270 4,560 

1,440 5,190 

970 3,480 

920 3,300 

870 3,130 

850 3,060 

830 2,990 

800 2,860 

780 2,800 

730 2,620 

+36 

0 

-18 

-29 

-36 

-41 

-45 

-77 

-72 

-45 

-19 

0 

+5 

+27 

+49 

+70 

+14 

+8 

+3 

0 

-2 

-7 

-9 

-14 

1

69,100,000 at risk.

2

35,400,000 at risk.

3

Percentage of change from total shown in boldface (the outcome from Tables 6-

2 and 6-3, 

using the 11 U.S. studies).

4

Z = 1.75, RR2 = 1.19, RR1 = 9.26. 

6-28 
Varying more than one parameter value simultaneously may have a 

compounding or canceling effect on the total lung cancer mortality due to ETS. 

For example, at the following values of RR2, the range of percentage changes 

from the total of 3,060 ETS-attributable lung cancer deaths for values of Z in the 

interval 1.50 to 3.0 are shown in parentheses: RR2 = 1.04 

(-69%, -88%), RR2 = 1.15 (+10%, -56%), RR2 = 1.25 (+73%, -30%), and RR2 = 

1.35 (+131%, -7%). The total ETS-attributable LCD estimates range from 380 

(at RR2 = 1.04, Z = 3.0) to 7,060 (at RR2 = 1.35, Z = 1.5). Without considering 

the additional variability that other parameters might add, it is apparent that the 

estimated lung cancer mortality from ETS is very sensitive to the parameters RR2 

and Z and that the uncertainty in these parameters alone leaves a fairly wide 

range of possibilities for the true population risk. 

While various extreme values of these parameters can lead to the large 

range of estimates noted, the extremities of this range are less likely possibilities 

for the true population risk because the parameters RR2 and Z are not actually 

independent and would be expected to co-vary in the same direction, not in the 

opposite direction as expressed by the extreme values. For example, if the 

contributions of background to total ETS exposure decrease, Z would increase, 

and the observable relative risk from spousal exposure, RR2, would be expected 

to increase as well. In addition, most of the evidence presented in this report 

suggests that a narrower range of both RR2 and Z are appropriate. Thus, while 

substantially higher or lower values are conceivable, this report concludes that 

the estimate of approximately 3,000 ETS-attributable LCDs based on the 11 U.S. 

studies is a reasonable one. Furthermore, this estimate is well corroborated by 

the estimates of 2,700 and 3,600 calculated by analyzing the FONT data alone, 

the only study dataset from which estimates of both RR2 and Z are obtainable. 

6.4. SUMMARY AND CONCLUSIONS ON POPULATION RISK 

Having concluded in the previous chapter that ETS is causally associated 

with lung cancer in humans and belongs in EPA Group A of known human 

carcinogens, this chapter assesses the magnitude of that health impact in the U.S. 

population. The ubiquity of ETS in a typical individual's living environment 

results in the respiratory uptake of tobacco smoke to some degree in a very high 

percentage of the adult population, conservatively upwards of 75% based on the 

outcome of urinary cotinine/creatinine studies in nonsmokers. Compared with 

observations on active smokers, body cotinine levels in nonsmokers are low, on 

the order of a few percent, and there is considerable variability in interindividual 

metabolism of nicotine to cotinine. Some authors have used the relative cotinine 

levels in active and passive smokers to estimate the probability of lung cancer in 

nonsmokers by extrapolating downward on a dose-response curve for active 

smokers. This "cigarette-equivalents" approach requires several assumptions, 

e.g., that the dose-response curve used for active smokers is reasonably accurate 

6-29 
and low-dose extrapolation of risk for active smokers is credible, that cotinine is 

proportional (and hence a substitute for) whatever is used for "dose" in the doseresponse curve, and that the risk calculated in this way applies equally to active 

and passive smokers with equivalent cotinine measures. The effect of 

differences in physico-chemical properties of mainstream smoke and sidestream 

smoke (the principal component of ETS), in lung dosimetry between active and 

passive smoking, and in exposure patterns (related to concentration and duration 

of exposure) are not fully understood, but the current state of knowledge casts 

doubts on the validity of these assumptions. 

The remaining approach to population risk extrapolates to the general 

population from the epidemiologic evidence of increased relative risk of lung 

cancer in never-smoking women married to smokers. To extrapolate exposure 

and consequent risk to other sources of ETS exposure, cotinine levels of neversmokers exposed to spousal ETS are compared with those of never-smokers 

exposed only to other sources of ETS (background), and it is assumed that 

excess risks of lung cancer from ETS exposures, using cotinine levels as a 

surrogate measure, are proportional to current ETS exposure levels. (Here, 

cotinine levels are used to gauge relative levels of ETS exposure, not to 

extrapolate between active and passive smoking as in the "cigarette-equivalents" 

approach.) The use of current cotinine data to estimate ETS exposure in 

nonsmokers seems reasonable because cotinine levels correlate quite well with 

questionnaire response on ETS exposure. However, the total estimate of 

population risk is sensitive to uncertainty in making these assumptions and 

variability in the use of cotinine measures. 

This report uses the modeling approach based on direct ETS 

epidemiologic evidence because the assumptions are fewer and more valid than 

for the "cigarette-equivalents" approach, and the abundance of human data from 

actual environmental exposures makes this preferred approach feasible. The 

total number of lung cancer deaths in U.S. females from all causes is partitioned 

into components attributable to non-tobacco-smoke-related causes (background 

causes unrelated to active or passive smoking), background ETS (also called 

nonspousal ETS), spousal ETS, and ever-smoking. Two sets of calculations are 

made for the U.S. female population age 35 and over in 1985 based on parameter 

values from national statistics and estimates from the epidemiologic studies on 

ETS and lung cancer. They differ in the values assumed for two parameters in 

the formulae for attributable risk: RR2, the relative risk of lung cancer for neversmokers exposed to spousal smoke, and Z, the ratio of cotinine concentrations in 

never-smokers exposed to spousal ETS to those exposed to background ETS 

only. The first analysis uses the pooled estimate of RR2 from the 11 U.S. studies 

from Chapter 5, and a subjective value of Z based on the outcomes of 

independent U.S. cotinine studies (RR2 = 1.19 and Z = 1.75). The second 

analysis uses the estimates of RR2 and Z from the large, high-quality Fontham et 

6-30 
al. study (1991), the sole U.S. study that collected cotinine data for its study 

population (RR2 = 1.28 with mean Z = 2.0 and with median Z = 2.6). 

The estimated lung cancer mortality in never-smoking women from ETS 

(background and spousal ETS) is 1,500 in the first analysis and 1,760 (1,340) in 

the second analysis for Z = 2.0 (2.6). When estimates for never-smoking males 

and former smokers (5+ year quitters) of both sexes are added, the corresponding 

totals are 3,060 and 3,570 (2,670). All of these figures are based on calculations 

in which unknown parameter values are replaced with numerical estimates that 

are subject to uncertainty, and departures in either direction cannot be precluded 

as unrealistic possibilities for the correct population risks. Nonetheless, because 

of the large database utilized and the extensive analysis performed, there is a 

high degree of confidence in the estimates derived for female never-smokers. 

The figures for male never-smokers and former smokers of both sexes are 

subject to more uncertainty because more assumptions were necessary for 

extrapolation from the epidemiologic results. The estimates for male neversmokers, in particular, may be on the low side because males generally are 

exposed to higher levels of background ETS than females. In summary, our 

analyses support a total of approximately 3,000 as an estimate for the annual 

U.S. lung cancer deaths in nonsmokers attributable to ETS exposure. 

A quantitative estimate of the variance associated with the 3,000 estimate 

is not possible without many assumptions, both about the model and the 

accuracy of the parameters used to derive the population estimates. As exhibited 

in Table 6-6, we believe the largest variability to be associated with RR2 and Z. 

Based on the statistical variations, estimates as low as 400 and as high as 7,000 

are possible. However, where specific assumptions were made, we believe that 

they are generally conservative, and we expect that the actual number may be 

greater than 3,000. 

A feature of variability not addressed in the range presented above is the 

correlation between RR2 and Z. The greater the correlation, the smaller will be 

the expected variance of RR02, resulting in a narrower range of lung cancer 

estimates. Because only one lung cancer study, FONT, allows RR2 and Z to be 

jointly estimated, no assessment of this correlation is possible. However, the 

two point estimates derived from the FONT data--2,700 and 3,600--provide 

additional reassurance in the 3,000 estimate. 

In conclusion, despite some unavoidable uncertainties, we believe these 

estimates of ETS-attributable lung cancer mortality to be fairly reliable, if not 

conservatively low, especially with respect to the male nonsmoker component. 

First, the weight of evidence that ETS is a human lung carcinogen is very strong. 

Second, the estimates are based on a large amount of data from various studies 

of human exposures to actual environmental levels of ETS. They do not suffer 

from a need to extrapolate from an animal species to humans or from high to low 

exposures, as is nearly always the case in environmental quantitative health risk 

6-31 
assessment. Thus, the confidence in these estimates is judged to be medium to 

high. In summary, the evidence demonstrates that ETS has a very substantial 

and serious public health impact. 

6-32
7. PASSIVE SMOKING AND RESPIRATORY DISORDERS OTHER THAN CANCER 

7.1. INTRODUCTION 

In 1984, a report of the Surgeon General identified cigarette smoking as 

the major cause of chronic obstructive lung disease in the United States (U.S. 

DHHS, 1984). The same report stated that there is conclusive evidence showing 

that smokers are at increased risk of developing respiratory symptoms such as 

chronic cough, chronic phlegm production, and wheezing (U.S. DHHS, 1984). 

More recently, longitudinal studies have demonstrated accelerated decline in 

lung function in smoking adults (Camilli et al., 1987). In children and 

adolescents who have recently taken up smoking, several cross-sectional studies 

have found statistically significant increases in the prevalence of respiratory 

symptoms (cough, phlegm production, and dyspnea [i.e., shortness of breath]) 

(Seely et al., 1971; Bewley et al., 1973). Longitudinal studies also have 

demonstrated that, among young teenagers, functional impairment attributable to 

smoking may be found after as little as 1 year of smoking 10 or more cigarettes 

per week (Woolcock et al., 1984). 

From a pathophysiologic point of view, smoking is associated with 

significant structural changes in both the airways and the pulmonary parenchyma 

(U.S. DHHS, 1984). These changes include hypertrophy and hyperplasia of the 

upper airway mucus glands, leading to an increase in mucus production, with an 

accompanying increased prevalence of cough and phlegm. Chronic 

inflammation of the smaller airways leads to bronchial obstruction. However, 

airway narrowing also may be due to the destruction of the alveolar walls and 

the consequent decrease in lung elasticity and development of centrilobular 

emphysema (Bellofiore et al., 1989). Smoking also may increase mucosal 

permeability to allergens. This may result in increased total and specific IgE 

levels (Zetterstrom et al., 1981) and increased blood eosinophil counts (Halonen 

et al., 1982). 

The ascertained consequences of active smoking on respiratory health, and 

the fact that significant effects have been observed at relatively low-dose 

exposures, lead to an examination for similar effects with environmental tobacco 

smoke (ETS). Unlike active smoking, involuntary exposure to ETS (or "passive 

smoking") affects individuals of all ages, particularly infants and children. An 

extensive analysis of respiratory effects of ETS in children suggests that the lung 

of the young child may be particularly susceptible to environmental insults 

(NRC, 1986). Exposures in early periods of life during which the lung is 

undergoing significant growth and remodeling may alter the pattern of lung 

development and increase the risk for both acute and chronic respiratory 

illnesses. 

Acute respiratory illnesses are one of the leading causes of morbidity and 

mortality during infancy and childhood. One-third of all infants have at least 

7-1 
one lower respiratory tract illness (bronchitis, bronchiolitis, croup, or 

pneumonia) during the first year of life (Wright et al., 1989), whereas 

approximately one-fourth have these same illnesses during the second and third 

years of life (Gwinn et al., 1991). The high incidence of these potentially severe 

illnesses has an important consequence from a public health viewpoint: Even 

small increases in risk due to passive exposure to ETS would considerably 

increase the absolute number of cases in the first 3 years of life (see Chapter 8). 

In addition, several studies have shown that lower respiratory tract illnesses 

occurring early in life are associated with a significantly higher prevalence of 

asthma and other chronic respiratory diseases and with lower levels of 

respiratory function later in life (reviewed extensively by Samet and 

collaborators [1983]). 

This chapter reviews and analyzes epidemiologic studies of noncancer 

respiratory system effects of passive smoking, starting with possible biological 

mechanisms (Section 7.2). The evidence indicating a relationship between 

exposure to ETS during childhood and acute respiratory illnesses (Section 7.3), 

middle ear diseases (Section 7.4), chronic respiratory symptoms (Section 7.5), 

asthma (Section 7.6), sudden infant death syndrome (Section 7.7), and lung 

function impairment (Section 7.8) is evaluated. Passive smoking as a risk factor 

for noncancer respiratory illnesses and lower lung function in adults also is 

analyzed (Section 7.9). A health hazard assessment and population impact is 

presented in the next chapter. 

7.2. BIOLOGICAL MECHANISMS 

7.2.1. Plausibility 

It is plausible that passive smoking may produce effects similar to those 

known to be elicited by active smoking. However, several differences both 

between active and passive forms of exposure and among the individuals 

exposed to them need to be considered. 

The concentration of smoke components inhaled by subjects exposed to 

ETS is small compared with that from active smoking. Therefore, effect will be 

highly dependent on the nature of the dose-response curve (NRC, 1986). It is 

likely that there is a distribution of susceptibility to the effects of ETS that may 

depend on, among other factors, age, gender, genetic predisposition, respiratory 

history, and concomitant exposure to other risk factors for the particular outcome 

being studied. The ability to ascertain responses to very low concentrations also 

depends on the reliability and sensitivity of the instruments utilized. 

Breathing patterns for the inhalation of mainstream smoke (MS) and ETS 

differ considerably; active smokers inhale intensely and intermittently and 

usually hold their breath for some time at the end of inspiration. This increases 

the amount of smoke components that are deposited and absorbed (U.S. DHHS, 

1986). Passive smokers inhale with tidal breaths and continuously. Therefore, 

7-2 
patterns of particle deposition and gas diffusion and absorption differ 

considerably for these two types of inhalation. 

There are also important differences in the physicochemical properties of 

ETS and MS (see Chapter 3). These have been extensively reviewed earlier by 

the National Research Council (NRC, 1986) and the Surgeon General (U.S. 

DHHS, 1986). ETS is a combination of exhaled MS, sidestream smoke (that is, 

the aerosol that is emitted from the burning cone between puffs), smoke emitted 

from the burning side of the cigarette during puffs, and gases that diffuse 

through the cigarette paper into the environment. This mixture may be modified 

by reactions that occur in the air before involuntary inhalation. This "aging" 

process includes volatilization of nicotine, which is present in the particulate 

phase in MS but is almost exclusively a component of the vapor phase of ETS. 

Aging of ETS also entails a decrease in the mean diameter of its particles from 

0.32 :m to 0.1-0.14 :m, compared to a mean particle diameter for MS of 0.4 :m 

(NRC, 1986). 

Individual and socioeconomic susceptibility may be important 

determinants of possible effects of ETS on respiratory health. A self-selection 

process almost certainly occurs among subjects who experiment with cigarettes, 

whereby those more susceptible to the irritant or sensitizing effects of tobacco 

smoke either never start or quit smoking (the so-called "healthy smoker" effect). 

Infants, children, and nonsmoking adults thus may include a disproportionate 

number of susceptible subjects when compared with smoking adults. In 

addition, recent studies clearly have shown that, as incidence and prevalence of 

cigarette smoking has decreased, the socioeconomic characteristics of smokers 

also have changed. Among smokers, the proportion of subjects of lower 

educational level has increased in the past 20 years (Pierce et al., 1989). The 

female-to-male ratio also has increased (Fiore et al., 1989), and this is 

particularly true for young, poor women, in whom incidence and prevalence of 

smoking has increased (Williamson et al., 1989). It is thus possible that 

exposure to ETS may be most prevalent today among precisely those infants and 

children who are known to be at a high risk of developing respiratory illnesses 

early in life. 

7.2.2. Effects of Exposure In Utero and During the First Months of Life 

A factor that may significantly modify the effect of passive smoking 

(particularly in children) is exposure to tobacco smoke components by the fetus 

during pregnancy. This type of exposure differs considerably from passive 

smoking; in fact, the fetus (including its lungs) is exposed to components of 

tobacco smoke that are absorbed by the mother and that cross the placental 

barrier, whereas passive smoking directly affects the bronchial mucosa and the 

alveolus. It is difficult to distinguish between the possible effects of smoking 

7-3 
during pregnancy and those of ETS exposure after birth. Some women may quit 

smoking during pregnancy, only to resume after pregnancy is over. Most 

mothers who smoke during pregnancy continue smoking after the birth of their 

child (Wright et al., 1991), and among those who stop smoking after birth, the 

influence on that decision of events occurring shortly after birth (such as 

respiratory illnesses in their child) cannot be excluded. Recall bias also may 

influence the results of retrospective studies claiming differential effects on lung 

function of prenatal and postnatal maternal smoking habits (Yarnell and St. 

Leger, 1979). 

To attempt to circumvent these problems, researchers have studied infant 

lung function shortly after birth (the youngest group of infants reported was 2 

weeks old [Neddenriep et al., 1990]), with the implication that subsequent 

changes encountered could be attributed mainly to ETS exposure. However, the 

possibility that even brief exposure to ETS may affect the lungs at a highly 

susceptible age may not be discarded. Maternal smoking during pregnancy 

needs to be considered, therefore, as a potential modifier of the effect of passive 

smoking on respiratory health, particularly in children. 

Exposure to compounds present in tobacco smoke may affect the fetal and 

neonatal lung and alter lung structure much like these same compounds do in 

smoking adults. Neddenriep and coworkers (1990) studied 31 newborns and 

reported that those whose mothers smoked during pregnancy had significant 

increases in specific lung compliance (i.e., lung compliance/lung volume) at 2 

weeks of age when compared with infants of nonsmoking mothers. The authors 

concluded that exposure to tobacco products detrimentally affects the elastic 

properties of the fetal lung. Although these effects also could be attributed to 

postnatal exposure to ETS, it is unlikely that such a brief period of postnatal 

exposure would be responsible for these changes affecting the lung parenchyma 

(U.S. DHHS, 1986). 

There is evidence for similar effects of prenatal lung development in 

animal models. Collins and associates (1985) exposed pregnant rats to MS 

during day 5 to day 20 of gestation. They found that pups of exposed rats 

showed reduced lung volume, reduced number of lung saccules, and reduced 

length of elastin fibers in the lung interstitium. This apparently resulted in a 

decrease in lung elasticity: For the same inflation pressure, pups of exposed 

mothers had significantly higher weight-corrected lung volumes than did pups of 

unexposed mothers. Vidic and coworkers (1989) exposed female rats for 6 

months (including mating and gestation) to MS. They found that lungs of their 

15-day-old pups had less parenchymal tissue, less extracellular matrix, less 

collagen, and less elastin than found in lungs of control animals. This may 

explain the increased lung compliance observed by Collins et al. (1985) in pups 

exposed to tobacco smoke products in utero. 

7-4 
Hanrahan and coworkers (1990) reported that infants born to smoking 

mothers had significantly reduced levels of forced expiratory flows. The 

researchers studied 80 mother/child pairs and found significant correlations 

between the cotinine/creatinine ratio in urine specimens obtained during 

pregnancy in the mother and maximal expiratory flows and tidal volumes at a 

postconceptional age of 50 weeks or younger in their children. The investigators 

concluded that exposure due to prenatal smoking diminishes infant pulmonary 

function at birth and, by inference, airway size. These authors also measured 

maximal flows during tidal breathing in their subjects. At rather low lung 

volumes, such as those present during tidal breathing, airway size and maximal 

flows are both a function of lung elasticity. These results thus may be due to 

both a specific alteration of the infant's airways and an increased lung 

compliance in infants whose lungs are small relative to the infant's length. 

It also has been suggested that the increased IgE levels observed in adult 

smokers also may be present in fetuses whose mothers smoke during pregnancy. 

Magnusson (1986) reported that cord serum levels of IgE and IgD were 

significantly higher for neonates whose mothers smoked during pregnancy, 

particularly if the neonates had no parental history of allergic disorders. Cord 

serum levels of IgD (but not of IgE) were increased for neonates whose fathers 

smoked, and this effect was independent of maternal smoking. A more recent 

study on a larger sample (more than 1,000 neonates) failed to find any 

significant difference in cord serum IgE levels between infants (N = 193) of 

mothers who smoked during pregnancy and those (N = 881) of mothers who did 

not (Halonen et al., 1991). 

It also has been reported recently that the pulmonary neuroendocrine 

system may be altered in infants whose mothers smoke during pregnancy. The 

pulmonary neuroendocrine system, located in the tracheobronchial tree, consists 

of specialized cells (isolated or in clusters called "neuroepithelial bodies") that 

are closely related to nerves. In humans, these cells increase in number 

significantly during intrauterine development, reach a maximum around birth, 

and then rapidly decline during the first 2 years of life. Their function is not 

well understood, but the presence of potent growth factors and 

bronchoconstrictive substances in their granules suggests that they play an 

important role in growth regulation and airway tone control during this period of 

lung development (Stahlman and Gray, 1984). Chen and coworkers (1987) 

reported that maternal smoking during pregnancy increases the size of infant 

lung neuroepithelial bodies and decreases the amount of core granules present in 

them. Wang and coworkers (1984) had reported previously that mother mice 

receiving tap water with nicotine during pregnancy and during lactation had 

offspring with increased numbers of neuroepithelial bodies at 5 days of age 

when compared with baby mice whose mothers were not exposed. Baby mice 

exposed to nicotine only during pregnancy had neuroepithelial bodies of 

7-5 
intermediate size with respect to these two groups, whereas those exposed only 

during lactation had neuroepithelial bodies of normal size. By age 30 days, only 

baby mice exposed to nicotine during both pregnancy and lactation had 

neuroepithelial bodies that were larger than those of control animals. 

Activation of the pulmonary neuroendocrine system is not limited to ETS 

exposure; it is activated by active smoking as well. Aguayo and collaborators 

(1989) reported that bronchoalveolar lavage fluids obtained from healthy 

smokers have increased levels of bombesin-like peptides, which are a normal 

component and a secretion product of human lung neuroendocrine cells (Cutz et 

al., 1981). 

In summary, effects of maternal smoking during pregnancy on the fetus 

are difficult to distinguish from those elicited by early postnatal exposure to 

ETS. Animal studies suggest that postnatal exposure to tobacco products 

enhances the effects of in utero exposure to these same products. 

7.2.3. Long-Term Significance of Early Effects on Airway Function 

By altering the structural and functional properties of the lung, prenatal 

exposure to tobacco smoke products and early postnatal exposure to ETS 

increase the likelihood of more severe complications during viral respiratory 

infections early in life. Martinez and collaborators (1988a) measured lung 

function before 6 months of age and before any lower respiratory illness in 124 

infants. They found that infants with the lowest levels for various indices of 

airway size were three to nine times more likely to develop wheezing respiratory 

illnesses during the first year of life than the rest of the population. The same 

authors (Martinez et al., 1991) subsequently showed that, in these same infants 

with lower initial levels of lung function, recurrent wheezing illnesses also were 

more likely to occur during the first 3 years of life. A similar study performed in 

Australia (Young et al., 1990) confirmed that infants who present episodes of 

coughing and wheezing during the first 6 months of life have lower maximal 

expiratory flows before any such illnesses develop. 

The increased likelihood of pulmonary complications during viral 

respiratory infections in infants of smoking parents has important long-term 

consequences for the affected individual. There is considerable evidence 

suggesting that subjects with chronic obstructive lung diseases have a history of 

childhood respiratory illnesses more often than subjects without such diseases 

(reviewed by Samet and coworkers [1983]). Burrows and collaborators (1988) 

found that active smokers without asthma (N = 41) who had a history of 

respiratory troubles before age 16 years showed significantly steeper declines in 

FEV1 (as a percentage of predicted) after the age of 40 than did nonasthmatic 

smokers without such a history (N = 396). Although these results may have 

been influenced by recall bias, they suggest that lower respiratory tract illnesses 

7-6 
during a period of rapid lung development may damage the lung and increase the 

susceptibility to potentially harmful environmental stimuli. 

There is no information available on the degree of reversibility of changes 

induced by exposure to ETS during early life. Longitudinal studies of lung 

function in older children have shown, however, that diminished levels of lung 

function are found in children of smoking parents at least until the adolescent 

years. 

7.2.4. Exposure to ETS and Bronchial Hyperresponsiveness 

Bronchial hyperresponsiveness consists of an enhanced sensitivity of the 

airways to pharmacologic or physical stimuli that normally produce no changes 

or only small decreases in lung function in normal individuals. Subjects with 

bronchial hyperresponsiveness have significant drops in airway conductance and 

maximal expiratory flows after inhalation of stimuli such as cold air, hypertonic 

saline, nebulized distilled water, methacholine, or histamine. Bronchial 

hyperresponsiveness is regarded as characteristic of asthma (O'Connor et al., 

1989) and may precede the development of this disease in children (Hopp et al., 

1990). It has also been considered as a predisposing factor for chronic airflow 

limitation in adult life (O'Connor et al., 1989). 

Recent studies of large population samples have shown that active 

smokers have increased prevalence of bronchial hyperresponsiveness (Woolcock 

et al., 1987; Sparrow et al., 1987; Burney et al., 1987) when compared with 

nonsmokers. This relationship seems to be independent of other possible 

determinants of bronchial hyperresponsiveness (O'Connor et al., 1989). 

However, one large study of almost 2,000 subjects from a general population 

sample failed to find a significant relationship between smoking and prevalence 

of bronchial hyperresponsiveness (Rijcken et al., 1987). The subjects involved 

in the latter study were younger and were therefore exposed to a smaller average 

cumulative pack-years of smoking than were the subjects of studies in which a 

positive relationship was found. This suggests that the relationship may be 

evident only among individuals with a high cumulative exposure. 

Epidemiologic studies have demonstrated that exposure to ETS is 

associated with an increased prevalence of bronchial hyperresponsiveness in 

children. Murray and Morrison (1986), in a cross-sectional study, reported that 

asthmatic children of smoking mothers were four times more likely to show 

increased responsiveness to histamine than were asthmatic children of 

nonsmoking mothers. O'Connor and coworkers (1987), in a study of a general 

population sample, found a significant association between maternal smoking 

and bronchial hyperresponsiveness (as assessed with eucapnic hyperpnea with 

subfreezing air) among asthmatic children, but not among nonasthmatic children 

(Weiss et al., 1985). Martinez and coworkers (1988b) reported a fourfold 

increase in bronchial responsiveness to carbachol among male children of 

7-7 
smoking parents when compared with male children of parents who were both 

nonsmokers. A smaller (and statistically not significant) increase in bronchial 

responsiveness was reported in girls. These authors also found that the effect of 

parental smoking was stronger in asthmatic children, and results were still 

significant after controlling for this factor in a multivariable analysis. Because 

only a small proportion of mothers in this population smoked during pregnancy, 

the effect was considered to be associated mainly with exposure to ETS in these 

children. Lebowitz and Quackenboss (1990) showed that odds of having 

bronchial reactivity (as assessed by the diurnal variability in maximal expiratory 

flow rate) were 3.6 times as high among 18 children aged 15 years and younger 

who lived with persons who smoked more than 20 cigarettes per day than among 

62 children of the same age who lived with nonsmokers (95% C.I. = 1.2, 10.6). 

Children living with smokers of 1 to 20 cigarettes per day had a prevalence of 

bronchial reactivity that was similar to that of children living with nonsmokers. 

Therefore, there is evidence indicating that parental smoking enhances 

bronchial responsiveness in children. The mechanism for this effect and the 

possible role of atopy in it are unknown. The doses required to enhance 

bronchial responsiveness in children exposed to ETS are apparently much lower 

than those required to elicit similar effects among adult active smokers. A 

process of self-selection, by which adults who are more sensitive to the effects of 

tobacco smoke do not start smoking or quit smoking earlier, may explain this 

finding. Variations in bronchial responsiveness with age also may be involved 

(Hopp et al., 1985). 

Increased bronchial responsiveness may be an important predisposing 

factor for the development of asthma in childhood (Hopp et al., 1990). 

Moreover, it has been suggested that bronchial hyperresponsiveness may have 

effects on the developing respiratory system that predispose to chronic 

obstructive lung disease in later life (O'Connor et al., 1989). Redline et al. 

(1989) examined bronchial responsiveness to hyperventilation with cold air and 

its association with growth of lung function over a 12-year period in 184 

children and young adults (aged 8 to 23 years) over a maximum span of 12 

years. Among subjects with persistent positive responses to cold air during 

followup, forced vital capacity grew faster, but forced expiratory flows grew 

more slowly, than among subjects who consistently did not respond to cold air. 

Among subjects with intermittently positive cold air responses, forced expiratory 

flows also grew more slowly than in controls, but growth of forced vital capacity 

was not changed. Although this study needs confirmation, its results suggest 

that bronchial hyperresponsiveness may have significant effects on the rate of 

growth of airway function and lung size in children. 

7-8 
7.2.5. ETS Exposure and Atopy 

Atopy has been defined epidemiologically as the presence of immediate 

hypersensitivity to at least one potential allergen administered by skin prick test. 

Atopy is an immediate form of hypersensitivity to antigens (called allergens) that 

is mediated by IgE immunoglobulin. Allergy (as indicated by positive skin test 

reactivity to allergens, high levels of circulating IgE, or both) is known to be 

present in almost all cases of childhood asthma. Recent epidemiologic studies 

have indicated that an IgE-mediated reaction may be necessary for the 

occurrence of almost all cases of asthma at any age (Burrows et al., 1989). 

Although genetic factors appear to play a major role in the regulation of 

IgE production (Meyers et al., 1987; Hanson et al., 1991), several reports have 

indicated that active smoking significantly increases total serum IgE 

concentrations and may thus influence the occurrence of allergy (Gerrard et al., 

1980; Burrows et al., 1981; Zetterstrom et al., 1981; Taylor et al., 1985). Active 

smokers also have been found to have higher eosinophil counts and increased 

prevalence of eosinophilia when compared with nonsmokers (Kauffmann et al., 

1986; Halonen et al., 1982; Taylor et al., 1985). The physical and chemical 

similarities between MS and ETS have prompted the investigation of a possible 

role of passive smoking in allergic sensitization in children. 

Weiss and collaborators (1985) first reported a 2.2-fold increased risk of 

being atopic in children of smoking mothers. Martinez and coworkers (1988b) 

confirmed that children of smoking parents were significantly more likely to be 

atopic than were children of nonsmoking parents, and the researchers reported 

that this association was stronger for male children. They also found a rough 

dose-response relationship between the number of cigarettes smoked by parents 

and the intensity of the skin reactions to a battery of allergens. Ronchetti and 

collaborators (1990) extended these findings in the same population sample of 

Martinez and coworkers. They found that total serum IgE levels and eosinophil 

counts were significantly increased in children of smoking parents, and the effect 

was related to both maternal and paternal smoking. 

It is relevant to note that, due to the so-called "healthy smoker effect," 

children of smokers should be genetically less sensitive than children of 

nonsmokers, because the latter are likely to include a disproportionate number of 

allergic subjects who are very sensitive to the irritant effects of smoke. As a 

consequence, the atopy-inducing effects of ETS may be substantially 

underestimated. 

In summary, there is convincing evidence that both maternal smoking 

during pregnancy and postnatal exposure to ETS alter lung function and 

structure, increase bronchial responsiveness, and enhance the process of allergic 

sensitization. These changes elicited by exposure to tobacco products may 

predispose children to lower respiratory tract illnesses early in life and to asthma, 

lower levels of lung function, and chronic airflow limitation later in life. Most 

7-9 
Table 7-1. Studies on respiratory illness referenced in the Surgeon General's

and National Research Council's reports of 1986 

Study 

No. of 

subjects Age of subjects 

Surgeo 

n 

Genera 

l 

NRC 

Cameron et al. 

(1969) 

158 Children (6 to 9) X 

Colley (1971) 2,205 Infants X 

Colley (1974) 1,598 Children (6 to 14) X 

Dutau et al. (1981) 892 Infants/children

(0 to 6) 

X 

Fergusson et al.

(1981) 

1,265 Infants X X 

Leeder et al. 

(1976) 

2,149 Infants X X 

Pedreira et al. 

(1985) 

1,144 Infants X X 

Pullan and Hey

(1982) 

130 Children (10 to 11) X 

Rantakallio (1978) 3,644 Infants/children

(0 to 5) 

X 

Speizer et al.

(1980) 

8,120 Children (6 to 10) X X 

X 

of these same effects have been described for active smoking in adults. These 

smoke-induced changes are, therefore, known biological mechanisms for the 

increased prevalence of respiratory diseases associated with ETS exposure 

described later in this chapter. 

Exposure to tobacco smoke products during pregnancy and to ETS soon 

after birth may be the most important preventable cause of early lung and airway 

damage leading to both lower respiratory illness in early childhood and chronic 

airflow limitation later in life. 

7.3. EFFECT OF PASSIVE SMOKING ON ACUTE RESPIRATORY ILLNESSES IN CHILDREN 

A review of the literature that examined the effects of exposure to ETS on 

the acute respiratory illness experiences of children was contained in the 

Surgeon General's report on the health consequences of involuntary smoking 

(U.S. DHHS, 1986) and in the report on environmental tobacco smoke by the 

NRC (1986). Table 7-1 shows the studies referenced in these two reports. 

The Surgeon General's report concluded that "the results of these studies 

show excess acute respiratory illness in children of parents who smoke, 

7-10 
particularly in children under 2 years of age," and that "this pattern is evident in 

studies conducted with different methodologies and in different locales" (page 

44). It estimated that the increased risk of hospitalization for severe bronchitis 

or pneumonia ranged from 20% to 40% during the first year of life. The report 

stated that "young children appear to be a more susceptible population for the 

adverse effects of involuntary smoking than older children and adults" (page 44). 

Finally, the report suggested that "acute respiratory illnesses during childhood 

may have long-term effects on lung growth and development, and might increase 

the susceptibility to the effects of active smoking and to the development of 

chronic lung disease" (page 44). 

The 1986 NRC report observed that "all the studies that have examined the 

incidence of respiratory illnesses in children under the age of 1 year have shown 

a positive association between such illnesses and exposure to ETS. The 

association is very unlikely to have arisen by chance" (page 208). It pointed out 

that "some of the studies have examined the possibility that the association is 

indirect by allowing for confounding factors . . . and have concluded that such 

factors do not explain the results. This argues, therefore, in favor of a causal 

explanation" (page 208). The report concluded that "bronchitis, pneumonia, and 

other lower-respiratory-tract illnesses occur up to twice as often during the first 

year of life in children who have one or more parents who smoke than in 

children of nonsmokers" (page 217). 

7.3.1. Recent Studies on Acute Lower Respiratory Illnesses 

Several recent studies not referenced in the Surgeon General's report or in 

the NRC report have addressed the relationship between parental smoking and 

acute lower respiratory illnesses in children (see Table 7-2). 

Chen and coworkers (1986) studied 1,058 infants out of 1,163 infants born 

in a given period in two neighborhoods in Shanghai, People's Republic of China. 

Information on hospital admissions from birth to 18 months, smoking habits of 

household members, parental education, and social and living conditions was 

obtained by use of a self-administered questionnaire completed by the parents 

when the child reached 18 months of age. Hospital admissions were divided into 

those due to respiratory illness and those from all other conditions. None of the 

mothers in the study smoked. There was no statistically significant association 

between exposure to ETS and admission to the hospital for any condition other 

than respiratory illnesses. Compared with nonsmoking households, the risk of 

being admitted to a hospital for respiratory illnesses was 17% higher when one 

to nine cigarettes were smoked daily by household members (95% C.I. = 0.6, 

2.3) and was 89% higher when more than nine cigarettes were smoked daily by 

household members (95% C.I. = 1.1, 3.4). The authors controlled for the effects 

of crowding, chronic respiratory illness in the family, father's education, type of 

feeding, and birthweight. 

7-11 
Table 7-2. Recent epidemiologic studies of effects of passive smoking on acute lower respiratory tract illnesses (LRIs) 

Authors Population studied 

ETS exposure assessment Outcome variable Results1 

Breese-Hall et al. (1984) 

Cases: 29 infants hospitalized withbronchiolitis due to respiratory syncytial virus(RSV)Controls: 

58 infants hospitalized fornonrespiratory conditions;58 infants hospitalized due toLRIs not due to RSV 

Parental questionnaire 

See populationstudied 

Cases vs. controls Odds ratio (OR) = 4.8(1.8, 13.0) (>5 cig./day none) LRI controls vs.non-LRI controls OR = 2.7 (1.3, 5.7) 

7-12 

Chen et al. (1986) 1,058 infants born in 

Shanghai, China 

Parental self- Admissions toadministered hospital forquestionnaire; number respiratory illness asof cigarettes smoked reported by parentsby householdmembers

Cig./day 1-9 >9 1.9 (1.1, 3.4) 

OR 

1.2 (0.6, 2.3) 

(contin
Table 7-2. (continued) 

Authors Population studied 

ETS exposure assessment Outcome variable Results1 

Chen et al. (1988) 2,227 infants born in 

Shanghai, China 

Household selfadministered questionnaire 

Incidence of hospitalization forrespiratory illness,incidence of bronchitis or pneumonia first 18 mo. of life 

First 6 mo. of life: OR = 3.0 (1.6, 5.7);7-18 mo. of life: OR = 1.8 (1.0, 3.2) 

Chen (1989) Same as above Same as above Same as above First 18 mo. of life: 

incidence density ratio(IDR) = 1.6 for breast-babies; IDR = 3.4 for non-breafed babies; confidence intervals not calculable 

7-13 

(contin
Table 7-2. (continued) 

Authors Population studied 

ETS exposure assessment Outcome variable Results1 

McConnochie and Roghmann (1986a) 

53 infants with bronchiolitis; 106 controls 

Parental questionnaire at mean age 8 yr. 

See populationstudied 

Cases vs. controls OR = 2.4 (1.2, 4.8)(smoking mother vs. 

nonsmoking mother) 

Ogston et al.(1987) 

1,565 infants in New Zealand Maternal and paternal 

smoking habits duringpregnancy byquestionnaire 

Upper and lowerrespiratory illnessesduring first year oflife 

Paternal smokingOR = 1.43 (1.05, 1.96)maternal smoking

OR = 1.82 (1.25, 3.64) 

Anderson et al. (1988) 

102 children hospitalized inAtlanta, Georgia, <2 yr.; 199controls 

Self-reported smokinghabits of family members 

LRI No effect of parental 

smoking after controllifor other risk factors 

7-14 

(contin
Table 7-2. (continued) 

Authors Population studied 

ETS exposure assessment Outcome variable Results1 

Woodward et al. (1990) 

2,125 children aged 18 mo. to 3 yr. 

Self-administered mailed questionnaire 

“Respiratory score”regarding 13 different symptoms; top 20% 

compared with low 20% 

OR = 2.0 (1.3, 3.4) ofhaving a smoking moth

for high scores comparwith low scores; no effof paternal smoking 

Wright et al. (1991) 847 white children born in 

Tucson, Arizona 

Self-administered questionnaire andcotinine levels in a subsample 

LRIs as assessed bythe infants' pediatricians 

OR = 1.5 (1.1, 2.2) ofhaving smoking mothe

no effect of paternal smoking 

Reese et al. (1992) 491 children aged 1 mo. to 17 

yr. 

Cotinine levels in urine of children; questionnaire ofparents' current smoking 

Hospitalizationfor bronchiolitis 

Higher levels in childrhospitalized forbronchiolitis than in controls (p<0.02) 

7-15 

195% confidence intervals in parentheses. 
 Chen and coworkers (1988) subsequently studied 2,227 out of 2,315 

children born in the last quarter of 1983 in Chang-Ning District, Shanghai, 

People's Republic of China. There were no smoking mothers in this population. 

The authors reported a significant linear relationship of total daily cigarette 

consumption by family members with incidence density of hospitalization for 

respiratory illness and with cumulative incidence of bronchitis and pneumonia in 

the first 18 months of life. The relationship was stronger for the 1- to 6-month 

period than for the 7- to 18-month period: When compared with households 

whose members did not smoke at home, the risk of being hospitalized for 

respiratory illness during the 1- to 6-month interval was three times as high (95% 

C.I. = 1.6, 5.7) in households whose members smoked more than nine cigarettes 

at home, whereas comparison of the same two types of household showed that 

the risk of being hospitalized for respiratory illness during the 7- to 18-month 

interval was only 1.8 times as high (95% C.I. = 1.0, 3.2) in the smoking 

household. The relationship also was stronger among low-birthweight infants. 

Results were independent of sex, birthweight, feeding practices, nursery care, 

paternal education, family history of chronic respiratory diseases, and use of coal 

for cooking. 

In a different publication based on the same data from the 1988 study, 

Chen (1989) reported that the effects of passive smoking were stronger in 

artificially fed infants than in breast-fed infants. When comparing breast-fed 

infants of nonsmoking and smoking families, the risk of being hospitalized for 

respiratory illness in the first 18 months of life was 1.6 times as high for 

breast-fed infants of smoking families (> 19 cig./day), whereas the same risk was 

3.4 times as high among non-breast-fed infants of smoking families. 

The studies by Chen (1989) and Chen and coworkers (1986, 1988) were 

retrospective in nature and thus not immune to possible biases generated by the 

fact that the occurrence of the outcome event may enhance reporting or recall of 

the conditions considered as risk factors. However, conclusions are strengthened 

by the finding that admissions for nonrespiratory illnesses were unrelated to 

passive smoking in the study in which the relationship was assessed (Chen et al., 

1986) and by the fact that the finding remained significant after adjusting for 

known confounders. 

Breese-Hall and coworkers (1984) studied 29 infants hospitalized with 

confirmed RSV bronchiolitis before age 2, 58 controls hospitalized for acute 

nonrespiratory conditions, and 58 controls hospitalized for acute lower 

respiratory illnesses from causes other than RSV. Cases and controls were 

matched for age, sex, race, month of admission, and form of payment for 

hospitalization. Information on smoking habits in the family was obtained at the 

time of each patient's admission. Cases were 4.8 times as likely as controls 

(95% C.I. = 1.8, 13.0) to have one or more household members who smoked five 

or more cigarettes per day. However, there was no significant difference in the 

prevalence of cigarette smoking in the households of subjects with respiratory 

7-16 
illnesses caused by RSV and those not caused by RSV. This was attributable to 

the fact that the controls with respiratory illnesses not caused by RSV were also 

much more likely to live with smokers of five or more cigarettes per day than 

were controls with nonrespiratory illnesses (OR = 2.7, 95% C.I. = 1.3, 5.7). 

Little information is given about enrollment and refusals; thus, it is not possible 

to know if selection bias may have influenced the results. Also, other possible 

confounders such as socioeconomic level were not taken into account when 

matching cases to controls or when data were analyzed. 

McConnochie and Roghmann (1986a) compared 53 infants drawn from 

the patient population of a group practice in Rochester, New York, who had 

physician-diagnosed bronchiolitis before age 2 years, with 106 controls from the 

same practice who did not have lower respiratory illnesses during the first 2 

years of life and who were matched with cases for sex and age. Parental 

interviews were conducted when the child had a mean age of 8.4 years. Parents 

were asked about family history of respiratory conditions and allergy, 

socioeconomic status, passive smoking, home cooking fuel, home heating 

methods, and household pets. Passive smoking was defined as current and 

former smoking of "at least 20 packs of cigarettes or 12 ounces of tobacco while 

living in the home with the subject." Current and former smoking was scored 

equally, based on the assumption that the report of either reflected passive 

smoking in the first 2 years of life. Frequency of paternal smoking was not 

increased among children who had bronchiolitis. Cases were 2.4 times (95% 

C.I. = 1.2, 4.8) as likely to have smoking mothers as were controls. The 

association was stronger in families with older siblings (OR = 8.9); however, a 

multiplicative test for this interaction did not reach statistical significance. The 

authors studied 63% of eligible cases and 34% of eligible controls. Although the 

reasons for exclusion from both groups are detailed, selection bias cannot be 

excluded completely, and the authors give no information about maternal 

smoking habits among excluded subjects. Also, overreporting of smoking by 

parents who were aware of their child's history of bronchiolitis may have 

introduced biases due to differential misclassification. However, the results 

were consistent across groups classified according to family history of asthma or 

allergy, social status, presence of older siblings, and crowding. 

Ogston and coworkers (1987) conducted a prospective study of 1,565 

infants of primigravidae enrolled antenatally in the Tayside Morbidity and 

Mortality Study in New Zealand. Information on the father's smoking habits and 

on the mother's smoking habits during pregnancy was obtained at the first 

antenatal interview and from a postnatal questionnaire. A summary record was 

completed when the child was 1 year of age and included a report of the child's 

respiratory illnesses (defined as "infections of the upper or lower respiratory 

tract") during the first year of life derived from observations made by health 

visitors during scheduled visits to see the child. The authors used a multiple 

logistic regression to control for the possible effects of maternal age, feeding 

7-17 
practices, heating type, and father's social class on the relationship between 

parental smoking and child health. Of the 588 children of nonsmokers in this 

sample, 146 (24.8%) had respiratory illnesses during the first year of life. 

Paternal smoking was associated with a 43% increase (95% C.I. = 4.7, 96.1) in 

the risk of having respiratory illnesses in the first year of life, and this was 

independent of maternal smoking. The risk of having a respiratory illness was 

82% higher (95% C.I. = 25.6, 264.4) in infants of smoking mothers than in 

infants of nonsmoking parents. Smoking by both parents did not increase the 

risk of having respiratory illnesses beyond the level observed in infants with 

smoking mothers and nonsmoking fathers. It is difficult to compare this study 

with other reports on the same issue because the authors could not distinguish 

between upper and lower respiratory tract illnesses. 

Anderson and coworkers (1988) performed a case-control study of 102 

infants and young children hospitalized in Atlanta, Georgia, for lower respiratory 

tract illnesses before age 2 and 199 age- and sex-matched controls. The 

unadjusted relative odds of having any family member smoking cigarettes were 

2.0 times as high (p < 0.05) among cases as among controls (confidence interval 

was not calculable from the reported data). The effect disappeared, however, 

after controlling for other factors (prematurity, history of allergy in the child, 

feeding practices, number of persons sleeping in the same room with the child, 

immunization of the child in the last month) in a multivariable logistic regression 

analysis. No information is provided in this report about maternal and paternal 

smoking separately, and the number of cigarettes smoked at home by each 

family member was not recorded either. Also, almost 30% of all target cases 

declined participation in the study, and no information was available on smoking 

habits in the families of these children. No information is given about number of 

refusals among controls. 

Woodward and collaborators (1990) obtained information about the 

history of acute respiratory illnesses in the previous 12 months on 2,125 children 

aged 18 months to 3 years whose parents answered a questionnaire mailed to 

4,985 eligible families in Adelaide, Australia. A "respiratory score" was 

calculated from responses to questions regarding 13 different upper and lower 

respiratory illnesses. A total of 1,218 parents (57%) gave further consent for a 

home interview. From this total, parents of 258 cases (children whose 

respiratory score fell in the top 20% of scores) and 231 "controls" (children 

whose scores were within the bottom 20% of scores) were interviewed at home. 

When compared with controls, cases were twice as likely to have a mother who 

smoked during the first year of life (95% C.I. = 1.3, 3.4). This effect was 

independent of parental history of respiratory illnesses, other smokers in the 

home, use of group child care, parental occupation, and level of maternal stress 

and social support. The authors found no differences in the way smokers and 

nonsmokers perceived or managed acute respiratory illnesses in their children. 

Based on this finding, they ruled out that such differences could explain their 

7-18 
findings. They also reported that feeding practices strongly modified the effect 

of maternal smoking; among breast-fed infants, cases were 1.8 times as likely to 

have smoking mothers as were controls (95% C.I. = 1.2, 2.8), whereas among 

non-breast-fed infants, cases were 11.5 times as likely to have smoking mothers 

as were controls (95% C.I. = 3.4, 38.5). 

Wright and collaborators (1991) studied the relationship between parental 

smoking and incidence of lower respiratory tract illnesses in the first year of life 

in a cohort of 847 white non-Hispanic infants from Tucson, Arizona, who were 

enrolled at birth and followed prospectively. Lower respiratory illnesses were 

diagnosed by the infants' pediatricians. Maternal and paternal smoking was 

ascertained by questionnaire. For verification of smoking habits, the researchers 

measured cotinine in umbilical cord serum of a sample of 133 newborns who 

were representative of the population as a whole. Cotinine was detectable in 

umbilical cord sera of all infants whose mothers reported smoking during 

pregnancy and in 7 of 100 cord specimens of infants whose mothers said they 

had not smoked during pregnancy. There was a strong relationship between 

cotinine level at birth and the amount that the mother reported having smoked 

during pregnancy. 

Children whose fathers smoked were no more likely to have a lower 

respiratory tract illness in the first year of life than were children of nonsmoking 

fathers (31.3% vs. 32.2%, respectively). The incidence of lower respiratory tract 

illnesses was 1.5 times higher (95% C.I. = 1.1, 2.2) in infants whose mothers 

smoked as in infants whose mothers were nonsmokers. This relationship became 

stronger when mothers who were heavy smokers were separated from light 

smokers; 45.0% of children born to mothers who smoked more than 20 

cigarettes per day had a lower respiratory illness, compared with 32.1% of 

children whose mothers smoked 1 to 19 cigarettes per day and 30.5% of children 

of nonsmoking mothers (p < 0.05). The authors tried to differentiate the effects 

of maternal smoking during pregnancy from those of postnatal exposure to ETS 

but concluded that the amount smoked contributed more to lower respiratory 

tract illness rates than did the time of exposure. The authors also found that 

maternal smoking had a significant effect on the incidence of lower respiratory 

tract illnesses only for the first 6 months of life; the risk of having a first lower 

respiratory illness between 6 and 12 months was independent of maternal 

smoking habits. A logistic regression showed that the effect of maternal 

smoking was independent of parental childhood respiratory troubles, season of 

birth, day-care use, and room sharing. Feeding practices, maternal education, 

and child's gender were unrelated to incidence of lower respiratory illnesses in 

this sample and were not included in the regression. The analysis also showed a 

significant interaction between maternal smoking and day-care use; the effects of 

maternal smoking were significant when the child did not use day care (OR = 

2.7; 95% C.I. = 1.2, 5.8) but were weaker and did not reach significance among 

infants who used day care (OR = 1.9; 95% C.I. = 0.9, 4.0). The authors 

7-19 
suggested that day-care use may protect against lower respiratory illnesses by 

reducing exposure to ETS. 

Reese et al. (1992) studied urinary cotinine levels in 491 children, aged 1 

month to 17 years, on admission to hospital. Children admitted for bronchiolitis 

had higher urinary cotinine levels than a group of children of similar age 

admitted for nonrespiratory illnesses (p < 0.02). The researchers concluded that 

there are objective data linking passive smoking to hospital admission for 

bronchiolitis in infants. 

7.3.2. Summary and Discussion on Acute Respiratory Illnesses 

Both the literature referenced in the Surgeon General's report (U.S. DHHS, 

1986) and the NRC report (1986) and the additional, more recent studies 

considered in this report provide strong evidence that children who are exposed 

to ETS in their home environment are at considerably higher risk of having acute 

lower respiratory tract illnesses than are unexposed children. Increased risk 

associated with ETS exposure has been found in different locales, using different 

methodologies, and in both inpatient and outpatient settings. The effects are 

biologically plausible (see Section 7.2). Several studies also have reported a 

dose-response relationship between degree of exposure (as measured by number 

of cigarettes smoked in the household) and risk of acute respiratory illnesses. 

This also supports the existence of a causal explanation for the association. 

The majority of studies found that the effect was stronger among children 

whose mothers smoked than among those whose fathers smoked. This is further 

evidence in favor of a causal explanation, because infants are generally in closer 

and more frequent contact with their mothers. There are now also fairly 

convincing data showing that the increased incidence of acute respiratory 

illnesses cannot be attributed exclusively to in utero exposure to maternal smoke. 

In fact, Chen (1989) and Chen and coworkers (1986, 1988) reported increased 

risk of acute respiratory illnesses in Chinese children living with smoking fathers 

and in the total absence of smoking mothers. This effect also could be attributed 

either to in utero exposure to the father's smoke or to an effect on the father's 

sperm. This seems unlikely, however, because no such effects of parental 

smoking during pregnancy have been described in similar studies performed in 

Western countries. Furthermore, Woodward and coworkers (1990) found that 

children of smoking mothers were significantly more prone to acute respiratory 

illnesses even after mothers who smoked during pregnancy were excluded from 

the analysis. This clearly suggests the existence of direct effects of ETS 

exposure on the young child's respiratory health that are independent of in utero 

exposure to tobacco smoke products. 

There is also convincing evidence that the risk is inversely correlated with 

age; infants aged 3 months or less are reported to be 3.3 times more likely to 

have lower respiratory illnesses if their mothers smoke 20 or more cigarettes per 

day than are infants of nonsmoking mothers (Wright et al., 1991). Increases in 

7-20 
incidence of 50% to 100% (relative risks of 1.5-2.0) have been reported in older 

infants and young children. The evidence for an effect of ETS is less persuasive 

for school-age children, although trends go in the same direction as those 

reported for younger children. This may be due to a decrease in illness 

frequency, to physiological development of the respiratory tract or immune 

system with age, or to a decreased contact between mother and child with age. 

Reasonable attempts have been made in most studies to adjust for a wide 

spectrum of possible confounders. The analyses indicate that the effects are 

independent of race, parental respiratory symptoms, presence of other siblings, 

socioeconomic status or parental education, crowding, maternal age, child's sex, 

and source of energy for cooking. One study (Graham et al., 1990) also showed 

that the effect of ETS exposure on proneness to acute respiratory illnesses in 

infancy and early childhood was also independent of several indices of maternal 

stress, lack of maternal social support, and family dysfunction. Other factors, 

such as breastfeeding, decreased birthweight, and day-care attendance, have been 

shown to modify the risk. 

Some sources of bias may have influenced the results, but it is highly 

unlikely that they explain the consistent association between acute lower 

respiratory illness and ETS exposure. With one exception (Wright et al., 1991), 

all studies relied exclusively on questionnaires or interviews to assess exposure. 

Although questions tend to be very specific, overreporting or more accurate 

reporting of smoking habits by parents of affected children is possible, 

particularly in case-control and retrospective studies. However, such a bias 

should affect both respiratory and nonrespiratory outcomes, and at least two 

studies have shown no association between nonrespiratory outcomes and ETS 

exposure (Chen et al., 1988; Breese-Hall et al., 1984). Selection bias could not 

be excluded in some case-control studies, but satisfactory efforts were made to 

avoid this source of bias in most studies. 

7.4. PASSIVE SMOKING AND ACUTE AND CHRONIC MIDDLE EAR DISEASES 

The Surgeon General's report (U.S. DHHS, 1986) and the NRC report 

(1986) reviewed five studies demonstrating an excess of chronic middle ear 

7-21 
Table 7-3. Studies on middle ear diseases referenced in the Surgeon

General's report

of 1986

Study No. of subjects Age of subjects

(years) 

Said et al. (1978) 3,290 10-20 

Iversen et al. (1985) 337 0-7 

Kraemer et al. (1983) 76 Young children

(unspecified age) 

Black (1985) 450 4-9 

Pukander et al. (1985) 264 2-3 

disease in children exposed to parental cigarette smoke (Table 7-3). Both reports 

conclude that the data are consistent with increased rates of chronic ear 

infections and middle ear effusions in children exposed to ETS at home. 

7.4.1. Recent Studies on Acute and Chronic Middle Ear Diseases 

Several recent studies not referenced in the Surgeon General's report or in 

the NRC report have addressed the relationship between parental smoking and 

middle ear illnesses in children (Table 7-4). 

Fleming and coworkers (1987) examined retrospectively risk factors for 

the acquisition of infections of the upper respiratory tract in 575 children less 

than 5 years of age. Information on smoking habits and on upper respiratory 

tract infections and ear infections in the 2 weeks prior to interview was obtained 

from the children's guardians. The authors reported a 1.7-fold increase 

(p = 0.01) in the risk of having an upper respiratory illness in children of 

smoking mothers when compared with children of nonsmoking mothers. This 

effect was independent of feeding practices, family income, crowding, day-care 

attendance, number of siblings aged less than 5 years, child's age, and race. The 

authors calculated that 10% of all upper respiratory illnesses in the population 

were attributable to maternal smoking, a proportion that was comparable with 

that attributable to day-care attendance. There was no relationship between 

maternal smoking and frequency of ear infections in this population sample. 

Willatt (1986) studied 93 children who were the entire group of children 

admitted to a Liverpool hospital for tonsillectomy (considered an index of 

frequent upper respiratory or ear infections) during a 3-month period and 61 ageand sex-matched controls. The median age was 6.9 years (range 1.8-14.9). 

Parents were asked about the number of sore throats in the previous 3 months 

and the smoking habits of all members of the household. There was a significant 

7-22 
relationship (p < 0.05) between number of episodes of sore throat and number of 

cigarettes smoked by the mother. The effect was independent of birthweight, 

sex, child's age, feeding practices, social class, crowding, and number of sore 

throats and tonsillectomies in other household members. The relative odds of 

having a smoking mother were 2.1 times as high (95% C.I. = 1.1, 4.0) in 

children about to undergo tonsillectomy as in children not undergoing 

tonsillectomy. 

Tainio and coworkers (1988) followed 198 healthy newborns from birth to 

2.3 years of age. The investigators recorded physician-diagnosed recurrent otitis 

media (defined as more than four episodes of otitis media during the first 2 years 

or more than four episodes during the second year). Parental smoking was more 

frequent (55%) among the infants with recurrent otitis media than in the 

comparison group (33%; p < 0.05). The authors comment, however, that 

"parental smoking was not a risk factor for recurrent otitis media," probably 

because there was no significant relationship between parental smoking and 

recurrent otitis media using definitions of the latter that differed from the one 

described above. No distinction was made in this study between the possible 

effects of maternal and paternal smoking. In addition, the study sample was 

probably too small to obtain reliable risk calculations. 

Reed and Lutz (1988) studied 24 of 70 eligible children who had been 

seen in a family practice office for acute otitis media during a period of 4 months 

and 25 of 70 eligible children who had been seen for other reasons. Forty-five of 

these children had tympanograms performed and had information on household 

smoke exposure. Prevalence of an abnormal tympanogram (indicating the 

presence of middle ear effusion) was higher among children exposed to smokers 

at home (OR = 4.86, 95% C.I. = 1.4, 17.2). Results were independent of feeding 

practices, history of upper respiratory illness in the past month, low 

socioeconomic status, sex, age, and attendance at a day-care center. Only a 

small fraction of eligible subjects were included in this study, and the possibility 

of selection bias as an explanation for the reported results cannot be ruled out. 

Hinton (1989) compared 115 children aged 1 to 12 years (mean = 5 years) 

admitted to a British hospital for grommet insertion with 36 children aged 2 to 

11 years (mean = 6 years) with normal ears who were taken from an orthoptic 

clinic. Prevalence of smoking was significantly higher in parents of cases than 

in parents of controls (OR = 2.1, 95% C.I. = 1.0, 4.5). Potential sources of 

selection bias or selective misclassification cannot be determined from the data 

reported by the author. No effort was made to control for possible confounders. 

7-23 
Table 7-4. Recent epidemiologic studies of effects of passive smoking on acute and chronic middle ear diseases 

Authors Population studied 

ETS exposure assessment Outcome variable Results1 

Willatt (1986) 93 children aged 2-15 yr.

admitted to hospital fortonsillectomy; 61 age- and 

sex-matched controls 

Questionnaire answered by parents 

Tonsillectomy OR = 2.1 (1.1, 4.0) of

having smoking mothe

Fleming et al. 575 children <5 yr. Questionnaire (1987) answered by child's 

guardian 

Upper respiratoryillnesses (URI) andinfections in previous2 weeks 

OR = 1.7 for URI when mother smoked; no effon ear infection 

Tainio et al. (1988) 198 Finnish newborns 

followed from birth to age 2.3 yr. 

Questionnaire to parents 

No effects 

Recurrent otitis media as diagnosed bypediatricians 

7-24 

(contin
Table 7-4. (continued) 

Authors Population studied 

ETS exposure assessment Outcome variable Results1 

Reed and Lutz (1988) 

24 cases of acute otitis media; 25 controls 

Questionnaire to parents 

Abnormal tympanometry 

OR = 4.9 (1.4, 17.2) ofhaving smokers at hom

Hinton (1989) 115 children aged 1-12 yr.

admitted for grommet insertion; 36 controls aged 2-11 yr. in Great Britain 

Questionnaire to parents 

Being admitted for grommet insertion 

OR = 2.1 (1.0, 4.5) ofhaving smoking parent

Teele et al. (1989) 877 children observed for 

1 yr.; 698 observed for 3 yr.;498 observed for 7 yr. inBoston, Massachusetts 

Questionnaire to parents 

Acute otitis media; number of days with middle ear effusion 

13% more acute otitis during first yr. of life; more days with middle effusion (p<0.009) onlyduring first yr.; no effeafter controlling forconfounders 

Corbo et al. (1989) 1,615 children aged 6-13 yr.

in Abruzzo, Italy 

Questionnaire to parents 

Child's snoring as

reported by parents 

OR = 1.8 (1.1, 3.0) for moderate smokers (1-1

cig./day);OR = 1.9 (1.2, 3.1) forheavy smokers ($20 

cig./day) 

7-25 

(contin
Table 7-4. (continued) 

Authors Population studied 

ETS exposure assessment Outcome variable Results1 

Strachan et al. (1989) 

736 children in third elementary class inEdinburgh, Scotland 

Salivary cotininelevel 

Prevalence of middle ear effusion as assessed by tympanogram 

OR for doublingsalivary cotinine =1.14 (1.03, 1.27) 

Takasaka (1990) 77 children aged 4-8 yr. with

otitis media with effusion; 134 controls matched for ageand sex in Sendai, Japan 

Questionnaire to parents 

See populationstudied 

No effect 

Etzel et al. (1992) 132 children from day- care

facility aged <3 yr. 

Serum cotinine levels Otitis media 

with effusion 

Incidence density ratio (1.2, 1.6) forexposed children;increases significant foages #2 years only 

7-26 

195% confidence intervals in parentheses. 
Teele and coworkers (1989) studied consecutively enrolled children being 

followed in two health centers in Boston from shortly after birth until 7 years of 

age. Acute otitis media and middle ear effusion were diagnosed by the children's 

pediatricians. Data were analyzed for 877 children observed for at least 1 year, 

698 children observed for at least 3 years, and 498 children observed until 7 

years of age. A history of parental smoking was obtained when each child 

became 2 years old. A parent was considered a smoker if he or she smoked 

more than one cigarette per day. The child was considered exposed if either 

parent was a smoker. The authors reported that the incidence of acute otitis 

media during the first year of life was 13% higher in children of smoking parents 

when compared with children of nonsmoking parents (p < 0.05), but statistical 

significance was no longer present after controlling for alleged confounders (site 

of health care, season of birth, birthweight, socioeconomic status, presence and 

number of siblings, room sharing, feeding practices, and sibling or parental 

history of ear infection and allergic diseases). Several of these variables may not 

have been confounders if they were not related to both parental smoking and 

incidence of acute otitis media. Controlling for risk factors that are not 

confounders may result in overcorrection. Parental smoking was not associated 

with an increased risk for acute otitis media during the first 3 years or 7 years of 

life. Likewise, parental smoking was associated with a significant increase in 

the number of days with middle ear effusion, but only during the first year of life 

(p < 0.009), and the effect was no longer present after alleged confounders were 

controlled for. The authors do not provide information on separate risks for 

maternal and paternal smoking or on the incidence of acute otitis media and 

middle ear effusion in children of heavy smokers. 

Takasaka (1990) performed a case-control study on 201 children aged 4 to 

8 in Sendai, Japan. Sixty-seven subjects had otitis media with effusion, and the 

remaining 134 children were a control group matched to cases by age, sex, and 

kindergarten class. The investigators found no significant differences in 

prevalence of exposure to two or more household cigarette smokers between 

children with and without otitis media with effusion (no information on either 

odds ratios or C.I.s was given). The power of this study may have been too low 

to determine risk factors for middle ear effusions reliably. 

Corbo and coworkers (1989) examined 1,615 children aged 6 to 13 years 

who shared a bedroom with siblings or parents in Abruzzo, Italy. Parents were 

asked if the child snored and the frequency of snoring. Parents were asked about 

their own smoking habits; they were considered moderate smokers if the 

summed total for both parents was fewer than 20 cigarettes per day and heavy 

smokers if the summed total was 20 or more cigarettes per day. Prevalence of 

habitual snoring in children increased slightly with the amount of cigarettes 

smoked by parents; children of heavy smokers were 1.9 times as likely to be 

7-27 
habitual snorers as children in nonsmoking households (95% C.I. = 1.2, 3.1), 

whereas children of moderate smokers were 1.8 times as likely to be habitual 

snorers as children of nonsmoking parents (95% C.I. = 1.1, 3.0). Habitual 

snorers were more likely to have had a tonsillectomy, but only if their parents 

smoked. The authors suggested that these results are plausible because adult 

smokers are also at increased risk of being habitual snorers. 

Strachan and collaborators (1989) performed tympanograms and collected 

saliva for cotinine determinations in 736 children in the third primary class (ages 

61⁄2 to 71⁄2 years) in Edinburgh, Scotland. Median of salivary cotinine 

concentrations was 0.19 ng/mL for 405 subjects living with no smoker, 1.8 

ng/mL for 241 subjects living with one smoker, and 4.4 ng/mL for 124 subjects 

living with two or more smokers. For a given number of smokers in the 

household, girls had higher cotinine levels than boys, and children living in 

rented houses (i.e., of lower socioeconomic level) had higher cotinine levels than 

children living in houses owned by their parents. The authors found a linear 

relation between the logarithm of the salivary cotinine concentration and the 

prevalence of middle ear effusion. The authors calculated odds ratios for 

abnormal tympanometry relative to children with undetectable cotinine 

concentrations, after adjustment for sex, housing tenure (rented or owned), social 

class, crowding, gas cooking, and the presence of damp walls. The odds ratio 

for a doubling of salivary cotinine concentration was 1.14 (95% C.I. = 1.03, 

1.27). At a salivary cotinine concentration of 1 ng/mL, the odds ratio of having 

an abnormal tympanogram was 1.7, whereas an odds ratio of 2.3 was calculated 

for a cotinine level of 5 ng/mL. At least one-third of all cases of middle ear 

effusion may have been attributable to passive smoking. 

Etzel and coworkers (1992) studied 132 children who attended a day-care 

facility during the first 3 years of life. The investigators measured serum 

cotinine levels and considered a level of 2.5 ng/mL or more to be indicative of 

exposure to tobacco smoke. The 87 children with serum cotinine above this 

level had a significantly (38%) higher rate of new episodes of otitis media with 

effusion during the first 3 years of life than the 45 children with lower or 

undetectable levels (incidence density ratio = 1.4, 95% C.I. = 1.2, 1.6). The 

authors calculated that 8% of the cases of otitis media with effusion occurring in 

this population were attributable to exposure to tobacco smoke. 

7.4.2. Summary and Discussion of Middle Ear Diseases 

There is some evidence suggesting that the incidence of acute upper 

respiratory tract illnesses and acute middle ear infections may be more common 

in children exposed to ETS. However, several studies have failed to find any 

effect. In addition, the possible role of confounding factors, the lack of studies 

showing clear dose-response relationships, and the absence of a plausible 

biological mechanism preclude more definitive conclusions. 

7-28 
Available data provide good evidence demonstrating a significant increase 

in the prevalence of middle ear effusion in children exposed to ETS. Several 

studies in which no significant association was found between ETS exposure and 

middle ear effusion were not specifically designed to test this relationship, and, 

therefore, either power was insufficient or assessment of the degree of exposure 

was inadequate. Also, Iversen and coworkers (1985), who assessed middle ear 

effusion objectively, suggested that the risk associated with passive smoking 

increased with age. This may explain the negative results of several studies 

based on preschool children; the sample sizes of these studies may have been 

inadequate to test for increased risks of 50% or less, as would be expected in 

children under 6 years of age. The finding of a log-linear dose-response 

relationship between salivary cotinine levels and the prevalence of abnormal 

tympanometry in one study (Strachan et al., 1989) adds to the evidence favoring 

a causal link. Although not all studies adjusted for possible confounders and 

selection bias cannot be excluded in the case-control studies reviewed, the 

evidence as a whole suggests that the association is not likely to be due to 

chance, bias, or factors related to both ETS exposure and middle ear effusion. 

The biological mechanisms explaining the association between ETS 

exposure and middle ear effusion require further elucidation. Otitis media with 

effusion is usually attributed to a loss of patency of the eustachian tube, which 

may be enhanced by upper respiratory infection, impaired mucociliary function, 

or anatomic factors (Strachan et al., 1989). It is possible that pharyngeal 

narrowing by adenoidal tissue (and, consequently, eustachian tube dysfunction) 

may be more common in these children. This is suggested by reports of a higher 

prevalence of maternal smoking among children about to undergo or who have 

undergone tonsillectomy and by an increased prevalence of habitual snoring 

among children of smoking parents. Impaired mucociliary clearance has been 

demonstrated convincingly in smoking adults (U.S. DHHS, 1984). No data are 

available on mucociliary transport in children exposed to ETS. However, ETS 

may affect mucociliary clearance in children as in adults. If this were the case 

and if normal mucociliary clearance is required for rapid resolution of otitis 

media, exposure to ETS could result in increased prevalence of chronic middle 

ear effusion. 

The increased prevalence of middle ear effusion attributable to ETS 

exposure has very important public health consequences. Middle ear effusion is 

the most common reason for hospitalization of young children for an operation 

and thus imposes a heavy financial burden to the health care system (Black, 

1984). There is also evidence suggesting that hearing loss associated with 

middle ear effusion may have long-term consequences on linguistic and 

cognitive development (Maran and Wilson, 1986). 

7-29 
Table 7-5. Studies on chronic respiratory symptoms referenced in the Surgeon

General's and National Research Council's reports of 1986 

Study No. of 

subjects 

Age of

subjects 

Respiratory 

symptoms 

Surge 

on 

Gener 

al 

NR 

C 

Bland et al. 

(1978) 

3,105 Children/ado

l. (12-13) 

Cough X X 

Charlton 

(1984) 

15,000 Children/ado

l. (8-19) 

Cough X 

Colley et al.

(1974) 

2,426 Children 

(6-14) 

Cough X X 

Dodge (1982) 628 Children 

(8-10) 

Wheeze, 

phlegm,

cough 

X 

Ekwo et al. 

(1983) 

1,355 Children 

(6-12) 

Cough,

wheeze 

X 

Kasuga et al.

(1979) 

1,937 Children 

(6-11) 

Wheeze, 

asthma 

X 

Lebowitz and 

Burrows 

(1976) 

1,525 Children 

(<15) 

Cough,

phlegm,

wheeze 

X 

Schenker et al. 

(1983) 

4,071 Children 

(5-14) 

Cough,

phlegm,

wheeze 

X 

Schilling et al.

(1977) 

816 Children/ado

l. (7-16) 

Cough,

phlegm,

wheeze 

X 

Tager et al.

(1979) 

444 Children/ado

l. (5-19) 

Cough,

wheeze 

X 

Ware et al. 

(1984) 

10,106 Children 

(6-13) 

Cough,

wheeze, 

phlegm 

X 

Weiss et al. 

(1980) 

650 Children (5-

9) 

Cough,

phlegm,

wheeze 

X 

X 

X 

X 

X 

X 

7-31
7.5. EFFECT OF PASSIVE SMOKING ON COUGH, PHLEGM, AND WHEEZING 

Studies addressing the effects of passive smoking on frequency of chronic 

cough, phlegm, and wheezing were reviewed both in the Surgeon General's 

report (U.S. DHHS, 1986) and in the report by the NRC (1986) (see Table 7-5). 

The Surgeon General's report concluded that children whose parents 

smoke were found to have 30% to 80% excess prevalence of chronic cough or 

phlegm compared with children of nonsmoking parents. For wheezing, the 

increase in risk varied from none to over sixfold among the studies reviewed. 

The report noted that the association with parental smoking was not statistically 

significant for all symptoms in all studies, but added that the majority of studies 

showed an increase in symptom prevalence with an increase in the number of 

smoking household members in the home. The report stated that the results of 

some studies could have been confounded by the child's own smoking habits, but 

noted that many studies showed a positive association between parental smoking 

and symptoms in children at ages before significant experimentation with 

cigarettes is prevalent. The report concluded that "chronic cough and phlegm are 

more frequent in children whose parents smoke compared to nonsmokers. The 

implications of chronic respiratory symptoms for respiratory health as an adult 

are unknown and deserve further study" (page 107). 

The NRC report concluded that "children of parents who smoke compared 

with children of parents who do not smoke show increased prevalence of 

respiratory symptoms, usually cough sputum and wheezing. The odds ratios for 

the larger studies, adjusted for the presence of parental symptoms, were 1.2-1.8, 

depending on the symptoms. These findings imply that ETS exposures cause 

respiratory symptoms in some children" (page 216). 

7.5.1. Recent Studies on the Effect of Passive Smoking on Cough, Phlegm, and Wheezing 

Several recent studies not considered either in the NRC report (1986) or in 

the Surgeon General's report (U.S. DHHS, 1986) have addressed the relationship 

between passive smoking and respiratory symptoms in children (Table 7-6). 

McConnochie and Roghmann (1986b) studied 223 of 276 eligible children 

aged 6 to 10 years without a history of bronchiolitis who were drawn from the 

patient population of a group practice in Rochester, New York. Information 

regarding the child's history of wheezing in the previous 2 years, socioeconomic 

status, family history of respiratory illnesses, and smoking in the household was 

obtained by questionnaire. Information on breastfeeding was obtained by record 

checks and interviews. Children whose mothers smoked were more likely to be 

current wheezers than were children whose mothers did not smoke (OR = 2.2, 

95% C.I. = 1.0, 4.8). Neither paternal smoking nor total household smoking had 

any influence on the prevalence of wheezing. 

7-32 
Table 7-6. Recent epidemiologic studies of effects of passive smoking on cough, phlegm, and wheezing 

Authors Population studied 

ETS exposure assessment Outcome variable Results1 

McConnochie and Roghmann (1986b) 

223 children aged 6 to 10 yr.in Rochester, New York 

Parental questionnaire Wheezing in the

previous 2 yr. 

OR = 2.2 (1.0, 4.8) for maternal smoking; no

effect of paternal smok

Park and Kim (1986) 

3,651 children aged 0 to 14yr. in South Korea 

Questionnaire to household members 

Cough in the 3 mo. prior to interview 

OR = 2.4 (1.4, 4.3) forfamilies smoking 1 to cig./day; OR = 3.2 (1.95.5) for families smoki

$15 cig./day 

7-34 

(contin
Table 7-6. (continued) 

Authors Population studied 

ETS exposure assessment Outcome variable Results1 

Bisgaard et al.(1987) 

5,953 infants enrolled at birth in Denmark 

Maternal questionnaire 

Episodes of wheezeduring first yr. of life 

OR = 2.7 (1.8, 4.0) forchildren whose mothersmoked $3 cig./day 

Geller-Bernstein et al. (1987) 

80 children aged 6 to 24 mo. in Israel 

Parental questionnaire Persistent wheeze as 

assessed by physicianafter 11⁄2 yr. offollowup 

OR = 3.1 (1.1, 8.9) forhaving smoking parent

Cogswell et al.(1987) 

100 infants of allergic parentsenrolled at birth; 73 still followed at age 5 yr. 

Parental questionnaire Number of subjects

who developedwheezing at differenttimes after birth 

By 5 yr., 63% of parenwho smoked had wheechildren, compared wit37% of nonsmokingparents (p<0.05) 

Toyoshima et al. (1987) 

48 wheezy children <3 yr.followed in Osaka, Japan 

Parental questionnaire Number of children 

still wheezing at endof followup 

OR = 11.8 (1.3, 105.0) children living in smokhouseholds 

Tsimoyianis et al.

(1987) 

193 12- to 17-year-old highschool athletes 

Questionnaire to the child on household smoking habits 

Self-report of cough,bronchitis, wheeze, and shortness of breath 

No effect on bronchitiswheeze, shortness of breath. Increased frequency of cough(p=0.08) 

7-35 

(contin
Table 7-6. (continued) 

Authors Population studied 

ETS exposure assessment Outcome variable Results1 

Andrae et al. (1988) 

4,990 children aged 6 mo. to 16 yr. in Norrkoping, Sweden 

Self-report of smoking by parents 

Exercise-induced cough as reported by parents 

OR = 1.4 (1.1, 1.8) forchildren whose parents smoked 

Somerville et al. (1988) 

7,144 children aged 5 to 11yr. in England and Scotland;134 controls matched for age and sex inSendai, Japan 

Questionnaire answered by child's mother 

Parental reports ofrespiratory symptoms in the child 

Among English childrewhose parents smoked 

$20 cig./day OR = 1.6

(1.2, 2.2) of having“wheezy chest most 

nights” 

Rylander et al.(1988) 

67 children aged 4 to 7 yr.hospitalized with respiratorysyncytial virus bronchiolitisin Stockholm, Sweden 

Parental questionnaire Subsequent

occasional and recurrent wheezing 

Occasional wheezing O= 4.3 (1.1, 16.4) inchildren of smokingparents; no effect onrecurrent wheezing 

Strachan (1988) 1,012 schoolchildren 6.5 to 

7.5 yr. old in Edinburgh,Scotland 

Parental questionnaire Respiratory 

symptoms in children 

No effect on wheeze; cough at night, OR = 1(1.1, 2.6) in children liwith one smoker; OR = 2.5 in children living wtwo smokers 

7-36 

(contin
Table 7-6. (continued) 

Authors Population studied 

ETS exposure assessment Outcome variable Results1 

Lewis et al. (1989) 60 cases of chronic cough

aged <6 yr.;60 controls; in Salford, United Kingdom 

Parental questionnaire See population

studied 

OR = 1.7 (0.8, 3.5) ichildren living with smoker 

Neuspiel et al.(1989) 

9,670 children enrolled at birth in Great Britain 

Parental questionnaire atbirth, at age 5 yr. and atage 10 yr. 

Wheeze between ages1 and 10 yr. 

Cumulative incidenc5.2% mother nonsmoker, 6.6% mothesmoked 1 to 4 cig./d7.5% mother smoke

to 11 cig./day, 8.1% mother smoked 15 to 24 cig./day, 8.9% mother smoked >24 cig./day 

Chan et al. (1989a) 134 children 7 yr. of age in

London, England, <2,000 gbirthweight; 123 controlswith normal birthweight 

Parental questionnaire Wheeze and cough OR = 2.7 (1.3, 5.5) o

having wheeze at agin children of smokimothers, OR = 2.4 (4.6) of having cough 

7-37 

195% confidence intervals in parentheses. 
 When the authors controlled for family history of respiratory allergy, direct 

effects of maternal smoking on prevalence of wheezing failed to reach statistical 

significance. However, there was a strong association between maternal 

smoking and wheezing among children with a positive family history of 

respiratory allergy (OR = 4.5, 95% C.I. = 1.7, 12.0), and the interaction between 

these terms was highly significant in multivariable analysis, suggesting the 

combined importance of both genetic factors and maternal smoking. 

Park and Kim (1986) studied 3,651 children aged 0 to 14 from a 

randomized, clustered sample of households in South Korea (response rate: 

89%). A questionnaire was administered to household members about their 

smoking habits and respiratory symptoms. Mothers answered questions about 

the presence of cough in the child in the 3 months prior to interview. The 

authors reported dose-response relationships between the child's cough and 

number of smokers in the family, number of smokers in the same room, number 

of cigarettes smoked by all family members, and number of cigarettes smoked 

by parents. The relationship was present in children of different ages (less than 5 

years, 6 to 11 years, and 12 to 14 years). The authors controlled for parental 

education, socioeconomic status, birth rank, parental age, birth interval, number 

of family members, and number of siblings. Family members with cough or 

with morning phlegm production were significantly more likely to live with 

children with cough. After correcting for these two factors, chronic cough was 

2.4 times as likely in children of families whose members smoked 1 to 14 

cigarettes per day (95% C.I. = 1.4, 4.3) and 3.2 times as likely in children of 

families whose members smoked more than 15 cigarettes per day (95% C.I. = 

1.9, 5.5). However, effects were more noticeable and only reached statistical 

significance in children of families whose adult members did not have chronic 

cough. 

Bisgaard and coworkers (1987) studied 5,953 infants of a total of 8,423 

eligible newborns (71%) enrolled in a prospective study. At the age of 1 year, 

the child's mother was interviewed regarding episodes of wheeze during the 

previous year and possible risk factors for wheezing. The risk of wheezing was 

2.7 times as high (95% C.I. = 1.8, 4.0) in children whose mothers smoked three 

or more cigarettes per day as in children whose mothers smoked fewer than three 

cigarettes per day. Results were independent of social status and sex of the 

child. The authors decided not to control for quarter of birth or use of day-care 

facilities, with the assumption that these factors did not modify the relationship 

between maternal smoking and wheezing. Also, biases could have been 

introduced by the fact that almost one-third of the original sample was not 

included in the analysis. 

Geller-Bernstein and coworkers (1987) studied 80 children aged 6 to 24 

months who had been seen as outpatients or inpatients in Israel for wheezing and 

who had a diagnosis of atopy. The children were examined every 6 months 

7-38 
during 4 years by a physician. At the end of assessment, the authors classified 

children as having "recovered" if they had been symptom-free for at least 1 (the 

last) year; otherwise they were classified as "persistent wheezers." "Persistent 

wheezers" were more likely to have smoking parents than were "recovered" 

children (OR = 3.1, 95% C.I. = 1.1, 8.9). This result was independent of 

changes in IgE levels during the study period. The authors did not control for 

the possible confounding effect of parental symptoms. 

Cogswell and coworkers (1987) studied 100 newborns who had at least 

one parent with a history of hay fever or asthma. Ninety-two children were still 

being followed at 1 year of age and 73 at the age of 5 years. Children were 

examined periodically and whenever they had signs of respiratory illness. At the 

child's first birthday, the number of those who had developed wheezing was 

equally distributed between parents who did or did not smoke. By the age of 5 

years, however, 62% of parents who smoked had children who had wheezed 

compared with 37% in nonsmoking families (p < 0.05). It is unlikely that these 

results can be explained by the confounding effect of parental symptoms, 

because all parents were allergic by definition. It is also quite unlikely that 

preferential withdrawal of nonwheezing children of smoking parents could have 

biased the results. 

Toyoshima and coworkers (1987) from Osaka, Japan, followed 48 of 65 

wheezy infants and children less than 3 years old for up to 4 years. Outcome 

information was obtained from charts or by telephoning the child's mother. 

Among 18 children who were still symptomatic 25 to 44 months after their first 

visit, 17 lived with smokers compared with 13 of 22 children who lived with 

smokers and who stopped having symptoms during followup (OR = 11.8, 95% 

C.I. = 

1.3, 105.0). Results were independent of family history of allergy, feeding 

practices, and disturbances at birth. Selection bias related to the number of 

subjects lost for followup or with missing information could have influenced the 

results of this study. 

Tsimoyianis and collaborators (1987) evaluated the effects of exposure to 

ETS on respiratory symptoms in a group of 12- to 17-year-old high school 

athletes (N = 193). Histories of smoking by all household members were 

obtained for all subjects. Athletes exposed to ETS at home were more likely to 

report cough than were unexposed athletes (p = 0.08). Frequency of bronchitis, 

wheeze, and shortness of breath was similar in both groups. A greater awareness 

of the smoking habits of those around them by subjects with cough cannot be 

excluded as an explanation of these findings, but this source of bias cannot 

explain the exposure-response trends for ETS and lung function seen in this 

same sample (see Section 7.8.1). 

Andrae and collaborators (1988) mailed questionnaires to the parents of 

5,301 children aged 6 months to 16 years living in the city of Norrkoping, 

7-39 
Sweden. Data were obtained from 4,990 children (94% response rate). Children 

with parents who smoked had exercise-induced cough more often than did 

children of nonsmokers (OR = 1.4, 95% C.I. = 1.1, 1.8). Exposure to ETS 

interacted with living in houses with damage by dampness; children exposed to 

both had more exercise-induced cough and allergic asthma when compared to 

those exposed to only one or neither. Results of this cross-sectional study may 

have been biased by preferential reporting of symptoms by smoking parents, 

although a reliability study performed in a random sample was reported to 

confirm 95% of the answers regarding respiratory symptomatology. In addition, 

no effort was made to control for active smoking in older children. 

Somerville and coworkers (1988) enrolled 88% of 8,118 eligible children 

aged 5 to 11 from England and Scotland. Data on the child's respiratory 

symptoms and parental smoking were obtained from a self-administered 

questionnaire completed by the child's mother. After exclusions for missing 

data, the proportions of children available ranged from 60.9% to 63.9% of all 

subjects, depending on the variables involved. Logistic regression analysis was 

used to control for child's age, presence of siblings, one- or two-parent families, 

paternal employment, social class, maternal smoking during pregnancy, 

overcrowding, maternal education, maternal age, triceps skinfold thickness, and 

birthweight. For Scottish children (who were only 19% of all subjects), the 

authors found a significant relationship between number of cigarettes smoked at 

home and "chest ever wheezy" (p < 0.01; OR not reported). Among English 

children, there was a significant relationship between number of cigarettes 

smoked at home by mother and father together and prevalence of a wheezy or 

whistling chest most nights (adjusted OR in children whose parents smoked 20 

cig./day = 1.6; 95% C.I. = 1.2, 2.2). Attacks of bronchitis and cough during the 

day or at night were also significantly correlated with number of cigarettes 

smoked by parents in the English sample; odds ratios in children of parents who 

smoked 20 cigarettes per day were 1.4 and 1.3, respectively, but no confidence 

intervals were reported. The authors concluded that the effect of parental 

smoking on respiratory symptoms in this age group is small and requires a large 

number of subjects to be detected. 

Rylander and collaborators (1988) from Stockholm, Sweden, studied 67 

children aged 4 to 7 years who had been hospitalized with virologically proven 

RSV infections before age 3. Questionnaires were mailed to parents regarding 

their smoking habits and the child's history of wheezing illnesses after the initial 

episode. Children who had subsequent occasional wheezing (N = 21) were more 

likely to have smoking parents than those (N = 24) who had no subsequent 

respiratory symptoms (OR = 4.3, 95% C.I. = 1.1, 16.4). However, frequency of 

parental smoking among children who had no subsequent respiratory symptoms 

was not significantly different from that of children who had subsequent 

7-40 
recurrent wheezing. The inconsistency of the results in this study may be 

explained by the small number of subjects involved. 

Strachan (1988) studied 1,012 of a target sample of 1,095 schoolchildren 

aged 6.5 to 7.5 years in Edinburgh, Scotland. Parents answered a questionnaire 

on their smoking habits and on respiratory symptoms in their children. There 

was no relationship between number of smokers in the household and prevalence 

of wheezing in the population. Cough at night (> 3 nights in the past month) 

was more likely to occur in children living with one smoker (OR = 1.6; 95% C.I. 

= 

1.1, 2.6) or two smokers (OR = 2.5; 95% C.I. = 1.5, 4.0) than in children living 

with nonsmokers. Occurrence of "chesty colds" in children was also more 

frequent in households with one (OR = 1.3; 95% C.I. = 0.9, 1.9) or two smokers 

(OR = 1.9; 95% C.I. = 1.3, 3.0). 

A subsequent report (Strachan et al., 1990) based on the same population 

sample studied the relationship between salivary cotinine levels and respiratory 

symptomatology in a subset of 770 children (see also Strachan et al. [1989], 

Section 7.4.1). The authors found no relationship between cotinine levels and 

wheezing or frequent night cough. Frequency of chesty colds was significantly 

correlated with quintals of salivary cotinine (p < 0.01). The authors noted that 

objective markers of recent exposure to ETS may not adequately reflect 

exposure at some critical period in the past. They also noted that there may be 

different ways of understanding the concept of "wheezing" and proposed that 

this could explain the lack of association between this symptom and both 

questionnaire-based and cotinine-based assessment of exposure to ETS in their 

sample. 

Lewis and coworkers (1989) performed a case-control study of risk factors 

for chronic cough in children under 6 years in Salford, United Kingdom. They 

enrolled 60 children referred to a pediatric outpatient clinic with cough lasting 

more than 2 months or frequent episodes of cough without wheeze. These 60 

subjects were compared with controls admitted for routine surgical procedures. 

Children with chronic cough were 1.7 times (95% C.I. = 0.8, 3.5) as likely to 

live with a smoker as were controls. Because of the small number of subjects 

and the high prevalence of parental smoking (> 50%), the power of this study 

may have been too low to allow for meaningful conclusions. 

Neuspiel and coworkers (1989) studied 9,670 of 9,953 eligible children 

enrolled at birth in Great Britain. Information on parental smoking was obtained 

at birth, at age 5 years, and at age 10 years. Outcome data were obtained from 

maternal interviews when the children were 10 years old. Children of smoking 

mothers had 11% higher risk (95% C.I. = 2%, 21%) of wheezing between ages 1 

and 10 than did children of nonsmoking mothers. An exposure-response 

relationship was also present: Cumulative incidence was 5.2% in children 

whose mothers were nonsmokers, 6.6% in children whose mothers smoked 1 to 

7-41 
4 cigarettes per day, 7.5% in children whose mothers smoked 5 to 14 cigarettes 

per day, 8.1% in children whose mothers smoked 15 to 24 cigarettes per day, and 

8.9% in children whose mothers smoked more than 24 cigarettes per day. The 

risk also was increased in children of mothers who did not smoke during 

pregnancy but were smokers thereafter (RR = 2.2, 95% C.I. = 1.2, 3.9). The 

association persisted after a logistic regression model was used to control for the 

effect of child's sex, child allergy, paternal smoking, parental allergy, crowding, 

bedroom dampness, feeding practices, gas cooking, and social status. The 

increase in risk was cut approximately in half but did not disappear when 

additional corrections for maternal respiratory symptoms and for a measure of 

maternal depression were made. Results of this study may be explained in part 

by preferential reporting of wheezy illnesses by smoking mothers. However, it 

is unlikely that the association between maternal smoking and wheezy illnesses 

found in this study can be explained exclusively by uncontrolled sources of bias; 

there was a striking exposure-response effect, and the association persisted after 

controlling for most known confounders and was independent of maternal 

smoking during pregnancy. 

Chan and collaborators (1989a) studied 134 children aged 7 years out of 

216 eligible infants of under 2,000 g birthweight who were admitted to the 

neonatal unit of two hospitals in London, England. Parents of these 134 children 

and of 123 control schoolchildren born in the same period but with normal 

birthweight completed a self-administered questionnaire on respiratory illnesses 

and on social and family history. At age 7, children whose mothers smoked 

were at increased risk of having frequent wheeze independent of their neonatal 

history (adjusted OR = 2.7; 95% C.I. = 1.3, 5.5), although the increase only 

reached statistical significance for children of normal birthweight. Prevalence of 

frequent cough was also more likely to occur in children of smoking mothers 

(OR = 2.4, 95% C.I. = 1.3, 4.6), and the association was significant for both 

cases and controls studied separately. The authors performed a logistic 

regression to control for possible confounders (only the low-birthweight group 

was included). The relationship between frequent wheeze and maternal smoking 

persisted among low-birthweight children after controlling for family history of 

asthma, atopy, socioeconomic status, and use of neonatal oxygen. The 

relationship between frequent cough and maternal smoking was no longer 

significant among low-birthweight infants after controlling for the same possible 

confounders. For the low-birthweight group, the authors assessed the reliability 

of some of the responses to their questionnaires; there was a high correlation (r = 

0.96) between the number of hospitalizations reported by parents and those 

documented in the outpatient clinic of the neonatal unit that followed the infants. 

The authors concluded that misclassification due to parental failure to recall 

previous respiratory illnesses in the low-birthweight group was unlikely. 

7-42 
Krzyzanowski and collaborators (1990) studied a sample of 298 children 

aged 5 to 15 who were family members of county employees enrolled in a 

prospective study. Parents answered a questionnaire on their smoking habits and 

on respiratory symptoms in their children. Indoor formaldehyde concentrations 

in the living environment also were measured. Prevalence rates of chronic 

bronchitis (as diagnosed by a physician) were significantly higher in children 

exposed both to ETS and to formaldehyde concentrations of over 60 parts per 

billion than in children with one or none of these exposures. The authors also 

reported that similar effects were not seen in adults. 

Dijkstra and collaborators (1990) obtained consent for participation in 

their study for 1,051 of a total of 1,314 (80%) eligible 6- to 12-year-old 

schoolchildren from a rural area in The Netherlands. Parents completed a 

self-administered questionnaire on their smoking habits and on respiratory 

symptoms in their children. Complete information was available for 775 

children. When compared to children of nonsmoking households, children 

exposed to ETS at home were significantly more likely to have cough on most 

days for at least 3 months consecutively (OR = 2.5, 95% C.I. = 1.1, 5.6), wheezy 

or whistling sounds in the chest in the last year (OR = 1.9; 95% C.I. = 1.0, 3.5), 

and attacks of shortness of breath with wheeze in the last year (OR = 2.0; 95% 

C.I. = 0.9, 4.2). Exposed children were significantly more likely to have one or 

more of the above symptoms than were unexposed children (OR = 2.0; 95% C.I. 

= 1.2, 3.7). Results were still significant after adjusting for parental respiratory 

symptoms and for maternal smoking during pregnancy. The authors also 

measured nitrogen dioxide in the homes of all children but found no association 

of the latter with respiratory symptoms. 

Mertsola and coworkers (1991) followed prospectively for 3 months 54 

patients aged 1 to 6 years from Turku, Finland, who had a history of recurrent 

attacks of wheezy bronchitis. The parents were told to record the symptoms of 

the child daily and were asked to bring their child to the hospital emergency 

room if the child developed signs of an acute respiratory infection. Incidence of 

prolonged wheezing episodes (> 4 days) during followup was significantly more 

likely in children exposed to ETS than in unexposed children (OR = 4.8; 95% 

C.I. = 1.9, 12.6). The result was independent of number of siblings, age, sex, 

medication, and personal history of allergy. 

7.5.2. Summary and Discussion on Cough, Phlegm, and Wheezing 

Recent studies reviewed in this report that were not included either in the 

Surgeon General's report (U.S. DHHS, 1986) or in the NRC report (1986) 

substantially confirm the conclusions reached in those two reports. There is 

sufficient evidence for the conclusion that ETS exposure at home is causally 

associated with respiratory symptoms such as cough, phlegm, or wheezing in 

children. 

7-43 
The evidence is particularly strong for infants and preschool children; in 

this age range, most studies have found a significant association between 

exposure to ETS (and especially to maternal smoking) and respiratory symptoms 

in the children, with odds ratios generally ranging between 1.2 and 2.4. 

Selection bias may have influenced the results of certain cross-sectional studies; 

retrospective studies also may have been biased by preferential recall of their 

children's symptoms by smoking parents. However, the presence of a causal 

relationship is strongly supported by the consistency of the results for different 

geographic areas (Japan, Korea, People's Republic of China, Europe, and North 

America) and by the positive findings in prospective studies that are less subject 

to selection and recall biases. 

In addition, efforts have been made by all researchers to control for 

possible confounders and to avoid sources of bias. It is not feasible for each 

study to take into account all possible factors that may affect the relationship 

under study; some of these factors may even be unknown at present. However, 

all reviewed studies have controlled for at least some of the best-known 

confounders (family history of respiratory illnesses, parental respiratory 

symptoms, socioeconomic status, crowding, presence of other siblings, home 

dampness, gas cooking, maternal level of education, perinatal problems, low 

birthweight, maternal age, birth rank, and maternal stress, or depression). Of 

these possible confounders, a history of respiratory symptoms in parents has 

been particularly scrutinized. The NRC report (1986) noted that bias may be 

introduced by parents who have a history of respiratory illnesses for several 

reasons. These parents may overstate their children's symptoms, or their 

children actually may have more respiratory illnesses and symptoms. The latter 

possibility could be the result of intrafamily correlation of susceptibility 

(referred to as familial resemblance by Kauffmann and coworkers [1989a]). 

Because smokers are more likely to have respiratory symptoms, one would 

expect that controlling for respiratory symptoms in parents would result in a 

decrease in statistical significance of the relationship between ETS and 

symptoms in the child. In fact, most recent studies that have addressed the issue 

report that controlling for family history of respiratory symptoms decreases but 

does not entirely explain the increased risk of respiratory symptoms in young 

children exposed to ETS. It has been stressed, however, that the use of these 

statistical adjustment procedures may induce an underestimation of the effect of 

passive smoking; this would indeed be the case if parents with symptoms (and 

thus more likely to be smokers) were more prone to report symptoms in their 

children than were parents without symptoms. Several studies also have found 

that the effect is independent of maternal smoking during pregnancy and cannot 

be attributed exclusively to intrauterine exposure to tobacco products (although 

the latter may potentiate the effects of postnatal exposure to ETS). 

7-44 
The evidence is significant but less compelling for a relationship between 

exposure to ETS and respiratory symptoms in school-age children. Odds ratios 

for this age group are usually between 1.1 and 2.0. Several studies have shown 

that, among school-age children, there are significant differences in 

susceptibility to ETS exposure between individuals. There is, in fact, evidence 

showing that several factors may amplify the effects of passive smoking: 

prematurity, a family history of allergy, a personal history of respiratory illnesses 

in early childhood, and being exposed to other environmental pollutants such as 

formaldehyde. In addition, long-term exposure may have more important effects 

than short-term exposure. One study of 7-year-old children (Strachan, 1988; 

Strachan et al., 1990) used both questionnaires regarding smoking habits in the 

household and the child's saliva cotinine levels as indices of exposure to ETS. 

The authors found a significant increase in the risk of having frequent cough 

when the questionnaire was used to ascertain exposure, but no association 

between saliva cotinine levels and frequency of cough. As the authors remarked, 

biochemical markers permit characterization of recent tobacco smoke exposures, 

but they may not adequately reflect exposure at some critical period in the past. 

Recent studies of intraindividual variability of cotinine levels also have 

suggested that it may be misleading to assess the validity of questionnaire 

measures against a single determination of a biologic marker (Coultas, 1990b; 

Idle, 1990). It is thus possible that associations evaluated with salivary cotinine 

are likely to underestimate the true relationship between passive smoking and 

respiratory morbidity (Strachan et al., 1990). 

In the case of older children who may have started experimenting with 

cigarettes, the confounding effects of active smoking need to be considered. 

Most researchers have been aware of this problem and have attempted to control 

for it. A great difficulty lies in misclassification of smokers due to 

underreporting. Young persons may be reluctant to admit smoking cigarettes. 

Data are often obtained from parents, who may not be aware of the child's 

smoking. 

In summary, this report concludes that ETS exposure at home causes 

increased prevalence of respiratory symptoms in infants and young children. 

There is also good evidence indicating that passive smoking causes respiratory 

symptoms in some older children, particularly in children who have predisposing 

factors that make them more susceptible to the effects of ETS. 

7.6. EFFECT OF PASSIVE SMOKING ON ASTHMA 

Studies addressing the effects of passive smoking on frequency of asthma 

were directly reviewed only in the Surgeon General's report (U.S. DHHS, 1986) 

and not explicitly in the report on environmental tobacco smoke by the NRC 

(1986). The Surgeon General's report concluded that epidemiologic studies of 

children had shown no consistent relationship between the report of a doctor's 

7-45 
diagnosis of asthma and exposure to involuntary smoking. The report pointed 

out that, although one study had shown an association between involuntary 

smoking and asthma (Gortmaker et al., 1982), others had not (Schenker et al., 

1983; Horwood et al., 1985). This variability was attributed to differing ages of 

the children studied, differing exposures, or uncontrolled bias. The report also 

concluded that maternal cigarette smoking may influence the severity of asthma. 

Alteration of nonspecific bronchial responsiveness was proposed as a 

mechanism for this latter effect. 

7.6.1. Recent Studies on the Effect of Passive Smoking on Asthma in Children 

Several new cross-sectional and longitudinal studies published after the 

U.S. Surgeon General's report (U.S. DHHS, 1986) was released have addressed 

the relationship between frequency, incidence, and severity of asthma and 

parental cigarette smoke (Table 7-7). (Studies on the relationship between ETS 

exposure and bronchial responsiveness were reviewed in Section 7.2.4.) 

Burchfield and coworkers (1986) studied 3,482 nonsmoking children and 

adolescents ages 0 to 19 years out of 4,378 eligible subjects from Tecumseh, 

Michigan. Subjects or their parents (for children aged 15 years or younger) 

answered questionnaires on past history of asthma and other respiratory 

conditions. Information on parental smoking habits was obtained from each 

parent. Prevalence rates of asthma were higher among children whose parents 

both had smoked during the child's lifetime than among children whose parents 

had never smoked. The effect was stronger and only reached statistical 

significance for males (OR for boys = 1.7, 95% C.I. = 1.2, 2.5 in boys; OR for 

girls = 1.2, 95% C.I. = 0.8, 1.9). Children with one parental smoker were not 

more likely to have asthma than was the unexposed reference group. When 

results were stratified by parental history of respiratory conditions, there was 

some reduction in the magnitude of the parental smoking effects, but results 

remained significant for asthma in males. Results were also independent of age, 

parental education, family size, a diagnosis of hay fever, and a history of other 

allergies. Reporting bias and diagnostic bias may in part explain the 

relationships reported in this study; smoking parents may be more likely to 

report asthma in their children, and physicians may be more prone to diagnose 

asthma in children of smoking parents. 

D. Evans and coworkers (1987) studied 191 out of 276 children aged 4 to 

17 years from low- income families who were receiving health care for 

physician-diagnosed asthma in New York. Excluded children were younger and 

had fewer emergency room visits for asthma than those with complete data. The 

authors suggested that the latter subjects had more severe asthma than the 

general community population of low-income children with asthma. Emergency 

room visits and hospitalizations for asthma were assessed by reviewing hospital 

records. Passive smoking by the child was measured by asking one parent if he 

7-46 
or she or anyone else in the house smoked. Authors did not differentiate 

between maternal and paternal smoking; no attempt was made to assess the 

degree of exposure to cigarette smoke. Eight children who were active smokers 

were excluded. There was a significant correlation between number of 

emergency room visits and cigarette smoke exposure (p = 0.008); the mean 

frequency (± SD) of annual emergency room visits observed for children 

exposed to passive smoking was 3.1 ± 0.4, compared with 1.8 ± 0.3 for children 

from nonsmoking households. Passive smoking had no effect on either the 

frequency of days with asthma symptoms or on the annual frequency of 

hospitalizations. Results were independent of ethnicity and parental 

employment status. The association could have been explained by lower 

compliance with prescribed treatment of their children's asthma by smoking 

parents, but the authors found no significant differences in compliance (as 

assessed by an index of asthma self-management activities) between smoking 

and nonsmoking parents. The authors estimated that the additional cost for 

emergency care for asthma was $92 ± $68 per family per year. 

O'Connor and coworkers (1987) performed bronchial challenges with 

subfreezing air in 292 subjects 6 to 21 years of age. They were selected from 

879 eligible subjects of the same age who were participating in a longitudinal 

study on respiratory illnesses in East Boston. An attempt was made to include as 

many subjects as possible who reported a history of asthma or wheezing on 

standardized questionnaires. Therefore, the latter group of subjects were 

overrepresented among those tested. The change in FEV1 caused by subfreezing 

air was significantly higher in asthmatic subjects whose mothers smoked at least 

one cigarette per day than in those whose mothers were nonsmokers. This 

relationship was independent of age, sex, height, personal smoking, paternal 

smoking, atopy, and baseline lung function. There was no relationship between 

maternal smoking and response to cold air among nonasthmatics. 

7-47 
Table 7-7. Recent epidemiologic studies of effects of passive smoking on asthma in childhood 

Authors Population studied 

ETS exposure assessment Outcome variable Results1 

Burchfield et al. (1986) 

3,482 nonsmoking children 0to 19 yr. in Tecumseh, Michigan 

Questionnaire answered by subjects or parents 

Prevalence of asthma OR = 1.7 (1.2, 2.5) for

boys; OR = 1.2 (0.8, 1for girls 

D. Evans et al. (1987) 191 children aged 4 to 17 yr. Parental questionnaire Emergency room

in New York, New York visits and 

hospitalizations forasthma (from medical 

records) 

3.1 ± 0.4 vs. 1.8 ± 0.3 (p=0.008) emergency room visits in children smoking and non-smokparents 

7-48 

O'Connor et al. (1987) 

292 subjects aged 6 to 21 yr.in Boston, Massachusetts 

Parental questionnaire Bronchial response to

cold air 

Significantly increasedresponse in asthmatics whose mothers smoked 

(contin
Table 7-7. (continued) 

Authors Population studied 

ETS exposure assessment Outcome variable Results1 

Murray and Morrison(1989) 

415 children aged 1 to 17 yr.with asthma in Vancouver, 

Canada 

Parental questionnaire Asthma symptom 

score for severity ofasthma 

Higher scores (p<0.01) children of smoking mothers 

Krzyzanowskiet al. (1990) 

298 children aged 5 to 15 yr.in Tucson, Arizona 

Parental questionnaire Parental reports of

asthma in their children 

OR = 9.0 (2.4, 34.0) fochildren exposed to ETand formaldehyde vs.nonexposed 

Sherman et al. (1990) 

770 children aged 5 to 9 yr.followed for 11 yr. in Boston,Massachusetts 

Parental and subjectquestionnaire 

Physician diagnosisof asthma 

No effect of parental smoking on prevalence incidence of asthma 

Weitzman et al. (1990) 

4,331 children aged 0 to 5 yr.(U.S. National HealthInterview Survey) 

Maternal questionnaire 

Asthma for at least 3 mo. at time of questionnaire 

OR = 2.1 (1.3, 3.3) forchildren whose mothersmoked $10 cig./day 

7-49 

(contin
Table 7-7. (continued) 

Authors Population studied 

ETS exposure assessment Outcome variable Results1 

Oldigs et al. (1991) 11 asthmatic children Direct exposure to ETS

for 1 hour 

Changes in lungfunction 

No effect 

Martinez et al. (1992) 

774 children aged 0 to 5 yr.followed for several years inTucson, Arizona 

Parental questionnaire Physician diagnosis of

asthma 

OR = 2.5 (1.4, 4.6) fchildren of low mateeducation whose mosmoked $10 cig./day 

Ehrlich et al. (1992) 

228 children; 72 with acute asthma; 35 with nonacute asthma and 121 controls 

Cotinine levels in urine of children; smoking by maternal caregiver 

Emergency roomand asthma clinic visits 

Higher levels of cotiin asthmatics OR = (1.0, 3.4) 

7-50 

195% confidence intervals in parentheses. 
 Murray and Morrison (1989) studied 415 nonsmoking children aged 1 to 

17 years consecutively referred to an allergy clinic in Vancouver, Canada, for 

asthma or recurrent wheezing of the chest. Questionnaires were administered to 

the parents of all children at the time of their first visit. Forced expiratory flows 

and bronchial reactivity to histamine also were measured. An asthma symptom 

score was calculated for each subject based on the severity of asthma and the 

need for medication, as reported by parents. Children of smoking mothers had 

significantly higher indices of asthma severity (p < 0.01) and significantly lower 

FEV1 (84.4% predicted vs. 77.3% predicted, p < 0.01) than did children of 

nonsmoking mothers. They were also significantly more responsive to histamine 

than were children of nonsmoking mothers (p = 0.01). The effect was present in 

both genders but was stronger for boys than for girls. Also, the effect was 

stronger for older children (12 to 17 years of age) than for children 6 years of 

age or younger. The authors also reported a positive correlation between length 

of exposure to ETS and asthma symptom score. It is unlikely that these results 

can be explained by parental overreporting because the association between 

passive smoking and severity of symptoms paralleled that between passive 

smoking and objective measurements of severity. 

In their previously reviewed report (Section 7.5.1), Krzyzanowski and 

coworkers (1990) found that children exposed to ETS and to more than 60 ppb 

of formaldehyde had significantly higher prevalence rates of asthma than those 

exposed to only one of these contaminants or to none (OR for the latter 

comparison = 9.0; 95% C.I. = 2.4, 34.0). No such association was seen among 

adult household members. It is unlikely that this association is attributable to 

parental overreporting of asthma because the authors relied on objective 

measurement of indoor formaldehyde concentrations. 

Sherman and collaborators (1990) reported on the results of a longitudinal 

study of determinants of asthma in a sample of 770 schoolchildren enrolled in 

East Boston in 1974. Questionnaires were used to obtain data on respiratory 

symptoms and illnesses, cigarette smoking history of parents and children, and 

household demographics. They were administered on entry and for 11 

consecutive years (1978-1988). Parents answered for children aged 9 or less, 

except for questions on the child's smoking history. The authors identified risk 

factors for the onset of asthma, the occurrence of which antedated the time of 

first diagnosis of asthma. There was no significant relationship between 

maternal smoking and either prevalence of asthma at the first survey or 

incidence of new cases of asthma during followup (sex-adjusted RR = 1.1; 95% 

C.I. = 0.7, 1.7). The authors considered it unlikely that this finding could be due 

to exposure levels too low to increase the risk of asthma. However, no effort 

was made to assess the relationship between incidence of asthma and number of 

cigarettes smoked by parents. Likewise, no effort was made to determine the 

7-51 
possible role of factors known to modify exposure to ETS such as parental 

socioeconomic level (Strachan et al., 1989). 

Weitzman and coworkers (1990) studied 4,331 children aged 0 to 5 years 

who were part of the U.S. National Health Interview Survey. Children were 

categorized as having asthma if their parents reported that asthma was current at 

the time of interview and had been present for more than 3 months. Mothers 

were asked about their smoking habits during and after pregnancy. Odds of 

having asthma were 2.1 times as high (95% C.I. = 1.3, 3.3) among children of 

mothers who smoked 10 or more cigarettes per day than among children of 

nonsmoking mothers. The risk of having asthma was not significantly increased 

in children of mothers who smoked fewer than 10 cigarettes per day. Use of 

asthma medication was also more frequent among children of mothers who 

smoked 10 or more cigarettes per day (OR = 4.1; 95% C.I. = 1.9, 8.9). Results 

did not change significantly after controlling for gender, race, presence of both 

parents, family size, and number of rooms in the households. No information 

was available on parental respiratory symptoms or socioeconomic status. The 

results of this study could be explained partially by overreporting of asthma by 

smoking mothers. 

Oldigs and collaborators (1991) exposed 11 asthmatic children to ETS and 

to ambient air for 1 hour. They found no significant difference in lung function 

or in bronchial responsiveness to histamine after ETS exposure when compared 

with sham exposure. The study was designed only to determine if acute 

exposures to ETS caused immediate effects, and it did not assess the changes 

induced by chronic exposure to ETS. 

Martinez and coworkers (1992) studied incidence of new cases of asthma 

in a population sample of 774 out of 786 eligible children aged 0 to 5 years 

enrolled in the Tucson study of chronic obstructive lung disease. At the time of 

enrollment, the child's parents answered standardized questionnaires about 

personal respiratory history and cigarette smoking habits. Surveys were 

performed on an approximately yearly basis, and parents were asked if the child 

had been seen by a doctor for asthma in the previous year. There were 89 

(11.5% of the total) new cases of asthma during followup. Children of mothers 

with 12 or fewer years of formal education and who smoked 10 or more 

cigarettes per day were 2.5 times as likely (95% C.I. = 1.4, 4.6) to develop 

asthma as were children of mothers with the same education level who did not 

smoke or who smoked fewer than 10 cigarettes per day. This relationship was 

independent of self-reported symptoms in parents. Decrements in lung function 

paralleled the increase in asthma incidence. No relationship was observed 

between maternal smoking and asthma incidence among children of mothers 

with more than 12 years of formal education. 

Ehrlich et al. (1992) studied 72 children with acute asthma recruited in the 

emergency room; 35 nonacute asthmatic children from an asthma clinic; and 121 

7-52 
control children without asthma from the emergency room. They assessed 

exposure to ETS both by questionnaire and by measurement of urinary levels of 

cotinine/creatinine ratios. Smoking by maternal caregiver was significantly 

more prevalent among asthmatic children (OR = 2.0, 95% C.I. = 1.1, 3.4). This 

was confirmed by a significant difference between groups in prevalence of 

cotinine to creatinine ratio of greater or equal to 30 ng/mg (OR = 1.9; 95% C.I. = 

1.0, 3.4). There was no difference in exposure indices between acute and 

nonacute asthmatics. The authors concluded that smoking by a maternal 

caregiver was a significant risk factor for clinically significant asthma in 

children. 

7.6.2. Summary and Discussion on Asthma 

There is now sufficient evidence to conclude that passive smoking is 

causally associated with additional episodes and increased severity of asthma in 

children who already have the disease. Several studies have found that bronchial 

responsiveness is more prevalent and more intense among asthmatic children 

exposed to maternal smoke. Emergency room visits are more frequent in 

children of smoking mothers, and these children also have been found to need 

more medication for their asthma than do children of nonsmoking mothers (see 

Table 7-4). 

A simple bronchospastic effect of cigarette smoke is probably not 

responsible for the increased severity of symptoms associated with passive 

smoking because acute exposure to ETS has been found to have little immediate 

effect on lung function parameters and airway responsiveness in asthmatic 

children. Therefore, the mechanisms by which passive smoking enhances 

asthma in children who already have the disease are likely to be similar to those 

responsible for inducing asthma and entail chronic exposure to relatively high 

doses of ETS (see discussion below). Murray and Morrison (1988) reported that 

ETS exposure decreased lung function and increased medication requirements in 

asthmatic children only during the cold, wet season and not during the dry, hot 

season in Vancouver, Canada. These seasonal differences may be at least partly 

explained by the finding by Chilmonczyk and collaborators (1990) that urine 

cotinine levels of children exposed to ETS are significantly higher in winter than 

in summer. These seasonal fluctuations also suggest that the effects of passive 

smoking on asthma severity are reversible and that decreasing exposure to ETS 

could prevent many asthmatic attacks in affected children. 

New evidence available since the Surgeon General's report (U.S. DHHS, 

1986) and the NRC report (1986) also indicates that passive smoke exposure 

increases the number of new cases of asthma among children who have not had 

previous episodes (see Table 7-7 for results and references). Although most 

studies are based on parental reports of asthma, it is highly unlikely that the 

relationship between asthma and ETS exposure is entirely attributable to 

7-53 
reporting bias. In fact, concordance in the relationship between ETS exposure 

and both questionnaires and objective parameters such as lung function or 

bronchial provocation tests has been reported in several studies. The association 

is also biologically plausible; the mechanisms that are likely to be involved in 

the relationship between ETS exposure and asthma have been discussed 

extensively in Section 7.2. The consistency of all the evidence leads to the 

conclusion that ETS is a risk factor for inducing new cases of asthma. The 

evidence is suggestive of a causal association but is not conclusive. 

Data suggest that levels of exposure required to induce asthma in children 

are high; in fact, most recent and earlier studies that classified children as 

exposed to ETS if the mother smoked one cigarette or more usually failed to find 

any effect of ETS on asthma prevalence or incidence. Furthermore, two recent 

large studies found an increase in the prevalence (Weitzman et al., 1990) or 

incidence (Martinez et al., 1992) of asthma only if the mother smoked 10 

cigarettes or more per day. It is also important to consider that, for any level of 

parental smoking, exposure to ETS is higher in children belonging to families of 

a lower socioeconomic level (Strachan et al., 1989) and that the relationship of 

maternal smoking to asthma incidence may be stronger in such families 

(Martinez et al., 1992). Concomitant exposure to other pollutants also may 

enhance the effects of ETS (Krzyzanowski et al., 1990). 

7.7. ETS EXPOSURE AND SUDDEN INFANT DEATH SYNDROME 

The relationship between ETS exposure and sudden infant death syndrome 

(SIDS) was not addressed in either the Surgeon General's report (U.S. DHHS, 

1986) or in the NRC report (1986). Because of the importance of this syndrome 

as a determinant of infant mortality and because of the available evidence of an 

increased risk of SIDS in children of smoking mothers, the issue has been added 

to this report (Table 7-8). 

SIDS is the most frequent cause of death in infants aged 1 month to 1 year. 

Approximately 2 of every 1,000 live-born infants (more than 5,000 in the United 

States alone each year) die suddenly and unexpectedly, usually during sleep, and 

without significant evidence of fatal illness at autopsy (CDC, 1989b). The cause 

or causes of these deaths are unknown. The most widely accepted hypotheses 

suggest that some form of respiratory failure is involved with most cases of 

SIDS. 

In 1966, Steele and Langworth (1966) first reported that maternal smoking 

was associated with an increased incidence of SIDS. They studied the hospital 

records of 80 infants who had died of SIDS in Ontario, Canada, during 

1960-1961 and compared them with 157 controls matched for date of birth, sex, 

hospital at which the child was born, and parity of the mother. Infants of 

mothers who smoked 1 to 19 cigarettes per day were twice as likely (OR = 2.1; 

95% C.I. = 1.1, 3.8) to die of SIDS as were infants of nonsmoking mothers. The 

7-54 
odds ratio was 3.6 (95% C.I. = 1.7, 7.9) when infants of mothers who smoked 20 

or more cigarettes per day were compared to infants of nonsmoking mothers. 

The authors reported that the risk of dying of SIDS was higher in 

low-birthweight infants whose mothers smoked when compared with 

low-birthweight infants whose mothers did not smoke. However, they made no 

effort to control for other confounders that were related both to maternal 

smoking and to SIDS, such as maternal age and socioeconomic status. In 

addition, they made no reference to the relative roles of in utero exposure to 

tobacco smoke products and postnatal ETS exposure. 

Naeye and collaborators (1976) studied 59,379 infants born between 1959 

and 1966 in participating hospitals from several U.S. cities. After meticulous 

investigation of clinical and postmortem material, they identified 125 of these 

infants (2.3 per 1,000 live births) as having died of SIDS and compared them 

with 375 infants matched for place of birth, date of delivery, gestational age, sex, 

race, and socioeconomic status. Infants of mothers who smoked were more than 

50% more likely (OR = 1.6; 95% C.I. = 1.0, 2.4) to die of SIDS than were those 

of mothers who denied smoking. When compared with the latter, infants of 

mothers who smoked six or more cigarettes per day were 2.6 times more likely 

(95% C.I. = 1.7, 4.0) to die of SIDS. The authors made no attempt to distinguish 

between in utero exposure to tobacco smoke products and ETS exposure after 

birth. 

Bergman and Wiesner (1976) selected 100 well-defined cases of SIDS 

occurring in white children in King County, Washington. These cases were 

matched for race, sex, and birth date with 100 controls. Questionnaires were 

mailed to the mothers of cases and controls, but only 56 cases and 86 controls 

returned them. Mothers who did not respond tended to be younger and poorer. 

A higher proportion of mothers of SIDS victims smoked cigarettes during 

pregnancy (61% vs. 42%). Infants of mothers who smoked after delivery were 

2.4 times as likely (95% C.I. = 1.2, 4.8) to die of SIDS as were infants of 

nonsmoking mothers. The relationship between postnatal exposure to ETS and 

SIDS was significantly stronger and only reached statistical significance for 

mothers aged 25 years or less (OR = 4.4; 95% C.I. = 1.7, 11.2). Infants of 

mothers aged 25 years or less who smoked 20 or more cigarettes per day were 

7.7 times as likely to die of SIDS (95% C.I. = 1.7, 35.4) as were infants of 

nonsmoking mothers. Effects were independent of maternal education. The 

authors did not try to determine the independent effects of prenatal and postnatal 

exposures to maternal smoking on the incidence of SIDS. 

7-55 
Table 7-8. Epidemiologic studies of effects of passive smoking on incidence of sudden infant death syndrome (SIDS) 

Authors Population studied 

ETS exposure assessment Results1 Ob

Steele and Langworth(1966) 

80 infants who died of SIDS; 157 matched controls in Ontario, Canada 

Maternal report fromhospital record at birth 

OR = 2.1 (1.1, 3.8) when mother smoked 1 to 19 cig./day; OR = 3.6 (1.7,7.9) when mother smoked $20 

cig./day 

No ecoma

Naeye et al. (1976) 59,379 infants born in several 

U.S. cities 

Maternal report fromhospital record at birth 

OR = 1.6 (1.0, 2.4) for any maternal smoking; OR = 2.6(1.7, 4.0) for mothers smoking 

$6 cig./day 

Cobirgean

Bergman and Wiesner 

(1976) 

100 cases of SIDS; 100 matched controls in KingCounty, Washington 

Maternal question-naireanswered after death (orat equivalent age forcontrols) 

OR = 2.4 (1.2, 4.8);effect only significantfor mothers #25 yr.

(OR = 4.4 [1.7, 11.2]) 

Indedbir

Lewak et al. (1979) 44 cases of SIDS Maternal questionnaire OR = 4.4 (2.1, 9.2) No 

co

Malloy et al. (1988) 305,000 births in Missouri Maternal reports on birth

certificate 

OR = 1.8 (1.4, 2.2) Co

staedbir

7-56 

(contin
Table 7-8. (continued) 

Authors Population studied 

ETS exposure assessment Results1 Ob

Hoffman et al. (1988) 800 SIDS cases; 

1,600 controls (NICHDcooperative study) 

Maternal questionnaire OR = 3.4 (p<0.005) Co

bir

Haglund and Cnattingius(1990) 

279,000 births in Sweden Maternal questionnaire OR = 1.8 (1.2, 2.6). 

smoking mother: 

(1.9, 3.9) 

Indbirsocan

Mitchell et al. (1991) 162 SIDS cases; 

3 to 4 times as many controls 

Parental questionnaire Cig./day 

1 to 9 10 to 19 

$20 

Indcaredsexpaseabre

HeavyOR = 2.7 

OR 

1.9 (1.0, 3.5)

2.6 (1.5, 4.7) 

5.1 (2.9, 9.0) 

7-57 195% confidence intervals in parentheses. 
 Lewak and coworkers (1979) studied all infants who died during the first 

year of life and who were enrolled in a health plan in Oakland, California. Using 

predefined criteria, they classified 44 infants (2.3 per 1,000 live births) as having 

died of SIDS and compared them with the rest of the population for several 

possible risk factors for SIDS. Mothers of infants who died of SIDS were 4.4 

times (95% C.I. = 2.1, 9.2) as likely to be smokers as mothers of infants who 

survived. Paternal smoking had no significant influence on SIDS frequency. 

The authors made no effort to control for possible confounding factors, nor did 

they discriminate between the possible roles of prenatal and postnatal exposure 

to tobacco smoke products. 

Malloy and coworkers (1988) linked birth and death certificates to study 

possible risk factors for neonatal and postneonatal mortality in over 305,000 

singleton white live births in Missouri. They identified 372 infants whose deaths 

were attributed to SIDS (1.2 per 1,000 live births). Infants whose mothers 

smoked were 1.8 times as likely (95% C.I. = 1.4, 2.2) to die of SIDS than were 

infants of nonsmoking mothers. This relationship was independent of maternal 

marital status, education level, age, parity, and child's birthweight. There were 

no data available that would have allowed one to differentiate the effects of 

prenatal and postnatal exposure to tobacco smoke products. 

Hoffman and collaborators (1988) reported on the results of the National 

Institute of Child Health and Human Development Cooperative Epidemiological 

Study of Sudden Infant Death Syndrome risk factors. They studied 800 SIDS 

cases and 1,600 control infants collected at six study centers across the United 

States. Control infants were matched for age only (N = 800) or for age, low 

birthweight, and race (N = 800). SIDS cases were 3.8 and 3.4 times as likely to 

have smoking mothers as the first and second control groups mentioned earlier, 

respectively (p < 0.005 for both comparisons). There were no data on prenatal 

and postnatal exposure to tobacco smoke products. 

Haglund and Cnattingius (1990) examined risk factors for SIDS in a 

prospective study based on more than 279,000 Swedish infants who survived the 

first week of life. SIDS was reported as the sole cause of death in 190 infants 

(0.7 per 1,000), and in most cases the diagnosis was confirmed by the results of 

an autopsy. Infants of mothers who smoked one to nine cigarettes per day were 

1.8 times as likely (95% C.I. = 1.2, 2.6) to die of SIDS as were infants of 

nonsmoking mothers. Infants of mothers who were heavy smokers had an even 

higher risk (OR = 2.7; 95% C.I. = 1.9, 3.9) of dying of SIDS, suggesting an 

exposure-response relationship. These findings were independent of 

birthweight, maternal age, social situation, parity, sex, and type of birth. No 

information was available regarding smoking in the household by either mother 

or father after the infant's birth. 

Mitchell and coworkers (1991) studied SIDS cases occurring in several 

health districts in New Zealand between November 1, 1987, and October 31, 

7-58 
1988. After careful assessment of the material available from necropsy, 162 

infants were classified as having died of SIDS (3.6 per 1,000 live births). These 

cases were matched for age with three to four times as many controls. The 

researchers interviewed the parents and obtained complete information for 128 

cases and 503 controls. Information on maternal smoking during pregnancy (as 

a yes/no variable) was obtained from the obstetric records, whereas information 

on number of cigarettes smoked by the mother in the 2 weeks preceding the 

interview was obtained from questionnaires. Mothers of infants who died of 

SIDS were 3.3 times as likely (95% C.I. = 2.2, 5.0) to smoke during pregnancy 

as were mothers of controls. The analysis of the relationship between maternal 

smoking after the child's birth and frequency of SIDS showed clear evidence of a 

biological gradient of risk. Odds ratios were as follows: 1.9 (95% C.I. = 1.0, 

3.5) for mothers who smoked 1 to 9 cigarettes per day; 2.6 (95% C.I. = 1.5, 4.7) 

for mothers who smoked 10 to 19 cigarettes per day; and 5.1 (95% C.I. = 

2.9, 9.0) for mothers who smoked 20 or more cigarettes per day. The association 

between maternal smoking and SIDS frequency was independent of antenatal 

care, maternal age, maternal education, marital status, sex, neonatal problems, 

parity, socioeconomic status, birthweight, gestational age, race, season of death, 

sleep position at death, and breastfeeding. 

In summary, there is strong evidence that infants whose mothers smoke 

are at increased risk of dying suddenly and unexpectedly during the first year of 

life. This relationship is independent of all other known risk factors for SIDS, 

including low birthweight and low gestational age. The finding that there is a 

biological gradient of risk extending from nonsmoking mothers to those smoking 

more than 20 cigarettes per day adds to the evidence that exposure to cigarette 

smoke products is involved in the sequence of events that result in SIDS. 

Available studies cannot differentiate the possible effects with respect to SIDS of 

exposure to tobacco smoke products in utero from those related to passive 

smoking after birth. As explained earlier (Section 7.2.2), both human and 

animal studies show that maternal smoking during pregnancy may modify and 

potentiate the effects of postnatal ETS exposure. The relationship between 

maternal smoking and SIDS is independent of low birthweight, which is the 

most important known effect of maternal smoking during pregnancy. In 

addition, the incidence of SIDS is apparently associated with days of higher air 

pollution levels (Hoppenbrouwers et al., 1981), which could indicate a direct 

effect of airborne contaminants. 

In view of the fact that the cause of SIDS is still unknown, it is not 

possible to assess the biological plausibility of the increased incidence of SIDS 

related to ETS exposure. Consequently, at this time this report is unable to 

assert whether or not passive smoking is a risk factor for SIDS. 

7-59 
7.8. PASSIVE SMOKING AND LUNG FUNCTION IN CHILDREN 

The Surgeon General's report (U.S. DHHS, 1986) reviewed 18 

cross-sectional and longitudinal studies on the effects of ETS exposure on lung 

function in children (Table 7-9). The report concluded that "the available data 

demonstrate that maternal smoking reduces lung function in young children" 

(page 54). The hypothesis was proposed that passive smoking during childhood, 

by affecting the maximal level of lung function attainable during early adult life, 

may increase the subsequent rate of decline of lung function and, thus, increase 

the risk of chronic obstructive lung disease. 

The NRC report (1986) reached similar conclusions after reviewing 12 

articles (Table 7-9). The authors' summary asserted that "estimates of the 

magnitude of the effect of parental smoking on FEV1 function in children range 

from 0 to 0.5% decrease per year. This small effect is unlikely by itself to be 

clinically significant. However, it may reflect pathophysiologic effects of 

exposure to ETS in the lungs of the growing child and, as such, may be a factor 

in the development of chronic airflow obstruction in later life" (page 215). 

7.8.1. Recent Studies on Passive Smoking and Lung Function in Children 

Studies appearing since the 1986 reports are presented in Table 7-10. 

Lung function measurements were included in the cross-sectional study by 

O'Connor and collaborators (1987) described earlier (Section 7.6.1). When 

compared to 97 nonasthmatic children of nonsmoking mothers (mean age ± 

SEM = 12.8 ± 0.3 years), 168 nonasthmatic children of smoking mothers (mean 

age ± SEM = 12.9 ± 0.2 years) had significantly lower mean percentage of 

predicted FEV1 (mean ± SEM = 108.0 ± 1.4 vs. 101.4 ± 1.1, respectively, p < 

0.001) and significantly lower FEF25-75 (103.0 ± 2.3 vs. 88.2 ± 1.5, respectively, p 

< 0.001). These effects were independent of personal smoking by the child. 

Lebowitz and coworkers (1987) reported on the results of a longitudinal 

study of pulmonary function development in Tucson, Arizona. The authors 

analyzed 1,511 observations over an average followup period of 8.8 years in 353 

subjects aged 5.5 to 25 years. The last available lung function value (as 

residuals after regressing the data with different power functions of age and 

height) was used as outcome. Residuals for vital capacity were significantly 

higher among subjects aged 14 years or less at entry whose mothers smoked 

cigarettes (mean = +3.3 vs. -1.4 among nonexposed subjects, p < 0.001). 

Parental smoking had no direct effect on outcome FEV1 or Vmax50%, but showed 

significant interactions with personal smoking and parental history of airway 

obstructive diseases in their effects on Vmax50%; subjects who had started 

smoking or whose parents had airway obstructive diseases and were exposed to 

ETS had the lowest Vmax50% residuals at the end of followup. 

7-60 
Table 7-9. Studies on pulmonary function referenced in the Surgeon General's and

National Research Council's reports of 1986 

Study 

No. of 

subjects Age of subjects 

Surgeon

General NRC 

Berkey et al. (1986) 7,834 Children (6 to 10) X X 

Brunekreef et al. 

(1985) 

173 Adult women X 

Burchfield et al. 

(1986) 

3,482 Infants/children (0 to

10) 

X 

Chen and Li (1986) 571 Children/adol. (8 to

16) 

X 

Comstock et al. 

(1981) 

1,724 Adults X 

Dodge (1982) 558 Children (8 to 10) X X 

Ekwo et al. (1983) 1,355 Children (6 to 12) X 

Ferris et al. (1985) 10,000 Children/adol. (6 to

13) 

X 

Hasselblad et al. 

(1981) 

16,689 Children (5 to 17) X X 

Kauffmann et al. 

(1983) 

7,818 Adults X 

Kentner et al. (1984) 1,851 Adults X 

Lebowitz (1984) 117 Families X 

Lebowitz and 

Burrows (1976) 

271 Children/adol. (<16) X X 

Schilling et al.

(1977) 

816 Children/adol. (<18) X X 

Tager et al. (1979) 444 Children (5 to 19) X 

Tager et al. (1983) 1,156 Children (5 to 9) X X 

Tashkin et al. (1984) 1,080 Children (7 to 17) X X 

Vedal et al. (1984) 4,000 Children (6 to 13) X 

Ware et al. (1984) 10,106 Children (6 to 13) X 

Weiss et al. (1980) 650 Children (5 to 9) X X 

White and Froeb 

(1980) 

2,100 Adults X 

X 

7-62
Table 7-10. Recent epidemiologic studies on the effects of passive smoking on lung function in children 

Authors Population studied 

ETS exposure assessment Results1 Ob

O'Connor et al. (1987) 

97 children (12.8 ± 0.3 yr.) of smoking mothers; 168 children (12.9 ± 0.2 yr.) of nonsmoking mothers in Boston, 

Massachusetts 

Parental questionnaire Nonsmoking mothers vs. 

smoking mothers: 1 (%

predicted) 108.0 ± 1.4 vs.101.4 ± 1.1 (p<0.001);FEF25-75 (% predicted) 103.0 ±

2.3 vs. 88.2 ± 1.5 (p<0.001) 

Indsm

Lebowitz et al. (1987) 

353 subjects aged 5.5 to 25 yr. inTucson, Arizona 

Parental questionnaire Smoking mothers vs. nonsmoking mothers FVC 

(residuals) +3.3 vs. -1.4(p<0.001) 

Inthisillnsm

res

Tsimoyianis et al.(1987) 

132 athletes exposed to ETS;61 athletes not exposed to ETS 

Self-reported exposure toETS 

OR of having lowFEF25-75 4.7 (1.1-20.8) 

Kauffmann et al. (1989b) 

1,160 French children Parental questionnaire Loss of 10 mL of FEV1, 

(p=0.05); loss of 15 mL/sec of FEF25-75 (p<0.01) 

Indof weagfun

Chan et al. (1989b) 

130 children of low birthweight atage 7 yr. in England 

Maternal reports ofcigarette smoking 

Mean Vmax75% (% predicted)

in exposed vs. nonexposed80.7 vs. 91.4 (p<0.01) 

Indbirrestre

FEV

7-65 

(contin
Table 7-10. (continued) 

Authors Population studied 

ETS exposure assessment Results1 Ob

Dijkstra et al.(1990) 

634 children aged 6 to 12 yr.in The Netherlands 

Parental questionnaire Decrease in: 

FEV1 (-1.8% [-0.2 to 

-3.31]);FEF25-75% (-5.21% [-1.4 to -

8.8]);PF (-2.8% [0.6 to -4.8]) 

Indsm

Strachan et al. (1990) 

757 children in Scotland Salivary cotinine levels Negative correlation with

FEF25-75% (p<0.05) andVmax75% (p<0.05) 

Apbetexp

Martinez et al. (1992) 

774 children enrolled at age 0 to 5in Tucson, Arizona, and followed for several years 

Parental questionnaire 15% lower levels of % 

predicted FEF25-75% among

children of mothers who smoked and had a low level of education 

7-66 

195% confidence intervals in parentheses. 
 In subsequent reports, Lebowitz and Holberg (1988) and Tager and 

coworkers (1987) reanalyzed two sets of longitudinal pulmonary function data: 

the one on which the preceding study from Tucson, Arizona, was based 

(Lebowitz et al., 1987) and data for children of similar age from East Boston, 

Massachusetts (Tager et al., 1983). The objective was to determine if the 

different answers with regard to the effect of maternal smoking (significant for 

the Boston study; no effect for the Tucson study) were due to the use of different 

statistical tools. Applying the same multivariable analysis of covariance for both 

data sets, Lebowitz and Holberg (1988) confirmed the positive effect of maternal 

smoking of FEF25-75% with the data from Boston (p < 0.05) and the lack of a 

significant effect of maternal smoking on Vmax50% with the data from Tucson, 

Arizona. A first-order autoregressive model applied by Tager and collaborators 

(1987) to both data sets showed effects of maternal smoking on FEV1 with the 

Boston data but not with the Tucson data. The authors concluded that the most 

likely factor responsible for the disparate results was the exposure difference in 

the two populations. 

Tsimoyianis and collaborators (1987) compared the prevalence of low 

levels of FEF25-75% (< 70% of predicted) in athletes exposed and unexposed to ETS 

(for more information on this study see Section 7.5.1). Of 132 exposed athletes, 

18 (13.6%) had low FEF25-75% compared with 2 of 61 (3.3%) unexposed athletes 

(OR = 4.7; 95% C.I.= 1.1, 20.8). 

Kauffmann and collaborators (1989b) assessed familial factors related to 

lung function in a cross-sectional study of 1,160 French children. Levels of lung 

function (FEV1 and FEF25-75%) were significantly lower in children with mothers 

who smoked when compared to those whose mothers were nonsmokers. The 

authors reported a loss of 10 mL of FEV1 (p < 0.05) and of 15 mL/s of FEF25-75% (p 

< 0.01) for every gram of tobacco smoked per day by the mother. These 

associations were independent of sex, town of origin, age, height, weight, and 

intrafamilial aggregation of lung function. There was no effect of paternal 

smoking on lung function. 

Chan and coworkers (1989b) performed lung function tests in a cohort of 

130 children of low birthweight (under 2,000 grams) at 7 years. These authors 

had previously reported on the respiratory outcome of these same children (see 

Section 7.5.1). Children of low birthweight whose mothers smoked had 

significantly lower values of percentage of predicted Vmax75% than did lowbirthweight children whose mothers did not smoke (80.7% vs. 91.4%, p < 0.01). 

This association was independent of sex, birthweight, neonatal respiratory 

illness, and treatment. As 92% and 79% of mothers who smoked when the child 

was 7 years old were smokers before and during their pregnancy, respectively, it 

was not possible to determine whether the effect of maternal smoking was fetal 

or postnatal. 

7-67 
The study by Dijkstra and collaborators (1990) has been described earlier 

(Section 7.5.1). The authors studied, together with respiratory symptoms, lung 

function and its relationship with indoor exposures to ETS and nitrogen dioxide 

in a population of 634 Dutch children 6 to 12 years of age. When compared with 

unexposed children, children exposed to ETS had significantly lower levels of 

FEV1 (!1.8%; 95% C.I. = !0.2, !3.3), FEF25-75% (!5.2%; 95% C.I. = !1.4, !8.8) and 

Peak Flow (!2.8%; 95% C.I. = !0.6, !4.8). Adjustment for smoking by the 

mother when she was pregnant with the investigated child removed little of the 

effect of current ETS exposure on lung function. The authors suggested that this 

indicated that the associations seen at ages 6 to 12 years were not just mirroring 

harm that was caused when the children were exposed in utero to tobacco smoke 

components inhaled by the mother. There was no association between exposure 

to NO2 and lung function. 

A previously mentioned study by Strachan and coworkers (1990) (Section 

7.5.1) included lung function measurements in 757 children. Lung function 

variables were adjusted for sex, height, and housing characteristics. The authors 

found a significant negative correlation between salivary cotinine concentrations 

and levels of FEF25-75% (p < 0.05) and Vmax75% (p < 0.05). For these indices, the 

difference between adjusted mean values for the top and bottom quintiles of 

salivary cotinine was of the order of 7% of the mean value in the children with 

undetectable levels. 

The longitudinal study by Martinez and coworkers (1992) has been 

reviewed earlier (Section 7.6.1). In addition to their findings on incidence of 

childhood asthma, these authors reported that, at the end of followup, children of 

mothers with 12 or fewer years of formal education and who smoked 10 or more 

cigarettes per day had 15% lower mean values for percentage of predicted 

FEF25-75% than did children of mothers of the same level of education who were 

nonsmokers or smoked fewer than 10 cigarettes per day. Maternal smoking had 

no effect on percentage of predicted FEF25-75% values in children of mothers who 

had at least some education beyond high school. Female children of smoking 

mothers ($ 10 cig./day) had 7% higher vital capacity than did female children of 

mothers who were nonsmokers or light smokers (< 10 cig./day), and this was 

independent of maternal education. All differences were still significant after 

controlling for parental history of respiratory disease. 

7.8.2. Summary and Discussion on Pulmonary Function in Children 

This report concludes that there is a causal relationship between ETS 

exposure and reductions in airflow parameters of lung function (FEV1, FEF25-75%, 

Vmax50%, or Vmax75%) in children. For the population as a whole, these 

reductions are small relative to the intraindividual variability of each lung 

function parameter; for FEF25-75%, for example, reductions range from 3% to 7% of 

the levels seen in unexposed children, depending on the study analyzed. Groups 

7-68 
of particularly susceptible or heavily exposed subjects have larger decrements: 

Exposed children of low birthweight, for example, had 12% lower Vmax75% than 

did children of similar birthweight who were not exposed to ETS (Chen, 1989). 

Likewise, children of less educated mothers who smoked 10 or more cigarettes 

per day were shown to have 15% lower mean FEF25-75% than children of less 

educated mothers who did not smoke or smoked fewer than 10 cigarettes per 

day. This stronger effect may be explained by Strachan and coworkers' (1989) 

finding that children of lower socioeconomic status have higher salivary cotinine 

levels, for any amount of parental smoking, than do children of higher 

socioeconomic status. 

The studies reviewed suggest that a continuum of exposures to tobacco 

products starting in fetal life may contribute to the decrements in lung function 

found in older children. In fact, exposure to tobacco smoke products inhaled by 

the mother during pregnancy may contribute significantly to these changes, but 

there is strong evidence indicating that postnatal exposure to ETS is an important 

part of the causal pathway. 

New longitudinal studies have demonstrated that young adults who were 

exposed earlier in life to ETS are also more susceptible to the effects of active 

smoking (Lebowitz et al., 1987). In addition, Sherrill and collaborators (1990) 

showed, in a longitudinal study, that children who entered a longitudinal study 

with lower levels of lung function still had significantly lower levels later in life. 

The high degree of tracking shown by these spirometric parameters implies that 

the decrements in lung function related to passive smoking may persist into 

adulthood. Although the subsequent rates of decline in lung function of these 

subjects have yet to be studied in detail, the findings by Sherrill and coworkers 

(1990) support the idea proposed by the Surgeon General's report (U.S. DHHS, 

1986) that, by the mechanisms described above, passive smoking may increase 

the risk of chronic airflow limitation. 

7.9. PASSIVE SMOKING AND RESPIRATORY SYMPTOMS AND LUNG FUNCTION IN 

ADULTS 

Both the NRC report (1986) and the Surgeon General's report (U.S. 

DHHS, 1986) extensively reviewed the evidence then available on involuntary 

smoking and respiratory health in adults. The Surgeon General's report 

concluded that healthy adults exposed to ETS may have small changes on 

pulmonary function testing but are unlikely to experience clinically significant 

deficits in pulmonary function as a result of exposure to ETS alone. The report 

added that the small magnitude of the effect implied that a previously healthy 

individual would not develop chronic lung disease solely on the basis of ETS 

exposure in adult life. It was suggested that small changes in lung function may 

be markers of an irritant response, possibly transient, to the irritants known to be 

present in ETS. 

7-69 
The NRC report concluded that it was difficult to document the extent to 

which a single type of exposure like ETS affects lung function. The report 

attributed this difficulty to the large number of factors, including other 

exposures, that affect lung function over a lifetime. The report added that results 

in adults should be evaluated for possible misclassification of ex-smokers or 

occasional smokers as nonsmokers, as well as possible confounding by 

occupational exposures to other pollutants. The authors of the report considered 

it "unlikely that exposure to ETS can cause much emphysema" (page 212), but 

that, "as one of many pulmonary insults, ETS may add to the total burden of 

environmental factors that become sufficient to cause chronic airway or 

parenchymal disease" (page 212). 

7.9.1. Recent Studies on Passive Smoking and Adult Respiratory Symptoms and Lung Function 

Six recent studies of respiratory symptoms and lung function in adults are 

presented in Table 7-11. 

Svendsen and collaborators (1987) studied longitudinal data from 1,245 

married American men aged 35 to 57 years who reported that they had never 

smoked. Subjects who had smoking wives had significantly higher mean levels 

of exhaled carbon monoxide (7.7 vs. 7.1 ppm, p < 0.001) but not of serum 

thiocyanate. These men also had lower levels of age- and height-adjusted FEV1 

(mean difference = 99 mL; 95% C.I. = 5, 192.4 mL). However, those with wives 

who smoked 20 or more cigarettes per day had higher mean adjusted FEV1 

(3,549 mL) than those with wives who smoked 1 to 19 cigarettes per day (3,412 

mL), whereas nonexposed subjects had mean adjusted FEV1 of 3,592 mL. 

Kalandidi and coworkers (1987) studied 103 Greek ever-married women 

aged 40 to 79 who were admitted in 1982 and 1983 to a hospital in Athens with 

obstructive or mixed type reduction of pulmonary function, without 

improvement after bronchodilatation. The women denied that they had ever 

been smokers, and their husbands' smoking habits were compared with those of 

179 ever-married controls of the same age selected from visitors to the hospital. 

Patients were 1.9 times more likely to have smoking spouses than were controls 

(95% C.I. = 1.0, 4.0). However, odds ratios were higher for women whose 

spouses smoked 20 or fewer cigarettes per day (2.5) than for those whose 

spouses smoked more than 20 cigarettes per day. The unusually high number of 

nonsmoking women hospitalized with chronic lung disease in a 2-year period 

suggests that some could have severe asthma unresponsive to bronchodilators 

and that the results could in part illustrate exacerbation of symptoms in asthmatic 

women exposed to ETS. 

7-70 
Table 7-11. Recent epidemiologic studies on the effects of passive smoking on adult respiratory symptoms and lung function 

Authors Population studied 

ETS exposure assessment Outcome variable Results1 

Svendsen et al. (1987) 

1,245 married American 

nonsmoking men aged 35 to

57 yr. 

Subject's report ofspouse's smokinghabits 

FEV1 Mean difference of 99 

(5-192 mL) 

Kalandidi et al. (1987) 

103 Greek women withobstructive lung disease aged40 to 79 yr.;179 control women; allnonsmokers

Subject's report ofspouse's smokinghabits 

See populationstudied 

OR = 1.9 (1.0, 4.0) 

Masi et al. (1988) 636 subjects aged 15 to 36 yr. Subject's report of Maximal expiratory

exposure to ETS flows (MEF);

diffusing capacity(DC) 

Inverse relationship wiETS exposure at home men for MEF; with exposure at work in women for DC 

7-71 Kauffmann et al. (1989a) 2,220 American women aged 25 to 69 yr.;

3,850 French women aged 25

to 59 yr. 

Subject's report ofspouse's smokinghabits 

Self-report ofrespiratory symptoms; lung function 

OR = 1.3 for wheezed U.S. sample; OR = 1.4 for cough anOR = 1.2 for dyspnea iFrench sample; lower FVC and FEV1 

(p=0.01) in French woage $40 yr. 

(contin
Table 7-11. (continued) 

Authors Population studied 

ETS exposure assessment Outcome variable Results1 

Hole et al. (1989) 7,997 subjects aged 45 to 64

yr. in Scotland 

Questionnaires answered byhousehold members 

Cardiorespiratory symptoms; lung

function 

No significant increase risk of symptoms; decrease in FEV1 (60 m

when a cohabitee smok>15 cig./day 

Schwartz and Zeger(1990) 

100 student nurses in Los Angeles, California 

Questionnaire answered by subjecton presence of a smoking roommate 

Respiratory symptoms assessed by self-administered questionnaire 

Increased risk of havinphlegm (OR = 1.4 [1.11.9]) 

195% confidence intervals in parentheses. 

7-72 
 Masi and coworkers (1988) mailed questionnaires to 818 subjects aged 15 

to 35 who had previously performed detailed lung function testing and 

carboxyhemoglobin (COHb) measurements. A total of 636 subjects responded 

to the questionnaire, and 293 denied having smoked regularly before the date of 

the lung function tests. All but five subjects had COHb values below 5 grams %. 

Questionnaires assessed past and present ETS exposure, both at home and at 

work. Indices of cumulative exposure to ETS at home and at work were 

calculated from the number of reported smokers on each location, the smoking 

conditions reported for each area, and the number of years of exposure. In men, 

there were significant inverse relationships between cumulative exposure to ETS 

in the home and maximal expiratory flows at low lung volumes. A more 

detailed analysis showed that in these subjects, exposure before 17 years of age 

had the strongest effects on lung function, whereas exposure in the 5 years 

preceding the lung function tests had no effect on lung function. Exposure at 

work significantly decreased the diffusing characteristics of the lung in women. 

Kauffmann and collaborators (1989a) compared the results obtained from 

a parallel analysis of the association of passive smoking with respiratory 

symptoms and lung function in 2,220 American women aged 25 to 69 years and 

3,855 French women aged 25 to 59 years. Women were classified according to 

their personal and current spouse's smoking habits. After adjusting for age, city 

of origin, educational level, and occupational exposure, ever-passive-smokers 

(excluding active smokers) had significantly more wheeze than true neversmokers (i.e., never active and with nonsmoking spouse) in the U.S. sample (OR 

of approximately 1.3; C.I. cannot be calculated). There was a positive trend for 

French passive smokers to have more chronic cough (OR = 1.4) and dyspnea 

(OR = 1.2), but both results could be due to chance (95% C.I. = 0.8, 2.4 and 0.9, 

1.6, respectively). In both samples, no significant decrease of lung function was 

observed for passive smokers compared with true never-smokers in the whole 

sample, although FEV1/FVC values for ever-passive-smokers tended to be 

intermediate between those of true never-smokers and ex-smokers or active 

smokers. French women aged 40 or older who were passive smokers had 

significantly lower FVC (p < 0.01) and FEV1 (p < 0.01) than did true neversmokers, but no such effect was seen among American women of the same age. 

Hole and coworkers (1989) studied cardiorespiratory symptoms and 

mortality in a cohort of 7,997 subjects aged 45 to 64 and followed for 11 years in 

urban west Scotland. A self- administered questionnaire was used in 1972-76 to 

assess respiratory symptoms and active smoking by each member of the 

household. When compared with true never-smokers (i.e., persons who were not 

active smokers and did not live with an active smoker), passive smokers were 

invariably at a higher risk of having each cardiorespiratory symptom examined 

(including infected sputum, persistent sputum, and dyspnea), but all 95% 

confidence intervals for odds ratios included 1. FEV1 (adjusted for sex, age, and 

7-73 
height) was significantly higher in true never-smokers than in passive smokers (p 

< 0.01), but this effect was mainly due to the low adjusted FEV1 of passive 

smokers with high exposure (i.e., exposed to a cohabitee who smoked > 15 

cig./day; mean = 1.83 L) when compared with those with low exposure (mean = 

1.89 L) or with no exposure (mean = 1.88 L). This study was initiated when 

there was little concern for the possible ill effects of passive smoking and is 

based on self-reports of active smoking by cohabitees. It is thus probably not 

affected by classification bias due to overreporting of symptoms by smokers. 

Schwartz and Zeger (1990) studied data from a cohort of approximately 

100 student nurses in Los Angeles who kept diaries of acute respiratory 

symptoms (cough, phlegm, and chest discomfort) and for whom data on 

exposure to passive smoking and air pollution were available. After controlling 

for personal smoking, a smoking roommate increased the risk of an episode of 

phlegm (OR = 1.4; 95% C.I. = 1.1, 1.9) but not of cough. The authors also 

excluded asthmatics (on the assumption that medication could bias the results) 

and found that in this case, the odds ratio of having phlegm increased to 1.8 

(95% C.I. = 1.3, 2.3). The greater sensitivity of diaries of acute symptoms such 

as those used herein, compared with the indices of period prevalence of 

symptoms used in other studies, may have increased the power of this study. 

However, overreporting by exposed subjects is still a possible source of bias in a 

study that is solely based on self-report of symptoms. 

7.9.2. Summary and Discussion on Respiratory Symptoms and Lung Function in Adults 

Recent studies have confirmed the conclusion by the Surgeon General's 

report (U.S. DHHS, 1986) that adult nonsmokers exposed to ETS may have 

small reductions in lung function (approximately 2.5% lower mean FEV1 in the 

studies by Svendsen et al. [1987] and Hole et al. [1989]). Using modern 

statistical tools designed for longitudinal studies, new evidence also has emerged 

suggesting that exposure to ETS may increase the frequency of respiratory 

symptoms in adults. These latter effects are estimated to be 30% to 60% higher 

in ETS-exposed nonsmokers compared to unexposed nonsmokers. 

Because active smoking causes significant reductions in lung function and 

significant increases in prevalence of respiratory symptoms (U.S. DHHS, 1984), 

the reported effects of passive smoking in adults are biologically plausible. 

From a quantitative point of view, effects of passive smoking on lung function 

are approximately comparable to those reported for light (< 10 cig./day), male 

active smokers (Camilli et al., 1987). However, because of the self-selection of 

smokers and other factors, it is difficult to make direct quantitative comparisons 

between the effects of active and passive smoking. The process of self-selection 

is likely to occur among smokers by which more susceptible individuals never 

start smoking or quit smoking early in life (the "healthy smoker" effect). 

Therefore, lower lifetime doses may be required to elicit effects among 

7-74 
nonsmokers than among smokers. The different nature of ETS and MS also has 

been discussed in previous chapters and must be taken into account when 

comparing effects of active and passive smoking. 

Several sources of bias and confounding factors need to be considered in 

studies of the effects of single exposures in adults. Classification bias due to 

underreporting of active smoking or past smoking may significantly affect the 

results of these studies. Because there is marital aggregation of smoking (i.e., 

smokers tend to marry smokers, and nonsmokers are more prone to marry 

nonsmokers), this source of misclassification is more probable among spouses of 

smokers and may introduce differential biases in some studies. The resulting 

small overestimation of effect may be nevertheless substantial for effects that are 

particularly subtle, such as those described for ETS exposure in adults. In 

addition, recent public concern with passive smoking may increase the 

awareness of respiratory symptoms in exposed subjects, who may be thus more 

prone to report symptoms than are unexposed subjects. Studies using objective 

measures of lung function obviously are not affected by the latter type of bias. 

Adults are exposed to multiple sources of potentially harmful substances 

during their lifetimes, and it is not always possible to control for the effects of 

these substances because they often are unknown or unmeasurable. In general, 

the majority of these exposures should introduce nondifferential error to the 

studies, which would lead to underestimates of the true effects. For example, a 

significant nondifferential error may be introduced by ETS exposure during 

childhood, which is known to cause decrements in lung function (see Section 

7.7) that may be carried into adulthood. ETS exposure during childhood also is 

known to cause childhood respiratory diseases (see Sections 7.3, 7.5, and 7.6). 

Such childhood respiratory diseases, whatever the cause, also may be reflected in 

decreased respiratory health in adulthood. These effects have not been 

accounted for in the studies of ETS exposure and lung function in adults, but it is 

likely that they would lead to underestimates of the ETS effects in the adult 

studies. 

Conversely, effects of ETS would be overestimated if a certain noxious 

exposure were more likely to occur among ETS-exposed subjects. In this sense, 

social factors need to be accurately controlled, because prevalence of smoking is 

significantly higher among less educated than among higher educated subjects 

(Pierce et al., 1989). Most reviewed studies have controlled for indices of 

socioeconomic level in a satisfactory manner. Finally, lifestyles may differ 

between spouses of smokers and those of nonsmokers, but it is not possible to 

determine a priori the effect of this confounder on the relationship between 

passive smoking and respiratory health. 

The influence of these factors and sources of bias, together with the 

subtlety of the effects, may explain the inconsistent and sometimes contradictory 

results of the studies reviewed in this report. In fact, such variability should be 

7-75 
expected, particularly for studies with relatively low power (i.e., low probability 

of finding a statistically significant difference when a difference really exists). 

The lack of a dose-response relationship in some studies also may be explained 

by the multiplicity of uncontrolled factors that may affect lung function. 

In summary, recent evidence suggests that passive smoking has subtle but 

statistically significant effects on the respiratory health of nonsmoking adults. 

7-76 
8. 	ASSESSMENT OF INCREASED RISK FOR RESPIRATORY ILLNESSES 

IN CHILDREN FROM ENVIRONMENTAL TOBACCO SMOKE 

In the preceding chapter, a review was presented of recently published studies regarding the association 

between respiratory illnesses in children and environmental tobacco smoke (ETS) exposure.  The biological 

plausibility and the possible pathogenetic mechanisms involved in each group of illnesses included in the chapter also 

were discussed.  The purpose of this chapter is to consider the weight of the evidence as a whole, to analyze in detail 

possible sources of systematic bias or confounding that may explain the observed associations, and to estimate the 

population impact of ETS-associated respiratory illnesses. 

8.1. POSSIBLE ROLE OF CONFOUNDING 

In the review of the available evidence indicating an association (or lack thereof) between ETS exposure and 

the different outcomes considered in this report, the possible role of several confounding factors was analyzed in 

detail (see Chapter 7).  Such analysis will only be summarized here. 

Other indoor air pollutants (wood smoke, NO2, formaldehyde, etc.) have not been found to explain the


effects of ETS but may interact with it to increase the risk of both respiratory illnesses and decreased


lung function in children. 


Many of the studies reviewed in this report and in those of the National Research Council (NRC,


1986) and the Surgeon General (U.S. DHHS, 1986) used either multivariate statistical methods of


analysis or poststratification of the sample to control for the possible confounding effects of


socioeconomic status.  Others controlled for this effect by study design.  It can be concluded that


socioeconomic status does not explain the reported effects of ETS on children's health, although


children belonging to some social groups may be at an increased risk of suffering the effects of


passive smoking (see also Section 8.3). 


The effect of parental symptoms on the association between ETS and child health also has been


extensively analyzed.  It can be concluded that, although parents with symptoms may be more aware


of their children's symptoms than are parents without symptoms, it is unlikely that this fact by itself


explains the association.  In fact, objective parameters of lung function, bronchial responsiveness, and


atopy, which are not subject to such sources of bias, have been found to be altered in children exposed


to ETS. 


The effects of passive smoking may be modified by several characteristics of the exposed child. 


Increased risk has been reported in premature infants and infants of low birthweight, infants who are


not breast-fed, infants who are kept at home with smoking mothers and not sent to day-care centers,


asthmatic children, and children who are active smokers. 


8-1 
Maternal smoking during pregnancy has significant effects on fetal growth and development and may 

affect lung growth as well as the immunologic system.  However, reports of important effects of 

paternal smoking on the child's health and studies in which ETS exposure was found to have effects 

that were independent of in utero exposure indicate that maternal smoking during pregnancy does not 

explain the relation between passive smoking and child health, but modifies the effects of ETS. 

In summary, there are no single or combined confounding factors that can explain the observed respiratory 

effects of passive smoking in children. 

8.2. MISCLASSIFICATION OF EXPOSED AND UNEXPOSED SUBJECTS 

The importance of misclassification of exposed and unexposed children has not been addressed and will be 

analyzed in detail below. 

Two possible sources of systematic bias related to subject misclassification are considered.  The first is 

upward bias from the effect of active smoking in children; the second is downward bias due to misreporting and 

background exposure.  Both have also been considered in the assessment of ETS and lung cancer in adults. 

Adjustment for background exposure will be similar to that presented in Chapter 6, except that data for increased 

incidence of some ETS-associated respiratory diseases show some evidence of thresholds that must also be taken into 

account. 

8.2.1. Effect of Active Smoking in Children 

The possibility needs to be considered that some children may be smokers themselves and that this may 

happen more often among children of smoking parents than among those of nonsmoking parents.  This would bias the 

results upwards or against the null effect.  This source of bias is only applicable to studies of older children; regular 

active smoking may occur but is rare before early adolescence.  A study of third graders in Edinburgh, Scotland, by 

Strachan and coworkers (Strachan et al., 1989, see Section 7.4.1, for example) showed that salivary cotinine levels 

compatible with active smoking were found in 6 of 770 children ages 6-1/2 to 7-1/2 years, suggesting only a small 

potential for bias.  Consideration should also be given to the fact that some of the effects described in Chapter 7 (for 

example, the increased risks for acute respiratory illnesses [Section 7.3] and for cough, phlegm, and wheezing 

[Section 7.5]) have been found to be stronger in younger children (i.e., those less likely to be active smokers) than in 

older children.  This observed reduced effect with increasing age may be in part due to an age-related increase in 

misclassification of exposed subjects as "unexposed" (see below), but it is clear that these specific effects of ETS do 

not increase with age, as would be expected if active smoking biased the results of studies of ETS effects in older 

children.  It can thus be concluded that the association between respiratory health in children and ETS is not 

attributable to active smoking by some children.  It has been suggested that active and passive smoking may interact to 

increase the effects of either exposure separately (Lebowitz and Holberg, 1988).  This interaction is biologically 

8-2 
plausible, because it is likely that active smoking may be more harmful in children whose lungs have been previously 

affected by ETS (see Section 7.1). 

8.2.2. Misreporting and Background Exposure 

Various investigators have measured cotinine levels in body fluids in infants and children and correlated the 

results with parental reports of ETS exposure.  Coultas and coworkers (1987) reported that 37% of children under 5 

years of age whose parents were nonsmokers had a salivary cotinine level greater than 0, compared with 32% of 

children ages 6 to 12 and with 35% of children ages 13 to 17.  These authors did not ask parents to report possible 

sources of ETS exposure for their children other than their own tobacco consumption.  Strachan and coworkers' study 

in 6-1/2- to 7-1/2-year-old children in Scotland (Strachan et al., 1989) showed that 73% of children from households 

with no smokers had detectable concentrations of cotinine in saliva, whereas only 1 in 365 children from households 

with one or more smokers had no detectable salivary cotinine.  The assay used by Strachan and coworkers was 10 

times more sensitive than that used by Coultas and coworkers, and this may explain the larger number of subjects with 

detectable levels in the former study when compared with the latter. 

Greenberg and coworkers (1984) studied cotinine levels in 32 infants in North Carolina with reported 

exposure to tobacco smoke within the previous 24 hours and in 19 unexposed infants.  All subjects were under 10 

months old.  Urine samples of all exposed infants contained cotinine, whereas all unexposed infants except 2 (11%) 

had undetectable urine cotinine or levels below those of exposed infants with the lowest levels of urine cotinine.  This 

same group of researchers reported results for a larger sample (433 infants at a mean age of 18 days) of the same 

population (Greenberg et al., 1989).  They found that, of 157 infants who reportedly lived in nonsmoking households 

and were also not in contact with smokers the previous week, 37 infants (24%) had cotinine in their urine.  They 

concluded that these infants had contact with tobacco smoke during the previous week and that this contact was 

unknown to or was not reported by their mothers. 

Greenberg and coworkers (1991) followed 152 of the 433 infants originally enrolled and reassessed 

exposure to ETS (through maternal interviews) and urine cotinine levels when the child was 12.3 ± 0.6 months old. 

They found a significant increase in the prevalence of tobacco smoke absorption, indicated by excretion of cotinine, 

during the first year of life (from 53% at a mean age of 3 weeks to 77%).  The interviews showed that this was mainly 

due to an increased exposure to nonhousehold sources of smoke (from 14% to 36%).  The proportion of infants who 

reportedly had no contact with smokers but had cotinine in their urine increased from 24% at 3 weeks to 49% at 1 

year of age. 

These results indicate that studies relying exclusively on parental questionnaires to ascertain ETS exposure in 

children may misclassify many exposed subjects as nonexposed.  Moreover, the degree of misclassification may 

increase with the child's age. 

The possible consequences of this misclassification of exposure need to be discussed in detail. 

Nondifferential misclassification (i.e., exposure classification that is incorrect in equal proportions of diseased and 

8-3 
nondiseased subjects) biases the observed results toward a conclusion of no effect (Rothman, 1986).  The effect of 

differential misclassification depends on the direction in which misclassification occurs.  If true ETS exposure is 

preferentially reported by parents of diseased subjects (i.e., there is reporting bias), an excess of disease prevalence 

would be found among exposed subjects when compared with unexposed subjects that is unrelated to any biological 

effect of ETS.  The evidence available clearly indicates that this is a very unlikely explanation for the reported 

misclassification of ETS exposure in infants and children.  In fact, reporting bias cannot explain the substantial 

increase in "underreporting" of exposure with age.  The logical explanation is provided by the finding that exposure to 

nonhousehold smokers increases significantly with age and parallels the increase in the proportion of subjects who 

have cotinine in their urine (Greenberg et al., 1991).  There is no reason to believe that exposure to smokers may 

occur preferentially among diseased children, and the contrary may be more reasonable; the increased awareness of 

the ill effects of ETS inhalation may induce parents to limit contact between their diseased children and nonhousehold 

smokers.  Thus, the net effect of misclassification of exposure, both nondifferential and differential, should be a 

systematic downward bias or bias toward observing no effect.  A correction for the nondifferential misclassification 

bias of background exposure is made in Section 8.3. 

8.3. ADJUSTMENT FOR BACKGROUND EXPOSURE 

An important conclusion of the previous discussion is that studies based on parental questionnaires may 

underestimate the health risk from ETS in children due to underreporting of ETS exposure.  The NRC (1986) report 

on passive smoking adopted the use of cotinine measures to correct for misreporting of ETS exposure for lung cancer 

effects, and this approach was adapted for use in Chapter 6 of this report.  It will also be employed here, with the 

cotinine ratios, however, based on exposure data in children rather than in adults.  The method is based on several 

assumptions:  (1) cotinine concentrations in body fluids of nonsmokers are linearly related to ETS exposure, (2) the 

excess risk of respiratory illness in subjects exposed to ETS is linearly related to the dose of ETS absorbed, (3) the 

relationship between ambient and absorbed ETS is linear, and (4) one cotinine determination may adequately 

represent average childhood exposure to ETS. 

As support for assumptions 1 and 2, three recent studies have used body cotinine levels as biomarkers for 

ETS exposure in children.  All three have found significant associations between cotinine levels and respiratory 

effects in children.  Etzel et al. (1992) found a significant relationship between serum cotinine levels and otitis media 

with effusion for children who attended a day-care facility during the first 3 years of life.  Ehrlich et al. (1992), in a 

study that used questionnaires on maternal caregiver smoking as well as urinary cotinine levels to assess ETS 

exposure, found that by either measure ETS exposure was significantly associated with both acute and nonacute 

asthma in children.  Furthermore, urinary cotinine levels in asthmatic children showed a highly significant correlation 

with maternal caregiver smoking status.  In the third study, Reese et al. (1992) found urinary cotinine levels 

significantly (p < 0.02) elevated in children admitted to the hospital with bronchiolitis compared with a group of 

similarly aged children admitted with nonrespiratory illnesses.  There was also a highly significant correlation (p < 

8-4 
0.0005) between urinary cotinine levels and maternal smoking as determined by questionnaire.  Thus, the evidence 

suggests that questionnaire ascertainment of childhood exposure to ETS and cotinine biomarkers in children are 

highly correlated with each other and that both correlate with childhood diseases.  This information is used to develop 

the risk assessment models below. 

While considerable evidence exists for assumptions 1 through 3 (see also Chapter 3), there is some evidence 

that assumption 4 may not be entirely warranted, at least for older children.  Coultas and coworkers (1990b), in a 

small study of 9 children from 10 homes with at least 1 smoker, reported that there is considerable variability in 

cotinine levels in body fluids within individuals exposed to ETS when such levels are repeatedly measured on 

different days.  However, Henderson et al. (1989), doing repeated urinary cotinine measures in preschool children, 

found stable levels over 4 weeks.  Thus, while the method of adjustment is based on group mean body cotinine levels, 

which apparently reflect household ETS levels well, the intraindividual variability, at least in older children, may 

subject these means to some error. 

Application of the method proposed by the NRC requires some knowledge of Z, the ratio between the 

operative mean dose level in the "exposed" group, dE, and the mean dose level in the "unexposed" group, dN.  RR(dE), 

the relative risk for the group identified as "exposed" compared with the group identified as "unexposed," is thus 

given by 

RR(dE) = (1+Z* dN)/(1+ dN) (8-1) 

where  is the amount of increase per unit dose and Z > RR(dE) > 1.  (The "unexposed" group actually contains those 

with background exposure plus those truly unexposed.) 

Several studies are available that could be used for the purpose of estimating Z.  Jarvis and coworkers (1985) 

studied 569 nonsmoking schoolchildren ages 11 to 16 in Great Britain.  The investigators reported that, when 

compared with salivary cotinine levels in children of nonsmoking parents (N = 269), mean levels of salivary cotinine 

were 3.0 times as high in children whose father smoked (N = 96), 4.4 times as high in children whose mother smoked, 

and 7.7 times as high in children whose parents were both smokers.  Pattishall and coworkers (1985) reported that 

children from homes with smokers (N = 20) had 4.1 times as high mean levels of serum cotinine as children from 

nonsmoking families.  Black children in the same study, however, had lower values of Z (2.8) than did white children. 

Coultas and coworkers (1987) found that, among 600 U.S. children up to age 17 years, mean salivary cotinine levels 

were between 1.3 and 2.6 times as high among subjects exposed to one cigarette smoker at home as among unexposed 

subjects, and between 2.9 and 3.5 times as high among subjects exposed to two or more smokers at home as among 

subjects not exposed to cigarette smokers at home.  Strachan and coworkers (1989) reported separate results for 6-

1/2- to 7-1/2-year-old Scottish children belonging to families living in their own homes and for those belonging to 

families living in rented homes.  In the former, geometric mean salivary cotinine was 6 times as high among subjects 

exposed to one cigarette smoker at home as among unexposed subjects and 16 to 17 times as high among subjects 

8-5 
exposed to two or more smokers at home as among unexposed subjects.  For children belonging to families living in 

rented homes, the same ratios were 3 to 5.5 times and 4 to 7 times, respectively. 

While these studies show consistent relationships between mean body cotinine levels in children and home 

smoker occupancy, there is also a wide variability in the estimated Z ratios, ranging from 1+ to 17.  These different 

estimates may have very important effects on the background exposure adjustment and, thus, on the calculation of 

adjusted relative risks for different studies (see also Chapter 6).  For example, for a study in which the observed 

relative risk (RR) is 2.0 but for which the Z ratio is 3, equation 8-1 can be solved for  dN, which is the estimated 

increase in relative risk for the group called "unexposed" but who in fact have been exposed to some recent ETS. 

Solving,  dN = 1.  Thus, the adjusted RR for the group identified as "unexposed" would be 2, and the adjusted RR for 

an "exposed" group compared with a truly unexposed group would be 1 + (3*1) = 4, i.e., twice the observed risk.  For 

a similar example (observed RR = 2) but with Z = 5,  dN = 0.3, the RR for a group identified as "unexposed" in this 

case would be 1.3, and the adjusted RR for an "exposed" to a truly unexposed group would be 2.67.  Finally, if the 

observed RR is still 2 but Z = 17,  dN = 0.07, RR for "unexposed" would be 1.07 and the adjusted RR for exposed 

children would be 2.13.  These results are shown in Table 

8-1. 

These calculations show that when use of parental questionnaires significantly underestimates their children's 

exposures to other sources of ETS (other than via the parental ETS) and values of Z are lower (as found in black 

children by Pattishall and coworkers [1985], and in children of lower socioeconomic status by Strachan and 

coworkers [1989]), the "true" RR of children exposed to ETS may be considerably underestimated.  But perhaps the 

most important conclusion that may be derived from the above analysis is that exposure to ETS from sources other 

than smoking parents may be high enough to constitute a significant risk for their health.  This may be particularly 

consequential for children of lower socioeconomic levels, whose nutritional status, crowded conditions at home, and 

opportunity for contact with biological agents of disease make them a part of the population that is particularly 

susceptible to respiratory illnesses during infancy and childhood.  Available data show that ETS exposure via 

nonhousehold members in these children, as measured by cotinine levels in body fluids, may be as much as one-third 

that of children exposed to one smoking parent (Z = 3).  In the example presented above (observed RR = 2), the 

estimate of the adjusted relative risk is 4 for children of smoking parents to the truly unexposed children.  However, 

using the same assumptions, children of nonsmoking parents who are exposed to ETS (at background levels found in 

some of the studies) would have twice as high a risk of developing the illness under study as children truly unexposed 

to ETS. 

A cautionary note about the model is appropriate.  Table 8-1 shows that, for observed RR = 2 and Z = 3, the 

adjusted relative risk is 4.  However, as the observed RR and Z get closer together, the behavior of the model becomes 

erratic.  This is shown in Table 8-2.  In fact, the model (equation 8-1) becomes undefined if Z is less than or equal to 

the observed RR, and it reaches some stability only as Z becomes at least 30% to 50% greater than the RR. 

8-6 
Table 8-1.  Adjusted relative risks for "exposed children."  Adjusted or background exposure based on body cotinine 

ratios between "exposed" and "unexposed" and equation 8-1 

Z Ratio of body cotinine levels ("exposed"/"unexposed") 

1.50 2.00 3.00 5.00 7.00 10.00 13.00 17.00 

Observed 

Relative 

Risks 

(RR) 

1.0 

1.50 

1.75 

2.00 

2.50 

3.00 

1 1 1 1 1 1 1 1 

- 3.00 2.00 1.71 1.64 1.59 1.57 1.55 

- 7.00 2.80 2.15 2.00 1.91 1.87 1.84 

- - 4.00 2.67 2.40 2.25 2.18 2.13 

- - 10.00 4.00 3.33 3.00 2.86 2.76 

- - - 6.00 4.50 3.86 3.60 3.43 

Table 8-2.  Behavior variations in adjusted relative risks from equation 8-1 when the observed relative risks and Z ratios 

are close together 

Z ratio 

1.50 1.75 2.00 2.25 2.50 2.75 3.00 10.00 

Observed 

1.50 

Relative 

1.75 

Risks 

2.00 

(RR) 

2.25 

2.50 

- 4.50 3.00 2.50 2.25 2.10 2.00 1.59 

-3.5 - 7.00 4.38 3.50 3.06 2.80 1.91 

-2.0 -6.00 - 10.00 6.00 4.67 4.00 2.25 

-1.5 -3.38 -9.00 - 13.50 7.88 6.00 2.62 

-1.25 -2.50 -5.00 -12.50 - 17.50 10.00 3.00 

8-7 
Fortunately, the estimates of Z presented above are appreciably greater than the observed relative risk estimates 

seen in Chapter 7, and in the observed range of both RR and Z, the model yields relatively stable estimates of the adjusted 

RR.  Furthermore, as discussed in Chapter 6, the values of RR and Z are expected to be correlated for each study, i.e., the 

greater the Z ratio between exposed and unexposed groups in each study, the greater should be the observed RR and the 

less the effect of the (equation 8-1) adjustment. 

If the above model is correct, then exposure of children to ETS other than at home (parental smoking) may be an 

important risk factor for respiratory illness in childhood.  On the other hand, it is also possible that for at least some 

respiratory illnesses, outside exposure to ETS has relatively little effect, either because outside exposures in younger 

children tend to be less than those of older children or because there may be a threshold of exposure below which certain 

respiratory effects may not be expected to occur.  For this latter case, equation 8-1 is not an appropriate model, and the 

observed relative risk would be taken to be the true risk.  Both models are addressed in the sections that follow. 

8.4. ASSESSMENT OF RISK 

Neither the NRC report (1986) nor the Surgeon General's report (U.S. DHHS, 1986) attempted to assess the 

population or public health impact of the increased risk of respiratory 

disorders in children attributable to ETS exposure.  In this section, estimates will be derived for the number of ETSattributable lower respiratory tract infections in infants and for the induction and exacerbation of childhood asthma. 

Quantifying the public health impact of other conditions, such as reduced lung function, coughing, wheezing, and middle 

ear effusion, is difficult, either because of the lack of overt symptoms or because some necessary U.S. population health 

statistics are not available.  Estimates of sudden infant death syndrome (SIDS) occurrences attributable to ETS will not be 

made but will be discussed in Section 8.4.3. 

For the following quantitative analyses, estimates will be developed in terms of ranges.  The ranges are derived 

by the use of both threshold and nonthreshold (equation 8-1) models, different estimates for population incidence and 

prevalence, and estimated values of Z and RR from studies reviewed above.  Various differences in design, disease 

definition, and conduct among these studies make them less adaptable to meta-analysis techniques than were the lung 

cancer studies.  To the extent that a less rigorous statistical analysis is attempted here, the ranges should reflect that 

uncertainty. 

8.4.l. Asthma 

From the analysis of studies regarding risk for asthma and ETS exposure, it was concluded that passive smoking 

increases both the number and severity of episodes in asthmatic children.  It was further concluded that ETS is a risk 

factor for new cases among previously asymptomatic children, since the evidence is suggestive, but not conclusive, of a 

causal association (see Section 7.6).  Relative risks for asthma ranged from 1.0 to 2.5 in the studies analyzed, but 

methodologies differed considerably among studies, and effects were often found only in children of mothers who smoke 

heavily.  Of the four large studies, totaling more than 9,000 children (Burchfield et al., 1986; Sherman et al., 1990; 

8-8 
Weitzman et al., 1990; Martinez et al., 1991b), three showed statistically significant risk estimates ranging from 1.7 to 2.5, 

with the two largest ratios, 2.5 (Martinez et al., 1991b) and 2.1 (Weitzman et al., 1990), coming from comparisons using 

children of heavily smoking mothers (  l0 cig./day) as the exposed group.  The third study (Burchfield et al., 1986) had 

OR = l.7 for males with two smoking parents, but results were not significant either for girls or for children with one 

parental smoker.  The fourth study (Sherman et al., 1990) (770 children) did not find an effect, but made no effort to 

assess the effect of heavy smoking by parents, nor was there control for socioeconomic status.  Thus, assigning a range of 

1.75 to 2.25 for the estimated relative risk of developing asthma for children of mothers who smoke 10 or more cigarettes 

per day appears reasonable and is within the ranges of observed risk. 

The above results suggest two possible scenarios.  One scenario is that relatively heavy exposure to ETS is 

needed to bring on asthma, i.e., there is a threshold of exposure below which effects will not occur.  Alternatively, lesser 

exposures may merely induce fewer effects, not detectable statistically with these study designs.  The choice of scenario 

does not affect the observed relative risk but will affect whether or not an adjustment for background exposure (Z ratio) is 

appropriate.  Under the first (threshold) scenario, the estimates of RR = 1.75 to 2.25 need no adjustment; under the 

alternative (nonthreshold) scenario, equation 8-1 applies. 

Considering the nonthreshold model first, from the discussion in Section 8.3, it can be assumed that values of 3 

to 10 may be a reasonable range for estimates of Z (i.e., the ratio of body cotinine levels in children whose mothers smoke 

heavily to those of children whose mothers do not smoke).  Lower values of Z would yield significantly larger estimates 

of asthma cases attributable to ETS.  Based on the above estimates for a range of Z and RR and use of the nonthreshold 

model, the estimated range of adjusted relative risks for children of mothers who smoke 10 or more cigarettes per day 

would be approximately 1.91 to 6.00 (see Table 8-3).  Transforming relative risks to 

8-9 
Table 8-3.  Range of estimates of adjusted relative risk and attributable risk for asthma induction in children based on both threshold and nonthreshold models, and 

different values for Z. 

Threshold model1 Nonthreshold model2 

Observed relative risk 1.75 2.25 1.75 2.25 1.75 2.00 2.25 

Z = Cotinine ratio 

(exposed/unexposed) 

- - 10 10 3 3 3 

Adjusted relative risk3 - - 1.914 2.624 2.805 4.005 6.005 

ARE 

6 0.43 0.56 0.48 0.62 0.64 0.75 0.83 

AR  (P =0.17) T I 

7 8 0.07 0.09 - - - - -

AR  (P =0.26) T I 

9 - - 0.12 0.16 0.17 0.20 0.22 

ETS-attributable population 

impact10 

8,000 

to 

20,000 

10,000 

to 

26,000 

13,000 

to 

34,000 

18,000 

to 

45,000 

19,000 

to 

46,000 

22,000 

to 

54,000 

24,000 

to 

60,000 

8-10 

1
Threshold model assumes that heavy ETS exposure (i.e., mothers smoking > 10 cig./day) is required to induce new cases.  2
Nonthreshold model assumes that all ETS exposure can produce some new cases of asthma.

 3
Equation 8-1 for the nonthreshold model; no adjustment for the threshold model.

 4
Ratio of mean body cotinine levels:  Z = 10. 5
Ratio of mean body cotinine levels:  Z = 3.  6
Attributable risk fraction for the exposed population.

 7
Attributable risk fraction for the total (mixed) population.

 8
Proportion of women of reproductive age who smoke at least 10 cigarettes per day (0.26 × 0.65).

 9
Proportion of women of reproductive age who smoke cigarettes.

10
Range based on 2 million to 5 million asthmatic children under 18 years old in the United States, and assumes that the number of

 ETS-attributable new cases at each age is constant. 
attributable risks (Rothman, 1986), 48% to 83% of all cases of asthma among children of mothers who smoke 10 or 

more cigarettes per day may be attributable to passive smoking based on 

ARE = 100 * (1 - [1/RR]) (8-2) 

where ARE is the attributable risk (%) for the exposed population. 

Under the assumptions of the threshold model, RR = l.75 to 2.25 for children of heavily smoking mothers, 

and the ARE = 43% to 56% (see Table 8-3); for children of light-smoking mothers, RR = 1 and the ARE = 0. 

To calculate the percentage of all cases occurring in a mixed population of exposed and unexposed 

individuals that is attributable to exposure (ART), knowledge of the prevalence of mothers smoking 10 or more 

cigarettes per day is needed because 

ART = ARE * PI (8-3) 

where PI is the proportion of cases that is exposed (Rothman, 1986).  It has been reported that approximately 26% of 

the population of women of childbearing age smoked in the United States in 1988 (CDC, 1991b) and in 1990 (CDC, 

1992b).  For the number of cigarettes smoked, Weitzman and coworkers (1990), using the 1981 National Health 

Information Survey (NHIS), found that approximately 50% of smoking mothers of children ages 0 to 5 years smoke 

10 or more cigarettes per day.  The 1990 NHIS reports that 78% of smoking women ages 18 to 44 smoke at least 10 

cigarettes per day (data courtesy of Dr. Gary Giovino, CDC).  We have used an average of 65% to derive the 

estimates in Table 8-3.  Based on these figures and the threshold model, it can thus be estimated that approximately 

7% to 9% of all cases of asthma may be attributable to exposure to ETS from mothers who smoke 10 or more 

cigarettes per day.  Estimates of the prevalence of asthma among U.S. children less than age 18 vary from 5% to 10% 

(Clark and Godfrey, 1983) to 3% to 8% (R. Evans et al., 1987), depending on disease definition.  This latter paper 

uses the data from the 1979-1981 NHIS and derives a population asthma prevalence of 2 million to 5 million.  A more 

recent estimate from the 1989 NHIS is 3.9 million (U.S. DHHS, 1990b).  Use of these population prevalence figures 

and the threshold model provides a range of 8,000 to 26,000 as the annual number of new cases of childhood asthma 

attributable to mothers who smoke 10 or more cigarettes per day.  The confidence in this estimate is medium and is 

dependent on the conclusion that ETS is a risk factor for asthma induction. 

If the nonthreshold model applies, use of the same prevalence figures leads to a range of 13,000 to 60,000 

new cases per year attributable to all ETS exposures (Table 8-3). 

While the range of 8,000 to 60,000 is plausible, the existing data are more supportive of the threshold model, 

which assumes that rather heavy exposures to ETS are required to induce asthma in previously asymptomatic children 

(Section 7.6.2).  Thus, the range of 8,000 to 26,000 will be adopted as the more probable range of new cases among 

children per year attributable to ETS exposure. 

8-11 
In view of the increased number and severity of asthmatic episodes also caused by ETS, the public health 

impact of ETS on asthmatic children is considerably greater than the range of estimates for new cases presented 

above.  Shephard (1992), after reviewing several studies, concludes that ETS exposure (from any source) exacerbates 

preexisting asthma in approximately 20% of patients.  If this figure is correct, up to 1 million asthmatic children could 

be affected.  Also, in an earlier study, O'Connell and Logan (1974) found that parental smoking aggravated clinical 

symptoms of 67% of 265 asthmatic children in the Midwest versus 16% of 137 controls (p < 0.0001) and that 10% of 

400 asthmatic patients (of both smoking and nonsmoking parents) considered tobacco smoke a major aggravating 

factor.  D. Evans and coworkers (1987) found that passive smoking by asthmatic children in New York City (via 

presence of smokers in the household) was associated with a mean annual increase of 1.34 emergency room visits per 

year for asthmatic symptoms, an increase of 63% over asthmatic children from nonsmoking households.  Ehrlich et al. 

(1992), in a study not reviewed by Shephard (1992), found that asthmatics with clinically significant symptoms had 

both higher cotinine levels than controls (p = 0.04) and an 

OR = 2.0 (p = 0.03) for maternal caregivers who smoke.  Using this estimate of 2.0 with 

equation 8-1 and a Z = 3 also leads to an attributable risk fraction, ART, of 20% (equation 8-3).  Multiplying this 20% 

by the 2 million to 5 million asthmatic children in the United States yields estimates of 400,000 to 1,000,000 whose 

condition is aggravated by exposure to ETS.  Thus, exposure to ETS in general and especially to parental ETS 

adversely affects hundreds of thousands of asthmatic children. 

8.4.2. Lower Respiratory Illness 

From the assessment of available data (see Section 7.3), it was concluded that exposure of infants and young 

children to ETS causes an increased incidence of lower respiratory illness (LRI).  An examination of the data in the 

referenced studies of both Tables 7-l and 7-2 leads to the conclusion that the observed risk of having LRIs is 

approximately l.5 to 2.0 times as high in young children whose mothers smoke as in those whose mothers do not 

smoke and that the risk is probably higher in infants than in toddlers. 

This estimate is also consistent with that of the NRC (l986), which estimated a relative risk of up to 2 for 

infants who have one or more parents who smoke.  The more recent evidence reviewed here strongly suggests that the 

increased risk due to ETS exposure lasts for at least the first 18 months and decreases after that.  Based on this 

evidence, this chapter estimates a relative risk range of 1.5 to 2.0 for infants and children up to 18 months old who 

have smoking mothers.  It will assume that the increased risk is zero after l8 months. 

Based on these findings, and following equation 8-l with a range of Z = 3 to 10 and RR = 1.5 to 2.0, the 

adjusted relative risk range becomes 1.6 to 4.0, and ARE takes the range 38% to 75%.  As in the previous section, for 

equation 8-3, the mixed population attributable risk ART takes the range 10% to 20%, again based on l988 and 1990 

estimates of approximately 26% women of childbearing age who smoked (CDC, l99lb, 1992b).  Because the 

estimated mean number of cigarettes smoked by these women is approximately 17 to 20 per day (CDC 1991b, 

8-12 
1992b), it is reasonable to assume that most children of smoking mothers will be exposed.  Therefore, the proportion 

of cases exposed, PI

, is estimated to be 0.26. 

It has recently been shown that the incidence of LRIs early in life is approximately 30% (Wright et al., l99l). 

When the analysis is limited to the first l8 months of life, the population at risk is approximately 5.5 million children. 

A slight modification of the same algorithms described above yields 150,000 to 300,000 cases of LRIs annually in 

children under 18 months old attributable to exposure to ETS generated mostly by smoking mothers.  For RR = 1.5 

and Z = 10, the attributable risk fraction for the exposed population, ARE, is 0.38, and the attributable risk fraction for 

the total population, AR, is 0.10.  Assuming 3.7 million children less than 1 year old and a 30% incidence of LRI, the 

ETS-attributable population risk is 110,000.  In order to get the incidence rate for the 1.8 million children aged 12 to 

18 months, also with 30% incidence, the 110,000 must be subtracted from the 540,000 before multiplying by 0.10. 

The product of 43,000 is then added to 110,000 to determine the total annual incidence of 150,000 LRIs.  For RR = 

2.0 and Z = 3 the total annual incidence is about 300,000.  Approximately 5% of these LRIs require admission to a 

hospital (Wright et al., l989); therefore, it is estimated that 7,500 to 15,000 hospitalizations yearly for LRIs may be 

attributable to ETS exposure. 

While these estimates may appear large, three factors suggest that they are on the low side.  First, although 

these estimates are calculated only for children less than l8 months old, Section 7.3 presents evidence that these ETSattributed increased risks extend at a decreasing rate up to 

3 years of age.  Second, no estimates have been calculated for exposure in a smoking father-nonsmoking mother 

household.  Third, these numbers do not take into account the fact that many infants and young children have 

recurrent LRIs, and therefore, more than one episode of such illnesses may be attributable to ETS in each exposed 

child. 

8.4.3. Sudden Infant Death Syndrome 

Because this report concludes that there is an association between maternal smoking and SIDS but is unable 

to determine the contribution that ETS makes to that association (see Section 7.7), no estimate of ETS-attributable 

SIDS deaths will be calculated.  The Centers for Disease Control (CDC, l99la) provides an estimate of 702 SIDS 

deaths attributable to maternal smoking, based on a relative risk of l.5 for infants of actively smoking mothers.  While 

this report concurs with the numbers and the methodology used to determine that estimate, it is unable to apportion the 

in utero, lactation, and ETS exposure components of the risk. 

8.5. CONCLUSIONS 

This chapter has attempted to estimate the impact on the U.S. population of ETS exposure on childhood 

asthma and lower respiratory tract infections in young children.  For new cases of asthma in previously asymptomatic 

children under 18 years of age, we estimate that 8,000 to 26,000 is a probable range of new cases per year that are 

8-13 
attributable to ETS exposure from mothers who smoke at least 10 cigarettes per day.  The confidence in this range is 

medium and is dependent on the conclusion that ETS is a risk factor for asthma induction. 

While the data are most supportive of a situation in which heavy exposures to ETS are required to induce 

new cases of asthma, two other scenarios would lead to larger estimates.  The first is that even in the absence of 

smoking mothers, a child could receive heavy ETS exposure from other sources.  The second is that lesser ETS 

exposures induce fewer numbers of new cases, and the increase is not statistically detectable.  Under this latter 

(nonthreshold) scenario, the range of new cases of asthma annually attributable to ETS exposure is 13,000 to 60,000. 

This report concludes that, in addition to inducing new cases of asthma, ETS exposure increases the number 

and severity of episodes among this country's 2 million to 5 million asthmatic children.  This chapter considers 

exposure to parental smoking to be a major aggravating factor to approximately 10%, or 200,000, asthmatic children. 

Estimates of the number of asthmatics whose condition is aggravated to some degree by ETS exposure are very 

approximate but could run well over 1 million. 

This chapter also estimates that 150,000 to 300,000 cases annually of lower respiratory tract infections in 

children up to 18 months old are attributable to ETS exposure, most of which comes from smoking parents (mostly 

mothers).  These ETS-attributable cases are estimated to result in 7,500 to 15,000 hospitalizations annually. 

Confidence in these estimates is high based on the conclusion of a causal association and the strong validity of 

parental smoking as a surrogate of temporally relevant ETS exposure in infants and young children.  Additional cases 

and hospitalizations are expected to occur in children up to 3 years old in decreasing numbers, but this report makes 

no further quantitative estimates. 

Infants' exposure to ETS may also be responsible for a portion of the more than 700 deaths from SIDS 

attributable to maternal smoking by the CDC (1991a), but this report is unable to determine whether and to what 

extent these deaths can be attributed specifically to ETS exposure. 

The estimates of population impact presented above are given in ranges and approximate values to reflect the 

uncertainty of extrapolating from individual studies to the population.  As with the lung cancer population impact 

assessment (Chapter 6), these extrapolations are all based on human studies conducted at true environmental levels. 

Therefore, they suffer from none of the uncertainties associated with either animal-to-human or high-to-low exposure 

extrapolations. 

In addition to the estimates presented above, ETS exposure in children also leads to reduced lung function, 

increased symptoms of respiratory irritation, and increased prevalence of middle ear effusion, but this report does not 

provide estimates of the population impact of ETS exposure for these conditions. 

8-14 
ADDENDUM: PERTINENT NEW STUDIES 

Several pertinent studies on the respiratory health effects of passive smoking have appeared since the cutoff 

date for inclusion in this report.  The studies are cited here for the benefit of anyone who may wish to follow up on 

these topics.  The studies are briefly described below, and the authors' conclusions are presented.  We do not formally 

review these studies in this report, and the citations do not represent a full literature search.  These new studies are 

generally consistent with this report's conclusions that environmental tobacco smoke (ETS) exposure increases the 

risk of lung cancer in nonsmokers and affects the respiratory health of infants. 

Two of the new studies are case-control studies of ETS and lung cancer in U.S. female nonsmokers 

(Stockwell et al., 1992; Brownson et al., 1992).  Stockwell et al. conclude that "long-term exposure to [ETS] increases 

the risk of lung cancer in women who have never smoked."  Similarly, Brownson et al. conclude, "Ours and other 

recent studies suggest a small but consistent increased risk of lung cancer from passive smoking." 

In an autopsy study of Greeks who had died of causes other than respiratory diseases, Trichopoulos et al. 

(1992) found an increase in "epithelial, possibly precancerous, lesions" in the lungs of nonsmoking women who were 

married to smokers.  The authors concluded that their results "provide support to the body of evidence linking passive 

smoking to lung cancer. . . ."  In a fourth study, a case-control study of ETS exposure and lung cancer in dogs, Reif et 

al. (1992) found an association between lung cancer and exposure to a smoker in the home for breeds with short- and 

medium-length noses.  These results are not statistically significant, and the authors characterize their findings as 

"inconclusive." 

Finally, Schoendorf and Kiely (1992) conducted a case-control analysis of sudden infant death syndrome 

(SIDS) and maternal smoking status (i.e., maternal smoking both during and after pregnancy [combined exposure], 

maternal smoking only after pregnancy [passive exposure], and no maternal smoking).  These investigators conclude 

that their data "suggest that both intrauterine and passive tobacco exposure are associated with an increased risk of 

SIDS." 

ADDENDUM REFERENCES 

Brownson, R.C.; Alavanja, M.C.; Hock, E.T.; Loy, T.S. (1992) Passive smoking and lung cancer in nonsmoking 

women. Am. J. Public Health 82:1525-1530. 

ADD-1 
Reif, J.S.; Dunn, K.; Ogilvie, G.K.; Harris, C.K. (1992) Passive smoking and canine lung cancer risk. Am. J. 

Epidemiol. 135:234-239. 

Schoendorf, K.C.; Kiely, J.L. (1992) Relationship of sudden infant death syndrome to maternal smoking during and 

after pregnancy. Pediatrics 90:905-908. 

Stockwell, H.G.; Goldman, A.L.; Lyman, G.H.; Noss, C.I.; Armstrong, A.W.; Pinkham, P.A.; Candelora, E.C.; Brusa, 

M.R. (1992) Environmental tobacco smoke and lung cancer risk in nonsmoking women. J. Natl. Cancer Inst. 

84:1417-1422. 

Trichopoulos, D.; Mollo, F.; Tomatis, L.; Agapitos, E.; Delsedime, L.; Zavitsanos, X.; Kalandidi, A.; Katsouyanni, K.; 

Riboli, E.; Saracci, R. (1992) Active and passive smoking and pathological indicators of lung cancer risk in 

an autopsy study. JAMA 268:1697-1701. 

ADD-2 
CONTENTS

A.1. INTRODUCTION .......................................................................................................................... A-1 

A.2. CONSTRUCTION OF INDIVIDUAL STUDY REVIEWS .......................................................... A-1 

A.2.1 Review Form for Case-Control Studies ........................................................................ A-2 

A.3. TIER CLASSIFICATION SCHEME ............................................................................................. A-6 

A.4. INDIVIDUAL STUDY REVIEWS................................................................................................ A-19 

A.4.1. AKIB............................................................................................................................. A-20 

A.4.2. BROW .......................................................................................................................... A-23 

A.4.3. BUFF ............................................................................................................................ A-26 

A.4.4. BUTL(Coh)................................................................................................................... A-29 

A.4.5. CHAN ........................................................................................................................... A-32 

A.4.6. CORR ........................................................................................................................... A-35 

A.4.7. FONT............................................................................................................................ A-38 

A.4.8. GAO.............................................................................................................................. A-43 

A.4.9. GARF............................................................................................................................ A-46 

A.4.10. GARF(Coh)................................................................................................................... A-51 

A.4.11. GENG ........................................................................................................................... A-56 

A.4.12. HIRA(Coh) ................................................................................................................... A-59 

A.4.13. HOLE (Coh).................................................................................................................. A-69 

A.4.14. HUMB .......................................................................................................................... A-71 

A.4.15. INOU ............................................................................................................................ A-74 

A.4.16. JANE............................................................................................................................. A-76 

A.4.17. KABA ........................................................................................................................... A-81 

A.4.18. KALA ........................................................................................................................... A-85 

A.4.19. KATA ........................................................................................................................... A-89 

A.4.20. KOO.............................................................................................................................. A-92 

A.4.21. LAMT ........................................................................................................................... A-96 

A.4.22. LAMW.......................................................................................................................... A-99 

A.4.23. LEE ............................................................................................................................... A-102 

A.4.24. LIU................................................................................................................................ A-106 

A.4.25. PERS............................................................................................................................. A-110 

A.4.26. SHIM ............................................................................................................................ A-113 

A.4.27. SOBU............................................................................................................................ A-117 

A.4.28. STOC ........................................................................................................................... A-120 

A.4.29. SVEN............................................................................................................................ A-120 

A-i 
A.4.30. TRIC ............................................................................................................................. A-124 

A.4.31. WU................................................................................................................................ A-128 

A.4.32. WUWI........................................................................................................................... A-132 

A-ii 
 APPENDIX A 

REVIEWS AND TIER ASSIGNMENTS FOR EPIDEMIOLOGIC 

STUDIES OF ETS AND LUNG CANCER 
APPENDIX A. REVIEWS AND TIER ASSIGNMENTS FOR 

EPIDEMIOLOGIC STUDIES OF ETS AND LUNG CANCER 

A.1. INTRODUCTION 

This appendix contains material that is used in Section 5.5, entitled Analysis by Tier and Country. As 

described in that section, each study is individually reviewed and assigned to one of four tiers based on its assessed 

utility for the objective of evaluating the evidence of an association between environmental tobacco smoke (ETS) 

exposure and incidence of lung cancer. The means of constructing study reviews is described in the next section, 

followed by a description of the scheme for scoring studies on various items and then assigning the studies to tiers 

according to the outcome. The final section of this appendix contains the individual study reviews and the tier 

numbers assigned to them. 

A.2. CONSTRUCTION OF INDIVIDUAL STUDY REVIEWS 

Descriptions of the four prospective cohort studies are individualized according to the requirements of each 

study. Reviews of case-control studies follow a structured format, consisting of three parts: (1) the author's 

abstract, which summarizes the most salient features and conclusions in the author's opinion; (2) a study description 

based on the contents of a completed study form designed around principles of good epidemiologic practice and 

issues specific to environmental tobacco smoke; and (3) a section of comments related to evaluation and 

interpretation of the study. The study reviews are used to assign studies to tiers according to the procedure 

described in Section A.3. 

The review form for case-control studies shown in Section A.2.1 was completed for each case-control 

study in order to systematically extract information about characteristics of interest for preparation of the reviews. 

The form was an aid in treating study reviews uniformly and noting omissions or incomplete discussion on issues 

that may affect the potential for bias or confounding. 

The study descriptions in Section A.4 were then prepared by following the outline and information in the 

completed forms. Some items included in the form pertain to characteristics that would apply to a case-control 

study on any topic, i.e., they are "generic items" related to principles of good epidemiologic investigation; the 

remaining items tend to identify areas of potential bias specific to the topic of ETS and lung cancer. 

A-1
A.2.1. Review Form for Case Control Studies 

PART I. GENERAL 

Study name 

Location 

Time period (data collection) 

Study objective(s) 

The source of the primary data set is the current study ____ or a parent study 

(ref) 

nonsmoker 

never-smoker 

"Exposed" to ETS means (preferably in terms of spousal smoking) 

Recall span (how far back in time ETS exposure was measured) 

ETS sources include cigarette _____ cigar ______ pipe _____ other _____ 

Describe inclusion of nonsmoking (never-smoking) females not currently married (number of cases and 

controls, assumptions regarding exposure) 

II. DATA COLLECTION (includes NS_____ FS_____ CS_____ unless noted) 

Inclusion/exclusion criteria 

Cases 

A-2
Controls (include matching variables in PART V) 

Main source of subjects 

Hospital(s) # 

Community 

Other 

Incident cases Y______ N_______ 

Control sampling 

Cumulative 

Unmatched 

Cases Controls 

______ ______ 

______ ______ 

______ ______ 

Density 

Matched 

Method of collection Cases Controls 

Face-to-face ______ _______ 

Telephone ______ _______ 

Self-admin. ques. ______ _______ 

Medical records ______ _______ 

Vital stat. records ______ _______ 

Other________ ______ _______ 

Collected data verified/corroborated with other sources Y______ N______ 

Sample size 

(prior to attrition) 

females 

males 

Attrition 

(selection or followup) 

females 

males 

Source of response 

subject 

proxy 

Cases Controls 

_______ _______ 

_______ _______ 

_______ _______ 

_______ _______ 

_______ _______ 

_______ _______ 

Exposure sources NS_____ FS_____ CS_____ 

Yes No 

Childhood ____ ____ 

A-3
 Adulthood ____ ____ 

Spouse 

Parents/in-laws 

Other family/ 

live-ins 

Workplace 

Other 

____ ____ 

____ ____ 

____ ____ 

____ ____ 

____ ____ 

Age NS_____ FS_____ CS_____ 

Distribution

______________ 

______________ 

______________ 

______________ 

Mean 

Standard error 

Standard deviation 

Range 

PART III. CLINICAL DATA 

Primary lung cancer verified by 

Histology 

Cytology 

Radiology/clinical 

Death certificate 

Tumor registry 

Mortality records 

Other_______ 

Not verified 

Cases Controls 

____________ ____________ 

____________ ____________ 

____________ ____________ 

____________ ____________ 

____________ ____________ 

____________ ____________ 

____________ ____________ 

____________ ____________ 

NS____ FS____ CS____ 

____ 

____ 

____ 

____ 

____ 

____ 

____ 

____ 

Airway proximity (no. exp cases/no. cases) NS____ FS____ CS____ 

Central _______________ 

Table ________ 

Peripheral _______________ 

A-4
Tumor type (no. exp cases/no. cases) NS____ FS____ CS____ 

Squamous cell ________________ 

Table________ 

Small cell ________________ 

Adenocarcinoma ________________ 

Large cell ________________ 

Others or unspecified ________________ 

PART IV. STATISTICAL ANALYSIS (includes NS____ FS____ CS____ unless noted) 

Raw data (for analysis) Cases 

females unexp ____________ 

exp ____________ 

males unexp ____________ 

exp ____________ 

Controls 

____________ 

____________ 

____________ 

____________ 

Comments (include measure of exposure) Table ________ 

Unadjusted (crude) analysis 

Estimate OR ______ ______% CI (______,______) 

Comments 

Test of p-value ________ 

signif. 

Test for p-value ________ 

trend 

Comments 

Adjusted analysis 

Estimate OR ______ ______% CI (______,______) 

Test of p-value ________ 

signif. 

Test for 

trend p-value _______ 

Comments 

Table ________ 

Table ________ 

Table ________ 

PART V. DEPENDENT VARIABLES (potential confounders and effects modifiers considered) 

A-5
 In Matching In Analysis Otherwise 

Age ____________ ____________ ____________ 

Gender ____________ ____________ ____________ 

Race/ethnicity ____________ ____________ ____________ 

Hospital ____________ ____________ ____________ 

Residence/ 

neighborhood ____________ ____________ ____________ 

Housing type ____________ ____________ ____________ 

House/room sizes ____________ ____________ ____________ 

Vital statistics ____________ ____________ ____________ 

Smoking status ____________ ____________ ____________ 

SES ____________ ____________ ____________ 

Medical health ____________ ____________ ____________ 

Menstrual/ 

reproductive ____________ ____________ ____________ 

Occupation ____________ ____________ ____________ 

Outdoor air 

pollution ____________ ____________ ____________ 

Cooking habits ____________ ____________ ____________ 

Drinking ____________ ____________ ____________ 

Diet ____________ ____________ ____________ 

Education ____________ ____________ ____________ 

Family history 

of lung cancer ____________ ____________ ____________ 

Other indoor 

smoke/fumes ____________ ____________ ____________ 

Radon ____________ ____________ ____________ 

Lifestyle ____________ ____________ ____________ 

Climate/ 

ventilation ____________ ____________ ____________ 

A.3. TIER CLASSIFICATION SCHEME

The items and study scores used in the algorithm to calculate tier numbers are given in Table A-1. The 

items and scoring system in that table and the algorithm for converting the scores to a tier number are the topics of 

this section. 

The items displayed in the headings of Table A-1 will be described after explanation of how assignments 

are calculated from the numbers in that table. Positive values in the table are unfavorable (penalty points); a blank 

entry means the item was not a problem; negative values are favorable (bonus points) and occur in a few instances 

where the study performed well above the norm indicated by a blank, e.g., FONT, KOO, and HOLE(Coh) each 

have an entry of "-0.5" under "Less than 90% confirmation by histology or cytology" in Category C for particularly 

high attention given to confirming primary lung cancer in subjects classified as cases. Bonus scores are always -0.5 

and are assigned somewhat sparingly as they have the potential to cancel penalty scores and thus mask a study 

weakness. Parentheses around an entry indicate that the penalty points were assigned due to insufficient 

information (so there is effectively a penalty imposed if the information needed was not included in the source). 

The asterisk that occurs under the item "unsuitable indoor environment" is a marker that automatically places the 

A-6
study into Tier 4 under the assignment rule to be described next (the unsuitable environment refers to high levels of 

coal smoke in all instances). 

Tier numbers for each study are calculated from the entries in Table A-1 as follows. Totals are calculated 

by category and across all items, as shown in Table A-2. If the total for each category is less than 2.5, then the tier 

assignment is determined as follows: 

Total Score Tier 

1.75 or less 1 

2.00 - 3.75 2 

4.00 - 5.75 3 

6.00 or greater 4 

The value 2.5 is designated as a cutoff point for each category. If a study has one or more category totals greater 

than or equal to 2.5, the tier classification is increased by 1 (i.e., 1 is added to the tier number shown in the above 

table if any category totals are 2.5 or greater). The three studies conducted in regions of China where indoor air is 

heavily polluted with smoke from burning coal, denoted by an asterisk under item "unsuitable indoor environment," 

are placed in Tier 4 (see reviews in Section A.4 for GENG, LIU, and WUWI). The resultant assignment of studies 

to tiers is shown in Table A-2. 

A scheme that attempts to assess utility and to numerically rank studies accordingly, as done here, has a 

high degree of subjectivity. Different analysts would be apt to disagree about elements of any such approach and 

the appropriate weights for those elements in assigning studies to tiers, as suggested above. One of the difficulties 

is that the significance of a study "weakness" is difficult to assess. For example, the use of proxy respondents may 

be a source of bias, but the direction and magnitude of bias are unknown for any given study. Thus, one is faced 

with rating studies largely on the basis of one's ability to ascertain what study features are significant and 

A-7
Table A-1. Study scores for tier assignments 

Category A Category B 

Study 

Former smokers 

included 

Smoking status 

unverified 

Exposure criteria 

questionable 

Exposure of 

unmarrieds 

Exposure 

Status unverified 

AKIB -0.5 

BROW 1 (0.5) 

BUFF 1.5 

CHAN 2 (0.5) 

CORR 0.5 

FONT -0.5 -0.5 

GAO 1.5 0.5 

GARF 0.5 0.5 

GENG 1 1 

HUMB 0.5 

INOU 1 1 

JANE 

KABA 0.5 1 

KALA 

KOO 

LAMT 0.5 

LAMW 

LEE 

LIU 1 

PERS -0.5 

SHIM 

SOBU 

SVEN 

TRIC 1 

WU 0.5 

WUWI 1 

BUTL(Coh) 

GARF(Coh) 1 

HIRA(Coh) 0.5 

HOLE(Coh) 

(continued on the following page) 

A-8
Table A-1. (continued) 

Category C Category D 

Study 

Secondary lung 

Cancers possible 

Less than 90% confirm. 

histol./cytol. 

Less than 90% 

face-to-face 

Unblinded 

interviews 

AKIB 1 0.5 

BROW 

BUFF 

CHAN 0.75 0.5 

CORR (0.5) 

FONT -0.5 (0.5) 

GAO 0.5 (0.5) 

GARF 

GENG 

HUMB 0.5 

INOU 0.75 (0.5) (0.5) 

JANE 0.5 

KABA 

KALA 0.5 (0.5) 

KOO -0.5 

LAMT 

LAMW (0.5) 

LEE 0.75 (0.5) 0.5 

LIU 0.75 1 

PERS 0.5 

SHIM 0.5 (0.5) 

SOBU 0.5 (0.5) 

SVEN 1 0.5 

TRIC 1 0.5 

WU 1 0.5 

WUWI 0.5 0.5 

BUTL(Coh) 0.5 

GARF(Coh) 0.5 1 0.5 

HIRA(Coh) (0.5) 0.5 

HOLE(Coh) (0.5) -0.5 

(continued on the following page) 

A-9
Table A-1. (continued) 

Category E Category F 

(Cohort Only) 

Study More than 10% proxy 

respondents 

Uneven proxy response 

distribution 

Change in smoking or 

ETS status 

More than 10% loss 

to followup 

AKIB 1 

BROW 1 0.75 

BUFF 1 

CHAN 0.75 

CORR 0.5 

FONT 0.5 

GAO 

GARF 1.5 

GENG 

HUMB 1 0.75 

INOU 1 

JANE 0.5 

KABA 

KALA 

KOO 

LAMT 

LAMW 

LEE 0.5 

LIU 

PERS (0.5) 

SHIM 

SOBU 

SVEN 

TRIC 

WU 

WUWI 

BUTL(Coh) 0.5 

GARF(Coh) 0.5 0.75 

HIRA(Coh) 0.5 

HOLE(Coh) 0.5 (0.5) 

(continued on the following page) 

A-10
Table A-1. (continued) 

Category G 

(Case-control only) 

Study 

Unsuitable 

Indoor environment 

Smoking-related disease in 

controls 

Nonincident cases 

Included 

AKIB 0.5 

BROW (0.5) 

BUFF 

CHAN 0.75 

CORR 0.5 

FONT 

GAO 

GARF 0.75 (0.5) 

GENG * 

HUMB 

INOU 0.75 (0.5) 

JANE 

KABA 

KALA 

KOO 

LAMT 

LAMW 

LEE 

LIU * 

PERS 

SHIM 0.75 (0.5) 

SOBU 0.75 

SVEN 0.5 

TRIC 

WU 

WUWI * 

BUTL(Coh) 

GARF(Coh) 

HIRA(Coh) 

HOLE(Coh) 

(continued on the following page) 

A-11
Table A-1. (continued) 

Category H 

Study 

Uncontrolled 

for age 

Uncontrolled for 

other factors 

Problem(s) 

with stat. methods 

AKIB 

BROW 1.5 0.5 

BUFF 1.5 

CHAN 1.5 

CORR 1.5 

FONT 0.5 

GAO 1 

GARF 

GENG 1.5 1 

HUMB 

INOU 

JANE 1 

KABA 1.5 

KALA 

KOO 1 

LAMT 1.5 

LAMW 1.5 1 

LEE 

LIU 1.5 1 

PERS 

SHIM 1.5 

SOBU 1 

SVEN 

TRIC 1.5 

WU 1 

WUWI 1 

BUTL(Coh) 1 

GARF(Coh) 

HIRA(Coh) 

HOLE(Coh) 

A-12
Table A-2. Total scores and tier assignment 

Category 

Study A B C D E F G H Total 

Tier 

Assign. 

AKIB -0.5 1 0.5 1 0.5 2.5 2 

BROW 1.5 1.75 0.5 2.0 5.75 3 

BUFF 1.5 1 1.5 4.0 3 

CHAN 2.5 1.25 0.75 0.75 1.5 6.75 4 

CORR 0.5 0.5 0.5 0.5 1.5 3.5 2 

FONT -0.5 -0.5 -0.5 0.5 0.5 0.5 0 1 

GAO 1.5 0.5 0.5 1.5 4.0 3 

GARF 1 1.5 1.25 3.75 2 

GENG 1 1 * 2.5 4.5 4 

HUMB 0.5 0.5 1.75 2.75 2 

INOU 1 1 1.25 0.5 1 1.25 6.0 4 

JANE 0.5 0.5 1 2.0 2 

KABA 0.5 1 1.5 3.0 2 

KALA 0.5 0.5 1.0 1 

KOO -0.5 1 0.5 1 

LAMT 0.5 1.5 2.0 2 

LAMW 0.5 2.5 3.0 3 

LEE 1.25 0.5 0.5 2.25 2 

LIU 1 1.75 * 2.5 5.25 4 

PERS -0.5 0.5 0.5 0.5 1 

SHIM 1 1.25 1.5 3.75 2 

SOBU 1 0.75 1 2.75 2 

SVEN 1.5 0.5 2.0 2 

TRIC 1 1 0.5 1.5 4.0 3 

WU 0.5 1.5 1 3.0 2 

WUWI 1 0.5 0.5 * 1 3.0 4 

BUTL(Coh) 0.5 0.5 1 2.0 2 

GARF(Coh) 1 1.5 0.5 1.25 4.25 3 

(continued on the following page) 

A-13
Table A-2. (continued) 

Category 

Study A B C D E F G H Total 

Tier 

Assign. 

HIRA(Coh) 0.5 1 0.5 2.0 2 

HOLE(Coh) 1 1.0 1 

*Unsuitable indoor environment 

some quantitative construct reflecting an opinion of their relative importance. Additionally, there is the possibility 

of misinterpreting the source or of the omission of needed information from the source. A further limitation is the 

inability to include all features of all studies that might affect one's judgment of it. 

Reservations notwithstanding, the heterogeneity of the ETS studies in objectives and characteristics of 

design, data collection, analysis, and interpretation make it worthwhile to classify studies according to some 

evaluation of their utility for assessing ETS and lung cancer. The items used for scoring studies are described in the 

remainder of this section. The descriptions are written in the language of case-control studies (references to "cases," 

"controls," etc.). Where cohort studies are evaluated (end of Table A-1), the equivalent concept for cohort studies is 

applied under each category heading, with exceptions as noted in the text. An "ideal" is described for each item, to 

give the scores a reference point. The ideal applies to the needs of this report, however, and not to what may have 

been the ideal for the individual study objectives. 

Very few of the studies were designed and executed with the sole, or even primary, objective of this report. 

Consequently, high penalty scores or an unfavorable tier assignment indicating limited utility for our objectives 

should not be interpreted as low study quality relative to the purpose for which the study was conducted. 

Comments included on the likely direction of bias refer to bias of the relative risk estimate. "Upward bias" is an 

expected excess in the observed relative risk above its true (but unknown) value (which is 1.0 if the null hypothesis 

of no effect is correct). "Downward bias" refers to bias in the opposite direction. "Bias toward the null hypothesis" 

is used sometimes in the text. It refers to an influence on the observed relative risk toward 1.0, the value of the true 

relative risk when the null hypothesis is correct. When the true 

relative risk exceeds 1, "bias toward the null" and "downward bias" are interchangeable. The probable magnitude 

of bias is more difficult to ascertain than the likely direction of bias. The relative values of the penalty scores under 

items in Table A-1 reflect our judgment on this issue. To determine why a specific study was scored with penalty or 

bonus points on any particular item, the reader needs to refer to the review of that study in Section A.4. A 

description of items in Table A-1 follows. 

A-14
Category A: Never-Smoker Status 

� Inclusion of former smokers. The ideal is for all subjects to be true never-smokers. Inclusion of 

subjects who report themselves as never-smokers but who are actually current smokers causes an 

upward bias in the relative risk (see Section 5.2.2 and Appendix B). Inclusion of former smokers may 

be a source of upward bias by similar arguments. Some degree of former smoking may be 

inconsequential depending on how much was smoked and the subsequent duration of abstinence, but 

this relationship is not well understood. Penalty points of 0.5 or 1 were assigned to studies that 

allowed some prior smoking because we view it as adding some degree of uncertainty compared with 

exclusive use of never-smokers as subjects. 

� Verification of smoking status. The ideal is to implement all means available to verify the neversmoking status claimed by subjects. No studies were penalized on this item, but the few studies (i.e., 

FONT and PERS) that conducted thorough verification were given a bonus of -0.5. 

Category B: ETS-Exposure Criteria 

� Exposure criteria questionable. The ideal is for a female to be classified as ETS exposed according to 

a measure of duration (e.g., years of spousal smoking) and a measure of intensity (e.g., number of 

cigarettes smoked per day by the spouse). Of course, collecting data on measures of exposure is not 

meaningful unless it enters into the analysis. For the purpose of this report, the objective for casecontrol studies is to differentiate between subjects as sharply as possible on exposure to ETS using 

spousal smoking as an indicator. Knowledge is too limited to know how to accomplish this exactly, 

but extremes wherein the exposed group contains subjects with very little exposure or includes only 

subjects with very high exposure (while all lesser exposed subjects are classified as "unexposed") 

should bias results toward the null hypothesis. For cohort studies, GARF(Coh) was penalized because 

the duration of exposure to spousal ETS was limited. 

� Exposure of unmarrieds. Ideally for this report, where the presence or absence of spousal smoking is 

emphasized as the main determinant of ETS exposure because of its high commonality among studies, 

subjects would be female never-smokers whose history of exposure to spousal smoke has been 

reasonably constant over an extended duration (independent of whether a subject may have been 

married more than once). Studies vary in the extent to which this topic is considered and how it is 

handled, and assumptions may need to be considered in view of a country's social practices. For 

example, some studies classify women as unexposed to ETS while unmarried, which may be more 

reasonable in some cultures than others (e.g., probably more reasonable in Greece than in the United 

States). Biases resulting from this item are most commonly toward the null hypothesis. 

A-15
� Verification of exposure status. The ideal is to verify statements regarding present and past exposure 

to ETS from spousal smoking from other sources. Two studies, AKIB and FONT, were given bonus 

points for extended efforts in that direction; no studies were penalized. 

Category C: Lung Cancer Indication 

� Secondary lung cancers possible. The ideal is assurance that all cases are accurately diagnosed with 

primary lung cancer and that cases are not included where the lung cancer may be secondary to 

another site. This item is closely related to the next one, which is concerned with the method of 

diagnosis/confirmation. Bias is toward the null hypothesis. 

� Less than 90% confirmation by histology or cytology. The ideal is that the original diagnosis of lung 

cancer, or a confirmation of it, is conducted by histology. No penalty points are assigned, however, if 

at least 90% of the cases are diagnosed or confirmed by histology or cytology. Three studies, FONT, 

KOO, and HOLE(Coh), were given bonus points for extended efforts in diagnostic confirmation. The 

direction of bias is toward the null hypothesis. 

Category D: Interview Type 

� Less than 90% face-to-face interview. The ideal interviewing technique is face-to-face by trained 

interviewers. The effect on the quality of information from other types of data collection is unclear, 

but telephone interviews and mail-in questionnaires probably increase the rate of misclassification of 

subject information. The bias is toward the null hypothesis if the proportion of interviews by type is 

the same for cases and controls, and of indeterminate direction otherwise. 

� Unblinded (case-control studies only). The ideal is for the interviewer to be unaware whether the 

subject is among the cases or controls and the subject to be unaware of the purpose and intended use 

of the information collected. Blinding of the interviewer is generally not possible in a face-to-face 

interview. In face-to-face and telephone interviews, potential bias may arise from the investigator's 

expectations regarding the relationship between ETS exposure and lung cancer incidence. The 

potential for bias is probably less with mail-in interviews. 

Category E: Proxy Respondents 

� More than 10% proxy respondents (10% of total for cohort studies and 10% of either total cases or 

total controls for case-control studies). The ideal is for data to be supplied by the subject because the 

subject generally would be expected to be the most reliable source. A subject may be either deceased 

or too ill to participate, however, making the use of proxy responses unavoidable if those subjects are 

to be included in the study (some studies appeared to exclude them). The direction and magnitude of 

A-16
bias from use of proxies is unclear, and may be inconsistent across studies. 

� Uneven distribution between cancer/noncancer subjects. Ideally, the use of proxies is evenly 

distributed between cases and controls because this might be expected to minimize any net bias 

remaining from the use of proxy responses. The use of proxies is often much higher for cases than for 

controls, as one might expect. The effect of proxy distribution on bias is indeterminate. 

Category F: Followup (Cohort Studies Only) 

� Changes in smoking or ETS exposure not addressed. The ideal is for any changes in personal 

smoking status or exposure to spousal ETS to be recorded and taken into account in the analysis. If a 

subject begins active smoking during the course of the study, it may lead to upward bias (from 

arguments like those given for the effect of smokers who misreport themselves as never-smokers, as 

discussed in Section 5.2.2 and Appendix B); if the smoking status of the spouse changes, the likely 

bias would be toward the null hypothesis. 

� More than 10% loss to followup. The ideal, of course, is zero loss to followup. The ideal is not 

achievable in practice, but it seems reasonable to expect loss to followup not to exceed 10%. The bias 

from loss to followup is indeterminate. Random loss may have less effect than if subjects who are not 

followed up have some significant characteristics in common. 

Category G: Design Issues 

� Unsuitable indoor environment. The ideal indoor air environment contains no significant sources of 

pollution from nontobacco sources that likely contain one or more of the known or suspected 

carcinogens identified in tobacco smoke or would otherwise be expected to increase the incidence of 

lung cancer. The presence of high concentrations of indoor smoke from unvented or inadequately 

vented indoor combustion of coal for purposes of warmth or cooking is commonplace in some regions 

of China where studies were conducted. This condition is indicated in some studies and has been 

confirmed from other sources (see reviews in Section A.4 for GENG, LIU, and WUWI). It is 

expected that indoor coal smoke increases the level and variability of exposure to many of the same 

carcinogenic agents that occur in ETS, and therefore detection of an incremental increase in lung 

cancer incidence from ETS would be highly unlikely in such a setting. 

� Smoking-related disease in controls (case-control studies only). The ideal is for controls to be free of 

any disease related to tobacco smoke. This is an issue in some studies where hospital controls are 

used. Potential bias is toward the null hypothesis. 

� Nonincident cases included (case-control studies only). The ideal is for all cases to be incident (i.e., 

new cases that develop during an interval of time). A few studies began with prevalent cases and then 

A-17
proceeded with incident cases. The use of prevalent cases may introduce some bias of unknown 

direction because prevalence is affected by survival rate and lung cancer patients generally do not 

survive for an extended period. All studies scored on this item were given one-half point, which is in 

parentheses in most instances, indicating that information in the source is incomplete. Interview 

information must be obtained from surviving kin or other proxy subjects as well, but that issue is 

treated separately in a following item. Potential bias is of uncertain direction. 

Category H: Analysis Issues 

� Uncontrolled for age. The ideal is to control for age by matching on age in the design and then 

adjusting for age in the analysis of data. There is no clear formula for deciding which variables 

should be included in a matched analysis, and/or addressed in the analysis of the data collected. Age, 

however, is likely correlated with total exposure for those classified as exposed to ETS and is 

suspected of playing a role in cancer etiology. The potential bias from age might be significant, but its 

likely direction and magnitude depend in an unknown way on the disparity of age distributions 

between cases and controls. 

� Uncontrolled for other factors of importance. This item applies to studies that report an increased 

association of lung cancer with factors other than ETS exposure but do not consider further whether 

these factors may be confounders that should be controlled for in the analysis for ETS. For a variable 

to be a confounder of ETS, exposure to the variable and to ETS must be correlated (which determines 

the degree of confounding), and the association of the factor with lung cancer must be causal. The 

correlation should be readily calculable from the study data. Conclusions about causation may not be 

warranted, but one could still make the necessary calculations under the assumptions that they are 

causative and then report what implications causation (if correct) would have for the assessment of 

ETS. The expected effect from controlling for confounders is to move the estimated relative risk 

closer to the true value. 

� Problem(s) with statistical methods. The ideal is that conclusions are drawn from the application of 

statistical methods that are appropriate to the problem and accurately interpreted. One penalty point 

was assigned studies where we took issue with the statistical methodology or results. The direction of 

bias is indeterminate, in general, as the situations differ between studies. 

A-18
A.4. INDIVIDUAL STUDY REVIEWS 

This section of Appendix A contains a review of each epidemiologic study based on the primary references 

listed in Table 5-1. Descriptions of the four prospective cohort studies are individualized according to the 

requirements of each study--for example, HIRA(Coh) has a long history of controversy in the literature, so the main 

arguments are chronicled and discussed as part of the review. As noted previously, reviews of case-control studies 

follow a structured format, consisting of three parts: (1) the author's abstract, which summarizes the most salient 

features and conclusions in the author's opinion; (2) a study description based on the contents of a completed study 

format designed around principles of good epidemiologic practice and features specific to ETS; and (3) a section of 

comments related to evaluation and interpretation of the study. The author's abstract is, of course, entirely the 

author's own words; the study description is intended to portray accurately the reference article vis-a-vis items in the 

study format, so the author's words are used when possible; the comments section is entirely our own assessment of 

characteristics relevant to study interpretation and utility in this report. 

An abstract only is available for the case-control study by Stockwell et al., (1991), referred to as STOC, 

which has not appeared in print yet. There is insufficient information on the study to include it in the main body of 

this report. Similarly, an abstract only is available for the second study of Kabat and Wynder (Kabat, 1990), which 

is included in an addendum following the review of their first study, KABA. The data for many of the studies 

reviewed have been extracted from a larger, more comprehensive study that includes active smokers. The subjects 

and their data used for investigation of an association between ETS exposure and lung cancer incidence are referred 

to as "ETS subjects" and "ETS data," respectively. 

A-19
A.4.1. AKIB (Tier 2) 

A.4.1.1. Author's Abstract 

"A case-control study conducted in Hiroshima and Nagasaki, Japan, revealed a 50% increased risk of lung 

cancer among nonsmoking women whose husbands smoked. The risks tended to increase with amount smoked by 

the husband, being highest among women who worked outside the home and whose husbands were heavy smokers, 

and to decrease with cessation of exposure. The findings provide incentive for further evaluation of the relationship 

between passive smoking and cancer among nonsmokers." 

A.4.1.2. Study Description 

This community-based case-control study was conducted in Hiroshima and Nagasaki, Japan, in 1982. The 

data collected on passive smoking are part of a larger investigation of lung cancer among atomic bomb survivors, 

the principal objective of which is to evaluate the interactive roles of cigarette smoking and ionizing radiation. This 

article reports on married female never-smokers, an unmatched subset of the data from the whole study. 

The whole study includes a total of 525 primary lung cancer cases diagnosed between 1971 and 1980. 

Cases were identified from the Hiroshima and Nagasaki Tumor and Tissue Registries and other records. Controls 

were selected from among the cohort members without lung cancer, two per case in Hiroshima and three per case in 

Nagasaki. The controls were individually matched to the cases with respect to year of birth (" 2 years), city of 

residence (Hiroshima or Nagasaki), sex, biennial medical examinations, and vital status. The majority of cases were 

deceased; those cases were matched to decedent controls by year of death (" 3 years), in addition to the other 

criteria. Controls were selected from causes of death other than cancer and chronic respiratory disease. Face-toface interviews were conducted for 81% (82%) of the eligible cases (controls), but 80% to 85% of the interviews for 

both cases and controls were actually conducted with the subject's next of kin. The mean age of cases at diagnosis 

is 72.1 years (range 36-94) for males and 70.2 (range 35-95) for females, which is high for lung cancer in Japan. 

Fifty-seven percent of the cases were pathologically confirmed; the remaining 43% were diagnosed by radiological 

or clinical findings. 

ETS exposure in adulthood was assessed by spousal smoking status, including the average number of 

cigarettes smoked per day, age the spouse started smoking, and, for those who stopped smoking, the age at 

cessation. For childhood exposure, a single question was asked regarding whether the subject's mother or father or 

both smoked when the subject was living at home as a child; responses were obtained for only two-thirds of the 

subjects. No specific information on exposure to smoking by other household members' smoking or to smoking in 

the workplace was obtained. ETS exposure data were checked by comparing smoking status with records from 

RERF surveys in 1964-68 (self-reported by subjects when they were alive). Cases and controls who had never 

married were excluded. Of the female cases exposed to spousal smoking, 16% had squamous or small cell 

carcinoma, whereas no unexposed cases had those cell types. No information was provided on location of the 

A-20
carcinomas. 

The number of female cases exposed to ETS is 73 out of 94 (number exposed/total) compared with 188 out 

of 270 female controls (crude odds ratio [OR] is 1.52 [95% confidence interval [C.I.] = 0.88, 2.63], by our 

calculations). Application of logistic regression to the whole study that includes active smokers, gives an adjusted 

odds ratio of 1.5 (90% C.I. = 1.0, 2.5), similar to the crude analysis. It is not stated explicitly that matching 

variables were included in the logistic regression model. Four additional analyses were conducted on the ETS data 

alone (i.e., without active smokers). The authors stratified exposure by number of cigarettes smoked per day by 

husband (0, 1-19, 20-29, 30+) and obtained a marginally significant trend (p = 0.06). No dose-response gradient 

was found in the association between the number of years the husband smoked cigarettes and the risk of lung cancer 

in female never-smokers; the odds ratio decreases from lowest to highest exposure level (2.1, 1.5, and 1.3). 

Stratified analysis according to recency of exposure to husband's smoking (unexposed, exposed but not within the 

past 10 years, and exposed within the past 10 years) shows a significant upward trend (p = 0.05). Further 

stratification of exposed subjects by occupation found that lung cancer risk tends to increase across occupational 

categories in the following order: housewife, white collar worker, blue collar worker. The highest odds ratio 

occurred for women who had blue collar jobs and were married to men who smoked one or more packs of cigarettes 

per day, but the number involved was small. It is reported that additional analyses of the data indicated that factors 

for matching in the whole study have little influence, but the details are omitted. 

Limited histological information is provided. Among cases exposed to spousal smoking, 16% had 

squamous or small cell cancer, and 84% had adenocarcinoma or large cell cancer. All of the unexposed cases had 

adenocarcinoma. 

The authors conclude that there may be a moderate excess in lung cancer risk associated with passive 

smoking. The odds ratio for lung cancer among nonsmoking women tends to increase with amount smoked by their 

husbands, a trend seen among housewives, as well as among women who work outside the home. There was little 

association with parental smoking or from passive smoking that had ceased more than 10 years previously. 

A.4.1.3. Comments 

The larger study from which the ETS data are taken was primarily intended to investigate the interaction of 

smoking and ionizing radiation in atomic bomb survivors of Nagasaki and Hiroshima. The information on passive 

smoking has been collected posthumously in a large percentage of the cases, requiring heavy use of proxy 

responses. The response rate was not high, however, because some next of kin refused to answer questions about 

deceased relatives and no attempt was made to locate next of kin of some subjects who had died or moved away 

from Hiroshima or Nagasaki. The dependence on proxy respondents raises questions about the validity of the 

exposure data for some measures, particularly in childhood, and about detailed information such as the number of 

cigarettes smoked per day, duration of smoking habit, and years since cessation of smoking. Information on 

A-21
childhood exposure was obtained for only two-thirds of the subjects. The omission of data on subjects where the 

next of kin had refused response or the subject had moved may be a source of bias. The diagnosis of lung cancer 

was not pathologically confirmed in more than 40% of the cases. Also, it is not clear that the subjects are 

representative of the target population. They had been exposed to ionizing radiation to varying degrees, whatever 

implication that may have; they are among the survivors, which may suggest selective characteristics; and their age 

distribution is high, ranging from about 35 to 90 years of age with an average of 70 years or more. 

Only ever-marrieds are included in the ETS subjects, which is helpful in the analysis. There is some 

ambiguity in the statistical analyses, however, in reference to Tables 2 through 6 (the main results). The tables 

contain odds ratios that are reported to be the result of logistic regression with matching. The details regarding 

matching in the analysis are not given, but it is reported that analysis of the crude data and matched logistic 

regression give similar values. Regarding the analyses for trend, the outcome seems to be sensitive to the measure 

of exposure used. The odds ratios are strictly increasing for stratification by number of cigarettes smoked per day, 

but a different pattern emerges when ETS exposure is measured by the number of years the husband smoked 

cigarettes. 

In general, the conclusions are presented more strongly than the data warrant. The assertions are somewhat 

tenuous that risks tend to increase with amount smoked by the husband, are highest among those who work outside 

the home and whose husbands are heavy smokers, and decrease with cessation of smoking. Conversely, whereas 

little association between ETS exposure in childhood and lung cancer is reported, relevant information was 

available for only two-thirds of the subjects, and its accuracy is questionable because most of that information was 

provided by proxies. Overall, the observed data suggest that ETS exposure may be related to risk of lung cancer, 

but there is some potential for misclassification and other sources of bias. Thus, this study provides some useful 

information on lung cancer risk in passive smokers, but its interpretation needs to be conservative, taking into 

account the atypical characteristics of the subjects and other concerns described above. 

A-22
A.4.2. BROW (Tier 3) 

A.4.2.1. Author's Abstract 

"The relation between various risk factors and adenocarcinoma of the lung was evaluated in a case-control 

study. Subjects were selected from the Colorado Central Cancer Registry from 1979-82 in the Denver metropolitan 

area. A total of 102 (50 males and 52 females) adenocarcinoma case interviews and 131 (65 males and 66 females) 

control interviews were completed. The control group consisted of persons with cancers of the colon and bone 

marrow. The risk estimates associated with cigarette smoking were significantly elevated among males (OR = 4.49) 

and females (OR = 3.95) and were found to increase significantly (p < 0.01) with increasing levels of cigarette 

smoking for both males and females. For adenocarcinoma in females, the age- and smoking-adjusted odds ratios at 

different levels of passive smoke exposure followed an increasing overall trend (p = 0.05). After additional 

adjustment for potential confounders, prior cigarette use remained the most significant predictor of risk of 

adenocarcinoma among males and females. Analysis restricted to nonsmoking females revealed a risk of 

adenocarcinoma of 1.68 (95% C.I. = 0.39, 2.97) for passive smoke exposure of 4 or more hours per day. Neither 

sex showed significantly elevated risk for occupational exposures, although males bordered on significance (OR = 

2.23, 95% C.I. = 0.97, 5.12). The results suggest the need to develop cell type-specific etiologic hypotheses." 

A.4.2.2. Study Description 

This study was conducted in Denver, Colorado, to evaluate the role of smoking, passive smoking, 

occupation, community air pollution, and socioeconomic status in the etiology of adenocarcinoma of the lung. 

Because subjects include active smokers, the data on ETS subjects are part of a larger data set. 

Cases and controls were drawn from the Colorado Central Cancer Registry. All subjects were diagnosed 

with lung adenocarcinoma between 1979 and 1982. Cases are white female Denver residents of at least 6 months' 

duration. Controls are of similar description to the cases, except that they were diagnosed with colon cancer or bone 

marrow cancer. Controls were matched on a group basis to produce the same age and gender composition. It is not 

clear if incident cases were used and whether control sampling was cumulative or density. 

The subjects are not matched on smoking status, so the data on ETS subjects alone are unmatched for all 

variables considered in the larger study. Face-to-face interviews were conducted, blindly, on a total of 149 cases 

and 169 controls, after attrition in selection and follow-up of 47 cases and 38 controls. The subject was interviewed 

in 31% of the cases and 61% of the controls; the remaining interviews were conducted with a friend or relative. The 

mean age of the female cases (controls) was 64.9 (68.2) years; no further details are provided. Clinical verification 

of lung cancer diagnosis was conducted microscopically. 

"Exposed" to ETS is used in two ways, depending on context: (1) the husband smoked (presumably "eversmoked" is intended, rather than "currently smokes," but that is not explicit); (2) the subject was in the presence of 

tobacco smoke, from any source, 4 or more hours per day on average. Although there are two operational 

A-23
definitions of exposure, neither includes duration of ETS exposure. Questions were apparently asked regarding 

exposure in both childhood and adulthood, the latter including sources in the home and in the workplace. No 

indication was found that the data collected from subjects were checked for internal consistency or against other 

sources. No mention was found regarding the number of unmarried women in the study or what assumptions may 

have been made regarding their exposure to ETS when spousal smoking is the source considered (the first of the 

definitions given above). 

The ETS subjects consist of 4 out of 19 (exposed/total) female cases and 7 out of 47 controls, when ETS 

exposure means the spouse smoked (Definition 1). For exposure from all sources (Definition 2), the corresponding 

numbers for cases and controls are 4 out of 19 and 6 out of 47, respectively. The crude odds ratio is 1.52 (95% C.I. 

= 0.39, 5.96) for Definition 1 of ETS exposure and 1.82 (95% C.I. = 0.45, 7.36) for Definition 2 (data 

communicated from first author, Brownson). A test for trend using hours per day as the exposure measure is 

conducted on the whole data set for females including smokers (33 of 52 cases are smokers and 19 of 66 controls 

are smokers; the two exposure categories, 4 to 7 and 8 or more hours per day of exposure to passive smoke, contain 

a total of only 4 cases and 6 controls who are nonsmokers, but 19 cases and 7 controls who are smokers). The 

method of Miettenen is applied with stratification on age and smoker status (p = 0.05 for trend). The data for neversmokers alone were used in a multiple logistic regression to compare subjects exposed 0 to 3 hours per day with 

those exposed from all sources 4 or more hours per day (Definition 2 of ETS exposure). Adjustments were made 

for age, income, and occupation. The reported odds ratio is 1.68 (95% C.I. = 0.39, 2.97). (Note: It appears that the 

upper confidence value may be in error. In view of the outcome for the crude odds ratio, a value about twice what 

is shown might be anticipated.) 

To summarize the statistical tests and authors' conclusions, no significant risk estimates were shown when 

smoking by the spouse was considered as a dichotomous variable. When the data for both active smokers and 

passive smokers were stratified according to level of passive smoke exposure, a statistically significant trend in the 

risk estimates was shown for females (p = 0.05) after adjustment for age and cigarette smoking. However, after 

adjustment by logistic regression for age, income, occupation, and cigarette smoking, with the two exposure 

categories for ETS combined (> 3 and 4+ hours per day), no significant risk was detected. 

A.4.2.3. Comments 

The study is very small when reduced to the never-smokers alone. The measure of ETS exposure used 

(hours/day from all sources) is not very specific to differentiate exposed from unexposed persons, particularly 

exposure 20 to 30 years ago, which may be more relevant than current exposure. Only 15% of the controls have a 

husband who smoked; only 13% of ETS subjects are exposed from any source 4 or more hours per day. Thus, the 

cut-point selected by the researchers for general ETS exposure (4+ hours/day) may be too high, resulting in a 

substantial amount of exposure in the "unexposed" group. For either definition of ETS exposure, however, the 

A-24
percentage exposed is extremely low. Details are lacking also in other areas that may have a bearing (e.g., the 

treatment of unmarried subjects--whether they were present and, if so, the assumption made regarding ETS 

exposure). 

We experienced some difficulty with the statistical analyses. One of the adjusted procedures is the trend 

test. Perhaps because the number of ETS subjects is so small, smokers were included in the analysis and then a 

method was used to attempt to adjust the effects of their presence on the outcome. It would be preferable, in our 

view, to omit the smokers from the analysis entirely. There are so few ETS subjects in the exposure categories (see 

above) that it seems highly unlikely that a test for trend would be significant if based on the ETS subjects alone (we 

did not have the number of ETS subjects by exposure group, however, so we were unable to conduct the trend test 

to check the outcome). 

When the two exposure categories were combined and only the ETS subjects used, the results were not 

close to statistically significant (OR is 1.68; 95% C.I. = 0.39, 2.97). We also view that result with caution because 

using the same data for analysis that were used to determine which variables to adjust for may distort the statistical 

interpretation. There also may be a typographical error in the upper confidence limit because the value shown is 

only about half the corresponding value for the crude odds ratio. 

The remaining analyses are from the crude odds ratio, 1.52 (95% C.I. = 0.39, 5.99) and 1.82 (95% C.I. = 

0.45, 7.36), which suggests a possible association between ETS exposure and lung cancer, although it could easily 

be ascribed to chance in view of the wide confidence intervals. The study has a very strict requirement for 

classification as exposed to ETS (4+ hours per day from any source of ETS), which is reflected in only 15% of the 

controls being designated as exposed (40-60% is more typical). This percentage is only slightly higher than the 

12% figure based on simply being married to a smoker. The control subjects thus appear unrepresentative of 

exposure to the target population, or else the classification of subjects exposed is too rigid. The crude odds ratio 

may be the preferred statistical measure to represent the outcome of the data, but care should be exercised in using 

the results from this study in conjunction with those of other studies. 

A-25
A.4.3. BUFF (Tier 3) 

A.4.3.1. Author's Abstract 

"A population-based case-comparison interview study of lung cancer was conducted from 1979 to 1982 in 

six Texas coastal counties--Orange, Jefferson, Chambers, Harris, Galveston, and Brazoria--to evaluate the 

association of lung cancer with occupational and other environmental exposures. Lung cancer mortality rates in 

these counties consistently have exceeded lung cancer mortality rates observed for Texas and the United States from 

1950-69 to 1970-75 for both sexes and races (white and nonwhites). 

Histologically and cytologically confirmed incident cases diagnosed during the interval July 1976 to June 

1980 among white male and female residents ages 30 to 79 years were ascertained from participating hospitals in 

the six-county area. Both population-based and decedent comparisons were selected and matched on age, race, sex, 

region of residence, and vital status at time of ascertainment. The exposures of primary interest in the study of lung 

cancer are those associated with occupation (employment in specific industries and occupations) in conjunction with 

tobacco, alcohol, diet, and residential exposures." 

A.4.3.2. Study Description 

This population-based case-control study was conducted in six coastal counties of eastern Texas to 

evaluate the association of lung cancer with occupational and other environmental exposures. Those of primary 

interest are associated with occupation in conjunction with tobacco, alcohol, diet, and residential exposures. The 

ETS subjects are part of this larger study that includes active smokers. 

Cases include males and females ascertained from hospital and State records during 1976-80, except for 

Harris County, which includes only females from 1977-80. All subjects are white (including Hispanic) county 

residents of at least 6 months. Cases are incident, without restriction to cell type, and histologically diagnosed to 

eliminate secondary lung cancers (there is some inconsistency in the article on whether all diagnoses were by 

histology or whether some were by cytology). Controls were selected from State and Federal records, group 

matched on age, sex, race or ethnicity, county of residence, and vital status. The candidate sample size is estimated 

in the report at approximately 1,650, including both sexes, of which just over 700 were lost to attrition in selection 

or followup for various reasons. Face-to-face interviews were conducted, a large number of which were with next 

of kin as necessitated by inclusion of decedent cases and controls. For example, for females, the number of subject 

interviews is only 18% for cases (81/460) and 24% (116/366) for controls. The distribution of ages is similar for 

cases and controls, based on groupings of 10-year intervals. 

"ETS exposed" means having ever lived with a household member who smoked regularly. Exposure 

sources include the home environment during childhood and adulthood but exclude the workplace. There is no 

mention of whether data on ETS exposure were cross-checked with other interview questions or other sources. No 

indication was found regarding unmarried females in the sample and how marital status may affect level of exposure 

A-26
to ETS. Some summary information is provided on the distribution of tumors by cell type, but totals include 

smokers, so they are not reproduced here. The ETS data for females consist of 33 out of 41 (exposed/total) cases 

and 164 out of 196 controls; for males, the respective figures are 5 out of 11 and 56 out of 90. For the exposure 

definition given above, the crude odds ratio reported is 0.78 (95% C.I. = 0.34, 1.81) for females (direct calculation 

from the data yields a value of 0.81; Buffler apparently added 0.5 to all cells to compensate for inclusion of no 

subjects in some cells). Little difference was found when female smokers were categorized by number of years 

lived with a household member who smoked. No adjusted statistical analysis is provided to account for variables 

used in matching for the study as a whole, nor is there a test for trend. The authors conclude that no effect of 

passive smoking is indicated for lung cancer. No attempt is made to evaluate whether exposure to ETS in childhood 

or adulthood is a factor. 

A.4.3.3. Comments 

The potential relationship between ETS exposure and lung cancer risk was not a principal issue in the 

design of this study. As described in the abstract, and more fully in the study description above, other potential 

etiologic factors were of more central concern. There are several limitations regarding the study's contribution to 

the epidemiologic evidence on ETS exposure and lung cancer risk. For example, the interview question on 

exposure to ETS is not very specific. "Having lived with a household member who smoked regularly" does not 

distinguish between exposure in childhood and in adulthood, between substantial and only light exposure, or 

between short-term and long-term exposure. One might expect a high percentage of persons to qualify as "exposed" 

under such a broad definition, and that is what the study demonstrates: 84% of the controls are classified as 

exposed. With such a high percentage, both cases and controls may include a number of subjects who have 

experienced very light exposure to ETS. Another concern in this study is the use of decedent subjects. The 

majority of both male (86%) and female (82%) cases in the study (including smokers) were deceased. 

Consequently, a very high percentage of interviews was by proxy (82% of cases and 76% of controls). 

This study was conducted in a region with a significantly higher age-adjusted mortality rate for lung cancer 

than for the United States in general. For all ages combined, the overall excess lung cancer mortality in the Texas 

study area is approximately 30% to 40% and is considerably higher for some age groups, according to the article. 

This was the apparent motivation for the study, with emphasis on important occupational and industrial exposures 

for residents of the Texas coastal area, including those associated with shipbuilding and repair, chemical and 

petrochemical manufacturing, petroleum refining, construction, and metal industries. If these nonsmoking factors 

affect the incidence of lung cancer, then they may be confounding the attempt to detect an effect from passive 

smoking. Appropriate statistical methods need to be applied to adjust the effect of each risk factor for the others. 

Other factors may affect the ETS analysis also. Harris County, which is frequently addressed in the article 

as distinct from the other five counties, was apparently added to the study later (case ascertainment began 1 year 

A-27
later there and included only females; 10 of the 11 hospitals that did not participate are in Harris County). 

Consequently, there are some regional differences in the study as well as ethnic and racial differences (white and 

Hispanic). Although the authors took care to match controls on these and other factors, the matching only applies to 

the whole study (91% and 97% of male and female cases, respectively, are classified as having smoked regularly), 

not to the ETS subject group specifically, and there is no adjustment for these factors in the analysis. The 

unadjusted analysis, the insensitive indicator of ETS exposure, and the large use of decedent cases and proxy 

responses limit the value of this study for assessing any health effects associated with passive smoking. 

A-28
A.4.4. BUTL(Coh) (Tier 2) 

This study was undertaken to explore the role of active and passive smoking in Seventh-Day Adventists in 

California. Subjects were participants in a larger prospective cohort study of factors affecting health in Adventists. 

In 1974, the Adventist Health Study was initiated with the purpose of investigating the associations of a 

number of lifestyle and nutritional factors with morbidity and mortality in California Seventh-Day Adventists. 

Registered Adventist households were identified by contacting the clerks of all 437 California Adventist churches. 

A basic demographic questionnaire sent to all households received a response rate of 58%. In 1976, all subjects 

aged 25 or older in 1974 were asked to complete a lifestyle questionnaire that included many demographic, medical, 

psychological, and dietary variables. More than two-thirds of the targeted subjects responded. From the nonHispanic whites among these respondents, Butler and his colleagues drew two cohorts. One consisted of 22,120 

spouses married and living together at the time of completion of the lifestyle questionnaire in 1976 ("spouse-pairs" 

cohort) and the other of 6,467 individuals participating in an Adventist Health Smog Study of air pollution and 

pulmonary disease (the "ASHMOG" cohort); about two-thirds of the ASHMOG cohort also was included in the 

spouse-pairs cohort. 

Subjects received annual forms for self-reporting of hospitalizations in the past year. Medical records 

relating to reported hospitalizations were then reviewed. Mortality was traced in four ways: linkage with California 

Death Certificate and National Death Index Systems, church clerk notification of deaths entered in church records, 

and followup of hospitalization history form responses (or nonresponses). Underlying and contributing causes of 

death were obtained from death certificates. Death certificates were obtained for all reported fatalities. 

For the spouse-pairs cohort, subjects were considered unexposed to ETS if their spouses were either neversmokers or ex-smokers baptized into the Adventist church--which proscribes tobacco usage--before marriage. 

Those whose spouses were ex-smokers with less than 5 years of total smoking also were considered unexposed. All 

other subjects with ex- and current smoker spouses were classified as exposed. 

Incidence rates were calculated using person-years. In the spouse-pairs cohort, age-adjusted lung cancer 

mortality rates for females married to past or current smokers were higher than those for female spouses of neversmokers, yielding relative risks of 1.94 and 2.47 for past and current smokers, respectively. Comparison of wives 

with ever- versus never-smoking husbands yielded a relative risk of 2.0. The same age-adjusted relative risk 

resulted when analyses were restricted to the 9,207 never-smoking females included in the spouse pairs. Virtually 

identical risk estimates resulted from both Mantel-Haenszel and maximum likelihood analyses. None of the relative 

risks was statistically significant at the 5% level. 

In the ASHMOG cohort, the relative risk of lung cancer adjusted for age and past smoking status among 

females was 1.16 for women who had lived with a smoker for at least 11 years compared with women who had not 

lived with a smoker; no difference was observed for women who had lived for less than 11 years with a smoker, 

although this group was only one-tenth as large as the others. A similar pattern was seen among males who had 

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lived for at least 11 years with a smoker, with an adjusted relative risk of 1.17. 

In the spouse-pairs cohort, age-adjusted rates of smoking-related cancers (excluding lung cancer) were 

only slightly higher among nonsmoking females married to smokers than among nonsmokers (relative risk [RR] = 

1.06); the relative risk rose to 1.22 when lung cancers were included. 

In the ASHMOG cohort, age-adjusted rates using conditional maximum likelihood analysis for all 

smoking-related cancers were higher among males who lived with a smoker (RR = 1.45 for 1-10 years; 1.74 for 11+ 

years) or worked with a smoker (RR = 2.62 for 1-10 years; 1.47 for 11+ years). Among females, in contrast, only 

one (at RR = 1.03) of the four exposed categories had a higher rate than the nonexposed groups. 

All lifestyle questionnaires were administered anonymously, thus reducing the potential for inaccurate 

responses caused by fear of discovery; respondents to the special supplemental ASHMOG questionnaire were 

assured of confidentiality but not anonymity. 

Although causes of death were obtained from death certificates, review of medical records revealed 

histological confirmation in 99% of the primary malignancies reported among the spouse-pairs cohort. Thus, 

substantial misclassification of lung cancer deaths is unlikely. Subsequent study of patients discharged from 1 of 

the 11 participating Adventist medical centers over a 6-month period indicated that under 2% of study participants 

failed to report their hospitalizations; serious underascertainment of cases thus also seems unlikely. Losses to 

followup by study's end totaled only 1.2% of the original study cohort--a very low rate. 

Comparing the results of the 1976 questionnaire with those of a supplemental questionnaire given to 

ASHMOG subjects in 1987, 4.7% of male smokers now reported themselves as "never-smokers" and 1.4% of 

never-smokers now reported themselves as nonsmokers. Concordance of female responses was even higher. This 

concordance of responses does not necessarily imply the degree of accuracy of responses, only their reliability. 

Comparison of responses to the 1987 questionnaire by females revealed that about 6% of those previously 

classified as not having a smoking spouse now reported having had one; the converse was also true for 6% of the 

women. These data indicate a mild nondifferential misclassification of exposure, which would push results toward 

the null. 

Information is available on a large number of variables of possible interest as potential confounders or risk 

mediators. Unfortunately, the modest number of total lung cancer deaths among females in the spouse-pairs cohort 

(8) or among both sexes in the ASHMOG cohort (13) discourages attempts to control for other potential 

confounders in addition to age in the analyses. Separate consideration of the association between variables other 

than passive smoking and age-adjusted lung cancer mortality among women indicated a high relative risk (RR > 4) 

for spousal blue collar occupation. No other variables produced nearly as strong or consistent an association; in 

fact, the only other consistent association was a relative risk of 1.3 to 1.6 for nonrural status. Unfortunately, no 

breakdown of blue collar spousal status by exposure groups was presented. 

By virtue of its basic design, the inherent minimization of sources of confounding provided by its study 

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population and the level of information available regarding potential confounders, and other sources of bias, the 

Butler study has many of the key ingredients to produce convincing results. Unfortunately, this potential goes 

largely unrealized because of the low number of outcome events occurring during the followup period, which for 

the most part renders stratification or control for multiple factors simultaneously impractical; even stratification by 

several age or exposure levels produces unstable results. 

Nevertheless, the findings of this study are quite consistent with the hypothesis that ETS exposure of 

nonsmokers is associated with mildly elevated lung cancer, (active) smoking-related cancer, and ischemic heart 

disease mortality. Insofar as the study data allow for consideration of potential misclassification and confounding 

effects, neither misclassification nor confounding can account for the observed association. Because of the limited 

number of outcome events, several possible confounding factors could not be definitively or adequately addressed 

in the analyses, and the observed associations were not statistically significant; therefore, the study's findings must 

be viewed as suggestive but not of themselves convincing. 

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A.4.5. CHAN (Tier 4)

A.4.5.1. Author's Abstract

(Note: This study is described in two sources, both of which were used for the description below. Chan et al. 

[1979] is the more complete description, but it contains considerable attention to active smoking as a cause of lung 

cancer. Chan and Fung [1982] is a condensed version that specifically addresses nonsmokers. The abstract given 

here is for the 1979 article. No abstract is provided in the 1982 source.) 

"Bronchial cancer is a disease of high and increasing annual incidence in Hong Kong, especially in 

women, whose age-specific death rates from this cause are among the highest in the world. A case-control study of 

the relationship of bronchial cancer with smoking was carried out during 1976-77, taking particular note of the 

histological type of the tumor. Two hundred and eight male and 189 female patients were interviewed, covering 

about one-half the total number of cases of bronchial cancer registered as dead from the disease in Hong Kong 

during the period of the survey. The association with smoking was more evident in males than in females, and in 

squamous and small cell types, as a group, than in adenocarcinoma. Forty-four percent of the women with 

bronchial cancer were nonsmokers, their predominant tumor being adenocarcinoma, and in them no association 

could be detected with place of residence or occupation. There was no strong evidence of an association with the 

use of kerosene or gas for cooking; 23 did not use kerosene. The cause of the cancer in these nonsmoking women 

remains unknown." 

A.4.5.2. Study Description

(Note: This description is primarily based on Chan et al. [1979]. Chan and Fung [1982] are cited when used as a 

reference.) 

This study is the earliest of four from Hong Kong that consider ETS exposure as a potential etiologic factor 

for lung cancer incidence in nonsmoking women. Here, however, that objective is secondary to evaluation of the 

relationship of bronchial cancer with active smoking. 

In the whole study, target cases are the lung cancer patients, male and female, in five hospitals in Hong 

Kong during 1976-77 who were willing and able to be interviewed. Controls are patients of the same general age 

groups from the orthopedic wards of the same hospitals as the cases. No specific diseases are excluded. Cases are 

incident and control sampling is density. The candidate sample size is 208 (189) male (female) cases and 204 (189) 

male (female) controls. Attrition from selection or followup is not reported but appears to be high. Subjects were 

personally interviewed, when possible. About half of the estimated number of lung cancer cases diagnosed in Hong 

Kong during the study period were actually interviewed. Some patients were too ill to answer questions, and more 

than expected were treated elsewhere than in the hospitals covered. No interviews with next of kin were obtained 

for the cases interviewed. 

The ETS subjects (never-smokers) alone include 84 (2) female (male) cases and 139 (30) female (male) 

A-32
controls. The age distribution of the female cases (controls) is, by percentage, as follows: age less than 40, 7 (5%); 

ages 40 to 49, 15 (15%); ages 50 to 59, 23 (30%); ages 60 to 69, 23 (22%); and age 70 or more, 32 (28%). Cases 

with a histological diagnosis were reviewed and verified by reexamination of the pathological specimens. In the 

absence of a histological specimen, cytological diagnosis was accepted. In some cases, on histological grounds, 

secondary adenocarcinoma was suspected, and a few cases were rejected after detailed examination of the clinical 

records. Of the cases, 46 (55%) were diagnosed by histology, 23 (27%) by cytology, and 15 (18%) by radiology 

and clinical means. Diagnoses by cell type were as follows: squamous or small cell, 19 (22%); adenocarcinoma or 

large cell, 40 (48%); others and unspecified, 25 (30%). Of the unspecified, 15 had no histological or cytological 

verification. 

ETS subjects are never-smokers. Classification of a subject as exposed or unexposed to ETS is based on 

the response to these questions: (1) If you do not smoke, have you been exposed to cigarette smoke from other 

people at home or at work? (2) Does your husband/wife smoke? (If "yes," how many cigarettes per day?) (The first 

question is included in Chan et al. [1979]. The second one is from a personal communication of Linda C. Koo.) No 

information is reported on the distribution of tumors by central and peripheral location. 

The ETS data on females based on question 1, above, consists of 50 out of 84 (unexposed/total) cases and 

73 out of 139 controls. The authors state that "this is a rather subjective approach to the problem." No statistical 

estimates are provided; our calculation of the crude odds ratio is 0.75 (95% C.I. = 0.43, 1.30). No clear conclusion 

is drawn regarding the potential relationship between ETS exposure and lung cancer occurrence, but the authors 

imply that no connection was found (which the odds ratio and confidence interval amply support). The authors 

found no particular occupation as being dangerous. Their findings also do not support air pollution as a factor, and 

they provide no strong evidence that cooking with various types of fuel is relevant. 

A.4.5.3. Comments 

Although data on spousal smoking were collected along with an indication of the number of cigarettes 

smoked per day, they are referred to only in the 1982 article, where the authors note without further elaboration that 

more nonsmoking cases have nonsmoking spouses. It is reported that answers to the question, "Are you exposed to 

the tobacco smoke of others at home or at work?" gave no indication that other people's smoking was a risk factor 

for lung cancer in nonsmokers, with 40.5% of cases and 47.5% of controls answering yes to this question. Why the 

data for spousal smoking are not given and analyzed is unknown. The question about general ETS exposure 

combines sources in the household and workplace and refers only to current exposure without a measure of 

duration, which would likely affect any risk associated with passive smoking. 

Although it is reported that cases and controls are similar in age, occupation, and other characteristics, 

comparability is questionable. The article cites a criticism of the whole study (including smokers) for use of 

orthopedic patients as controls, on the basis that some patients may be hospitalized with smoking-related diseases 

A-33
(e.g., osteoporosis). It was found that the controls smoke more than a group representative of the population of 

Hong Kong. This would create a bias toward negative association. Although these comments refer to smoking 

habits, they suggest the potential for selection bias of controls that may extend to nonsmoking controls as well. 

It is noted, also, that there are more cases from Hong Kong Island than would be expected from the 

population distribution of Hong Kong as a whole, possibly due to more success contacting cases in Hong Kong 

Island than in Kowloon. The authors caution about reaching any conclusion about the distribution of cases within 

Hong Kong as a whole. The failure to follow up on patients who were eventually treated at other hospitals or were 

too ill to be interviewed is itself, of course, a potential source of bias. 

Other differences are apparent between cases and controls. Among nonsmokers, a higher percentage of 

cases than controls (1) are Cantonese (81 vs. 70) or (2) have ever cooked with kerosene (73 vs. 60). It is speculated 

that the Cantonese diet, high in nitrite or nitrate content, may be a factor in lung cancer incidence (Chan and Fung, 

1982). More broadly, these comparisons between cases and controls indicate differences in ethnic composition, 

lifestyle, and socioeconomic status that are difficult to assess. 

In summary, ETS subjects are not matched in the design, and an adjusted statistical analysis is not 

conducted. Consequently, potential sources of bias are not controlled. There is substantial basis to question the 

comparability of cases and controls, as described above. Data quality is suspect because confirmation of primary 

lung cancer was limited and cases were missed because patients were too ill to be interviewed personally or were 

eventually treated at another hospital. Also, the question posed to subjects for classification as exposed or 

unexposed to ETS is sufficiently general to invite a subjective response. Overall, methodological shortcomings 

hamper the interpretation of this study's results. 

The finding that spousal smoking appears to be more frequent in controls, mentioned in the 1982 report, is 

noted to be at variance with the Hirayama study, which may have motivated the authors to conduct this secondary 

analysis of ETS exposure using their previously collected data. Whatever the motivation, the limitations of the 

original study, which was not designed to assess passive smoking, limit this study's value for assessing ETS 

exposure and lung cancer. 

A-34
A.4.6. CORR (Tier 2) 

A.4.6.1. Author's Abstract 

"Questions about the smoking habits of parents and spouses were asked in a case-control study involving 

1,338 lung cancer patients and 1,393 comparison subjects in Louisiana, United States. Nonsmokers married to 

heavy smokers had an increased risk of lung cancer, and so did subjects whose mothers smoked. There was no 

association between lung cancer risk and paternal smoking. The association with maternal smoking was found only 

in smokers and persisted after controlling for variables indicative of active smoking. It is not clear whether the 

results reflect a biological effect associated with maternal smoking or the inability to control adequately for 

confounding factors related to active smoking. This preliminary finding deserves further investigation." 

A.4.6.2. Study Description 

This study was conducted in Louisiana to investigate the relationship of smoking habits of parents and 

spouses to lung cancer occurrence. Results of the study were published in 1983; some clarifying details regarding 

study methodology were supplied in a 1984 paper addressing only the effects of active smoking. The accrual period 

is not stated; cases are probably a mixture of prevalence and incidence, and controls are cumulatively sampled. ETS 

subjects constitute a small portion of the whole study, which includes active smokers. 

Cases consist of patients diagnosed with primary lung cancer, exclusive of bronchioalveolar carcinoma, 

from participating hospitals in several Louisiana parishes (counties), predominantly in the southern part of the state. 

A total of 302 female and 1,036 male cases and an equal number of controls are included in the whole study. 

Controls were selected from other patients, excluding those diagnosed with emphysema, chronic bronchitis or 

obstructive pulmonary diseases, or certain cancers (laryngeal, esophageal, oral cavity, and bladder). They were 

matched to cases on hospital, age (" 5 years), sex, and race. Information about active and passive smoking was 

obtained by interview (presumably face-to-face and unblinded), with responses obtained from next of kin in 24% of 

cases and 11% of controls; no information on refusals is provided. ETS subjects were identified by exclusion of 

individuals who had ever smoked or had never been married, which eliminated 279 female and 1,026 male cases. 

Removal of subjects with no spousal smoking data eliminated one additional female and two male cases, leaving 22 

female and 8 male cases. Similarly, a total of 1,080 men and women were excluded from controls. No 

demographic comparisons are given, either for the whole study or for the ETS subjects alone, nor is the number of 

proxy responses provided for the ETS subjects. Histological confirmation was obtained for 97% of cases in the 

whole study, including ever-smokers. 

"ETS exposed" is used in two ways, depending on the analysis given: (1) the spouse has smoked at least 1 

pack-year of cigarettes or (2) the spouse currently smokes. Units of exposure are pack-years and current 

consumption is in cigarettes per day for (1) and (2), respectively. ETS exposure in childhood means that at least 

one parent smoked during most of the subject's childhood. Types of tobacco smoking other than cigarettes (e.g., 

A-35
cigars and pipes) are referenced indirectly in regard to interview questions but are not included in the data analysis. 

Other sources of exposure, either at home or in the workplace, are not considered. Never-married women are 

excluded from ETS analysis, but no information is given on the number of nonsmoking widows and divorcees and 

how they were handled with regard to ETS exposure. Adenocarcinoma accounts for 54% of lung cancers in 

nonsmoking women, compared with 22% in women who actively smoke. No further histological breakdowns are 

provided. 

For the main analysis of spousal smoking, exposure constitutes 1 or more pack-years of spousal cigarette 

consumption. ETS-exposed subjects include 14 (61) of 22 (133) female cases (controls) and 2 (26) of 8 (180) male 

cases (controls). These data yield a crude odds ratio of 2.07 (95% C.I. = 0.81, 5.25) for females (confidence 

interval was calculated by reviewers). Among females, stratification by 0, 1 to 40, and 41 or more pack-years of 

exposure yields odds ratios of 1.0, 1.18, and 3.52, respectively, with the highest exposure category being 

statistically significant at p < 0.05. No adjusted results are presented. It is, however, reported that analyses based 

on current daily spousal cigarette consumption produced very similar results to the pack-year analyses. In addition, 

it is reported that neither exclusion of proxy interview data nor restriction to same-race subjects significantly alters 

the results. Analysis of parental smoking during childhood embraces the combined population of smokers and 

nonsmokers, adjusting for smoking status by logistic regression. Maternal smoking is associated with significantly 

increased estimated risk of lung cancer (OR = 1.38, p < 0.05) but paternal smoking is not (OR = 0.83). No 

association was noted among nonsmokers alone, but the authors note that small numbers preclude adequate analysis 

of this group. 

A.4.6.3. Comments 

The study entails a major multicentric effort to assemble hospital-, age-, race-, and sex-matched lung 

cancer cases and controls from Louisiana hospitals. Its use of trained local interviewers familiar with the region's 

culture increases the probability of obtaining accurate interview data for the nearly 3,000 subjects involved. 

Exclusion of active smokers to assess ETS exposure, however, exacts a toll on the study's power and validity. 

Because the initial matching of cases and controls did not include smoking status, the ETS subjects are unmatched 

in the analyses of spousal and parental smoking. This potential problem is not addressed by the authors. The lack 

of any demographic information on cases and controls leaves the comparability of these groups uncertain. 

The potential problem of misdiagnosis of primary lung cancer is minimized by the high rate (97%) of 

histological case confirmations. Eligibility criteria for controls were intended to exclude smoking-related diseases. 

Some 15% of the controls had cardiovascular disease, however, which has been associated with both active and 

passive smoking. The authors also speculate that the inclusion of adenocarcinoma, reportedly less smokingassociated than other lung cancers, may have diluted the significance of their results, but they do not present 

analyses using their extensive histological data to assess this question. 

A-36
Restriction of the spousal smoking analysis to ever-married individuals eliminates potential bias due to 

differences between lifelong single and married individuals. Stratification by gender controls for any sex-related 

differences. Both race and proxy interviews were reported to have no effect on the spousal smoking results, and the 

spousal smoking association was still observed after division of women into more than and less than 60 years of 

age. A small number of nonsmoking ever-married cases (8 males and 22 females for this study) hampers efforts to 

control statistically for other factors; nonetheless, direct adjustment for age and race is needed. 

It is concluded that females married to heavy smokers have an increased risk of lung cancer. A significant 

increase in risk for nonsmokers was found from maternal but not from paternal smoking in childhood. The results 

for childhood exposure, however, use statistical methods to adjust for the presence of active smokers. It would be 

preferable, in our view, to remove the data for active smokers prior to analysis. The potential for bias in all of the 

analyses, which could be in either direction and may or may not be of consequence, needs to be kept in mind when 

using this study's results. 

A-37
A.4.7. FONT (Tier 1) 

A.4.7.1. Author's Abstract 

"The association between exposure to ETS and lung cancer in female lifetime never-smokers was 

evaluated using data collected during the first 3 years of an ongoing case-control study. This large, multicenter, 

population-based study was designed to minimize some of the methodological problems that have been of concern 

in previous studies of ETS and lung cancer. Both a cancer control group and a population control group were 

selected in order to evaluate recall bias. A uniform histopathologic review of diagnostic material was conducted for 

case confirmation and detailed classification. Biochemical determination of current exposure to tobacco and 

screening of multiple sources of information to determine lifetime nonuse were employed to minimize 

misclassification of smokers as nonsmokers. 

A 30% increased risk of lung cancer was associated with exposure to ETS from spouse, and a 50% 

increase was observed for adenocarcinoma of the lung. A statistically significant positive trend in risk was 

observed as pack-years of exposure from spouse increased, reaching a relative risk of 1.7 for pulmonary 

adenocarcinoma with exposures of 80 or more pack-years. The predominant cell type of the reviewed, eligible lung 

cancer cases was adenocarcinoma (78%). Results were very similar when cases were compared with each control 

group and when separate analyses were conducted for surrogate and personal respondents. Other adult-life 

exposures in household, occupational, and social settings each were associated with a 40% to 60% increased risk of 

adenocarcinoma of the lung. No association was found between risk of any type of lung cancer and childhood 

exposures from father, mother, or other household members." 

A.4.7.2. Study Description 

This study was initiated in 1985 in five major U.S. metropolitan areas to investigate the association 

between exposure to ETS and lung cancer in female lifetime never-smokers. The study was designed specifically to 

address this issue and includes only never-smokers. The results reviewed are from an interim report, with the 

completed study expected to encompass an additional 2 years of case accrual. 

Patients were English-, Spanish-, or Chinese-speaking female residents 20 to 79 years of age who have 

never used tobacco, have no prior history of malignancy, and have histopathologically confirmed primary lung 

cancer. The lung cancers were originally diagnosed at participating hospitals in Atlanta, Houston, Los Angeles, 

New Orleans, and the San Francisco Bay area, between December 1, 1985, and December 31, 1988. Two control 

groups were assembled, one from colon cancer patients and the other from the general population, with the same 

general eligibility requirements as cases. The population control group, consisting of women selected from the 

general population by random digit dialing and by sampling from Health Care Financing Administration files, was 

frequency-matched on age (< 50, 50-59, 60-69, 70+), with two controls per case. The colon cancer controls were 

frequency-matched to cases by 10-year age groups and by race. The lung cancer group consists of incident cases, 

A-38
but there is no indication whether density or cumulative sampling was employed for either control group. Exposure 

data were collected in face-to-face, apparently unblinded, interviews. 

Extensive efforts were made to include only never-smokers. For cases and colon cancer controls, medical 

records were reviewed for tobacco use and physicians were contacted as necessary. Eligible cases not previously 

excluded and all population controls were contacted by telephone to screen for prior use of tobacco (no more than 

100 cigarettes smoked or use of any tobacco in any form for more than 6 months). Urinary cotinine was bioassayed 

to eliminate any misreported current smokers. 

A total of 514 eligible cases were identified, of which 83 were not interviewed for unspecified reasons and 

2 had urinary cotinine levels consistent with active smoking. Independent histopathologic review by a pulmonary 

pathologist was performed for 84% (359/429) of the lung cancer cases, resulting in nine exclusions. Only the 

remaining 420 cases are included in the study. Colon cancers were not reviewed. Of 489 (1,105) eligible colon 

cancer (population) controls, 131 (311) were not interviewed and 7 (14) were excluded for high urinary cotinine. 

Proxies were interviewed for 143 (34%) of the lung cancer cases and 35 (10%) of the colon cancer controls, 

whereas no proxies were used for the population controls. 

Cases and the two control groups all have similar age distributions, with the majority of subjects between 

60 and 79 (73%, 74%, and 74% of the cases, colon, and population groups, respectively). The proportion of whites 

is similar across all groups (63-69%), but the control groups contain a somewhat higher proportion of blacks and 

lower proportion of other minorities, and a little higher percentage of high school graduates (76% and 79% vs. 

68%). Cases and controls are comparable by metropolitan size of adulthood and childhood residences and also by 

annual income. 

Four sources of adult ETS exposure are assessed: smoking by (1) spouse(s) and (2) other household 

members while living with the subject, and reported exposure to ETS in (3) occupational and (4) social settings. 

Three sources of possible exposure in childhood (up to 18 years of age) are considered: smoking by (1) father, (2) 

mother, or (3) other household member(s) while living in the subject's home for at least 6 months. Subjects are 

characterized as ever- versus never-exposed with a subanalysis by tobacco type (cigarette, pipe, or cigar). Years of 

exposure are also tabulated. In addition, cigarettes per day for spouse and for other household sources and packyears for spouse(s) are calculated. No checks on exposure (aside from the cotinine screening) are reported. 

Adenocarcinoma is the dominant type of lung cancer among study subjects, representing 76% (311/409) of 

all cases included in the study (with the exception of 11 cases with "review pending") and also 78% (281/359) of all 

independently confirmed primary bronchogenic carcinomas among those cases. Other cell types include 12% 

(48/409) large cell, 7% (27/409) squamous cell, 3% (14/409) small cell, and 2% (9/409) other cancers. No data on 

airway proximity are provided. 

The final study population (for this interim report) consists of 420 lung cancer cases, 351 colon cancer 

controls, and 780 population controls. Exposure to spousal smoking from all types of tobacco is reported for 294 

A-39
cases, 231 colon cancer controls, and 492 population controls, yielding similar odds ratios (adjusted for age, race, 

area, income, and education) of 1.28 (95% C.I. = 0.93, 1.75) and 1.29 (0.99, 1.69) using the respective control 

groups. Elevated but statistically nonsignificant observed risks are also observed when cigarette, cigar, and pipe 

exposure are assessed separately, with either control group. Restriction of analyses to the 281 independently 

reviewed adenocarcinomas results in stronger associations, with adjusted odds ratios of 1.44 (95% C.I. = 1.01, 2.05) 

and 1.47 (1.08, 2.01) for all types of tobacco, and increased odds ratios for each type of tobacco as well. 

Odds ratios were also calculated for ETS exposure from cigarette smoking alone, with the two control 

groups combined (the individual results using each control group are entirely consistent). For all lung cancer types 

combined, the adjusted odds ratios are 1.21 (0.96, 1.54) for spousal smoking, 1.23 (0.97, 1.56) for other household 

members, 1.34 (1.03, 1.73) for occupational environments, and 1.58 (1.22, 2.04) for social exposure, the last two of 

which are significant (p < 0.05 and 0.01, respectively). The corresponding odds ratios for adenocarcinoma cases 

alone continue to be uniformly higher: 1.38 (95% C.I. = 1.04, 1.82), 1.39 (1.05, 1.82), 1.44 (1.06, 1.97), and 1.60 

(1.19, 2.14). The odds ratio tends to increase over years of exposure for all carcinomas combined and for 

adenocarcinoma alone, although not monotonically (without downturns). The tests for upward trend are all 

significant or suggestive, with p-values ranging from < 0.001 to 0.07 (these p-values are one-half those reported, 

which apply to a trend in either direction). Finally, for spousal smoking measured in pack-years, the upward trend 

is significant for adenocarcinoma alone and for all lung cancers together (p < 0.005 and 0.04, respectively). 

The authors interpret their findings as evidence of a causal relationship between ETS exposure in 

adulthood and lung cancer in never-smoking women. In contrast to adulthood, ETS exposure during childhood 

shows no association with lung cancer, for either all cell types combined or adenocarcinoma alone. Adjusted odds 

ratios for childhood exposure tend to be slightly (but not significantly) below unity for all exposure sources. 

A.4.7.3. Comments 

This study is much larger than any other ETS case-control study. More than 400 never-smoking female 

lung cancer cases were enrolled in just over 3 years, in contrast to the 25 to 75 cases typical of most studies, and two 

control groups were formed, totaling more than 1,200 subjects. Additionally, the cases and controls are drawn from 

five widely dispersed metropolitan centers in the United States, representing a population of approximately 18.5 

million people, about 8% of the U.S. population. This characteristic increases the generalizability of the study and 

diminishes the potential for bias related to locale. 

Extensive efforts were made to achieve precision and validity, in evidence throughout the study. Cases and 

controls are highly comparable. They are frequency-matched on age and, for colon cancer controls, on race as well. 

The distributions of other demographic variables--annual income, childhood residence, and adult residence--are 

quite similar between cases and both control groups. The control groups contain a little higher (lower) proportion 

of blacks (Asians and Hispanics) and a higher percentage of high school graduates. These differences, however, 

A-40
should not have influenced the reported associations because all odds ratios are adjusted for race and education. 

The use of incident cases reduces the potential for selection bias, and the implementation of two control 

groups allowed for assessment of potential bias from comparison with cancer patients or the general population 

alone. The similarity of results obtained from the two control groups suggests little bias from choice of controls. 

The use of a multistep procedure to eliminate inclusion of former or current smokers reduces the potential 

for smoker misclassification as a source of upward bias. As a further safeguard, urinary cotinine was bioassayed for 

all consenting persons to exclude those likely to be current smokers. This is the only published study we are aware 

of to implement this precaution. Attention to histopathology is also very thorough. Inclusion of only histologically 

diagnosed primary carcinoma reduces the likelihood of diagnostic error, which is further reduced by the use of 

independent histopathologic review of most cases by a single pulmonary pathologist. The study's histopathologic 

findings bring out two interesting points. First, comparison of cell type diagnoses between hospital and independent 

reviewers revealed poor concordance for large (56%) and squamous (67%) cell carcinomas, indicating that celltype-specific analyses for these cancers may be misleading, particularly if all diagnoses are not made by the same 

pathologist. The histopathologic review also resulted in a net increase of adenocarcinomas from 244 to 281, 78% of 

the total, a higher proportion than in most but not all other studies. The statistical results were stronger when 

limited to cases of adenocarcinoma alone. 

Exposure information was obtained in the most reliable way, by face-to-face interviews with each 

interviewer trained and fluent in the subject's primary language. Information for a substantial proportion of lung 

cancer cases (34%) was obtained from proxy respondents, but fewer proxies were required for colon cancer controls 

(10%), and none were used for population controls. The use of proxy respondents raises the possibility of 

information bias, but their exclusion reportedly did not alter the study's findings. The apparent lack of blinding also 

raises the possibility of interviewer bias, but it is unlikely that such bias (or recall bias, for that matter) would focus 

its effect on adenocarcinoma. Also, the same relationships hold whether the colon cancer or population controls are 

used. 

Particular attention is paid to all sources of ETS exposure, which is more informative than addressing only 

spousal smoking, with four sources in adulthood and three in childhood evaluated both individually and in 

combination. Additionally, subjects are counted as exposed to the ETS of a spouse or other household smoker only 

while living with the source, giving a more accurate account of exposure than simply determining whether a spouse 

or household member ever smoked. Consequently, the measures of ETS exposure are more specific by source, and 

probably more accurate, than in most studies. This reduces bias toward unity in the odds ratio arising from poor 

distinction between exposed and unexposed subjects. Still, further accuracy might have been achieved by 

stipulating that smoking must occur in the subject's household or presence, but this is a minor point. 

Most of the standard risk modifiers, such as age, race, geographic area, income, and education, are adjusted 

for in all analyses and thus can be ruled out as sources of the observed results. Although information on diet, 

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occupational exposures, and "other exposures of interest" were collected, these factors are not addressed in this 

interim report. Thorough treatment of the possible impact of these factors presumably will be undertaken after 

subject accrual is finished and published in the completed study. 

To summarize, this study was designed specifically and solely to address the topic of ETS as a potential 

lung cancer risk to nonsmoking women. Several issues were given special attention, such as the potential 

misclassification of smoking status, histopathologic specificity, recall bias, and source of ETS exposure. 

Histopathologic specificity has not been convincingly demonstrated in prior studies, and the meaning of "exposed to 

ETS" has differed widely between studies, even those addressing spousal smoking only. The remaining issues are 

largely related to controlling potential sources of bias and confounding to enhance validity. The qualitative rigor 

and completeness of detail in this study is impressive. In addition, it is quite large, which increases precision of 

estimates and power to detect an association, if it exists. Use of dietary, occupational, and other exposure data in 

the analyses, along with an additional 2 years of subject accrual, will make the completed study for which this 

constitutes an interim report even more valuable. As it stands, however, this study is already the largest and most 

useful case-control study available. Its high quality and the reasonable consistency of the evidence across sources 

of ETS exposure strongly support an increase in lung cancer incidence associated with passive smoking. 

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A.4.8. GAO (Tier 3) 

A.4.8.1. Author's Abstract 

"A case-control study involving interviews with 672 female lung cancer patients and 735 population-based 

controls was conducted to investigate the high rates of lung cancer, notably adenocarcinoma, among women in 

Shanghai. Cigarette smoking was a strong risk factor, but accounted for only about one-fourth of all newly 

diagnosed cases of lung cancer. Most patients, particularly with adenocarcinoma, were lifelong nonsmokers. The 

risks of lung cancer were higher among women reporting tuberculosis and other preexisting lung diseases. 

Hormonal factors were suggested by an increased risk associated with late menopause and by a gradient in the risk 

of adenocarcinoma with decreasing menstrual cycle length, with a threefold excess among women who had shorter 

cycles. Perhaps most intriguing were associations found between lung cancer and measures of exposure to cooking 

oil vapors. Risks increased with the number of meals cooked by either stir frying, deep frying, or boiling; with the 

frequency of smokiness during cooking; and with the frequency of eye irritation during cooking. Use of rapeseed 

oil, whose volatiles following high-temperature cooking may be mutagenic, was also reported more often by the 

cancer patients. The findings thus confirm that factors other than smoking are responsible for the high risk of lung 

cancer among Chinese women and provide clues for further research, including the assessment of cooking 

practices." 

A.4.8.2. Study Description 

This study was undertaken in Shanghai, China, during 1984-86 to explore reasons for the high rates of lung 

cancer among women in Shanghai. Potential etiologic factors associated with the high occurrence of 

adenocarcinoma among females in a population where few women smoke cigarettes is of particular interest. 

Several potential risk factors, in addition to exposure to ETS, are investigated. These are included in the abstract 

above. Smokers are included in the study as well as nonsmokers. 

A special reporting system for lung cancer linked with the area's medical facilities was set up for the study 

period, integrated with the Shanghai Cancer Registry. Incident cases of lung cancer occurring among 35- to 69-

year-old female residents of urban Shanghai from February 1984 to February 1986 were interviewed by trained 

study personnel. Controls were women selected from residents of the urban Shanghai community by stratified 

random sampling designed to mimic the age distribution of Registry-reported lung cancer cases during 1980-81. It 

is not clear whether cumulative or density sampling was employed. 

Face-to-face interviews were conducted with 672 cases and 735 controls. No cases refused to be 

interviewed, but 93 died before interview and were therefore excluded; it is not mentioned whether there were any 

refusals among potential controls. Nonsmokers composed 436 of the cases and 605 of the controls. In the total 

subject population, distribution of age, education, and marital status between cases and controls is described as 

similar, except for a larger proportion of controls (32% vs. 20%) in the oldest age group (65-69 years). The age 

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distribution in the ETS population alone is not described. 

ETS exposure is based on living with a smoker. For general exposure in childhood or adulthood, exposed 

subjects are those who ever lived with a smoker. For spousal smoking alone, however, women are ETS exposed 

only if they lived with a smoking husband for at least 20 years. General ETS exposure sources include all 

household members but not coworkers. Verification of exposure data was not mentioned. Based on the reported 

exposure criteria, widows and divorcees would have been included in the spousal smoking data set, whereas nevermarried women would have been excluded. 

For ETS subjects, 246 (375) cases (controls) from the total of 672 (735) cases (controls) are included in 

Table II of the article that lists the number of cases and controls by number of years lived with a smoking husband. 

Presumably, the 190 cases and 230 controls not included in the table are unmarried (or never-married) and do not 

include women married and living with a nonsmoker; no explanation is provided in the article. 

Among nonsmoking women included in Table II, 189 out of 246 cases and 276 out of 375 controls had 

lived with a smoking husband for at least 20 years. These subjects were divided into exposure categories of 20 to 

29, 30 to 39, and 40 or more years for comparison with the "unexposed" (< 20 years spousal smoking) subjects. 

The authors present no unadjusted analyses, but calculations from their raw data yield an overall odds ratio of 1.2 

and stratum-specific odds ratios of 1.2, 1.3, and 1.1 for 20 to 29, 30 to 39, and 40 or more years of exposure, 

respectively. Age- and education-adjusted odds ratios increase with the number of years exposed: 1.1 (95% C.I. = 

0.7, 1.8) for 20 to 29 years, 1.3 (0.8, 2.1) for 30 to 39 years, and 1.7 (1.0, 2.9) for 40 or more years. The authors 

report an odds ratio of 2.9 (1.0, 8.9) for squamous and oat cell cancer for 40 years of exposure or less but present no 

other type-specific results. 

Information on cell type is available for the 542 (81%) study cases diagnosed by histology or cytology; the 

rest of the cases were diagnosed by radiological or other means. Diagnostic evidence was reviewed by a team of 

pathologists and clinicians. For the lung cancer cases histologically typed, adenocarcinoma (61%) greatly 

predominates, followed by squamous (22%), small cell (6%), and other (11%) types. No breakdowns of tumor type 

are provided for the ETS group. 

The authors conclude that ETS may account for some, but probably few, of the cancers among 

nonsmokers, because there was little or no association with ever having lived with a smoker. Among nonsmoking 

women married to smokers, however, there was an upward trend in risk associated with increasing years of 

exposure. This latter finding is consistent with reports in other parts of the world. Little evidence was found to 

implicate the type of fuels used for cooking in lung cancer risk; occupational factors did not appear to be important, 

nor did familial tendency to lung cancer. Our data suggest, however, that prior lung diseases, hormonal factors, and 

cooking practices may be involved. Most provocative is the association with cooking oil volatiles, and further 

investigations are needed to evaluate their contribution to the high lung cancer rates among Chinese women in 

various parts of the world. 

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A.4.8.3. Comments 

The number of ETS subjects for analysis is relatively large. Unfortunately, the study is unmatched, with 

no demographic breakdown of the cases and controls, either for the whole study or for the ETS subjects alone. 

Controls were selected to make their age distribution similar to that expected for cases in the whole study, but the 

similarity may not apply to ETS subjects alone. Consequently, there is little basis for evaluating the comparability 

of cases and controls. Age and education were adjusted for in the analyses, which has some compensatory value. 

The use of direct interview with all subjects without reliance on proxies to gather exposure information 

should enhance the validity of the exposure comparisons. On the other hand, the possible use of unblinded 

interviewers could have biased results. In light of the lack of association noted for passive smoke exposure as a 

child or adult, however, it is unlikely that such a bias produced the observed association between spousal smoking 

and lung cancer. For evaluation of spousal smoking, the reference group can hardly be classified as "unexposed" to 

spousal smoking because it includes women who lived with a smoking husband for up to 20 years. The 

investigators probably selected the cutoff level of exposure for their spousal smoking reference group to balance the 

numbers in each exposure category, as a practical matter. The reference group contains an undisclosed number of 

women who may have been exposed to spousal smoking for many years, potentially creating a substantial bias 

toward the null hypothesis (no association between ETS exposure and lung cancer). Consequently, the odds ratios 

may be biased downwards. The relative comparison across years of spousal smoking, however, is not affected. An 

increasing trend in the odds ratio was observed, but no statistical test for trend is cited. In a similar vein, it appears 

that active smokers may have been included in the data analysis of overall ETS exposure. That factor, in 

combination with the use of ever- versus never-exposed classifications without regard to degree or duration of ETS 

exposure in the analyses, may have reduced the likelihood of detecting any positive association that may exist. 

The study appears to have focused on potential risk factors other than ETS. Unfortunately, the effects of 

these other factors on the ETS results were not explored, even though many of these appeared to be stronger risk 

factors than passive smoking. Some factors, such as age and education, were adjusted for in all analyses. Control 

for education should in turn produce a degree of adjustment for factors related to socioeconomic status (e.g., 

dwelling size and quality of diet). 

Overall, the study presents evidence of a mild duration-dependent association between lung cancer and 

spousal smoking that skirts statistical significance. Several sources of misclassification bias are possible, but most 

would tend to bias the odds ratio downward. The study was not, however, specifically designed to evaluate the 

ETS-lung cancer hypothesis. Information was collected and analyzed on a number of other potential risk factors, 

but they were not adjusted for in the analysis. Coupled with other limitations, this omission reduces the weight of 

the study's results with regard to ETS, although they support an increase in lung cancer risk with spousal smoking. 

A-45
A.4.9. GARF (Case-Control) (Tier 2) 

A.4.9.1. Author's Abstract 

"In a case-control study in four hospitals from 1971 to 1981, 134 cases of lung cancer and 402 

cases of colon-rectum cancer (the controls) were identified in nonsmoking women. All cases and controls 

were confirmed by histologic review of slides, and nonsmoking status and exposures were verified by 

interview. Odds ratios increased with increasing number of cigarettes smoked by the husband, 

particularly for cigarettes smoked at home. The odds ratio for women whose husbands smoked 20 or 

more cigarettes at home was 2.11 (95% C.I. = 1.13, 3.95). A logistic regression analysis showed a 

significant positive trend of increasing risk with increasing exposure to the husband's smoking at home, 

controlled for age, hospital, socioeconomic class, and year of diagnosis. Comparison of women classified 

by number of hours exposed a day to smoke in the last five years and in the last 25 years showed no 

increase in risk of lung cancer." 

A.4.9.2. Study Description 

This study was undertaken in New Jersey and Ohio to investigate the relationship of involuntary 

smoking to primary lung cancer. All data were collected specifically for this study, and only nonsmokers 

were included as subjects. Cases are the lifelong nonsmoking women histologically diagnosed with 

primary lung cancer during 1971-81 in four participating New Jersey and Ohio hospitals. Controls 

selected from patients with colorectal cancer were matched 3 to 1 to a case on hospital and age (" 5 

years). Subjects were not restricted to incident cases, and controls were apparently cumulatively sampled. 

Exposure data were obtained by blinded, face-to-face interviews with subjects or their relatives. 

A total of 1,175 female lung cancer cases were initially identified from medical records. 

Exclusion of women found to be current or former smokers or not to have histologically verified primary 

lung cancer eliminated 1,041 of the identified cases, leaving 134 ETS subjects. Interviews were 

conducted with patient, spouse, or child in about 75% of the subject population, whereas the rest were 

conducted with another relative. The age distributions of cases and controls are nearly identical. 

ETS exposure includes pipe and cigar use as well as cigarette smoking. Three sources of passive 

smoking are considered, which will be referred to as follows: "exposure to husband's smoke" means 

having a husband or other related cohabitant who smokes more than occasionally, either (1) anyplace or 

(2) at home; "general exposure" applies to the smoke of others at home, work, or otherwise who have 

smoked more than occasionally during the past (1) 5 years or (2) 25 years; and "childhood exposure" 

refers to experiencing ETS from any source during childhood. Husband's smoking is quantified as 

cigarettes per day and years smoked; general exposure is given as average hours per day; and childhood 

exposure is treated as a dichotomous variable. Only 57 percent of the cases were women living with a 

A-46
husband at the time of diagnosis. No checks on exposure status are described, and no classification of 

subjects by marital status was implemented. Adenocarcinoma (87) predominates among lung cancer 

cases, followed by large cell (21), small cell and miscellaneous (15), and squamous cell cancer (11); no 

data on airway proximity are provided. 

Ninety of 134 cases were exposed to husband's (or other relative's) smoking at home, compared 

with 245 of 402 controls, giving a crude odds ratio of 1.31 (reported 95% C.I. = 0.99, 1.73; C.I. 

calculated by reviewers is 0.87, 1.98). For husband's smoking of 20 or more cigarettes per day, the 

highest exposure category, the odds ratio increases to 2.11 (1.13, 3.95). Husband's smoking averaged 

11.5 cigarettes per day for the exposed subject. For husband's smoking anyplace, 91 of 134 cases and 254 

of 402 controls were exposed, giving a crude odds ratio of 1.23 (0.94, 1.60). At the highest exposure 

category, 40 or more cigarettes per day, the odds ratio is 1.99 (1.13, 3.50). Cigar and pipe smoking alone 

yields odds ratios of 1.17 and 1.13 for husband's smoking at home and anyplace, respectively. There are 

statistically significant trends for both husband's smoking at home and for smoking anyplace when 

measured by cigarettes per day, but not when evaluated by number of years smoked. The odds ratio for 

ETS exposure from husband's smoke, both total and at home, is calculated by source of interview 

respondent for the categories of "self," "husband," "daughter or son," and "other." It is readily apparent 

that the excess risk is attributable to "daughter or son," with some contribution from "other." None of the 

excess risk is attributable to "self" or "husband." 

General smoke exposure also shows an association with lung cancer. Exposure over the past 5 

and past 25 years yields odds ratios of 1.28 (0.96, 1.70) and 1.13 (0.60, 2.14), respectively. The odds 

ratios do not increase with increasing level of exposure, however, and none of the associations is 

statistically significant. No association was found between childhood smoke exposure and lung cancer 

(OR = 0.9, 0.74-1.12). When the odds ratio is calculated by source of respondent, "other" and "self" 

account for the excess risk when smoking for 5 years is the measure; for 25 years of smoking, "other" and 

"daughter or son" account for the excess risk. 

Stratification by cell type reveals that husband's smoking is much more strongly associated with 

squamous cell (OR = 5.00, both for smoking at home and anyplace) than adenocarcinoma (corresponding 

ORs = 1.33 and 1.48); no association with other cell types was detected. Stratification by age and 

socioeconomic status suggests little effect of these variables on the results. The results, however, appear 

to be sensitive to whether the interview data were obtained from the subject or a surrogate (offspring, 

relative, etc.), as noted above. 

A logistic regression analysis including adjustment for age, hospital, socioeconomic status, and 

year of diagnosis was undertaken for passive smoking. Cigarettes per day of husband's at-home smoking 

is significantly associated with lung cancer, with an estimated relative risk of 1.7 at exposure of 20 

A-47
cigarettes per day compared to none. In contrast, husband's smoking outside the home is not significantly 

associated with lung cancer, although the estimated relative risk is 1.26 for 20 cigarettes per day. General 

smoke exposure is not significantly associated with lung cancer, for either the past 5 years or 25 years of 

exposure. Adjustment for type of respondent reportedly had no significant effect on the logistic 

regression results. 

A.4.9.3. Comments 

The abundance of nonsmoking cases (134) and controls (402) in this study relative to most ETS 

studies gives it above-average statistical power. Comparability of cases and controls appears good based 

on their very similar age distributions, matching on hospital and age, and restriction to nonsmokers, 

although the lack of further demographic comparisons means that divergence on some other factor(s) 

cannot be ruled out. 

A major difficulty in this study, however, arises from the extensive use of proxy respondents. 

Only 12% (16 of 134) of the case interviews were with the patient. In the stratified analysis, it was found 

that the husband's smoking at home is positively associated with lung cancer only when the smoking 

information is provided by a son or a daughter rather than by the patient or her husband. This leads to 

several possibilities. Perhaps the son or daughter claimed that the patient's husband smoked when he 

actually did not, thereby shifting cases from the nonexposed to exposed category and increasing the odds 

ratio, or the patient or her husband claimed that the husband did not smoke when actually he did, thereby 

shifting cases from the exposed to nonexposed category and depressing the odds ratio. In general, it is 

thought more likely that true smokers are misclassified as nonsmokers more often than true nonsmokers 

are misclassified as smokers (see, for example, Lee, 1986, and Machlin et al., 1989). Also, Machlin 

indicates that proxies tend to misclassify smokers no more often than smokers themselves do. Thus, it 

may be that the son or daughter data are better than the self or husband data. Alternatively, the difference 

among the reporting sources may be due only to chance; the results in JANE on self or proxy reports are 

quite the opposite of those in this paper, with the proxy reports (in this case including the spouse) leading 

to lower odds ratios than the self-reports. 

Another possible problem with this study is the use of colon and rectal cancer cases as controls on 

the theory that these diseases are not smoking related. A recent paper, Zahm (1991), notes that 

associations have been found between smoking and these cancers. If these associations carry over to 

passive smoking, they might bias the result downward. 

In general, the detailed results from the stratified analysis in Table 6 of the paper exhibit 

considerable variation, probably caused by chance. Hence, the overall results in Table 5 of the article, 

where all the cases and controls are used, may be the most reliable. They indicate an odds ratio of 1.31 

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(1.24 after adjustment for smoker misclassification bias in the body of this report) for exposure to all 

types of husband's smoking at home. 

The study's exposure assessment methodology is strengthened by the attempt to maintain blinding 

by not informing interviewers of the study hypothesis or the subjects' disease status. This is impractical 

in most studies, but given the use of controls who also have cancer and a high proportion of proxy 

interviews, effective blinding of interviewers and subjects may have been largely achieved here. Detailed 

data on smoke exposure at home as well as elsewhere, including pipe and cigar smoking, were collected. 

Pipe and cigar smoking are often not considered in ETS studies, thus constituting a potential source of 

exposure misclassification, and smoking at home should be a more meaningful index of smoke exposure 

than total smoking. What the authors termed "husband's smoking" actually includes smoking by related 

cohabitants as well. Presumably, this was done both to increase subject numbers (by not excluding 

unmarried women) and to enhance detection of passive smoke exposure. However, it could cause some 

oversight with regard to classification of ETS exposure (e.g., a widow, living with a nonsmoking sister, 

whose husband had been a heavy smoker). Less understandable is the failure to include smoking by 

unrelated cohabitants and the inclusion of single women living alone. Diagnostic misclassification is 

unlikely given the histological verification of all cases and controls. 

Both husband's at-home and total cohabitant smoking are associated with lung cancer, the 

association being stronger for at-home smoking. Both exposures show a statistically significant general 

increase in association with level of smoking, with substantial associations only at high levels. The 

adjusted association for at-home cohabitant smoking is much stronger (OR = 1.7; p = 0.03) than that for 

smoking outside the home (OR = 1.3; p = 0.13), a pattern consistent with home smoke exposure rather 

than some other smoking-related factor as the basis of the observed results. General ETS exposure, in 

contrast, was inconsistently related to lung cancer in the unadjusted analyses, with a stronger association 

for exposure within the last 5 years than within the last 25 (possibly attributable to better recall). No 

dose-response pattern is evident, however, and no association was found in the adjusted analyses. 

The adjusted analyses include age, hospital, socioeconomic status, and year of diagnosis in a 

logistic regression model, along with the passive smoking variable. This adjustment did not significantly 

reduce the association between husband's smoking at home and lung cancer observed before the 

adjustment, but it did eliminate any association with general ETS exposure. Thus, the results for 

husband's smoking at home are probably not biased due to influences of age, socioeconomic status, 

hospital, or temporal variables. Dietary factors, heating and cooking practices, and family history of 

cancer were not considered as modifying risk; thus, an effect by one or more of these factors cannot be 

ruled out. 

The heavy reliance on proxy respondents and their uncertain impact on the analysis leaves some 

A-49
uncertainty in interpretation. On the favorable side of this issue, the authors' attempt to blind subjects and 

interviewers to the study hypothesis lessens the likelihood of potential bias from proxy response, and no 

significant effect due to respondent type was found in the adjusted analyses. Some of the exposure 

categories seem vague, but this would tend to reduce the magnitude of the observed association rather 

than to give rise to one. In summary, this study is suggestive of a dose-dependent association between 

smoking in the home and lung cancer, with reservations due to the use of proxies. 

A-50
A.4.10. GARF(Coh) (Tier 3) 

A.4.10.1. Author's Abstract 

"Lung cancer mortality rates were computed for nonsmokers in the American Cancer Society's (ACS) 

prospective study for three 4-year periods from 1960 to 1972 and in the Dorn study of veterans for three 5-year 

periods from 1954 to 1969. There was no evidence of any trend in these rates by 5-year age groups or for the total 

groups. No time trend was observed in nonsmokers for cancers of other selected sites except for a decrease in 

cancer of the uterus. Compared to nonsmoking women married to nonsmoking husbands, nonsmokers married to 

smoking husbands showed very little, if any, increased risk of lung cancer." 

A.4.10.2. Study Description 

This study examines the role of passive smoking in lung cancer among married women in the United 

States. It uses data collected in a large prospective study initiated by Cuyler Hammond of the ACS in 1959. The 

ACS's objective was to evaluate the association between potential cancer risk factors and cancer mortality. 

Although data were collected on the smoking status of women and their spouses at the start of the study, Hammond 

thought the study data should not be used to estimate lung cancer death rates in relation to amount of passive 

smoking by female never-smokers. Specifically, Hammond notes that the study was not designed for that purpose, 

and no special information on the subject was obtained; information was available on the smoking habits of the 

husbands of many of the married women in the study, but not on the smoking habits of the former husbands of 

women who were widowed, divorced, separated, or married for a second time. More important is his statement that 

women in America at that time were not generally barred from public and social gatherings where men were 

smoking, and working husbands who smoked generally did much if not most of their smoking away from home 

(Hammond and Selikoff, 1981). Similar reservations are expressed by Garfinkel, who also notes that 13% of the 

women nonsmokers who died of lung cancer in the ACS study reported that they were previously married and that 

the classification of their exposure to their husbands' smoking may not be pertinent (Garfinkel, 1981, p. 1,065). 

A total of 29 ACS divisions encompassing 25 states took part in the study; participating counties were in 

turn selected by division leaders based on feasibility. Data collection was undertaken by networks of volunteers set 

up within participating counties. Recruitment of subjects and subsequent followup monitoring were undertaken by 

volunteers who were instructed to enlist qualifying acquaintances. Subjects were restricted to persons more than 30 

years of age whose household contained at least one person over 45 years of age. Illegal immigrants and persons 

who were illiterate, institutionalized, or itinerant were excluded. Detailed questionnaires were distributed to 

subjects and all members of their household over 35 years of age. These questionnaires covered factors such as 

diet, alcohol consumption, and occupational exposures as well as smoking habits, but they did not address passive 

smoke exposure. Volunteers who recruited subjects were given responsibility for tracing the subject's vital statistics 

for the next 6 years and contacting living subjects again in 1961, 1963, and 1965 to complete a questionnaire on 

A-51
changes in smoking habits. Alternate researchers were appointed as necessary to replace volunteers who moved or 

quit. Finally, death certificates were obtained for subjects reported deceased; where death due to cancer was 

indicated, verification was sought from the certifying physician. Although followup initially ceased with 1965, in 

1972 an additional followup was initiated in 26 of the original 29 ACS divisions and terminated in September 1972. 

A.4.10.3. Comments 

The passive smoking study being described was undertaken by assembling a subcohort of married women 

who reported that they had never smoked and whose husbands completed a questionnaire including smoking habits. 

This subcohort totaled 176,739 women out of the 375,000 never-smoking women enlisted by the ACS in 1959. 

Women were divided into three exposure categories based on their husband's smoking status--nonexposed for 

never-smokers, and low (high) for current smokers of less (more) than 20. Wives of former cigarette smokers and 

men who smoked cigars or pipes rather than cigarettes were excluded (Garfinkel, 1984); presumably, these had 

already been excluded from the reported total (176,739). Mortality rates were computed by 5-year age intervals for 

unexposed women (i.e., wives of nonsmokers), from which the expected number of deaths for exposed women was 

estimated under the hypothesis that spousal smoking does not affect lung cancer mortality. The ratio of observed to 

expected deaths in the exposed group provides an age-standardized mortality ratio. This mortality ratio is 1.27 

(95% C.I. = 0.85, 1.89) for spousal smoking of under 20 cigarettes per day (low exposure) and 1.10 (0.77, 1.61) for 

over 20 cigarettes per day (high exposure). 

In a separate analysis, women healthy at the start of followup were divided into groups matched on age (5-

year grouping), race, education, urban or rural residence, and occupational exposure of husband to dust, fumes, or 

vapors. Each of these matched groups was then subdivided into zero, low, and high exposure categories. The 

proportion of observed deaths in each category was multiplied by the proportion of subjects in the smallest category 

of the matched group relative to that category. This "adjusted" number of deaths was then summed across all 

groups with a given exposure and compared with the corresponding value for the unexposed (zero exposure) 

category to provide a mortality ratio. In addition, we conducted a Mantel-Haenszel analysis of mortality using data 

supplied by Garfinkel that yielded results similar to the author's analyses. Ages 35 to 39 and 70 to 79 were 

excluded due to insufficient numbers. After stratifying by age and correcting for time under study, the calculated 

lung cancer risk was greater in subjects whose husbands smoked, but the predicted risk at low exposure was greater 

than at high exposure. It is notable, however, that the lower risk at higher exposure is entirely attributable to the 50-

to 59-year-old age group; otherwise, predicted mortality would be equivalent at the low and high exposure (see 

Table C-1 of the report under discussion). 

The original ACS cohort study was a massive undertaking. By using it as the basis of his cohort, Garfinkel 

was able to assemble a very large number (more than 170,000) of never-smoking married women. A cohort of this 

magnitude attains a number of lung cancer cases ordinarily feasible only by means of a large case-control study, 

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while avoiding the attendant pitfalls of potential recall and interviewer bias associated with case-control studies. 

There are several important limitations, however, that make the results of this study difficult to interpret. The ACS 

study was not designed to yield a representative sample of the general population. The sample of women is older 

(all at least 35 years of age, two-thirds between 40 and 59 at start of followup), more educated (only 5.6% were 

limited to a grade school education), and contains a much smaller proportion of ethnic minorities (only 6.8% 

nonwhite) than the general population (Stellman and Garfinkel, 1986). Although not representative of the 

population as a whole, the relative homogeneity of the subject population does reduce the potential for 

complications of interpretation that differences in ethnic or socioeconomic factors or both may pose, and it increases 

efficiency by not including subjects belonging to age groups unlikely to experience significant mortality during 

followup. Overall, the study population's unrepresentativeness strengthens rather than undermines the study's 

conclusions. It would have been useful, however, to confirm that exclusion of greatly underrepresented groups, 

such as nonwhites and persons with no formal education beyond the eighth grade, had no effect on the results. 

Because the data on smoking habits were collected prospectively, no information on exposures prior to 

1959 was obtained. Exposure history for the years before 1959 may be as important as for the 12 years of followup, 

however, if lung cancer has a long latency period, such as 20 years or so. Inclusion of persons whose exposure 

status may have changed markedly by 1959 could be a biasing influence. Neither were changes in exposure status 

during the followup period considered, despite the availability of data on smoking habits in 1961, 1963, 1965, and 

1972. In fairness to the author, keep in mind that our comments are directed at evaluation of the study for its 

contribution to the issues of passive smoking and lung cancer, although the ACS study was not designed to assess 

ETS exposure. The only data collected on ETS exposure are based on the spouse's current smoking habits at 

initiation of the study. If the ACS study had been directed at evaluation of health effects of ETS, these issues would 

likely have been taken into consideration to sharpen the classification of subjects with respect to ETS exposure. 

Overall, the likely consequence of these factors is to reduce the sensitivity of the study to detect an association 

between lung cancer and ETS exposure, but the potential for bias in the direction of a false positive cannot be ruled 

out. For example, if wives of smokers are more likely to become active smokers during followup than wives of 

nonsmokers, these changes in smoking status could bias results toward finding a positive association with passive 

smoking. (Relevant to this particular example, the authors state that "very few" subjects reported a change in their 

smoking status, but provide no further details. Also, 12 or fewer years is a short exposure to produce lung cancer. 

It is thus probable that any bias introduced by active smoking would be minor; furthermore, the fact that a stronger 

association was observed for low than for high levels of spousal smoking argues against a confounder associated 

with spousal smoking. Nevertheless, potential sources of bias may be present that influence the study outcome in 

either direction.) 

During 1959-65, confirmation of primary lung cancer diagnosis was obtained from physicians for 78% of 

all cancer cases. Among 203 cases of lung cancer in nonsmoking women diagnosed by death certificate, 

A-53
confirmation attempts on an unspecified number of these cases found 34 misdiagnosed as primary lung cancer, 

whereas 10 primary lung cancers were discovered among cancers diagnosed as nonlung on death certificates. Thus, 

it appears that only about 85% of the death certificate diagnoses of primary lung cancer were accurate, while a small 

percentage of primaries were misdiagnosed as cancers of other sites. No confirmation of diagnoses was undertaken 

during the period after 1965 when nearly two-thirds (119 out of 182, according to data supplied to reviewers by 

Garfinkel) of the lung cancer deaths in the ETS study population were reported. In light of the misdiagnosis rates 

found for 1959-65, it is likely that a substantial percentage of the study's reported primary lung cancers in cases 

actually arose in other sites, whereas a substantial percentage of reported cancers of other sites actually arose in the 

lung. The resultant errors in subject classification probably bias the results toward no association (i.e., a false 

negative conclusion), if a positive association actually exists. 

Loss of subjects to followup is another source of potential bias. A subsequent report on the ACS cohort 

(Garfinkel, 1985) states that, whereas more than 98% of the original cohort was successfully traced through 1965, 

more than 10% (3 of 29) of the original ACS divisions declined to participate in the 1971-72 followup effort. In the 

study now under review, Garfinkel reports successful followup of 98.4% through 1965 and 92.8% through 1972, 

apparently not considering subjects in the division who declined to participate in the extended followup as losses. It 

thus appears that, whereas more than 98% of the original cohort was successfully followed up through 1965, less 

than 90% of the cohort was targeted for followup through 1972, and losses for this targeted group approached 7%. 

Such losses not only reduced the number of observed deaths--and, hence, the study's power--but introduced the 

possibility that differential loss to followup could have distorted the study's results. A greater proportion of losses 

among exposed subjects than among unexposed could partially mask a true positive association, whereas greater 

loss among the unexposed could potentially create a spurious association. 

Aside from the issues above, the study controls for risk modifiers. Subjects were all of the same gender 

and marital status, and age was controlled for in all analyses. Analysis by groups matched on race, education, 

residence, and occupation, along with age, produced nearly identical results as the analyses standardized by age 

alone, indicating no confounding due to these and unlikely confounding due to other socioeconomic, occupational, 

or geographic factors. 

In summary, this study predicts a weak positive association between spousal smoking at levels of 1 to 19 

cigarettes per day and lung cancer, but only slight association at higher exposure levels; neither association is 

statistically significant. The lack of apparent dose-response pattern undermines the association, but the confidence 

intervals of the point estimates for the high- and low-exposure groups overlap so broadly that the existence of a 

dose-response relationship cannot be ruled out entirely. Meaningful interpretation of the results for the issue of ETS 

exposure and lung cancer, however, is limited. Because the study's objectives were directed elsewhere, the data 

collected on ETS exposure are limited to the status of spousal smoking at the start of the study. Past history and 

future changes in status are not well addressed. There is ample indication that death certificate diagnoses are not a 

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reliable source for the selection and classification of subjects. Although a second 6-year followup period was 

undertaken to increase the followup period to 12 years, its success was limited by incomplete participation and, 

perhaps, by organizational difficulties related to long-term reliance on volunteers (who may relocate, change 

interests, lose contact with the subjects originally enlisted over an extended period, etc.). Even if the followup were 

entirely successful, however, 12 years of followup without regard to exposure experience is not a particularly long 

period to evaluate the lung cancer potential for ETS because the latency period associated with active smoking may 

be on the order of 20 years. Although the ACS study has been an important contribution to its main study 

objectives, the limited exposure information and other potential sources of bias for the issue of passive smoking and 

lung cancer leave its assessment in question. 

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A.4.11. GENG (Tier 4) 

A.4.11.1. Author's Abstract 

Not included in source. 

A.4.11.2. Study Description 

This study was conducted in Tianjin, where China's highest incidence of female lung cancer occurs, to 

illustrate the relationship between cigarette smoking and lung cancer in females. The study explores both active and 

passive smoking, so the analyses for passive smoking apply to a subgroup of the larger subject population. The 

source of the study's subjects and the time over which they accrued are not specified. Subjects resided in Tianjin for 

more than 10 years. The source of controls is not given, but they consist of females pair-matched with cases on 

race, age (" 2 years), marital status, and birthplace. It is unclear from the article whether cases were incident or 

prevalent and how controls were obtained. A draft summary description of this study (Liang and Geng, undated) 

from Liang indicates, however, that hospitalized cases (96) were matched with inpatient controls and that general 

population cases (61) were matched with neighborhood controls. 

The source of the study's exposure data is not clearly stated, but the draft from Liang indicates that all 

identified cases and controls were interviewed. No information on collection or verification of smoking or other 

data is provided. The authors state that cases and controls do not differ significantly in age, education, occupation, 

race, marital status, birthplace, or residence, but this refers only to the total study population of 157 cases and 157 

controls that includes active smokers; the same similarity may not hold for the 54 cases and 93 controls used in the 

passive smoking analysis. Tumor types are provided for 85% of the total case population but not specifically for the 

passive smoking subpopulation; adenocarcinomas (36.9%) predominate, being about twice as common as squamous 

(22.3%) or small cell (19.7%) tumors. Although nearly 85% of the total cases were diagnosed histologically or 

cytologically, it does not appear that verification of diagnosis or primary status of tumor was undertaken by the 

authors, and no information on tumor distribution is supplied. 

A nonsmoker (which usually means never-smoker) is ETS exposed if the spouse smokes. Presumably, 

women not currently married are excluded from the analysis, although they could have been included with some 

assumption made regarding their exposure status. Information on dose and duration of exposure was collected but 

not used in the passive smoking analysis, and it is not indicated if cigar or pipe smoke was included. ETS exposure 

from parents and colleagues is reported to have been evaluated. The parental smoking referred to is apparently in 

adulthood, as cohabitants in the home, but that is not made explicit. Exposure during childhood was not specifically 

addressed. 

Among the ETS subjects, 34 of 54 cases and 41 of 93 controls were exposed. This yields a statistically 

significant crude odds ratio of 2.16 (95% C.I. = 1.03, 4.53) for husband's smoking. No analyses adjusted for age or 

other factors are reported. On a rather confusing note, an odds ratio of 1.86 is cited twice later, but that value is 

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inconsistent with the odds ratio of 2.16 from the raw data. Whether this is an error or the product of an unspecified 

adjustment by conditional logistic regression, which the authors employ for other purposes throughout the paper, is 

unknown. The odds ratio increases with the number of cigarettes smoked per day by the husband and with the 

duration of the husband's smoking. The odds ratios for smoking rates of 1 to 9, 10 to 19, and 20 or more cigarettes 

per day are 1.4, 2.0, and 2.8, respectively. For 1 to 19, 20 to 39, and 40 or more years of exposure, the odds ratios 

are 1.5, 2.2, and 3.3, respectively. No tests for trend are cited, and the relevant data are not given. Consideration of 

ETS exposure from smoking by father, mother, or "colleagues" reportedly yielded no results that are "quite 

significant." No further details are provided, and it is not clear whether these results consider past smoking status or 

apply only to current status. 

The authors conclude that active and passive smoking are the most important risk factors for female lung 

cancer in Tianjin. They attribute 35% to 42% of lung cancer occurring in their nonsmoking female population to 

passive smoking. Female lung cancer also is found to be associated with other factors, such as occupational 

exposure, with an odds ratio of 3.1 (95% C.I. = 1.58, 6.02); history of lung disease, with an odds ratio of 2.12 (95% 

C.I. = 1.23, 3.63); and cooking with coal, where the odds ratio increases with the duration of exposure from 1.5 to 

5.5 (see Table 8 of this reference). 

A.4.11.3. Comments 

The quality of this study is difficult to assess given the dearth of details supplied by the authors. Certainly 

the number of nonsmoking cases and controls included is more substantial than in some other studies, and the 

reported association between passive smoking and lung cancer is statistically significant. Questions regarding the 

mechanics of data collection and analysis, however, remain unanswered. 

Exposure and other data were obtained from hospitalized subjects at bedside and from others in their 

homes. Apparently no information was obtained from proxy sources; the number of cases (or controls) who could 

not be interviewed is unspecified. No blinding was employed, but that may not have been feasible. Despite the 

reported similarity of the demographic characteristics of the total case and control populations, dissimilarity cannot 

be ruled out within the subgroup used for ETS analyses. Although the whole study, including active smokers, is 

matched on several variables, that matching need not apply to the ETS subjects alone. 

Lack of validation of diagnostic and exposure information may have led to substantial misclassification, 

although the fact that 85% of the lung cancer diagnoses were obtained via histology or cytology suggests that 

diagnostic misclassification would not have been extreme. Lack of consideration of former smoking status is a 

potential problem. Inclusion of former smokers among the nonsmokers, in combination with a tendency for former 

smokers to marry smokers, could produce an upward bias in the odds ratios. 

Finally, although the crude odds ratio of 2.16 for passive smoking is statistically significant, it does not 

take into account even the most basic potential confounder--age. For the larger case-control population (including 

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smokers), occupational exposure (OR = 3.1), history of lung disease (OR = 2.64), and cooking with coal (OR = 

1.54-5.56, rising with cumulative exposure) are statistically significant risk factors that the authors claim have joint 

effects with smoking, yet the ETS analysis is not adjusted for these likely confounders. The anomalous odds ratio 

of 1.86 given later in the results may have been adjusted for age or other factors, but there is no way to tell. Also, 

the detection of an effect of ETS would be unexpected if the study area suffered from high environmental levels of 

carcinogenic combustion products of coal, as seen in LIU and WUWI. Although the literature contains no studies 

of Tianjin, Beijing is nearby. Zhao (1990) reports that mean levels of a urinary indicator of polyaromatic 

hydrocarbon exposure 

(1-HP) in nonsmoking housewives are much lower in Beijing than in Shenyang, one of the WUWI study sites, but 

Wang (1990) found that indoor air pollution, principally due to coal burning, sometimes masks the effect of active 

cigarette smoking. 

In summary, the study's results are consistent with the hypothesis that passive smoking increases the risk of 

lung cancer, but they are not definitive. More detail regarding the mechanics of the study is needed to assess its 

general validity. If warranted, a clearer and more complete analysis of the study's data regarding passive smoking, 

including consideration of the information on dose, duration, and potential confounders already available, would 

then be useful. For the current evaluation of epidemiologic evidence on ETS exposure and lung cancer, too many 

questions remain about the design and execution of the study to properly interpret the data and assess the authors' 

conclusions. 

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A.4.12. HIRA(Coh) (Tier 2)

(Note: Because of the many publications relating to this study, a different format of presentation is used.) 

This cohort study and a later case-control study based on it were undertaken to explore the relationship of 

passive smoking and other factors with lung cancer in Japanese women. Subjects and data used in this study were, 

however, drawn from a larger study that was not designed to investigate passive smoking. 

An exploratory study of mortality determinants targeting adults at least 40 years of age inhabiting 29 health 

center districts in Japan was initiated in 1965. In autumn of 1965, more than 90% of the target population was 

interviewed to ascertain the status of lifestyle factors that might affect health (e.g., cigarette smoking, alcohol 

consumption, and occupation). Individuals, including husbands and wives, were interviewed separately. Followup 

of the interviewees was conducted using a combination of an annual census of residents and death certificates to 

monitor mortality. Mortality, as determined by death certificate, was the outcome variable. Hirayama used this 

study population to examine the potential effect of passive smoking on lung cancer mortality. In 1981, he reported 

the results derived from the first 14 years of followup (through 1979) in the British Medical Journal. 

A total of 142,857 women were interviewed in 1965, of whom 91,540 were nonsmokers whose husbands 

also had been interviewed regarding smoking status. Using their husbands' smoking status as a surrogate for 

exposure to ETS, Hirayama calculated lung cancer mortality rates for comparison of women married to smokers 

with women married to nonsmokers; rates also were calculated using various strata of spousal smoking intensity 

(number of cig./day), as well as age and occupation. A total of 346 lung cancer deaths occurred in this cohort 

during the first 14 years of followup. 

After standardization for age and occupation, it was found that women whose husbands smoked daily had a 

higher annual rate of lung cancer mortality than did women whose husbands were nonsmokers or only "occasional" 

smokers. The rate increased with the level of smoking (e.g., 8.7/100,000 annually for no or occasional smoking, 

14.0 for smoking 1-19 cig./day, and 18.1 for 20+ cig./day). Higher rates and a dose-response pattern were observed 

in women married to smokers after stratification on either husband's age or agricultural work status. Mortality due 

to two diseases associated with active smoking, emphysema and asthma, was also higher in wives of smokers and 

increased with exposure. Conversely, mortality due to two cancers not linked to active smoking, cervical and 

stomach cancer, was no higher in wives of smokers. Consideration of husbands' drinking habits had no significant 

impact on mortality for lung cancer or other diseases mentioned above. 

Further study results appeared in the October 3, 1981, issue of the British Medical Journal. Among other 

things, results were presented by husband's age in 10-year intervals instead of 20-year intervals and for 10 

occupational categories instead of 2. These tabulations revealed a statistically significant overall association 

between husbands' smoking and lung cancer mortality with a dose-response pattern (1.00 RR for nonsmokers plus 

former smokers, 1.44 RR for medium smokers, and 1.85 RR for heavy smokers). Also of interest was a breakdown 

of lung cancer mortality and smoking habits in greater detail for both husband and wife. Notably, nonsmoking 

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husbands with smoking wives showed a higher lung cancer mortality rate (RR = 2.94) than did those with 

nonsmoking wives. Because nonsmoking husbands with smoking wives were rather rare, however, the numbers in 

this stratum were low (only seven deaths); thus, the observed association was not statistically significant. 

In 1984, Hirayama published results of an additional 2 years of followup of his cohort in Preventive 

Medicine. The same basic associations reported after 14 years of followup for spousal smoking and lung cancer 

remained after 2 additional years of followup. Mortality rates increased with increasing exposure after stratification 

by age of husband, occupation, geographical area, and time period during study; a trend had been reported after 

stratification for age of wife at start of study only for ages 40 to 49 and 50 to 59. It also was reported that the 

elevation of lung cancer mortality in nonsmoking women married to smokers was significantly less among women 

who consumed green-yellow vegetables daily (e.g., for spousal smoking of 20+ cig./day, the RRs for disease 

mortality were 1.63 and 2.38). No such pattern was observed for ischemic heart disease. In addition, a statistically 

significant excess of para nasal sinus cancer in nonsmoking wives of smokers had been observed, which showed an 

apparent dose-response relationship across four smoking categories, culminating in an RR of 3.44 for spouses of 

smokers of more than 20 cigarettes per day. That effect dwarfed those related to social class and dietary factors that 

were also examined. 

In 1988, Hirayama reported the results of a case-control study nested within his cohort in Environmental 

Technology Letters. To explore the relationship of women's age at marriage as well as husbands' smoking status 

with lung cancer mortality, lung cancer cases occurring among nonsmoking women in the cohort study were 

contrasted with stomach cancer cases as controls. Including only women under 59 years of age at the start of the 

cohort, the study divided husbands' smoking into three categories--none, 1 to 19, and 20 or more cigarettes per day. 

Age at marriage also was trifurcated in 19 or fewer, 20 to 23, and 24 or more years. Apparently as a result of 

exclusion of women over the age limit or because of missing data, only 115 cases and 423 controls were ultimately 

compared out of the 200 lung cancers and 854 stomach cancers among the nonsmoking female cohort. Adjusting 

for woman's age and husband's smoking category resulted in odds ratios for lung cancer of 4.95, 1.76, and 1.41 for 

the respective age-at-marriage groups; the first two of these odds ratios were statistically significant. An additional 

comparison found that among lung cancer cases, the mean age at first marriage to a smoking husband was nearly 

8 years less than the mean age at start of smoking for active smokers. 

A greatly expanded nested study was presented in the following year (Hirayama, 1989). The study was 

designed to explore the potential effect of dietary habits on the relationship between lung cancer and spousal 

smoking. A "baseline" sample of 2,000 nonsmoking wives, aged 40 to 69 at the start of the cohort study, with 

known spousal smoking habits was randomly selected from the available cohort of 90,458 for comparison with the 

194 lung cancer cases occurring in equivalent subjects within the cohort. After determining that the age 

distributions of the case and baseline groups were very similar within smoking categories, the combined population 

was stratified on daily versus less-than-daily consumption for each of five food types (green-yellow vegetables, fish, 

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meat, milk, and soybean paste soup), and wives with smoking and nonsmoking husbands were contrasted to assess 

differences in dietary habits. After adjustment for wife's age and husband's occupation, only daily meat 

consumption was significantly more common among wives of smoking husbands, and this was limited to smokers 

of 20 or more cigarettes per day. Calculation of odds ratios for dietary habits resulted in a "significant" elevation 

only in daily fish consumers (OR = 1.365, 90% C.I. = 1.05, 1.77; Table IV). A nearly significant lowering of the 

odds ratio was found in daily meat consumers. 

Finally, odds ratios were calculated for lung cancer adjusted by wife's age, husband's occupation, and each 

of the dietary habit categories in succession. A dose-response pattern was observed between lung cancer and 

husband's smoking that persisted after adjustment for any of the five dietary factors. Odds ratios for the five dietary 

habit categories ranged from 1.42 to 1.69 for former smokers and smokers of 1 to 19 cigarettes per day and from 

1.66 to 1.91 for smokers of 20 or more cigarettes per day compared with nonsmoking husbands. The observed 

trend was highly statistically significant, regardless of which factor was adjusted for in the calculation. 

A.4.12.1. Chronology of Controversy 

Publication of Hirayama's initial 14-year followup results in 1981 provoked a sizeable volume of 

commentary in the scientific literature. Following the release of updated results in 1983-84, the study attracted little 

controversy until the latter part of the 1980s, when criticisms were directed at the study by a number of authors. 

This process reached its culmination in response to the EPA's release for external review of the document Health 

Effects of Passive Smoking: Assessment of Lung Cancer in Adults and Respiratory Disorders in Children, which 

placed considerable emphasis on Hirayama's results. An author-by-author, letter-by-letter consideration of the 

arguments regarding Hirayama's work would be dauntingly duplicative and tedious. Instead, the most-discussed 

concerns are highlighted below, followed by an overall assessment of the study as it stands today. 

Chronology of Selected Events Relevant to the Hirayama Cohort Study

Jan. 7, 1981 Results of cohort study are published in British Medical Journal (282:183-185). 

Oct. 3, 1981 Comments and letters to the editor by Kornegay and Kastenbaum (of the U.S. Tobacco Institute), 

Mantel, Harris, and DuMouchel, and MacDonald regarding Jan. 7 article appear in British 

Medical Journal, along with the author's reply. 

March 3-5 Hirayama presents updated results for his study cohort incorporating an 

and July additional 2 years of followup (for a total of 16 years) to the International Lung 

10-15, 1983 Cancer Update Conference in New Orleans and the 5th World Conference on Smoking and Health

in Winnipeg, Canada. 

Dec. 17, 1983 Updated results of the cohort study are published in Lancet. 

1984 Results presented in conference of July 1983, and in summary form in Lancet later that year, are 

published in full in Preventive Medicine. In addition, Hirayama now reports a statistically 

A-61
significant increase in brain tumors with husbands' smoking. In a roundtable discussion published 

in the same journal, Lee proposes that misclassification of active smoking status may have biased 

Hirayama's results. 

1985 Another publication of results for the 16-year followup appears in Tokai Journal of Experimental 

Clinical Medicine. 

1987 Hirayama includes previously published study data in a book chapter (Aoki et al., 1987). 

1988 Uberla and Ahlborn publish an article from the Proceedings of the Indoor Ambient Air Quality 

Conference in London (which is essentially the same as an earlier presentation at the 1987 Tokyo 

International Conference on Indoor Air Quality) criticizing the Hirayama study on several 

grounds. Their primary assertion is that correction for the cohort's age distribution removes the 

apparent effect of spousal smoking. 

1988 Hirayama publishes the results of nested case-control study based on cohort study data in 

Environmental Toxicology Letters. Estimated risk of lung cancer is reported to increase with 

earlier age of marriage to smoker. 

1989 Layard and Viren publish a paper presented at the Conference on the Present and Future of Indoor 

Air Quality in Belgium. Making their own projections of expected deaths and estimating losses to 

followup, they conclude that mortality rates were anomalously low and followup losses 

unacceptably high in the Hirayama study. 

1989 Hirayama publishes nested case-control results in Present and Future of Indoor Air Quality. 

Positive association of husband's smoking and lung cancer with dose-response pattern is reported 

after adjustment for dietary variables. 

A.4.12.2. Some Major Critical Works 

A basic point raised by MacDonald (1981) and others soon after publication of Hirayama's initial results 

concerned the selection of the study's sample population. It appeared that the 

29 health centers included in the study were selected on grounds of convenience rather than to provide a randomly 

sampled, representative cross-section of the Japanese population. The resultant sample might thus be 

unrepresentative of the Japanese population as a whole. 

Hirayama replied in 1981 that "the satisfactory representativeness [of the study population] 

. . . with regard to demographic and social indices was confirmed after the survey." He did not, however, provide 

supporting data. MacDonald (1981) contended that the six prefectures from which the sample was drawn are 

relatively industry-heavy. Hirayama (1983a) presented data showing that 40,390 of the cohort's wives were married 

to agricultural workers, 19,264 to industry workers, and 31,886 to "others," indicating some overrepresentation of 

agricultural areas. He later (1990b) cited quality of incidence data, geographical diversity, and coverage of 

communities of both urban and rural character as well as different dominant industries as key selection criteria. 

Women aged 70 or more are clearly underrepresented, composing less than 1% of the study's 40-and-older 

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nonsmoking female population; this aspect of the study will be addressed later. 

The key problem arising from an unrepresentative sample is that it may limit generalizability of results 

derived from that sample to the population as a whole. In lieu of good reasons to think that the association between 

exposure and disease would be different in the study population and the general population, however, the possibility 

of an unrepresentative sample assumes less importance. Further, in this case, substantial numbers from each major 

geographical and occupational element of the general population were included in the sample. And, as will be seen 

in the subsequent discussion, similar patterns of association were observed in a number of demographic subgroups. 

Misclassification may occur in any epidemiologic study. Most of the critical commentary has focused on 

potential misclassification of exposure status. Because the study relies on interview data to establish smoking 

status, misreporting by interviewees may affect accurate classification of both wives and their husbands' smoking 

habits. It has been argued that women are especially likely to misrepresent their smoking habits because smoking is 

considered less socially acceptable for women than for men, particularly in Asian societies. Such misclassification 

would tend to reduce the degree of association between passive smoke exposure and its effect(s) if women in the 

"exposed" and "unexposed" groups were equally likely to misreport their own smoking. One of the most prominent 

criticisms leveled at the Hirayama study postulates a differential misclassification of smoking status in women. 

Peter Lee (Lehnert, 1984) raised the argument that if women married to smokers are more likely to be (or to have 

been) smokers than women who are married to nonsmokers, and a given percentage of smoking women claim to be 

nonsmokers, then purportedly nonsmoking wives of spousal smokers will include a higher proportion of active 

smokers than wives of spousal nonsmokers. This will cause bias in the direction of a positive association. 

Arguments over the probable size of this bias have occurred with estimated elevations in risk ranging from a few 

percent to around 50%, depending on assumptions regarding the extent of misreporting, the risk inherent in active 

smoking, and the degree of marital concordance between smokers (Lehnert, 1984; Wald et al., 1986; Lee, 1987a, b). 

Uberla and Ahlborn (1987) raised a number of points regarding the Hirayama study, including those 

previously mentioned. Citing the "severe selection bias by age," the authors report that the increase in risk with 

spousal smoking disappears when this bias is corrected for. The study population in fact contained a very small 

proportion of women aged 70 or older (only about 1%)--so small that the rates generated by nonsmoking married 

women aged 70 or older are too unstable to provide meaningful results. But by taking the negative results observed 

in this tiny, unstable stratum of the cohort and weighting them to "correct" for the underrepresentation of this age 

group, the overall association is made to disappear. Such a "correction" is meaningless. In addition, Hirayama 

(1990b) has noted that the authors inappropriately adjusted to the total female population rather than to the 

population of currently married females, and he characterized the adjustment as "neither of scientific significance 

nor of creative value." 

The authors also essentially take Lee's approach to the differential misclassification problem and claim that 

a modest differential misclassification "leads to risk ratios of around unity." As seen previously, this argument is 

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plausible but purely speculative--and potential biases toward the null are ignored in this and other "corrections." 

The authors conclude that "the null hypothesis . . . is consistent with the Hirayama data in the same way as is the 

alternative." But unless one applies the aforesaid "corrections," the Hirayama data are, in fact, more consistent with 

the hypothesis of association than with the null hypothesis. 

Layard and Viren (1989) estimated "projected" mortality rates for a cohort with the age and time 

distribution found in the Hirayama cohort by applying "standard demographic life table procedures" to year- and 

age-specific life table data from United Nations and Japanese sources. They concluded that female all-cause and 

lung cancer reported rates were only 76% and 85%, respectively, of projected values. In a separate analysis, the 

authors also "calculated the numbers of person-years that would have been observed in the cohort if there had been 

100% followup" from the reported numbers of deaths. The assumptions used in this calculation are unstated. The 

authors then estimated, based on the difference between their person-years for 100% followup and the reported 

person-years, and an assumption that 8 years of observation were lost on average for each person lost to followup 

over the 16-year course of the study, that approximately 10% of the cohort was lost to followup. Dismissing other 

possible causes of their estimated mortality deficits, Layard and Viren conclude that "it is possible that biases exist 

in the data which might invalidate an observed relationship between exposure to ETS and mortality." 

Acceptance of Layard and Viren's conclusions must start with acceptance of the validity of their 

assumptions and calculations, not all of which are stated explicitly. Beyond that, their rejection of alternative 

explanations for the difference between projected and reported deaths is not convincing. For example, random 

sampling variation and regional variations in death rates are both dismissed because neither could produce an effect 

as large as that observed, although the authors' figures indicate that in combination they could well account for a 

sizeable portion of the difference. Likewise, the effect of admitting only (initially) "healthy" people to the cohort is 

dismissed based on the observation of "still very substantial cohort deficits in the last years of the study" without 

specification of how substantial such deficits were and ignoring the fact that a pattern in which all-cause mortality is 

most affected and cancer mortality least, as their calculations showed, is the expected pattern for an effect of 

selection of healthy individuals. Finally, to produce a spurious association, a bias must operate differently on the 

exposed (smoking spouse) and unexposed (nonsmoking spouse) groups, and no evidence is provided that supports 

such a pattern. In fact, Hirayama (1990b) reported an approximately 8% loss to followup for the whole cohort, 

which did not differ significantly by male smoking status. Lacking a pattern of differential loss, the most likely 

effect of loss to followup is a reduction in the observed associations due to missing mortality events. The effect of 

selecting an abnormally healthy cohort would in a strict sense limit generalizability of conclusions but would not in 

itself produce an exposure-effect association when none actually existed. 

A.4.12.3. Critique and Assessment 

Hirayama's cohort is drawn from a study population assembled to explore the associations between a 

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number of potential health-influencing factors determined via interview and subsequent mortality. Thus, the study 

was not designed to investigate passive smoking and lung cancer specifically. Most of the weaknesses attributable 

to Hirayama's study derive from this fact. 

The only indicator of ETS available to Hirayama was self-reported smoking status at time of baseline 

interview. Thus, misclassification of spousal smoking status is possible, and change in status over time, modifiers 

of exposure to spousal smoking, and other sources of ETS exposure cannot be determined. 

As previously seen, an overrepresentation of current and former active smokers claiming to be nonsmokers 

among wives of tobacco smokers probably biases the association between spousal smoking and lung cancer in 

reported nonsmokers upward. Even the leading proponent of this argument, however, states that unless this bias is 

much stronger than it appears to be in U.S. and Western populations, it could not account for the major part of the 

observed results (Lee, 1990). Lack of information regarding the amount of smoking actually done in the home and 

in the presence of the spouse, room size and ventilation, and other exposure-modifying factors must lead to 

imprecision in the estimates of exposure via spousal smoking. This imprecision would make an actual ETS-lung 

cancer association more difficult to detect. The fact that spousal smoking exposure, even if precisely measured, is 

an imperfect surrogate for total ETS exposure because workplace and ambient environmental sources are not 

assessed introduces a similar effect. Both of these problems would thus introduce a bias toward the null, suggesting 

that the study's results are an underestimate of the real association. 

Mortality information was derived from death certificate linkage. It has been contended that lung cancer is 

routinely overdiagnosed as a cause of death on death certificates, thus undermining the study's credibility. But the 

resultant misclassification of cause of death would presumably be nondifferential, and thus bias results toward the 

null. To cause overestimation of the association, a greater proportion of women in the spousal smoking groups than 

in the nonsmoking group would have to be falsely diagnosed as having lung cancer. Because the study cohort was 

made up of nonsmoking women, there would be little reason for such a pattern (unless, of course, all such cases 

came from women who falsely reported their initial smoking status or took up smoking in the course of the study 

and the misclassification/smoking habit concordance hypothesized by Lee were actually strongly at work). 

No information is given regarding whether the same interviewers interviewed both husbands and their 

wives. Thus, interviewers may not have been blind to spousal smoking characteristics of interviewees. This is 

likely to have been of little importance, however, because the outcome--lung cancer mortality--was measured 

prospectively, and thus did not occur for some time after exposure had been assessed. If information bias was to 

some extent operant in the interview, the most likely scenario would find women whose husbands smoked being 

probed more strongly for admission of their own smoking than were women whose husbands did not smoke. This 

would tend to reduce underreporting of active smoking in the "exposed" group relative to the "unexposed" group. 

The result would be to lower the observed association between husbands' smoking and lung cancer mortality. 

Hirayama's cohort includes only married, reportedly nonsmoking women who were at least 40 years of age 

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and "healthy" at the start of the study. In addition, almost all of these women were under 70 years of age, and 

agricultural families composed a larger part of the cohort than of the general population. Thus, the cohort does not 

present a proportionately accurate cross-section of the Japanese population as a whole. Nevertheless, there is little 

obvious reason why a relationship between spousal smoking and lung cancer mortality found in this cohort should 

be dismissed on the grounds that it is not generalizable to the greater Japanese (or other) population. 

The possibility that confounding by other risk factors explains an observed association must be considered 

in any study. For lung cancer, of course, smoking, gender, and age are major risk determinants. Restriction of 

comparison groups to same-gender nonsmokers avoids possible effects due to gender or smoking (but see 

misclassification discussion regarding smoking status). Age is only partially restricted in the study design, so its 

consideration in the analysis is essential. Hirayama chose to control for husband's age in analyzing the cohort 

study's results. All observed associations persisted after such adjustment. Spousal ages should be closely 

correlated, but direct adjustment using the subject's own age rather than the age of their spouse would clearly be 

preferable. One such analysis was supplied (Hirayama, 1983a), and in it a significant association between spousal 

smoking and lung cancer mortality persisted. Furthermore, in analyzing the nested case-control studies, adjustment 

for wife's age was used throughout, which produced findings that confirmed the results of the cohort study. 

The potential role of confounding by other factors in the observed results has received considerable 

emphasis. A correlation between smoking and lower socioeconomic status with concomitant lifestyle and 

environmental differences could be expected. Among these differences, particular attention has been paid to the 

possible effect of dietary factors (particularly low beta- carotene intake) and occupational exposures, both of which, 

some hold, should correlate with spousal smoking and thus could bring about the observed association even if 

spousal smoking and ETS exposure have no effect. Yet, neither stratification on daily green-yellow vegetable 

consumption--the best available surrogate for beta carotene intake in the data--nor on agricultural versus 

nonagricultural occupation of husband eliminated the association between spousal smoking and lung cancer 

mortality in the cohort study. Similarly, adjustment for husband's occupation and any of five dietary habit 

characteristics, along with wife's age, yielded similar results in the case-control approach. Thus, neither of the 

major proposed confounders satisfactorily accounts for the observed results. 

Because the data set does not contain the necessary information to examine effects due to differences in 

cooking practices (such as stir-frying), this cannot be ruled out, although such practices might be expected to covary with some of the dietary factors considered in the analyses. Similarly, use of coal for cooking or heating 

cannot be directly assessed, although a degree of covariance with dietary habits or occupation is likely. 

Husbands' drinking habits were only marginally associated with lung cancer risk; mortality rates stratified 

by both drinking and smoking would have been more useful (and stratification by wives' own drinking habits would 

have been more useful still). 

When lung cancer mortality among wives is stratified by wife's age (in 10-year increments) and husband's 

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smoking category, a clear dose-response pattern is seen only in the 40 to 49 and 50 to 59 age strata, whereas a 

decrease in mortality with spousal smoking is seen in the 70 and older stratum. Given that the latter stratum 

includes less than 1% of the cohort and very few deaths, its rates are too unstable to justify much confidence. The 

dose-response pattern does become weaker with ascending age strata, however, which has led to conclusions of 

inconsistency with an ETS-lung cancer connection and presence of confounding. Hirayama has proposed that agerelated increases in spousal mortality, smoking cessation, and decreased time spent in husband's proximity during 

the followup period may account for the observed pattern (Hirayama, 1990a). The proximity effect seems 

questionable because retirement of older husbands would eliminate time spent away from the house at work, but the 

other arguments are plausible. Alternatively, older women recently married to smokers may be more likely to die 

from competing causes of death that increase with age before passive-smoke cancer develops. Remarriage, possibly 

to a spouse whose smoking habits differ from those of the former spouse, also would increase with age and could 

lead to misclassification of (former) exposure with a bias toward the null. (It is unfortunate that history of former 

spouses' smoking habits and recency of marriage apparently were not obtained in the baseline interview because if 

the information had been collected, the aforementioned problems could have been readily addressed.) Temporal 

trends in some risk modifiers, such as dietary factors, also could play a role. 

Confounding cannot be ruled out entirely in certain instances, but the underlying question that must be 

raised in this regard is the following: If the spousal smoking group contains a disproportionate number of 

individuals with risk-elevating factors such as poor diet, lack of exercise, low socioeconomic status, and 

occupational hazard exposure, and these factors are sufficient to produce an increase in lung cancer mortality 

relative to the spousal nonsmoking group, despite an absence of any real smoking effect, why does this multitude of 

risk factors result in elevations of established smoking-related diseases only and no substantial elevation of risk of 

other causes of mortality (except brain cancer, which encompasses relatively few deaths)? 

In considering the study's results in broader terms, Hirayama's findings are consistent with the hypothesis 

that exposure of nonsmoking women to passive smoke via spousal smoking increases risk of lung cancer. The 

observed association is statistically significant. In addition, the persistence of the association after stratification on 

numerous variables, the observation of a parallel association in nonsmoking husbands of smoking wives, the 

appearance of associations with other smoking-related diseases, the existence of a dose-response pattern in most 

analyses of strata containing adequate numbers, and the production of similar conclusions by either cohort or casecontrol approaches argues against attribution of results purely to chance or confounding. 

Possible inclusion of active smokers among "nonsmoking" spouses of smokers through misclassification 

bias or differential change in smoking status during followup remains the study's greatest weakness. This problem 

could have been addressed by followup interviews or questionnaires coupled with verification of smoking status by 

alternative means in a subsample of the cohort, and still could be. In addition, losses to followup and failure to use 

more sophisticated survival analysis techniques are weaknesses that probably reduced the study's power. 

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Overall, the Hirayama study provides supportive, although not definitive, evidence that ETS exposure 

increases lung cancer risk. 

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A.4.13. HOLE(Coh) (Tier 1) 

This prospective cohort study was undertaken in the towns of Paisley and Renfrew, Scotland. The primary 

objective was to explore the relationship between passive smoking and cardiorespiratory symptoms and mortality, 

including lung cancer. The towns were selected because they are situated in an area with a high incidence of lung 

cancer. All persons residing in these towns between 45 and 64 years of age, inclusive, were visited between 1972 

and 1976. Each person was asked to complete a self-administered questionnaire and to visit a cardiorespiratory 

screening center where further interviews were conducted; 80% (15,399 persons) responded. 

Participating households in which at least two "apparently healthy" subjects lived were included in the 

study, yielding a study population of 3,960 males and 4,037 females. Data on smoking habits were obtained from 

the questionnaire and verified by interview at the screening visit. Mortality among subjects was traced using the 

Scottish National Health Service Central Register and General Register offices (for death certificate linkage), as 

well as the national cancer registry system. Results for followup through 1982 were published in 1984 (Gillis et al., 

1984). The primary results reported here are for followup through 1985, published in 1989 (Hole et al., 1989). In 

addition, the results of unpublished data extending followup through December of 1988 are reported (personal 

communication from Hole to A.J. Wells). 

Smoking habits were divided into three categories: persons who have never smoked, former smokers, and 

current smokers. In addition, the number of cigarettes smoked per day was obtained for current smokers. Both pipe 

and cigar smokers were excluded from the group who had never smoked. Never-smokers with former or current 

smokers as cohabitants in their household were classified as passive smokers; otherwise never-smokers were 

classified as "controls." This classification yielded 1,538 passive smokers and 917 controls for both sexes 

combined. The corresponding numbers for females alone are 1,295 and 489. 

The number of lung cancer deaths among females occurring in the cohort during the followup period is 

only six, too small to yield much statistical precision. The unpublished data extending followup through 1988 

includes one additional female lung cancer death that occurred subsequent to 1985. The crude relative risk is 2.27 

(95% C.I. = 0.40, 12.7), which is in the direction of a positive association between ETS exposure and lung cancer. 

The extremely wide confidence interval is the result of the small number of cancer deaths being compared and 

indicates that the data could easily arise when the true value of the relative risk is much larger or smaller than the 

estimated value. After adjustment for age and social class, the relative risk is 1.99 (95% C.I. = 0.24, 16.72). Lung 

cancer incidence was somewhat higher than mortality (10 cases vs. 7 deaths), yielding an adjusted relative risk of 

1.39 (95% C.I. = 0.29, 6.61). The relative risks for adjusted mortality (5.30) and incidence (3.54) were higher in 

males than in females but were based on even fewer cases (four deaths, six incident cases). 

Although the observed association could easily occur by chance, it is a useful contribution to the pool of 

evidence on lung cancer and passive smoking. Consequently, it is worth noting that the observed associations are 

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not likely to be attributable to other factors, because they persisted after control not only for age and gender, but for 

social class, diastolic blood pressure, serum cholesterol, and body mass index. Thus, differences in lifestyle or 

environmental factors such as diet, housing, and employment between passive-smoking households and 

nonsmoking households is an unlikely source of the results. Specific adjustment for potential occupational 

exposures or radon were not carried out, but these variables would presumably co-vary with social class to a great 

extent. 

As for other sources of bias, interviewer bias can be discounted because subjects were "apparently healthy" 

at interview and supplied smoking information before cardiovascular screening, and the investigators did not begin 

determining the passive smoking status of subjects until 1983 (for the first published study on this cohort). The 

extent of loss to followup is not specified, so one cannot tell whether this was a potential source of problems. 

However, linkage was carried out through two registries for general mortality and an additional registry specifically 

designed for cancers. Diagnoses of cancer mortality from death certificates were checked against cancer registry 

records for verification, thus reducing potential inaccuracies attendant on use of death certificates. 

Some data regarding misclassification were collected in an additional questionnaire administered to a 

portion of the cohort at some unspecified point in the study. Among controls, 5% said that their household 

contained a smoker--presumably someone who had not met the inclusion criteria (e.g., age 45 to 64) for the study. 

Thus, a small portion of the control group was actually currently exposed, which would produce a slight bias toward 

the null. Differential misclassification of smokers as never-smokers resulting from concordance of smoking habits 

among cohabitants cannot be assessed or ruled out, despite the authors' suggestion that persons cohabitating with 

smokers may be more likely to falsely claim to be smokers themselves, providing a bias toward the null. 

In summary, this study appears well designed and executed, but the number of ETS- exposed subjects is 

small. Although the study carries little statistical weight, there are no apparent methodological problems that would 

limit its usefulness otherwise. 

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A.4.14. HUMB (Tier 2) 

A.4.14.1. Author's Abstract 

"As part of a population-based case-control study of lung cancer in New Mexico, we have collected data 

on spouses' tobacco-smoking habits and on-the-job exposure to asbestos. The present analyses include 609 cases 

and 781 controls with known passive and personal smoking status, of whom 28 were lifelong nonsmokers with lung 

cancer. While no effect of spouse cigarette smoking was found among current or former smokers, never smokers 

married to smokers had about a twofold increased risk of lung cancer. Lung cancer risk in never-smokers also 

increased with duration of exposure to a smoking spouse, but not with increasing number of cigarettes smoked per 

day by the spouse. Our findings are consistent with previous reports of elevated risk for lung cancer among neversmokers living with a spouse who smokes cigarettes." 

A.4.14.2. Study Description 

This population-based case-control study was conducted through the New Mexico Tumor Registry during 

1980-84. The original purpose was to explain differing lung cancer occurrence in Hispanic and non-Hispanic 

whites in New Mexico. The study questionnaire included questions on spousal smoking and on indirect exposure to 

asbestos through a spouse's job. The current report describes the risks associated with those exposures in smokers 

and nonsmokers. The data on ETS exposure in nonsmokers is extracted from the larger study containing smokers. 

For the whole study, a total of 724 eligible primary lung cancer patients were identified, of which 641 were 

interviewed (89%). About one-half (48%) of the case interviews were conducted with the subject. Information on 

the remaining subjects was obtained from surrogates, generally the surviving spouse or a child. Cases were 

collected in two series, the first consisting of patients with cancer incident in 1980-82. That group includes all cases 

less than 50 years of age and all Hispanics, but not those exclusively. The number of cases was supplemented by a 

second series of patients with cancer incident to a 1-year period beginning November 1983. Most of the controls 

were selected by random telephone sampling, but some older subjects were randomly selected from Medicare 

participants. The control group was frequency-matched to the cases for sex, ethnicity, and 10-year age category, at 

a ratio of approximately 1.2 controls per case. Interviews were held for 784 of the 944 eligible controls, with 98% 

of the responses from subjects. 

The term "never-smoker" means not a cigarette smoker, where the latter is defined to be someone who has 

smoked for at least 6 months. The smoker classification is divided further into current smokers and ex-smokers. 

The current smoker status includes smokers who have stopped within 18 months before the interview; the exsmoker status applies if smoking ceased more than 18 months before the interview. Assuming that the minimum 6-

month duration of smoking is intended to apply to current and ex-smokers, never-smokers could have smoked 

previously for up to 6 months. 

An ETS-exposed subject is one ever-married to a spouse who smoked cigarettes, regardless of the spouse's 

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use of pipes or cigars. No information was obtained on exposure to ETS from other sources, such as from other 

household smokers, in the workplace, or from parental smoking during childhood. Measures of ETS exposure from 

spousal smoking include duration of exposure (in years) and the average number of cigarettes smoked per day by 

the spouse. The ETS subjects (never-smokers) include 20 (4) female (male) cases and 162 (130) controls (the 

article reports 8 male cases, the number used in much of the analyses, but 4 of those 8 were found to be smokers, 

personal communication from Humble). The age distribution for the female cases (controls) is as follows: age less 

than 65, 5 (74); age 65 or more, 15 (88). 

The odds ratio for the crude data on female never-smokers is 1.8 (90% C.I. = 0.6, 5.4) for spousal smoking 

of cigarettes only and 2.3 (90% C.I. = 0.9, 6.6) when spousal smoking also includes use of pipes and cigars. Based 

on mean cigarettes per day smoked by the spouse, the odds ratio of 1.2 at more than 20 cigarettes per day is 

somewhat lower than the odds ratio of 1.8 at the lower rate, fewer than 20 cigarettes per day. For duration of 

exposure, the odds ratio increases from 1.6 at less than 27 years to 2.1 at 27 or more years. It is reported that 

adjustment for age and ethnicity did not alter these results from the crude analysis. A trend test is included for 

duration of spousal smoking, but the sample sizes are too small to be meaningful. Application of logistic regression 

to adjust for variables gives values very close to the odds ratios for the crude analyses shown above for spousal 

smoking, for use of cigarettes only and also for combined use of cigarettes, cigars, and pipes. 

The distribution of cases by cell type is given, but only with males and females combined. The ratios of 

ETS-exposed cases to the total, by cell type, are as follows: squamous cell (2/4), small cell (1/1), adenocarcinoma 

(either 6/12, 7/12, or 8/12), and others (either 3/3, 2/3, or 1/3, depending on correct ratio for adenocarcinoma). 

The authors conclude that the results indicate increased risk from ETS exposure in never-smokers but not 

in active smokers. 

A.4.14.3. Comments 

This study evaluates smokers as well as nonsmokers for increased risk of lung cancer from spousal 

smoking. Not surprisingly, the number of smokers among the cases far outweighs the number of nonsmokers. No 

evidence of added risk to smokers from passive smoking is found. Such an evaluation, however, puts a great deal 

of faith in the exposure data and the power of statistical methods to detect what may be only a marginal increase in 

risk from ETS on top of active smoking. 

Of more central concern to this review is the assessment of lung cancer from ETS exposure in neversmokers. The ETS data are taken from a larger study, so the matching no longer applies, although the adjustment for 

those variables (ethnicity and age category) in the analysis is worthwhile. The article suggests that the high rate of 

proxy response for cases in the original study (52%) may be due, at least in part, to inclusion of decedent cases. 

That topic is not explicitly addressed, however, and controls were not matched to cases on vital status. 

Never-smokers apparently may have a history of smoking, provided it is of less than 6 months' duration. Whether 

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any never-smokers actually have a short smoking history is not discussed, but the never-smoker classification is less 

strict than in most studies. 

The data are evaluated in a number of different ways, consistently yielding an increased odds ratio. The 

number of cases, however, is too small (15 exposed, 5 unexposed) for the observed odds ratio to achieve statistical 

significance. Similar values of the odds ratios might be observed in a larger study, but, of course, that cannot be 

assumed. The study outcome is consistent with an association between ETS exposure and lung cancer occurrence. 

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A.4.15. INOU (Tier 4)

A.4.15.1. Author's Abstract

(Note: No abstract was provided; the following was paraphrased from author's discussion.) 

A case-control study on smoking and lung cancer in women was conducted in Kamakura and Miura, both 

in Kanagawa prefecture, Japan. The two cities are distinctly different in social environment; the former is a 

residential community and the latter is a fishing village. After stratification on city and age groups, the odds ratio of 

lung cancer in nonsmoking wives was shown to be 1.58 when husbands smoked fewer than 19 cigarettes a day and 

3.09 when husbands smoked 20 or more cigarettes a day. For comparison, the odds ratio for active smoking is 5.50. 

Although the study size is quite small, it provides additional evidence favoring the passive smoking and lung 

cancer hypothesis. 

A.4.15.2. Study Description 

This study was conducted to assess the roles of active and passive smoking in the etiology of lung cancer 

in women. It is unclear how subjects or diagnoses were obtained, but cases are women who died of lung cancer in 

Kamakura or Miura in the time periods 1980-83 and 1973-81, respectively. Controls, consisting of women who 

died of cerebrovascular disease during the same timeframes, are individually matched to cases on year of birth, year 

of death (" 2.5 years), and district of residence. It is not clear whether incident cases were used. 

Face-to-face interviews were conducted by public health nurses and midwives. ETS subjects consist of the 

28 nonsmoking cases and 62 nonsmoking controls remaining after elimination of 9 cases and 12 controls who were 

smokers. Husband's smoking status was not available for unspecified reasons in a total of 8 cases and 20 controls, 

but these figures include smokers as well as nonsmokers. The exact number of nonsmokers for which spousal 

smoking status was available is not specified but can be back-calculated from what is given (see below). No 

information is given on the number of proxy respondents, the age distribution of the subjects, or attempts to confirm 

diagnoses of primary lung cancer. 

The term "nonsmoker" is not defined, so it is not clear whether it refers to persons who never smoked or 

who do not smoke at present. Nonsmoking women whose husbands smoke at least five cigarettes per day are 

classified as exposed to passive smoking. Considerations of former smoking or marital status, ETS exposure at the 

workplace or in childhood, and duration of exposure are not addressed. No attempts to verify the reliability or 

validity of the data are mentioned. 

The number of subjects is not delineated by case versus control and exposed versus unexposed figures. 

They can be determined from the odds ratio and confidence interval, however, as 18 of 22 (exposed over total) 

cases and 30 of 47 controls. For nonsmoking women with smoking husbands, the crude odds ratio calculated by the 

reviewers is 2.55 (95% C.I. = 0.74, 8.78). (Note: OR = 2.25 is erroneously reported in the article. The OR value of 

2.55 has been confirmed by Hirayama.) When husbands' smoking is divided into two strata (< 19 cig./day and 20+ 

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cig./day), the odds ratios increase with exposure from 1.16 to 3.35, giving a statistically significant trend (p < 0.05). 

Age-adjusted odds ratios of 1.39 and 3.16 are reported for the two strata; adjustment for both age and district yields 

corresponding odds ratios of 1.58 and 3.09. (Note: The first OR value, 1.58, is incorrectly reported in the article as 

2.58. The value 1.58 has been confirmed by Hirayama.) The authors conclude that, although the study size is quite 

small, the results provide more evidence favoring the hypothesis that passive smoking causes lung cancer. 

A.4.15.3. Comments 

The number of subjects remaining after active smoking and missing data exclusions is small, guaranteeing 

poor power and lack of statistical significance in the absence of large odds ratios. The details on study design are 

limited. The source of cases and controls is not mentioned, for example, and it is unclear whether incident or 

prevalent cases were used. 

Information regarding quality control and related concerns is equally sparse. Interviewers used 

standardized questionnaires, which would help to promote consistency, but no mention is made of blinding them to 

subject background or study question, the absence of which could introduce interviewer bias (probably in a positive 

direction). Because cases and controls are stated to have died during the study period, it is probable that proxy 

respondents were required, but the extent is unknown. In addition, neither duration of ETS exposure from spousal 

smoking nor exposure from other sources, such as other cohabitants, was considered. The resultant inaccuracy of 

exposure assessment probably biases the results toward the null. Lack of information on former smoking status or 

verification of diagnosis may introduce biases of indeterminate direction. Except insofar as the district acts as a 

surrogate for factors related to socioeconomic status, no risk modifiers other than age or district of residence were 

considered. The meaning of "nonsmoker" is not given, so treatment of smoking history is unknown, and it is 

unclear whether the accurate and meaningful segregation of never-smoking subjects needed for effective analysis 

was accomplished. 

Although a substantial odds ratio was observed for husband's smoking, these results are based on a small 

sample with too few details provided to assess adequately the study's design and execution and its bearing on the 

evidence, particularly with regard to potential sources of bias. The statistical uncertainty of the odds ratios given is 

reflected in the extremely wide confidence intervals shown. The test for trend does not add any additional 

information. It is basically a restatement of the significant comparison between the heavily exposed group (husband 

smokes > 20 cig./day) and the unexposed group. Unfortunately, the brevity of the description of this study in the 

source available severely limits its utility. 

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A.4.16. JANE (Tier 2) 

A.4.16.1. Author's Abstract 

"The relation between passive smoking and lung cancer is of great public health importance. 

Some previous studies have suggested that exposure to environmental tobacco smoke in the household 

can cause lung cancer, but others have found no effect. Smoking by the spouse has been the most 

commonly used measure of this exposure. 

In order to determine whether lung cancer is associated with exposure to tobacco smoke within 

the household, we conducted a population-based case-control study of 191 patients with histologically 

confirmed primary lung cancer who had never smoked and an equal number of persons without lung 

cancer who had never smoked. Lifetime residential histories including information on exposure to 

environmental tobacco smoke were compiled and analyzed. Exposure was measured in terms of `smokeryears,' determined by multiplying the number of years in each residence by the number of smokers in the 

household." 

A.4.16.2. Study Description 

This study was undertaken in New York State to clarify the role of exposure to tobacco smoke in 

the household as a possible cause of lung cancer among nonsmokers. Interviews were conducted with 

former smokers as well as never-smokers initially (Varela, 1987), but because matching was carried out 

on smoking status, only never-smoking case-control pairs were included in the analyses for this article. 

The study includes both males and females, which are combined in all of the analyses. There are 146 (45) 

female (male) pairs. 

Cases are never-smokers aged 20 to 80 years newly diagnosed with lung cancer at 125 referral 

centers in New York from July 1, 1982, to December 31, 1984. Controls are cumulatively sampled 

never-smokers identified from files of the New York Department of Motor Vehicles. Controls are 

individually matched to cases on age (" 5 years), gender, and residence. In addition, the same interview 

type (proxy or direct) was used for controls as for their corresponding cases. Exposure data were 

collected face-to-face via standardized questionnaire, and interviewers were apparently uninformed of the 

subject's diagnosis. 

From the 439 case-control pairs interviewed, 242 pairs containing former smokers and 6 pairs 

with a mismatch on the source of response were excluded. Of the remaining 191 pairs used in the ETS 

study, interviews were conducted directly with the subjects in 129 pairs (68%) and with proxies in 62 

pairs (32%) (if a proxy was interviewed for a case, then a proxy was used for the matching control as 

well). No demographic comparisons were provided for the ETS cases and controls. For the whole study 

including smokers, the mean age of cases and controls is nearly identical (67.0 and 68.1, respectively; 

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Varela, 1987). Histological verification of diagnosis was obtained for all but five cases (for whom only 

clinical information was available) out of the initial population of 439. 

Persons smoking no more than 100 cigarettes over the course of their lifetime qualified as neversmokers for this study. Cigar or pipe smoking was apparently not considered. Exposure to ETS was 

deemed to occur when a smoker lived in the subject's household at any time from infancy to adulthood. 

Both total household smoke exposure and spousal smoke exposure were determined. Preadult (before 21 

years of age) and adult exposure were examined separately. Exposures were computed in units of 

"smoker-years," the total number of years lived with each smoker summed over smokers. In addition, 

pack-years were calculated for spousal smoking. Workplace exposure also was estimated by smokeryears, whereas exposure in social settings was estimated subjectively on a scale from 1 to 12 for each 

decade of life and summed. Exposure data were not checked, and marital status was not considered in the 

analyses. No information on tumor type or location was provided for the never-smoking population. 

Preadult exposure to 24 or more smoker-years occurred in 52 (29) cases (controls), whereas 82 

(94) were exposed to 1 to 24 smoker-years and 57 (68) were unexposed. Odds ratios were calculated 

using matched-pairs regression analysis. Preadult passive smoking yielded increasing odds ratio of 1.09 

(95% C.I. = 0.68, 1.73) for 1 to 24 smoker-years and 2.07 (1.16, 3.68) for 25 or more smoker-years. The 

odds ratios for adult exposure are low but also increase--from 0.64 (0.34, 1.21) at 1 to 24 smoker-years to 

1.11 (0.56, 2.20) at 75 or more smoker years. The odds ratios for lifetime exposure increase from 0.78 

(0.36, 1.67) at 1 to 24 smoker-years to 1.80 (0.83, 3.90) at 25 to 99 smoker-years and then dip to 1.13 

(0.56, 2.28) at 100 or more smoker-years. Spousal smoking was not significantly associated with lung 

cancer. In fact, when results were stratified by type of interview, proxy interviews yielded strong and, in 

some instances, statistically significant negative associations for spousal smoking, with odds ratios 

between 0.20 and 0.68 for ETS expressed in terms of present or absent, smoker-years, and pack-years of 

exposure. The odds ratios for direct interviews, in contrast, range from 0.71 to 1.10 and are uniformly 

higher than the odds ratios for corresponding proxy responses. Workplace exposure to 150 or more 

person-years yielded an odds ratio of 0.91 (0.80, 1.04), whereas a social setting exposure score of 20 led 

to a statistically significant decreased odds ratio of 0.59 (0.43, 0.81). 

The authors conclude that they found a significant adverse effect of relatively high levels of 

exposure to ETS during early life (before age 21). For those who were exposed to 25 or more smokeryears in their first two decades of life, the risk of lung cancer doubled. By contrast, the authors found no 

adverse effect of exposure to ETS during adulthood, including exposure to a spouse who smoked. This 

lends further support to the observation that passive smoking may increase the risk of subsequent lung 

cancer, and it suggests that it may be particularly important to protect children and adolescents from this 

environmental hazard. 

A-77
A.4.16.3. Comments 

The number of never-smoking cases is relatively large, resulting in above-average statistical 

power for evaluation of ETS effects. Controls were matched to cases on smoking status, as well as the 

key demographic factors of age, gender, and neighborhood. Comparability of cases and controls was 

likely good, as evidenced by the similar mean ages for the total population, although no other 

comparative information is available. In view of the use of population-based, basically healthy controls, 

it is questionable that any attempted diagnostic blinding would be effective. The study's matching on 

smoking status with subsequent retention of matching and use of matched-pairs analysis for ETS 

exposure effectively eliminates potential effects on risk attributable to age, gender, or residence, and it 

makes bias by related factors (such as socioeconomic status) less likely. A rare feature is the use of 

matching on interview type (i.e., proxy or subject direct) to control for bias due to this source. 

Comparison of spousal smoking results for direct and proxy interviews, however, indicates consistently 

lower estimated risks from proxies. This suggests that use of proxy respondents did not merely lead to 

increased random misclassification but might have biased the outcome toward a negative association. 

The authors posit that proxies of lung cancer patients may be more likely to underreport exposure than 

those of control subjects. Curiously, however, although the authors report that odds ratios "frequently 

differed according to type of interview," they do not specify how the odds ratios differed for exposure 

other than spousal smoking. Also, the composition of the proxy groups--relative proportions of spouses, 

other relatives, and friends or associates--is never discussed, leaving unexplored the possibility that 

misreporting by spouses of cases may lie at the heart of the observed discrepancy. It is also interesting 

that the outcome of self-responses versus proxy responses in this study is in the opposite direction of the 

findings in GARF. Diagnostic misclassification is unlikely, given the histological verification of nearly 

all cases. 

The restriction of subjects to persons smoking no more than 100 cigarettes in their lifetime 

theoretically eliminates active smoking as a source of bias, although no verification of smoking status was 

undertaken. Consideration of potential sources of ETS exposure is commendably thorough, and the 

calculation of total years of living with smokers, regardless of relation to the smoker, as an index of 

household smoke exposure minimizes the possibility that any source (e.g., roommates) is overlooked. In 

contrast, the index of exposure in social settings is highly subjective, and persons more habituated to 

passive smoke may report a given exposure as less severe than persons less accustomed to smoke, thus 

creating a negative bias. The proportion of controls classified as exposed to ETS is 80%, which is high in 

comparison with other studies. This suggests that some exposed controls may have only minor exposure 

to ETS, making detection of an association (if present) less likely. Unlike almost every other ETS study, 

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males and females are combined in the analysis and only the joint results are reported. Because there are 

45 (146) pairs of males (females), the sample sizes are sufficient to warrant reporting odds ratios 

separately by sex and to test the hypothesis of no difference due to gender. 

Lung cancer odds ratios for adulthood, lifetime, and spousal smoking are consistently well below 

1 for low ETS exposure relative to nonexposure, as if exposure had a protective effect. Thereafter, 

however, the odds ratios associated with increasing levels of exposure are suggestive of an upward trend 

in response. Although we would not dismiss the occurrence of this outcome as attributable to chance 

alone, it is consistent with the baseline lung cancer mortality rate in the control population simply being 

higher than that of the case population for reasons other than exposure to spousal smoking. A pervasive 

(systematic) negative bias linked with exposure could also produce such an effect. Both of these 

contingencies are necessarily speculative because there is no evidence in the article to support either, 

aside from the outcome of the data analysis. Further fueling the speculation, however, are the markedly 

lower odds ratios obtained from surrogate responses, indicative of some source of bias acting unequally 

on proxy and nonproxy sources. Also speculative is the idea that using predicted responses from a model 

that fits the data poorly might produce such an effect, but that level of detail is beyond the scope of most 

published articles, including this one. Some discussion of these issues by the authors, as well as 

separation of the analyses by sex, would enhance interpretation of results and facilitate their comparison 

with results of other studies on females. 

The authors' finding that exposure during childhood and adolescence appears to influence 

subsequent lung cancer risk more than exposure during adulthood raises some interesting possibilities. 

More time may be spent in proximity to a household smoker (particularly the mother), on average, in 

childhood than in adulthood. According to data presented by K.M. Cummings (Roswell Park Memorial 

Institute, Buffalo, New York) at the Science Advisory Board meeting on EPA's draft ETS report (U.S. 

EPA, 1990), on December 4-5, 1990, heavy childhood exposure is a better surrogate for total lifetime 

exposure than is spousal exposure. Also, early exposure may appear to become a risk, either due to a 

long latency period for lung cancer or, perhaps, due to increased susceptibility at an earlier age. The 

results suggesting an effect from early exposure but not from spousal smoking are more nearly atypical 

than reinforced by other studies, though, and the number of exposure sources considered raises the 

possibility that the strength of association seen for preadult exposure may be due to chance. However, 

after elimination of 78 pairs with incomplete marriage or household exposure data, the association 

persisted and was strengthened (OR = 2.59), arguing against chance as the major influence. It is unclear 

what role, if any, negative bias due to proxy respondents may have had in the nonspousal analyses. 

In summary, the findings for preadult exposure are not readily attributable to chance or 

confounding, although some role of interviewer bias or other factors such as diet cannot be ruled out. No 

A-79
association with lung cancer incidence is observed for spousal smoking. The authors conclude, however, 

that, spousal smoking aside, other sources of household ETS exposure support the conclusion that 

exposure to ETS can cause cancer. That conclusion is not unequivocal in our view. In general, the odds 

ratios (aside from preadulthood exposure) tend to be low but trend upward with exposure, exhibiting 

more of a patterned response than one might expect to see due to randomness. This is puzzling because 

there is no apparent source of bias and the study appears to have been conducted with considerable 

forethought and thoroughness. The only exception noted is the lack of separate analyses and comparisons 

of males and females. These concerns notwithstanding, the study is a useful addition to the literature on 

ETS exposure and lung cancer. 

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A.4.17. KABA (Tier 2) 

A.4.17.1. Author's Abstract 

"Among 2,668 patients with newly diagnosed lung cancer interviewed between 1971 and 1980, 134 cases 

occurred in `validated' nonsmokers. The proportion of nonsmokers among all cases was 1.9% (37 of 1,919) for men 

and 13.0% (97 of 749) for women, giving a sex ratio of 1:2.6. Kreyberg Type II (mainly adenocarcinoma) was 

more common among nonsmoking cases, especially women, than among all lung cancer cases. Comparison of 

cases with equal numbers of age-, sex-, race-, and hospital-matched nonsmoking controls showed no differences by 

religion, proportion of foreign-born, marital status, residence (urban/rural), alcohol consumption, or Quetelet's 

index. Male cases tended to have higher proportions of professionals and to be more educated than controls. No 

differences in occupation or occupational exposure were seen in men. Among women, cases were more likely than 

controls to have worked in a textile-related job (RR = 3.10, 95% C.I. = 1.11, 8.64), but significance of this finding is 

not clear. Preliminary data on exposure to passive inhalation of tobacco smoke, available for a subset of cases and 

controls, showed no differences except for more frequent exposure among male cases than controls to sidestream 

tobacco smoke at work. The need for more complete information on exposure to secondhand tobacco smoke is 

discussed." 

A.4.17.2. Study Description 

In 1969, the American Health Foundation began interviewing newly diagnosed lung cancer patients with 

cancer at sites potentially related to tobacco use for a case-control study (Wynder and Stellman, 1977) that is still 

ongoing. The current article considers the data on lung cancer in nonsmokers alone collected from newly diagnosed 

lung cancer patients between 1971 and 1980. Several factors are of interest: histology, demographic factors, 

residence, Quetelet's index, alcohol consumption, previous diseases, occupation and occupational exposures, and 

ETS exposure. The number of nonsmokers among the cases is small, so the authors consider the results to be 

preliminary. 

The study from which the data on lung cancers in nonsmokers are extracted is a very large effort that 

includes tobacco-related cancers at multiple organ sites and includes smokers as well as nonsmokers. The cases are 

from approximately 20 hospitals in 8 U.S. cities (about one-third from New York City). With reference to the lung 

cancer cases in that study, histologic type of lung cancer was determined from pathology reports and discharge 

summaries. Secondary lung cancer cases were excluded. Controls consist of hospital patients with diseases 

unrelated to tobacco use who were pair-matched with cases on hospital, age (within 5 years), sex, race (with five 

exceptions), date of interview (within 2 years), and nonsmoking status. Cases appear to be incident, and control 

sampling is density. All subjects were interviewed while they were in the hospital. The questionnaire for the 

interviews was expanded in 1976. Questions on exposure to ETS were not included, however, until an addendum to 

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the questionnaire in 1978, which was then modified in 1979. 

The term "nonsmoker" applies to subjects who have smoked fewer than one cigarette, pipe, or cigar per 

day for a year. The term "never-smoker" is used interchangeably. Independent of the intended definition, however, 

subjects whose hospital charts indicated any record of smoking, even in the remote past, were excluded from the 

nonsmoker classification. ETS subjects include 53 (25) females (males), after combined attrition of 22 (9 without 

primary lung cancer and 13 with a record of smoking). The age distribution of the female cases (controls) is as 

follows: age less than 50, 12 (15); age 50 to 59, 26 (24); age 60 to 69, 29 (34); age 70 or more, 30 (24). Histologic 

data on lung cancer type are given for female cases: squamous cell (16), adenocarcinoma (60), alveolar (12), large 

cell (4), and unspecified (5). The authors report that exposed cases did not differ from the unexposed cases in the 

distribution of histologic type. 

A person is "ETS exposed" (1) at home, if currently exposed on a regular basis to family members who 

smoke, (2) at work, if currently exposed on a regular basis to tobacco smoke at work, and (3) to spousal smoke, if 

the spouse smokes. There are data on 53 cases and their controls for exposure at home and at work, but data on 

only 24 cases and 25 controls for spousal smoking. This is because of the change in the questionnaire from 1978 to 

1979 and because spousal smoking was only applicable for women currently married. Because nonsmoking status 

was a variable for matching, the 53 pairs of cases and controls for analysis of exposure at home or at work are 

matched; the data for spousal smoking, however, are technically not matched. There is no indication at all of an 

association between ETS exposure and lung cancer for women from exposure at home, at work, or from spousal 

smoking. For ETS exposure at home, there are 16 of 53 (exposed/total) cases and 17 of 53 controls; for exposure at 

work, the figures are 26 of 53 cases and 31 of 53 controls; and for spousal smoking, the data are 13 of 24 cases and 

15 of 25 controls. No statistical calculations are provided for females. From our calculations, the odds ratio for 

spousal smoking is 0.79 (95% C.I. = 0.25, 2.45). (Among male subjects, exposure to ETS in the workplace was 

slightly significant, p = 0.05, as reported in the article.) For other potential risk factors for lung cancer in women 

other than passive smoking, it was found that cases were more likely than controls to have worked in a textilerelated job (OR = 3.1; 95% C.I. = 1.1, 8.6), but the significance of the finding was not clear. It also was found that 

more female cases had a history of pneumonia compared with controls, but no interpretation could be attached to 

the observation. 

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A.4.17.3. Addendum 

Unpublished preliminary results of a study of ETS and lung cancer in never-smokers conducted at the 

American Health Foundation have been reported at two meetings--The American Public Health Association 

(APHA) 119th Annual Meeting, Atlanta, Georgia, November 10-14, 1991, and The Toxicology Forum, 1990 

Annual Winter Meeting, Washington, D.C., February 19-21, 1990. A completed report for our review was not 

available at the cutoff date for inclusion in this document (personal communication with the first author, Dr. G.C. 

Kabat). Enclosed below is the abstract for the APHA meeting. 

RISK FACTORS FOR LUNG CANCER IN LIFETIME NONSMOKERS 

Geoffrey C. Kabat, Ernst L. Wynder 

Risk factors for lung cancer in lifetime nonsmokers (NS) were assessed in a hospital-based case-control 

study carried out between 1983 and 1990. The study population consisted of 41 male and 69 female NS 

cases and 117 male and 187 female NS controls matched on age, race, hospital, and date of interview. 

Evidence of an effect of exposure to ETS was inconsistent. In males, there was no difference between 

cases and controls in reported exposure to ETS (yes/no) in childhood, in nonsignificant association with 

exposure in childhood (OR = 1.6, 95% C.I. = 0.9, 2.8), but no association with exposure in adulthood at 

home or at work. Male cases were somewhat more likely to have a smoking spouse (OR = 1.6, 95% C.I. = 

0.7, 3.9), whereas there was no difference in females. Cases and controls did not differ in reporting a 

history of previous respiratory diseases. Female cases were more likely to report a history of radiation 

treatment (OR = 4.3, 95% C.I. = 1.5, 12.3). In females, but not in males, a significant inverse association 

was observed between body mass index (based on self-reported weight 5 years prior to diagnosis) and lung 

cancer risk. 

A.4.17.4. Comments 

Although the study contains more than 2,600 patients, only a small number of nonsmokers are available 

because questions about ETS exposure were not included in the interview until 1978 and the questions were 

changed in 1979. It is not known just how the questionnaire was changed, although the general tenor of the article 

suggests care in study planning and execution. The design for the larger study from which the ETS data are taken is 

pair-matched on numerous factors of potential interest, including "nonsmoking status," which contributes favorably 

to the analysis of ETS data alone. Cases with secondary tumors were excluded, histological type was considered, 

and all subjects were personally interviewed. It appears that only the currently married females were included in the 

question regarding exposure to spousal smoke, which alleviates the need to make some approximating assumptions 

regarding exposure of widows, single females, and so forth. 

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Two areas that may need to be addressed in the analysis of ETS subjects have to do with the definition of 

"ETS exposure" and "nonsmoker." The duration of smoking was comparable in cases and controls, but interview 

questions regarding exposure to ETS refer only to current exposure (this is not explicit in the article but was 

confirmed by the first author). Any effect from reliance on current exposure alone should be a bias toward the null 

hypothesis. Also, a measure of exposure in units (e.g., number of cigarettes per day or pack-years smoked by 

spouse) would make the question less subjective and help to dichotomize on ETS exposure more sharply. Because 

lung cancer may have a latency period of 20 years or so, exposure in the past, both in terms of duration and 

intensity, should be more meaningful than current exposure alone. With regard to the definition of nonsmoker, the 

requirement is less rigid than is often imposed. Ever-smokers are included provided they did not smoke more than 

the equivalent of 1 cigarette per day for 1 year (about 18 packs). It is difficult to know, however, what constitutes a 

"negligible" level of past smoking. Any bias from former smoking should inflate the relative risk, but that outcome 

appears unlikely in this study (RR = 0.74). 

One of the factors of interest to the investigators is occupation, so cases and controls were not matched on 

that variable. For ETS exposure, occupation could be a confounding factor. Among females, the controls contain a 

higher percentage of professional and skilled workers than do the cases (47 to 25) and a lower percentage of 

housewives (41 to 50). Some differences are also apparent in religious preference between cases and controls that 

may bear some influence through lifestyle or dietary practices. Variables such as these may need to be taken into 

account in an adjusted analysis when more data become available. 

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A.4.18. KALA (Tier 1) 

A.4.18.1. Author's Abstract 

"A case-control study was undertaken in Athens to explore the role of passive smoking and diet in lung 

cancer, by histologic type, in nonsmoking women. Among 160 women with lung cancer admitted to one of seven 

major hospitals in Greater Athens between 1987 and 1989, 154 were interviewed in person; of those interviewed, 91 

were lifelong nonsmokers. Among 160 identified controls with fractures or other orthopedic conditions, 145 were 

interviewed in person; of those interviewed 120 were lifelong nonsmokers. Marriage of a nonsmoking woman to a 

smoker was associated with a relative risk for lung cancer of 2.1 (95% C.I. = 1.1, 4.1); number of cigarettes smoked 

daily by the husband and years of exposure to husband's smoking were positively, but not significantly, related to 

lung cancer risk. There was no evidence of any association with exposure to smoking of other household members, 

and the association with exposure to passive smoking at work was small and not statistically significant. Dietary 

data collected through a semiquantitative food-frequency questionnaire indicated that high consumption of fruits 

was inversely related to the risk of lung cancer (the relative risk between extreme quartiles was 0.27 (95% C.I. = 

0.10, 0.74). Neither vegetables nor any other food group had an additional protective effect; furthermore, the 

apparent protective effect of vegetables was not due to carotenoid vitamin A content and was only partly explained 

in terms of vitamin C. The associations of lung cancer risk with passive smoking and reduced fruit intake were 

independent. Passive smoking was associated with an increase of the risk of all histologic types of cancer, although 

the elevation was more modest for adenocarcinoma." 

A.4.18.2. Study Description 

This study was undertaken in Athens, Greece, in 1987-89. It sought to explore the role of passive smoking 

and diet in the causation of lung cancer in nonsmoking women. All data used in the study were collected 

specifically for that purpose. 

Cases are never-smoking women hospitalized in one of seven Greater Athens area hospitals during an 18-

month period of 1987-89 with a definite diagnosis of lung cancer from histologic, cytologic, or bronchoscopic 

exam. Controls were selected from female never-smoking patients in the orthopedic ward of the same seven 

hospitals and an orthopedic hospital. A control was interviewed within 1 week of a corresponding case, thus 

essentially density-sampled but otherwise unmatched. Cases were not specifically restricted to incident cancers. 

All subjects were interviewed face-to-face by one of five trained interviewers; interviews apparently were 

unblinded. A total of 160 lung cancer cases and an equal number of controls were initially identified; 6 cases and 

12 controls were too ill to interview, whereas 3 controls and no cases refused to participate. After exclusion of 

smokers, 91 cases and 120 controls remained. The age distributions of the cases and controls are very similar: for 

cases (controls), 16.5% (14.2%) were less than 50 years of age, 19.8 (18.3%) were 50 to 59, 29.7 (25.8%) were 60 

A-85
to 69, and 34.1 (41.7%) were 70 or older. Current residence, level of education, occupation (housewife vs. other) 

and marital status were also similarly distributed between cases and controls. Case diagnosis was established by 

histology (48%), cytology (38%), or bronchoscopy (14%), with exclusion of cancers diagnosed as secondary. 

Persons reportedly smoking fewer than 100 cigarettes in their lifetime are classified as nonsmokers. No 

mention is made of pipe or cigar smoking. Several different sources of ETS exposure are considered: husbands 

who smoke quantified in terms of years exposed and average number of cigarettes smoked per day; household 

members other than husbands who smoke, quantified by the sum of years exposed to each smoker; and coworkers 

who smoke, measured by the number of smokers sharing the "same closed space" as the subject. Presumably, 

childhood exposure is included in the household exposure assessment. For spousal smoking, single women are 

considered unexposed, whereas exposure of widowed or divorced women is based on the period when they were 

married. No attempts to verify exposure are mentioned. 

For analysis of husband's smoking based on cigarettes per day, 64 out of 90 (exposed/total) cases and 70 

out of 116 controls gives a crude odds ratio of 1.6 for 90 cases and 116 controls; 64 cases and 70 controls were 

exposed. The authors present results stratified by four exposure categories, which indicate no significant 

association (p = 0.16). Crude data for husband's smoking stratified by five levels of smoking duration (never, < 20, 

20-29, 30-39, and 40+ years) yield a marginally significant increase in association with increasing duration (p = 

0.07), with odds ratios of 1.0, 1.3, 1.3, 2.0, and 1.9, respectively. No statistically significant association was noted 

for ETS exposure from other household members (p = 0.60) or for exposure at work (p = 0.13), but the crude odds 

ratios for these exposures were 1.41 and 1.39, respectively. Stratification by level of intake for each of 16 food and 

nutrient groups yielded a significant negative (favorable) association with cereals (p = 0.04) and a possible 

association with fruits (p = 0.11). 

Multiple logistic regression was then used to adjust results for age, education, and interviewer. An 

adjusted relative risk estimate of 1.92 (95% C.I. = 1.02, 3.59) was obtained for marriage to a smoker. After 

adjustment, trends for estimated lung cancer risk showed an increase with duration of exposure (average 16% per 10 

years) and packs per day (6% per pack), but these were not statistically significant. No trend was observed for ETS 

in the household or workplace. Adjustment for other sources of air pollution had no effect on the analyses. 

Adjustment of dietary analyses for age, education, interviewer, and total energy intake indicated a significant 

decrease in estimated risk between highest and lowest quartiles of consumption of fruit (RR = 0.33; p = 0.02) and a 

nearly significant increase with consumption of retinol (RR = 1.31; p = 0.06), whereas beta carotene (RR = 1.01) 

and other dietary factors had no significant effect. Adding fruit consumption to the model for passive smoking 

increased the adjusted relative risk for husband's smoking slightly, from 1.92 to 2.11. Stratification by lung cancer 

cell type yielded somewhat lower adjusted estimated relative risks for adenocarcinoma (2.04) than for squamous, 

small, and large cell cancer combined (2.58). No adjusted results were presented for other household or workplace 

exposure. 

A-86
The authors' conclusion is best reflected in their abstract (shown in full above). Marriage of a nonsmoking 

woman to a smoker was associated with a relative risk for lung cancer of 2.1. Number of cigarettes smoked daily by 

the husband and years of exposure to husband's smoking were positively, but not significantly, related to lung 

cancer risk. There was no evidence of any association with exposure to smoking of other household members, and 

the association with exposure to passive smoking at work was small and not statistically significant. Dietary data 

indicated that high consumption of fruits was inversely related to the risk of lung cancer. Neither vegetables nor 

any other food group had an additional protective effect. The associations of lung cancer risk with passive smoking 

and reduced fruit intake were independent. Passive smoking was associated with an increase of the risk of all 

histologic types of cancer, although the elevation was more modest for adenocarcinoma. 

It is noted that these findings are compatible with the relatively low incidence of lung cancer in the Greek 

population--a population with the highest per capita tobacco consumption in the world, but with a very high fruit 

consumption as well. 

A.4.18.3. Comments 

This study was generally well designed and executed. Set up specifically to address passive smoking and 

diet as etiological factors in lung cancer, it includes sufficient numbers of nonsmoking women to produce 

substantive results. Interviews were face-to-face, and no proxies were used, enhancing accuracy and comparability 

of responses, whereas the very low rate of refusal minimizes potential bias due to volunteer selection. Cases and 

controls were very similar demographically, were drawn from most of the same hospitals, and were matched 

temporally on time of interview, so comparability seems high. Furthermore, the study hospitals' patient population 

accounts for the majority of lung cancer and trauma patients seen in the Athens area, enhancing generalizability of 

results. Most lung cancers were histologically or cytologically confirmed, reducing chances for misclassification of 

disease status. 

On the debit side, the apparently unblinded interviews could have been biased (although what can be 

accomplished toward that end is limited). Adjustment for interviewer in the analyses did not affect the results, 

however, and it is unlikely that all interviewers would share the same bias. Determination of what constitutes 

workplace exposure is vague, and childhood exposure is not clearly differentiated from adult household exposure; 

these were notably the passive smoking categories, which showed the least association with lung cancer. ETS 

exposure in the workplace is analyzed with regard to trend (Table 2), with levels of exposure represented by 

"housewife" (zero exposure), "minimal," and "some," resulting in a p value of 0.13. Perhaps correctly, the authors 

cautiously note the evidence that ETS exposure is associated with increased risk (referring to Table 2 in general, not 

just exposure at work) but indicate that the differences are not large enough to be interpretable without controlling 

for other factors. An analysis of exposed versus unexposed for the workplace may have been useful, especially an 

adjusted analysis. Our calculation of the crude odds ratio for a comparison of "minimal" and "some" exposure at 

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work is 1.7, which is suggestive. 

Methodological rigor and thoroughness are particularly evident in the treatment of other factors that may 

affect risk. Despite the demographic similarity of cases and controls, the key demographic variables of age and 

education were nevertheless controlled for in the analyses, along with interviewer identity. The potential effects of 

air pollution, total energy intake, and other dietary factors on lung cancer incidence were examined, and the impact 

of cancer type was evaluated. An association of husband's smoking with lung cancer yielding an odds ratio of 

around 2 persisted with adjustment for those factors. The authors claim to have taken special effort to exclude exsmokers from misclassification as never-smokers, taking account of this potential source of upward bias. No 

discussion was found, however, of what measures were taken to control misclassification of former smokers as 

never-smokers, beyond interviewing subjects about current and former smoking habits. 

In summary, this study presents evidence of a level- and duration-dependent association between husband's 

smoking and lung cancer in a well-defined and highly comparable group of Greek cases and controls. Positive but 

nonsignificant relationships with general home or workplace passive smoking were observed, and there are 

indications that additional analysis of workplace exposure may be worthwhile. No effect of air pollution was 

observed. With regard to dietary factors, the large number of potential factors considered raises the issue of 

multiple comparisons. Fruit consumption may be a significant factor, but further evidence is needed to firmly 

establish this, particularly in view of the number of dietary factors explored. Dietary factors, however, do not 

account for the results for ETS exposure in this study. The results regarding spousal smoking cannot be readily 

attributed to bias, and they provide good quantitative data on the issue of passive smoking and lung cancer. This 

well-conducted study makes a valuable contribution to the evidence on lung cancer and ETS exposure. 

A-88
A.4.19. KATA (No tier assignment is made on this study because the OR is undefined.) 

A.4.19.1. Author's Abstract 

"It is becoming noticeable in Japan that with increased incidence of lung cancer, there has been an increase 

in pulmonary carcinoma in women. Active smoking by women is increasing, while concern over passive smoking 

has been intensifying, and the effect of passive smoking on carcinogenesis has become a social problem. Regarding 

this effect, immunological and public health reports have appeared in Japan, but there have been few clinical 

reports, and detailed analysis of patients has been inadequate. Lung cancer presents a variegated histological 

picture, and presumably there are different carcinogenic factors for different histological types, although there have 

also been few reports on this subject. The effect of passive smoking probably varies depending on the regional 

environment and custom, and these factors should also be analyzed and included in the investigation. The present 

report describes our findings regarding the effects of smoking and familial aggregation of cancer in cases of 

pulmonary carcinoma in women." 

A.4.19.2. Study Description 

This study was undertaken in the Nara Prefecture, Japan, to investigate the effects of smoking and familial 

aggregation of cancer in cases of pulmonary carcinoma in women. Active smokers are included in the study, from 

which the nonsmokers are drawn for analysis. Matching is retained, however, in the nonsmokers. 

For the whole study, subjects were drawn from a hospital (presumably the Nara Prefecture Medical 

University Hospital) during an unspecified period of time. Cases are female patients with histologically diagnosed 

lung cancer; controls are female patients with "nonmalignant" disease, matched 2 to 1 with cases on age plus or 

minus 2 years. It is not clear if only incident cases were used and if controls were density sampled. Case diagnoses 

were obtained from histological exam results, whereas control diagnoses were presumably from medical charts. 

Other information was collected from apparently unblinded "questioning," with an unspecified degree of reliance on 

proxy responses from family members. 

A total of 25 cases and 50 controls are included in the study; no information on refusals is provided. 

Exclusion of active smokers leaves only 17 cases and, with retention of 1:1 matching, 17 controls. Mean ages for 

the total study population are 67.5 " 8.8 years (67.6 " 8.5 years) for cases (controls). The age distribution of ETS 

subjects is not discussed. Nonsmokers are defined by exclusion of "active smokers," with no delineation between 

former and current smokers. ETS exposure is defined as exposure to smoking more or less daily through living 

with a smoker. Three periods of ETS exposure are considered: current, past, and childhood, the last for those 

"exposed since early childhood." Clearly these types are not mutually exclusive, although current sources of 

exposure are omitted from the "past" exposure category, even if present for a long time. 

ETS exposure is quantified as cigarettes per day smoked times number of years. No mention is made of 

cigar or pipe smoking, nor of checks on exposure data. No distinction is made regarding marital status. Tumors 

A-89
occurring among current passive smokers were mostly adenocarcinomas (13/17), the remainder (4/17) being 

squamous or small cell cancers. Airway proximity was not specified. Excluding active smokers, all 17 cases were 

current passive smokers, compared with 14 out of 17 controls, for an odds ratio of 1.2, whereas past passive 

smoking characterized 16 of 17 cases and 17 of 17 controls, for an odds ratio of 0.9 (these odds ratios reflect the 

substitution of 0.5 for 0 in the exposure categories in which no subjects fall). Childhood passive smoking was 

reported in 13 of 15 cases and 7 of 15 controls (apparently all those for whom information was available), for an 

odds ratio of 7.4 (p < 0.1). None of the passive smoking odds ratios was statistically significant at the 5% level. No 

definite conclusion can be drawn from the present study, but there is a suggestion that passive smoking is associated 

with development of lung cancer in the Nara region. The effect of passive smoking that continued to the present 

time was especially marked, particularly in squamous cell carcinoma and small cell carcinoma. With 

adenocarcinoma, an effect of passive smoking in the past is suspected. Along with passive smoking, the association 

of some intrinsic factor (genetic tendency) to varying degrees in the different histologic types of lung cancer in 

women, especially in adenocarcinoma, is apparent. 

A.4.19.3. Comments 

The histological diagnosis of all cases, in combination with the apparent involvement of the researchers in 

the diagnoses, virtually eliminates the potential pitfall of misclassification of lung cancer cases. It also allows 

specific breakdowns by cell type. With regard to passive smoking, however, limitations related to exclusion of 

active smokers greatly reduced the study's potential. 

In their initial analyses, the authors investigate passive smoking without excluding or stratifying on active 

smoking and report statistically significant associations with lung cancer and combined effects with family history 

of cancer. This is not a meaningful analysis, because the effects of active and passive smoking cannot be separated 

and passive smoke exposure probably correlates strongly with extent of active smoking. Excluding active smokers 

greatly reduces the available numbers of matched subjects and, in combination with the very high exposure 

prevalence among qualifying controls, makes the differences between cases and controls highly unstable for all 

comparisons except for that of childhood exposure. Even here, with an estimated relative risk of 7.4, the results do 

not reach the 5% level of statistical significance, notwithstanding the problem of multiple comparisons. The authors 

also conduct cell-type-specific analyses, but these too fail to yield significant results. The extraordinarily high 

proportion of exposed present and past passive smoking controls is apparently a fluke, because the proportion is not 

as high in the total control subject population (or childhood passive smoking controls). Nevertheless, exposure was 

very common among controls. This indicates that the exposure criteria may be too lax or, alternatively, that the 

control population included a substantial proportion of persons with smoking-related diseases (controls being only 

stipulated not to have malignant disease). 

In light of the minimal utility of the study's passive smoking analyses, detailed consideration of design 

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strengths and weaknesses is unwarranted. Major points not already mentioned relate to information ascertainment 

and confounding. Interviews were apparently unblinded and, especially if conducted by the authors themselves, 

may thus have been biased toward uncovering exposure among cases (although the high prevalence of exposure 

among controls as well as cases argues against this). Furthermore, the extent of proxy interviews, potentially 

decreasing accuracy of exposure assessment, is unclear. 

All subjects are female and, although results are not age adjusted, matching on age was retained for all 

analyses. No other risk factors except family history of cancer were considered, probably due to limited subject 

numbers, because much information on other factors was collected. Moreover, family history was considered only 

in the nonmeaningful analyses, which did not differentiate active and passive smokers. Thus, although the problems 

with numbers and exposure misclassification probably reduced the study's ability to detect whether an association 

exists, information bias and confounding could have biased results either up or down. 

In summary, this study's data are consistent with an association of passive smoking, particularly childhood 

exposure, with lung cancer, but the results are too unstable and subject to potential bias to carry much weight, and 

the quantitative results must be viewed with extreme caution. 

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A.4.20. KOO (Tier 1) 

A.4.20.1. Author's Abstract 

"Lifetime exposures to environmental tobacco smoke from the home or workplace for 88 "never-smoked" 

female lung cancer patients and 137 "never-smoked" district controls were estimated in Hong Kong to assess the 

possible causal relationship of passive smoking to lung cancer risk. When relative risks based on the husband's 

smoking habits, or lifetime estimates of total years, total hours, mean hours/day, or total cigarettes/day, or earlier 

age of initial exposure, were combined with years of exposure, there were no apparent increases in relative risk. 

However, when the data were segregated by histological type and location of the primary tumor, it was seen that 

peripheral tumors in the middle or lower lobes (or less strongly, squamous or small cell tumors in the middle of 

lower lobes) had increasing relative risks that might indicate some association with passive smoking exposure." 

A.4.20.2. Study Description 

This study, the second of four from Hong Kong, is based on a secondary data set of reported female neversmokers. The parent study from which the data on ETS subjects were drawn includes ever-smokers in a matched 

case-control study of 200 cases and 200 controls (Koo et al., 1984; also see Koo et al., 1983). Its objective is to 

assess the role of passive smoking as a potential etiological factor in the high incidence rate of lung cancer among 

Chinese females in Hong Kong. The current article emphasizes the quantitation of lifetime ETS exposure and the 

histological profile of lung cancer in exposed never-smokers. 

In the parent study, cases are from the wards or outpatient departments of eight hospitals in Hong Kong 

during 1981-83. Controls are healthy subjects from the community, matched on age (within 5 years), district of 

residence, and type of housing (public or private). The cases are incident, and control sampling is density. Attrition 

due to selection or followup totals 26 (8 too ill to interview and 18 with secondary lung cancers), leaving 200 cases 

for interview. Face-to-face interviews of 1.5 to 2 hours were conducted directly with cases and controls. There was 

no restriction of cases by cell type of lung cancer. The ETS subjects extracted from the parent study include 88 

cases and 137 controls. Of the 88 cases, 83 were confirmed by histology and 5 were "confirmed malignant." The 

number of squamous cell and small cell cases combined is 32 (23 ETS exposed; 72%); the corresponding figure for 

adenocarcinoma and large cell combined is 44 (31 ETS exposed; 70%); 12 cases are of another cell type or 

otherwise unspecified. For the 86 cases with available information, tumors were centrally located in 37 (25 ETS 

exposed; 67%) and peripherally in 46 (34 ETS exposed; 74%). 

The term "never-smoker" applies to persons who have smoked a total of fewer than 20 cigarettes. 

Interview questions regarding exposure to ETS include cigarette and cigar smoking in the home during childhood, 

by the spouse and other cohabitants in adulthood, and workplace exposure. "ETS exposed" is technically used in 

several ways. For the comparison of exposed with unexposed ever-marrieds, it means the husband ever smoked in 

the wife's presence. For measures of exposure in terms of duration or rate (e.g., total years, hours/day, total hours, 

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and cig./day), there is some variation. For example, total years of exposure is derived by adding the years during 

which tobacco exposure occurred in the home or workplace. The total hours of exposure are calculated by 

multiplying the average hours per day of exposure by the years of exposure from each household smoker, or the 

amount of exposure at each workplace. The mean hours per day of exposure are found by adding the hours per day 

of home and workplace exposures and dividing this figure by the age of the subject. This figure is intended to 

approximate the average number of hours of exposure per day experienced by the subject, over her lifetime. 

Cumulative exposure is estimated by the total cigarettes smoked by family members, weighted by years of exposure. 

When data are analyzed on the simple basis of whether a husband ever smoked in the presence of the wife, 

the crude and adjusted odds ratios are 1.55 (95% C.I. = 0.94, 3.08) and 1.64 (95% C.I. = 0.87, 3.09), respectively. 

The crude analysis applies to ever-marrieds only, which excludes three subjects. An adjusted analysis uses 

cigarettes per day smoked by the husband as the measure of ETS exposure. Conditional logistic regression was 

applied with stratification on district of residence, and housing type (public/private); model parameters were 

included for age, family history of lung cancer (yes/no), number of live births, and number of years since exposure 

at home or in the workplace. 

The crude and adjusted methods give very similar odds ratios and confidence intervals, but the tests for 

trend differ substantially. The test for trend on the crude data is based on the Mantel-Haenszel test, using midpoints 

of the intervals for cigarettes per day smoked by the husband; the significance value is p = 0.10. The p value for 

trend in the adjusted analysis is 0.32. For analysis of data by other measures of exposure, as described above, the 

estimated odds ratio ranges between 1.0 and 4.1 across the three levels of the various measures of ETS exposure for 

both the analyses of the crude data and the adjusted analyses by conditional logistic regression, with two exceptions 

from analysis of the crude data for hours per day of exposure. The results are not statistically significant in most 

cases, because the sample sizes at each exposure level are small. The dose-response patterns observed are clearly 

sensitive to the measure of ETS exposure used, with several exhibiting an apparent peak at a low exposure level. 

Although the authors acknowledge that it was troubling to find the lack of a response pattern, no further explanation 

is given. 

The authors did not detect a significant trend in the crude or adjusted odds ratio for the four lifetime 

measures of passive smoking (total years, hours, mean hours/day, cig./day). Although the odds ratio for the 

intermediate level exposures of hours per day and cigarettes per day was significant, the odds ratio at the highest 

levels of exposure for these two variables fell to a nonsignificant 1.0 to 1.2. In fact, the odds ratio for the highest 

exposure levels for three out of the four measurements were below all of those with lower exposures and ranged 

from a very weak 1.0 to 1.4. On the other hand, most of the crude and adjusted odds ratios were greater than 1.0. 

Measurements based on increasing intensity of exposure, defined as increasing years (or hours, or cig./day) by mean 

hours per day of exposure, also did not indicate a dose-response relationship. The analysis of total years of 

exposure with age of exposure did not suggest that earlier age of initial exposure and increasing years of exposure 

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led to higher odds ratios. 

It is concluded that when the lung tumors were segregated by histological type and location, the resulting 

analyses showed that peripheral tumors in the middle or lower lobes, and squamous or small cell tumors in the same 

lobes, exhibited better odds ratio patterns for passive smoking in terms of consistency, strength, and dose response. 

The odds ratio for total years, hours, and hours per day measurements of squamous and small cell lung tumors 

indicated consistently elevated risks with increasing exposure. This pattern was not found for any of the adjusted 

odds ratios for adenocarcinoma or large cell lung cancers. 

The cases are divided into two groups histologically, those with squamous cell or small cell tumors and 

those with adenocarcinoma or large cell malignancies. Although none of the crude or adjusted analyses are found to 

be significant, it is concluded that an observed dose-response pattern seems to be more apparent in the squamous or 

small cell group. With regard to tumor location, some evidence suggests that peripheral tumors in the middle or 

lower lobes may be more common in passive smokers. 

A.4.20.3. Comments 

As described above, the data employed in the current study were taken from a larger retrospective study of 

female lung cancer in Hong Kong (Koo et al., 1984) that matched 200 cases and controls on age, district of 

residence, and housing type (private or public, an indication of socioeconomic status). Attention to detail and 

accuracy is evident in most aspects of the parent study. In particular, considerable effort was put into attempting to 

ascertain a better quantitative measure of exposure than used in preceding studies of ETS. Records were apparently 

verified to the extent possible to cross-check the accuracy of information collected, cancers were verified 

histologically, and analyses investigated questions related to the histological types and sites of tumors that may be 

related to passive smoking. 

The never-smokers from the parent study, 88 cases and 137 controls, compose the secondary data set on 

which the current article is based. The matching of the subjects, of course, is no longer assured, leaving the 

comparability of the two groups uncertain. In addition, 60 (27%) of the subjects are widows, with no information 

provided on the distribution between cases and controls. Because spousal smoking is typically the variable on 

which ETS exposure pivots, this may have some bearing on the response. However, an adjustment is made in some 

analyses for years since exposure to cigarette smoke ceased. 

Some factors in the study itself may be contributing to the variable dose-response patterns. First, the 

number of ETS subjects is fairly small. When the subjects are classified into finer categories of exposure, the 

statistical variability is greatly increased (total of cases and controls is typically below 60). Second, questionable 

measurements of ETS may be causing some distortion. For instance, in the calculation of total years and total hours 

of ETS exposure, the years and hours were not added for simultaneous exposure to more than one smoker. Pipe 

smoking and the cigarette consumption levels of coworkers were excluded from the weighted average of the total 

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cigarettes per day smoked by each household member. Thus, measurement appears to be based on the assumption 

that never-smoking women were exposed to ETS evenly throughout their lives (the authors claim that only subjects 

were used for which the exposure remained relatively regular during the lifetime, although no mention was found of 

cases being omitted because of failure to satisfy this criterion). Even if this assumption were valid, childhood and 

adulthood exposures are mixed as if the effects of exposure are interchangeable. Interestingly, differences between 

exposure in childhood and adulthood is one of the questions addressed in the article. 

Although the objective is worthy, the attempt to quantitate exposure more precisely than previous studies 

appears to obscure more than to clarify. Some assumptions are not made very explicit, and their potential 

implications are not addressed well, which leaves some uneasiness about the conclusions. The authors have 

published at least three articles before this study that have some bearing on passive smoking and lung cancer, but 

their results are not discussed in the current study, even when the data analyzed are from the same source (Koo et 

al., 1983, 1984, 1985). Those articles, one of which describes the parent study (the 1984 citation), appear to reach 

somewhat different conclusions from this study regarding the predominance of histological type associated with 

passive smoking. Putting the current study's conclusions within the context of related prior work would enhance 

their clarity and interpretation. 

Considering the reservations described above, the suggestion that the evidence indicates some association 

of passive smoking with the location of tumors is an overinterpretation of the data. A weaker conclusion is 

warranted, namely, that ETS exposure is associated with increased lung cancer incidence. What may be of most 

value in this study is the analysis based on the dichotomous classification of cases and controls as exposed or 

unexposed based on spousal smoking. Two concerns, however, will be reiterated. The ETS data are taken from a 

larger study not matched on smoking status, so they are unmatched. The study includes 80 widows, without 

mention of their distribution between cases and controls. In the adjusted analysis, an attempt is made to take into 

account the number of years since last exposure, which would require some assumption regarding the change of risk 

relative to cessation of exposure. Both of these concerns are mitigated, however, by the similarity of the odds ratios 

and confidence intervals for the unadjusted and adjusted analyses. The care and thoroughness of the study in 

general make the results on the odds ratio for exposure to spousal smoke a useful contribution for evaluation with 

other study outcomes. 

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A.4.21. LAMT (Tier 2) 

A.4.21.1. Author's Abstract 

"In a case-control study in Hong Kong, 445 cases of Chinese female lung cancer patients all confirmed 

pathologically were compared with 445 Chinese female healthy neighborhood controls matched for age. The 

predominant histological type was adenocarcinoma (47.2%). The relative risk in ever-smokers was 3.81 (p < 0.001, 

95% C.I. = 2.86, 5.08). The RRs were statistically significantly raised for all major cell types with significant trends 

between RR and amount of tobacco smoked daily. Among never-smoking women, RR for passive smoking due to a 

smoking husband was 1.65 (p < 0.01, 95% C.I. = 1.16, 2.35), with a significant trend between RR and amount 

smoked daily by the husband. When broken down by cell types, the numbers were substantial only for 

adenocarcinoma (RR = 2.12, p < 0.01, 95% C.I. = 1.32, 3.39) with a significant trend between RR and amount 

smoked daily by the husband. The results suggest that passive smoking is a risk factor for lung cancer, particularly 

adenocarcinoma in Hong Kong Chinese women who never smoked." 

A.4.21.2. Study Description 

This hospital-based case-control study was conducted in Hong Kong during 1983-86, to investigate 

whether smoking is a major risk factor for lung cancer in Hong Kong Chinese women and, if so, to determine the 

relationship between smoking and the histological types of lung cancer. Both active and passive smoking are of 

interest. The ETS subjects constitute only a subset of the whole study because it includes active smokers. 

Eligible cases for the whole study are the 445 female patients with pathology-verified lung cancer admitted 

into eight large hospitals in Hong Kong during 1983-86. Cases were interviewed in person. Only a few eligible 

patients declined or were too ill to cooperate. An equal number of healthy neighborhood controls were identified 

and interviewed by density sampling. Controls were matched to cases on sex, age (" 5 years), and place of 

residence. The cases and controls include both never-smokers and ever-smokers, but smoking status was not used 

in matching. "Never-smoker" means a person who never smoked as much as one cigarette per day, or its 

equivalent, for as long as 1 year. 

A woman is "ETS exposed" if her husband smoked for at least 1 year while they lived together. If the 

husband was an ever-smoker, information on the type of tobacco and amount usually smoked per day by the 

husband and the duration of exposure was obtained. No information was collected on ETS exposure from other 

household members' smoking or smokers at work. Single (never-married) women were classified as nonexposed 

(6.8% and 5.2% in cases and controls, respectively). The treatment of widowed and divorced subjects is not 

explicitly addressed. Age and place of residence, as well as a series of other demographic variables, are similar 

between cases and controls. 

The distribution of lung cancer by cell type in ETS cases is as follows: squamous cell, 12 of 27 (number 

exposed/total); small cell, 6 of 8; adenocarcinoma, 78 of 131; large cell, 7 of 9; and others or unspecified, 12 of 24. 

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The corresponding crude odds ratios and 95% confidence intervals are 0.85 (0.35, 2.06), 3.00 (0.53, 16.90), 2.12 

(1.32, 3.39), 3.11 (0.50, 19.54), and 1.08 (0.41, 2.82), respectively. The odds ratio for all cell types combined is 

1.65 (1.16, 2.35), based on 115 of 199 (exposed/total) cases and 152 of 335 controls. The data for all cell types 

together, and for adenocarcinoma alone, are both significant at p < 0.01. No information is available on the airway 

proximity of tumors. 

Trend tests were conducted for the amount smoked daily by the husband, categorized in terms of cigarettes 

as "nil," 1 to 10, 11 to 20, and 21 or more. The odds ratios in the three exposure categories are 2.18, 1.85, and 2.07, 

respectively, when all cell types are included. For adenocarcinoma alone, the corresponding odds ratios are slightly 

higher (2.46, 2.29, and 2.89, respectively). The dose-response relationship does not appear to increase between the 

lowest dose and the highest dose, but a test for trend is significant (p < 0.01 for all cell types and p < 0.001 for 

adenocarcinoma alone) when the "nil" group is included. No adjusted analyses are given. 

The authors conclude that the significant trends observed between relative risk and amount smoked daily 

by husband, for all cell types combined and for adenocarcinoma alone, support the view that the observed 

association between ETS exposure and lung cancer is likely to be causal. 

A.4.21.3. Comments 

This study is the fourth of the Hong Kong epidemiologic inquiries into tobacco smoke as a possible 

etiological factor in the high rate of lung cancer, particularly adenocarcinoma, among women. Active smoking was 

included as well as passive smoking because the previous studies in Hong Kong were inconclusive. According to 

the authors, this led to the hypothesis that smoking is not a risk factor for adenocarcinoma in Hong Kong Chinese 

women. Matching of controls to cases was conducted for the whole study, including active smokers. It cannot be 

assumed, however, that the never-smokers alone, who constitute 45% of the cases and 76% of the controls, are 

matched. 

Overall, the study demonstrates care in planning and execution. The sample size of ETS subjects is 

moderately large, providing higher statistical power than the previous Hong Kong studies. All cases were 

pathologically confirmed as primary lung cancers, essentially eliminating the potential for error due to disease 

misclassification. Odds ratios were calculated by histological type for comparison. Cases and controls were 

interviewed personally, apparently with no proxy respondents and very few refusals, which reduces the potential for 

response bias. The exclusive use of incident cases helps to control potential selection bias, and density sampling of 

controls contributes to comparability of cases and controls. For the whole study, including smokers, healthy 

controls were matched to cases by sex, age, and neighborhood of residence. The mean and standard deviation of 

ages are nearly identical in cases and controls. According to the authors, a comparison by other demographic 

variables showed that, for the whole study, cases and controls were also comparable in place of birth, duration of 

stay in Hong Kong, level of education, marital status, and husband's occupation. Further attention to detail is 

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evident in the clear definitions of "never-smoker" and "ETS exposure," essential to accurate classification of 

subjects for analysis and interpretation. Single women were treated as not exposed to husband's smoking, which 

could be a source of bias because these women may be exposed from other household members. This possibility 

was considered, however, because the article reports that similar results were obtained when single women were 

excluded. 

In summary, the crude odds ratios vary between 2.1 and 3.1 for small cell carcinoma, adenocarcinoma, and 

large cell carcinoma, with adenocarcinoma significant at p < 0.01. The odds ratios are consistently elevated at all 

three intensity levels of spousal smoking, varying between 1.8 and 2.9, with the odds ratio for adenocarcinoma 

alone somewhat higher than for all cell types combined. There is no apparent upward trend, however, from the 

lowest smoking intensity (1-10 cig./day) to the highest (21+ cig./day). These statistical results are ostensibly 

suggestive of an association between ETS exposure and lung cancer incidence, but they are based on only crude 

data with cases and controls unmatched, even on ages. Nor are statistical methods used that could adjust for 

matching variables, or other factors, in the data analysis (e.g., by stratification or logistic regression). Although this 

study was carefully conducted in most respects, the disregard for potential confounding effects leaves the authors' 

conclusion uncertain. 

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A.4.22. LAMW (Tier 3)

(Note: This study is part of the thesis of LAM Wah Kit submitted to the University of Hong Kong for the M.D. 

degree in 1985, entitled A Clinical and Epidemiological Study of Carcinoma in Hong Kong. The description given 

below is from Chapter 7 of the thesis only, entitled Case-Control Study of Passive Smoking, Kerosene Stove Usage 

and Home Incense Burning in Relation to Lung Cancer in Nonsmoking Females (1981-84), which the author

submitted in response to our request. The abstract below was prepared by the reviewers, since none was available 

from the author.) 

A.4.22.1. Abstract 

The study's objective is to investigate the hypothesis that an inhaled carcinogen may be related to the high 

incidence of centrally situated adenocarcinoma of the lung observed in nonsmoking female patients. Air pollution 

is probably not an important factor because it presumably affects both men and women. Most women in Hong 

Kong either stay at home or join the work force in commerce, services, or manufacturing, which are not associated 

with any known risk factor for lung cancer. Three etiological activities, all predominantly in the home, are 

considered in this study: passive smoking, kerosene stove cooking, and home incense burning. No evidence was 

found to implicate exposure to kerosene stove fumes or incense burning in centrally located adenocarcinoma. There 

is suggestive evidence of an association between ETS exposure from smoking husbands and occurrence of 

peripheral (but not central) adenocarcinoma. Why the location tends to be peripheral instead of central is 

speculative. 

A.4.22.2. Study Description

(Note: The details of the study are not complete in the material provided. Some useful information, however, is

available.) 

The cases are all of the Chinese female patients admitted to the University Department of Medicine, Queen 

Mary Hospital, Hong Kong, between January 1981 and April 1984 with histologically and/or cytologically 

confirmed carcinoma of the lung of the four major cell types. Care was taken to exclude patients with secondary 

carcinoma of the lung; otherwise, all patients were included. The controls are Chinese female patients admitted to 

the orthopedic wards of the hospital in the period 1982-84, comparable to lung cancer patients in age and social 

class. Patients with pathological fractures due to smoking-related malignancies or with peripheral vascular diseaserelated orthopedic conditions were excluded. 

Both cases and controls were patients of the third-class general wards, mostly from the lower income 

group. All subjects were interviewed in person. The questions covered dialect group, occupation, smoking habits, 

passive smoking, domestic cooking with kerosene, and home incense burning, in the form of a standardized 

questionnaire. For very ill patients, or for patients who spoke a dialect other than Cantonese or Mandarin, the next 

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of kin was interviewed, with the patient as interpreter. The whole study, including active smokers, contains 161 

cases and 185 controls, similar in age (median age is 67.5 [66] for cases [controls]), socioeconomic status (as 

measured by occupation and years of schooling), and recent residence. The author considered it unnecessary to 

stratify on these or any other variables. 

The ETS subjects consist of 75 (144) cases (controls), including 16 (14) never-married cases (controls). 

The distribution of cases by cancer cell type is as follows: squamous cell (7), small cell (3), large cell (5), and 

adenocarcinoma (60). Questions related to ETS exposure include details on each smoker in the home (husband, 

others, mother, and father), amount smoked per day, hours of ETS exposure per day, and number of years smoked. 

Information about exposure in the workplace includes size of the workplace, number of coworkers who smoke, 

exposure time/day, and number of years of exposure at work. 

Only the data for adenocarcinoma, the predominant cell type observed and the pathogenesis of interest, are 

analyzed. The number of cases is 37 out of 60 (exposed/total), and the number of controls is 64 out of 144, where 

ETS exposure refers to spousal smoking. The odds ratio (calculated by the reviewers) is 2.01 (95% C.I. = 1.09, 

3.72). The author divides the cases by location according to airway proximity, with 18 of 32 (exposed/total) located 

centrally and 19 of 28 in peripheral regions. The respective risk ratios are 1.61 and 2.64. Two tests were conducted 

for significance, including the Bayesian risk ratio analysis and a test of the slope for the exposure parameter in a 

simple logistic regression model. The significance levels are 0.11 and 0.19, respectively, for the central location 

and 0.01 and 0.02, respectively, for peripheral tumors. The test results differ widely for total passive smoking 

(home or workplace). For the central location, the respective significance levels are 0.09 and 0.3; for peripheral 

locations, the corresponding values are 0.03 and 0.15. It is suggested that the different outcomes for the two tests 

applied to total passive smoking may be due to a nonlinear logistic dose-response curve or to errors in assessing the 

level of exposure due to incomplete information. The apparent association between passive smoking and peripheral 

adenocarcinoma (and not central tumors) in the cases was unexpected. Based on the available raw data, exposure to 

a smoking spouse, cohabitant, and/or coworker is associated with an odds ratio of 2.51 (95% C.I. = 1.34, 4.67) for 

all cell types combined. The author concludes that there is a suggestion of passive smoking associated with 

peripheral adenocarcinoma, particularly passive smoking attributable to smoking husbands. Kerosene and incense 

burning were not found to be associated with adenocarcinoma, either central or peripheral. 

A.4.22.3. Comments 

Cases and controls appear to be comparable in age, socioeconomic status, and recent residence for the 

whole study (including active smokers), although the study design is not matched on these or other variables. Some 

discrepancies between cases and controls are apparent, however, such as a higher percentage of cases than controls 

working outside the home (41% compared with 28%). The figures for nonsmokers alone (i.e., the ETS subjects) are 

not given, so comparability is uncertain for analysis of ETS exposure. Care has been taken to include only primary 

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lung cancer patients among the cases, essentially eliminating this potential source of bias. Subjects were personally 

interviewed, with apparently only a small number of proxy respondents required, although no figure is given. The 

interviews apparently were not blinded, but that may not have been feasible considering the nature of the questions 

asked and the use of noncancer patients as controls. Considerable attention is given to histological type of cancer 

and the location in terms of airway proximity. 

The author is particularly interested in the etiology of adenocarcinoma and focuses discussion on the 

adenocarcinoma cases to the exclusion of others. Although the raw data pertaining to other cell types are tabulated, 

more attention to those types in the analyses would have been useful. The adenocarcinoma cases are categorized 

further by central and peripheral location, which are analyzed separately. Again, a combined analysis would be 

useful (the reviewers calculated the crude odds ratio for the combined data, which is given above). Although 

logistic regression is employed as one of the two statistical tools for analysis, factors that may differ between cases 

and controls are not included. Potential confounding variables need to be controlled for, by logistic regression, 

poststratification, or otherwise. To claim that cases and controls are similar in potential confounding characteristics 

does not alleviate the need to adjust for them in the analysis, particularly when the ETS data are a subset of the 

larger data set to which reference is made. Similarly, in testing three factors for an association with lung cancer 

(passive smoking, cooking with kerosene, and burning incense), it would be useful to conduct an analysis that will 

allow evaluation of the effect of each after adjustment for the other two. 

The suggestive evidence that passive smoking is more likely associated with adenocarcinoma in peripheral 

rather than central locations may be logical but is weak, especially considering the lack of analytical rigor. The 

proportion of ETS-exposed cases of adenocarcinoma is 18 of 32 (56%) for central locations and 19 of 28 (68%) for 

peripheral locations. This difference is not statistically significant (p = 0.26 by Fisher's exact test). Consequently, 

the "apparent association" between passive smoking and peripheral adenocarcinoma (and not central tumors) may 

well be due to chance alone. There is suggestive evidence in the data that passive smoking may be associated with 

lung cancer (OR = 2.01, p < 0.03 for a one-sided test), but that is based only on the crude odds ratio in unmatched 

data and needs to be confirmed by a more thorough evaluation of the data that takes potential confounders into 

account. Overall, this study provides some suggestive evidence for an association between passive smoking and 

lung cancer. Potential confounders (including age) have not been controlled for, however, so attribution of the 

elevated odds ratio to ETS exposure is uncertain. 

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A.4.23. LEE (Tier 2) 

A.4.23.1. Author's Abstract 

"In the latter part of a large hospital case-control study of the relationship of type of cigarette smoked to 

risk of various smoking-associated diseases, patients answered questions on the smoking habits of their first spouse 

and on the extent of passive smoke exposure at home, at work, during travel and during leisure. In an extension of 

this study an attempt was made to obtain smoking habit data directly from the spouses of all lifelong nonsmoking 

lung cancer cases and of two lifelong nonsmoking matched controls for each case. The attempt was made 

regardless of whether the patients had answered passive smoking questions in the hospital or not. 

Among lifelong nonsmokers, passive smoking was not associated with any significant increase in risk of 

lung cancer, chronic bronchitis, ischemic heart disease, or stroke in any analysis. 

Limitations of past studies on passive smoking are discussed and the need for further research underlined. 

From all the available evidence, it appears that any effect of passive smoke on risk of any of the major diseases that 

have been associated with active smoking is at most small, and may not exist at all." 

A.4.23.2. Study Description 

This study was undertaken in England, essentially from 1979 to 1983. Its stated objective is to investigate 

the relationship between passive smoking and risk of lung cancer in nonsmokers. It is an outgrowth, however, of a 

hospital-based case-control study to assess whether the risk of cardiorespiratory disease associated with smoking 

varies by type of cigarette smoked. It was initiated in 1977 in 10 hospital regions in England. In 1979, interviewers 

began gathering information on passive smoking as well in four of the regions. Then in 1982, this case-control 

study of the effects of passive smoking was begun using nonsmoking cases identified by the ongoing 

cardiorespiratory effects study. For the new study, spouses of cases and specially selected controls were 

interviewed regarding smoking habits. Previously collected data on passive smoke exposure obtained from patients 

back to 1979 were used. 

Basically, two substudies were conducted. One used the data obtained directly from hospitalized cases and 

controls to address several sources of passive smoke, including spousal (henceforward the "passive smoking" 

study); the second substudy used data obtained from the spouses of cases and controls along with corresponding 

information from the patients themselves, when available, to address spousal smoke exposure only (henceforward 

the "spousal smoking" study). Cases for the passive smoking study were currently married lifelong nonsmokers 

diagnosed with lung cancer (of any cell type), chronic bronchitis, ischemic heart disease, or stroke in one of four 

participating hospital regions. Controls were currently married lifelong nonsmoker inpatients diagnosed with a 

condition definitely or probably not related to smoking and individually matched on sex, age, hospital region, and, 

when possible, hospital ward and time of interview. Thus, density sampling was used when possible. For the 

spousal smoking study, previously married patients were excluded; the same criteria otherwise applied, except that 

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controls were now matched on sex, age decade, and--as far as possible--hospital and time of interview. 

Diagnoses were obtained from medical records. Exposure data were obtained through apparently 

unblinded, presumably face-to-face interviews with inpatients and their spouses. A total of 3,832 married cases and 

controls were interviewed regarding passive smoking through 1982; it is unclear how many potential subjects 

refused or died before interview. Only 56 of these were married lung cancer cases meeting the spousal smoking 

study criteria. Spousal interview data were obtained for 34 of these cases and 80 controls; interviews were refused 

by the remainder. Although matching of cases and controls was initially carried out, it was not retained in the 

analysis, and no demographic comparison of cases and controls used in the analyses is provided. Diagnoses were 

apparently drawn from patients' charts; provisional diagnoses were used where no final diagnosis was specified, no 

data on diagnostic technique(s) or histology was presented, and no diagnostic verification was reported. 

The patient population consists of never-smokers, defined as lifelong nonsmokers, which presumably 

excludes cigar and pipe smokers. Exposure to ETS is approached in several ways. The primary exposure is that of 

a spouse smoking manufactured cigarettes at some point over the course of a marriage. Spousal smoking in the 12 

months before interview also was assessed. In addition, "regular" exposure to passive smoke in various situations 

(i.e., at home or work, during travel or leisure) was assessed. The first two exposures were quantified in numbers of 

cigarettes smoked per day, the others in terms of "not at all, a little, average, or a lot." Thus, it appears that cigar 

and pipe smoking may not have been included in the spousal smoking exposures. Comparison of individual 

responses regarding spousal smoking status by patients and their spouses revealed a high degree of concordance 

(97%) for smoking during the past 12 months and a substantial concordance (85%) for smoking during marriage. 

No other checks on exposure data were reported. 

The ETS patient data set includes 56 cases and 112 controls who met the initial study criteria. Not all of 

these answered each passive exposure question, however, and not all met the criteria for the spousal interview 

study. Similarly, spouses of 34 cases and 80 controls provided exposure information of varying completeness. 

Thus, the numbers involved in each analysis varied considerably. For smoking during marriage, data obtained 

directly from spouses indicated that for males and females combined, 24 of 34 lung cancer cases and 51 of 80 

controls were exposed, which yields a crude odds ratio of 1.4 for spousal smoking. With standardization for age, an 

odds ratio of 1.33 (95% C.I. = 0.50, 3.48) was reported. Data obtained from qualifying patients, in contrast, 

revealed 13 of 29 cases and 27 of 59 controls to be exposed, yielding a crude and adjusted odds ratio of 1.00 (95% 

C.I. = 0.41, 2.44). Stratification by gender yielded adjusted odds ratios from spousal interview data of 1.60 (0.44, 

5.78) and 1.01 (0.23, 4.41) for females and males, respectively, with corresponding odds ratios from patient 

interview data of 0.75 (0.24, 2.40) and 1.5 (0.37, 6.34). When spouses identified as smokers by interview with 

either source were classified as exposed, an odds ratio of 1.00 (0.37, 2.71) was obtained for female subjects. For 

the larger inpatient passive smoking study population, age-standardized odds ratios for passive smoke exposure at 

home, at work, during travel, and during leisure revealed no consistent associations, with as many negative as 

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positive relationships observed after adjustment for both age and whether still currently married. The same 

inconsistency held true for spousal smoking during the last 12 months and during the whole marriage. Adjustment 

for working in a dusty job reportedly did not affect the conclusion that passive smoking was not associated with 

risk. 

Spousal smoking was slightly negatively associated with chronic bronchitis, ischemic heart disease, and 

stroke, whereas a combined ETS exposure index was negatively associated with heart disease but positively 

associated with bronchitis and stroke. 

The author concluded that the findings appear consistent with the general view, based on all the available 

evidence, that any effect of passive smoking on risk of lung cancer or other smoking-associated diseases is at most 

quite small, if it exists at all. The marked increases in risk noted in some studies are more likely to be a result of 

bias in the study design than of a true effect of passive smoking. 

A.4.23.3. Comments 

The heart of this study is the spousal interview investigation of lung cancer and spousal smoking. Only 34 

case spouses and 80 control spouses, and even fewer of the corresponding cases and controls themselves, are 

included, which gives the study low statistical power. Because the study began with hospital inpatient married 

lifelong nonsmokers, and matching on several key factors was employed, good comparability of cases and controls 

would seem readily achievable. No case-control demographics are provided, however, and matching is abandoned 

in the analyses. The occurrence of interview refusals and omitted responses (themselves a potential source of 

selection and information bias) may have contributed to the decision to abandon matching, with the aim of 

preventing further substantial reduction in numbers through exclusion of unmatched subjects. As a result, the 

comparability of the cases and controls is uncertain. At least all are drawn from the same four hospital areas within 

a fairly limited timespan, which, in combination with the other study criteria, reduces the likelihood of serious 

noncomparability. 

Numerous opportunities for misclassification of disease and exposure status are present. Current working 

diagnoses are apparently drawn from patient charts without verification, and controls are selected from patients with 

diagnoses judged either probably or definitely not associated with smoking by unspecified criteria. This creates 

considerable potential for misclassification, both through inaccuracies in diagnoses generally and through inclusion 

of smoking-related diseases in the control group particularly, which would produce a downward bias in results. 

Exposure misreporting and recall problems would seem least likely where spouses are interviewed directly about 

exposure within the past 12 months. Results for this situation are not presented, although they are reportedly similar 

to those for smoking during marriage. 

The larger inpatient study elicited smoking data from patients, and only for their first spouse for patients 

who had remarried; thus, exposure occurring in subsequent marriages is not addressed. In addition, no information 

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on duration or level of smoking in marriage is used in any of the spousal smoking analyses. The most likely result 

of these problems is nondifferential misclassification resulting in a bias toward the null. For general estimated 

home, work, travel, or leisure exposure to passive smoke, rough quantification is attempted by having patients 

categorize their exposure as "not at all, a little, average, or a lot." By necessity, this is a very subjective evaluation, 

and people more acclimated to smoke and tolerant of exposure might well tend to characterize a given amount of 

exposure as less severe than would a person less tolerant of smoke who more actively avoids exposure. This 

tendency would produce a bias toward negative association. 

Standardization for age and restriction of cases and controls to currently married lifelong nonsmokers 

should control the effects of age, marital status, or active smoking, although misreporting of current or former active 

smoking cannot be ruled out entirely. Dusty occupation reportedly had no effect on the larger inpatient study 

results. Potential effects of race, socioeconomic status, diet, cooking habits, or any additional factors were not 

addressed. 

One might expect the most accurate reporting of spousal smoke exposure when spouses are interviewed 

directly regarding their own smoking habits, and the most inadvertent misclassification when patients are queried 

about the smoking status of their first marital partner only. Analyses along these lines yielded slightly positive 

associations with smoking for the former and negative with the latter approach. No consistent pattern of association 

was seen for other sources and lung cancer, although high combined exposure scores were associated positively 

with chronic bronchitis and stroke and negatively with ischemic heart disease. 

In summary, this study presents equivocal results that neither strongly confirm nor refute the hypothesis 

that passive smoking mildly increases risk of lung cancer. The quality of the study, however, is a limitation. The 

discrepant results for subject-supplied data (OR = 0.75) and spouse-supplied data (OR = 1.60), varying degrees of 

completeness of information on subjects, and the subjective nature of questions regarding ETS exposure limit 

confidence in the study's data and, consequently, the results of its analysis of those data. 

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A.4.24. LIU (Tier 4) 

A.4.24.1. Author's Abstract 

"In Xuanwei County, Yunnan Province, lung cancer mortality rates are among the highest in China in both 

males and females. Previous studies have shown a strong association of lung cancer mortality with indoor air 

pollution from `smoky' coal combustion. In the present case-control study, 110 newly diagnosed lung cancer 

patients and 426 controls were matched with respect to age, sex, occupation (all subjects were farmers), and village 

of residence (which provided matching with respect to fuel use). This design allowed assessment of known and 

suspected lung cancer risk factors other than those mentioned above. Data from males and females were analyzed 

by conditional logistic regression. In females who do not smoke, the presence of lung cancer was statistically 

significantly associated with chronic bronchitis (OR = 7.37, 95% C.I. = 2.40, 22.66) and family history of lung 

cancer (OR 4.18, 95% C.I. = 1.61, 10.85). Females' results also suggested an association of lung cancer with 

duration of cooking food (OR 1.00, 9.18, and 14.70), but not with passive smoking (OR 0.77, 95% C.I. = 0.30, 

1.96). In males, lung cancer was significantly associated with chronic bronchitis (OR 7.32, 95% C.I. = 2.86, 20.18), 

family history of lung cancer (OR 3.78, 95% C.I. = 1.70, 8.42), and personal history of cooking food (OR 3.36, 

95% C.I. = 1.27, 8.88). In males, a dose-response relationship of lung cancer with smoking index (years of 

smoking/amount of smoking) was shown by risks of 1.00, 2.61, 2.17, and 4.70." 

A.4.24.2. Study Description 

This study was undertaken in Xuanwei County of China's Yunnan Province, a county whose lung cancer 

mortality rates are among the country's highest and wherein burning of smoky coal indoors in unventilated pits is a 

common practice. The study sought to assess "the influence of factors other than type of fuel on the occurrence of 

lung cancer in Xuanwei." 

Cases of newly diagnosed lung cancer occurring among farmers at hospitals and clinics in Xuanwei 

between November 1985 and December 1986 were identified as potential study subjects. Up to five controls were 

identified for each case, depending on availability after matching on age (" 2 years), gender, and village of 

residence. A total of 112 cases were identified, from which 2 were excluded due to unknown addresses. Of 452 

candidate controls, 26 were excluded due to erroneous questionnaire responses. All subjects were interviewed faceto-face by trained personnel using a standardized questionnaire, and blinding extended to both interviewers and 

interviewees. 

The final study groups consist of 54 (56) female (male) cases and 202 (224) female (male) controls. Mean 

age is 52 years for both cases and controls, who are also similar in family size, ethnicity, birthplace, dwelling type, 

and type of fuel used (smoky coal, wood). Separate breakdowns for males and females are not provided. Very few 

of the cases (19/110 = 17%) were histologically or cytologically diagnosed, and no verification of diagnosis or 

exclusion of secondary tumors was undertaken (except to monitor mortality among some of the cases). 

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Exposure to ETS was not evaluated for males. Among females, only one subject (a control) reported ever 

having smoked, so the ETS population of females effectively consists of never-smokers. Subjects were classified as 

exposed to ETS if their household contained at least one smoker. Exposure is not quantified, and it is unclear 

whether former or only current exposure is intended. No checks on exposure status or consideration of marital 

status are mentioned, and no histological data are presented. 

The proportion of exposed female subjects is 45 out of 54 (176/202) for cases (controls), yielding a crude 

odds ratio of 0.74. A conditional logistic regression analysis adjusted for other risk factors (presumably the other 

factors referred to are age-began-cooking and years-of-cooking) gives an odds ratio of 0.77 (95% C.I. = 0.30, 1.96). 

No further analyses of ETS exposure are provided. 

Four non-ETS factors are significantly associated with lung cancer among females: family history of lung 

cancer (OR = 4.18; 95% C.I. = 1.61, 10.85), personal history of bronchitis (OR = 7.37; C.I. = 2.40, 22.66), agebegan-cooking (OR = 2.44-1.03, but with a reversing and nonsignificant dose-response), and years-of-cooking (OR 

= 2.49-2.25, nonsignificant trend). Among males, significant positive associations were noted for total smoking 

index, often-cooking-own-food, family history of lung cancer, and history of chronic bronchitis, whereas agebegan-smoking, years of smoking, and intensity of smoking showed modest but nonsignificant associations with 

lung cancer. 

The authors conclude that "it is quite conceivable that the large amount of air pollutants inhaled during 

indoor smoky coal burning in Xuanwei partly overwhelm the carcinogenic effect of tobacco smoking" and "may 

also overwhelm the carcinogenic effect of passive smoking." "Our results disclose important associations of lung 

cancer with factors other than fuel type and therefore indicate that those factors must be considered in any 

comprehensive, quantitative risk assessment of lung cancer in Xuanwei. Our results also confirm indirectly that 

smoky coal pollution is an important determinant of lung cancer in Xuanwei." 

A.4.24.3. Comments 

This modestly sized study was not designed to test for effects of ETS exposure. Rather, it is a hypothesisgenerating exercise aimed at covering a broad range of possible risk factors. Within that context, the study has 

considerable merit, but as an investigation of ETS it has numerous flaws. 

Restriction to farmers minimizes concerns with occupation and overall lifestyle, and control selection, 

including matching on age, gender, and village, produced demographically comparable case and control populations 

for males and females combined despite the enigmatic exclusion criterion for controls. It is unknown, however, 

whether the groups remain comparable after subdivision into males and females. 

The use of newly diagnosed cases reduces potential selection bias due to inclusion of prevalent cases, but 

the heavy reliance (83%) on clinical and radiological diagnosis and the absence of independent confirmation or 

exclusion of secondary tumors introduces a strong potential for misclassification of disease and precludes analyses 

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by cell type. The observation that followup of a number of lung cancer patients revealed that almost all died within 

6 months of diagnosis does little to confirm diagnostic validity, contrary to the authors' interpretation. Such 

presumably random misclassification would make detection of an existing ETS-lung cancer association more 

difficult. 

Exposure data collection procedures, particularly the exclusive use of face-to-face interviews without 

resort to proxies and the blinding of both interviewers and subjects, are laudable. For ETS, however, the exposure 

measure used is nonspecific and nonquantitative. Complications due to past exposure and differences in degree or 

duration could distort the observed disease-exposure relationship, probably biasing results toward no effect. 

Potential confounding is not adequately addressed in the statistical analysis. The authors are particularly 

concerned with indoor smoky coal burning due to the known strong correlation between smoky coal use and lung 

cancer mortality in Xuanwei. Wishing to focus their investigations on factors other than smoky coal, they matched 

cases and controls on village, which "provided effective matching on fuel type." But because age and a host of 

other demographic factors, as well as smoky coal consumption, were comparably distributed in cases and controls 

(see study description), these factors were not considered further in the data analysis. This is a serious flaw, for pair 

matching was not retained in the analysis; thus, none of the above factors is effectively controlled for. The 

conditional regression analyses do control for risk factors other than those cited above, but exclusion of age, fuel 

type (e.g., smoky coal), and degree of exposure to fuel fumes may produce misleading results. 

The presence of other significant risk factors for lung cancer makes detection of an effect from ETS, if 

present, less likely. Masking by the presence of smoky coal and other factors in the study environment is probably a 

factor in the remarkably weak association between active smoking and lung cancer among study males (adjusted 

OR = 1.36). If even an effect of active smoking remains largely obscured under study conditions, it is unlikely that 

an effect of ETS would be detected. Supporting these concerns are other recent studies in Xuanwei County that 

have confirmed widespread smoky coal use (e.g., 100% of households in Cheng Guan commune before 1958) and 

serious indoor air pollution with combustion byproducts, including mean indoor benzo[a]pyrene (BaP) levels of 9-

15 ng/m3

 in two communes using smoky coal during fall of 1983 (Mumford et al., 1987). Prior use of smoky coal 

at age 12 is associated with an OR of 3.7 for lung cancer in pair-matched female residents (Chapman et al., 1988). 

He et al. (1991), who report a strong association between indoor BaP and lung cancer, conclude that indoor air 

pollution appears to be the strongest risk factor for lung cancer in Xuanwei females. 

Overall, this study makes important contributions to its principal objectives but is not helpful in assessing 

ETS and lung cancer. It is observed, for example, that persons in areas of Xuanwei with high lung cancer rates (and 

high smoky coal consumption) may inhale more BaP by spending 8 hours indoors than by smoking 20 cigarettes. 

Due to such factors, the authors observe, "the effect of passive smoking on lung cancer may depend on local 

environmental factors and results obtained in a given region therefore may not be applicable to other regions." 

Avoidance of areas atypically rich in competing exposures and careful control of potential confounders and 

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interactive risk factors must be key objectives in studies of ETS and lung cancer. 

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A.4.25. PERS (Tier 1) 

A.4.25.1. Author's Abstract 

"The relation between passive smoking and lung cancer was examined by means of a case-control study in 

a cohort of 27,409 nonsmoking Swedish women identified from questionnaires mailed in 1961 and 1963. A total of 

77 cases of primary carcinoma of the bronchus or lung were found in a followup of the cohort through 1980. A new 

questionnaire in 1984 provided information on smoking by study subjects and their spouses as well as on potential 

confounding factors. The study revealed a relative risk of 3.3, constituting a statistically significant increase 

(p < 0.05) for squamous cell and small cell carcinomas in women married to smokers and a positive dose-response 

relation. No consistent effect could be seen for other histologic types, indicating that passive smoking is related 

primarily to those forms of lung cancer that show the highest relative risks in smokers." 

A.4.25.2. Study Description 

This case-control study, undertaken to explore the role of passive smoking in lung cancer, is based on 

cohorts of Swedish women assembled prior to 1963. Nonsmokers were drawn from these cohorts to create matched 

case and control groups. 

Cases are nonsmoking Swedish women included in the Swedish National Census or Twin Registry who 

responded to smoking status questionnaires in 1961-63 and who subsequently developed primary lung or bronchial 

cancer by 1980. Two control groups were cumulatively sampled from National Census or Twin Registry subjects 

who did not develop lung or bronchial cancer. In group 1, two controls were matched to each case on year of birth 

(" 1 year). In group 2, two controls were matched to each case (2:1) on year of birth (" 1 year) and vital status in 

1980. Thus, there were 58 cases and 232 controls from the National Census and 34 cases and 136 controls from the 

Twin Registry. A followup questionnaire that included questions on spousal and parental smoking habits was 

distributed to each subject or the next of kin in 1984. Out of 92 cases of tracheal, bronchial, lung, or pleural cancer 

occurring by 1980, 15 cases in which a diagnosis of primary cancer of the lung or bronchus was not established 

were excluded. Exclusion of women indicated to be active smokers according to the 1984 questionnaire, or for 

whom ETS exposure information was not available, eliminated a further 10 cases. Active smoking and lack of 

exposure information eliminated 21 of the 368 controls initially assembled. Histological confirmation was available 

for 64 of the 77 cases with primary lung or bronchial cancer; 12 cases were cytologically confirmed, and the 

remaining case was verified at autopsy. 

Never-smokers are subjects who report that they have never smoked any form of tobacco. A woman is 

ETS exposed if she has ever been married to a tobacco smoker; for women married more than once, only the longest 

marriage is considered. Exposure to spousal smoking is quantified in units of cigarettes per day or packs of pipe 

tobacco per week; parental smoke exposure is defined as 0, 1, 2, etc. (equal to the number of parents who smoke). 

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No other sources of ETS exposure are considered. Never-smoking status was checked by comparing the responses 

to the 1961-63 questionnaires with those obtained in 1984. Data on sources of ETS were not checked. Nevermarried women were classified as nonexposed to spousal smoke; widows and divorcees were classified according to 

the smoking status of the former husband with whom they had lived the longest. Of the never-smoking cases for 

whom passive smoking information was available, squamous and small cell tumors constituted 20 cases, 13 of 

whom were exposed to spousal smoke; of the other 47 cases, 20 were exposed to spousal smoke. 

Responses to the ETS questionnaire were available for a total of 81 never-smoking cases and 347 neversmoking controls. The 67 cases with primary lung or bronchial cancer constitute the ETS study subjects. It is not 

clear how many of the 347 potential controls were employed in each analysis. Presumably many (up to 4 for each 

excluded case from the original 81 never-smoking cases) were not used in the matched analysis, whereas most or all 

were used in the unmatched analyses described subsequently. 

A total of 33 of the 67 cases were exposed to spousal smoking. Among the never-smoking women, 

matched analyses indicate that the odds ratio for marriage to a smoker is 3.8 (95% C.I. = 1.1, 16.9) for squamous or 

small cell cancer compared with control group 1, 3.4 (0.8, 20.1) compared with control group 2, and 3.3 (1.1, 11.4) 

compared with both groups combined. For other cell types, corresponding odds ratios are 0.7, 0.8, and 0.8, 

respectively. Subsequent analyses abandoned matching and pooled all controls. For squamous and small cell 

cancer, high exposure to spousal smoking (15 or more cig./day or at least one pack of pipe tobacco/week for 30+ 

years) is associated with an age-adjusted odds ratio of 6.4 (1.1, 34.7), whereas the lower exposure is associated with 

an odds ratio of 1.8 (0.6, 5.3). The estimated odds ratios for other types of cancer are also elevated for the higher 

exposure, but not at the lower one. Odds ratios adjusted for age and spousal smoking when at least one parent 

smokes as well are above 1 (1.9; 95% C.I. = 0.5, 6.2) for squamous and small cell types but not for other types. 

Logistic regression analyses reportedly produced the same results as did the stratified analyses. In 

addition, occupation, household radon, and urban or rural status had no significant effect. It is notable, however, 

that for all cancers combined, the odds ratio for radon exposure is 1.4 (0.4, 5.4), the odds ratio for spousal smoking 

is 1.2 (0.6, 2.6), and the odds ratio for radon and spousal smoking combined is 2.5 (0.8, 8.5). No separate analyses 

for squamous and small cell cancer are provided for radon and other potential confounders. The authors conclude 

that exposure to ETS is related primarily to the forms of lung cancer that show the highest relative risks in smokers. 

The results are internally consistent. 

A.4.25.3. Comment 

Although based on cohorts assembled for other purposes, this case-control study was specifically designed 

to investigate passive smoke exposure. Thus, all participants are ETS subjects that are matched. Matching criteria 

are rather modest--birthdate (" 1 year) for control group 1 and birthdate and vital status for control group 2. 

Because the study targeted all cases detected in the same cohorts from which matching controls were randomly 

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drawn, good comparability of cases and controls is likely. No demographic comparisons of cases and controls for 

whom ETS information was available--and thus who constituted the analytical subjects--were provided to confirm 

this, however. Data on active smoking among subjects were collected both at the start and after the end of mortality 

monitoring, providing an opportunity to verify the nonsmoking status over time and exclude individuals whose 

status had changed (apparently those reported in 1984 to have smoked daily for at least 2 years were so excluded). 

Thus, the probability of significant misclassification of active smoking status is low. Data on passive smoking were 

collected only after the end of mortality monitoring and by necessity employed proxy respondents extensively, so 

some misclassification of exposure is likely. Self-administration of questionnaires eliminates interviewer bias as a 

source of error, making misclassification less likely to be systematic, but preferential recall of smoke exposure by 

relatives of cancer victims could have produced a bias. Misclassification of disease is unlikely to have been a 

problem because most cases were histologically diagnosed and secondary lung cancers were excluded. 

Consideration of spousal smoke exposure only in their longest marriage among women married more than 

once means that some of the unexposed group probably had substantial exposure to spousal smoking, creating a bias 

toward no association. Classification of all never-married women as unexposed despite possible smoking by 

cohabitants creates the same bias. Few subjects (less than 20%) were single, but the frequency of remarriage is 

unknown; therefore, it is unclear how important this bias might have been. Lack of consideration of workplace 

smoke exposure also may have contributed a bias toward the null hypothesis of no association. 

The authors addressed a number of potential confounders and risk modifiers. Restriction of subjects to 

women eliminates potential effects of gender, and age is addressed by retaining age-matching or, alternatively, 

adjusting for age in all analyses. Reportedly neither occupation, radon, nor urban residence had significant 

confounding effects, which makes confounding by other factors related to socioeconomic status or lifestyle 

unlikely, too. An analysis of parental smoking controlled for spousal smoking. The authors do, however, present 

evidence that the odds ratio for simultaneous exposure to radon and spousal smoke approximately equals the sum of 

the separate odds ratios for radon and spousal smoke, consistent with additivity of the effects. But, perhaps due to 

limited numbers, they report results only for all cancers combined rather than for the squamous and small cell 

subgroup in which the only significant spousal smoking association was observed. 

In summary, this study reports a consistent, dose-related, and (for high exposure levels) statistically 

significant positive association between exposure to spousal tobacco smoke and squamous and small cell carcinoma 

of the lung; a positive but nonsignificant association was also observed for parental smoke exposure. No significant 

associations were observed for other cell types. The observed associations apparently are not due to confounding 

by other major risk factors, although dietary and smoking habits were not directly addressed. A possible recall bias 

cannot be ruled out but seems unlikely given the negative results obtained for cancers other than squamous and 

small cell. The study provides a useful contribution to investigation of the relationship between ETS exposure and 

lung cancer. 

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A.4.26. SHIM (Tier 2) 

A.4.26.1. Author's Abstract 

"A case-control study of Japanese women in Nagoya was conducted to investigate the 

significance of passive smoking and other factors in relation to the etiology of female lung cancer. A 

total of 90 nonsmoking patients with primary lung cancer and their age- and hospital-matched female 

controls were asked to fill in a questionnaire in the hospital. Elevated RR of lung cancer was observed 

for passive smoking from mother (RR = 4.0; p < 0.05) and from husband's father (RR = 3.2; p < 0.05). 

No association was observed between the risk of lung cancer and smoking of husband or passive smoke 

exposure at work. Occupational exposure to iron or other metals also showed high risk (RR = 4.8; p < 

0.05). No appreciable differences in food intakes were observed between cases and controls." 

A.4.26.2. Study Description 

This study was undertaken in Nagoya, Japan, during 1982-85 to investigate the significance of 

passive smoking and other factors such as occupational history, domestic heating system, and dietary 

habits in the etiology of lung cancer in nonsmoking Japanese women. All data were collected specifically 

for this study, which was limited to never-smokers. 

All subjects were obtained from four hospitals in Nagoya. Cases are women with primary lung 

cancer (of any type) treated in these hospitals between August 1982 and July 1985 who reported 

themselves to be never-smokers and consented to interview. Controls are women with a diagnosis other 

than lung cancer from the same or adjacent wards with controls matched 2:1 with cases on age (" 1 year), 

hospital, and date of admission. Cases were not restricted to incident disease, but controls were 

essentially density-sampled by admission date. Data collection was by self-administered questionnaire; 

no attempt at blinding is described. Of 118 female lung cancer cases treated during the study period, 4 

refused to participate in the study and 24 were excluded as current or former smokers. Only a single 

matching control could be found for 17 of the cases. No other information on loss of potential controls is 

provided. There is a total of 90 (163) cases (controls), with 52 (91) currently married to a smoker. Cases 

and controls share identical age ranges (35-81 years) and have nearly identical mean ages (59 years for 

cases, 58 for controls). All cases were histologically diagnosed, excluding secondary lung cancers. 

All study subjects are self-reported never-smokers. A number of individual sources of ETS in the 

home are considered, including smoking by mother, father, husband, father-in-law, mother-in-law, 

offspring, and siblings. For each of these sources, smoking in the home at any time constituted exposure. 

Workplace exposure was characterized simply as presence or absence; for other exposures, the number of 

cigarettes per day was obtained. In addition, data on length of marriage, time spent in the same room as 

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the wife, and total number of cigarettes smoked were obtained for husbands. Exposure data were not 

checked, and marital status was not considered in the design or analysis of the study. The predominant 

type of lung cancer is adenocarcinoma (69 of 90 cases), followed by squamous (13), large cell (4), small 

cell (3), and adenoid cystic carcinoma (1). No data on airway proximity are provided. 

Logistic regression was used to estimate the relative risk for each source of ETS exposure. No 

significant association with lung cancer was noted for smoking by the husband (RR = 1.1), father 

(RR = 1.1), husband's mother (RR = 0.8), offspring (RR = 0.8), or siblings (RR = 0.8); smoking by the 

subject's mother (RR = 4.0) and by the husband's father (RR = 3.2), however, are significant (p < 0.05). 

None of eight dietary factors, including green-yellow vegetable and fruit intake, demonstrated a 

significant association, nor did type of cooking fuel or frequency of cooking oil use. Occupational 

history of exposure to iron or other metals shows a moderately strong but nonsignificant association (RR 

= 2.8), whereas for use of kerosene, coal, or charcoal heating there is a mild association (RR = 1.6-1.7). 

Simultaneous stratification by father-in-law's and mother's smoking indicates that the effects of 

the two exposures are not additive. Smoking by father-in-law, smoking by mother, and occupational 

metal exposure were included simultaneously in a logistic regression model. After adjusting the effect of 

each variable for the other two, the relative risk for maternal smoking, father-in-law's smoking, and metal 

exposure are 2.1, 3.2 (p < 0.05), and 2.4, respectively. The authors conclude that the exposure to tobacco 

smoke from household members (i.e., mother or husband's father) could be associated with female lung 

cancer. Because the precise situation of passive smoking in the home or other places is still unclear, 

however, the authors find that further studies are needed to clarify the significance of passive smoking in 

relation to the etiology of lung cancer in Japanese women. 

A.4.26.3. Comments 

This study employs a moderate number of well-matched cases and controls. Their comparability 

appears good, as supported by the identical age ranges and similar mean age and occupational categories 

for the two groups. A further strength of the study is its lack of reliance on proxy information with 

attendant potential for inaccurate recall. Exposure information was obtained from self-administered 

questionnaires, which eliminates the possibility of interviewer bias but may lead to inaccuracy due to 

misinterpretation of questions or varying care in their completion. Such problems with exposure 

information would tend to mask any actual association. Lung cancer was histologically diagnosed in all 

subjects and secondary lung cancers excluded, so diagnostic accuracy appears good for cases. Control 

diagnoses, however, were not validated, so some smoking-related disorders (in addition to the heart 

conditions noted in 3% of controls) may be included among the controls, a problem that once again would 

tend to reduce any observed association. 

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Restriction of subjects to never-smokers maximizes efficiency because effects of passive smoking 

would likely be dwarfed by active smoking. But it is unclear precisely what subjects were asked about 

their smoking status. Were any cut-points regarding past history, duration, or intensity specified? Thus, 

some misclassification of smoking status may have occurred, and if a greater proportion of persons with 

smoking family members misreport themselves to be never-smokers, this would create an upward bias. 

The authors restrict their assessment of exposure from relatives to at-home smoking, which 

should be more meaningful than total smoking as a potential source of passive smoke exposure. 

Furthermore, they collected data on smoking habits of all relatives, not just spouses or parents, thus 

reducing the chance of missing an exposure source. On the other hand, there is no consideration of total 

household smoking (all sources combined), cumulative exposure (except for husbands), or of pipe or 

cigar smoking; nor is there differentiation of current and former exposure--all potential sources of 

exposure misclassification, which would tend to make an association more difficult to detect. 

Of the several sources of ETS exposure at home, only the relative risks for smoking by the 

mother and by the father-in-law are suggestive, and both of these are significant (p < 0.05). When these 

sources are considered simultaneously, however, and the effect of each is adjusted for the other, smoking 

by the husband's father remains significant (RR = 3.2; p < 0.05) but the effect of mother's smoking is 

diminished (RR = 2.1) and is not statistically significant. Exposure from the father-in-law is, of course, in 

adulthood. There is no evidence of an effect from husband's smoking (RR = 1.1), however, and these 

exposure sources were considered simultaneously so that the effect of one could be adjusted for the other. 

The large number of comparisons (e.g., eight groupings of passive smoke exposure, alternative spousal 

exposure measures, several occupational factors, and eight dietary factors) increases the likelihood that an 

observed relative risk will appear to be significant by chance alone (the effect of multiple comparisons). 

Another aspect of the statistical analysis worth noting is that, although cases and controls appear 

well matched on age, hospital, and hospital admission date, these factors are not included in an adjusted 

analysis of the data (aside from the example with three sources of exposure described above). 

Consequently, some bias due to these factors is a possibility, although the demographic similarities 

between cases and controls makes a large effect unlikely. 

In summary, this study presents some interesting results. It finds a strong (adjusted RR = 3.2) 

and statistically significant association between father-in-law's smoking at home and lung cancer and 

associations for maternal smoking and occupational metal exposure as well. The lack of association for 

any of the other sources of ETS examined could be due to problems with exposure assessment and control 

disease criteria. Equally, however, given the unclear treatment of matching factors in the analysis and the 

number of variables explored, the few substantial associations noted might be due to chance, 

confounding, or both. Were potential confounders clearly treated in their analyses, this study would have 

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made a stronger contribution. As it stands, the study's data are of moderate utility, providing the number 

of comparisons and limitations regarding bias are kept in mind. 

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A.4.27. SOBU (Tier 2) 

A.4.27.1. Author's Abstract 

"A hospital-based case-control study among nonsmoking women was conducted to clarify risk factors in 

nonsmoking females in Japan. Cases consisted of 144 nonsmoking female lung cancer patients, and these were 

compared to 713 nonsmoking female controls. The odds ratios (95% confidence interval) for use of wood or straw 

as cooking fuels when subjects were 30 years old was estimated as 1.77 (1.08, 2.91). For those whose household 

members, other than husbands, had smoked, the odds ratio was estimated as 1.50 (1.01, 2.32). For those whose 

mothers had smoked, the odds ratio was estimated as 1.28 (0.71, 2.31). Use of heating appliances did not show an 

elevated risk. Some points to be noted in this study of low-risk agents for lung cancer are discussed." 

A.4.27.2. Study Description 

This study was conducted in Osaka, Japan, to clarify risk factors for lung cancer in nonsmoking females in 

Japan. Of interest are the roles of both active and passive smoking and other indoor air pollutants, particularly 

smoke or fumes from sources of indoor cooking and heating. This article reports only on female nonsmokers in the 

study, which is not matched on any variables. A very similar article presenting interim results and using slightly 

fewer subjects than the one described here is by Sobue and coworkers (1990). 

Cases consist of all newly admitted lung cancer patients in eight Osaka hospitals between January 1986 

and December 1988. Controls were collected from newly admitted patients in one or two other wards of the same 

hospitals during that period. Almost 90% of the controls were admitted as cancer patients, about half of whom were 

diagnosed with breast cancer. Self-administered questionnaires designed for this study were completed by both 

cases and controls at the time of hospital admission. Cases are incident, and control sampling is density, unmatched 

aside from the time of hospital admission (within 1.5 years). The entire study, including active smokers and males, 

consists of 295 (1,079) female (male) cases and 1,073 (1,369) female (male) controls. Nonsmoking females 

compose 156 cases, of which there was missing information on 12. The resultant number of ETS subjects is 144 

(731) female nonsmoking cases (controls). The age distribution of the cases (controls) is as follows: 40 to 49, 20 

(238); 50 to 59, 34 (229); 60 to 69, 41 (186); and 70 to 79, 34 (78). The corresponding percentages are 14 (33), 34 

(31), 28 (25), and 24 (11), which indicates that controls tend to be younger than cases. Also, the mean age of cases 

(controls) is 60 (56). There was no systematic review of histological diagnosis. All original diagnoses were 

confirmed microscopically, however, and all the pathologists involved in the eight participating hospitals were 

experienced specialists in lung cancer. Thus, the likelihood of secondary lung cancers among the cases should be 

small. 

Several sources of ETS exposure are included, all of which occur in the home. Exposure in adulthood is 

expressed by two measures--smoking by the husband and other household members (the last category consists 

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chiefly of households where the husband's father and/or sons smoke). Three sources of exposure in childhood are 

considered--father smokes, mother smokes, and other household members smoke. No information is provided on 

how exposure to spousal smoking is handled for unmarried women (single, divorced, or separated). The entire 

complement of cases and controls is included in the summary data for each of the five sources of exposure given 

above. If only married women were included in the study, no mention of it was found. 

The histological data for ETS subjects are not classified by exposure to ETS, but the percentage of cases by 

cell type are given: squamous cell (8), small cell (5), adenocarcinoma (78), large cell (5), and other (4). The ETS 

data on spousal smoking consists of 80 of 144 (exposed/total) cases and 395 of 731 controls, for an odds ratio of 

1.13 (95% C.I. = 0.78, 1.63). (Our calculations give 1.06 [0.74, 1.52].) The odds ratio for ETS exposure from other 

household members in adulthood is 1.57 (95% C.I. = 1.07, 2.31). (Our calculated values are 1.77 [1.21, 2.58].) For 

ETS exposure in childhood by the father, mother, and by other household members, the respective odds ratios are 

0.79 (95% C.I. = 0.52, 1.21), 1.33 (95% C.I. = 0.74, 2.37), and 1.18 (95% C.I. = 0.76, 1.84). Tests were conducted 

by the Mantel-Haenszel procedure, with stratification by age and education (two levels). Analysis by logistic 

regression, adjusted for age at time of hospitalization, was conducted for two of the exposure measures described 

above with similar outcomes. Based on this evidence, the author concludes that for childhood exposure, a slight 

increase of risk was suggested for those with smoking mothers, although statistical significance was not observed. 

For exposure in adulthood, an elevated risk was estimated for those with smoking household members other than 

husbands. 

The statistical analysis includes exposure to sources other than ETS, namely, the use of wood or straw as 

cooking fuel, the use of heating equipment that pollutes the room with combustion products, and the use of charcoal 

foot warmers. All exposures considered, including ETS, are smoke or fumes from products burned indoors. It is 

concluded that significantly elevated risks were observed for subjects who had used wood or straw as cooking fuels 

at 30 years of age (OR = 1.89; 95% C.I. = 1.16, 3.06). No elevated risks were found for sources of indoor heating 

(use of kerosene, gas, coal, charcoal, and wood stoves without chimneys). Similarly, no significance was found for 

the use of charcoal foot warmers, a practice that was popular until the 1960s. 

A.4.27.3. Comments 

With 144 cases and 731 controls, the sample size is larger than many of the other case-control studies on 

ETS. Information on cases and controls was obtained by self-administered questionnaire, which is generally 

considered less reliable than face-to-face interviews. The questionnaires were presumably completed by the 

subjects themselves in all cases, however, which is preferable to proxy-supplied information. The information 

supplied was not verified from other sources, as noted by the authors in reference to testing for biomarkers of 

exposure to tobacco smoke (they note that laboratory tests can only detect recent exposure, but they could still be 

useful in eliminating current smokers who may misreport themselves as never-smokers). Although cases and 

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controls were newly diagnosed patients within a short time period in the eight participating hospitals and were 

supplied with the same questionnaire, there are still some questions regarding the comparability of cases and 

controls and their representativeness of the target population. 

Controls tend to be younger than cases: While mean ages are 56 and 60, respectively, 33% of controls, 

compared with 14% of cases, are below the age of 40. Controls also tend to be more educated than cases, with 69% 

of controls having completed 10 or more years of education compared to 52% of cases. Differences in age and 

educational level further reflect differences in lifestyle and socioeconomic status that may affect risk of disease. 

Also, the controls are predominantly cancer patients too, almost half with breast cancer, suggesting that the controls 

may be a biased sample (as noted by the authors). On the other hand, exclusion of breast cancer controls reportedly 

leaves the results unchanged. Furthermore, the statistical analysis stratifies on age and education, so even though 

cases and controls were not strictly matched on these variables, the reported results should not be due to 

confounding by either of these factors. 

Although some of the issues and reservations described above are methodological in nature and apply to 

the study throughout, others are specific to the ETS data alone. For example, one might expect a question regarding 

the use of cooking with wood or straw at age 15 and at age 30 to be open to little subjective interpretation or error in 

recall, presuming that methods of cooking persisted for several years between changes within a household. 

Although there is some suggestive evidence of increased lung cancer from ETS exposure, the statistical evidence 

may be stronger for an association between lung cancer and use of wood or straw for cooking at age 30. Further 

support is provided by the observation that among those who had used wood or straw for cooking at age 30, 90% 

had also used those fuels at age 15, suggesting extended exposure in most cases. The age distribution of those 

exposed to wood or straw cooking is not given, but exposure at 30 years of age and before would allow for the long 

latency expected for lung cancer because 86% of the patients are at least 50 years of age. 

The smoke from cooking sources may obscure or distort any impact of ETS exposure because the two 

sources probably contain some of the same carcinogens. The temporal dimension of exposure also may be a factor 

because indoor smoke from cooking may be less common at present than 30 years ago in comparison to ETS 

exposure. Further statistical analysis to adjust the effect of ETS exposure for the presence of smoke from cooking 

might aid interpretation of the results in this study. 

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A.4.28. STOC

A.4.28.1. Author's Abstract

(Note: This study has not been published. Only the abstract is available, which is given below.) 

"Risk factors for lung cancer among women who had never smoked cigarettes were examined in an 

ongoing, population-based, case-control study conducted in Florida. One hundred and twenty-four primary 

carcinomas of the lung and 241 control women who had never smoked were included. Results suggest that 

childhood and adult exposures to environmental tobacco smoke may increase the risk of lung cancer among women 

who never smoked cigarettes. Having a husband who smoked cigarettes resulted in a statistically significant 

increase in risk of lung cancer among women who had never smoked, with an odds ratio of 1.8 (95% C.I. 1.1, 2.9). 

A 40% increase in risk was observed among women with less than 25 years of exposure to a spouse who smoked, 

when compared with women who reported their spouse had never smoked, with the risk increasing to 60% among 

women exposed 25 years or longer. 

When exposure to tobacco smoke in childhood was considered, the data were less consistent. Having a 

parent who had smoked during the respondent's childhood did not increase the risk of lung cancer. However, 

among those respondents with high levels of exposure to parental smoking, an excess risk, although not statistically 

significant, was observed. Never- smoking women who accumulated 25 or more exposure years experience a 70% 

increase in risk (OR = 1.7, 95% C.I. 0.8, 3.6) of lung cancer compared with women who reported neither parent had 

smoked cigarettes." 

A.4.29. SVEN (Tier 2) 

A.4.29.1. Author's Abstract 

"In a population-based case-control study, the association between female lung cancer and some possible 

etiological agents was investigated: 210 incident cases in Stockholm County, Sweden, and 209 age-matched 

population controls were interviewed about their exposure experiences according to a structured questionnaire. A 

strong association between smoking habits and lung cancer risk was found for all histological subgroups. Relative 

cancer risk was found for all histologic subgroups. Relative risk for those who had smoked daily during at least 1 

year ranged between 3.1 for adenocarcinoma to 33.7 for small cell carcinoma in a comparison with never-smokers. 

All histological types showed strong dose-response relationships for average daily cigarette consumption, duration 

of smoking, and cumulative smoking. There was no consistent effect of parental smoking on the lung cancer risk in 

smokers. Only 38 cases had never been regular smokers and the risk estimates for exposure to environmental 

tobacco smoke were inconclusive. The high relative risks of small cell and squamous cell carcinoma associated 

with smoking may have relative implications for risk assessments regarding passive smoking." 

A.4.29.2. Study Description 

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This study was undertaken in Stockholm County, Sweden, from 1983 to 1986 to investigate the association 

between female lung cancer and some possible etiologic agents, particularly active and passive smoking. Because 

active smoking was an exposure of interest, cases and controls were not matched on smoking status; thus, the ETS 

study population is unmatched. 

Cases are Swedish-speaking women with primary lung cancer from three Stockholm County hospitals who 

were willing and able to be interviewed between September 1983 and December 1985. Cases with carcinoid tumors 

were excluded from the ETS analysis. Both population and hospital-based control groups were assembled. 

Population controls were women randomly selected from the county population register, matched to a case on 

birthdate and interviewed between September 1983 and December 1986. Hospital controls were subjects originally 

interviewed as potential lung cancer cases but subsequently diagnosed with nonmalignant conditions. Population 

controls were enlisted and interviewed as soon as a case's diagnosis was confirmed, but because this confirmation 

took as long as a year after the interview, controls were not density sampled. Unblinded interviews were conducted 

face-to-face with all cases (and hospital controls) and 58% of the total population controls; the remainder were 

interviewed by telephone. 

After exclusion of 21 potential cases due to initial diagnostic uncertainty, refusal, or illness precluding 

interview, 210 confirmed cases remained. Elimination of 172 ever-smokers and four subjects with carcinoid or notmicroscopically-confirmed tumors left 34 never-smoking cases. Similarly, 209 population and 191 hospital controls 

were included in the total study, but a combined total of only 174 were never-smokers. The total case population 

averaged 62.5 years of age, but no other demographic information regarding cases or controls is provided. All cases 

used in the ETS analyses were histologically or cytologically confirmed primary lung cancers. 

Daily smoking for at least 1 year is the criterion for a smoker; all other persons are considered neversmokers. Pipe and cigar smoking are never specifically addressed. Exposure to ETS is calculated for four sources: 

mother, father, home, and work. Having a smoking mother or father (at any time during ages 0-9 years) constitutes 

exposure to that particular source, whereas the presence of a smoker at home and work constitutes exposure. 

Adulthood and total lifetime exposure are considered separately for home and workplace exposure. Exposure levels 

are arbitrarily scored 1 for nonexposure, 2 for exposure to one source, and 3 for exposure to both sources in trend 

analyses of never-smokers, where exposures are considered in pairs (i.e., maternal and paternal smoking, home and 

workplace exposure). No other units of ETS exposure are used. Adenocarcinomas constituted 22, squamous cell 5, 

and small cell 2 of the 34 lung cancers occurring among never-smokers in the ETS population; no further histologic 

details regarding the ETS study population are provided. 

To maximize available case numbers, parental smoking was first analyzed among all cases and community 

controls using stratification to adjust for active smoking (cig./day) and age. A risk of 1.8 (95% C.I. = 0.5, 7.0) was 

estimated for maternal smoking and 0.8 (0.3, 1.4) for paternal smoking. A trend analysis in which maternal, 

paternal only, and no parental smoke exposure were scored as 3, 2, and 1, respectively, revealed no indication of 

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trend (p = 0.9). Analyses restricted to never-smokers used both community and hospital-based controls combined. 

Among cases (controls), for childhood up through 9 years of age, 3 (5) had smoking mothers, 12 (71) had smoking 

fathers (but not mothers), and 19 (98) were unexposed. This yielded an age-adjusted risk estimate of 3.3 for 

maternal smoking (with or without paternal smoking) and 0.9 for paternal smoking during childhood. Adult 

exposure at home and at work yielded an estimated risk of 2.1, whereas exposure at home or work yielded a risk of 

1.2. For lifetime exposure, the estimated risks for exposure as both a child and adult and as either a child or an 

adult were 1.9 and 1.4, respectively. None of these associations were statistically significant, and no significant 

trends were observed. The authors conclude that the results pertaining to ETS in the present study were not 

conclusive. The small number of never-smokers among the cases could be one important reason. It should be 

noted, however, that most of the point estimates of relative risk were greater than unity, which agree with results 

from previous studies on ETS exposure and with risk estimates concerning active smoking. 

A.4.29.3. Comments 

This study was undertaken to explore the role of active as well as passive smoking in lung cancer. After 

exclusion of active smokers, the available number of cases is too small to yield much statistical power. 

Cases and population-based controls were initially matched on date of birth, but this matching was 

abandoned in the ETS analysis; furthermore, unmatched hospital-based controls are combined with the populationbased controls in most analyses to boost available numbers. The comparability of these groups is thus unclear, and 

the authors provide no demographic comparisons to facilitate assessment of this potential problem. The reported 

similarity of results using only population-based controls is reassuring, but no details are provided as to how similar 

results actually were. 

Diagnostic misclassification of cases is unlikely, given the histological or cytological confirmation of all 

cases and exclusion of secondary cancers. All cases were interviewed face-to- face, but 42% of controls were 

interviewed by telephone. The accuracy of responses may thus be lower for controls than for cases. In addition, 

because interviews were not conducted blindly, inflation of estimated associations through interview bias is 

possible. A potential bias is also introduced by the rather large amount of active smoking required for classification 

as an ever-smoker. This allows considerable active smoking among persons in the never-smoker group, the effect 

of which could mask an effect of passive exposure, or, if co-varying positively with passive smoking, cause 

overestimation of association. 

The first set of analyses of paternal and maternal smoking includes ever-smokers while attempting to adjust 

for active smoking on the basis of average daily cigarette consumption. The adequacy of this adjustment is 

questionable given the large estimated risks associated with active smoking relative to those posited for passive 

smoking, so the elevated estimated risks for maternal smoking obtained in these analyses are of questionable 

validity. 

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Restriction of the analyses to never-smokers similarly produces an elevated odds ratio for maternal 

smoking of 3.3, but the numbers involved (three cases and five controls) are so small that this value is quite 

unstable. A pattern of increasing estimated risk with increasing sources of exposure (at home or at work) as an 

adult and increasing periods of exposure (in childhood or adulthood) over the lifetime is suggestive of an 

association between lung cancer and ETS, but again small numbers preclude statistical significance of these results. 

Restriction of the study population to females rules out the possibility of a gender-related effect. The 

likelihood of an ethnicity effect is reduced by restriction to Swedish-speaking residents of Stockholm County, and 

age is reportedly controlled for in all analyses. No other potential risk modifiers are addressed. For example, 

marital status is not considered in the analyses of spousal smoking, leaving open the possibility that nonsmokingrelated differences between married and unmarried women contributed to the observed association. The reported 

similarity of results when only population controls were used instead of hospital and population controls combined 

provides a general argument against bias due to source of controls, although no specifics regarding the degree of 

similarity were supplied. 

In summary, this study presents consistent evidence of associations between lung cancer and maternal, 

home, and workplace passive smoking exposure. Limited numbers preclude statistical significance, and interviewer 

bias or effects due to dietary or other factors cannot be ruled out as contributors to the observed results. Bearing 

these limitations in mind, the study's results are inconclusive but (excluding the analyses that include active 

smokers) do make a useful contribution to the pool of information available regarding ETS and lung cancer. 

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A.4.30. TRIC (Tier 3) 

A.4.30.1. Author's Abstract 

"Fifty-one women with lung cancer and 163 other hospital patients were interviewed regarding the 

smoking habits of themselves and their husbands. Forty of the lung cancer cases and 149 of the other patients were 

nonsmokers. Among the nonsmoking women, there was a statistically significant difference between the cancer 

cases and the other patients with respect to their husbands' smoking habits. Estimates of the relative risk of lung 

cancer associated with having a husband who smokes were 2.4 for a smoker of less than one pack and 3.4 for 

women whose husbands smoked more than one pack of cigarettes per day. The limitations of the data are 

examined; it is evident that further investigation of this issue is warranted." 

A.4.30.2. Study Description 

This study was undertaken in Athens, Greece, to investigate the relationship of spousal smoking and lung 

cancer. All female Caucasian Athenian residents admitted to one of three chest or cancer hospitals in Athens and 

assigned a final diagnosis of lung cancer other than adenocarcinoma and alveolar carcinoma from September 1978 

through June 1980 were interviewed by a physician. Controls were gathered from nonsmoking female Caucasian 

Athenian patients hospitalized during the same time period in the Athens Orthopedic Hospital. Some prevalent 

cases were thus presumably included, so control sampling probably approximated a density approach but did not 

strictly conform to one. 

Diagnostic information was obtained from patients' charts. Exposure information was obtained by face-toface unblinded interviews conducted by the same physician for all subjects. A total of 51 cases and 163 controls 

were interviewed. Of these, 11 cases and 14 controls reported themselves to be active smokers, leaving 40 cases 

and 149 controls as ETS subjects. No interview refusals are reported. Mean age of cases (controls) is 62.8 (62.3) 

years. Husband's education was marginally higher in controls than cases, with 63% and 58% of spouses having 

completed primary school, respectively. No other demographic comparisons are reported for the ETS subjects 

alone. For the sample population including smokers, factors such as age, duration of marriage, occupation, 

education, and urban versus rural residence are all similar for cases and controls, except once again educational 

level is slightly higher for controls. There is no indication that verification of diagnosis or exclusion of secondary 

lung cancers was undertaken in cases. Of the 51 total cases, 14 were diagnosed histologically, 19 cytologically, and 

18 by radiological or clinical means. No breakdown is given for the ETS subjects alone. 

The study classifies as nonsmokers both reported never-smokers and former smokers who quit more than 

20 years ago. It is not mentioned whether cigar and pipe smoking are considered as sources of exposure. 

Nonsmoking women are considered exposed to ETS if they are married to a man classified as a smoker. The 

average number of cigarettes smoked per day by the husband and the number of years of marriage are used to 

estimate the total number of cigarettes smoked by the husband during marriage. No data on childhood or 

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nonspousal ETS exposure were collected. Single women are grouped with women married to a nonsmoker and are 

thus considered unexposed. Widowed or divorced women were classified according to their former husband's 

smoking status on the assumption that smoking stopped at death or divorce. No checks of exposure information are 

reported. 

For ETS subjects, the number of cases (controls) exposed over the total is 29 to 40 (78/149). The crude 

odds ratio calculated by the reviewers is 2.4 (95% C.I. = 1.12, 5.16). The results presented in the article are all 

stratified by level of husband's smoking. The odds ratios are 1.8, 2.4, and 3.4 when the husband is a former smoker, 

smokes 1 to 20 cigarettes per day, and smokes 20 or more cigarettes per day, respectively. No confidence intervals 

are given, but a test for upward trend was statistically significant (p < 0.02). When ETS exposure is estimated by 

total number of cigarettes smoked during marriage, odds ratios (1.3, 2.5, and 3.0) increase with cumulative exposure 

(1-99, 100-299, and 300+ thousand, respectively). The upward trend remains statistically significant at p < 0.02. 

No analyses adjusted for age or other factors. With regard to age and other demographic variables, the authors 

conclude from the similarity of cases and controls that it is not necessary to stratify for these variables in the 

analysis, particularly because none is significantly associated with smoking in the study. 

The authors note that this study has obvious limitations and is offered principally to suggest that further 

investigation of this issue should be pressed. Most seriously, the numbers of cases are small. Nevertheless, the 

association is in the direction expected if passive smoking is related to lung cancer, and the outcome is unlikely to 

be due to chance. Other limitations noted include the high percentage (35%) of cases lacking cytology and the 

selection of controls from a hospital different from those of the cases; it is argued, however, that neither of these 

appears to be consequential. The observation is made that it is potentially easier to detect an effect of passive 

smoking in the Greek population than in most Western populations, because in the latter groups, the overwhelming 

effects of active smoking, together with the high correlation between smoking habits of spouses, would tend to 

confound and conceal the lesser effects of passive smoking. 

A.4.30.3. Addendum 

In a letter to the editor of Lancet in 1983, Trichopoulos et al. released a data table derived from extension 

of subject collection through December 1982. This nearly doubled the sample size used in the 1981 publication, 

yielding 77 nonsmoking cases (102 total) and 225 smoking controls (251 total). The crude odds ratio calculated by 

the reviewers is 2.08 (95% C.I. = 1.20, 3.59). The results for the expanded study show very little change; 

(estimated) relative risks when husbands are former smokers (1-20 cig./day and > 20 cig./day) compared with 

nonsmokers are 1.95, 1.95, and 2.54, respectively. The test for upward trend in the dose-response is significant 

(p = 0.01). No other analyses are presented. 

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A.4.30.4. Comments 

This study was conceived and undertaken to explore the association of spousal smoking with lung cancer 

and does not rely on a preexisting data set. Thus, the investigators were in a position to design their selection and 

data collection to maximize the strength of their findings. This did not, however, prevent the appearance of some 

design and analytical flaws. 

Demographics of the total case and control populations are very similar. All subjects in the spousal 

smoking analysis are resident Athenian nonsmoking women hospitalized in the same area of Athens; case and 

control groups have very similar mean ages, and their husbands are comparable in education. Thus, the groups 

probably have good demographic comparability, although it would have been helpful if the detailed demographic 

comparisons were focused on the nonsmokers alone. Most of the controls (108 out of 163) were being treated for 

fractures, a relatively minor and nonchronic illness compared with lung cancer, which may make them more 

representative of the general community than of hospitalized patients as a whole. This should reduce the problem of 

inclusion of smoking-related illnesses in the control group. 

Although the researchers sought to exclude adenocarcinomas and alveolar carcinomas, presumably 

considering these would be less smoking related, nearly two-thirds of the cases were not histologically confirmed, 

so an indeterminate number of these cell types was probably included. More important, the infrequency of 

histologic confirmation and lack of mechanisms to verify diagnoses or primary tumor status introduces potential for 

misclassification. The likely effect is a bias toward no association. 

The researchers clearly devoted considerable thought to the smoking and exposure criteria, particularly 

with regard to changes in smoking and marital status over time. Single women were, however, automatically 

classified as unexposed. The authors contend that this is warranted by the traditional nature of Greek society and 

report that analyses restricted to married women result in similar, and still statistically significant, associations, 

although with somewhat lower estimated risks. There is a small reduction in the odds ratios after exclusion of 

single women, however, and the restriction of the full analyses and results to married women may have been useful. 

Another issue related to exposure concerns inclusion of former smokers in the study, provided they had not 

smoked for at least 20 years. Active smoking 20 to 30 years before the onset of lung cancer may be of etiological 

relevance, however, in view of a long latency period for lung cancer. Although use of the same interviewing 

physician for all subjects eliminates the problem of interobserver variability, it leaves open the potential problem of 

interviewer bias in exposure assessment, presumably toward a positive association, because the interviews were 

apparently conducted unblinded (virtually unavoidable with regard to diagnosis, given that controls were drawn 

from orthopedic trauma and rheumatology wards). 

A larger concern, however, is the potential effect of risk factors or modifiers not addressed in the analysis. 

The authors contend that the similar distribution of demographic variables between cases and controls eliminates the 

need to consider these variables in the analyses, but adjusting for relevant variables is recommended even in a 

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matched study (see Section 5.4.1). More convincing is the contention that these variables were not significantly 

associated with smoking in these data, although no specifics are included. The appearance of a statistically 

significant trend for ETS exposure measured by either current spousal smoking or cumulative cigarette consumption 

during marriage lends further support to an association between spousal smoking and increased lung cancer 

incidence. Potential factors such as diet, cooking, and heating practices, however, are not addressed. 

Overall, the issues addressed above would probably produce a conservative bias, resulting in an 

underestimate of the degree of association. The study's basic design is sound. It provides statistically significant 

evidence of dose-response, and although the limitations described above should be borne in mind, it provides useful 

data for assessment of the relationship between ETS and lung cancer. 

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A.4.31. WU (Tier 2) 

A.4.31.1. Author's Abstract 

"A case-control study among white women in Los Angeles County was conducted to investigate the role of 

smoking and other factors in the etiology of lung cancer in women. A total of 149 patients with adenocarcinoma 

(ADC) and 71 patients with squamous cell carcinoma (SCC) of the lung and their age- and sex-matched controls 

were interviewed. Personal cigarette smoking accounted for almost all of SCC and about half of ADC in this study 

population. Among nonsmokers, slightly elevated RRs for ADC were observed for passive smoke exposure from 

spouse(s) (RR = 1.2; 95% C.I. = 0.5, 3.3) and at work (RR = 1.3; 95% C.I. = 0.5, 3.3). Childhood pneumonia (RR 

= 2.7; 95% C.I. = 1.1, 6.7) and childhood exposure to coal burning (RR = 2.3; 95% C.I. = 1.0, 5.5) were additional 

risk factors for ADC. For both ADC and SCC, increased risks were associated with decreased intake of β-carotene 

foods but not for total preformed vitamin A foods and vitamin supplements." 

A.4.31.2. Study Description 

This study was undertaken in California during 1981 and 1982 to investigate the role of smoking and other 

factors in the etiology of lung cancer in women. These other factors included prior lung disease, coal heating and 

cooking, diet, and occupation. Both active and passive smokers are included; some of the ETS analyses retain 

active smokers while attempting to adjust for smoking status. 

Cases are white female English-speaking Los Angeles County residents under 76 years of age at time of 

diagnosis with primary adenocarcinoma or squamous cell cancer of the lung between April 1, 1981, and August 31, 

1982. Cases are restricted to U.S.-, Canadian-, or European-born individuals with no history of prior cancer other 

than nonmelanoma skin cancer. Controls are density sampled, matched individually on neighborhood and age (" 5 

years), and meet all case criteria (except, of course, diagnosis of lung cancer). The L.A. County tumor registry was 

used to identify incident cases for inclusion in the study, whereas controls were recruited house to house. 

Interviews to obtain exposure data were conducted by telephone with participating subjects, apparently unblinded. 

A total of 490 eligible cases were identified; 270 were not interviewed because they were too ill or had 

died (190), their physician refused permission to contact them (28), they could not be located (8), or they refused 

(44). Those not interviewed did not differ significantly from those interviewed with regard to age or their marital, 

religious, or smoking status as recorded on registry records. Refusals eliminated 70 potential controls. The case 

and control populations had nearly identical mean ages for adenocarcinoma, 59.7 versus 59.5 years, respectively, 

and for squamous cell cancer, 61.4 versus 61.1 years, respectively. No other demographics are provided. 

Histologic diagnoses were obtained for all cases. 

For spousal smoking, exposure constitutes having a spouse who smoked while living with the subject. For 

workplace smoke, exposure is based on the opinion of the subject. It is not clear whether for the lung cancer 

analyses, parental smoking refers only to adult life (as for spousal and workplace exposure) or to the childhood and 

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teen years (as was stipulated for coal and preadult lung disease exposures). Adult life seems most probable. Units 

of exposure for spousal and parental smoking are cigarettes per day and years of exposure, apparently entered into a 

regression model as a combined variable; for occupational exposure, units are in years of exposure. Exposure data 

were apparently not checked, treatment of cigar and pipe smoking is never mentioned, and no results are reported 

for household smoking aside from spouse and parents, although information on this exposure was collected. Nevermarried women were excluded from the spousal smoking analysis, but marital status was not otherwise considered 

in the analyses. The only histologic or airway proximity information provided for the ETS subjects is that 29 

adenocarcinomas occurred among nonsmokers, 12 of which were bronchoalveolar. 

The total study population includes 220 cases and an equal number of matched controls. Of the cases, 149 

are adenocarcinoma and 71 are squamous cell. Nonsmokers constituted 29 of the adenocarcinoma cases and 62 of 

the corresponding controls, while composing 2 of the squamous cell cases and 30 of the controls. No raw data are 

presented regarding passive smoking and lung cancer. Logistic regression analysis of matched pairs was used in all 

calculations. Results restricted to nonsmokers are presented only for adenocarcinoma. An estimated relative risk of 

1.2 is found for spousal smoking, 1.3 for workplace exposure, and 0.6 for smoking by either parent. None of these 

estimates was statistically significant. Exposure from spouses and at work, however, shows a dose-response trend 

with years of exposure, yielding estimated relative risks of 1.0, 1.2, and 2.0, for 0, 1 to 30, and 30 or more years of 

exposure, respectively. 

Analyses that include active smokers but attempt to adjust for them by including the number of cigarettes 

smoked per day and age at start of smoking in a logistic regression model are presented for both lung cancer types. 

For adenocarcinoma, estimated relative risks for maternal, paternal, spousal, and workplace exposure of 1.7, 1.3, 

1.2, and 1.2, respectively, were obtained. For squamous cell cancer, maternal, paternal, spousal, and workplace 

relative risks are 0.2, 0.9, 1.0, and 2.3, respectively. None of these estimates is statistically significant. 

History of lung disease at least 5 years prior to diagnosis of lung cancer reportedly had no significant 

association with lung cancer. History of lung diseases before age 16 yielded a significant association for pneumonia 

(RR = 2.7 [95% C.I. = 1.1, 6.7] for adenocarcinoma and 

RR = 2.9 [95% C.I. = 0.5, 17.4] for squamous cell cancer) but not for six other diseases. 

Heating or cooking with coal during the childhood and teenage years is also significantly associated with 

lung cancer (RR = 2.3 [95% C.I. = 1.0, 5.5] for adenocarcinoma and RR = 1.9 [95% C.I. = 0.5, 6.5] for squamous 

cell). Among dietary factors, low beta carotene consumption is significantly associated with adenocarcinoma (RR = 

2.7) and mildly associated with squamous cell (RR = 1.5). Diets low in dairy products and eggs have similar 

relative risk values. No significant associations were noted for vitamin A consumption, occupation, or other health 

history factors not previously considered. 

The authors conclude that the etiology of squamous cell carcinoma can be explained almost entirely by 

cigarette smoking. Cigarette smoking, however, explains only about half of the adenocarcinoma cases. On the 

A-129
basis of this study, childhood lung disease and exposure to coal fires in childhood explain at least another 22% of 

adenocarcinoma cases. Passive smoking and vitamin A may be involved, but more research is needed to clarify 

their roles in lung cancer etiology. 

A.4.31.3. Comments 

This study took particular care with its treatment of case and control assembly. Extensive inclusion criteria 

extending to both groups, matching not only on age but neighborhood of residence, and retention of matching 

through analysis all bode well for comparability of cases and controls. The virtually identical mean ages of cases 

and controls indicate the success of these efforts. In addition, exclusive use of incident cases reduces the potential 

for selection bias, and density sampling of controls reduces potential problems with temporal variation. The only 

real fault in the treatment of cases and controls is the failure to provide any demographic comparison other than for 

age, thus denying concrete confirmation of the expected high case-control comparability. 

Case diagnoses are likely to be accurate, because all were histologically diagnosed, making 

misclassification unlikely and making cell-type-specific analyses possible. Although no one pathologist or team 

verified these determinations, the authors note that there is generally good interobserver agreement for the cell types 

included in this study. Potentially eligible cases not interviewed due to illness, refusal, or other reasons did not 

differ significantly in demographic or smoking status from those actually interviewed, again arguing against biased 

selection. 

No proxy interviews were used, and all subjects were English-speakers, enhancing the chances of 

obtaining accurate exposure information. On the other hand, interviews were by telephone--possibly decreasing 

accuracy relative to face-to-face interviewing--and apparently unblinded, thus introducing possible interviewer bias 

toward positive results. 

Collection of exposure data seems generally adequate, except that treatment of pipe and cigar smokers is 

not described. This is coupled with an uncertain definition of parental smoking and lack of treatment of household 

smokers other than parents or spouses in the analyses, despite collection of data on this point. These uncertainties 

probably translate into nondifferential exposure misclassification, biasing results toward the null. 

The analyses suffer from the common problem of restricted numbers of nonsmoking cases--29 for 

adenocarcinoma and only 2 for squamous cell. Some factors examined are restricted to nonsmokers alone for 

adenocarcinoma, but for most analyses, an adjustment for active smoking by logistic regression modeling was 

attempted. The adequacy of such adjustment may be questionable. For adenocarcinoma, however, the results for 

passive smoking were very similar, regardless of whether restriction or adjustment was used. Further, a doseresponse pattern was seen for cumulative years of spousal and workplace exposure among nonsmokers. The results 

of the analyses for squamous cell are too unstable to be meaningful, given the paucity of cases. 

The findings of substantial associations between lung cancer (or, at least, adenocarcinoma) and childhood 

A-130
pneumonia and coal burning are of interest. It must be borne in mind that seven adult respiratory diseases 

(including pneumonia) as well as six other childhood respiratory diseases were examined, so the possibility that the 

pneumonia association was an artifact of multiple comparisons cannot be ruled out. History of hysterectomy and 

multiparity showed nearly significant associations with adenocarcinoma, but it is not clear how many other health 

history factors also were considered. Coal burning has been associated with lung cancer in several other studies. 

Similarly, as in several other studies, one found an association with low beta carotene intake, but there was no 

evidence of a dose-response gradient, and no significant association was found for preformed vitamin A. The 

strongest association with a dietary factor was actually that for low intake of dairy products and eggs, which showed 

a consistent dose-response pattern. The use of a matched-pair analytical approach controls for effects of age or 

neighborhood, which also reduces the likelihood of neighborhood-related factors such as socioeconomic status as 

major sources of bias. Confounding due to active smoking can be ruled out in the passive smoking results for 

adenocarcinoma and is not likely in regard to other factors given adjustment for this variable in all analyses. 

Likewise, the authors report that adjustment for childhood pneumonia, coal burning, and beta carotene intake did 

not alter their results. Strangely, however, no adjustment for dairy product and egg intake--the dietary factor with 

the most convincing association with lung cancer in their data--was carried out. 

Overall, this study's results are consistent with a mild association between spousal and workplace ETS 

exposures and lung adenocarcinoma, although they support no such association for parental smoking. In addition, 

the study raises childhood pneumonia, coal burning during early life, low intakes of beta carotene, and low intake of 

dairy products and eggs as potential moderate risk factors that should be considered by future studies. The results 

for squamous cell carcinoma are uncertain given the small number of nonsmoking cases available, and in all 

instances, they lack statistical significance due to sample size limitations. Thus, the study provides useful 

information on the relationship of adenocarcinoma of the lung with ETS and a number of other factors; information 

regarding squamous cell cancer is of less utility for the objectives of this report. 

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A.4.32. WUWI (Tier 4) 

A.4.32.1. Author's Abstract 

"A case-control study of lung cancer involving interviews with 965 female patients and 959 controls in 

Shenyang and Harbin, two industrial cities that have among the highest rates of lung cancer in China, revealed that 

cigarette smoking is the main causal factor and accounted for about 35% of the tumors among women. Although 

the amount smoked was low (the cases averaged eight cigarettes per day), the percentage of smokers among women 

over age 50 in these cities was nearly double the national average. Air pollution from coal burning stoves was 

implicated, as risks of lung cancer increased in proportion to years of exposure to Kang and other heating devices 

indigenous to the region. In addition, the number of meals cooked by deep frying and the frequency of smokiness 

during cooking were associated with risk of lung cancer. More cases than controls reported workplace exposures to 

coal dust and to smoke from burning fuel. Elevated risks were observed for smelter workers and decreased risks for 

textile workers. Prior chronic bronchitis/emphysema, pneumonia, and recent tuberculosis contributed significantly 

to lung cancer risk, as did a history of tuberculosis and lung cancer in family members. Higher intake of carotenerich vegetables was not protective against lung cancer in this population. The findings were qualitatively similar 

across the major cell types of lung cancer, except that the associations with smoking and previous lung diseases 

were stronger for squamous/oat cell cancers than for adenocarcinoma of the lung." 

A.4.32.2. Study Description 

The objective of this study was to evaluate the role of potential risk factors for lung cancer in Harbin and 

Shenyang, two cities among those with the highest mortality rate for lung cancer in China. Active smokers are 

included in the cases, so data on ETS subjects constitute a subset of the whole study. 

Cases consist of female residents under age 70 newly diagnosed with primary lung cancer in about 70 

participating hospitals in Harbin and Shenyang between 1985 and 1987. Controls are female residents randomly 

selected from the general population of these cities and frequency matched by 5-year age group to the age 

distribution of female lung cancer cases reported in the cities in 1983. Trained interviewers collected information 

on smoking habits, diet, cooking and heating practices, and other factors from subjects in face-to-face unblinded 

interviews. 

A total of 1,049 qualifying cases were found, including both ever-smokers and never-smokers, of which 

405 were diagnosed by histology, 309 by cytology, and 351 by radiology or clinical means. (Note: These 

diagnostic numbers do not total 1,049. The 351 figure may be intended to be 251, which would give a total of 965 

diagnoses, about the number of cases interviewed.) Of these, 85 either died prior to interview, refused to 

participate, or could not be located. Mean age of participating cases was 55.9 years, whereas that of the 959 

controls was 55.4 years. Nonsmokers compose 417 of the interviewed cases and 602 of the controls. 

A smoker is defined as a person who has smoked cigarettes for 6 months or longer, so a nonsmoker 

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apparently may have smoked for up to 6 months. Information on all types of tobacco products smoked was 

collected. Sources of ETS exposure include smoking by any household cohabitant and smoking by individuals 

(spouse, mother, and father) over the course of the subject's lifetime. Exposure at the workplace is also addressed. 

ETS exposure in the home is expressed in terms of cigarettes per day and number of years smoked; no units of 

measurement are used for workplace smoking. No checks on exposure data were undertaken. Marital status of 

subjects is not discussed. Of the cases with histological or cytological data, adenocarcinomas compose 310 

(41.7%), squamous cell cancers 201 (28.9%), small and oat cell cancers 117 (16.8%), and large cell or unspecified 

types 66 (9.5%). No data on airway proximity or diagnostic breakdowns limited to nonsmokers are provided. 

Statistical analyses of potential risk factors, including ETS, largely include data on active smokers and then 

adjust for the effect due to smoking by logistic regression, along with other potential confounders such as age, 

education, and location (Shenyang vs. Harbin). These analyses indicate no increase in risk from household sources 

of ETS, with estimated relative risks of 0.8 (household cohabitants), 0.9 (spouse), 1.0 (mother), and 1.0 (father). 

The estimated risk for workplace exposure is nonsignificant (RR = 1.2). Restriction of analyses to ETS subjects 

alone (i.e., only the nonsmokers) produced similar results, with estimated relative risks of 0.7 for general cohabitant, 

0.7 for spouse, 0.9 for mother, 1.1 for father, and 1.1 for workplace exposure. The ETS exposure from spousal 

smoking is significantly low (i.e., associated with a decrease in lung cancer by this analysis, as apparent from the 

confidence interval; RR = 0.7; 95% C.I. = 0.6, 0.9). 

The smoking-adjusted analyses indicate associations with lung cancer for several types of heating devices, 

including kangs (brick beds heated by pipes from the stove or by burners directly underneath), coal stoves, and 

heated brick walls or floors. The risk associated with the use of burning kangs (those heated by stoves underneath) 

shows an upward trend with years of use, becoming statistically significant at 21 or more years of use (RR = 1.5; 

95% C.I. = 1.1, 2.0). Significantly elevated risks are also associated with use of heated brick walls or floors (RR = 

1.5 [1.1, 2.1] for 1-20 years of use; RR = 1.4 [1.1, 1.9] for > 20 years). Nonsignificant increases in risk are noted 

for use of kangs of all types, coal stoves, and coal burners; nonsignificant reductions in risk are indicated for 

noncoal stoves and central heat. Deep-frying cooking at least twice a month and eye irritation during cooking are 

both significantly associated with lung cancer, as are regular intake of animal protein and fresh fruit. (Note: 

Multiple comparisons may be a factor for the apparent significance of some items, as discussed further in the next 

section.) 

The authors find no overall association between lung cancer and ETS exposure. On the other hand, coal 

burning, exposure to cooking oil fumes, and chronic lung disease all may be risk factors. Consumption of beta 

carotene shows no evidence of a protective effect. Overall, active smoking is the major cause of lung cancer among 

women in the regions sampled. 

A-133
A.4.32.3. Comments 

The sample size is impressive, with ETS exposure data available for nearly 1,000 cases including smokers 

and more than 400 cases when restricted to nonsmokers, thus providing substantial statistical power. All subjects 

are women recruited from two industrial cities in northeast China, reducing potential for complications due to 

regional or urban-rural differences. Nearly all of the hospitals in these cities were involved, all cases occurring in 

these hospitals were targeted, and the rate of participation among eligible cases was high; thus potential for selection 

bias is minimized. The effective case recruitment in combination with the use of general population controls 

maximizes generalizability of the study's results for northeast China. It would have been useful, however, to present 

the results for the two component study locations separately. Although coordinated in planning and execution, there 

are two separate study locations, and the sources of heterogeneity between them tends to be obscured when results 

are combined. 

Unfortunately, the study's results with regard to ETS are more limited than the strengths listed above might 

suggest. The inclusion of age, education, and city as control variables in all analyses is laudable, thus eliminating 

the possible influence of these factors. The attempt to control for potential sources of confounding that may be 

causally related to lung cancer by statistical methods, however, is less certain. Although some analysis was 

conducted with data for active smokers included, to the authors' credit they also analyzed data for ETS subjects 

alone (i.e., with the data for active smokers removed), which is the surest way to control for confounding by active 

smoking. Other potential causes of lung cancer (e.g., air pollution from coal-burning stoves, smokiness during 

cooking, and deep-fat frying foods) also need to be taken into account in an analysis of ETS. This cannot always be 

accomplished effectively by statistical methods, particularly when there are multiple risk factors to be taken into 

account that are variable, poorly measured, and possibly more potent risk factors than ETS may be. 

A case-control study is ideally designed and executed under conditions where cases and controls are as 

comparable as possible aside from the factor of interest, such as ETS exposure. The presence of other risk factors 

may tend to pollute and obscure, much like the contamination of a laboratory experiment. In this same sense, the 

presence of indoor sources of smoke other than ETS may contaminate an environment for measuring ETS effects 

because the non-ETS smoke likely contains many of the same carcinogens as ETS, and possibly in much larger 

quantities, depending on the relative levels of exposure. Other factors outside the home, such as workplace 

exposure to coal dust and to smoke from burning fuel that was reported more often in cases than controls, contribute 

to the potential confounding in a similar way. Consequently, a credible analysis of ETS requires being able to 

adjust for these likely confounding factors satisfactorily, and the ability to do that depends on precise measures of 

all exposures as well as the presence of substantial numbers of subjects for various exposure combinations. That 

kind of statistical analysis is not given in the article, and it does not appear to have been possible, based on 

conversations with the authors (Wu-Williams and Blot) and the text of the article: "Despite the large size of our 

study, we were unable to clarify the magnitude of risks due to passive smoking, recognized as a cause of lung 

A-134
cancer around the world (U.S. DHHS, 1986). Perhaps in this study population the effects of environmental tobacco 

smoke was obscured by the rather heavy exposures to pollutants from coal-burning Kang, other indoor heating 

sources, and high levels of neighborhood air pollution (Xu et al., 1989)." 

The potential rate of non-ETS sources of indoor air pollution, particularly coal combustion, appears 

exceptionally strong in the study area. For example, a case-control study of primary lung cancer in urban Shenyang 

residents aged 30-69 in 1985-87 reports that the age, education, and smoking-adjusted OR for kang use among 

women ranges from 1.9 to 3.4, the latter figure being for the higher exposure level (at least 50 years of use). Fully 

44% of the controls and 55% of the cases are at the highest exposure level, and only 3% of controls and less than 

1% of cases have no exposure. Benzo[a]pyrene levels in 30 homes sampled during the winter averaged 60 ng/m3

, 

which is 60 times the U.S. recommended limit, and indoor measurements in single and two-story homes were even 

higher (Xu et al., 1989). Abstracts of two papers published in Chinese indicate that similar conditions exist in 

Harbin. Sun (1992) found a smoking-adjusted OR for soft coal use of 2.26 with a highly significant trend for 

duration of exposure among female residents. Also, Wang (1989) reports ORs of 10.6 for high coal consumption 

and 15.2 for "indoor smog pollution in winter" among females in Harbin. It is noted that winter levels of 

benzo[a]pyrene are 26.7 times higher in residents' bedrooms than outdoors, suggesting that indoor coal combustion 

may even be more of a problem in Harbin than Shenyang. 

The multivariate analysis reported in the article reinforces the viewpoint that any ETS effect may be 

dominated by the presence of other risk factors. In that analysis, variables were allowed to enter a logistic 

regression model in the order of their explanatory value (a stepwise regression exercise in statistical terminology). 

The order of entry into the model is deep frying, eye irritation, pneumonia, household tuberculosis, burning kang, 

self-reported occupational exposure to burning fuel, passive smoking, and heated brick wall or floor. Passive 

smoking, in this exercise, is significant (p < 0.05) but in the direction of reducing lung cancer, not contributing to it. 

The 0.05 value, however, is not fully meaningful as a significance level for ETS, because of the stepwise procedure 

used (the same data used in the construction of a model is used for testing variables in the model) and because of the 

likely confounding between ETS and other variables. Note, for example, that passive smoking entered the model 

ahead of heated brick wall or floor, which is highly significant when analyzed alone, whereas passive smoking is 

not. 

The evidence for association of lung cancer with burning coal and deep-frying foods is particularly 

provocative, as it indicates two factors that may play a substantial role in the etiology of lung cancer in northeast 

China and, hence, in other areas as well where such practices occur. The associations noted with other factors are 

also of interest, but their importance is undermined by the problem of multiple comparisons. In the table presenting 

results for dietary factors, for example, 26 risk estimates are computed, 4 of which are significant at the 5% 

significance level (for a two-sided test, 2.5% level for the test of an effect), only one more significant finding than 

expected due to chance alone. 

A-135
Being somewhat speculative, the use of cases age 70 and below may be a factor. Wells (1988) showed that 

about one-half of the female passive smoking deaths occur after age 70 for the studies included in that reference. If 

ETS is a risk for lung cancer and if individual susceptibility to lung cancer is a factor, some of the stronger risk 

factors such as coal burning and cooking oil may have caused lung cancer in the more susceptible subjects before 

passive smoking had a chance to exert itself. 

In summary, this large and basically well-executed study observed no significant association between 

exposure to ETS from cohabitants, spouse, parents, or workplace and lung cancer. Lack of control for a number of 

other significant risk factors identified in the study undermines these results, however. The associations with coal 

burning for heat and oil frying are particularly notable. Use of the heating devices most strongly linked with lung 

cancer is presumably more common in colder northern regions, whereas stir-frying may be more widespread in 

Asian communities, without regard to climate. Thus, this study was exploratory, designed to generate hypotheses 

rather than to test the specific hypothesis that ETS exposure is associated with lung cancer. It identifies a number of 

potential risk factors for consideration in future studies. The prevalence of these factors in the study population 

combined with the lack of analysis of their association with ETS exposure, however, renders the results for ETS 

inconclusive. 

A-136
APPENDIX B 

METHOD FOR CORRECTING RELATIVE RISK 

FOR SMOKER MISCLASSIFICATION 
APPENDIX B. METHOD FOR CORRECTING RELATIVE RISK 

FOR SMOKER MISCLASSIFICATION 

B.1. INTRODUCTION 

The purpose of this appendix is to present the details of the method used in 

Section 5.2.2. to correct observed passive smoking relative risks for the 

systematic upward bias caused by misclassification of some smokers as neversmokers. The method used is that proposed by A. J. Wells and W. F. Stewart 

(Wells, 1990) with minor modifications, including an adjustment for passive 

smoking risk to smokers. This appendix covers the following: the principles of 

the method (Section B.2); how the method differs from those previously used by 

the National Research Council and P. N. Lee (Section B.3); the data used to 

calculate the misclassification factors and other parameters (Section B.4); the 

mathematical model used to calculate the corrected relative risks (Section B.5); 

and a numerical example to show how the method is applied in a practical case 

(Section B.6). The results show that the bias due to smoker misclassification is 

highly unlikely to be responsible for the increased risks observed in the passive 

smoking lung cancer epidemiology studies. Evidence is also presented 

suggesting that the true downward corrections for smoker misclassification bias 

may be even smaller than those developed below and used in Section 5.2.2. 

While some of the rates presented below are subject to variability and argument, 

attempts are made to provide reasonable estimates and a defensible 

methodology. 

There is considerable literature on this topic and a history of controversy 

regarding the magnitude of the bias and whether it may explain the observed 

increase in lung cancer mortality due to ETS exposure. The NRC report on the 

health effects of passive smoking (NRC, 1986) delves into this topic in 

considerable detail. It concludes that bias is likely; further, it estimates an 

adjustment for the summary relative risk from the combined results for all ETS 

studies. The NRC report further concludes that smoker misclassification does 

not account for the observed passive smoking risk. On the other hand, in various 

publications Lee (1987b, 1988, 1990, 1991a) has claimed that the smoker 

misclassification bias is large enough to explain most or all of the observed 

passive smoking lung cancer risk. 

Approaches to estimation of misclassification bias have used mathematical 

modeling with parameters estimated from a variety of sources that have not 

always been consistent. The procedure described below attempts to rectify some 

previous sources of misunderstanding on this topic and utilizes the extensive 

data sources now available to improve parameter estimates and tailor 

refinements to individual populations. 

B-1 
B.2. PRINCIPLES OF THE WELLS-STEWART METHOD 

The Wells-Stewart method is based on the following principles, the nature 

and need for which have largely become apparent from the chronological 

evolution and disparate approaches to and results for this problem. 

The parameters are: 

a. Since the passive smoking epidemiology is essentially concerned 

entirely with self-reported never-smokers, it is necessary to limit the 

misclassifieds to those who said they never smoked, not simply to 

nonusers, because the latter would include a substantial proportion of 

self-reported former smokers. 

b. Use one minus sensitivity or its close relative, false negatives 

(misclassified smokers) divided by observed positives (self-reported 

smokers) as the vehicle for transferring misclassification data from 

cotinine and discordant answer studies to the passive smoking studies. 

Sensitivity is the term used to describe the fraction correctly classified 

as exposed, namely, true positives divided by true positives plus false 

negatives, but since we are assuming that the true positives and the 

observed positives are the same (no misclassification of never-smokers 

as smokers), sensitivity in this case becomes observed positives 

divided by observed positives plus false negatives. Then one minus 

sensitivity becomes false negatives divided by observed positives plus 

false negatives. Ignoring the false negatives in the denominator 

introduces negligible error. In any case, do not use specificity (true 

negatives divided by true negatives plus false positives) or any 

parameter that uses as its denominator true or observed negatives (selfreported never-smokers). The reason is that sensitivity is affected 

much less by smoker prevalence than parameters based on observed 

negatives. 

c. Calculate a correction for each epidemiologic study separately using a 

misclassified smoker relative risk and a proportion of smokers among 

subjects and spouses that is characteristic of the timeframe and locale 

of each study. Use data from the study itself or from another study 

with the same target population, if possible. 

d. Use only female data to correct misclassification of female subjects. 

For the mathematical model, calculate the corrected risk directly--that is, 

do not first calculate a bias assuming no passive risk and then divide the 

observed risk by that bias to get a corrected risk. 

Subjects found to be misclassified as nonsmokers are categorized 

according to their self-reported smoking status--former or current. Misclassified 

current smokers are further classified as "regular" or "occasional," according to 

observed cotinine levels. "Regular" means the cotinine level is above 30% of the 

self-reported smoker mean; "occasional" applies to the range 10% to 30%. 

B-2 
Cotinine levels are not informative for misclassified former smokers, who tend 

to be long-term abstainers (10+ years, according to Lee [1987b] and Wald et al. 

[1986]). The two studies with detailed cotinine levels on female current smokers 

(Lee, 1986 and Haddow et al., 1986, in Table B-1) indicate that about 10% of the 

current smokers are occasionals. 

B.3. DIFFERENCES FROM EARLIER WORK 

The Wells-Stewart method differs from the method used by the NRC 

(1986), which is also described by Wald et al. (1986), in that the NRC method 

failed to separate the misclassified smokers into regular, occasional, and exsmokers, and failed to account for the effect of smoker misclassification on 

active smoker risk. The NRC made an overall correction to the aggregated 

passive relative risk using United Kingdom (U.K.) smoking prevalence and risk 

rather than making the corrections study-by-study with appropriate smoking 

prevalences and risk for each study's time and locale, and it mixed male data 

with female data in arriving at misclassification factors. Their calculated bias of 

1.34/1.25 = 1.07, or 7%, for the combined worldwide studies is substantially 

higher than the 2% overall bias that would result if the biases in Table 5-7 were 

aggregated. The discrepancy is largely due to NRC's use of U.K. parameters for 

all of the studies regardless of locale, plus some overestimation of the impact of 

misclassified occasional and ex-smokers. 

Lee's methods have evolved over the years in three stages. In Lee (1987b, 

1988), he improved on the NRC method in that he divided the misclassified 

smokers into ex-smokers and current regular and occasional smokers, and he 

corrected the smoker risk for misclassification. However, all of the five 

principles listed above were violated to some degree, resulting in about a 

twelvefold overestimation of the bias (Wells, 1992). The Lee (1990) paper 

correctly limits misclassifieds to never-smokers, relates misclassified smokers to 

smokers, not to never-smokers, and treats each study separately, but still mixes 

male input data with female data for use in calculating bias for females. 

Furthermore, his mathematical model still relies on the assumption of a passive 

smoking relative risk of 1.00 (no risk), an assumption that fails at passive risks 

above about 1.3 and overstates those biases. In addition, Lee (1990) has 

changed from separating the misclassified smokers into three groups in favor of 

the (less useful) overall category of "ever- smokers." Most recently, Lee (1991a) 

presented a more complex mathematical model that includes a term for passive 

risk, but the method still has the other shortcomings noted for Lee (1990). A 

comparison of the most recent Lee bias estimates with those in Table 5-7 is 

shown in Table B-2 for the five U.S. studies with the greatest statistical weight. 

When Lee's inputs are used with the Wells-Stewart mathematical model, the 

calculated biases are, if anything, somewhat larger than when using Lee's most 

recent model. 

B-3 
Table B-1. Observed ratios of occasional smokers to current smokers (based on

cotinine studies) 

Females Both sexes1 

Study Occl 

. 

2 

Curre 

nt 

Occl./curre 

nt 

Occ 

l. 

Curre 

nt 

Occl./curre 

nt 

Lee (1986) 4 72 0.056 12 176 0.068 

Coultas 

et al. (1988) 

59 278 0.212 

Haddow 

et al. (1986) 

10 64 0.156 

Feyerabend

et al. 

(1982)3 

7 82 0.085 

Jarvis 

(1987) 

12 90 0.133 

Pojer

(1984) 

25 187 0.134 

Wald et al. 

(1984) 

13 131 0.099 

Overall 14 136 0.103 128 944 0.136 

1

The "both sexes" data are shown to indicate that the female value of 10.3% is

not unduly high.

2

Occasional smokers are defined as persons who have cotinine levels in body

fluids that are

between 10% and 30% of the mean of all self-reported current smokers. 3

The Feyerabend et al. (1982) data are for nicotine.

Therefore, the difference between Lee's most recent estimates of bias and those

shown in Table 5-7 are in practical terms due almost entirely to differences in

input parameters. The input parameters we have chosen are developed in the

next section, and comparisons with the Lee parameter estimates are shown as

footnotes to Table B-2.

B.4. PARAMETER ESTIMATES 

The key input in these calculations is the proportion of misclassified 

regular current smokers who claim they have never smoked. Our definition of 

misclassified regular current smokers, first suggested by Lee (1987b), produces a 

mean cotinine level approximately equal to that of all self-reported current 

smokers. Detailed data from three large cotinine studies have been assembled 

for use herein with the cooperation of their principal investigators (Coultas, 

Cummings, and Pierce in Table B-3). The data identify individual nonsmokers 

with cotinine values greater than 10% of the mean for self-reported smokers, by 

sex sex and self-reported smoking status (never or former). Data on nonusers 

are also available from several other studies (the lower 

B-4 
Table B-2. Examples, using five U.S. studies, of differences in smoker misclassification bias between EPA estimates and those o

passive smoking relative risks for females 

Wells-Stewart model 

% of Lee (1991a) model1 EPA 

Study U.S. Lee (1991a) input parameters Lee (1991a) input2 parameters 

weight RRo RRc Bias RRo RRc Bias RRo 

FONT 35 1.32 1.18 1.11 1.32 1.133 1.16 1.29 

GARF (Coh) 25 1.17 1.02 1.14 1.17 1.024 1.14 1.17 GARF 15 1.23 1.10 1.12 1.23 1.085 1.14 1.31 JANE 10 0.75 0.62 1.21 0.75 0.616 1.24 0.86 CORR 3 2.07 1.84 1.12 2.07 1.707 1.22 2.07 

B-5 Note: Calculated bias is very sensitive to three key factors, high values of which will drive the bias up; namely, fraction of obse

misclassified, female active smoker relative risk, and female smoking prevalence. Lee's inputs are higher than EPA's, as 

7 below. RRo = observed passive risk. RRc = passive risk corrected for smoker misclassification bias. Bias = RRo/RRc. 

1Additive model, Lee's Table 3. His additive model was chosen because it is similar to our additive model for passive smoking

effects on smokers. 

2EPA's misclassification factors developed in Section B.4., namely, 1.09% of current regular smokers, 24.2% of current occasiona

smokers, and 11.7% of ex-smokers, when weighted for their respective prevalence and relative risk, are equivalent to about 1.5% 

of average self-reported ever-smokers. EPA used these rates for all studies except FONT, which is a special case. Lee used 2.0% 

of self-reported ever-smokers for all studies. 3Lee used 49% ever-smokers vs. our 43% based on the case age distribution. Our misclassification rates for current smokers, m2 

(4.3%) and m3 (0%), were developed as noted in Section B-4, except that 2 out of 3.5 expected misclassified occasional smokers h

been eliminated by cotinine tests, leaving 1.5/35 = 0.043 for m2 in this study. For m1, we assumed that it was the same percentage

(41%) of 0.117 as 10% was of 24.2% for m2. 

(contin
Table B-2. (continued) 

4A female smoker risk of 3.58 (U.S. DHHS, 1986) and smoker prevalence of 22% (Hammond, 1966) for age distribution of cases.

Lee used 8.0 and 49%. 

5EPA estimates a smoker risk of 6 and a smoking prevalence of 34% for the time period 1971-81 vs. Lee's values of 8.0 and 49%. 6The main difference is in the assumed smoker misclassification rate, but Lee's assumption of 49% smoking prevalence vs. 42% 

assumed by EPA increases the bias estimate from 1.09 to 1.15. 7Lee assumed 58% smoking prevalence vs. 47%, which EPA got from the paper itself. Lee assumed a lower smoker risk (9.5) vs.

EPA's 12.4; the effect of this was offset by Lee's higher misclassification rates. 

B-6 
Table B-3. Misclassification of female current smokers 

Self-reported smoking status

number 

Study 

Cotinine 

level1 

Number 

Never 

Current 

Coultas et al. (1988)2 10-30 

30+ 

All 

7 

5 

387 

3 

8 

79 184 

Cummings (1990)3 10-30 

30+ 

All 

0 

2 

225 

1 

0 

143 116 

Pierce et al. (1987)4 10-30 

30+ 

All 

9 

3 

232 

4 

3 

79 167 

Subtotal 10-30 

30+ 

All 

16 

10 

844 

8 

11 

301 

(67% never)

(48% never)

467 

Lee (1986)5 10-30 

30+ 

All 

3 

3 

333 

2 

2 

125 256 

Haddow et al. (1986)5 10-30 

30+ 

All 

1 

0 

174 

1 

1 

58 64 

Haddow et al. (1988)5 10-30 

30+ 

All 

15 

1 

1,128 

7 

1 

380 503 

Riboli (1991)5,6--U.S.7 10-30 

30+ 

All 

1 

0 

224 

0 

0 

81 143 

Riboli (1991)5,6--East 

Asia8 

10-30 

30+ 

All 

1 

1 

325 

1 

0 

25 77 

Riboli (1991)5,6-- Greece9 

10-30 

30+ 

All 

0 

0 

96 

0 

0 

5 5 

Total 10-30 

30+ 

All 

37 

15 

3,124 

19 

15 

975 1,525 

Proportion

misclassified10 

10-

30% 

30+ 

24.2% 

1.09% 

12.4% 

1.09% 

Former 

1

(continued on the following page) 

B-7
Table B-3. (continued) 

1

Cotinine levels are in units of percentages of the mean of self-reported smokers

for each study;

30+% are defined as current regular smokers, 10-30% are occasional smokers. 2

Dr. Coultas kindly provided the individual cotinine values for females ages 18+

that were used in 

Table 3 of their paper. The totals differ slightly from the totals in the paper. 3

Dr. Cummings kindly provided the cotinine levels for the six misclassified

current smokers, 

three males and three females. As noted in the paper, current smokers were

recruited during

only the first half of the study. Therefore, the total equivalent current smokers

were estimated 

from the current smoker/never-smoker ratio from national statistics. 4

Individual cotinine levels for the misclassifieds by gender are from a personal

communication 

from Petra Macaskill, who now has the basic data for this study.

5

For Lee (1986), Haddow et al. (1986, 1988), and Riboli (1991), no breakdown

was given between

"Never" and "Former." An estimate was made based on the subtotal 

distribution. The number of 

smokers had to be estimated in some cases. The mean for self-reported

smokers for Haddow et 

al. (1988) was very low, at 145 ng/mL, because the women were pregnant.

6

Personal communication--individual country data from Riboli et al. (1990).

7

New Orleans, Los Angeles, and Honolulu.

8

China (Shanghai), Hong Kong, and Japan (Sendai).

9

Athens. 

10The observed current smokers are assumed to be 90% regular (1,372) and 10%

occasional (153)

smokers. For regular smokers, misclassification as never-smokers is 15/1,372

= 1.09% of 

observed current regulars or 15/(1,372 + 15 + 15) = 1.07% of true current

regulars. For 

occasional smokers, misclassification is 37/153 = 24.2% of observed current

occasionals or 

37/(153 + 37 + 19) = 17.7% of true current occasionals. For current smokers 

misclassified as 

former smokers, the factors are 15/1,372 = 1.09% for observed and 15/1,402 =

1.07% for true 

regular smokers, and 19/153 = 12.4% for observed and 19/209 = 9.1% for true

occasionals. 

Data on nonusers are also available from several other studies (the lower portion 

of Table B-3). The proportions of misclassified smokers who would have said 

"never" versus "former" are estimated using the proportions observed in the first 

three studies. Data sets not differentiating outcomes by sex have not been used. 

Also, the large 1987 study by Haddow and colleagues has not been used for this 

purpose on the advice of one of the authors (personal communication from G.J. 

Knight). This study of the effect of current smoking on birthweight relied on the 

cotinine data to distinguish smokers from nonsmokers. The questionnaire data 

were not collected in a manner that could be equated to the care that would be 

taken in either their or others' passive smoking studies. 

The number of self-reported never- and former smokers with sufficiently 

high cotinine levels to be reclassified as current smokers is shown by study in 

B-8 
Table B-3. As described above, those with cotinine levels in the 10-30% range 

are considered to be occasional smokers, whereas those above 30% are treated as 

regular smokers. If it is assumed (Table B-1) that 1,372 (90%) of 1,525 selfreported current smokers are regular smokers, leaving 153 (10%) as occasionals, 

then the percentage of current regular smokers misclassified as never-smokers 

totalled over all studies in Table B-3 is 15/1,372 or 1.09%. The percentage is 

almost the same if the number of true, i.e., self-reported plus misclassified 

current regular, smokers is used. For the occasional smokers only, the 

misclassification rate is much higher, about 24% (18%) of observed (true) 

occasional smokers. It is possible, however, that the subjects classified as 

occasional smokers based on cotinine levels in the range 10-30% may contain 

some true never-smokers that are just highly exposed to passive smoke. 

The cutoff points used, namely, 30% of the self-reported current smoker 

mean cotinine level to distinguish misclassified regular smokers from occasional 

smokers and 10% of the self-reported current smoker mean cotinine level to 

distinguish occasional smokers from current nonsmokers, were chosen originally 

by Lee (1987b). They are justified as follows: the actual cotinine levels of the 

15 misclassified current smokers in the Never column of Table B-3 whose levels 

exceeded 30% of the mean cotinine level for self-reported current smokers in 

each study were divided by the mean smoker cotinine level for that study. These 

values were then averaged for each study, and a mean for all studies was 

obtained by weighting each study's mean by the number of smokers in that 

study. The overall mean cotinine level for the misclassified smokers was 94% of 

the mean for all of the self-reported smokers because the misclassifieds tended to 

concentrate near the bottom of the 30%+ range. A cutoff of 35% could be 

justified since the misclassifieds' mean cotinine level was 99% of the mean for 

the self-reported smokers, but we chose to continue with 30% to be conservative. 

The cutoff between the current nonsmokers and the occasional smokers 

must be somewhat arbitrary because there is an overlap between heavily ETSexposed nonsmokers and very light current smokers. Authors who have tried to 

eliminate all possible smokers from their cohorts have used lower cutoff points. 

For example, Coultas et al. (1988), Cummings (1990), and Haddow et al. (1988), 

who were trying to eliminate smokers, used cutoffs between 7% and 8%. 

However, Pierce et al. (1987) and Lee (1986), who, as we are, were trying to 

distinguish smokers from nonsmokers, used higher cutoffs, 16% and 9%, 

respectively. The mean of the percentages (calculated as above for the 

misclassified current regular smokers) that the misclassified occasional smokers' 

cotinine levels bear to the mean of the self-reported current smokers is 16% for 

the seven studies in Table B-3. This is lower than the midpoint of the 10-30% 

range, again because the individual values concentrate at the lower end of the 

range. If we had used a 5% cutoff instead of 10%, the misclassification rate for 

occasional smokers would have been increased from 24% to about 40%, but the 

B-9 
average of the percentages of current self-reported mean cotinine levels for the 

misclassified occasional smokers would have dropped from 16% to 13%. This 

in turn would reduce the estimated smokers' relative risk for this group, and the 

overall effect on the corrected risk of never-smokers would be negligible. 

The studies in Table B-4 provide data on discordant answers, i.e., reported 

never-smokers who have called themselves smokers on one or more previous 

occasions. Based on those data, the estimated percentage of former smokers 

misclassified as never-smokers is 11.7% (10.8%) of the observed (true) number 

of former smokers. As mentioned previously, evidence suggests (Wald et al., 

1986; Lee, 1987b) that most former smokers misclassified as never-smokers 

have been nonsmokers for an extended period, such as 10+ years, and may have 

been light smokers on average. Accordingly, we have used a weighted average 

of the data of Alderson et al. (1985), Lubin et al. (1984), and Garfinkel and 

Stellman (1988) for 10+ year abstainers to estimate misclassified former smoker 

relative risk, namely, an excess risk that is 9% of current self-reported smoker 

excess risk. 

Some confusion and misleading conclusions on smoker misclassification 

have resulted from the practice of expressing the number of smokers 

misclassified as never-smokers as a percentage of the total number of (either true 

or observed) never-smokers, rather than as a percentage of the number of 

smokers. That leads to a higher expected percentage of smokers misclassified as 

never- smokers among cases than controls because lung cancer cases are much 

more likely to have been smokers than never-smokers. Some people (Lee, 1988) 

have interpreted a higher percentage of observed never-smokers later found to be 

misclassified smokers among the cases as evidence that smokers with lung 

cancer are more apt to claim falsely to be never-smokers than persons without 

cancer. That conclusion, however, appears to be an artifact of treating the 

misclassification rate as a percentage of the number of never-smokers rather than 

as a percentage of the number of smokers. The study data summarized in Table 

B-5 do not support that conclusion. If anything, they are more supportive of the 

conclusion that ever-smokers in lung cancer studies may be less likely to 

misrepresent themselves as never-smokers than members of the general public 

who are questioned in community surveys. The 1.0% average misclassification 

rate shown in Table B-5 for the lung cancer cases suggests that estimates such as 

the 5.7% from the general population studies (Table B-5) or the equivalent of 

3.9% of ever-smokers (Table B-4) that we have used may be much too high. 

Further corroboration that the misclassification rates from the community studies 

are too high relative to those in the epidemiologic studies is found in the recent 

lung cancer case-control study by Fontham et al. (1991), which specifically 

included in its design a screening by urinary cotinine levels to eliminate current 

smokers from both cases and controls. After eliminating possible smokers 

among the self-reported never-smokers by the usual epidemiologic questionnaire 

B-10 
and medical records review techniques, the investigators found by cotinine 

measurements that only two probable occasional smokers and no probable 

regular smokers were left among the 239 never-smoking lung cancer cases for 

which cotinine measurements were made. Using the procedures herein and 

assuming 43% ever-smokers among controls and an ever-smoker relative risk of 

8, which translates to 10 for misclassified current regular smokers, 2.44 for 

misclassified occasionals, and 1.81 for misclassified ex-smokers, there would 

have been 1,363 smoker cases, consisting of 1,328 current smokers and 35 

occasional smokers to go along with 420 never-smoking cases. It is seen that a 

misclassification rate of 0/1,328 = 0.00% for regular smokers is well below the 

1.09% that we have used from the surveys in Table B-3. For occasionals, there 

would be 20 cases to go along with 239 never-smoking cases, yielding a 

misclassification rate of 2/20 = 10%, which is also well below the 24.2% for 

occasionals that we have used from Table B-3. 

Another indication that the estimates based on community surveys may be 

too high comes from analysis of male data. The observed percentage of neversmokers is typically much lower for males (17% to 35%) than females (41% to 

86%). To correct for smoker misclassification, we set up a table analogous to 

Table B-6 where the number of current and former smokers misclassified as 

never-smokers are subtracted from the reported number of never-smokers. 

When the misclassification rates generated from community surveys are applied 

to the male data, the outcome is not credible--the number deleted for 

misclassification exceeds the total number of reported never-smokers in 3 of the 

11 examples of which we are aware and drives the corrected relative risk well 

below unity in 4 more. This outcome indicates that the misclassification rates 

derived from the community surveys are too high. It is probable that the true 

smoker misclassification bias is on the order of one-fourth to one-half of the 

values shown in Table 5-7. 

It has also been suggested (Lee, 1991b) that East Asian women 

misclassify themselves at much higher rates than Western women. The data 

from the International Agency for Research on Cancer (Riboli, personal 

communication) in Table B-3 do not support that claim, however, because the 

East Asia (Hong Kong, Japan, and China) misclassification rate for current 

regular smokers is 1/77 = 1.3%, which is not much different from the overall rate 

of 1.09%. 

In conclusion, it would appear that the bias introduced by misclassification 

of smokers as never-smokers is not a serious problem. It probably increases 

observed excess relative risks on a worldwide basis by about 1% and for 

combined U.S. studies by about 3%. 

B-11 
Table B-4. Misclassification of female former smokers reported as never-smokers

based on

discordant answers

Study Locale 

Former 

smokers 

(FS)1 

Eversmokers 

(ES)1 

Reported neversmokers who reported

earlier that they had

smoked1 

Percentage

N 

Kabat and 

Wynder (1984)2 

Controls 

Cases 

Machlin 

et al. (1989) 

Krall et al. 

(1989)3 

Britten (1988)4 

Lee (1987b) 

Akiba et al. 

(1986) 

Overall5 

U.S. 

U.S. 

Mass. 

U.K. 

U.K. 

Japan 

109 

222 

194 

11 

320 

85 

8 

949 

319 

652 

687 

30 

878 

243 

38 

2847 

0 

7 

52 

1 

38 

13 

0 

111 

0.0 

1.1 

7.6 

3.3 

4.3 

5.5 

0.0 

3.9 

0.0 

3.2 

26.8 

9.1 

11.9 

15.3 

0.0 

11.7 

of ES of FS 

1

Number of former smokers and ever-smokers had to be estimated in some cases. 2

Dr. Kabat (personal communication) advised that of 13 misclassifieds, 8 were

females, 1 of whom 

used snuff. 

3

Krall data are based on 20-year recall.

4

Britten data include only those persons who said they never smoked but actually

had smoked 

regularly one or more cigarettes per day.

5

For former smokers, misclassification as never-smokers would appear to be

111/949 = 11.7% of

observed former smokers or 111/(949 + 111) = 10.5% of true former smokers,

but from Table 

B-3 16 + 15/(16 + 15 + 975) = 3.08% of former smokers are really current

smokers, so the 949 + 

111 = 1,060 should be reduced by 3.08% to 1,027 as the number of true former

smokers. Then 

111/1,027 = 10.81%, based on true former smokers. 

B-12 
Table B-5. Misclassification of female lung cancer cases 

Source Number of ever-smokers Number misclassified 

CHAN 

Chan et al. (1979)1 

12 1 

KABA 

Kabat and Wynder

(1984)2 

652 7 

AKIB 

Akiba et al. (1986) 

38 0 

PERS 

Pershagen et al. (1987) 

179 2 

HUMB 

Humble et al. (1987)3 

223 1 

Total 1,104 11 (1.0%) 

General population4 1,838 104 (5.7%) 

1

Chan sampled five Type I and II never-smokers, one of whom was said by a

relative to have 

smoked a few hand-wrapped cigarettes for a year at age 71. The ratio of 

smoking to nonsmoking

cases for Types I and II was 44/19, which, multiplied by 5, leads to 12 estimated

ever-smokers. 

2

Dr. Kabat (personal communication) advised that of 13 misclassifieds, 8 were

females, 1 of whom 

used snuff. 

3

Of the four misclassifieds found, Dr. Humble (personal communication) has

advised that most if 

not all were males. We have assumed one female. 4

The general population data are taken from the four nonlung cancer cohorts in

Table B-4, 

namely, Machlin et al. (1989), Krall et al. (1989), Britten (1988), and Lee

(1987b). 

B-13 
Table B-6. Deletions from the "never" columns in Tables B-13 and B-16 and 

corrected elements 

Wife's smoking status 

Husband's 

smoking

status 

Forme 

r 

(1) 

Occl. 

(2) 

Regul 

ar 

(3) 

Sum1 

(4) 

Observ 

ed 

never 

(5) 

Correcte 

d 

never2 

(6) 

Table B-13 Never 0.00679 0.00194 0.00081 0.00953 

0.286 0.27647 

(controls) Ever 0.01275 0.00532 0.00219 0.02027 0.242 

0.22173 

Table B-16 Never 0.00198 0.00120 0.00217 0.00534 

0.052 0.04666 

(cases) Ever 0.00770 0.00365 0.00604 0.01739 0.092 

0.07461 

1

(4) = (1) + (2) + (3)

2

(6) = (5) - (4) 

B.5. MATHEMATICAL MODEL 

The proportion of smokers, mh0, misclassified as never-smokers is 

estimated separately for former smokers (m10), occasional smokers (m20), and 

regular smokers (m30). Similarly, the proportion of current smokers, mh1, 

misclassified as former smokers is estimated separately for occasional smokers 

(m21) and regular smokers (m31). These estimates are given in Tables B-3 and B4. It is assumed that there is no misclassification of true never-smokers as 

current or former smokers or of true former smokers as current smokers. Also, 

these misclassification factors are used for all the studies unless otherwise noted. 

We suspect that misclassification rates probably vary from study to study. That 

variability, however, would tend to cancel out as the individual study results are 

combined. 

Let cijk designate the observed distribution of controls (i = 0) and cases (i = 

1) by their smoking status (j = 0,1,2,3) and the smoking status of their husbands 

(k = 0,1), as illustrated in Table B-7. Following the notational convention that a 

dot in the subscript position means summation on that subscript, then c0.. = c1.. = 

1. 

The observed cijk's are corrected for misclassification of the wife's smoking 

status by first specifying a 4 × 4 matrix of distribution (Table B-8), where Phj (h,j 

= 0,1,2,3) is the probability that a subject with true smoking status h will also be 

observed to have smoking status j. The subscripted notation is shown in Table 

B-8 for easy reference. P.. is equal to unity. 

B-14 
For passive smoking, we are interested only in correcting the ci0k values 

that are for the observed never-smokers. hj's are the same 

for cases and controls (nondifferential misclassification). 

wife's subject status (i) and husband's smoking status (k), the correction when 

the wife's observed smoking status is "never" (j = 0) is: 

(B-1) 

where Ci0k is the corrected form of the element ci0k. 

risk, RR(c), becomes: 

RR(c) = (C101 × C000)/(C100 × C001) (B-2) 

The values of c0jk in Table B-7 are from prevalence data in the study itself or 

from a related study, from concordance data, and from each study's data on the 

smoking prevalence of the never-smokers' husbands. 

former smokers can be estimated from the ever-smokers based on data from nine 

studies known to us where the percentage of both current smokers and former 

smokers is known (see Table B-9). 

nontraditional societies, from 20% former smokers relative to ever-smokers in 

1960 to 45% in 1985; we estimate an 8-year lag for the traditional societies such 

as Hong Kong, China, Japan, and Greece, based on the data in Koo et al. (1983) 

and Sobue et al. (1990). 

It is assumed that the P

For given values of 

Then the corrected passive 

If necessary, the number of 

These data indicate a time trend in 

B-15
Table B-7. Notation for distribution of reported female lung cancer cases and

controls by husband's smoking status 

Wife's observed smoking status (j) 

Wife's 

subject

status (i) 

Husband's 

smoking

status (k) 

Never 

(j = 0) 

Ex 

(j = 1) 

Occl. 

(j = 2) 

Reg.

(j = 3) Total 

Control Never (k = 0) c000 c010 c020 c030 c0.0 

(i = 0) Ever (k = 1) c001 c011 c021 c031 c0.1 

Total c00. 01. 02. 03. 0.. ( = 

1) 

Case Never (k = 0) c100 c110 c120 c130 c1.0 

(i = 1) Ever (k = 1) c101 c111 c121 c131 c1.1 

Total c10. 11. 12. 13. 1.. ( = 

1) 

c c c c

c c c c

Table B-8. Notation for distribution of subjects by observed and true smoking 

status 

Wife's 

observed 

smoking status

(j) 

Wife's true smoking status (h) 

Never 

(h = 0) 

Total 

Never (j = 0) P00 P10 P20 P30 P.0 

Former (j = 1) P01 P11 P21 P31 P.1 

Occl. (j = 2) P02 P12 P22 P32 P.2 

Reg. (j = 3) P03 P13 P23 P33 P.3 

Total P0. P1. 2. 3. P..(= 

1) 

Former Occl. Reg.

(h = 1) (h = 2) (h = 3)

P P

B-16 
Table B-9. Observed ratios of female former smokers to ever-smokers in the U.S., 

U.K., and Swedish studies: populations or controls (numbers or percentage) 

Study 

Timeframe Neversmoke 

rs 

Curren 

t 

smoker 

s 

Former 

smoker 

s 

Eversmoker 

s 

Former/eve

r-smokers 

Hammond 

(1966)1 

1960 78.0% 17.6% 4.4% 22.0% 0.20 

Buffler 

et al. (1984)2 

1978 41% 38% 21% 59.0% 0.36 

Wu et al. 

(1985)2 

1980 92 73 55 128 0.43 

Lee (1987b)3 1980 48.3% 33.6% 18.1% 51.7% 0.35 

Brownson 

et al. (1987)2 

1980 47 11 8 19 0.42 

Britten (1988)3 1982 767 558 320 878 0.36 

Humble 

et al. (1987)2 

1982 162 63 48 111 0.43 

Svensson 

et al. (1989)2 

1984 120 53 36 89 0.40 

Garfinkel and 

Stellman 

(1988)1 

1982 58.9% 18.7% 22.4% 41.1% 0.54 

Assumed ratios by years (nontraditional societies)4 

Year 

Ratio 0.25 0.30 

1960 1965 1970 1975 1980 1985 

0.20 0.35 0.40 0.45 

1

Using age distribution of never-smoking cases.

2

Using age distribution of ever-smoking cases.

3

Smoking status of general population.

4

Traditional societies (Japan, Greece, China, Hong Kong) are estimated to lag

these ratios by

about 8 years, based on data in Koo et al. (1983) and Sobue et al. (1990).

However, because the

bias for the traditional societies is very low, changes in values of this parameter

have little effect.

To calculate the individual elements, c0jk, of Table B-7, it is necessary to 

establish concordance factors--that is, the cross products in 2 x 2 tables of 

smoking status of husbands and wives by smoking level of the wives. Using 

data from Sutton (1980), Lee (1987b), Akiba et al. (1986), and Hirayama (1984) 

and the detailed data in Lee (1987b) on never-smokers, current smokers, and 

former smokers, we have calculated that an appropriate average concordance 

factor for current smoking wives and ever-smoking husbands versus neversmoking wives and never-smoking husbands is 3.2; for ever-smoking wives and 

husbands versus never-smoking wives and husbands, it is 2.8, and for former 

B-17 
smoking wives and ever-smoking husbands versus never-smoking wives and 

husbands, it is 2.2. 

study to study, but the effect of the variability should tend to cancel out as the 

studies are 

aggregated. 00. and a quantity s0 = c0j. are obtained 

from smoking prevalence data in the study itself, in a related study on the same cohort, or as a last resort 

from national statistics. tics are used, care must be taken to use 

the rates from an age distribution that is consistent with the age distribution of 

the passive smoking cases. 01. and c02. + c03. are taken from the 

study or are estimated from Table B-9. 02. is estimated to be 10% 

of (c02. + c03.); c03. is 90%. 000 and c001 are obtained from c00. and the 

proportion of never-smoking controls in the study who are married to either 

never-smokers or ever-smokers. 010 and c011 are obtained by 

solving the equations 

c010 + c011 = c01. and (c000 × c011)/(c001 × c010) = 2.2. 00 = c0j0 and s01 = c0j1 are 

obtained from the equations s00 + s01 = s0 and (s01 × c000)/(c001 × s00) = 2.8. 020 + 

c030 = s00 - c010 and c021 + c031 = s01 - c011. 020 and c021 are then assumed to 

be 10% of c020 + c030 and c021 + c031, respectively, and c030 and c031 are assumed to be 

90%. 

To obtain the elements for the subject cases (i = 1) in Table B-7, it is 

necessary first to set up relative risks for the passively exposed (k = 1) and not 

passively exposed (k = 0) wives by observed smoking status (j = 0,1,2,3). 

risks are shown in Table B-10. 

In most instances, the relative risk, RR(e), for female ever-smokers can be 

obtained from the study itself or from a related paper (Table B-11). 

instances, it is necessary to estimate RR(e) from other studies similar in time and 

locale. 

explanation above) that the misclassified regular smoker risk, RR(a)3, is equal to 

the self-reported current smoker risk. 3 can 

be assumed to be equal to 1.24 × RR(e) based on the data in Table B-12. 

Because occasional smokers have mean cotinine levels that are 16% of those of 

regular smokers, it is assumed that RR(a)2 - 1 = 0.16(RR(a)3 - 1), and because the 

former smokers (j = 1) are said to be, on average, long term (Wald et al., 1986; 

Lee, 1987b), we have averaged the data of Alderson et al. (1985), Lubin et al. 

(1984), and Garfinkel and Stellman (1988) for the ratio of excess risk of 10+ 

year former smokers to the excess risk for current smokers and found it to be 

9%. 1 - 1 = 0.09 (RR(a)3 -1). 

These concordance factors can be expected to vary from 

The element c

If national statis

The elements c

The element c

The elements c

The elements c

Terms s

Then c

The values of c

These 

In a few 

In some papers, a current smoker risk also is given. We assume (see 

Where only RR(e) is available, RR(a)

Thus, RR(a)

B-18
Table B-10. Notation for observed lung cancer relative risks for exposed (k=1) and

nonexposed (k=0) wives by the wife's smoking status, using average neversmoking wives RR(a)0 as the reference category 

Wife's smoking status 

Husband's 

smoking status 

Never 

(j = 0) 

Former 

(j = 1) 

Occl. 

(j = 2) 

Reg.

(j = 3) 

Never (k=0) RR00 RR10 RR20 RR30 

Ever (k=1) RR01 RR11 RR21 RR31 

Weighted RR(a)0 = RR(a)1 RR(a)2 RR(a)3 

1.00 

avg.

active risk 

RR(p)j = 

RRj1/RRj0 

Passive risk1 

RR(p)0 RR(p)1 RR(p)2 RR(p)3 

1

Observed passive risk--the ratio of the exposed risk to the unexposed risk in

each column. 

B-19 
Table B-11. Prevalences and estimates of lung cancer risk associated with active

and passive smoking 

Ever-smokers Never-smokers 

Casecontrol Prev. 

(%)1 RR2 

Prev. of 

exposed

(%)3 

Crude 

RR2, 4

 Adj.

RR2, 4, 5 

AKIB 21 2.38 

(1.67,

3.39) 

70 1.52 

(0.96, 2.41) 

1.5 

(1.0, 

BROW6 29 4.30 

(2.24,

8.24) 

15 

12 

1.52 

(0.49, 4.79)

1.82 

(0.45,

7.36)7 

* 

1.68 

(0.39, 6.90)7 

BUFF 59 7.068 

(5.18,

9.63) 

84 0.818 

(0.39, 1.66) 

* 

CHAN 26 3.48 

(2.42,

4.99) 

47 0.75 

(0.48, 1.19) 

* 

CORR 47 12.40 

(8.35,

18.4) 

46 2.079 

(0.94, 4.52) 

* 

FONT10 4311 8.011 63 

66 

64 

1.37 

(1.10, 1.69)

1.21 

(0.94, 1.56)

1.32 

(1.08, 1.61) 

1.29 

(1.03, 1.62)

1.28 

(0.98, 1.66)

* 

GAO 18 2.54 

(2.06,

3.12) 

74 1.19 

(0.87, 1.63) 

1.3412,13 

GARF 3411 6.011 61 1.31 

(0.93, 1.85) 

1.7014 

(0.98, 2.94)7 

GENG 41 2.7715 

(1.89,

4.07) 

44 2.16 

(1.21, 3.84) 

* 

HIRA16 16 3.2017 

(2.67,

3.83) 

77 1.5312 

(1.10, 2.13) 

1.6412 

* 

HUMB 41 16.3 

(10.5,

25.1) 

56 2.34 

(0.96, 5.69) 

2.2 

(0.9, 5.5) 

INOU 16 1.66 

(0.73,

3.76) 

64 2.5518 

(0.90, 7.20) 

2.5412,19 

* 

JANE 4211 8.011 6820 0.86 

(0.57, 1.29) 0.93/0.4421 

Crude 

2.5) 

B-20
Table B-11. (continued) 

Ever-smokers Never-smokers 

Casecontrol Prev. 

(%)1 RR2 Prev. of 

exposed

(%)3 

Crude 

RR2, 4

 Adj.

RR2, 4, 5 

KABA22 42 5.90 

(4.53,

7.69) 

60 0.79 

(0.30, 2.04) 

* 

KALA 17 3.32 

(2.12,

5.22) 

60 1.6223 

(0.99, 2.65)

1.4123 

(0.78, 2.55) 

1.92 

(1.02, 3.59)7 

KATA 28 1.21 

(0.50,

2.90) 

82 *24 * 

KOO 32 2.77 

(1.96,

3.90) 

49 1.55 

(0.98, 2.44) 

1.64 

LAMT 24 3.77 

(2.96,

4.78) 

45 1.65 

(1.22, 2.22) 

* 

LAMW 22 4.12 

(2.79,

6.08) 

56 2.5125 

(1.49, 4.23) 

* 

LEE 6026 4.6126 68 1.03 

(0.48, 2.20) 

0.75/1.6027 

LIU 0.05 * 87 0.74 

(0.37, 1.48) 

0.77 

(0.35, 1.68) 

PERS 3711 4.211 43 1.28 

(0.82, 1.98) 

1.2 

(0.7, 2.1)7 

SHIM 2111 2.811 56 1.0828 

(0.70, 1.68) 

* 

SOBU 21 2.81 

(2.22,

3.57) 

54 1.0623 

(0.79, 1.44)

1.7723 

(1.29, 2.43) 

1.1323 

(0.78, 1.63)7 

1.5723 

(1.07, 2.31)7 

SVEN 43 5.97 

(4.11,

8.67) 

66 1.2629 

(0.65, 2.48) 

1.429 

TRIC 10 2.8130 

(1.69,

4.68) 

52 2.0830 

(1.31, 3.29) 

* 

WUWI 37 2.24 

(1.92,

2.62) 

55 0.79 

(0.64, 0.98) 

0.7 

Crude 

(continued on the following page)

B-22
Table B-11. (continued) 

Ever-smokers Never-smokers 

Casecontrol Prev. 

(%)1 RR2 Prev. of 

exposed

(%)3 

Crude 

RR2, 4

 Adj.

RR2, 4, 5 

BUTL 

(Coh) 

1411 4.011 * .4532 2.02 

(0.48, 8.56)7 

GARF 

(Coh) 

2233 3.5833 72 * 1.1712 

(0.85, 1.61)7 

HIRA 

(Coh) 

16 3.2017 

(1.96,

3.90) 

77 1.38 

(1.03, 1.87) 

1.61 

* 

HOLE34 

(Coh) 

56 4.211 73 2.27 

(0.40, 12.7) 

1.99 

(0.24, 16.7)7 

Crude 

2

1

Percentage ever-smokers in controls of whole study (or parent study).

2

Parentheses contain 90% confidence limits, unless noted otherwise. Crude ORs 

and their 

confidence limits were calculated by the reviewers wherever possible.

Boldface type indicates

values used for analysis in text of this report. OR for case-control studies; 

relative risk (RR) for

cohort studies. The reference category for active smoking is all never-smoking;

for passive

smoking, it is unexposed never-smokers.

3

Percentage of never-smoking controls exposed to spousal smoking, unless

noted otherwise. 

4

ORs for never-smokers applies to exposure from spousal smoking, unless

indicated otherwise. 

5

Calculated by a statistical method that adjusts for other factors (see Table 5-5).

6

Adenocarcinoma only. Data and OR values communicated from author 

(Brownson).

7

95% confidence interval (C.I.).

8

Exposure to regularly smoking household member. Differs slightly from

published value of

0.78, wherein 0.5 was added to all exposure cells.

9

Excludes bronchioalveolar carcinoma. Crude OR with bronchioalveolar 

carcinoma included is 

reported to be 1.77, but raw data for calculation of confidence interval are not

provided.

10The first, second, and third entries are calculated for population controls, colon

cancer controls, 

and both control groups combined, respectively. For adenocarcinoma alone, 

the corresponding

ORs, both crude and adjusted, are higher by 0.15 to 0.18.

11From other studies similar in location and time period (see Table 5-7).

12Composite measure formed from categorical data at different exposure levels. 13For GAO, data are given as (number of years lived with a smoker, adj. OR): (<

20, 1.0), (20-29,

1.1), (30-39, 1.3), (40+, 1.7).

14Estimate for husband smoking 20 cigarettes per day.

15Crude OR reported in study is 3.05 (95% C.I. = 1.77, 5.30); adjusted OR is 2.6

(95% C.I. = 1.4,

4.6). 

B-23 
16Case-control study nested in the cohort study of Hirayama. OR for eversmokers is taken from 

cohort study. This case-control study is not counted in any summary results

where HIRA(Coh)

is included. 

17Crude OR is calculated from prospective data in Hirayama (1988). Adjusted

OR for eversmokers given there is 2.67 (no confidence interval).

18OR reported in study is 2.25, in contrast to the value shown that was

reconstructed from the 

confidence intervals reported in the study; no reply to inquiry addressed to

author had been 

received by press time.

19For Inoue, data are given as (number of cig./day smoked by husband, adj. OR):

(< 19, 1.58),

(20+, 3.09).

20Taken from Kabat (1990) as closest in time and place.

21From subject responses/from proxy responses.

22For second KABA study (see addendum in study description of KABA),

preliminary

unpublished data and analysis based on ETS exposure in adulthood indicate

68% of 

never-smokers are exposed and OR = 0.90 (90% C.I. = 0.51, 1.58), not

dissimilar from the table 

entry shown.

23For the first value, "ETS exposed" means the spouse smokes; for the second

value, "ETS 

exposed" means a member of the household other than the spouse smokes.

24Odds ratio is not defined because number of unexposed subjects is 0 for cases

or controls. 

25Table entry is for exposure to smoking spouse, cohabitants, and/or coworkers;

includes lung

cancers of all cell types. The OR for spousal smoking alone is for

adenocarcinoma only:

2.01 (90% C.I. = 1.20, 3.37).

26From Alderson et al. (1985).

27From subject responses/from spouse responses.

28From crude data estimated to be the following: exposed cases 52, exposed

controls 91, 

unexposed cases 38, unexposed controls 72.

29Exposure at home and/or at work.

30Known adenocarcinomas and alveolar carcinomas were excluded, but 

histological diagnosis was

not available for many cases. Data are from Trichopoulos et al. (1983). 31Raw data for WU is from Table 11 of the Surgeon General's report (U.S.

DHHS, 1986). Data 

apply to adenocarcinoma only.

32RR is based on person-years of exposure to spousal smoking. Prevalence in 

those units is 20%. 

33Prevalence is calculated from figures in Hammond (1966) for the age

distribution of the cases. 

RR is from U.S. Surgeon General (U.S. DHHS, 1982).

34RR values under never-smoker are for lung cancer mortality. For lung cancer

incidence, crude 

RR is 1.51 (90% C.I. = 0.41, 5.48) and adjusted RR is 1.39 (95% C.I. = 0.29,

6.61). 

*Data not available. 

B-24 
Table B-12. Observed ratios of current smoker lung cancer risk to ever-smoker risk

for females 

Lung cancer RR Ratio 

Study Exposed 

cases 

plus

controls 

Current 

smoker 

Eversmoker Current smoker RR/

ever-smoker RR 

Alderson 

et al. (1985) 

901 4.5 4.75 0.95 

Buffler 

et al. (1984) 

701 7.9 6.9 1.15 

Garfinkel 

and 

Stellman 

(1988) 

832 12.7 8.35 1.52 

Humble et 

al. (1985) 

268 18.0 13.0 1.38 

Svensson 

et al. (1989) 

261 8.46 6.10 1.39 

Wu et al. 

(1985) 

Overall 

317 

3,280 

6.5 

8.05 

4.4 

6.52 

1.48 

1.241 

1

The summary ratio of 1.24 is the geometric mean of the individual ratios

weighted by the

exposed cases plus controls in that study. 

The elements RR00 and RR01 are obtained from the observed passive 

relative risk in the 

study and the never-smoking population weights for controls in Table B-7 by 

solving the 

equations 

1.00 = [(RR00 × c000) + (RR01 × c001)]/(c000 + c001) (B-3) 

and 

RR01 /RR00 = RR(p)0. (B-4) 

Various assumptions regarding passive risks can be used for j = 1,2, and 3. 

We have assumed, based on the data in Varela (1987), who found that 242 longterm former smokers had essentially the same passive risk as 197 never-smokers, 

that the passive risk for former smokers is the same as for never-smokers, 

namely, that RR(p)1 = RR(p)0. Passive relative risks for female smokers were 

taken from seven of the passive smoking studies (Akiba et al., 1986; Brownson 

B-25 
et al., 1987; Buffler et al., 1984; Humble et al., 1987; Koo et al., 1985; Wu et al., 

1985; Hole et al., 1989). 

trend with either active smoking risk or passive smoking risk. 

mean estimate is 1.25. 

are exposed to considerable ETS from their own smoking, it is probable that the 

additional ETS from others will have an additive effect rather than a 

multiplicative effect. 

the active smoking risks of passively exposed and nonexposed current smokers 

such that RR21 - RR20 = RR31 - RR30 = 0.25, and RR21/RR20 = RR(p)2 and RR31/RR30 

= RR(p)3. 20 and RR30 are derived as follows: 

RR20 = RR(a)2 - 0.25 c021/c02., and RR21 = RR20 + 0.25 (B-5) 

RR30 = RR(a)3 - 0.25 c031/c03., and RR31 = RR30 + 0.25. (B-6) 

The relative risks for former smokers, RR10 and RR11, can be obtained by solving 

the equations 

RR(p)1 = RR11/RR10 (B-7) 

and 

RR(a)1 = [(RR10 c010) + (RR11 c011)]/(c010 + c011). (B-8) 

Crude versions of the elements c1jk (i = 1 for cases) are obtained by 

multiplying each element c0jk by its respective RRjk. 

give the case elements of Table B-7 by 

c0jkRRjk c1jk = 

(B-9) 

The next step is to set up Table B-8, which is the table of subjects by 

observed and true smoking status. is is done by multiplying the observed 

misclassification rates (Pho/P.j) from Tables B-3 and B-4 by the appropriate 

elements from Table B-7. 10 = c01.(P10/P.1). 

to use the true misclassification rates from Tables B-3 and B-4 on the theory that 

they would exhibit less variability in being transferred from the cotinine and 

discordant answer studies to the passive smoking calculations. 

method is laborious and, as is shown in the Correa example below, does not lead 

to increased accuracy. 

The next step is to develop a deletions table to implement Equation B-1 

above using the control and case smoking prevalences in Table B-7 and the 

The estimates range from 0.7 to 2.3 with no evident 

The weighted log 

Since the smokers not exposed to passive smoke already 

Therefore, we have assumed a difference of 0.25 between 

The values for RR

These are then normalized to 

Th

For example, P An attempt was made 

However, the 

B-26
distribution in Table B-8. i0k, in Table B-7 is multiplied 

by its appropriate observed misclassification factor, Ph0 /P.j, where h = j, to yield 

a deletion element to be subtracted from the appropriate observed wives' neversmoking-status elements: 000, c001, c100, and c101, to obtain corrected elements C000, 

C001, C100, and C101. 

(B-10) 

Once these corrected never-smoker elements are obtained, the relative risk 

corrected for smoker misclassification is obtained from Equation B-2; RR(c)0 = 

(C101 × C000)/(C100 × C001), and the bias becomes RR(p)0 /RR(c)0. 

B.6. AMPLE 

Using the Correa et al. (1983) study as an example, the study tells us that 

52.8% of the wives never smoked and that 45.9% of the never-smoking wives 

were exposed to their spouses' smoke. 00. as 0.528 and c000 and 

c001 as 0.286 and 0.242, respectively. 0., the proportion of eversmokers, by difference is 0.472. 

smokers are 35.5% of the ever-smokers. 01., become 

0.167, and the current smokers (c02. + c03.) become 0.305. 

are divided into current regular smokers at 90% (c03. = 0.275) and current 

occasional smokers at 10% (c02. = 0.030). 

line of Table B-13. 

Using the concordance factor of 2.8 for ever-smokers versus neversmokers, it is possible to show as described above that 33.2% of the females in 

the Correa study would be ever-smoker wives with smoking husbands (s01) and 

that 14.0% would be ever-smoker wives with never-smoking husbands (s00). 

Similarly, using the concordance factor of 2.2 for former smoking wives and 

ever-smoking husbands versus the never-smokers, the former smoking wives 

married to ever-smoking husbands (c011) would be 10.9% of the total and those 

married to the never-smoking husbands (c010) would be 5.8%. 

difference, exposed current smoking wives (c021 + c031) would be 22.3%, to be split 

into 20.1% regular smokers (c031) and 2.2% occasional smokers (c021), and the 

nonexposed current smoking wives (c020 + c030) would be 8.2%, split into 7.4% 

regular smokers (c030) and 0.8% occasional smokers (c020). 

all the elements needed in Table B-13 and the control part of Table B-7. 

The estimate of relative risk for passive smoking, RR(p)o, for females is 

2.07 (Correa et al., 1983). 

smoking from a related paper 

Each observed element, c

c

Thus, 

NUMERICAL EX

This establishes c

The quantity s

From Correa's Table 2 we find that the former 

Thus, the former smokers, c

The current smokers 

These data are shown in the bottom 

Then by 

These data now supply 

The age- and sex-adjusted relative risk for current 

B-27
Table B-13. Observed smoking prevalence among the controls--Correa example 

Wife's smoking status 

Husband's 

smoking status Never Former Occasional Regul 

ar 

All 

Never 0.286 0.058 0.008 0.074 0.426 

All 0.528 

Ever 0.242 0.109 0.022 0.201 0.574 

0.167 0.030 0.275 1.000 

(Correa et al., 1984) is 12.6. The ratio of female smoking crude risk to the 

average for males and females is about 80%, indicating an age-adjusted current 

female risk of about 10. (Note: This is different from the current smoker relative 

risk that would be calculated from the crude ever-smoker risk of 12.4 used in 

Table 5-7 [of this report] and Table B-3. The adjusted risk is used here simply 

as an example.) With these inputs and the weights of controls in the study, the 

various exposed and nonexposed relative risks are those shown in Table B-14. 

The weighted average risk for the occasional smokers is calculated as 0.16 

(current regular risk ! 1) + 1, which for this example is 0.16 (10 ! 1) + 1 = 2.44. 

The weighted average risk for former smokers is 0.09 (current regular risk ! 1) + 

1, which is 0.09 (10 ! 1) + 1 = 1.81. The weighted average risks are split 

between never-smoking and ever-smoking husbands by using the passive risks, 

the population weights, and Equations B-3, B-4, B-5, B-6, B-7, and B-8. A 

crude case prevalence table is then made up (Table B-15) by multiplying each c0jk 

by its respective RRjk. This table is then normalized (Equation B-9) by dividing 

by 3.653 to yield Table B-16, which is the lower half of Table B-7 for this 

example. 

The smoking status distribution table (Table B-17) is developed, as 

described above, from the misclassification factors in Tables B-3 and B-4 and 

the bottom line of Table B-13. For example, to arrive at element (h = 3, j = 0), 

the observed P.3 of 0.275 is multiplied by an observed misclassification factor of 

0.0109 (from Table B-3) to yield 0.003. To explore the value of using the true 

misclassification factors instead of the observed ones, the true and observed m's 

were carried to five decimal places. An approximation procedure to determine 

the true smoking probabilities P0., P1., P2., and P3. was carried through four stages. 

The resulting total true distribution of smoking status rounded to three decimal 

places was essentially identical to the distribution shown in the bottom line of 

Table B-17. Similarly, any differences in the individual elements were very 

small and beyond the accuracy of the underlying data. 

B-28 
Table B-14. Observed relative risks--Correa example 

Wife's smoking status 

Husband's 

smoking status 

Never 

(j = 0) 

Former 

(j = 1) 

Occasional 

(j = 2) 

Regular

(j = 3) 

Never 0.67 1.07 2.26 9.82 

Ever 1.39 2.21 2.51 10.07 

Weighted 

average 

1.00 1.81 2.44 10.00 

Passive risk, 

RR(p), 

2.07 2.07 1.11 1.025 

Table B-15. Crude case table, prevalence of cases by smoking status--Correa

example 

Wife's smoking status 

Husband's 

smoking status Never Former 

Occasional Regular All 

Never 0.192 0.062 0.018 0.726 0.998 

Ever 0.336 0.240 0.055 2.024 2.655 

All 0.528 0.302 0.073 2.750 3.653 

Table B-16. Normalized case table, prevalence of cases by smoking status--Correa

example 

Wife's smoking status 

Husband's 

smoking status 

Never Former Occasional Regular All 

Never 0.052 0.017 0.005 0.199 0.273 

Ever 0.092 0.066 0.015 0.544 0.727 

All 0.144 0.083 0.020 0.743 1.000 

B-29 
Table B-17. Distribution of subjects by observed and true smoking status for wives

in Correa example1 

Wife's true smoking status 

Wife's observed 

smoking status 

Never 

(h = 0) 

Former 

(h = 1) 

Occasional 

(h = 2) 

Regular

(h = 3) All 

Never (j = 0) 0.499 0.019 0.007 0.003 0.528 

Ex (j = 1) 0 0.160 0.004 0.003 0.167 

Occasional (j = 2) 0 0 0.030 0 0.030 

Regular (j = 3) 0 0 0 0.275 0.275 

All 0.499 0.179 0.041 0.281 1.000 

1

 Values rounded to three decimal places. 

The Correa study was chosen as our example because the female ever-smoking 

prevalence is reasonably high (47.2%) and the female current smoker lung 

cancer relative risk is high (10), both of which are factors that should lead to a 

greater rather than a smaller correction to the passive risk. 

We now can set up a deletions table, Table B-6, which is the equivalent of 

equations B-1 and B-10 above, by multiplying the control and case elements in 

Table B-13 and B-16 by the appropriate observed misclassification rates Ph0 /P.j 

(h = j), namely, P10/P.1 = 0.117, P20 /P.2 = 0.242, and P30 /P.3 = 0.0109. For 

example, to get 0.00679, one multiplies 0.058 from Table B-10 by 0.117. Then 

the first three columns are summed horizontally to get the fourth column, which 

is then subtracted from the elements in the "never" columns of Tables B-13 and 

B-16 (column 5) to get the "corrected never" elements (column 6). 

The corrected passive risk is now obtained by taking the cross-product 

from the "corrected never" column: (0.07461 × 0.27647)/(0.04666 × 0.22173) = 

1.99, which is to be compared with the observed risk of 2.07. The bias is then 

2.07/1.99 = 1.04. It is interesting to note how sensitive the bias is to the smoker 

relative risk that is assumed. When the crude smoker risk (no age adjustment) of 

12.4 for ever-smokers, equivalent to about 15.4 for current regular smokers, is 

assumed, the corrected passive risk estimate is 1.89 and the bias is twice as great 

at 1.10. 

B-30 
APPENDIX C 

LUNG CANCER MORTALITY RATES ATTRIBUTABLE TO SPOUSAL 

ETS IN INDIVIDUAL EPIDEMIOLOGIC STUDIES 
APPENDIX C. LUNG CANCER MORTALITY RATES ATTRIBUTABLE TO SPOUSAL 

ETS IN INDIVIDUAL EPIDEMIOLOGIC STUDIES 

Many of the epidemiologic studies on lung cancer and environmental 

tobacco smoke (ETS) were part of larger investigations that included eversmokers and never-smokers. For those studies, the lung cancer mortality rate 

(LCMR) for all causes, appropriate to the location and time period of the study, 

has been obtained from other sources. Those values and parameter estimates 

from the studies are used to partition the excess LCMR from all causes (i.e., the 

excess after allowance for baseline sources) into components attributable to 

ever-smokers (from current and former smoking) and never-smokers (from 

exposure to spousal ETS) and to estimate the LCMR in the subpopulations of 

interest--unexposed never-smokers (meaning not exposed to spousal smoking), 

exposed never-smokers (exposed to spousal smoking), and ever-smokers 

("exposed" is not used to mean exposure to nonspousal ETS, which applies to 

the whole target population). The method is explained in Sections 6.3.1 and 

6.3.2. 

Lung cancer mortality rates for the case-accrual periods of case-control 

studies are displayed in Table C-1. For the studies that collected data on both 

ever-smokers and never-smokers, the parameter estimates used are shown in 

Table C-2. The value for the lung cancer mortality rate is from Table C-1, and 

the remaining estimates are from individual study data. The rate for the 

followup period of the study is estimated for HIRA(Coh) and GARF(Coh). 

These values may not be very "representative" for lung cancer mortality in these 

two cohort studies because they extended over several years, and the LCMRs 

changed from year to year, particularly in the United States. This same difficulty 

arises in choosing a "representative" year for lung cancer mortality in the casecontrol studies, although to a lesser degree. The most extreme examples are 

KABA, PERS, INOU, and GARF, with case-accrual periods of 10 years or 

more. 

C-1 
Table C-1. Female lung cancer mortality from all causes in case-control studies1 

Study Locatio 

n 

Case 

accrual Begin Averag 

e 

End 

Accrua 

l10 yrs 

average 2 

Accrua 

l-20 

yrs 

averag 

e2 

AKIB Japan 1971-80 5.13 6.05 7.08 4.57 2.30 

BROW USA 1979-82 15.68 17.29 19.09 9.49 4.75 

BUFF USA 1976-80 13.94 15.29 17.20 7.86 4.38 

CHAN HK 1976-77 23.59 23.59 23.59 19.05 * 

CORR3 USA 1979-82 26.0 26.0 9.49 4.75 

GAO4 China 1984-86 * 18.0 * 14.33 5.13 

GARF USA 1971-81 9.45 13.55 17.20 6.87 * 

GENG4 China 1983 * 27.8 * 13.83 * 

HIRA5 Japan 1965-81 4.46 5.70 7.08 4.01 * 

HUMB3 USA 1980-84 17.7 * 10.55 5.13 

INOU Japan 1973-83 5.55 6.53 7.46 4.93 2.95 

JANE3 USA 1982-84 23.7 * 9.06 5.42 

KABA6 USA 1961-80 4.69 13.20 17.20 6.61 4.16 

KALA6 Greece 1987-89 6.58 6.586 6.58 6.75 5.836 

KATA6 Japan 1984-87 * 7.466 * 4.66 2.26 

KOO HK 1981-83 22.34 22.61 22.75 19.82 * 

LAMT6 HK 1983-86 22.75 23.46 23.69 21.33 * 

LAMW HK 1981-84 22.34 22.88 23.69 20.09 * 

LEE Eng/W

al 

1979-82 16.28 17.11 17.89 12.60 8.1 

PERS6 Sweden 1961-80 3.71 5.09 7.56 3.956 * 

SHIM6 Japan 1982-85 7.46 7.466 7.46 5.65 4.28 

SOBU6 Japan 1986-88 7.46 7.466 7.46 6.36 4.93 

SVEN6 Sweden 1983-85 7.72 7.726 7.72 5.78 3.80 

TRIC Greece 1978-80 6.88 6.40 5.99 5.75 5.317 

WU USA 1981-82 17.20 18.15 19.09 10.14 4.96 

WUWI8 China 1985-87 * 11.6 * 9.22 * 

26.0 

17.7 

23.7 

1

Rates are per 100,000 per year, standardized to the 1950 world population age

distribution. Data 

are drawn from Kurihara et al. (1989), and annual rates for 2-year periods were

averaged over

the years cases were accrued for each study unless otherwise noted. Where part

(or all) of the

accrual period fell 1 or 2 years outside the years for which rates were available,

rates from the 

nearest 2-year period available were assumed to apply to the missing years.

U.S. rates are for 

white females only. 

(continued on the following page) 

C-2 
2

The accrual-10 years average is the average for the time period of the same

length as the accrual

period but 10 years previous to it. Similarly, the accrual-20 years value is for

the time period 20

years previous to the accrual period.

3

Data for accrual period from 1978-82 rates in IARC (1987b), standardized to

1950 world 

population from Kurihara et al. (1989). For Correa, weighted average of white

and black rates; 

for Humble, weighted average of Hispanic and non-Hispanic white rates.

4

Accrual period data for GAO and GENG derived from IARC (1987b) by

standardizing to same

1950 world population used by Kurihara et al. (1989). GAO rates are for 1978-

82; GENG, 1981-

82. For the accrual-10 years value, GAO and GENG are 1973-75 rates

standardized to the 1960 

world population from China Map Press (1979). The GAO accrual-20 years

value is nonadjusted

1961 rate from Kaplan and Tsuchitani (1978).

5

The nested case-control study of Hirayama (mortality rates for this study also

apply to the cohort

study in which it is nested).

6

Where rates for the period were not available in Kurihara et al. (1989),

substitutions were made as 

follows: Kalandidi from 1984-85 rates; Kabat, 1982-83; Katada, 1982-83; 

Lam, T., 1984-85; 

Pershagen, 1952-53; Shimizu, 1982-83; Sobue, 1982-83; and Svensson, 1982-

83.

7

World-standardized rate for 1961-65 from Katsouyanni et al. (1990) (in Greek:

translation

provided by Trichopoulos).

8

Accrual period value estimated by multiplying LCMR in Shanghai for period

1978-82 

(standardized to the 1950 world population) by the ratio of LCMRs in Liaoning

and Heilonjiang

to Shanghai, for the period 1973-75 (standardized to the 1960 world

population). Data are from 

China Map Press (1979). Value for accrual-10 years is the 1973-75 rate. 

*Data not available. 

C-3 
Table C-2. Parameter values used to partition female lung cancer mortality into 

component sources1 

Ever-smokers 

Case-control Lung 

cancer 

mortality 

Prevalence 

(%) 

Relative 

risk 

Percentage

exposed

(%) 

Relative 

risk 

AKIB 6.05 21 2.38 70 1.50 

BROW 17.29 29 4.30 15 1.50 

BUFF 15.29 59 7.06 84 0.81 

CHAN 23.59 26 3.48 47 0.74 

CORR 26.00 47 12.40 46 1.90 

GAO 18.00 18 2.54 74 1.19 

GARF(Coh) 7.002 33 3.58 72 1.15 

GENG 27.80 41 2.77 44 2.16 

HIRA 5.70 16 3.20 77 1.53 

HIRA(Coh) 5.702 16 3.20 77 1.37 

HUMB 17.70 41 16.30 56 1.98 

INOU 6.53 16 1.66 64 2.55 

KABA 13.20 42 5.90 60 0.74 

KALA 6.58 17 3.32 60 1.92 

KOO 22.61 32 2.77 49 1.54 

LAMT 23.46 24 3.77 45 1.64 

LAMW 22.88 22 4.12 56 2.51 

LEE 17.11 60 4.61 68 1.01 

SOBU 7.46 21 2.81 54 1.13 

SVEN 7.72 43 5.97 66 1.19 

TRIC 6.40 11 2.81 52 2.08 

WU 18.15 58 4.38 60 1.31 

WUWI 11.60 37 2.24 55 0.78 

Never-smokers 

1

For studies with data on both ever-smokers and never-smokers. Table entries 

are drawn from 

Tables 5-8, B-11, and C-1, which contain explanatory footnotes.

2

Average of world-standardized rates for location during followup period of

study from Kurihara

et al. (1989). White female rates used for GARF. 

C-4 
The estimates of prevalence of ever-smokers and the percentage of neversmokers exposed to spousal smoking are the observed proportions in the control 

group. The extent to which the control group is representative of the country's 

population differs between studies; the study reviews in Appendix A provide 

more detailed information. The restriction of cell types among cases in some 

studies is another consideration. Active smoking is much more strongly 

associated with occurrence of squamous and small cell carcinoma than with 

large cell carcinoma and adenocarcinoma. FONT presents evidence that passive 

smoking is more associated with adenocarcinoma than with other cell types. As 

noted in Table 5-14, some studies excluded candidate lung cancer cases of 

specific histopathological types. This may produce some bias and distortion of 

comparison between studies. For example, BROW includes only cases of 

adenocarcinoma, which should bias the relative risk of ever-smokers toward 

unity, thus attributing too little lung cancer mortality to active smoking and too 

much to passive smoking and background sources. 

Of a more positive nature, there is some advantage to using data from a 

single study to assign attributable fractions to different causes. To estimate the 

yearly number of lung cancers from each cause, the fraction is multiplied by the 

LCMR for the location and time of the study; that figure has to be obtained from 

sources on vital statistics. As seen in Table C-2, the mortality rates from lung 

cancer vary considerably between and within countries. For example, the rates 

used for studies in the United States range between 9 and 26. Applying the lung 

cancer rate suitable to each individual study should provide better estimates for 

comparison within a country than using a single figure for the whole country for 

some specific year. 

Despite the reservations described, partitioning the lung cancer mortality 

for each study into components attributable to ever-smoking, spousal ETS, and 

baseline sources (nontobacco smoke and nonspousal ETS) provides a broad 

overview worth noting. The calculated values are shown in Table C-3. 

C-5 
Table C-3. Female lung cancer mortality rates by attributable source1 

Baseline 

sources2 Spousal

smoking 

Ever-smoking 

Study Location No. % No. % No. % 

AKIB Japan 3.47 57 0.96 16 1.61 27 

BROW USA 8.22 48 0.44 3 8.63 50 

BUFF USA 3.34 22 0.00 0 11.95 78 

CHAN HK 14.34 61 0.00 0 9.25 39 

CORR USA 2.89 11 0.63 2 22.47 86 

GAO China 12.36 69 1.42 8 4.22 23 

GARF(Coh

) 

USA 3.41 49 0.25 4 3.34 47 

GENG China 10.67 38 3.21 12 13.92 50 

HIRA(Coh

) 

Japan 3.28 58 0.78 14 1.63 29 

HUMB USA 1.57 9 0.51 3 15.62 88 

INOU Japan 2.97 45 2.47 38 1.09 17 

KABA USA 4.32 33 0.00 0 8.88 67 

KALA Greece 3.04 46 1.39 21 2.15 33 

KOO HK 11.41 50 2.05 9 9.14 40 

LAMT HK 10.94 47 2.39 10 10.12 43 

LAMW HK 7.35 32 4.85 21 10.68 47 

LEE Eng./Wale 

s 

5.37 31 0.01 0 11.73 69 

SOBU Japan 5.05 68 0.28 4 2.13 29 

SVEN Sweden 2.19 28 0.16 2 5.37 70 

TRIC Greece 3.42 53 1.71 27 1.27 20 

WU USA 5.17 28 0.40 2 12.58 69 

WUWI China 7.95 69 0.00 0 3.65 31 

1

Rates are per 100,000 per year. Data not available for GARF, JANE, PERS, 

SHIM, BUTL(Coh),

and HOLE(Coh).

2

Nonspousal ETS and non-ETS sources. 

C-8 
. Estimates of relative risk for exposure to spousal ETS (RR2 in notation of 

Section 6.3.2) less than 1.0 (see Table 5-9) were replaced by 1.0 to avoid a 

negative LCMR attributable to spousal ETS and the consequent inflation of the 

LCMR attributable to baseline sources and ever-smoking. Aside from the 

studies for Hong Kong and China, estimates of lung cancer mortality due to 

background sources cluster in the interval 1.5 to 5.5 (excluding BROW, which is 

strongly biased), predominantly from 3 to 5. The values for Hong Kong and 

China, however, are much higher, ranging from 7 to 14.5. The presence of 

indoor sources of non-ETS encountered in some of the studies in China may be a 

factor, but there is no apparent explanation for the outcome in Hong Kong. 

Assuming that the background rate of lung cancer is much higher in Hong Kong 

(and possibly China) as it appears, then the question arises as to whether the high 

excess rate relative to other countries may be attributable to higher exposure to 

ETS aside from spousal smoking or whether it is more likely due to other causes. 

Summary data from the 10-country collaborative study of ETS exposure to 

nonsmoking women conducted by the International Agency for Research on 

Cancer (IARC) (Riboli et al., 1990) was kindly submitted to us for Hong Kong, 

Japan (Sendai), and the United States (Los Angeles, New Orleans) from Drs. 

L.C. Koo, H. Shimizu, A. Wu-Williams, and T.H. Fontham, respectively. The 

average cotinine/creatinine (ng/mg) levels for nonsmoking women who are not 

employed and not married to a smoker are close for Sendai, Los Angeles, and 

New Orleans, but they are several times higher for Hong Kong. Consequently, a 

high contribution to background lung cancer mortality from ETS aside from 

spousal smoking cannot be eliminated as a factor. 

The lung cancer attributable to ever-smoking, spousal smoking, and 

baseline sources depends on the population proportions for those categories as 

well as the relative risks. Study estimates of the LCMR in each category, in 

units of lung cancer deaths per 100,000 at risk per year, are shown in Table C-4. 

C-9 
Table C-4. Lung cancer mortality rates of female ever-smokers (ES) and neversmokers (NS) by exposure status1 

Study Location 

(1)

Unexpos

ed 

NS2 

(2)

Expose

dNS3 

(3) 

ES 

(2) As a 

percenta

ge of (3) 

(2) - (1)

As a 

percentag

e of (3) -

(1) 

AKIB Japan 3.47 5.21 11.16 47 23 

BROW USA 8.21 12.32 37.99 32 14 

BUFF USA 3.34 3.34 23.59 14 0 

CHAN HK 14.34 14.34 49.91 29 0 

CORR USA 2.89 5.49 50.70 11 5 

GAO China 12.35 14.70 35.79 41 10 

GARF(Coh

) 

USA 3.41 3.92 13.54 29 5 

GENG China 10.66 23.03 44.62 52 36 

HIRA(Coh) Japan 3.28 4.49 13.49 33 12 

HUMB USA 1.57 3.11 39.66 8 4 

INOU Japan 2.96 7.56 9.80 77 67 

KABA USA 4.32 3.78 25.46 17 0 

KALA Greece 3.04 5.84 15.66 37 22 

KOO HK 11.41 17.57 39.98 44 22 

LAMT HK 10.94 17.94 53.12 34 17 

LAMW HK 7.35 18.45 55.89 33 23 

LEE Eng/Wal 5.36 5.42 24.91 22 0 

SOBU Japan 5.05 5.70 15.18 38 6 

SVEN Sweden 2.18 2.60 14.69 18 3 

TRIC Greece 3.41 7.10 14.99 47 32 

WU USA 5.16 6.77 26.85 25 7 

WUWI China 7.95 7.95 17.81 45 0 

1

Rates are per 100,000 per year. Data not available for GARF, JANE, PERS, 

SHIM, BUTL(Coh),

and HOLE(Coh).

2

Exposed to baseline sources--nonspousal ETS and non-ETS sources.

3

Exposed to baseline sources plus spousal ETS. 

C-10 
APPENDIX D 

STATISTICAL FORMULAE 
APPENDIX D. STATISTICAL FORMULAE 

D.1. CELL FREQUENCIES 

The observed outcome of a case-control study or a cohort study may be depicted in a 2 x 2 table, where a, b, 

c, and d are cell frequencies. 

ETS Exposed 

Yes No 

Lung Cancer Yes 

Present 

No 

D.2. CASE-CONTROL STUDIES 

The true (but unknown) odds ratio is estimated by the observed odds ratio (OR), 

OR = ad/bc. 

A confidence interval on the (true) odds ratio may be calculated from the normal approximation to the distribution of 

log(OR), the natural logarithm of OR (Woolf, 1955).  The variance of log(OR) is estimated by 

Var(log(OR)) = 1/a + 1/b + 1/c + 1/d 

and the standard error by its square root, 

1⁄2 SE(log(OR)) = (Var(log(OR))) . 

Approximate 90% confidence limits are given by 

log(OR) ± 1.645 SE(log(OR)). 

The value 1.645 is replaced by 1.96 for 95% confidence limits and, in general, by Z /2 for 100(1 - )% confidence 

limits.  The confidence bounds obtained in this way are sometimes called logit limits (Breslow and Day, 1980, p. 134). 

Significance level (p-value) of a test for effect, i.e., Ho: (true) odds ratio = 1 against the alternative Ha: (true) odds ratio 

> 1, is the area under the standard normal curve to the right of the value of the test statistic, given by 

log(OR)/SE(log(RR)). 

If the (true) odds ratios are assumed to be equal in k studies, then a pooled estimate is calculated from 

log(OR(P)) =  w  log(OR) / i i wi 

a b 

c d 

D-1 
where the summations are on i, from 1 to k; OR(P) is the pooled estimate; log(OR)

-1 th 

i is the logarithm of OR from the ith 

study; and wi = (Var(log(OR)i))  is the weight of the i  study (Breslow and Day, 1980).

D.3. COHORT STUDIES 

The true (but unknown) relative risk is estimated by the observed relative risk (RR), 

RR = (a/a+c)/(b/b+d). 

A confidence interval on the (true) relative risk may be calculated from the normal approximation to the distribution 

of log(RR), using the analogue of Woolf's method referred to above (Katz et al., 1978).  The variance of log(RR) is 

estimated by, 

Var(log(RR)) = c/(a2 + ac) + d/(b2 + bd) 

and the standard error by its square root, 

SE(log(RR)) = (Var(log(RR)))1⁄2. 

The remaining calculations follow the description for case-control studies in Section D.2 with "odds ratio" 

and "OR" replaced by "relative risk" and "RR," respectively.  The pooled estimate of relative risk from both casecontrol and cohort studies is calculated by the same methodology for pooling estimates from case-control studies or 

from cohort studies separately, i.e., the logarithm of each individual estimate is weighted inversely proportional to its 

estimated variance (Kleinbaum et al., 1982). 

D-2 
SELECTED BIBLIOGRAPHY 

Note:  This section includes all references cited in the report as well as additional references that were 

reviewed during the preparation of this report.  This bibliography is not intended to be a comprehensive list of all 

references available on the topic. 

Adams, J.D.; O'Mara-Adams, K.J.; Hoffmann, D. (1987) Toxic and carcinogenic agents in undiluted mainstream 

smoke and sidestream smoke of different types of cigarettes. Carcinogenesis 8(5):729-731. 

Aguayo, S.M.; Kane, M.A.; King, T.E.; Schwarz, M.I.; Grauer L.; Miller, Y.E. (1989) Increased levels of 

bombesin-like peptides in the lower respiratory tract of asymptomatic cigarette smokers. J. Clin. Invest. 

84:1105-1113. 

Akiba, S.; Kato, H.; Blot, W.J. (1986) Passive smoking and lung cancer among Japanese women. Cancer Res. 

46:4804-4807. 

Alderson, M.R.; Lee, P.N.; Wang, R. (1985) Risks of lung cancer, chronic bronchitis, ischaemic heart disease, and 

stroke in relation to type of cigarette smoked. J. Epidemiol. Community Health 39:286. 

Alfeim, I.; Randahl, T. (1984) Contribution of wood combustion to indoor air pollution as measured by mutagenicity 

in Salmonella and polycyclic aromatic hydrocarbon concentration. Environ. Mol. Mutagen. 6:120-121. 

American Academy of Pediatrics, Committee on Environmental Hazards. (1986) Involuntary 

smoking--a hazard to children. J. Pediatr. 77(5):755. 

Ames, B.N. (1983) Dietary carcinogens and anticarcinogens.  Science 221:1256-1264. 

Anderson, L.J.; Parker, R.A.; Strikas, R.A.; et al. (1988) Day-care center attendance and hospitalization for lower 

respiratory tract illness. Pediatrics 82:300-308. 

Andrae, S.; Axelson, O.; Bjorksten, B.; Fredriksson, M.; Ljellman, N-IM. (1988) Symptoms of bronchial 

hyperreactivity and asthma in relation to environmental factors. Arch. Dis. Child. 63:473-478. 

Aoki, Y.; et al. (1987) Smoking and health. Elsevier Science Publishers B.V. (Biomedical Division), pp. 483-486. 

Arundel, A.; Sterling, T.; Weinkam, J. (1987) Never-smoker lung cancer risks from exposure to particulate tobacco 

smoke. Environ. Intl. 13:409-426. 

Badre, R.; Guillerm, R.; Abran, N.; Bourdin, M.; Dumas, C. (1978) Atmospheric pollution by cigarette smoking. Ann. 

Pharm. Fr. 36:443-452. 

Baker, R.R.; Proctor, C.J. (1990) The origins and properties of environmental tobacco smoke.  Environ. Int. 16:231-

245. 

Basrur, P.K.; McClure, S.; Zilkey, B. (1978) A comparison of short-term bioassay results with carcinogenicity of 

experimental cigarettes. In: Nieburgs, H.E., ed. Prevention and detection of cancer, part 1, v. 2. New York: 

Marcel Dekker, pp. 2041-2048. 

Bellofiore, S.; Eidelman, D.H.; Macklem, P.T.; Martin, J.G. (1989) Effects of elastase-induced emphysema on airway 

responsiveness to methacholine in rats. J. Appl. Physiol. 66:606-612. 

R-1 
Benner, C.L.; Bayona, J.M.; Caka, F.M.; Tang, H.; Lewis, L.; Eatough, D.J. (1989) Chemical composition of 

environmental tobacco smoke. 2. Particle-phase compounds. Environ. Sci. Technol. 23:688-699. 

Bergman, A.B.; Wiesner, B.A. (1976) Relationship of passive cigarette smoking to sudden infant death syndrome. 

Pediatrics 58:665-668. 

Berkey, C.S.; Ware, J.H.; Dockery, D.W.; Ferris, B.G., Jr.; Speizer, F.E. (1986) Indoor air pollution and pulmonary 

function in preadolescent children. Am. J. Epidemiol. 123:250-260. 

Bernfeld, P.; Homburger, F.; Soto, E.; Pai, K.J. (1979) Cigarette smoke inhalation studies in inbred Syrian golden 

hamsters. J. Natl. Cancer Inst. 63:675-689. 

Best, E.W.R.; Josie, G.H.; Walker, C.B. (1961) A Canadian study of mortality in relation to smoking habits: A 

preliminary report. Can. J. Public Health 52:99-106. 

Bewley, B.R.; Halil, T.; Snaith, A.H. (1973) Smoking by primary schoolchildren: prevalence and associated 

respiratory symptoms. Br. J. Prev. Soc. Med. 27:150-153. 

Billick, I.H.; Baker, P.E.; Colome, S.D. (1988) Simulation of indoor nitrogen dioxide concentrations. In: Combustion 

processes and the quality of the indoor environment.  Harper, J.P., ed. Transaction of an international 

conference sponsored by the Air and Waste Management Association (TR-15). Niagara Falls, NY. 

Bisgaard, H.; Dalgaard, P.; Nyboe, J. (1987) Risk factors for wheezing during infancy: a study of 5953 infants. Acta 

Paediatr. Scand. 76:719-726. 

Black, N. (1984) Surgery for glue ear--a modern epidemic? Lancet 1:835-837. 

Black, N. (1985) The etiology of glue ear--a case-control study. Int. J. Pediatr. Otorhinolaryngol. 9:121-133. 

Bland, M.; Bewley, B.R.; Pollard, V.; Banks, N.M. (1978) Effect of children's and parents' smoking on respiratory 

symptoms. Arch. Dis. Child. 53:100-105. 

Blot, W.J.; Fraumeni, J.F. (1986) Passive smoking and lung cancer. J. Natl. Cancer Inst. 77(5):993-999. 

Breese-Hall, C.; Hall, J.H.; Gala, C.L.; MaGill, F.B.; Leddy, J.P. (1984) Long-term prospective study in children after 

respiratory syncytial virus infection. J. Pediatr. 105:358-364. 

Breslow, N.E.; Day, N.E. (1980) Statistical methods in cancer research. v. I--The analysis of case-control studies. 

Lyon, France: IARC Sci. Publ. No. 32. 

Breslow, N.E.; Day, N.E. (1987) Statistical methods in cancer research. v. II--The design and analysis of cohort 

studies. Lyon, France: IARC Sci. Publ. No. 82. 

Britten, N. (1988) Validity of claims to lifelong nonsmoking at age 36 in a longitudinal study. Int. J. Epidemiol. 

17(3):525-529. 

Bross, I.D.J.; Gibson, R. (1968) Risk of lung cancer in smokers who switch to filter cigarettes. Am. J. Public Health 

58:1396-1403. 

Brown, C.C.; Chu, K. (1987) Use of multistage models to infer stage affected by carcinogenic exposure: example of 

lung cancer and cigarette smoking. J. Chronic Dis. 40(2):171A-179A. 

Browne, C.L.; Keith, C.H.; Allen, R.E. (1980) The effect of filter ventilation on the yield and composition of 

mainstream and sidestream smoke.  Beitr. Tabakforsch. 10:81-90. 

R-2 
Brownson, R.C.; Reif, J.S.; Keefe, T.J.; Ferguson, S.W.; Pritzl, J.A. (1987) Risk factors for adenocarcinoma of the 

lung. Am. J. Epidemiol. 125:25-34. 

Brunekreef, B.; Boleij, J.S.M. (1982) Long-term average suspended particulate concentrations in smokers' homes. Int. 

Arch. Occup. Environ. Health 50:299-302. 

Brunekreef, B.; Fischer, P.; Remijn, B.; Van der Lende, R.; Schouten, J.; Quanjer, P.H. (1985) Indoor air pollution 

and its effects on pulmonary function of adult nonsmoking women. III. Passive smoking and pulmonary 

function. Int. J. Epidemiol. 14:227-230. 

Brunnemann, K.D.; Hoffmann, D.; Wynder, E.L.; Gori, G.B. (1976) Chemical studies on tobacco smoke: 37. 

Determination of tar, nicotine, and carbon monoxide in cigarette smoke. A comparison of international 

smoking conditions. In: Wynder, E.L.; Hoffmann, D; Gori, G.B., eds. Modifying the risk for the smoker: 

proceedings of the third world conference on smoking and health; June 1975; New York. U.S. Department 

of Health, Education, and Welfare, National Cancer Institute. DHEW Pub. No. (NIH) 76-1221, pp. 441-449. 

Brunnemann, K.D.; Adams, J.D.; Ho, D.P.; Hoffmann D. (1978) The influence of tobacco smoke on indoor 

atmospheres. II. Volatile and tobacco-specific nitrosamines in main and sidestream smoke and their 

contribution to indoor pollution. In: Proceedings of the 4th joint conference on sensing of environmental 

pollutants. Washington, DC: American Chemical Society, pp. 876-880. 

Brunnemann, K.D.; Kagan, M.R.; Cox, J.E.; Hoffmann, D. (1990) Analysis of 1,3-butadiene and other selected gasphase components in cigarette mainstream and sidestream smoke by gas chromatography--mass selective 

detection.  Carcinogenesis 11(10):1863-1868. 

Brunnemann, K.D.; Cox, J.E.; Hoffmann, D. (1992) Analysis of tobacco-specific N-nitrosamines in indoor air. 

Carcinogenesis (in press). 

Buffler, P.A.; Pickle, L.W.; Mason, T.J.; Contant, C. (1984) The causes of lung cancer in Texas. In: Mizell, M.; 

Correa, P., eds. Lung cancer: causes and prevention. New York: Verlag Chemie International, pp. 83-99. 

Burchfield, C.M.; Higgins, M.W.; Keller, J.B.; Howatt, W.F.; Butler, W.J.; Higgins, I.T.T. (1986) Passive smoking in 

childhood: respiratory conditions and pulmonary function in Tecumseh, Michigan. Am. Rev. Respir. Dis. 

133:966-973. 

Burney, P.G.; Britton, J.R.; Chinn, S.; et al. (1987) Descriptive epidemiology of bronchial reactivity in an adult 

population: results from a community study. Thorax 42:38-44. 

Burrows, B.; Halonen, M.; Barbee, R.A.; Lebowitz, M.D. (1981) The relationship of serum immunoglobulin E to 

cigarette smoking. Am. Rev. Respir. Dis. 124:523-525. 

Burrows, B.; Knudson, R.J.; Cline, M.G.; Lebowitz, M.D. (1988) A reexamination of risk factors for ventilatory 

impairment. Am. Rev. Respir. Dis. 138:829-836. 

Burrows, B.; Martinez, F.D.; Halonen, M.; Barbee, R.A.; Cline, M.G. (1989) Association of asthma with serum IgE 

levels and skin-test reactivity to allergens. N. Engl. J. Med. 320:271-277. 

Butler, T.L. (1988) The relationship of passive smoking to various health outcomes among Seventh-Day Adventists in 

California [dissertation]. Los Angeles: University of California at Los Angeles. 

Butler, W.J. (1990) Comments submitted to EPA on its draft report entitled "Health Effects of Passive Smoking: 

Assessment of Lung Cancer in Adults and Respiratory Disorders in Children," EPA/600/6-90/006A, May 

1990. 

R-3 
Butler, W.J. (1991) Supplementary information on confounding and the reported epidemiologic association between 

lung cancer and spousal smoking status (unpublished). 

Caddeback, J.E.; Donovan, J.R.; Burg, W.R. (1976) Occupational aspects of passive smoking. Am. Ind. Hyg. Assoc. 

J. 37:263-267. 

Cameron, P.; Kostin, J.S.; Oselett, B.; Stocker, R.; Tighe, G.; Winton, J.; Wolfe, J.H.; Zaks, J.M. (1969) The health of 

smokers' and nonsmokers' children.  J. Allergy 43(6):336-341. 

Camilli, A.E.; Burrows, B.; Knudson, R.J.; Lyle, S.K.; Lebowitz, M.D. (1987) Longitudinal changes in FEV1 in 

adults: effects of smoking and smoking cessation. Am. Rev. Respir. Dis. 135:794-799. 

Cano, J.P.; Catalin, J.; Badre, R.; Dumas, C.; Viala, A.; Guillerme, R. (1970) Determination de la nicotine par 

chromatographie en phase gazeuse. II. Applications. Ann. Pharm. Fr. 28:633-640. 

Castro, A.; Monji, N. (1986) Dietary nicotine and its significance in studies on tobacco smoking.  Biochem. Arch. 

2:91-97. 

CDC. See Centers for Disease Control. 

Cederlöf, R.; Friberg, L.; Hrubec, Z.; Lorich, U. (1975) The relationship of smoking and some social covariables in 

mortality and cancer morbidity: a ten-year followup on a probability sample of 55,000 Swedish subjects age 

18-69, parts 1 and 2. Stockholm, Sweden: Department of Environmental Hygiene, Karolinska Institute. 

Centers for Disease Control. (1989a) Chronic disease reports: mortality trends--United States, 1979-1986. MMWR 

38:189-191. 

Centers for Disease Control. (1989b) Years of potential life lost before age 65--United States, 1987. MMWR 

38:27-28. 

Centers for Disease Control. (1990) The Surgeon General's 1990 report on the health benefits of smoking cessation: 

executive summary. MMWR 39:viii-10. 

Centers for Disease Control. (1991a) Smoking-attributable mortality and years of potential life lost--United States, 

1988. MMWR 40:62-71. 

Centers for Disease Control. (1991b) Cigarette smoking among adults--United States, 1988. MMWR 40:757-765. 

Centers for Disease Control (CDC). (1992a) Smoking and health in the Americas: a 1992 report of the Surgeon 

General, in collaboration with the Pan American Health Organization.  Atlanta, GA: U.S. DHHS, Public 

Health Service, CDC.  DHHS Publication No. (CDC) 92-8419. 

Centers for Disease Control (CDC). (1992b) Cigarette smoking among adults--United States, 1990. MMWR 41:354-

355, 361-362. 

Chan, W.C.; Fung, S.C. (1982) Lung cancer in nonsmokers in Hong Kong. In: Grundmann, E., ed. Cancer campaign, 

v. 6, cancer epidemiology. Stuttgart, West Germany: Gustav Fischer Verlag, pp. 199-202. 

Chan, W.C.; Colbourne, M.J.; Fung, S.C.; Ho, H.C. (1979) Bronchial cancer in Hong Kong, 1976-1977. Br. J. Cancer 

39:182-192. 

Chan, K.N.; Elliman, A.; Bryan, E.; Silverman, M. (1989a) Respiratory symptoms in children of low birthweight. 

Arch. Dis. Child. 64:1294-1304. 

R-4 
Chan, K.M.; Noble-Jamieson, C.M.; Elliman, A.; Bryan, E.M.; Silverman, M. (1989b) Lung function in children of 

low birthweight. Arch. Dis. Child. 64:1284-1293. 

Chapman, R.S.; Mumford, J.L.; Harris, D.B.; Xingzhou, H.; Jiang, W.; Yang, R. (1988) The epidemiology of lung 

cancer in Xuan Wei, China: current progress, issues, and research strategies. Arch. Environ. Health 3:180-

183. 

Charlton, A. (1984) Children's coughs related to parental smoking. Br. Med. J. 288:1647-1649. 

Chen, Y. (1989) Synergistic effect of passive smoking and artificial feeding on hospitalization for respiratory illness 

in early childhood. Chest 95:1004-1007. 

Chen, Y.; Li, W. (1986) The effect of passive smoking on children's pulmonary function in Shanghai. Am. J. Public 

Health 76:515-518. 

Chen, Y.; Li, W.; Yu, S. (1986) Influence of passive smoking on admissions for respiratory illness in early childhood. 

Br. Med. J. 293:303-306. 

Chen, M.F.; Kimisuka, G.; Wang, N.S. (1987) Human fetal lung changes associated with maternal smoking during 

pregnancy. Pediatr. Pulmonol. 3:51-58. 

Chen, Y.; Li, W.; Yu, S.; Qian, W. (1988) Chang-Ning epidemiological study of children's health: I. Passive smoking 

and children's respiratory diseases. Int. J. Epidemiol. 17:348-355. 

Chilmonczyk, B.A.; Knight, G.J.; Palomaki, G.E.; Pulkkinen, A.J.; Williams, J.; Haddow, J.E. (1990) Environmental 

tobacco smoke exposure during infancy. Am. J. Public Health 80:1205-1208. 

China Map Press. (1979) Atlas of cancer mortality in the People's Republic of China. 

Chortyk, O.T.; Schlotzhauer, W.S. (1989) The contribution of low-tar cigarettes to environmental tobacco smoke.  J. 

Anal. Toxicol. 13:129-134. 

Clark, T.J.H.; Godfrey, S. (1983) Asthma. 2nd ed. Cambridge, MA: Chapman and Hall Medical. 

Claxton, L.D.; Morin, R.S.; Huges, T.J.; Lewtas, J. (1989) A genotoxic assessment of environmental tobacco smoke 

using bacterial bioassays. Mutat. Res. 222:81-99. 

Coghlin, J.; Hammond, S.K.; Gann, P. (1989) Development of epidemiologic tools for measuring environmental 

tobacco smoke exposure. Am. J. Epidemiol. 130:696-704. 

Cogswell, J.J.; Mitchel, E.B.; Alexander, J. (1987) Parental smoking, breast feeding, and respiratory infection in 

development of allergic diseases. Arch. Dis. Child. 62:336-344. 

Colley, J.R.T. (1971) Respiratory disease in childhood. Br. Med. Bull. 27:9-14. 

Colley, J.R.T. (1974) Respiratory symptoms in children and parental smoking and phlegm production. Br. Med. J. 

2:201-204. 

Colley, J.R.T.; Holland, W.W.; Corkhill, R.T. (1974) Influence of passive smoking and parental phlegm on 

pneumonia and bronchitis in early childhood. Lancet 2:1031-1034. 

Collier, A.M.; Goldstein, G.M.; Shrewsbury, R.P.; Zhang, C.A.; Williams, R.W. (1990) Urine cotinine elimination 

half-life in young children exposed to sidestream cigarette smoke. In: Indoor air '90: proceedings of the 5th 

R-5 
international conference on indoor air quality and climate, v. 2, Characteristics of indoor air; July-August. 

Ottawa, Ontario, Canada: Canada Mortgage and Housing Corporation, pp. 195-200. 

Collins, M.H.; Moessinger, A.C.; Kleinerman, J.; Bassi, J.; Rosso, P.; Collins, A.M.; James, L.S.; Blanc, W.A. (1985) 

Fetal lung hypoplasia associated with maternal smoking: a morphometric analysis. Pediatr. Res. 19:408-412. 

Comstock, G.W.; Meyer, M.B.; Helsing, K.J.; Tockman, M.S. (1981) The respiratory effects of household exposure to 

tobacco smoke and gas cooking. Am. Rev. Respir. Dis. 124:143-148. 

Corbo, G.M.; Fuciarelli, F.; Foresi, A.; De Benedetto, F. (1989) Snoring in children: association with respiratory 

symptoms and passive smoking. Br. Med. J. 299:1491-1494. 

Correa, P.; Fontham, E.; Pickle, L.; Lin, Y.; Haenszel, W. (1983) Passive smoking and lung cancer. Lancet 2:595-597. 

Correa, P.; Pickle, L.W.; Fontham, E.; Dalager, N.; Lin, Y.; Haenszel, W.; Johnson, W.D. (1984) The causes of lung 

cancer in Louisiana. In: Mizell, M.; Correa, P., eds. Lung cancer: causes and prevention. New York, NY: 

Verlag Chemie International, pp. 73-82. 

Coultas, D.B.; Howard, C.A.; Peake, G.T.; Skipper, B.J.; Samet, J.M. (1987) Salivary cotinine levels and involuntary 

tobacco smoke exposure in children and adults in New Mexico. Am. Rev. Respir. Dis. 136:305-309. 

Coultas, D.B.; Howard, C.A.; Peake, G.T.; Skipper, B.J.; Samet, J.M. (1988) Discrepancies between self-reported and 

validated cigarette smoking in a community survey of New Mexico Hispanics. Am. Rev. Respir. Dis. 

137:810-814. 

Coultas, D.B.; Peake, G.T.; Samet, J.M. (1989) Questionnaire assessment of lifetime and recent exposure to 

environmental tobacco smoke. Am. J. Epidemiol. 130:338-347. 

Coultas, D.B.; Samet, J.M.; McCarthy, J.F.; Spengler, J.D. (1990a) A personal monitoring study to assess workplace 

exposure to environmental tobacco smoke. Am. J. Public Health 80:988-990. 

Coultas, D.B.; Samet, J.M.; McCarthy, J.F.; Spengler, J.D. (1990b) Variability of measures of exposure to 

environmental tobacco smoke in the home. Am. Rev. Respir. Dis. 142:602-606. 

Cummings, K.M. (1990, December 4) Statement to the U.S. Environmental Protection Agency Science Advisory 

Board Indoor Air Quality and Total Human Exposure Committee. Environmental Tobacco Smoke Review, 

Arlington, VA. 

Cummings, K.M.; Markello, S.J.; Mahoney, M.C.; Marshall, J.R. (1989) Measurement of lifetime exposure to passive 

smoke. Am. J. Epidemiol. 130:122-132. 

Cummings, K.M.; Markello, S.J.; Mahoney, M.C.; Bhargava, A.K.; et al. (1990) Measurement of current exposure to 

environmental tobacco smoke. Arch. Environ. Health 45:74-79. 

Cutz, E.; Chan, W.; Track, N.S. (1981) Bombesin, calcitonin, and leuenkephalin immunoreactivity in endocrine cells 

of the human lung. Experientia (Basel) 37:765-767. 

Dagle, G.E.; McDonald, K.E.; Smith, L.G.; Stevens, D.L., Jr. (1978) Pulmonary carcinogenesis in rats given implants 

of cigarette smoke condensate in beeswax pellets. J. Natl. Cancer Inst. 61:905-910. 

Dalager, N.A.; Pickle, L.W.; Mason, T.J.; Correa, P.; Fontham, E.; Stemhagen, A.; Buffler, P.A.; Ziegler, R.G.; 

Fraumeni, J.F. (1986) The relation of passive smoking to lung cancer. Cancer Res. 46:4808-4811. 

R-6 
Davies, R.F.; Day, T.D. (1969) A study of the comparative carcinogenicity of cigarette and cigar smoke condensate 

on mouse skin. Br. J. Cancer 23:363-368. 

Davis, R.A.; Stiles, M.F.; DeBethizy, J.D.; Reynolds, J.H. (1991) Dietary nicotine: a source of urinary cotinine. Food 

Chem. Toxicol. 29(12):821-827. 

Day, N.E.; Brown, C.C. (1980) Multistage models and primary prevention of cancer. J. Natl. Cancer Inst. 64:977-989. 

Dean, G.; Lee, P.N.; Todd, G.F.; Wicken, A.J. (1977) Report on a second retrospective study in Northeast England. 

Part I: Factors related to mortality from lung cancer, bronchitis, heart disease, and stroke in Cleveland 

County, with particular emphasis on the relative risks associated with smoking filter and plain cigarettes. 

Research Paper 14. London: Tobacco Research Council. 

Deaner, R.M.; Trummer, M.J. (1970) Carcinoma of the lung in women. J. Thorac. Cardiovasc. Surg. 59:551-554. 

DeMarini, D.M. (1983) Genotoxicity of tobacco smoke and tobacco smoke condensate. Mutat. Res. 114:59-89. 

Dijkstra, L.; Houthuijs, D.; Brunekreef, B.; Akkerman, I.; Boleij, J.S.M. (1990) Respiratory health effects of the 

indoor environment in a population of Dutch children. Am. Rev. Respir. Dis. 142:1172-1178. 

Dodge, R. (1982) The effects of indoor pollution on Arizona children. Arch. Environ. Health 37:151-155. 

Doll, R. (1971) The age distribution of cancer. Implication for models of carcinogenesis. J.R. Stat. Soc. A. 134:133-

155. 

Doll, R.; Hill, A.B. (1964a) Mortality in relation to smoking: ten years' observations of British doctors. Br. Med. J. 

i:1399-1410. 

Doll, R.; Hill, A.B. (1964b) Mortality in relation to smoking: ten years' observations of British doctors. Br. Med. J. 

i:1460-1467. 

Doll, R.; Peto, R. (1976) Mortality in relation to smoking: 20 years' observations on male British doctors. Br. Med. J. 

ii:1525-1536. 

Doll, R.; Peto, R. (1978) Cigarette smoking and bronchial carcinoma: dose and time relationships among regular 

smokers and lifelong nonsmokers. J. Epidemiol. Community Health 32:303-313. 

Doll, R.; Hill, A.B.; Kreyberg, L. (1957) The significance of cell type in relation to the aetiology of lung cancer. Br. J. 

Cancer 11:43-48. 

Doll, R.; Gray, R.; Hafner, B.; Peto, R. (1980) Mortality in relation to smoking: 22 years' observations on female 

British doctors. Br. Med. J. i:967-971. 

Dontenwill, W.; Chevalier, H.J.; Harke, H.P.; Lafrenz, U.; Reckzeh, G.; Schneider, B. (1973) Investigations on the 

effects of chronic cigarette smoke inhalation in Syrian golden hamsters. J. Natl. Cancer Inst. 51:1781-1832. 

Dube, M.F.; Green, C.R. (1982) Methods of collection of smoke for analytical purposes. Recent Adv. Tobacco Sci. 

8:42-102. 

Duc, T.V.; Huynh, C.K. (1989) Sidestream tobacco smoke constituents in indoor air modelled in an experimental 

chamber--polycyclic aromatic hydrocarbons.  Environ. Int. 15:57-64. 

R-7 
Dupont, W.D.; Plummer, W.D. (1990) Power and sample size calculations: a review and computer program. In: 

Controlled clinical trials, v. 11. New York: Elsevier Science Publishing Co., pp. 116-128. 

Dutau, G.; Enjaume, C.; Petrus, M.; Darcos, P.; Demeurisse, P.; Rochiccioli, P. (1981) Enquete epidemiologue sur le 

tabagisme passif des enfants de 0 a 6 ans. Arch. Fr. Pediatr. 38:721-725. 

Eatough, D.J.; Benner, C.; Mooney, R.L.; Batholomew, D.; Steiner, D.S.; Hansen, L.D.; Lamb, J.D.; Lewis, E.A. 

(1986) Gas and particle phase nicotine in environmental tobacco smoke: proceedings of 79th annual meeting 

of the Air Pollution Control Association; June; Minneapolis, MN. Paper 86-685. 

Eatough, D.J.; Benner, C.L.; Bayona, J.M.; Caka, H.; Tang, H.; Lewis, L.; Lamb, J.D.; Lee, M.L.; Lewis, E.A.; 

Hansen, L.D. (1989a) Measurement of toxic and related air pollutants. Pittsburgh, PA: Air Pollution Control 

Association, pp. 132-139. 

Eatough, D.J.; Benner, C.L.; Tang, H.; Landon, V.; Richards, G.; Caka, F.M.; Crawford, F.; Lewis, E.A.; Hansen, 

L.D.; Eatough, N.L. (1989b) The chemical composition of environmental tobacco smoke. III. Identification 

of conservative tracers of environmental tobacco smoke. Environ. Int. 15:19-28. 

Eatough, D.J.; Caka, F.M.; Crawford, J.; Braithwaite, S.; Hansen, L.D.; Lewis, E.A. (1990) Environmental tobacco 

smoke in commercial aircraft. In: Indoor air '90: proceedings of the 5th international conference on indoor 

air quality and climate, v. 2, Characteristics of indoor air; July-August. Ottawa, Ontario, Canada: Canada 

Mortgage and Housing Corporation, pp. 311-316. 

Ehrlich, R.; Kattan, M.; Godbold, J.; Saltzberg, D.S.; Grimm, K.T.; Landrigan, P.J.; Lilienfeld, D.E. (1992) Childhood 

asthma and passive smoking. Urinary cotinine as a biomarker of exposure. Am. Rev. Respir. Dis. 145:594-

599. 

Ekwo, E.; Weinberger, W.M.; Lachenbruch, P.A.; Humtley, W.H. (1983) Relationship of parental smoking and gas 

cooking to respiratory disease in children. Chest 84:662-668. 

Elliot, L.P.; Rowe, D.R. (1975) Air quality during public gatherings. J. Air Pollut. Control Assoc. 25:635-636. 

Etzel, R.A.; Greenberg, R.A.; Haley, N.J.; Loda, F.A. (1985) Urinary cotinine excretion in neonates exposed to 

tobacco smoke products in utero. J. Pediatr. 107:146-148. 

Etzel, R.A.; Pattishall, E.N.; Haley, N.J.; Fletcher, R.M.; Henderson, F.W. (1992) Passive smoking and middle ear 

effusion among children in day care. Pediatrics 90:228-232. 

Eudy, L.W.; Thorne, F.A.; Heavor, D.L.; Green, C.R.; Ingebrethsen, B.J. (1985) Studies on the vapour-phase 

distribution of environmental nicotine by selected trapping and detection methods. Presented at: 39th 

Tobacco Chemists Research Conference; October; Montreal. 

Eudy, L.W.; Thomas, F.A.; Heavner, D.L.; Green, C.R.; Ingebrethsen, B.J. (1986) Studies on the vapor-particulate 

phase distribution of environmental nicotine by selective trapping and detection methods: proceedings of the 

Air Pollution Control Association 79th annual meeting; June; pp. 2-14. 

Evans, D.; Levison, J.; Feldman, C.H.; et al. (1987) The impact of passive smoking on emergency room visits of 

urban children with asthma. Am. Rev. Respir. Dis. 135:567-572. 

Evans, R.; Mullolly, D.I.; Wilson, R.W.; Gergen, P.J., Rosenberg, H.M.; Grauman, T.S.; Chevarley, F.M.; Feinleib, M. 

(1987) National trends in the morbidity and mortality of asthma in the U.S.: prevalence, hospitalization and 

death from asthma over two decades: 1965-1984. Chest 91, June 1987, supplement, pp. 65S-72S. 

R-8 
Federal Trade Commission. (1990) Tar, nicotine, and carbon monoxide of the smoke of 370 varieties of domestic 

cigarettes.  Federal Trade Commission, Washington, DC. 

Feinlein, M.  (1987) National trends in the morbidity and mortality of asthma in the U.S.  Chest 91(6):655-745. 

Fergusson, D.M.; Horwood L.J.; Shannon, F.T.; Taylor, B. (1981) Paternal smoking and lower respiratory illness in 

the first three years of life. J. Epidemiol. Community Health 35:180-184. 

Ferris, B.G.; Ware, J.H.; Berkey, C.S.; Dockery, D.W.; Spiro, A.; Speizer, F.E. (1985) Effects of passive smoking on 

health of children. Environ. Health Perspect. 62:289-295. 

Feyerabend, C.; Higenbottam, T.; Russell, M.A.H. (1982) Nicotinic concentrations in urine and saliva of smokers and 

nonsmokers. Br. Med. J. 284:1002-04. 

Fielding, J.E. (1985) Smoking: health effects and control (part I). N. Engl. J. Med. 313:491. 

Fiore, M.C.; Novotny, T.E.; Pierce, J.P.; Hatziandreu, E.J.; Patel, K.M.; Davis, R.M. (1989) Trends in cigarette 

smoking in the United States: the changing influence of gender and race. JAMA 261:49-55. 

First, M.W. (1984) Environmental tobacco smoke measurements: retrospect and prospect. Eur. J. Respir. Dis. 65 

(Suppl. 133):9-16. 

Fleming, D.W.; Cochi, S.L.; Hightower, A.W.; Broome, C.V. (1987) Childhood upper respiratory tract infections: to 

what degree is incidence affected by day-care attendance? Pediatrics 79:55-60. 

Floderus, B.; Cederlöf, R.; Friberg, L. (1988) Smoking and mortality: a 21-year followup based on the Swedish Twin 

Registry. Int. J. Epidemiol. 17(2):322. 

Fontham, E.T.H.; Correa, P.; Wu-Williams, A.; Reynolds, P.; Greenberg, R.S.; Buffler, P.A.; Chen, V.W.; Boyd, P.; 

Alterman, T.; Austin, D.F.; Liff, J.; Greenberg, S.D. (1991, November) Lung cancer in nonsmoking women: 

a multicenter case-control study. Cancer Epidemiol. Biomarkers Prev. 1(1):35-334. 

Fontham, E.T.H.; Correa, P.; Wu-Williams, A.; Reynolds, P.; Greenberg, R.S.; Buffler, P.A.; Chen, V.W.; Boyd, P.; 

Alterman, T.; Austin, D.F.; Liff, J.; Greenberg, S.D. (1992, May/June) Reply. Cancer Epidemiol. Biomarkers 

Prev. 1(1):333-334. 

Fraser, G.E.; Beeson, W.L.; Phillips, R.L. (1991) Diet and lung cancer in California Seventh Day Adventists. Am. J. 

Epidemiol. 133:683-693. 

Freedman, D.A.; Navidi, W. (1987a) On the multistage model for carcinogenesis. Tech. Report. No. 47, University of 

California. 

Freedman, D.A.; Navidi, W. (1987b) On the risk of lung cancer for ex-smokers. Tech. Report. No. 135, University of 

California. 

Friedman, G.D.; Petitti, D.B.; Bawol, R.D. (1983) Prevalence and correlates of passive smoking.  Am. J. Public Health 

73:401-406. 

Gaffney, M.; Altshuler, B. (1988) Examination of the role of cigarette smoke in lung carcinogenesis using multistage 

models. J. Natl. Cancer Inst. 80:925-931. 

Gairola, C. (1982) Genetic effects of fresh cigarette smoke in Saccharomyces cerevisiae. Mutat. Res. 102:123-136. 

R-9 
Gao, Y.; Blot, W.J.; Zheng, W.; Ershow, A.G.; Hsu, C.W.; Levin, L.I.; Zhang, R.; Fraumeni, J.F. (1987) Lung cancer 

among Chinese women. Int. J. Cancer 40:604-609. 

Garfinkel, L. (1981) Time trends in lung cancer mortality among nonsmokers and a note on passive smoking. J. Natl. 

Cancer Inst. 6:1061-1066. 

Garfinkel, L. (1984) Passive smoking and cancer: American experience. Prev. Med. 13:691-697. 

Garfinkel, L. (1985) Selection, followup, and analysis in the American Cancer Society prospective studies. Presented 

at a workshop on the selection, followup, and analysis in prospective studies held at the Waldorf-Astoria 

Hotel; October 1983; New York. 

Garfinkel, L.; Silverberg, E. (1991) Lung cancer and smoking trends in the United States over the past 25 years. Ca 

41:137-145. 

Garfinkel, L.; Stellman, S.D. (1988) Smoking and lung cancer in women: findings in a prospective study. Cancer Res. 

48:6951-6955. 

Garfinkel, L.; Auerbach, O.; Joubert, L. (1985) Involuntary smoking and lung cancer: a case-control study. J. Natl. 

Cancer Inst. 75:463-469. 

Geller-Bernstein, B.; Kenett, R.; Weisglass, L.; Tsur, S.; Lahav, M.; Levin, S. (1987) Atopic babies with wheezy 

bronchitis. Allergy 42:85-91. 

Geng, G.; Liang, Z.H.; Zhang, G.L. (1988) On the relationship between smoking and female lung cancer.  In: 

Smoking and health. Elsevier Science Publishers, pp. 483-486. 

Gerrard, J.W.; Helner, D.C.; Ko, C.G.; Mink, J.; Meyers, A.; Dosman, J.A. (1980) Immunoglobulin levels in smokers 

and nonsmokers. Ann. Allergy 44:261-262. 

Gillis, C.R.; Hole, D.J.; Hawthorne, V.M.; Boyle, P. (1984) The effect of environmental tobacco smoke in two urban 

communities in the west of Scotland. Eur. J. Respir. Dis. 133(Suppl.):121-126. 

Glantz, S.A.; Parmley, W.W. (1991) Passive smoking and heart disease. Circulation 83:1-12. 

Goldstein, G.M.; Collier, A.; Etzel, R.; Lewtas, J.; Haley, N. (1987) Elimination of urinary cotinine in children 

exposed to known levels of side-stream cigarette smoke. In: Seifert, H.; Esdorn, M.; Fischer, H.; Ruden, J.; 

Wegner, eds. Indoor air '87, v. 2. Berlin: Oraniendruck GmbH, pp. 61-67. 

Gortmaker, S.L.; Walker, D.K.; Jacobs, F.H.; Ruch-Ross, H. (1982) Parental smoking and the risk of childhood 

asthma. Am. J. Public Health 72:572-579. 

Graham, N.M.H.; Woodward, A.J.; Ryan, P.; Douglas, R.M. (1990) Acute respiratory illness in Adelaide children. II. 

The relationship of maternal stress, social supports, and family functioning. Int. J. Epidemiol. 19:937-944. 

Greenberg, R.A.; Haley, N.J.; Etzel, R.A.; Loda, F.A. (1984) Measuring the exposure of infants to tobacco smoke. N. 

Engl. J. Med. 310:1075-1078. 

Greenberg, R.A.; Bauman, K.E.; Glover, L.H.; Strechar, V.J.; Kleinbaum, D.G.; Haley, N.J.; Stedman, H.C.; Fowler, 

M.G.; Loda, F.A. (1989) Ecology of passive smoking by young infants. J. Pediatr. 114:774-780. 

Greenberg, R.A.; Bauman, K.E.; Strecher, V.J.; Keyes, L.L.; Glover, L.H.; Haley, N.J.; Stedman, H.C.; Loda, F.A. 

(1991) Passive smoking during the first year of life. Am. J. Public Health 81:850-853. 

R-10 
Greenland, S. (1987) Quantitative methods in the review of epidemiologic literature. Epidemiol. Rev. 9:1-30. 

Grimmer, G.; Brune, H.; Dettbarn, G.; Naujack, K.-W.; Mohr, U.; Wenzel-Hartung, R. (1988) Contribution of 

polycyclic aromatic compounds to the carcinogenicity of sidestream smoke of cigarettes evaluated by 

implantation into the lungs of rats. Cancer Lett. 43:173-177. 

Grimsrud, D.T.; Sherman, M.H.; Sonderegger, R.C. (1982) Calculating infiltration: implications for a construction 

quality standard.  In: Proceedings of the ASHRAE-DOE Conference on the Thermal Performance of the 

Exterior Envelope of Buildings II; December; Las Vegas, NV.  New York: ASHRAE, pp. 422-452. 

Grot, R.A.; Clark, R.E. (1979) Air leakage characteristics and weatherization techniques for low-income housing. In: 

Proceedings of the ASHRAE-DOE Conference on the Thermal Performance of the Exterior Envelope of 

Buildings; December; Orlando, FL. New York: ASHRAE, pp. 178-194. 

Guerin, M. (1987) Formation and physicochemical nature of sidestream smoke. In: O'Neill, I.K.; Brunnemann, K.D.; 

Dodet, B.; Hoffmann, D., eds. Environmental carcinogens--selected methods of analysis: v. 9, passive 

smoking. IARC Monographs No. 81. Lyon, France: International Agency for Research on Cancer. 

Guerin, M.R.; Jenkins, R.A.; Tomkins, B.A. (1992) The chemistry of environmental tobacco smoke: composition and 

measurement. Chelsea, MI: Lewis Publishers. 

Gwinn, J.V.; Martinez, F.D.; Wright, A.L.; Ray, C.G.; Taussig, L.M. (1991) Etiology and symptomatology of lower 

respiratory illnesses (LRIs) in the first three years of life. Am. Rev. Respir. Dis. 143:A509. 

Haddow, J.E.; Palomaki, G.E.; Knight, G.J. (1986) Use of serum cotinine to assess the accuracy of self-reported 

nonsmoking. Br. Med. J. 293:1306. 

Haddow, J.E.; Knight, G.J.; Palomaki, G.E.; Kloza, E.M.; Wald, N.J. (1987) Cigarette consumption and serum 

cotinine in relation to birthweight. Br. J. Obstet. Gynaecol. 94:678-681. 

Haddow, J.E.; Knight, G.J.; Palomaki, G.E.; et al. (1988) Second-trimester serum cotinine levels in nonsmokers in 

relation to birthweight. Am. J. Obstet. Gynecol. 159:481-484. 

Haenszel, W.; Taeuber, K.E. (1964) Lung-cancer mortality as related to residence and smoking histories. II. White 

females. J. Natl. Cancer Inst. 32:803-838. 

Haglund, B.; Cnattingius, S. (1990) Cigarette smoking as a risk factor for sudden infant death syndrome: a 

population-based study. Am. J. Public Health 80:29-32. 

Haley, N.J.; Colosimo, S.G.; Axelrad, C.M.; Harris, R.; Sepkovic, D.W. (1989) Biochemical validation of selfreported exposure to environmental tobacco smoke. Environ. Res. 49:127-135. 

Halonen, M.; Barbee, R.A.; Lebowitz, M.D.; Burrows, B. (1982) An epidemiologic study of the interrelationships of 

total serum immunoglobulin E, allergy skin-test reactivity, and eosinophilia. J. Allergy Clin. Immunol. 

69:221-228. 

Halonen, M.; Stern, D.; Lyle, S.; Wright, A.; Taussig, L.; Martinez, F.D. (1991) Relationship of total serum IgE levels 

in cord and 9-month sera of infants. Clin. Exp. Allergy 21:235-241. 

Hammond, E.C. (1966) Smoking in relation to the death rates of one million men and women. In: Haenszel, W., ed. 

Epidemiological approaches to the study of cancer and other chronic 

diseases. Washington, DC: National Cancer Institute Monograph No. 19, pp. 127-204. 

R-11 
Hammond, E.C.; Horn, D. (1958a) Smoking and death rates: report on forty-four months of followup of 187,783 

men. I. Total mortality. JAMA 166:1159-1172. 

Hammond, E.C.; Horn, D. (1958b) Smoking and death rates: report on forty-four months of followup of 187,783 

men. II. Death rates by cause. JAMA 166:1294-1308. 

Hammond, S.K.; Leaderer, B.P. (1987) A diffusion monitor to measure exposure to passive smoking. Environ. Sci. 

Technol. 21:494-497. 

Hammond, E.C.; Seidman, H. (1980) Smoking and cancer in the United States. Prev. Med. 9: 

169-173. 

Hammond, E.C.; Selikoff, I.J. (1981) Commentary: passive smoking and lung cancer with comments on two new 

papers. Environ. Res. 24:444-452. 

Hammond, S.K.; Leaderer, B.P.; Roche, A.C.; Schenker, M. (1987) Collection and analysis of nicotine as a marker for 

environmental tobacco smoke. Atmos. Environ. 21:457-462. 

Hammond, S.K.; Smith, T.J.; Woskie, S.R.; Leaderer, B.P.; Bettinger, N. (1988) Markers of exposure to diesel 

exhaust and cigarette smoke in railroad workers. Am. Ind. Hyg. Assoc. J. 49:516-522. 

Hammond, S.K.; Lewtas, J.; Mumford, J.; Henderson, J.; Henderson, F.W. (1989) Exposures to environmental 

tobacco smoke in homes. In: Measurement of toxic and related air pollutants. U.S. Environmental Protection 

Agency/Air and Waste Management Association international symposium. Pittsburgh, PA: Air and Waste 

Management Association, pp. 590-595. 

Hammond, S.K.; Gann, P.H.; Coughlin, J.; Tannenbaum, S.R.; Skipper, P.L. (1990) Tobacco smoke exposure and 

carcinogen-hemoglobin adducts. In: Indoor air '90: proceedings of the 5th international conference on indoor 

air quality and climate, v. 2, Characteristics of indoor air; July-August. Ottawa, Ontario, Canada: Canada 

Mortgage and Housing Corporation, pp. 157-161. 

Hanbury, W.J. (1964) Bronchogenic carcinoma in women. Thorax 19:338-342. 

Hanrahan, J.P.; Tager, I.B.; Segal, M.R.; et al. (1990) Effect of prenatal smoking on infant lung function. Am. Rev. 

Respir. Dis. 141:A282. 

Hanson, B.; McGue, M.; Roitman-Johnson, B.; Segal, N.L.; Bouchard, T.J.; Blumenthal, M.N. (1991) Atopic disease 

and immunoglobulin E in twins reared apart and together. Am. J. Hum. Genet. 48:873-879. 

Harmsden, H.; Effenberger, E. (1957) Tobacco smoke in public transportation, dwellings, and work rooms. Arch. 

Hyg. 141:383-400. 

Hasselblad, V.; Humble, C.G.; Graham, M.G.; Anderson, H. (1981) Indoor environmental determinants of lung 

function in children. Am. Rev. Respir. Dis. 123:479-485. 

Hawthorne, V.M.; Fry, J.S. (1978) Smoking and health: the association between smoking behaviour, total mortality, 

and cardiorespiratory disease in West Central Scotland. J. Epidemiol. Community Health 32:260-266. 

Hawthorne, A.R.; Gammage, D.; Dudney, C.S.; Hingerty, B.E.; Schuresko, D.D.; Parzyek, D.C.; Womak, D.R.; 

Morris, S.A.; Westeley, R.R.; White, D.A.; Schrimscher, J.M. (1984) Air indoor quality study of forty east 

Tennessee homes. ORNL 5965. Oak Ridge, TN: Oak Ridge National Laboratory, pp. 134. 

R-12 
He, X-Z.; Chen, W.; Liu, Z-Y.; Chapman, R.S. (1991) An epidemiological study of lung cancer in Xuan Wei County, 

China: current progress.  Case-control study on lung cancer and cooking fuel. Environ. Health Perspect. 

94:9-13. 

Henderson, F.W.; Reid, H.F.; Morris. R.; et al. (1989) Home air nicotine levels and urinary cotinine excretion in 

preschool children. Am. Rev. Respir. Dis. 140:197-201. 

Higgins, C.E.; Jenkins, R.A.; Guerin, M.R. (1987) Organic vapor phase composition of sidestream and environmental 

tobacco smoke from cigarettes. In: Proceedings of the U.S. Environmental Protection Agency/Air Pollution 

Control Association symposium on measurement of toxic and related air pollutants, Research Triangle Park, 

NC, pp. 140-151. 

Hill, A.B. (1953) Observation and experiment. N. Engl. J. Med. 248:995-1001. 

Hill, A.B. (1965) The environment and disease: association or causation? Proc. R. Soc. Med. 58:295-300. 

Hinds, W.C.; First, M.W. (1975) Concentrations of nicotine and tobacco smoke in public places. N. Engl. J. Med. 

292:844-845. 

Hinton, A.E. (1989) Surgery for otitis media with effusion in children and its relationship to parental smoking. J. 

Laryngol. Otol. 103:559-561. 

Hirayama, T. (1967) Smoking in relation to the death rates of 265,118 men and women in Japan. Tokyo: National 

Cancer Center Research Institute. 

Hirayama, T. (1975a) Smoking and cancer: a prospective study on cancer epidemiology based on a census population 

in Japan. In: Steinfeld, J.; Griffiths, W.; Ball, K.; et al., eds. Proceedings of the 3rd world conference on 

smoking and health, v. 2, Washington, DC: U.S. Department of Health, Education, and Welfare, pp. 65-72. 

Hirayama, T. (1975b) Prospective studies on cancer epidemiology based on a census population in Japan.  In: 

Bucalossi, P.; Veronesi, U.; Cascinelli, N., eds. Proceedings of the 11th international cancer congress; v. 3, 

Cancer epidemiology, environmental factors; 1974; Florence, Italy; Amsterdam: Exerpta Medica, pp. 26-35. 

Hirayama, T. (1977) Epidemiology of lung cancer based on population studies. In: National Cancer Center Library, 

ed. Collected papers from the National Cancer Center Research Institute, v. 12. Tokyo: National Cancer 

Center, pp. 452-461. 

Hirayama, T. (1978) Prospective studies on cancer epidemiology based on census population in Japan. In: Nieburgs, 

H.E., ed. Prevention and detection of cancer, v. 1, Etiology. New York: Marcel Dekker, pp. 1139-1147. 

Hirayama, T. (1981a) Nonsmoking wives of heavy smokers have a higher risk of lung cancer: a study from Japan. Br. 

Med. J. 282:183-185. 

Hirayama, T. (1981b) [Letter] Br. Med. J. 283:916-917. 

Hirayama, T. (1982) Smoking and cancer in Japan. A prospective study on cancer epidemiology based on census 

population in Japan. Results of 13 years followup. In: Tominaga, S.; Aoki, K., eds. The UICC smoking 

control workshop; August 1981; Nagoya, Japan. Nagoya: University of Nagoya Press, pp. 2-8. 

Hirayama, T. (1983a) Passive smoking and lung cancer. Presented at the 5th world conference on smoking and health, 

Winnipeg, Canada. 

Hirayama, T. (1983b) Passive smoking and lung cancer: consistency of association. Lancet 2:1425-1426. 

R-13 
Hirayama, T. (1984) Cancer mortality in nonsmoking women with smoking husbands based on a large-scale cohort 

study in Japan. Prev. Med. 13:680-690. 

Hirayama, T. (1985) A cohort study on cancer in Japan. In: Blot, W.J.; Hirayama, T.; Hoel, D.G., eds. Statistical 

methods in cancer epidemiology. Hiroshima: Radiation Effects Research Foundation, pp. 73-91. 

Hirayama, T. (1988) Duration of exposure as a determinant of lung cancer risk in passive smokers. Environ. Tech. 

Lett. 9:731-732. 

Hirayama, T. (1989) Dietary habits are of limited importance in influencing the lung cancer risk among Japanese 

females who never smoked. In: Bieva, D.J.; Courtois, Y.; Govaerts, M., eds. Present and future of indoor air 

quality. New York: Elsevier. 

Hirayama, T. (1990a) Passive smoking and cancer: the association between husbands' smoking and cancer in the 

lungs of nonsmoking wives. In: Kaskuga, H., ed. Indoor air quality. Berlin: Springer-Verlag. 

Hirayama, T. (1990b) Life-style and mortality; a large-scale census-based cohort study in Japan. In: Wahrendorf, J., 

ed. Contributions to epidemiology and biostatistics. Tokyo: Karger. 

Hoegg, U.R. (1972) Cigarette smoke in closed spaces. Environ. Health Perspect. 2:117-128. 

Hoffman, H.J.; Damus, K.; Hillman, L.; Krongrad, E. (1988) Risk factors for SIDS. Results of the National Institute 

of Child Health and Human Development SIDS Cooperative Epidemiological Study. Ann. N.Y. Acad. Sci. 

533:13-30. 

Hoffmann, D.; Hecht, S.S. (1989) Advances in tobacco carcinogenesis. In: Cooper, C.S.; Grover, P.L., eds. Chemical 

carcinogenesis and mutagenesis. New York: Springer-Verlag, pp. 64-102. 

Hoffmann, D.; Wynder, E.L. (1971) A study of tobacco carcinogenesis. XI. Tumor initiators, tumor accelerators, and 

tumor-promoting activity of condensate fractions. Cancer 27:848-864. 

Hoffmann, D.; Haley, N.J.; Adams, J.D.; Brunnemann, K.D. (1984) Tobacco sidestream smoke. Uptake by 

nonsmokers. Prev. Med. 13:608-617. 

Hoffmann, D.; Brunnemann, K.D.; Haley, N.J. (1989) Absorption of smoke constituents by nonsmokers.  In: 

Reducing workplace exposures to environmental tobacco smoke.  EPA/HHS Manual. 

Hole, D.J; Gillis, C.R.; Chopra, C.; Hawthorne, V.M. (1989) Passive smoking and cardiorespiratory health in a 

general population in the west of Scotland. Br. Med. J. 299:423-427. 

Hopp, R.J.; Bewtra, A.; Nair, N.M.; Townley, R.G. (1985) The effect of age on methacholine response. J. Allergy 

Clin. Immunol. 76:609-613. 

Hopp, R.J.; Townley, R.G.; Biven, R.E.; Bewtra, A.K.; Nair, N.M. (1990) The presence of airway reactivity before the 

development of asthma. Am. Rev. Respir. Dis. 141:2-8. 

Hoppenbrouwers, T.; Ceeb, M.; Arakawa, K.; Hodgman, J.E. (1981) Seasonal relationship of sudden infant death 

syndrome and environmental pollutants. Am. J. Epidemiol. 113:623-635. 

Horwood, L.J.; Fergusson, D.M.; Shannon, F.T. (1985) Social and familial factors in the development of early 

chilhood asthma. Pediatrics 75:859-868. 

Hulka, B.S.; Wilcosky, T.C.; Griffith, J., eds. (1990) Biological markers in epidemiology.  New York: Oxford Press. 

R-14 
Humble, C.G.; Samat, J.M.; Pathak, D.R.; Skipper, B.J. (1985) Cigarette smoking and lung cancer in "Hispanic" 

whites and other whites in New Mexico. Am. J. Public Health 75:145-148. 

Humble, C.G.; Samet, J.M.; Pathak, D.R. (1987) Marriage to a smoker and lung cancer risk. Am. J. Public Health 

77:598-602. 

Husgafvel-Pursiainen, K.; Sorsa, M.; Moller, M.; Benestad, C. (1986) Genotoxicity and polynuclear aromatic 

hydrocarbon analysis of environmental tobacco smoke samples from restaurants. Mutagenesis 1:287-291. 

IARC. See International Agency for Research on Cancer. 

Idle, J.R. (1990) Titrating exposure to tobacco smoke using cotinine--a minefield of misunderstandings. J. Clin. 

Epidemiol. 43:313-317. 

Ingebrethsen, B.J.; Sears, S.B. (1985) Particle size distribution measurements of sidestream cigarette smoke. Presented 

at: 39th Tobacco Chemists' Research Conference; Montreal, Quebec, Canada. 

Inoue, R.; Hirayama, T. (1988) Passive smoking and lung cancer in women. In: Smoking and health. Elsevier Science 

Publishers, pp. 283-285. 

International Agency for Research on Cancer. (1986) IARC monographs on the evaluation of the carcinogenic risk of 

chemicals to man. v. 38, Tobacco smoking. Lyon, France: World Health Organization. 

International Agency for Research on Cancer. (1987a) Environmental carcinogens--methods of analysis and exposure 

measurement: v. 9, Passive smoking. O'Neill, I.K.; Brunnemann, K.D.; Dodet, B.; Hoffmann, D. eds., Lyon, 

France: IARC Sci. Publ. No. 81. 

International Agency for Research on Cancer. (1987b) Cancer incidence in five continents: v. 5, Muir, C.; 

Waterhouse, J.; Mack, T.; Powell, J.; Whelan, S., eds. Lyon, France: IARC Sci. Pub. No. 88. 

Ishizu, Y. (1980) General equation or the estimation of indoor pollution. Environ. Sci. Technol. 14:1254-1257. 

Iversen, M.; Birch, L.; Lundqvist, G.R.; Elbrond, O. (1985) Middle ear effusion and the indoor environment. Arch. 

Environ. Health 40:74-79. 

Janerich, D.T.; Thompson, W.D.; Varela, L.R.; et al. (1990) Lung cancer and exposure to tobacco smoke in the 

household. N. Engl. J. Med. 323:632-636. 

Jarvis, M.J. (1987) Uptake of environmental tobacco smoke. IARC Sci. Publ. 81:43-58. 

Jarvis, M.J. (1989) Application of biochemical intake markers to passive smoking measurement and risk estimation. 

Mutat. Res. 222:101-110. 

Jarvis, M.J.; Russell, M.H. (1985) Passive exposure to tobacco smoke. Br. Med. J. 291:1646. 

Jarvis, M.J.; Russell, M.H.; Feyerabend, C. (1983) Absorption of nicotine and carbon dioxide from passive smoking 

under natural conditions of exposure. Thorax 38:829-833. 

Jarvis, M.; Tunstall-Pedoe, H.; Feyerabend, C.; Vesey, C.; Kabat, G.C.; Wynder, E.L. (1984) Lung cancer in 

nonsmokers. Cancer 53:1214-1221. 

R-15 
Jarvis, M.J.; Russell, M.A.H.; Feyerabend, C.; Eiser, J.R.; Morgan, M.; Gammage, P.; Gray, E.M. (1985) Passive 

exposure to tobacco smoke: saliva cotinine concentrations in a representative sample of nonsmoking 

children. Br. Med. J. 291:927-929. 

Joly, O.G.; Lubin, J.H.; Caraballoso, M. (1983) Dark tobacco and lung cancer in Cuba. J. Natl. Cancer Inst. 70:1033-

1039. 

Kabat, G.C. (1990) Epidemiologic studies of the relationship between passive smoking and lung cancer. Presented at 

the 1990 annual winter meeting of the Toxicology Forum in Washington, DC. 

Kabat, G.C.; Wynder, E.L. (1984) Lung cancer in nonsmokers. Cancer 53:1214-1221. 

Kahn, H.A. (1966) The Dorn study of smoking and mortality among U.S. veterans: report on eight and one-half years 

of observation. In: Haenszel, W., ed. Epidemiological approaches to the study of cancer and other chronic 

diseases. Washington, DC: National Cancer Institute Monograph No. 19, pp. 1-125. 

Kalandidi, A.; Trichopoulos, D.; Hatzakis, A.; Tzannes, S.; Saracci, R. (1987) Passive smoking and chronic 

obstructive lung disease. Lancet ii:1325-1326. 

Kalandidi, A.; Katsouyanni, K.; Voropoulou, N.; et al. (1990) Passive smoking and diet in the etiology of lung cancer 

among nonsmokers. Cancer Causes Control 1:15-21. 

Kaplan, H.S.; Tsuchitani, P.J., eds. (1978) Cancer in China. New York: Alan R. Liss, Inc. 

Kasuga, H.; Hasebe, A.; Osaka, F.; Matuski, H. (1979) Respiratory symptoms in school children and the role of 

passive smoking. Tokai J. Exp. Clin. Med. 4:101-104. 

Katada, H.; Mikami, R.; Konishi, M.; Koyama, Y.; Narita, N. (1988) Effect of passive smoking in lung cancer 

development in women in the Nara region. Gan No Rinsho 34(1):21-27. 

Katsouyanni, K.; Kogevinas, M.; Dontas, N.; Maisonneuve, P.; Boyle, P.; Trichopoulos, D. (1990) Mortality from 

malignant neoplasms in Greece 1960-1985. Greek Cancer Society, Athens, pp. 1-125 [in Greek]. 

Katz, D.; Baptista, J.; Azen, S.P.; Pike, M.C. Obtaining confidence intervals for the risk ratio in cohort studies. 

Biometrics 78:469-474. 

Kauffmann, F.; Tessier, J.F.; Oriol, P. (1983) Adult passive smoking in the home environment: a risk factor for 

chronic airflow limitation. Am. J. Epidemiol. 117:269-280. 

Kauffmann, F.; Neukirch, F.; Orobaeff, M.; Marne, M.J.; Claud, J.R.; Lellouch, J. (1986) Eosinophils, smoking, and 

lung function: an epidemiologic survey among 912 working men. Am. Rev. Respir. Dis. 134:1172-1175. 

Kauffmann, F.; Dockery, D.W.; Speizer, F.E.; Ferris, B.G. (1989a) Respiratory symptoms and lung function in 

relation to passive smoking: a comparative study of American and French Women. Int. J. Epidemiol. 

18:334-344. 

Kauffmann, F.; Tager, I.B.; Munoz, A.; Speizer, F.E. (1989b) Familial factors related to lung function in children aged 

6-10 years: results from the PAARC epidemiologic study. Am. J. Epidemiol. 129:1289-1299. 

Kentner, M.; Triebig, G.; Weltle, D. (1984) The influence of passive smoking on pulmonary function: a study of 1351 

office workers. Prev. Med. 13:656-69. 

R-16 
Kleinbaum, D.G.; Kupper, L.L.; Morgenstern, H. (1982) Epidemiologic research. Belmont, CA: Lifetime Learning 

Publications. 

Knoth, A.; Bohn, H.; Schmidt, F. (1983) Passive smoking as a causal factor of bronchial carcinoma in female 

nonsmokers. Med. Klin. 78:66-69. 

Koo, L.C. (1988) Dietary habits and lung cancer risk among Chinese females in Hong Kong who never smoked. Nutr. 

Cancer 11:155-172. 

Koo, L.C. (1989) Environmental tobacco smoke and lung cancer: is it the smoke or the diet? In: Bieva, C.J.; Courtois, 

Y.; Govaerts, M., eds. Present and future of indoor air quality. Excerpta Medica. Amsterdam: Elsevier 

Science Publishers, pp. 65-75. 

Koo, L.C.; Ho, J.H-C.; Saw, D. (1983) Active and passive smoking among female lung cancer patients in Hong Kong. 

J. Exp. Clin. Cancer Res. 4:367-375. 

Koo, L.C.; Ho, J.H-C.; Saw, D. (1984) Is passive smoking an added risk factor for lung cancer in Chinese women?  J. 

Exp. Clin. Cancer Res. 3:277-283. 

Koo, L.C.; Ho, J.H-C.; Lee, N. (1985) An analysis of some risk factors for lung cancer in Hong Kong. Int. J. Cancer 

35:149-155. 

Koo, L.C., Ho, J.H.; Saw, D.; Ho, C.Y. (1987) Measurements of passive smoking and estimates of lung cancer risk 

among nonsmoking Chinese females. Int. J. Cancer 39:162-169. 

Koo, L.C.; Ho, J. H-C.; Rylander, R. (1988) Life-history correlates of environmental tobacco smoke: a study on 

nonsmoking Hong Kong Chinese wives with smoking versus nonsmoking husbands. Soc. Sci. Med. 

26(7):751-760. 

Koutrakis, P.; Fasano, A.M.; Slater, J.L.; Spengler, J.D.; McCarthy, J.F.; Leaderer, B.P. (1989) Atmos. Environ. 

23:2767-2773. 

Koutrakis, P.; Briggs, S.L.K.; Leaderer, B.P. (1992) Source apportionment of indoor aerosols in Suffolk and 

Onandaga Counties, New York. Environ. Sci. Technol. 26:521-527. 

Kraemer, M.J.; Richardson, M.A.; Weiss, N.S.; et al. (1983) Risk factors for persistent middle ear effusions: otitis 

media, catarrh, cigarette smoke exposure, and atopy. JAMA 249:1022-1025. 

Krall, E.A.; Valadian, I.; Dwyer, J.T.; Gardner, J. (1989) Accuracy of recalled smoking data. Am. J. Public Health 

79:200. 

Krzyzanowski, M.; Quackenboss, J.J.; Lebowitz, M.D. (1990) Chronic respiratory effects of indoor formaldehyde 

exposure. Environ. Res. 52:117-125. 

Kuller, L.H.; Garfinkel, L.; Correa, P.; Haley, N.; Hoffmann, D.; Preston-Martin, S.; Sandler, D. (1986) Contribution 

of passive smoking to respiratory cancer.  Environ. Health Perspect.  70:57-69. 

Kurihara, M.; Aoki, K.; Miller, R.W.; Muir, C.S., eds. (1989) Changing cancer patterns and topics in cancer 

epidemiology. New York: Plenum Press. 

Lam, W.K. (1985) A clinical and epidemiological study of carcinoma of lung in Hong Kong [doctoral thesis]. Hong 

Kong: University of Hong Kong. 

R-17 
Lam, T.H.; Kung, I.T.M.; Wong, C.M.; Lam, W.K.; Kleevens, J.W.L.; Saw, D.; Hsu, C.; Seneviratne, S.; Lam, S.Y.; 

Lo, K.K.; Chan, W.C. (1987) Smoking, passive smoking, and histological types in lung cancer in Hong 

Kong Chinese women. Br. J. Cancer 6:673-678. 

Layard, M.W.; Viren, J.R. (1989) Assessing the validity of a Japanese cohort study. Elsevier Science Publishers B.V. 

(Biomedical Division). 

Leaderer, B.P. (1988) Measuring exposure to environmental tobacco smoke. Report prepared for the U. S. 

Environmental Protection Agency. 

Leaderer, B.P. (1989) Unpublished data. 

Leaderer, B. (1990) Assessing exposure to environmental tobacco smoke.  Risk Anal. 10(1):19-26. 

Leaderer, B.P.; Cain, W.S.; Isseroff, R.; Berglund, L.G. (1984) Ventilation requirements in buildings II. Particulate 

matter and carbon monoxide from cigarette smoking. Atmos. Environ. 18:99-106. 

Leaderer, B.P.; Koutrakis, P.; Briggs, S.; Rizzuto, J. (1990) Contribution of indoor sources to residential aerosol 

concentrations. In: Indoor air '90: proceedings of the 5th international conference on indoor air quality and 

climate, v. 2, Characteristics of indoor air; July-August. Ottawa, Ontario, Canada: Canada Mortgage and 

Housing Corporation, pp. 269-274. 

Leaderer, B.P.; Lioy, P.J.; Spengler, J.D. (1992) Assessing exposures to inhaled complex mixtures.  Environ. Health 

Perspect. (in press) 

Lebowitz, M.D. (1984) The effects of environmental tobacco smoke exposure and gas stoves on daily peak flow rates 

in asthmatic and nonasthmatic families. Eur. J. Respir. Dig. 133:190-195. 

Lebowitz, M.D.; Burrows, B. (1976) Respiratory symptoms related to smoking habits of family adults. Chest 

69:49-50. 

Lebowitz, M.D.; Holberg, C.J. (1988) Effects of parental smoking and other risk factors on the development of 

pulmonary function in children and adolescents. Analysis of two longitudinal population studies. Am. J. 

Epidemiol. 128:589-597. 

Lebowitz, M.D.; Holberg, C.J.; Knudson, R.J.; Burrows, B. (1987) Longitudinal study of pulmonary function 

development in childhood, adolescence, and early adulthood. Am. Rev. Respir. Dis. 136:69-75. 

Lebowitz, M.D.; Quackenboss, J.J. (1990) The effect of environmental tobacco smoke on pulmonary function. Int. 

Arch. Occup. Environ. Health (Suppl):147-152. 

Lebowitz, M.D.; Quackenboss, J.J.; Soczek, M.L.; Kollander, M.; Colome, S. (1989) The new standard environmental 

inventory questionnaire for estimation of indoor concentrations.  J. Air Pollut. Control Assoc. 39:1411-1419. 

Lebret, E.; Boley, J.; Brumekreef, B. (1990) Environmental tobacco smoke in Dutch homes. In: Indoor air '90: 

proceedings of the 5th international conference on indoor air quality and climate, v. 2, Characteristics of 

indoor air, July-August. Ottawa, Ontario, Canada: Canada Mortgage and Housing Corporation, pp. 263-268. 

Lee, P.N. (1986) Does breathing other people's tobacco smoke cause lung cancer? [Letter] Br. Med. J. 293:1503-

1504. 

Lee, P.N. (1987a) Lung cancer and passive smoking: association an artifact due to misclassification of smoking 

habits. Toxicol. Lett. 35:157-162. 

R-18 
Lee, P.N. (1987b) Passive smoking and lung cancer association: a result of bias?  Hum. Toxicol. 6:517-524. 

Lee, P.N. (1988) Misclassification of smoking habits and passive smoking. Berlin: Springer. 

Lee, P.N.  (1989)  Passive smoking and lung cancer: fact or fiction. In: Bieva, C.J.; Courtois, Y.; Govaerts, M., eds. 

Present and future of indoor air quality. Excerpta Medica. Amsterdam: Elsevier Science Publishers, pp. 119-

128. 

Lee, P.N. (1990) A detailed review of epidemiological evidence relating environmental tobacco smoke (ETS) to the 

risk of cancer, heart disease, and other causes of death in adults who have never smoked. Draft 3 of Annex 

A. 

Lee, P.N. (1991a) Correcting meta-analyses of the association of lung cancer in females with spouse (or household) 

exposure for bias due to misclassification of active smoking status.  Report submitted to U.S. EPA, dated 

November 29, 1991. 

Lee, P.N. (1991b) An estimate of adult mortality in the United States from passive smoking.  Environ. Int. 17:379-

381. 

Lee, P.N.; Chamberlain, J.; Alderson, M.R. (1986) Relationship of passive smoking to risk of lung cancer and other 

smoking-associated diseases. Br. J. Cancer 54:97-105. 

Lee, B.L.; Benowitz, N.L.; Jacob P. (1987) Influence on tobacco abstinence on the disposition kinetics and effects of 

nicotine. Clin. Pharmacol. Ther. 41:474-479. 

Leeder, S.R.; Corkhill, R.T.; Irwig, L.M.; Holland, W.W.; Colley, J.R. (1976) Influence of family factors on the 

incidence of lower respiratory illness during the first year of life. Br. J. Prev. Soc. Med. 30:203-212. 

Lehnert, G. (1984) Roundtable discussion from symposium on medical perspectives on passive smoking. Prev. Med. 

13:732-733. 

Lewak, N.; van den Berg, B.J.; Beckwith, J.B. (1979) Sudden infant death syndrome risk factors. Clin. Pediatr. (Phila) 

18:404-411. 

Lewis, H.M.; Haeney, M.; Jeacock, J.; Thomas, H. (1989) Chronic cough in a hospital population: its relationship to 

atopy and defect in host defence. Arch. Dis. Child. 64:1593-1598. 

Lewtas, J.; Claxton, L.; Mumford, J.L. (1987) Human exposure to mutagens from indoor combustion sources. In: 

Seifert, B.; Esdorn, M.; Fischer, M.; Ruden, H.; Wegner, J., eds. Indoor air '87, v. 1. Berlin: Oraniendruck 

GmbH, pp. 473-477. 

Liang, Z-H; Geng, G.; et al. Effects of smoking and passive smoking on female lung cancer in Tianjin area. Tianjin, 

People's Republic of China: Dept. of Epidemiology, Tianjin Medical College. 

Ling, P.I.; Lofroth, G.; Lewtas, J. (1987) Mutagenic determination of passive smoking. Toxicol. Lett. 35:147-151. 

Liu, Z.; He, X.; Chapman, R.S. (1991) Smoking and other risk factors for lung cancer in Xuanwei, China. Int. J. 

Epidemiol. 20:26-31. 

Löfroth, G.; Zebühr, Y. (1992) Polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs) in 

mainstream and sidestream cigarette smoke.  Bull. Environ. Contam. Toxicol. 48:789-794. 

R-19 
Löfroth, G.; Nilsson, L.; Alfeim, I. (1983) Passive smoking and urban air pollution: Salmonella/microsome 

mutagenicity assay of simultaneously collected indoor and outdoor particulate matter. In: Waters, M.D.; 

Sandhu, S.S.; Lewtas, J.; Claxton, L.; Chernoff, N.; Nesnow, S., eds. Short-term bioassays in the analysis of 

complex environmental mixtures, v. 3. New York: Plenum, pp. 515-525. 

Löfroth, G.; Ling, P.I.; Agurell, E. (1988) Public exposure to environmental tobacco smoke. Mutat. Res. 202:103-110. 

Löfroth, G.; Burtin, R.; Forehand, L.; Hammond, K.; Selia, R.; Zwiedinger, E.; Lewtas, J. (1989) 

Characterization of genotoxic components of environmental tobacco smoke. Environ. Sci. Technol. 23:610-

614. 

Lossing, E.H.; Best, E.W.R.; McGregor, J.T.; Josie, G.H.; Walker, C.B.; Delaquis, F.M.; Baker, P.M.; McKenzie, A.C. 

(1966) A Canadian study of smoking and health. Ottawa, Canada: Department of National Health and 

Welfare. 

Lubin, J.H.; Blot, W.J.; Berrino, F.; Flamant, R.; Gillis, C.R.; Kunze, M.; Schmahl, D.; Visco, G. (1984) Modifying 

risk of developing lung cancer by changing habits of cigarette smoking. Br. Med. J. 288:1953-1956. 

MacDonald, E.J. (1981) [Letter] Br. Med. J. 283:915-916. 

Machlin, S.R.; Kleinman, J.C.; Madans, J.H. (1989) Validity of mortality analysis based on retrospective smoking 

information. Stat. Med. 8:997-1009. 

Maclure, M.; Katz, R.B.-A.; Bryant, M.S.; Skipper, P.L.; Tannenbaum, S.R. (1989) Elevated blood levels of 

carcinogens in passive smokers. Am. J. Public Health 79:1381-1384. 

Magnusson, C.G.M. (1986) Maternal smoking influences cord serum IgE and IgD levels and increases the risk for 

subsequent infant allergy. J. Allergy Clin. Immunol. 78:898-904. 

Makin, J.; Fried, P.A.; Watkinson, B. (1991) A comparison of active and passive smoking during pregnancy: longterm effects. Neurotoxicol. Teratol. 13:5-12. 

Malloy, M.H.; Kleinman, J.C.; Land, G.H.; Schramm, W.F. (1988) The association of maternal smoking with age and 

cause of infant death. Am. J. Epidemiol. 128:46-55. 

Mantel, N. (1963) Chi-square tests with one degree of freedom: extensions of the Mantel-Haenszel procedure. J. Am. 

Stat. Assoc. 58:690-700. 

Mantel, N.; Haenszel, W. (1959) Statistical aspects of the analysis of data from retrospective studies of disease. J. Natl. 

Cancer Inst. 22:719-748. 

Maran, A.G.D.; Wilson, J.A. (1986) Glue ear and speech development. Br. Med. J. 293:713-714. 

Marbury, M.C.; Hammond, S.K.; Haley, N.J. (1990) Assessing exposure to environmental tobacco smoke in 

epidemiological studies of acute health effects. In: Indoor air '90: proceedings of the 5th international 

conference on indoor air quality and climate, v. 2, Characteristics of indoor air; July-August. Ottawa, 

Ontario, Canada: Canada Mortgage and Housing Corporation, pp. 189-194. 

Marchand, L.L.; Wilkens, L.R.; Hankin, J.H.; Haley, N.J. (1991) Dietary patterns of female nonsmokers with and 

without exposure to environmental tobacco smoke. Cancer Causes Control 2:11-16. 

Martin, T.R.; Bracken, M.B. (1986) Association of low birthweight with passive smoke exposure in pregnancy. Am. 

J. Epidemiol. 124:633-642. 

R-20 
Martinez, F.D.; Morgan, W.J.; Wright, A.L.; Holberg, C.J.; Taussig, L.M. (1988a) Diminished lung function as a 

predisposing factor for wheezing lower respiratory tract illness in infants. N. Engl. J. Med. 319:1112-1117. 

Martinez, F.D.; Antognoni, G.; Macri, F.; Bonci, E.; Midulla, F.; De Castro, G.; Ronchetti, R. (1988b) Parental 

smoking enhances bronchial responsiveness in nine-year-old children. Am. Rev. Respir. Dis. 138:518-523. 

Martinez, F.D.; Morgan, W.J.; Wright, A.L.; Holberg, C.; Taussig L.M. (1991) Initial airway function is a risk factor 

for recurrent wheezing respiratory illnesses during the first three years of life. Am. Rev. Respir. Dis. 

143:312-316. 

Martinez, F.D.; Cline, M.; Burrows, B. (1992) Increased incidence of asthma in children of smoking mothers. 

Pediatrics 89:21-26. 

Masi, M.A.; Hanley, J.A.; Ernst, P.; Becklake, M.R. (1988) Environmental exposure to tobacco smoke and lung 

function in young adults. Am. Rev. Respir. Dis. 138:296-299. 

Mattson, M.E.; Boyd, G.; Byar, D.; Brown, C.; Callahan, J.F.; Cullen, J.W.; Grenblatt, J.; Haley; Hammond, N.; J.F.; 

Lewtas, J.; Reeves, W. (1989) Passive smoking on commercial airline flights. JAMA 261:867-872. 

McConnochie, K.M.; Roghmann, K.J. (1986a) Parental smoking, presence of older sibling, and family history of 

asthma increase risk of bronchiolitis. Am. J. Dis. Child. 140:806-812. 

McConnochie, K.M.; Roghmann, K.J. (1986b) Breast feeding and maternal smoking as predictors of wheezing in 

children age 6 to 10 years. Pediatr. Pulmonol. 2:260-268. 

McRae, D.D. (1990) The physical and chemical nature of tobacco smoke. In: Recent advances in tobacco science, v. 

16: Symposium of the formation and evolution of cigarette smoke.  44th Tobacco Chemists Research, 

Winston-Salem, NC, pp. 233-323. 

Mertsola, J.; Ruuskanen, O.; Vanto, T.; Koivikko, A.; Halonen, P. (1991) Recurrent wheezy bronchitis and viral 

respiratory infections. Arch. Dis. Child. 66:124-129. 

Meyers, D.A.; Beaty, T.H.; Freidhoff, L.R.; Marsh, D.G. (1987) Inheritance of total serum IgE (basal level) in man. 

Am. J. Hum. Genet. 41:51-62. 

Miesner, E.A.; Rudnick, S.N.; Hu, F.; Spengler, J.D.; Preller, L.; Ozkaynak, H.; Nelson, W. (1989) Particule and 

nicotine sampling in public facilities and offices. J. Air Pollut. Control Assoc. 39:1577-1582. 

Miller, G.H. (1984) Cancer, passive smoking, and nonemployed and employed wives. West. J. Med. 140(4):632-635. 

Mitchell, E.A.; Scragg, R.; Stewart, A.W.; et al. (1991) Results from the first year of the New Zealand cot death study. 

N.Z. Med. J. 104:71-6. 

Moolgavkar, S.H.; Dewanji, A.; Luebeck, G. (1989) Cigarette smoking and lung cancer: reanalysis of the British 

doctors' data. J. Am. Cancer Inst. 81(6):415-420. 

Moschandreas, D.J. (1981) Exposure to pollutants and daily time budgets of people. Bull. N.Y. Acad. Med. 57:845-

859. 

Mumford, J.L.; He, X.Z.; Chapman, R.S.; et al. (1987) Lung cancer and indoor air pollution in Xuanwei, China. 

Science 235:217-220. 

R-21 
Mumford, J.L.; Lewtas, J.; Burton, R.M.; Henderson, F.W.; Forehand, L.; Allison, J.C.; Hammond, S.K. (1989) 

Assessing environmental tobacco smoke exposure of preschool children in homes by monitoring air 

particles, mutagenicity, and nicotine. In: Measurement of toxic and related air pollutants. U.S. Environmental 

Protection Agency/Air and Waste Management Association international symposium. Pittsburgh, PA: Air 

and Waste Management Association, pp. 606-610. 

Muramatsu, M.; Umemura, S.; Okada, T.; Tomita, H. (1984) Estimation of personal exposure to tobacco smoke with a 

newly developed nicotine personal monitor. Environ. Res. 35:218-227. 

Murray, A.B.; Morrison, B.J. (1986) The effect of cigarette smoke from the mother on bronchial responsiveness and 

severity of symptoms in children with asthma. J. Allergy Clin. Immunol. 77:575-581. 

Murray, A.B.; Morrison, B.J. (1988) Passive smoking and the seasonal difference of severity of asthma in children. 

Chest 94:701-708. 

Murray, A.B.; Morrison, B.J. (1989) Passive smoking by asthmatics: its greater effect on boys than on girls and on 

older than on younger children. Pediatrics 84:451-459. 

Naeye, R.L.; Ladis, B.; Drage, J.S. (1976) Sudden infant death syndrome: a prospective study. Am. J. Dis. Child. 

130:1207-1210. 

Nagda, N.; Fortmann, R.; Koontz, M.; Konheim, A. (1990) Investigation of cabin air-quality aboard commercial 

airlines. In: Indoor air '90: proceedings of the 5th international conference on indoor air quality and climate, 

v. 2, Characteristics of indoor air. July-August. Ottawa, Ontario, Canada: Canada Mortgage and Housing 

Corporation, pp. 245-250. 

National Institute for Occupational Safety and Health (NIOSH). (1991) Environmental tobacco smoke in the 

workplace: lung cancer and other health effects. Current Intelligence Bulletin 54. U.S. Department of Health 

and Human Services, NIOSH, Cincinnati, OH. 

National Research Council, Committee on Indoor Pollutants. (1981) Tobacco smoke. In: Indoor pollutants. 

Washington, DC: National Academy Press, pp. 149-168. 

National Research Council. (1986) Environmental tobacco smoke: measuring exposures and assessing health effects. 

Washington, DC: National Academy Press. 

National Research Council and Committee on Biological Markers. (1987) Biological markers in environmental health 

research.  Environ. Health Perspect. 64:3-9. 

Neal, A.D.; Wadden, R.A.; Rosenberg, S. (1978) Evaluation of indoor particulate concentrations for an urban 

hospital. Am. Ind. Hyg. Assoc. J. 29:578-582. 

Neddenriep, D.; Martinez, F.D.; Morgan, W.J. (1990) Increased specific lung compliance in newborns whose mothers 

smoked during pregnancy. Am. Rev. Respir. Dis. 141:A282. 

Nelson, P.A.; Quant, F.R.; Sem, G.F. (1982) Experimental measurements of aerosol concentrations in offices. 

Environ. Int. 8:223-227. 

Neurath, G.B.; Dunger, M.; Krenz, O.; Orth, D.; Pein, F.G. (1988) Trans-3'-hydroxycotinine--a main metabolite in 

smokers. Klin. Wochenschr. 66(Suppl. 11):2-4. 

Neuspiel, D.R.; Rush, D.; Butler, N.; Golding, J.; Bijur, P.E.; Kurzon, M. (1989) Parental smoking and post-infancy 

wheezing in children: a prospective cohort study. Am. J. Public Health 79:168-171. 

R-22 
NIOSH. See National Institute for Occupational Safety and Health. 

Nitschke, I.A.; Clarke, W.A.; Clarkin, M.E.; Traynmor, G.W.; Wadach, J.B. (1985) Indoor air quality infiltration and 

ventilation in residential buildings. NYSERDA #85-10. Albany, NY: New York State Energy Research and 

Development Authority. 

NRC. See National Research Council. 

O'Connell, E.J.; Logan, G.B. (1974) Parental smoking in childhood asthma.  Ann. Allergy 32:142-145. 

O'Connor, G.T.; Sparrow, D.; Weiss, S.T. (1989) The role of allergy and nonspecific airway hyperresponsiveness in 

the pathogenesis of chronic obstructive pulmonary disease. Am. Rev. Respir. Dis. 140:225-252. 

O'Connor, G.T.; Weiss, S.T.; Tager, I.B.; Speizer, F.E. (1987) The effect of passive smoking on pulmonary function 

and non-specific bronchial responsiveness in a population based sample of children and young adults. Am. 

Rev. Respir. Dis. 135:800-804. 

Ogden, M.W.; Maiolo, K.C.; Oldaker, G.B., III; Conrad, F.W., Jr. (1990) Evaluation of methods for estimating the 

contribution of ETS to respirable suspended particles. In: Indoor air '90: proceedings of the 5th international 

conference on indoor air quality and climate, v. 2, Characteristics of indoor air; July-August. Ottawa, 

Ontario, Canada: Canada Mortgage and Housing Corporation, pp. 483-488. 

Ogden, M.W.; Nystrom, C.W.; Oldaker, G.B., III; Conrad, F.W., Jr. (1989) Evaluation of a personal passive sampling 

device for determining exposure to nicotine in environmental tobacco smoke. In: Measurement of toxic and 

related air pollutants. Pittsburgh, PA: Air Pollution Control Association, pp. 552-558. 

Ogston, S.A.; Florey, C. du V.; Walker, C.M. (1987) Association of infant alimentary and respiratory illness with 

parental smoking and other environmental factors. J. Epidemiol. Community Health 41:21-25. 

Oldaker, G.B., III; Conrad, F.W., Jr. (1987) Estimation of the effect of environmental tobacco smoke (ETS) on air 

quality within aircraft cabins of commercial aircraft. Environ. Sci. Technol. 21:994-999. 

Oldaker, G.B.; Ogden, M.W.; Maiolo, K.C.; Conner, J.M.; Conrad, F.W.; DeLuca, P.O. (1990) Results from surveys 

of environmental tobacco smoke in restaurants in Winston-Salem, North Carolina. In: Indoor air '90: 

proceedings of the 5th international conference on indoor air quality and climate, v. 2, Characteristics of 

indoor air; July-August. Ottawa, Ontario, Canada: Canada Mortgage and Housing Corporation, pp. 281-285. 

Oldigs, M.; Jrres, R.; Magnussen, H. (1991) Acute effects of passive smoking on lung function and airway 

responsiveness in asthmatic children. Pediatr. Pulmonol. 10:123-131. 

Ong, T.M.; Stewart, J.; Whong, W.Z. (1984) A simple in situ mutagenicity test for detection of mutagenic air 

pollutants. Mutat. Res. 139:177-181. 

Overpeck, M.D.; Moss, A.J. (1991) Children's exposure to environmental cigarette smoke before and after birth. 

Advance Data from Vital and Health Statistics of the National Center for Health Statistics #202. DHHS Pub. 

No. (PHS) 91-1250. 

Park, J.K.; Kim, I.S. (1986) Effect of family smoking on acute respiratory disease in children. Yonsei Med. J. 

27:261-270. 

Parker, G.B.; Wilfert, G.L.; Dennis, G.W. (1984) Indoor air quality and infiltration in multifamily naval housing. 

Annual PNWIS/APCA meeting; November; Portland, OR, pp. 1-14. 

R-23 
Pattishall, E.N.; Strope, G.L.; Etzel, R.A.; Helms, R.W.; Haley, N.J.; Denny, F.W. (1985) Serum cotinine as a measure 

of tobacco smoke exposure in children. Am. J. Dis. Child. 139:1101-1104. 

Pedreira, F.A.; Guandolo, V.L.; Feroli, E.J.; Mella, G.W.; Weiss, I.P. (1985) Involuntary smoking and incidence of 

respiratory illness during the first year of life. Pediatrics 75:594-597. 

Perera, F.R.; Santella, R.M.; Brenner, D.; Poirier, M.C.; Munshi, A.A.; Fischman, H.K.; Van Ryzin, J. (1987) DNA 

adducts, protein adducts, and sister chromatid exchange in cigarette smokers and nonsmokers. J. Natl. 

Cancer Inst. 79:449-456. 

Pershagen, G.; Hrubec, Z.; Svensson, C. (1987) Passive smoking and lung cancer in Swedish women. Am. J. 

Epidemiol. 125(1):17-24. 

Peto, R.; Doll, R. (1984) Keynote address: the control of lung cancer. In: Mizell, M.; Correa, P., eds. Lung cancer: 

causes and prevention. New York: Verlag Chemie International, pp. 1-19. 

Phillips, R.L.; Garfinkel, L.; Kuzma, J.W.; et al. (1980a) Mortality among California Seventh-Day Adventists for 

selected cancer sites. J. Natl. Cancer Inst. 65:1097-1107. 

Phillips, R.L.; Kuzma, J.W.; Beeson, W.L.; et al. (1980b) Influence of selection versus lifestyle on risk of fatal cancer 

and cardiovascular disease among Seventh-Day Adventists. Am. J. Epidemiol. 112:296-314. 

Pierce, J.P.; Dwyer, T.; et al. (1987) Cotinine validation of self-reported smoking in commercially run community 

surveys. J. Chronic Dis. 40:689-695. 

Pierce, J.P.; Fiore, M.C.; Novotny, T.E.; Hatziandreu, E.J.; Davis, R.M. (1989) Trends in cigarette smoking in the 

United States. Projections to the year 2000. JAMA 261:61-65. 

Pimm, P.E.; Silverman, F.; Shepard, R.J. (1978) Physiological effects of acute passive exposure to cigarette smoke. 

Arch. Environ. Health 33:201-213. 

Pojer, R.; Whitfield, J.B.; Poulos, V.; Eckhard, I.F.; Richmond, R.; Hensley, W.J. (1984) Carboxyhemoglobin, 

cotinine, and thiocyanate assay compared for distinguishing smokers from non-smokers. Clin. Chem. 

30:1377-1380. 

Pukander, J.; Luotonen, J.; Timonen, J.; Karma, P. (1985) Risk factors affecting the occurrence of acute otitis media 

among 2-3-year old urban children. Acta Otolaryngol. 100:260-265. 

Pullan, C.R.; Hey, E.N. (1982) Wheezing, asthma, and pulmonary dysfunction 10 years after infection with 

respiratory syncytial virus in infancy. Br. Med. J. 284:1665-1669. 

Putnam, D.L.; David, R.M.; Melhorn, J.M.; Dansie, D.R.; Stone, C.J.; Henry, C.J. (1985) Dose-responsive increase in 

sister-chromatid exchanges in bone-marrow cells of mice exposed nose-only to whole cigarette smoke. 

Mutat. Res. 156:181-186. 

Quant, F.R.; Nelson, P.A.; Sem, G.J. (1982) Experimental measurements of aerosol concentrations in offices. 

Environ. Int. 8(1-6):249-258. 

Rantakallio, P. (1978) Relationship of maternal smoking to morbidity and mortality of the child up to the age of five. 

Acta Paediatr. Scand. 67:621-631. 

R-24 
Redline, S.; Tager, I.B.; Segal, M.R.; Gold, D.; Speizer, F.E.; Weiss, S.T. (1989) The relationship between 

longitudinal changes in pulmonary function and nonspecific airway responsiveness in children and young 

adults. Am. Rev. Respir. Dis. 140:179-184. 

Reed, B.D.; Lutz, L.J. (1988) Household smoking exposure--association with middle ear effusions. Fam. Med. 

20:426-430. 

Reese, A.C.; James, I.R.; Landau, L.I.; LeSouef, P.N. (1992) Relationship between urinary cotinine levels and 

diagnosis in children admitted to hospital. Am. Rev. Respir. Dis. 146:66-70. 

Remmer, H. (1987) Passively inhaled tobacco smoke: a challenge to toxicology and preventive medicine. Arch. 

Toxicol. 61:89-104. 

Repace, J.L. (1987) Indoor concentrations of environmental tobacco smoke: models dealing with effects of ventilation 

and room size. In: O'Neill, I.K.; Brunnemann, K.D.; Dodet, B.; Hoffmann, D., eds. Environmental 

carcinogens--selected methods of analysis, v. 9, Passive smoking. Chapter 3, IARC Monographs No. 81. 

Lyon, France: International Agency for Research on Cancer. 

Repace, J.L. (1989) Workplace restrictions on passive smoking: justification on the basis of cancer risk. In: Harper, 

J.P., ed. Transactions of an international specialty conference--Combustion processes and quality of the 

indoor environment. Niagara Falls, NY, pp. 333-347. 

Repace, J.L.; Lowrey, A.H. (1980) Indoor air pollution, tobacco smoke and public health. Science 208:464-472. 

Repace, J.L.; Lowrey, A.H. (1982) Tobacco smoke, ventilation and indoor air quality. Am. Soc. Heat Refrig. Air 

Cond. Eng. Trans. 88:894-914. 

Repace, J.L.; Lowrey, A.H. (1985) A quantitative estimate of nonsmokers' lung cancer risk from passive smoking. 

Environ. Int. 11:3-22. 

Repace, J.L.; Lowrey, A.H. (1990) Risk assessment methodologies in passive smoking. Risk Anal. 10(1):27-37. 

R.J. Reynolds Tobacco Company. (1988) New cigarette prototypes that heat instead of burn 

tobacco. Winston-Salem, NC: R.J. Reynolds Tobacco Co. 

Riboli, E.; Preston-Martin, S.; Saracci, R.; Haley, N.J.; et al. (1990) Exposure of nonsmoking women to 

environmental tobacco smoke: a 10-country collaborative study. Cancer Causes Control 1:243-252. 

Rickert, W.S.; Kaiserman, M.J.; Collishaw, N.E. (1990) Smoking in the home environment: a controlled room study. 

In: Indoor air '90: proceedings of the 5th International Conference on Indoor Air Quality and Climate, v. 2, 

Characteristics of indoor air; July-August. Toronto, Ontario, Canada: Canada Mortgage and Housing 

Corporation. 

Rickert, W.S.; Robinson, J.C.; Collinshaw, N.E. (1984) Yields of tar, nicotine and carbon monoxide in the sidestream 

smoke from 15 brands of Canadian cigarettes. Am. J. Public Health 74:228-231. 

Rijcken, B.; Schouten, J.P.; Weiss, S.T.; Speizer, F.E.; Van der Lende, R. (1987) The relationship of nonspecific 

bronchial responsiveness to respiratory symptoms in a random population sample. Am. Rev. Respir. Dis. 

136:62-68. 

Rimington, J. (1981) The effect of filters on the incidence of lung cancer in cigarette smokers. Environ. Res. 24:162-

166. 

R-25 
Roberts, D.L. (1988) Natural tobacco flavor.  Rec. Advan. Tob. Sci. 14:49-81. 

Robins, J.M.; Blebins, D.; Schneiderman, M. (1989) The effective number of cigarettes inhaled daily by passive 

smokers: are epidemiologic and dosimetric estimates consistent?  J. Haz. Mat. 21:215-238. 

Rogot, E.; Murray, J.L. (1980) Smoking and causes of death among U.S. veterans: 16 years of observation. Public 

Health Rep. 95:213-222. 

Ronchetti, R.; Macri, F.; Ciofetta, G.; et al. (1990) Increased serum immunoglobulin E and increased prevalence of 

eosinophilia in 9-year-old children of smoking parents. J. Allergy Clin. Immunol. 86:400-407. 

Rothman, K.J. (1986) Modern epidemiology. Boston: Little, Brown and Co. 

Russell, M.A.H.; Feyerabend, C. (1975) Blood and urinary nicotine in nonsmokers. Lancet 1:179-181. 

Russell, M.A.H.; Jarvis, M.J.; West, R.J. (1986) Use of urinary nicotine concentrations to estimate exposure and 

mortality from passive smoking in non-smokers. Br. J. Addict. 81:275-281. 

Rylander, E.; Eriksson, M.; Freyschuss, U. (1988) Risk factors for occasional and recurrent wheezing after RSV 

infection in infancy. Acta Pediatr. Scand. 77:711-715. 

Said, G.; Zalokar, J.; Lellouch, J.; Patois, E. (1978) Parental smoking related to adenoidectomy and tonsillectomy in 

children. J. Epidemiol. Community Health 32:97-101. 

Samet, J.M.; Tager, I.B.; Speizer, F.E. (1983) The relationship between respiratory illness in childhood and chronic 

air-flow obstruction in adulthood. Am. Rev. Respir. Dis. 127:508-523. 

Sandler, D.P.; Everson, R.B.; Wilcox, A.J. (1985) Passive smoking in adulthood and cancer risk. Am. J. Epidemiol. 

121(1):37-48. 

Saracci, R. (1989) Passive smoking and cancer risk. IARC report of a panel of experts. Prepared at the request of the 

European School of Oncology through the Europe Against Cancer program of the European Economic 

Community. Lyon, France: IARC. 

Saracci, R.; Riboli, E. (1989) Passive smoking and lung cancer: current evidence and ongoing studies at the 

International Agency for Research on Cancer. Mutat. Res. 222:117-127. 

Schelesselman, J.J. (1978) Assessing effects of confounding variables. Am. J. Epidemiol. 108:3-8. 

Schelesselman, J.J. (1982) Case-control studies: design, conduct, analysis. New York: Oxford University Press. 

Schenker, M.B.; Samet, J.M.; Speizer, E.F. (1983) Risk factors for childhood respiratory disease. The effect of host 

factors and home environment exposures. Am. Rev. Respir. Dis. 128:1038-1043. 

Schenker, M.B.; Samuels, S.J.; Kado, N.Y.; Hammond, S.K.; Smith, T.J.; Woskie, S.R. (1990) Markers of exposure to 

diesel exhaust. Research Publication Number 33. Cambridge, MA: Health Effects Institute. 

Schilling, R.S.F.; Letai, A.D.; Hui, S.L.; Beck, G.J.; Schoenberg, J.B.; Bouhuys, A. (1977) Lung function, respiratory 

disease, and smoking in families. Am. J. Epidemiol. 106:274-283. 

Schwartz, J.; Zeger, S. (1990) Passive smoking, air pollution, and acute respiratory symptoms in a diary of student 

nurses. Am. Rev. Respir. Dis. 141:62-67. 

R-26 
Seely, J.E.; Zuskin, E.; Bouhuys, A. (1971) Cigarette smoking: objective evidence for lung damage in teen-agers. 

Science 172:741-743. 

Seigel, D.G.; Greenhouse, S.W. (1973) Validity in estimating relative risk in case-control studies. J. Chronic Dis. 

26:219-226. 

Sexton, K.; Spengler, J.D.; Treitman, R.D. (1984) Personal exposure to respirable particulates: a case-study in 

Waterbury, Vermont. Atmos. Environ. 18:1385-1398. 

Sheen, S.J. (1988) Detection of nicotine in foods and plant materials.  J. Food Sci. 53:1572-1573. 

Shephard, R.J. (1992) Respiratory irritation from ETS. Arch. Environ. Health 47:(2):123-130. 

Shephard, R.J.; Collis, R.; Silverman, F. (1979) "Passive" exposure of asthmatic subjects to cigarette smoke. Environ. 

Res. 20:392-402. 

Sherman, C.B.; Tosteson, T.D.; Tager, I.B.; Speizer, F.E.; Weiss, S.T. (1990) Early childhood predictors of asthma. 

Am. J. Epidemiol. 132:83-95. 

Sherrill, D.; Holberg, C.J.; Lebowitz, M.D. (1990) Differential rates of lung growth as measured longitudinally by 

pulmonary function in children and adolescents. Pediatr. Pulmonol. 8:145-154. 

Shimizu, H.; Morishita, M.; Mizuno, K.; Masuda, T.; Ogura, Y.; Santo, M.; Nishimura, M.; Kunishima, K.; Karasawa, 

K.; Nishiwaki, K.; Yamamoto, M.; Hisamichi, S.; Tominaga, S. (1988) A case-control study of lung cancer 

in nonsmoking women. Tohoku J. Exp. Med. 154:389-397. 

Shultz, T.M.; Novotny, T.E.; Rice, D.P. (1991) Quantifying the disease impact of cigarette smoking with SAMMEC II 

Software.  Public Health Rep. 106(3)326-333. 

Sidney, S.; Caan, B.; Friedman, G. (1989) Dietary intake of carotene in nonsmokers with and without passive smoke 

at home. Am. J. Epidemiol. 129:1305-1309. 

Sims, D.G.; Downham, M.A.P.S.; Gardner, P.S.; Webb, J.K.G.; Weightman, D. (1978) Study of 8-year-old children 

with a history of respiratory syncytial virus bronchiolitis in infancy. Br. Med. J. 1:11-14. 

Sobue, T.; Suzuki, R.; Nakayama, N.; Inubuse, C.; Matsuda, M.; Doi, O.; Mori, T.; Furuse, K.; Fukuoka, M.; 

Yasumitsu, T.; Kuwabara, O.; Ichigaya, M.; Kurata, M.; Nakahara, K.; Endo, S.; Hattori, S. (1990) Passive 

smoking among nonsmoking women and the relationship between indoor air pollution and lung cancer 

incidence--results of a multicenter case controlled study. Gan To Rinsho 36(3):329-333. 

Somerville, S.M.; Rona, R.J.; Chinn, S. (1988) Passive smoking and respiratory conditions in primary school children. 

J. Epidemiol. Community Health 42:105-110. 

Sparrow, D.; O'Connor, G.; Colton, T.; Barry, C.L.; Weiss, S.T. (1987) The relationship of nonspecific bronchial 

responsiveness to the occurrence of respiratory symptoms and decreased levels of pulmonary function. The 

normative aging study. Am. Rev. Respir. Dis. 135:1255-1260. 

Speizer, F.E.; Ferris, B., Jr.; Bishop, Y.M.; Spengler, J. (1980) Respiratory disease rates and pulmonary function in 

children associated with NO exposure. Am. Rev. Respir. Dis. 121:3-10. 

Spengler, J.D.; Dockery, D.W.; Turner, W.A.; Wolfson, J.M.; Ferris, B.G. (1981) Long-term measurements of 

respirable sulphates and particles inside and outside homes. Atmos. Environ. 15:23-30. 

R-27 
Spengler, J.D.; Treitman, R.D.; Tosteson, T.D.; Mage, D.T.; Soczek, M.L. (1985) Personal exposures to respirable 

particulates and implications for air pollution epidemiology. Environ. Sci. Technol. 19:700-707. 

Spitzer, W.O.; Lawrence, V.; Dales, R.; Hill, G.; Archer, M.C.; Clark, P.; Abenhaim, L.; Hardy, J.; Sampalis, J.; 

Pinfold, S.P.; Morgan, P.P. (1990) Links between passive smoking and disease: a best evidence synthesis. A 

report of the working group on passive smoking. Clin. Invest. Med. 13:17-42. 

Stahlman, M.T.; Gray, M.E. (1984) Ontogeny of neuroendocrine cells in human fetal lung. I. An electron microscopic 

study. Lab. Invest. 51:449-463. 

Stanton, M.F.; Miller, E.; Wrench, C.; Blackwell, R. (1972) Experimental induction of epidermoid carcinoma in the 

lungs of rats by cigarette smoke condensate. J. Natl. Cancer Inst. 49:867-877. 

Steele, R.; Langworth, J.T. (1966) The relationship of antenatal and postnatal factors to sudden unexpected death in 

infancy. Can. Med. Assoc. J. 94:1165-1171. 

Steenland, K. (1992) Passive smoking and the risk of heart disease. JAMA 267:94-99. 

Stellman, S.D.; Garfinkel, L. (1986) Smoking habits and tar levels in a new American Cancer Society prospective 

study of 1.2 million men and women. J. Natl. Cancer Inst. 76(6):1057-1063. 

Sterling, T.D.; Sterling, E.M. (1983) Investigations on the effect of regulating smoking on levels of indoor pollution 

and on the perception of health and comfort of office workers. Eur. J. Respir. Dis. 65 (Suppl. 133):17-32. 

Stockwell, H.G.; Candelora, E.C.; Armstrong, A.W.; Pinkham, P.A. (1991) Environmental tobacco smoke and lung 

cancer in never smoking women. Presented at the annual meeting abstract forum: Society for Epidemiologic 

Research; June; Buffalo, New York. 

Strachan, D.P. (1988) Damp housing and childhood asthma: validation of reporting of symptoms. Br. Med. J. 

297:1223-1226. 

Strachan, D.P.; Jarvis, M.J.; Feyerabend, C. (1989) Passive smoking, salivary cotinine concentrations, and middle ear 

effusion in 7 year old children. Br. Med. J. 298:1549-1552. 

Strachan, D.P.; Jarvis, M.J.; Feyerabend, C. (1990) The relationship of salivary cotinine to respiratory symptoms, 

spirometry, and exercise-induced bronchospasm in seven-year-old children. Am. Rev. Respir. Dis. 

142:147-151. 

Sun, X-W. (1992) Heating fuels and respiratory diseases in the risks of female lung cancer. [In Chinese with English 

abstract.] Chung Hua Chung Liu Tsa Chih 13(6):413-415. 

Sutton, G.C. (1980). Assortive marriage for smoking habits. Ann. Human Biol. 7:449-456. 

Svendsen, K.H.; Kuller, L.H.; Martin, M.J.; Ockene, J.K. (1987) Effects of passive smoking in the multiple risk 

intervention trial. Am. J. Epidemiol. 126:783-795. 

Svensson, D. (1988) Lung cancer etiology in women [dissertation]. Karolinska Institute, Stockholm, Sweden. 

Svensson, C.; Pershagen, G.; Klominek, J. (1988) Smoking and passive smoking in relation to lung cancer in women. 

Department of Epidemiology, National Institute of Environmental Medicine, Stockholm, Sweden. 

Svensson, C.; Pershagen, G.; Klominek, J. (1989) Smoking and passive smoking in relation to lung cancer in women. 

Acta Oncol. 28:623-629. 

R-28 
Tager, I.B.; Segal, M.R.; Munoz, A.; Weiss, S.T.; Speizer, F.E. (1987) The effect of maternal smoking on the 

pulmonary function of children and adolescents. Analysis of data from two populations. Am. Rev. Respir. 

Dis. 136:1366-1370. 

Tager, I.B.; Weiss, S.T.; Munoz, A.; Rosner, B.; Speizer, F.E. (1983) Longitudinal study of the effects of maternal 

smoking on pulmonary function in children. N. Engl. J. Med. 309:699-703. 

Tager, I.B.; Weiss, S.T.; Rosner, B.; Speizer, F.E. (1979) Effect of parental cigarette smoking on the pulmonary 

function of children. Am. J. Epidemiol. 110:15-26. 

Tainio, V.M.; Savilahti, E.; Salmenpera, L.; Arjomaa, P.; Siimes, M.A.; Perheentupa, J. (1988) Risk factors for 

infantile recurrent otitis media: atopy but not type of feeding. Pediatr. Res. 23:509-12. 

Takasaka, T. (1990) Incidence, prevalence, and natural history of otitis media in different geographic areas and 

populations. Ann. Otol. Rhinol. Laryngol. 99:13-14. 

Tashkin, D.P.; Clark, V.A.; Simmons, M.; Reems, C.; Coulson, A.H.; Bourque, L.B.; Sayre, J.W.; Detels, R.; Rokaw, 

S. (1984) The UCLA population studies of chronic obstructive respiratory disease. VII. Relationship 

between parental smoking and children's lung function. Am. Rev. Respir. Dis. 129:891-897. 

Taylor, R.G.; Gross, E.; Joyce, H.; Holland, F.; Pride, N.B. (1985) Smoking, allergy, and the differential white blood 

cell count. Thorax 40:17-22. 

Teele, D.W.; Klein, J.O.; Rosner, B. (1989) Epidemiology of otitis media during the first seven years of life in 

children in greater Boston: a prospective, cohort study. J. Infect. Dis. 160: 83-94. 

Thompson, L.V.; Jenkins, R.A.; Higgins, C.E. (1989) A thermal desorption method for the 

determination of nicotine in indoor environments. Environ. Sci. Technol. 23:429-435. 

Toyoshima, K.; Hayashida, M.; Yasunami, J.; Takamatsu, I.; Niwa, H.; Muraoka, T. (1987) Factors influencing the 

prognosis of wheezy infants. J. Asthma 24:267-270. 

Trichopoulos, D. (1988) Passive smoking and lung cancer. Scand. J. Soc. Med. 16:75-79. 

Trichopoulos, D.; Kalandidi, A.; Sparros, L. (1983) Lung cancer and passive smoking: conclusion of Greek study. 

[Letter] Lancet 667-668. 

Trichopoulos, D.; Kalandidi, A.; Sparros, L.; MacMahon, B. (1981) Lung cancer and passive smoking. Int. J. Cancer 

27:1-4. 

Tsimoyianis, G.V.; Jacobson, M.S.; Feldman, J.G.; Antonio-Santiago, M.T.; Clutario, B.C.; Nussbaum, M.; Shenker, 

I.R. (1987) Reduction in pulmonary function and increased frequency of cough associated with passive 

smoking in teenage athletes. Pediatrics 80:32-36. 

Tunstall-Pedoe, H.; Woodward, M.; Brown, C.A. (1991) Tea drinking, passive smoking, and serum cotinine in the 

Scottish heart health study.  J. Clin. Epidemiol. 44:1411-1414. 

Turk, B.H.; Brown, J.T.; Geisling-Sobotka, K.; Froehlich, D.A.; Grimsrud, D.T.; Harrison, J.; Koonce, J.F.; Prill, R.J.; 

Revzan, K.L. (1987) Indoor air quality and ventilation measurements in 38 Pacific Northwest commercial 

buildings: final report to the Bonneville Power Administration. v. 1, Measurement results and interpretation. 

Uberla, K.; Ahlborn, W. (1987) Passive smoking and lung cancer; a reanalysis of Hirayama's data. In: Proceedings of 

international conference on indoor air quality. Tokyo: Council for Environment and Health, p. 41. 

R-29 
U.S. Bureau of the Census. (1990)  Statistical abstract of the United States, 1990. 

U.S. Department of Health and Human Services (U.S. DHHS). (1982) The health consequences of smoking: cancer. 

A report of the Surgeon General. U.S. DHHS, Public Health Service, Washington, DC. 

U.S. Department of Health and Human Services. (1983) The health consequences of smoking:  cardiovascular 

disease. A report of the Surgeon General. U.S. DHHS, Public Health Service, Office of the Assistant 

Secretary for Health, Office of Smoking and Health, Washington, DC. DHHS Pub. No. (PHS) 84-50204. 

U.S. Department of Health and Human Services. (1984) The health consequences of smoking: chronic obstructive 

lung disease. A report of the Surgeon General. U.S. DHHS, Public Health Service, Office of the Assistant 

Secretary for Health, Office of Smoking and Health, Washington, DC. DHHS Pub. No. (PHS) 84-50205. 

U.S. Department of Health and Human Services. (1986) The health consequences of involuntary smoking. A report of 

the Surgeon General. U.S. DHHS, Public Health Service, Office of the Assistant Secretary for Health, Office 

of Smoking and Health, Washington, DC. DHHS Pub. No. (PHS) 87-8398. 

U.S. Department of Health and Human Services. (1989) Reducing the health consequences of smoking: 25 years of 

progress. A report of the Surgeon General. U.S. DHHS, Public Health Service, Washington, DC. DHHS 

Pub. No. (CDC) 89-8411. 

U.S. Department of Health and Human Services. (1990a) The health benefits of smoking cessation. A report of the 

Surgeon General. U.S. DHHS, Public Health Service, Washington, DC. DHHS Pub. No. (CDC) 90-8416. 

U.S. Department of Health and Human Services. (1990b) Vital and health statistics: current estimates from the 

national health interview survey, 1989. U.S. DHHS, Public Health Service, Washington, DC. 

U.S. Department of Health, Education, and Welfare. (1964) Smoking and health.  Report of the Advisory Committee 

to the Surgeon General of the Public Health Service, Washington, DC. PHS Pub. No. 1103. 

U.S. Department of Health, Education, and Welfare. (1977) Nicotine. NIOSH manual of analytical methods, v. 3, 2nd 

ed. NIOSH, Cincinnati, OH. Publication No. 77-157-C. 

U.S. DHEW. See U.S. Department of Health, Education, and Welfare. 

U.S. DHHS. See U.S. Department of Health and Human Services. 

U.S. Department of Transportation. (1971) Health aspects of smoking in transport aircraft. U.S. Department of 

Transportation, Washington, DC. Available from: National Technical Information Service, Springfield, VA. 

U.S. Environmental Protection Agency. (1986a) Guidelines for carcinogen risk assessment. Federal Register 

51:33992-34003. 

U.S. Environmental Protection Agency. (1986b) Guidelines for the health risk assessment of chemical mixtures. 

Federal Register 51:34014-34025. 

U.S. Environmental Protection Agency. (1989) Workshop report on EPA guidelines for carcinogen risk assessment: 

use of human evidence. Office of Research and Development, Risk Assessment Forum, Washington, DC. 

EPA/625/3-90/017. 

U.S. Environmental Protection Agency. (1990) Health effects of passive smoking: assessment of lung cancer in adults 

and respiratory disorders in children. Office of Research and Development, Office of Health and 

Environmental Assessment, Washington, DC. External Review Draft. EPA/600/6-90/006A. 

R-30 
U.S. Environmental Protection Agency. (1992) Respiratory health effects of passive smoking: lung cancer and other 

disorders. Office of Research and Development, Office of Health and Environmental Assessment, 

Washington, DC. SAB Review Draft. EPA/600/6-90-006B. 

U.S. EPA. See U.S. Environmental Protection Agency. 

Vainio, H.; Hemminki, K.; Wilbourn, J. (1985) Data on the carcinogenicity of chemicals in the IARC Monographs 

programme. Carcinogenesis 6:1653-1665. 

Varela, L.R. (1987) Assessment of the association between passive smoking and lung cancer. [doctoral dissertation]. 

New Haven, CT: Yale University. 

Vaughan, W.M.; Hammond, S.K. (1990) Impact of designated smoking area. Policy on nicotine vapor and particle 

concentrations in a modern office building. J. Air Waste Management Assoc. 40:1012-1017. 

Vedal, R.E.; Schenker, M.B.; Samet, J.M.; Speizer, F.E. (1984) Risk factors for childhood respiratory disease. Am. 

Rev. Respir. Dis. 130:187-192. 

Vidic, B.; Ujevic, N.; Shabahang, M.M.; Van de Zande, F. (1989) Differentiation of interstitial cells and stromal 

proteins in the secondary septum of early postnatal rat: effect of maternal chronic exposure to whole cigarette 

smoke. Anat. Rec. 165:165-173. 

Vincent, R.G.; Pickren, J.W.; Lane, W.W.; Bross, I.; Takita, H.; Houten, L.; Gutierrez, A.C.; Rzepka, T. (1977) The 

changing histopathology of lung cancer: a review of 1682 cases. Cancer 39:1647-1655. 

Vincent, T.N.; Satterfield, J.V.; Ackerman, L.V. (1965) Carcinoma of the lung in women. Cancer 18:559-570. 

Vutuc, C. (1984) Quantitative aspects of passive smoking and lung cancer. Prev. Med. 13:698-704. 

Wald, N.J.; Boreham, J.; Bailey, A.; et al. (1984) Urinary cotinine as a marker of breathing other people's tobacco 

smoke. Lancet 1:230-231. 

Wald, N.J.; Ritchie, C. (1984) Validation of studies on lung cancer in nonsmokers married to smokers. Lancet 1:1067. 

Wald, N.J.; Nanchahal, K.; Thompson, S.G.; Cuckle, H.S. (1986) Does breathing other people's tobacco smoke cause 

lung cancer? Br. J. Med. 293:1217-1222. 

Wall, M.; Johnson, J.; Jacob, P.; Benowitz, N. (1988) Cotinine in the serum, salivia, and urine of nonsmokers, passive 

smokers, and active smokers. Am. J. Public Health 78:699-701. 

Wang, F-L. (1989) Analysis of risk factors for female lung adenocarcinoma in haerbin: indoor air pollution. [In 

Chinese with English abstract] Chung Hua Yu Fang I Hsueh Tsa Chih 23(5):270-273. 

Wang, J-N.; Zhang, Y. (1990) CO and particle pollution of indoor air in Beijing and its elemental analysis. Biomed. 

Environ. Sci. 3(2):132-138. 

Wang, N.S.; Chen, M.F.; Schraufnagel, D.E. (1984) The cumulative scanning electron microscopic changes in baby 

mouse lungs following prenatal and postnatal exposures to nicotine. J. Pathol. 144:89-100. 

Ware, J.H.; Dockery, D.W.; Spiro, A., III.; Speizer, F.E.; Ferris, B.G., Jr. (1984) Passive smoking, gas cooking, and 

respiratory health of children living in six cities. Am. Rev. Respir. Dis. 129:366-374. 

Weber, A.; Fischer, T. (1980) Passive smoking at work. Int. Arch. Occup. Environ. Health 47:209-221. 

R-31 
Weber, A.; Fischer T.; Grandjean, A. (1979) Passive smoking in experimental and field conditions. Environ. Res. 

20:205-216. 

Weir, J.M.; Dunn, J.E., Jr. (1970) Smoking and mortality: a prospective study. Cancer 25:105-112. 

Weiss, S.T.; Tager, I.B.; Speizer, F.E.; Rosner, B. (1980) Persistent wheeze: its relation to respiratory illness, cigarette 

smoking, and level of pulmonary function in a population sample of children. Am. Rev. Respir. Dis. 

122:697-707. 

Weiss, S.T.; Tager, I.B.; Munoz, A.; Speizer, F.E. (1985) The relationship of respiratory infections in early childhood 

to the occurrence of increased levels of bronchial responsiveness and atopy. Am. Rev. Respir. Dis. 

131:573-578. 

Weiss, W.; Boucot, K.R.; Seidman, H.; Carnahan, W.J. (1972) Risk of lung cancer according to histologic type and 

cigarette dosage. JAMA 222:799-801. 

Weitzman, M.; Gortmaker, S.; Klein Walker, D.; Sobol, A. (1990) Maternal smoking and childhood asthma. 

Pediatrics 85:505-511. 

Wells, A.J. (1988) An estimate of adult mortality in the United States from passive smoking. Environ. Int. 

14:249-265. 

Wells, A.J. (1990, December 4) Smoker misclassification does not account for observed passive smoking risk for 

lung cancer.  Submission to Indoor Air Quality and Total Human Exposure Committee, Science Advisory 

Board, U.S. Environmental Protection Agency, Washington, DC. 

Wells, A.J. (1991) An estimate of adult mortality in the United States from passive smoking; a 

response to criticism. Environ. Int. 17:382-385. 

Wells, A.J. (1992) An estimate of adult mortality in the United States from passive smoking; a further reply. Environ. 

Int. 18:321-325. 

White, J.R.; Froeb, H.F. (1980) Small airways dysfunction in nonsmokers chronically exposed to tobacco smoke. N. 

Engl. J. Med. 302:720-723. 

Whittemore, A.S. (1988) Effect of cigarette smoking in epidemiological studies of lung cancer. Stat. Med. 7:223-238. 

Wigle, D.T.; Collishaw, N.E.; Kirkbride, J.; Mao, Y. (1987) Deaths in Canada from lung cancer due to involuntary 

smoking. J. Can. Med. Assoc. 136:945-951. 

Willatt, D.J. (1986) Children's sore throats related to parental smoking. Clin. Otolaryngol. 11:317-321. 

Williamson, D.F.; Serdula, M.K.; Kendrick, J.S.; Binkin, N.C. (1989) Comparing the prevalence of smoking in 

pregnant and nonpregnant women, 1985 to 1986. JAMA 261:70-74. 

Woodward, A.; Douglas, R.M.; Graham, N.M.H.; Miles, H. (1990) Acute respiratory illness in Adelaide children: 

breast feeding modifies the effect of passive smoking. J. Epidemiol. Community Health 44:224-230. 

Woolcock, A.J.; Peat, J.K.; Leeder, S.R.; Blackburn, C.R.B. (1984) The development of lung function in Sydney 

children: effects of respiratory illnesss and smoking. A ten-year study. Eur. J. Resp. Dis. 65(Suppl):1-137. 

Woolcock, A.J.; Peat, J.K.; Salome, C.M.; et al. (1987) Prevalence of bronchial hyperresponsiveness and asthma in a 

rural adult population. Thorax 42:361-368. 

R-32 
Woolf, B. (1955) On estimating the relationship between blood group and disease. Ann. Hum. Genet. 19:251-253. 

Wright, A.L.; Holberg, C.; Martinez, F.D.; Taussig, L.M. (1991) Relationship of parental smoking to wheezing and 

nonwheezing lower respiratory tract illnesses in infancy. J. Pediatr. 118:207-214. 

Wright, A.L.; Taussig, L.M.; Ray, C.G.; Harrison, H.R.; Holberg, C.J. (1989) The Tucson's children respiratory study. 

II. Lower respiratory tract illnesses in the first year of life. Am. J. Epidemiol. 129:1232-1246. 

Wu, A.H.; Henderson, B.E.; Pike, M.D.; Yu, M.C. (1985) Smoking and other risk factors for lung cancer in women. J. 

Natl. Cancer Inst. 74(4):747-751. 

Wu-Williams, A.H.; Samet, J.H. (1990) Environmental tobacco smoke: exposure-response relationships in 

epidemiologic studies. Risk Anal. 10:1. 

Wynder, E.L.; Gottlieb, S.; Wright, G. (1957) A study of tobacco carcinogenesis. IV. Different tobacco types. Cancer 

10:1206-1209. 

Wynder, E.L.; Hoffmann, D. (1967) Tobacco and tobacco smoke: studies in experimental carcinogenesis. New York: 

Academic Press. 

Wynder, E.L.; Mabuchi, K.; Beattie, E.J., Jr. (1970) The epidemiology of lung cancer: recent trends. JAMA 

213:2221-2228. 

Wynder, E.L.; Stellman, S.D. (1977) Comparative epidemiology of tobacco-related cancers. Cancer Res. 37:4608-

4622. 

Xu, Z.Y.; Blot, W.J.; Xiao, H.P.; et al. (1989) Smoking, air pollution, and the high rates of lung cancer in Shenyand, 

China. J. Natl. Cancer Inst. 81:1800. 

Yarnell, J.W.; St. Leger, A.S. (1979) Respiratory illness, maternal smoking habit, and lung function in children. Br. J. 

Dis. Chest 73:230-236. 

Young, S.; LeSouef, P.N.; Reese, A.C.; Stick, S.M.; Landau, L.I. (1990) Factors predicting cough and wheeze in the 

first 6 months of life. Am. Rev. Respir. Dis. 141:A901. 

Zahm, S.H.; Cocco, P.; Blair, A. (1991) Tobacco smoking as a risk factor for colon polyps. Am. J. Public Health 

81:846-849. 

Zetterstrom, O.; Osterman, K.; Machado, L.; Johansson, S.G.O. (1981) Another smoking hazard: raised serum IgE 

concentration and increased risk of occupational allergy. Br. Med. J. 283:1215-1217. 

Zhao, Zhen-Hua; Quan, Wen-Yi; Tian, De-Hai (1990) Urinary 1-hydroxypyrene as an indicator of human exposure 

to ambient polycyclic aromatic hydrocarbons in a coal-burning environment. Sci. Total Environ. 92:145-

154. 

R-33