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52 I 1 I priori knowledge of potential confounders (i.e., by age even if it had not shown up as confounder in the data) (Greenland 1989) were used in model building. Concomitant variation in the stratified analysis step was assessed contrasting the rates of lung cancer among ETS unexposed non-smokers to k categories of ETS exposed non-smokers. Ordinai variables were created from categories of dummy variables to test the hypothesis of increasing rates by increasing levels of exposure to ETS using the likelihood ratio test. We treated k number of categories of cumulative exposure (i. e., k categories of number of hours exposed to ETS, or pack-years of cigarettes smoked by spouses), as continuous variables. Adjustment for covariates was allowed in testing this hypothesis by blocking for them. Regression diagr~ostics used include plotting survival curves [log -log (S l(t)) and log -log(S0(0] and checked for a pattern of parallelism (a constant ratio). For most analyses the estimates were obtained by blocking for them, rather than including them in the model However, when estimates were obtained for the covadates, all of them along with the main exposure were included in the model. Kaplan-Meier survival estimates were computed for the main exposure variables, as well as the covariates and the above mentioned graphic approach was used to check for the proportional hazard assumption. 3.11. Sample Size and Power Considerations The statistical power attained by the sample size of this study to detect different values of the rate ratio, including the point estimates from this study, was computed using the following estimator that assumes the rate ratio is a binomial parameter (Breslow 1987): 0 O~ 01 -0 0 I I I I I I I I

53 I I I I I I I I I I I I I I t-3=t-O(A)= where XA is the most extreme value in the acceptance zone under the the null hypothesis. One way of estimatin~ XA is by using the beta distribution with parameters 1- (z and tho expected number of exposed and unexposed cams under the null.

54 Chapter 4: Comparisons of Demographics and Smoking Habits in the US, CPS II, and the Study Populations Rationale A comparison of the 1980 US population with the CPS II population and specifically with the two analytic cohorts (i.e., 1) self-reported ETS and 2) spousal ETS by gender, age, race, occupation, education, geographic residence and smoking habits, is presented below. We used the population figures from the 1980 US Census as standard for age-adjustment, unless specified otherwise, because it was the Census closer in time to the cohort at the time of enrollment. Therefore, we excluded for the purpose of these comparisons those CPS II participants who resided in Puerto Rico, since they were not included in the 1980 US Census. Comparisons with the 1983 National Health Interview Survey (US DHHS Surgeon Genera/1989) figures are a/so presented. These comparisons lend a general perspective to better understand the analytic cohorts, and particularly to generate a profile of the demographics and smoking habits of the subjects in the study cohorts. Race Demographic information in the US is available by 'race'. Race is a proxy of socioeconomic status and was used here for the purpose of demographic comparisons. Twelve percent (or 26 million) in the US are blacks. In CPS II they represent 4.4 percent (or 52,038) of the participants. For these masons, further comparisons of demographics were restricted to whites. Gender and Age Structure The ratio of males to females (or gender ratio) in CPS II is considerably lower (0.75) than that among persons 30 years and older in the 1980 US Census 0 I I I I I / I

I I I I- I I I I I I I I I I I I I I 55 (0.88). Participants in this larg~ cohort were more likely to be in their 50's 60's at enrollment (Tables 5 and 6). Nonsmoking men and women (i.e., in our analytic cohorts) did not differ in their age distribution from the entire cohort (median 57 years in both groups). I Table 5. Comparison of age distributions of white males 30 years and over, in the US population in 1980, with CPS II participants*, .................. andI analytic c, ohorts* ..... Men Age 1980 Entire Self- Husbands Group Census % CPS II % reported % (spousal % 30-34 7,386,562 16.1 7,610 1.6 3,078 3.0 1,126 1.2 35-39 5,848,891 12.7 9,270 1.9 2,890 2.8 1,875 2.0 40-44 4,862,473 10.6 15,052 3.2 3,890 3.7 3,.286 3.4 45-49 4,616,347 10.1 6~,776 14.4 l 7,079 16.4 16,003 16.8 50-54 4,925,489 I0.7 87,030 18.2 19,14I 18.4 18,480 I9.4 55-59 4,877,635 10.6 91,236 19.l 17,647 16.9 16,893 17.7 60-64 4,199,446 9.1 79,344 16.6 15,804 15.2 15,306 16.0 65-69 3,470,295 7.6 58,162 12.2 11,861 11.4 11,406 11.9 70-74 2,565,929 5.6 35,487 7.4 7,069 6.8 6,534 6.8 75-79 1,652,668 3.6 17,045 3.6 3,687 3.5 3,206 3.4 80-84 918,166 2.0 5,909 1.2 1,361 1.3 1,029 1.1 85+ 603,663 1.3 ~.419 0.5 624 0.6 330 0.3 Total 45,927,564 I00 477.340 i00 104,131 100 95,474 100 *Excludes CPS II participants who resided in Puerto Rico

56 Table years and over, in the US population in 1980, with CPS II I I I I I ! I ! ! ! 6. Comparison of age distributions of white females 30 participants*, and analytic cohorts* Women Age 1980 Census Entire Self- Wives Group % CPS H % reported % (spousal % ETS ETS) 30-34 7,411,223 14.2 I 1,764 1.9 5,591 2. I 2,971 1.5 35-39 5,949,670 11.4 18,831 3.0 7,579 2.9 5,753 2.8 40-44 4,981,237 9.5 44,595 7.1 18,241 6.9 16,858 8.3 45-49 4,807,473 9.2 91,972 14.7 37,349 14.2 34,006 16.8 50-54 5,249,428 I0.0 106,175 17.0 43,434 16.5 38,805 19.2 55-59 5,409,320 I0.3 107,900 17.2 43,756 16.7 38,098 18.8 60-64 4,826,403 9.2 92,102 14.7 38,274 14.6 30,949 15.3 65-69 4,344,316 8.3 68,889 11.0 28,367 10.8 19,637 9.7 70-74 3,562,454 6.8 44,568 7.1 19,731 7.5 10,295 5.1 75-79 2,667,233 5. I 23,892 3.8 11,736 4.5 3,866 1.9 80.84 1,756,793 3.4 9,916 1.6 5,366 2.0 881 0.4 85+ 1,400,053 2.7 5,350 0.9 3, I65 1.2 160 0.1 Total 52,365,603 100 625.954 I00 262,589 100.0 202,279 100 *Excludes CPS rr participants who resided in Puerto Rico Occupation The types of occupations presently held by CPS H employed white participants were categorized into white and blue collar occupations. Managerial and professional specialty occupations, technicians and related support occupations, sales occupations, and administrative support occupations including clerical represented white collar occupations. Precision production, craft, and repair occupations, operators, fabricators, and laborers were classified as blue collar occupations. For these comparisons we excluded subjects with the following occupational codes in CPS II: housewives, disabled, retired, and subjects with none or unspecified data on occupations. I i I I

I I I I- I I I I I I I I I I I I I I 57 CPS II participants were more likely to be engaged in white collar occupations (Table 7). White women in CPS II were more likely to hold white collar jobs than white men, in a higher proportion than their counterparts in the entire US population do. Nonsmokers di~ not differ from the entire cohort with respect to their occupations. Table 7. Comparison of occupations of employed white persons 30 years and over, in the US population in 1980, in CPS II participant*, and analytic cohorts* a. Men 1980 Entire Type of Census CPS 17 Jobs (%) f (%) White Collar 18,I65,788 200,612 (55.8) (73.7) Blue Collar 14,409,714 1 71,718 (44.2) (26.3) Total 32,575,502 272,330 (100.0) (100.0) Self-reported Husbands ETS (spousal (%) ETS) (%) 47,889 43,901 (74.3) (73.7) 16,573 I5,684 (25.7) (26.3) 64,462 59,585 (100.o) (IOO.O) b. Women 1980 Entire Self-reported Wives Type of Census CPS II ETS (spousal Jobs (%) I (%) (%) ETS) (%) White Collar 18,464,642 221,093 91,700 70,404 (84.8) (94.6) (94.3) (94.5) Blue Collar 3,299,972 I 12,553 5,518 (5.7) 4,137 (5.5) (15.2) (5.4) Total 21,764,614 233,646 97,218 74,541 (lOO.O) (lOO.O) (ioo.o) (ioo.o) *Excludes CPS II participants who resided in Puerto Rico 0 Ol 01

58 Schooling Nonsmoking CPS IT men and women were more educated than smokers in CPS II as is also true for the rest of the US population, as reflected by their considerably higher rates of college graduates (Table 8). The entire CPS II cohort, after adjustment for age is also more educated than the US population as a whole (28% of college graduates in CPS II women versus 12% in the US populations over 30 years of age). Nonsmoking men in the analytic cohorts (in the cohort for analyses of self-reported ETS and among nonsmoking husbands for analyses of ETS from spousal smoking) were more educated than the rest of the CPS rr men. Table 8. Comparison of the proportion (%) of college graduates among whites in the US population in 1980, CPS II participants§, and analytic cohorts§ I- Men -I I- Women -I Age US CPS II SRETS Hus- US CPS II SRETS Wives • ga~o~ up .... C.ensus ~[ bands Census q[ 30-34 31.5' ' 49.~' 62.5 66.0 21.4 40.4 47.1 43.7 35-39 27.7 48.4 61.1 64.3 17.2 34.9 39.9 37.9 40-44 23.6 43.8 56.7 56.6 13.6 30.8 32.0 31.3 45-49 22.6 46.2 56.9 56.5 11.6 28.9 28.8 28.4 50-54 19.7 43.1 53.1 52.4 10.3 26.6 25.3 25.0 55-59 t 7.0 39.0 47.6 47. I 8.5 23.0 21.7 21.4 60-64 13.2 32.6 40.0 39.8 8.2 21. I 20.3 20.6 65-69 11.4 27.1 32.9 33.2 8.0 20.8 20.0 20.5 70-74 II.I 26.1 30.2 30.9 8.5 22.4 21.1 22.2 75+ 9. I 24.8 27.8 30.0 6.7 21.2 13.0 20.3 Adjusted 20.6 40.4 50.1 51.0 12.0 27.9 28. I 28.2 § Excludes CPS II participants who resided in Puerto Rico ~ SRETS: Serf-reported ETS cohorts * The standards are taken from 1980 US Census race-gender specific populations 0 0"~ O- I I I I i I ! I I I I I I

59 I I I I I I I I I I I I I I I Marital Status As shown in table 9, CPS I1 participants were more likely to be married than the rest of the US population, a fact that may be related to their more affluent status and the way they were enrolled. There were more unmarried women, and particularly single women in CPS II than unmarried men. This difference may be explained by a more active participation of women in recruiting people (i.e., ACS volunteers), whereas the men ~ere more likely to get enrolled in CPS 11 as members of family ~oups. Table 9. Comparison of the proportion (%) of married whites in the US population in 1980, white CPS II ..~ partieipants§~ and lanalytie cohorts.§ Men Women Age group US CPS 1I SRETS US CPS II SRETStJ[ __ Census ~ ~[ Cens~us _ . .................. 30-34 77.4 62.4 60.61 79.4 67.4 67.6 35-39 83.5 80.7 77.2 82.0 82.3 82.4 40-44 85.8 91.3 90.4 82.8 91.4 92.4 45-49 86.6 95.9 95.7 82.2 88.6 90.9 50-54 86.5 96.4 96.5 79.6 87.0 89.1 55-59 86.8 96.8 96.6 75. I 83.3 85.9 I 60-64 86.3 96.7 96.8 ' 67.2 77.0 79.9 65-69 84.2 95.9 96.2 56.2 65.7 68.4 70-74 80.8 94.2 94.3 43.6 51.7 54.3 75-79 74.8 90.8 91.7 30.1 35.3 36.2 80-84 65.3 83.2 83.6 17.9 19.8 19.9 85+ 48.8 62.0 60.8 : 8.3 7.9 7.7 Age 82.8 87.3 86.5 67.9 71.8 73.3 Adjusted* §Excludes CPS II participants who resided in Puerto Rico ~ SRETS: Self-reported ETS cohorts * The standards are taken from the 1980 US Census race-gender specific populations

6O I Residence The distribution of the CPS II by territory in general resembles the distribution of the US population (Table I0). A few States in the South (e.g., Texas, Oklahoma), the Mid-West (e.g., Missouri) and the North-East (e.g., New York) showed a deficit with respect to the distribution of the US population. Two States, Minnesota and Utah, had an outstanding participation rate, reflecting the activities of the ACS Divisions and perhaps the advancement of public health in those communities. Smoking Habits The age-adjusted prevalence of smoking habits in CPS lI and the 1983 HIS is shown in Table 11. Prevalence fi~mares of smoking habits in CPS 1I are similar to those of the US population by 1982. ~0 0 0~ I I ! I I I I I <1 I :~1 I '1 I I

I I I I I I I I I I I I I I I I I I Table State US Alaska 0.2 Arizona 1.2 Arkansas 1.0 Caiifomia 10.5 Colorado 1.3 Connecticut 1.4 Delaware 0.3 D.C. 0.3 Florida 4.3 Georgia 2.4 Hawaii 0.4 Idaho 0.4 Illinois 5.0 Indiana 2.4 Iowa 1.3 Kansas 1.0 Kentucky 1.6 Lousiana 1.9 Maine 0.5 Maryland 1.9 Masss 2.5 Michigan 4. I Minnesota 1.8 Mississippi I. I Missouri 2.2 10. US population in 1980, and CPS II by State of residence cPS rrI Men Wamen 1,7 1.8 0.I 0.I 1.4 1.4 1.3 1.3 8.7 8.9 1.2 1.2 1.7 1.7 0.3 0.3 0.1 0.i 4.8 4.9 2.6 2.6 0.2 0.2 0.6 0.5 5.6 5.6 2.8 2.8 1.5 1.4 1.5 1.5 1.5 1.6 0.9 1.0 0.6 0.6 2.8 2.7 2.0 2.0 3.8 3.7 3.2 3.0 0.9 0.9 1.3 1.3 participants* CPS II State U S Men Women Montana 0.4 " 0.4 0.4 Nebraska 0.7 I. 1 1.0 Nevada 0.4 0.2 0.2 N Hamp. 0.4 0.4 0.4 New Iet~ey 3.3 3.7 3.7 New Mcx 0.6 0.5 0.5 New York 7.8 5.8 6.0 NCarolina 2.6 1.8 1.8 N Dakota 0.3 0.6 0.5 Ohio 4.8 4.5 4.5 Oklahoma 1.3 0.0 0.0 Oregon 1.2 1.3 1.4 Penn 5.2 6.4 6.5 R Island 0.4 0.7 0.7 S Carolina 1.4 1.2 1.3 S Dakota 0.3 0.6 0.5 Tennessee 2.0 2.6 2.7 Texas 6.3 4.6 4.5 Utah 0.6 2.0 1.9 Vermont 0.2 0.2 0.2 Virginia 2.4 2.7 2.8 Washington 1.8 1.8 1.8 W Virginia 0.9 1.0 I. i Wisconsin 2.1 2.7 2.6 Wyoming 0.2 0.2 0.2 *Excludes CPS II participants who resided in Puerto Rico 61 I

Table 11. Age-adjusted prevalence* of current, former, and never cigarette smoking, CPS II and NHIS-83 Current Former Never CPS H HIS CPS HIS CPS HIS II H Men White 30.1 31.1 44.4 43.5 25.5 25.4 Black 42.5 41.8 31.6 32.1 25.9 26. i Women White 20.4 26.0 22.5 19.7 57.1 54.3 Black 26.2 27.4 I5.8 14.4 58.0 58.2 *(Percent). Standard population: CPS H 62 I i I I I I I I I I I I I I I I I

I I I- I I I I I I I I I I I I I I I 63 Chapter 5: Validity and Completeness Information I On the Outcome Variable i. Follow-up Procedures of the A validation study of the CPs II automated follow-up procedure has been conducted previously using the National Death Index (ND1) (Calle, 1993). In a linkage of over 15,000 persons whose vital status through 1988 had been traced through manual follow-up, 4,686 out of 5,046 (or 92.9 percent) of all deaths known to ACS volunteers were identified by the National Death Index. Since the use of automated foliow-up in CPS rr started in 1988, when there were 340 deaths from lung cancer ascertained by volunteers, another 22 have been ascertained by the use of the NDI. At a false-negative rate of 7% for the automated procedure, less thad two deaths would have been missed in our study (i.e. 0.07"22=1.54), by using the automated procedure instead of ascertaining deaths by ACS volunteers . As noted earlier, follow-up of vital status is complete for 99.8 % of all enrolled subjects, and of those 101,541 deceased subjects only 3,258 (3.2%) did not have a death certificate (ACS: Update of the CPS-II Master Index Vital Status report, April 12, 1993). ii. Results of Validation Study of Death Certificate Diagnoses of Lung Cancer '~ For 30 deaths for which lung cancer was considered the underlying cause of death in CPS II nonsmoking participants who resided in SEER registry areas, SEER diagnosis was compardd with the underlying cause of death on death certificates. In 29 subjects classified as primary lung cancer by death certificates, SEER Cancer Registries also diagnosed primary lung cancer in 27, and for two, the primary site was listed unknown in the SEER database. For no cases was the

disease known to be metastatic from other sites to the lung. I.n 25 of these 29 I lung cancers (86.2 percent), the specific histologic type was known to the SEER Cancer Registries, and in 64 percent they were adenocarcinomas. From this small validation study we conclude that lung cancers coded from death certificates generally correctly classify deaths fro~ primary lung cancer. The confirmation rate was 93. I percent (27/29), similar to that found in the TNCS study (Percy I981). Even in the two instances in our validation study in which the primary site of cancer was unknown, the diagnosis of lung cancer was not ruled out. Main Exposure Variables i. Self Reported ETS Exposure in CPS II and NI=IIS As mentioned above, because the CPS II questionnaires did not require respondents to complete all fields, many questionnaires contained blanks (Table 12). Twenty-three percent of the questionnaires filled by men and thirteen percent of those f'Llled by women were left blank in the three spaces provided for self-reported number of hours exposed to ETS (i.e., at home, work and other places). Table 13 displays in detail the patterns of answers from CPS II enrollees to the questions: " Whether or not you smoke, on the average, how many hours a day are you exposed to cigarette smoke of others? At home? (hours); At work (hours); In other areas? (hours)". As shown in this table, most times a space was left blank when valid answers were provided for at least one of the three environments. 0 0~ 0'~ 0 0'~ 0 I I I I I I I I I I I I I i I I

I I I 65 I I I I I I I I I I I I I I Table 12. Answers to question in CPS II on reported hours of ETS exposure at different settings a. All Men in CPS II Hours Home % Work % Other % Places 0 196,031 38.5 I24,114 24.4 101,533 20.0 I I5,107 3.0 52,856 10.4 71,040 14.0 2 12,258 2.4 24,834 4.9 26,533 5.2 3 8,649 1.71 9,089 1.8 6,979 1.4 4 18,363 3.6 13,359 2.6 6,240 1.2 5 8,678 1.7 5,059 1.0 1,714 0.3 6 11,904 2.3 8,527 1.7 1,384 0.3 7 2,621 0.51 3,985 0.8 280 0.1 8+ 37,827 7.4 80,478 15.8 4,710 0.9 Blank 180,924 35.6 163,357 32. i 261,885 51.5 Unclass 16,232 3.2 22,936 4.5 26,296 5.2 Total 508,594 100.(~ 508,594 100.0 508,594 100.0 All three fields left blank 65,999 (13.0%) All three fields with unclassifiabIe data 5,006 (1.0%) ~0 0 O~ 0~ 0 I

66 I I I I b. All Women in CPS II 'i:Iours Home % Work -% Other % ' Places 0 208,404 30.8 [54,373 22.8 99,953 14.8 1 16,103 2.4 40,117 5.9 46,088 6.8 2 14,029 2. I 16,636 2.5 20,148 3.0 3 10,952 1.6 6,243 0.9 7,06 [ 1.0 4 20,430 3.0 8,937 1.3 4,726 0.7 5 13,642 2.0 4,766 0.7 1,385 0.2 6 15,753 2.3 7,204 1.1 928 0.1 7 4,097 0.6 6,630 1.0 181 0.0 8+ 59,412 8.8 59,133 8.7 4,393 0.6 Blank 282,326 41.7 345,165 51.0 433,178 64.0 Unclass 31,382 4.6 27,326 4.0 58,489 8.6 Total 676,530 100.0 676,530 i00.0 676,530 100.0 . All three fields left blank 156,249 (23.1%) All three fields with unclass data 6,285 (0.9%) 0 0 0 I I I I I I i I I

! I I I- I I I I I I I I I I I I I I I Table 13. Patterns of answers given by CPS [I participants to self- assessment of number of hours exposed,, to ETS ~.i.~ Men w~m~fi -' ' Home Work Other hours hours hours , • 65,999 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 I to 1 to 1 to 1 to 1 to I to 0 5,732 1 to 8' 26,097 9 * 8,993 0 l 4,422 0 0 186 0 1 to 8 130 0 9 30 1 to 8 50,206 1 to 8 0 319 I to 8 1 to 8 7,361 I to 8 9 373 9 . 9,208 9 0 25 9 1 to 8 110 9 9 1,733 7,704 0 2,334 1 to 8 2,216 9 431 11,190 65,314 28,323 4,791 1 21,994 1 19,818 I 28,225 1 1,284 654 522 299 932 31,703 0 145 1 to 8 5,311 9 167 0 2,244 0 0 4,146 0 0 0 0 I to8 0 9 to 8 to 8 0 to 8 I to 8 to 8 9 9 9 0 9 Ito8 9 9 12.98 156,249 23.10 l. 13 8,565 1.27 5.13 24,543 3.63 1.77 22,486 3.32 0.87 5,434 0.80 0.04 173 0.03 0.03 100 0.01 0.01 80 0.01 9.87 47,135 6.97 0.06 186 0.03 1.45 4,265 0.63 0.07 745 O. I 1 1.81 9,946 1.47 0.00 18 0.00 0.02 l I9 0.02 0.34 2,282 0.34 1.51 18,908 2.79 0.46 4,372 0.65 0.44 3,743 0.55 0.08 2,613 0.39 2.20 27,148 4.01 12.84 72,162 I0.67 5.57 22,997 3.40 0.94 13,632 2.01 4.32 19,751 2.92 3.90 8,292 1.23 5.55 10,249 1.51 0.25 1,871 0.28 0.13 841 0.12 O. 10 354 0.05 0.06 265 0.04 0.18 1,206 0.18 6.23 77,326 11.43 0.03 142 0.02 1.04 6,890 1.02 0.03 876 O. 13 0.44 5,009 0.74 0.82 4,022 0.59 67 o o~ 0~ 0~ o o~ o

68 I I to 8 0 1 to 8 3,050 0.60 2,810 0.42 1 to 8 0 9 174 0.03 505 0.07 1 to 8 1 to 8 . 46,980 9.24 44,622 6.60 1 to 8 1 to 8 0 2,897 0.57 1,518 0.22 i to 8 1 to 8 1 to 8 17,191 3.38 8,415 1.24 1 to 8 1 to 8 9 791 0.16 1,316 0.19 1 to 8 9 . 206 0.04 432 0.06 1 to 8 9 0 t7 0.00 19 0.00 1 to 8 9 1 to 8 123 0.02 96 0.01 1 to 8 9 9 262 0.05 420 0.06 9 . 5,362 1.05 14,569 2.15 9 0 15 0.00 15 0.00 9 1 to 8 69 0.01 133 0.02 9 . 9 1,079 0.21 3,735 0.55 9 0 37 0.01 71 0.01 9 0 0 27 0.01 76 0.01 9 0 1 to 8 11 0.00 23 0.130 9 0 9 39 0.01 131 0.02 9 1 to 8 390 0.08 922 0.14 9 1 to 8 0 I0 0.00 II 0.00 9 1 to 8 I to 8 137 0.03 62 0.01 9 I to 8 9 211 0.04 306 0.05 9 9 3,586 0.71 4,815 0.71 9 9 0 26 0.01 28 0.00 9 9 1 to 8 227 0.04 200 0.03 9 9 9 5,006 0.98 6,285 0.93 Total 508,594 100.130 676,530 100.00 *a 9 code means that unquantifiable answ~rs(~vor~g like a ,,10t,,or "little"), as well as question marks, were answered. The comparisons of CPS-II data on ETS exposure at home, with data from the 1988 National Health Interview Survey (NCHS NHIS 1988) is presented in table 14, stratified by age, race and gender. If spaces left blank for number of hours exposed to ETS at home in CPS II are considered.to represent zero hours (i.e., unexposed), and persons with "unclassifiable" ETS information are excluded, then the prevalence figures from self reported data on ETS exposure at home in CPS rr resemble the prevalence in NHIS. Indeed, all age-adjusted comparisons of gender and racial specific prevalence figures agree within 3.3 percent. The category of "unclassifiable" ETS represent vague wording (e.g., a question mark, 'Iittle') that could not be converted into hours during coding of questionnaires. We concluded that when self-reported ETS exposure in CPS II o 0~ o 0~ o o~ I I I ,|

I I- I I I I I I I I I I I I I I 69 I was left blank, persons should be considered unexposed, and that "unclassifiable" data on ETS exposure in the three blanks should be excluded from the analyses. Table 14. Percentage of nons~aokers reportedly exposed to ETS at home* in CPS II ** and NI:IIS *** by age, race and gender. White Men Black Men White Black Women Women Age CPS NI-IIS :kDiff CPS NHISI :k CPS NHIS :k CPS NHIS _.+ lI lI Diff lI Diff II Diff 30-34 12.8 10.2 2.6 12.9 II.6 1.3 21.2 15.9 5.3 22.9 21.8 1.I 35-39 10.5 9.2 1.3 12.7 I2.4 0.3 I9.9 14.9 5.0 20.1 18.1 2.0 40-44 8.7 7.7 45-49 9.1 7.3 t.0 t4.4 9.4 1 5.0 1.8 9.6 18.1 -8.5 19.3 15.3 4.0 22.4 20.7 1.7 18.9 17.6 1.3 21.1 18.4 2.7 50-54 8.7 15.5 -6.8 I1.0 14.2 -3.2 18.3 18.6 -0.3 19.4 30.0 -10.6 55-59 8.3 14.4 -6.1 12.0 17.9 -5.9 16.4 11.5 4.9 17.1 22.8 -5.7 60-64 7.3 11.4 -4.1 10.3 25.01 -14.7 13.1 13.0 0.1 15.5 24.0 -8.5 65+ 5.2 5.9 -0.7 5.4 12.0 -6.6 8.4 7.2 1.2 11.7 11.7 0.0 Total 7.8 9.4 -1.6 9.9 13.4 -3.5 14.7 12.8 1.9 17.0 19.2 -2.2 8.8§ 9.8 -t.0 t0.9 14.2 -3.3 15.8 13.2 2.6 18.5 19.9 -t.4 ETS exposure as self-repoSed'- ~umb~ oi"h~'~'~f'~xt~osurc to ETS at home in CPS IL m~d as living with a smoking person who smokc~ at home in NHIS. ** Excludes "unelassifiable" ETS exposure at home. Considers I-8 hours as exposed, and blanks in spaces provided to write ETS exposure at home, as well as O's as unexposed. *** Weighted percentages (i.e., weights are inverse of selection probabilities) §Age adjusted prevalence figures using the 1980 US Census sub-populations as standards I

7O Comparisons of CPS II participants in the analytic cohort for self-reported ETS analyses were conducted to contrast characteristics such as age, schooling and 'race', for individuals who filled all three spaces and those who left spaces blank. Those who left any space blank were more likely to be older, and less educated, and more likely to be non-whites than those who f'ti1ed the three spaces (Table 15). However, persons who f'tlled all three fields for hours of exposure at home, work and other places and who reportedly had zero hours of exposure to ETS, were similar to those who left any blank space for ETS in CPS II questionnaires. As will be discussed in Chapter 8, a possible implication of this distribution of missing data is that perhaps blanks might not represent ETS unexposed subjects. Table 15. Characteristics of CPS II nonsmokers in analytic cohort for self-reported ETS by completeness of the information provided for ETS Characteristic Left any ETS field Completed all ETS blank fields Cross-product (Column percent) (Column percent) . rati~ Age group 65 + 30-64 Schooling <12 years 12+ 'Race' Non-whites Whites 25.4 20.5 74.6 79.5 15.6 8.1 84.4 91.9 8.3 5.5 91.7 94.5 1.4 2.1 1.7 ! !

I I I I I I I I I I I I I I I I I 71 ii. CPS II Self-reported Exposure to ETS and Spousal Smoking Habits Results of the second validationlstudy that compared self-reported ETS exposure with the smoking status of cohabitees and spouses are presented in tablel6. Table 16.a. and 16.b show that seE-reported exposure to ETS at home by CPS nonsmoking women and men, respectively, agreed with having at least one current smoker among cohabi~ees: the observed agreement was 88.4% for. women, and 94.5% of men (k=56.0%; 95% CI=55.6-56.45 for women, and k=63.5%; 95% CI=62.7-64.3 for men). Self reported ETS (hours of exposure at home) agreed better with the smoking status of spouses (Table 16.c. and 16.d.) than with the number of ~moking cohabitees (Table 16.a. and I6.b.); the observed agreement was 87.8% and 95.4% for wives (Table 16.c.) and husbands, respectively (k=62.6%; 95% CI=62.2-62.9 for nonsmoking wives, and k=69.8%; CI=69.0-70.6, for nonsmoking husbands). We concluded that self-reported ETS exposure in CPS II was internally consistent with the smoking habits reported by spouses. We also concluded that self-reported ETS is closer to spousal ETS than to smoking of cohabitees. Using current smoking status of spouses as standard, self-reported ETS would misclassify 4.6% of the subjects, with a specificity of 98%. Table 16.a. Comparison of self-reported exposure to ETS at home by CPS II nonsmoking women and the number of ........ _current smokers among cohabitees. I Cohabitees status Self-reported At least one Nonsmoker and Total ETS current smoker former smokers .................... only, Yes 33,951 (9.8) 17,250 (5.0) 51,201(14.8) No 22,850 (6.6) 271,947 (78.6) 294,797 (85.2) Total 56,801 (16.4) 289,197 (83.6) 345,998 (100.0) kL-~6~0% (¢5% CI=55.6-56.4) .......... I 0 0 ~0

Table 16.b. Comparison of self-reported exposure to ETS 72 I at home by CPS II nonsmoking men and the number of _ ....... curren,t,smokers amon cohabitees Cohabitees status Self-reported At least one Nonsmoker and Total ETS current smoker former smokers _ ...... °n!y .... Yes 6,981 (5.6) 2,814 (2.2) 9,795 (7.8) No 4,204 (3.3) I 11,622 (88.9) 115,826 (92.2) Total 11,I85 (8.9) 114,436 (91.1) 125,621 (100.0) k=63.5% (95% CI=62.7-64.3) Table 16.c. Comparison of self-reported exposure to ETS at home by CPS II nonsmoking wives and the smoking status of their husbands Husband status Self-reported Current smoker Nonsmoker Total ETS and former smoker Yes 31,945 (14.2) 5,463 (2.4) 37,408 (16.6) No 22,047 (9.8) 165,781 (73.6) 187,828 (83.4) Total 53,992 (24.0) 171,244 (76.0) 225,236 (100.0) ..... ~--£6-2~-6~/,~-(95 % ci=62.2-62.~) ..................... Table 16.d. Comparison of self-reported exposure to ETS at home by CPS II nonsmoking husbands and the smoking status of their wives Wife Self-reported Current smoker • ETS status Nonsmoker and former smoker Total Yes 6,266 (6.0) 1,741 (t.7) 8,007 (7.6) No 3,058 (2.9) 93,549 (89.4) 96,607 (92.4) Total 9,334 (8.9) k=69.8% (95% ci=69.0-70.6)" 95,290 (91.1) 104,614 (100.0) 0 O~ o~ O~ ~0 0 0"~ ~ . 0 I I I I ! I I I I I I I I I

I I I I. I I I I I I I I Among nonsmok~ug women, we also compare.d the amount of cigarettes smoked by their male cohabitees and the self-reported number of hours exposed to ETS at home. As showrt in table 17 ~d figure 6, there is a concomitant variation of more hours of exposure to ETS and the number of cigarettes and pack of cigarettes reportedly smoked by their husbands. • ~ F,g~.~re 6. Percentage of nonsmoking women exposed to spedfied self-reported number of hours of ETS at home and number of dgarettes smoked by their husbands I ~100 Amount of Nonsmoking .~ ~~/ Cigarettes 1-9 ~~0 smoked by ' °~°p~a~ck ~'7~+ H°urs Husbands , 20-3; ~2 3 4 ~ I 0 " I I I I I I Number of *Restricted to nonsmoking women whose spouses were current cigarette smoking I 0 O~ 0 O~

74 Table 17. Distribution of reported hours of exposure to ETS at home by nonsmoking women, according to number of cigarettes smoked by their husbands. Cigarettes husband smoked 0 Non smoking lto9 10 to 19 I pack 20-39 2+ packs Number of Hours of ETS at home % 1 % 2 % 3 % 4 % 75299 89.9 69l 26.3 334 13.1 135 5.91 121 2.84 2211 2.64 388 I4.8 235 9.24 139 6.09 2081 2.49 520 19.8 500 19.7 368 16.1 2484 2.97 620 23.6 792 31.2 775 33.9 905 1.08 268 10.2 397 15.6 485 21.2 745 0.89 140 5.33 284 11.2 382 16.7 83725 I00 2627 1~0 2542 100 2284 160 3.75 550 12.9 1430 33.5 1065 25 939 22 4265 100 5 % 6 % 7 % 8 % Total % Non smoking Ito9 10 to I9 I pack 20-39 56 1.79 58 1.72 13 1.52 146 2.19 76853 70.2 77 2.46 85 2.52 II 1.29 203 3.05 3509 3.21 325 10.4 291 8.62 62 7.24 626 9.4 5323 4.86 966 30.9 999 29.6 227 26.5 2094 31.4 10387 9.49 892 28.5 1015 30.1 288 33.6 1720 25.8 7035 6.43 2+ packs 809 25.9 927 27.5 255 29.8 1874 28.1 6355 5.81 Toml 3125 I~0 3375 100 856 100 6663 100 109462 100 I I ! I ! I ! I

I I I 75 I Chapter 6: Descriptive Statistics Variables Frequency of Self-reported and Spousal ETS of Exposure Forty-eight percent of the nonsmoking population in our analytic cohort reported ETS exposure at home, work: or other places. Table 18 presents the distribution of self-reported number of hours of ETS exposure at home, work: and other places, and combined in the three settings, according to the definitions presented in Section 3.9. Fourteen percent reported any exposure at home, 26 percent at work: and 18 percent from elsewhe~. Among those exposed to any ETS, one third was exposed to ETS for one or two hours, another third was exposed for two to five hours, and the rest to six and more hours of ETS. Accordingly, cutoffs of ETS were used at 3, and 5 hours of self-reported exposure at home, I, 2 and 6 hours of self-reported exposure at work:, and 1, 2, and 3 for self- reported exposure elsewhere, to create categorical variables and conduct further analyses. Up to 9.7 percent of nonsmokers had 3 and more hours of ETS exposure at home, but only 2.6 percent obtained that amount of exposure to ETS in places other than work or home. I More than half of the nonsmoking spouses, or 53.6 percent, in the analytic cohort for spousal ETS were married to smoking spouses. As mentioned before, smoking of tobacco products other than cigarettes were not collected in the questionnaires sent to wome[~, and thus all the spousal smoking of nonsmoking husbands comprised exclusively cigarette smoking. On the other hand, 33.7 percent of nonsmoking wives (or 71, 891) were married to nonsmokers, and two-thirds, or 66.3 percent, were married to ever smoking husbands. The latter group could b~ further divided according to the following types of smoking: 15.8 percent ( or 33,705) were married to current cigarette smokers; 30.1 percent (or 64,230) to former cigarette smokers; 2.5 percent (or 5, 487) to smokers of both cigarettes and pipes or cigars; 4.6 percent (or 9,794) to current pipe and or cigar smokers [vho formerly smoked cigarettes; 6.7 percent I

76 or (14,306) to former smokers of both cigarettes and pipe/cigars; 4.3 percent (or 9,253) to former pipe/cigar smokers who never smoked cigarettes; and 2.1 percent (or 4,487) to former cigarette smokers who then smoked pipe or cigars. Correlates of ETS exposure However, the contributions of each ETS exposure setting to the overall exposure varied greatly by gender. More men more than women reported exposure at work, whereas women reported most of their exposure at home. Table 18. Hours of exposure to ETS reported by nonsmoking CPS II participants at different settings, 1982 a. Both Men and Women Places Total ETS None 337,144 86.0 288,832 73.6 321,012 81.8 205,433 52.4 1 9,855 2.5 37,737 9.6 46,554 11.9 61,490 t 5.7 2 7,324 1.9 14,039 3.6 14,379 3.7 31,140 7.9 3 8,679 1.4 4,911 1.3 4,202 1.1 13,116 3.3 4 5,367 1.4 6,376 t.6 2,512 0.6 t3,366 3.4 5 5,748 2.2 2,914 0.7 745 0.2 8,074 2.1 6 5,748 1.5 4,355 I. 1 433 0.1 9,051 2.3 7 1,290 0.3 3,349 0.9 102 0.0 5,010 1.3 8+ 11.484 2.9 29.713 7.6 2,287 0.6 45.546 11.6 Total 392,226 I00 392,226 1t30 392,226 1130 392,226 o 0~ o 0~ ! 1 I i I ! ! I I I I I I I

I I I 77 I I I I I I I I I I I I I I I b. Men Hours Home % .... Work % Other % Total % Places ETS None 101,481 91.7 69,9~3 63.2 81,912 74.0 48,175 43.5 1 2,641 2.4 l 6,909 15.3 20,758 18.8 24,272 21.9 2 1,488 1.3 6,363 5.7 4,990 4.5 12,548 11.3 3 933 0.8 2,072 1.9 I, 144 1.0 4,355 3.9 4 1,380 1.2 2,7~4 2.5 783 0.7 3,937 3.6 5 606 0.5 989 0.9 289 0.3 2,009 1.8 6 726 0.7 1,513 1.4 135 . 0.i 2,192 2.0 7 93 0. I 704 0.6 39 0.0 1,042 0.9 8,~- ~ l,.340 1.2 9.486 8.6. ..638 0.6 12,158 !I.0 Total 110,688 I00 110.688 I00 110,688 100 110,688 I00 e. Women Hou~ ....... H~in~ % Work % Other % Total ETS % : I Places None 235,663 83.7 218,859 77.7 239,100 84.9" 157,258 55.9 1 7,214 2.6 20,828 7.4 25,796 9.2 37,218 t3.2 2 5,836 2. I 7,703 2.7 9,389 3.3 l 8,592 6.6 3 4,402 1.6 2,83~ 1.0 3,058 1.1 8,761 6.6 4 7,299 2.6 3,652 1.3 1,729 0.6 9,429 3.3 5 4,761 1.7 t,925 0.7 456 0.2 6,065 2.2 6 5,022 1.8 2,842 1.0 298 0.1 6,859 2.4 7 I, 197 0.4 2,645t 0.9 63 0.0 3,968 1.4 8+ 10.144 3.6 20,245 7.2 1.649 0.6 33,388 11.9 Total 281.538 I00 281,538 1t30 281.538 L00 281,538 lt30 I As shown in table 19, self-reported exposure to ETS decreased from 70 percent to 16 percent with increasing age. Spousal smoking exposure, however, did not show this trend, except for current smokers (Table 20). One implication of this ! o P0 o

78 difference, as will be discussed in Chapter 8, may be that self-reported ETS does not reflect long-term, but rather current ETS exposure. Table 19. Proportion of nonsmoking CPS II participants in analytic cohorts who reported any ETS exposure by age at .......... interview,h. 1982 ..................... ...... Age Group . Men and Women .Women ................. Men_ .. 30-34 70.1 67.5 75.1 35-39 66.5 64.5 71.9 40-44 61.0 58.9 70.6 45-49 61.6 57.5 70.7 50-54 58.6 54.7 67.5 55-59 52.9 49.1 62.3 60-64 43.3 39.5 52.6 65-69 29.6 26.7 36.6 70-74 20.7 18.7 26.2 75+ years 15.5 14.7 18.1 Total 52.4 55.9 43.5 Table 20 presents the proportion of participants with spouses also in the study and whose spouses were ever smokers (i.e., spousal smoking). Almost two- thirds of nonsmoking women lived with ever smoker husbands whereas only 27 percent of men were married to ever smoker wives. Table 20..Proportion of nonsmoking participants married to ............ eve_r-smokin.g.....sP0use by age at, interview, 1982 Age Group Men and Women Men Women 30-34 46.5 53.9 27.2 35-39 52.7 60.7 29.2 40-44 57.4 62.7 31.3 45--49 52.8 63.7 29.8 50-54 54.8 67. i 29.0 55-59 56.7 69.4 28.1 60-64 54.3 68.3 26.1 65-69 51.2 67.4 23.4 70-74 49.0 66.6 21.4 ~75+ ~¢ears . 40.5 63.0 16.1 Total -53~6 .............66.3 " " 26.8 I I I I I I I I I I I

| I I I i I I I I I I I I I I I I 79 Important correlates of ETS exposure were schooling and race, both of which can be taken as surrogates of social class. Non-white men and women were slightly less self-reportedly exposed than whites: the ratio of the proportion of I exposed nonwhites to exposed whites was 0.8. Married women were 5.8 percent more likely to be self-reportedly exposed to ETS than unmarried women. More educated men and women were more likely to report ETS exposure, or to have an ever-smoker spouse than less educated men and women: the ratio of self-reported ETg exposure among the most formally educated, to that among the least formally educated was 2.8 and 2.0 for men and women, respectively. However, among husbands and wives, the ratio of smoking spouse among the most educated the least educated was 0.6 for men and women. Unlike self-reported ETS exposure, assessment of ETS exposure based on the smoking history provided by spouses in the study shows a picture consistent with the demography of ETS exposure in the US population at large that was described in Chapter 1. Therefore, the assessment of ETS exposure based upon 1 spousal ETS might reflect better true ETS exposure, than self-reported ETS. People reporting exposure to asbestos, chemicals, coal dust or tar, formaldehyde and ionizing radiation, were more likely to report ETS exposure but did not / differ substantially according to the smoking status of spouses. ETS exposed and unexposed were comparable with respect to medical history of any chronic non-malignant disease. ETS exposed and unexposed groups were also comparable with respect to the consumption of foods considered major sources I of carotenoids. 0~

Table Characteristic Number of subjects Age at interview (years) (standard deviation) Rac~ (% white) Married (%) Education (%) <High School High School Trade School or some College L>College Occupation (%) Any asbestos Other lung carcinogens§ Diet: times/week (standard d~viation) G~e~n leafy vegetables FruitHuices Characteristics of nonsmoking participants accordiag to self-reported ETS Men Women No ETS An,v ETS No ETS Any ETS 48,175 62,513 157,258 124,280 (43%) (57%) (56%) (44%) 60.4 53.6 60.2 53.2 (11.2) (9.6) (I 1.7) (10.0) 92.9 94.3 92.1 93.3 93.7 93.4 74.1 79.9 17.7 7.6 18.3 9.9 19.9 17.7 31.1 33.8 21.7 24.8 2&7 30.5 40.7 49.8 23.9 25.8 4.9 7.1 1.4 2.4 20. l 26.6 6.8 11.9 4.8 4.7 5.0 5.0 (2.0) (2.0) (2.0) (1.9) 5.2 5.0 5.5 5.4 (2.3) (2.3) (2.1) (2.2) Chronic lung dis. (%) Any 7.2 7.2 7.6 8.0 Tuberculosis I. I 0.9 1.0 1.0 Chronic bronchitis 1.7 1.7 2.9 3.1 Emphysema 1.0 0.5 0.5 0.3 Asthma 4.4 4.9 4.2 4.6 § Self-reported occupational exposures to: Chemicals, coal dust or tar, formaldehyde and ioni~.ing radiation. 80 o 0", r~ o o~ I I I I I

I I I I- I I I I I I I I I I I I I I Table 22. C'hamct~dstic Number of subjects Age at interview (years) (standard deviation) Race (% white) Mar~ed (~,) Education (%) <High School High School Trade School or some College _:>College Occupation (%) Any asbestos Other lung carcinogens§ Diet: dmes/w~k (standard deviation) Green leaf3, vegetables Fruit/Juices CharacteriStics of nonsmoking participants according to spousal smoking Husbands Non smoker , I 73,914 ~7.4 (10.2) 94.9 I I00.0 Wives W'fie Non smoker Husband ever husband ever smoked smoked 27,040 71,892 141,262 55.8 54.5 55.3 (9.4) (10.1) (9.5) 94.7 94.8 95.0 ~oo.o ~oo.o [oo.o 12.6 8.5 9.0 I 1.5 20.2 ; 16.2 31.3 36.0 23.9 23.2 30.1 29.6 43.2 52. I 29.5 23.0 6.2 6.6 1.7 1.8 24.3 24.2 8.9 9.4 4.0 (2.5) (2.3) 4.0 4.7 4.6 (2.5) (2.2) (2.3) 5.2 5.4 5.4 (2.3) (2.1) (2.2) Chronic lung dis. (%) Any 7.1 7. I 7.2 7.7 Tuberculosis 1.0 [ 1.0 0.9 1.0 Chronic bronchitis 1.7 1.4 2.6 3.0 Emphysema 0.8 0.6 0.3 0.3 Asthma 4.5 4.9 4.3 4.4 ~ Sel~S~eportcdr~cupati0nal ex~posure~' ~0: Chemicals, coal dust or t~r, formaldehyde and ionizing radihtion. 81

82 i Smoking status, quantity and duration of ETS from spouses Spouses of subjects in the study comprised the following major categories: I) nonsmoking spouses (145,806, or 46.4 percent) 2) current and former cigarette smokers with .complete data (41,099 or 13.1 percent, and 71,594 or 22.8 percent respectively), 3) former and current smokers with incomplete data (1,764 or 0.6 percent and 6,087 or 1.9 percent, respectively), 4) ever smokers with unclassifiable smoking (4,431 or 1.4 percent) and 5) ever pipe and or cigar smokers which includes a mixture of smoking of the different tobacco produ6ts (43,327 or 13.8 percent). Analysis of dose-response relationships between ETS from spousal smoking and the risk of cancer among nonsmokers is restricted to cigarette smoking spouses with complete data, and the univariate statistics of the variables used in the analyses are presented. The quantity of smoking is based upon frequency (i.e., cigarettes per day) as recalled by the smoking spouses of nonsmoking participants. We set a value of zero for nonsmoking spouses of nonsmokers in the study. The number of cigarettes smoked by the 41,099 spouses of nonsmoking participants who were current cigarette smokers and had complete smoking information, and who never smoked cigars or pipes, ranged from I to 100 a day, with a mean of 22.6 cigarettes per day, a first quartile of 15 cigarettes, a median of 20, and a third quartile of 30 cigarettes. Ninety percent of current smoking spouses smoked up to two packs of cigarettes. The position of the fast and second tertiles for the quantity of cigarette smoking among the current cigarette smokers of nonsmokers was 20 (i.e., one pack) and 25 cigarettes per day, respectively. Among the 71,594 nonsmokers in this analytic cohort whose spouses were former cigarette smokers, had complete smoking information, and did not smoke other tobacco products, the quantity of usual former cigarette smoking were O~ O~ O~ 0 I 1 1 1 ! 1 I I I I I I i I I

I I I I I I I I I I I I I I I I I I 83 similar to those previously shown for current cigarette smoking spouses: a range from I to 100 cigarettes per day, the mean was in 22.6 cigarettes per day, the median was 20 (i.e. one pack), but the first quartile was lower at I 1 cigarettes per day, and the third quartile was 30. Again, ninety percent smoked less up to two packs of cigarettes. The tertiles were 18 and 20 for the lower and upper, respectively. For those subjects in the analytic cohort of spousal ETS who were married to cigarette smoking spouses with complete data, we computed the time they were married to spouses, to assess the effect of this variable as well as to compute the pack-years smoked during marriage by smoking spouses. As described before, we excluded those subjects married more than once or whose spouse was also married more than once, or with incomplete data on age at marriage., since both were needed to compute time in marriage exposed to smoking spouse (i.e., the difference between age at interview and the age at first marriage yielded the duration of marriage, and is used in combination with the age at uptake and quitting smoking as well as the age at interview of smoking spouses, to compute the time during marriage nonsmokers were exposed to spousal smoking). Typically nonsmoking husbands and wives who were married to a cigarette smoking spouses, had spent in average 21 years (standard deviation of 12 years, median=21 years) exposed to ETS, and the values of this variable ranged from 1-63 years, and differences between men and women were small. The cutoffs for the tertiles of the distribution of the duration of exposure to ETS from spousal smoking for these group of individuals were 15 and 27 years for exposed men, and 17 and 30 for exposed women. The distribution of study subjects according to the combination of usual amount of cigarette smoking with the duration of exposure to ETS from spousal cigarette smoking during marriage is presented in Table 23. Among nonsmokers married to smoking spouses pack-years ranged from I to 198 with a mean of 24.0 pack-years, and a median of 20 pack-years, and the cutoffs of tertiles the cutoffs were approximately 16, and 35, but men and women differed considerably: the mean

84 packyears of E-tS spousal smoking among nonsmoking men and exposed to any Ei-S were 19 and 29, respectively. A t-test yielded a p-value <0.000I. Table 23. Study populations included in spousal analyses for intensity and duration of ETS exposure from spousal cigarette smoking among nonsmoking spouses in CPS II a. Smoking of current and former cigarette smoking (i.e., nonsmokers =0) n=258,499, see page 88. ..... ~0unt of "' Amount of current Number % former Number % .... s_mokin~g ............ ~moking 0 145,806 78.0 0 145,806 67.1 < I pack 12,606 6.7 < I pack 23,917 11.0 1 - t.9 packs 21,511 11.6 i - 1.9 packs 33,878 15.6 ..... 2_+. packs 6,982 3.7 .2+ packs 13,799 6.3 Total 186,905 100.0' Total 217,400 i00.0 Results in table37. " " ~-b. Time in marriage With cigarette smoking spouse, and packs of cigarette-years in marriage, (nonsmoking spouses set to 0), n=148,204. Results in table 39. Exposed to spousal ETS for: Years Men % Years Women % Number Number None 46~0~9 852 ~)2[ None 46,149 50.0 1-15 3,326 1-17 14,794 16.0 16-26 3,125 516 ! 18-29 15,491 16.8 27+ 3,492 6.2[ 30+ 15,788 17.1 .................... :Tot~ 148,204 100.0 c. Pa~ks of-ci~-t~tt~:y~ars-in ~a'r'riage; (nonsmoking spouses set to 0), n=148,204. Results in table 40. ...... Pack- " ' Mer~ ...... % " Pack-years ..... years Num~r ..... 46,039 82.2 0 0 1-8 9-22 23+ Women % Number 76,771 83~2 3,339 6.0 1-I6 15,451 16.7 3,263 5.8 17-35 15,569 16.9 3,341 6.0 36+ 15,053 16.3 To~l 148,204 100.0 I I I I I I I I I I i I

I I I I I I I I I I I I I I I I I 85 Chapter 7: Main Results 7.1 Deaths from Lung Cance.r ~tnd Histological Data in Death | Certificates There were 362 deaths from lung cancer among nonsmokers in the study cohort of self-reported ETS exposure. Before the ND[ update of follow-up status was completed to include new deaths frorh lung cancer that occurred between October I, I988, and December 31, 1989, we reviewed the death certificates from 284 or 78 percent of the deaths from lung cancer f'mally included in our analyses. These 284 deaths were the deaths ascertained during the f'trst six years of follow- up. In 169 instances or 59 percent, d~ath certificates only mentioned lung cancer without any reference to histological type. In the remaining 115 lung cancer deaths, or 41 percent, the certificate specifically mentioned histological type. Table 24, shows the frequencies of each major histologic type. Seventy percent of lung cancer among nonsmokdrs, when their histological types were documented in death certificates, were adenocarcinomas. If the unclassified were excluded, the proportion of adenocarcinomas would be 75 percent. There were no differences by gender in the distribution of histological types mentioned in death certificates. I Table 24. Distribution of hystological types in 115 deaths from lung cancer among nonsmokers in the analytic cohorts in CPS II, 1982-1988, for which this information was readily ....... _available from ~eath .certificates • ..T._)~pe_ Women. ,Men ....... Total _ Number (%) Number (%) Number (%) Adenocarcinomas 59 (71.1) 21 (65.6) 80 (69.6) Squamous cell 12 (14.4) I 7 (21.9) 19 (16.5) Large cell i (1.2) 3 (9.4) 4 (3.5) Other types 3 (3.6) 1 (3. i) 4 (3.5) Unclassified 8 (9.6) 0 (0.0) 8 (7.0) Total 83 (100.0) I 32 (100.0) 115 (100.0) l

86 I 7.2 Potential confounders: age, gender, schooling, race, prexisting lung disease, occupational exposure to lung carcinogens, consumption of foods containing carotenoids, and fat as nutrient index. Age The rates of lung cancer increased monotonically with age. Figure 7 depicts this feature of the risk of lung cancer by age: observed values were fitted empirically by Poisson and exponential regression models, both providing an adequate description of the data. As we described earlier, age was also strongly associated with self-reported and ETS exposure from spousal smoking. Thus, age was included in all models. Figure 7. Death Rates of Lung Cancer among CPS II Nonsmoking participants by Age, 1982-1989 8O 70 60 50 Rate per 40 lOO,OOO 30 20 10 0 <50 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85+ Age groups Observed ~'~ Exponential ~ Poisson o o 0~ I I I I I I I I I I / I I

87 I I I I I I I I I I I I I I Gender Nonsmoking men showed an increased risk of lung cancer as compared with nonsmoking women, the crude rate ratio being 1.2 (95% CI=I.0-1.5) (i.e., 116/ /786,532 , Men and women were comparable with respect to age, men being slightly younger (Table 25). Thus, the Mantel-Haenszel RR for gender, adjusted for age was 1.3 (95% CI= 1.1-1.7). Men had a slightly greater likelihood of being reportedly exposed to ETS than women (56 percent and 53 percent, respectively). Sources of exposures to ETS were different for men than for women (i.e., most for men from work, and women at home). Women were more exposed to ETS from, their husbands, than were nonsmoking men from their wives. Thus, gender was included in all the models. Table 25. Death rates of Lung Cancer among Nonsmokers by Age and G{mder, CPS II, 1982-1989 Men Women Age-group <50 3 121,1781 I5 2 4 50-54 4 133,136 17 3 18 55-59 4 144,161 18 3 21 60-64 16 131,477 17 12 30 65-69 27 109,5881 14 25 30 70-74 26 76,221 10 34 39 75-79 14 42,807 5 33 44 80-84 17 19,322 2 88 35 85+ 5 8,643 ~ 1 58 25 Person- % Rate t~ Person- % Rate >,e~ ...... lOT,~ ..... 7e~ ,,, _1o-5 ~ 341,834 17 1 303,204 15 6 338,198 17 6 329,075 16 9 270,185 13 I1 196,522 I0 20 129,427 6 34 69,869 3 50 41,768 2 60 Total 116 786,532 I00 15" 246 2,020,081 (n=392,226 subjects) *Age-adjusted to the CPS-rr population. Age-SRR=I.4 (95% CI=I.I-1.8) RR (m-h)=t.3 (95% CI=1.I-~1.7) I00 10"

88 Race I I I I I I ! ! ! ! ,, ! Only 9.4 percent of the deaths from lung cancer, or 34 occurred among 'nonwhites'. All but three of these deaths occurred among African-Americans. We collapsed all 'races' different from 'whites' into a category of 'nonwhites' for the purpose of the analyses. Table 26 presents deaths rates by this dichotomous variable, and by age. The total row presents age-adjusted rates. Nonwhites had a 44% increased risk of lung cancer, after adjusting for age [RR re.h=1.4 (95% CI=I.0-2.0)] (Table 26). As pointed out before, nonwhites were less likely to report ETS exposure but were comparable in the proportion of spousal ETS. Therefore, we included 'race' in the multivariate analysis of ETS and lung cancer. Table 26. Death rates of Lung Cancer among Nonsmokers by Age ,and 'Race', CPS II, 1982-1989 Whites Nonwhites Age-group ~ Person- % Rate t~hs Person- % Rate years 10-5 years 10-5 <50 0 43,513 22 0 7 419,493 16 2 50-54 2 30,306 15 7 20 406,037 16 5 55-59 2 31,258 16 6 23 451,103 17 5 60-64 1 28,440 14 4 45 432,112 17 10 65-69 10 23,123 12 43 47 356,650 14 13 70-74 6 17,487 9 34 59 255,256 I0 23 75-79 8 11,458 6 70 48 160,776 6 30 80-84 2 6,306 3 32 50 82,885 3 60 85+ 3 4,271 2 70 27 46,140 2 59 Total 34 196,161 I00 17" 326 2,610,452 100 11" (n=390,833 subjects and 360 deaths) *Age-adjusted to the CPS-II population. Age-SRR=I.6 (95% CI=1.1-2.3) RR (m-h) age-adjusted=l.4 (95% CI=I.0-2.I) 0

89 I I I I I I I I I I I I I Schooling Years of education was both related to ETS exposure in the entire study population and was a risk factor for lung cancer. Younger CPS II nonsmoking participants tended to be more educated than older, as shown in table 27, along with the corresponding number of deaths, person-years under observation, and death rates. The unadjusted comparison of rates of those who did not graduate from high school, as compared to those who did, was 2.2 (95% CI=1.8-2.8). After adjustment by age, the Mantel-Haenszel estimate dropped to 1.2 (95% CI=0.9-1.5). Years of education was positively associated with self-reported ETS, and inversely related with spousal smoking status. Although schooling was not a meaningful confounder based upon the data at hand, it was included in all multivariate analyses based upon a priori knowledge of the association between lung cancer and low socioeconomic status. Table 27. Death rates of Lung Cancer among Nonsmokers by Age and S.ehooling, .CPS II, ....1982-.!989 ..... <12 },rs 12 + ,vrs Age-~oup Dent Person- % Rate Dear Person- % Rate hs years 10-5 hs years 10-5 <50 0 20,515 6 0 7 442,497 18 2 50-54 1 27,204 7 4 21 409,136 17 5 55-59 2 41,590 I 1 5 23 440,769 18 5 60-64 4 52,470 14 8 42 408,081 17 10 65-69 13 60,234 I6 22 44 319,539 13 14 70-74 20 61,908 17 32 45 210,835 9 21 75-79 18 50,765 I4 35 40 121,468 5 33 80-84 21 31,749 9 66 31 57,442 2 54 85+ 13 23,322 6 56 17 27,089 1 63 Total 92 369,758 100 13" 270 2,436,856 100 12" (n=392,226 subjects) *Age-adjusted to the CPS-II population. Age-SRR=I. 1 (95% CI=0.8-1.4) RR (m-h) age-adj.=l.2 (95% CI=0.9-I.5) I 0 ".4

90 I Asbestos Self-report of being ever occupationally exposed to asbestos was associated with a two-fold higher risk of lung cancer among'nonsmokers in CPS lr (Table 28) [age-adjusted RR (m-h)=2.0 (95% CI=1.I-3.5)]. The effect estimate associated with asbestos was similar [multivariate RR=I.8 (95% CI=1.I-3.2)], after controlling for age, gender and the indicator of 'race', and schooling, as well as total intake of foods containing carotenoids, history of chronic lung disease and self-reported ETS exposure in Cox multivariate analyses (Table 30). Adjusted rate ratios associated with ever being exposed to asbestos at work were slightly lower for men [1.5 (95% CI=0.7-3.I)] than for women [2.3 (95% CI=I.0-5.3)]. Table 28. Death rates of Lung Cancer among Nonsmokers by Age and self-reported Occupational Exposure to Asbestos, CPS II,1982-1989 Age-group Ever exposed Unexposed Person- % Rate t~, Person- % Rate years 10-5 years 10-5 <50 0 13,913 20 0 7 449,099 16 2 50-54 2 12,326 18 16 20 424,018 15 5 55-59 0 13,073 19 0 25 469,288 17 5 60-64 2 11,730 17 i7 44 448,822 16 10 65-69 5 9,071 13 55 52 370,701 14 14 70-74 1 5,384 8 19 64 267,359 10 24 75-79 0 2,609 4 0 58 i69,625 6 34 80-84 2 999 1 200 50 88,192 3 57 85+ 2 457 I 437 28 49,953 2 56 Total 14 69,562 100 25* 348 2,737,057 100 11" (n=392,226 subjects) *Age-adjusted to the CPS-17 population. Age-SRR=2.2 (95% CI=1.2-3.9) RR (m-h) age-adjusted=2.0 (95% CI= 1. I-3.5) 0 0"~ CO 0", 0 O~ I I ! I I I I I I ! I I I I

! ! ! 91 Only 2.5 percent, or 9,664 subjects reported ever having occupational exposure to asbestos. Five percent of men in the analytic cohort for self-reported ETS fell in that category, and only 1.4 ~percent of women said they had ever been occupationally exposed in their life-time. Among those who said they had ever been exposed to asbestos at work, 65 percent were in the labor force by 1982. The occupations/industries more frequently mentioned by them included professions with presumably 10w exposure such as teaching (21 percent), management (i 1 percent), engineering (5 percent), and technicians (2 percent), as well as trades with potentially higher exposures such as automechanies (5 percent), and construction (2 percent). Twenty-five percent of those ever exposed to asbestos had retired from the same occupations. Sixty percent of CPS II participants had previously held a job different from that currently held or at retirement. The major frequencies were approximately the same (teachers, managers, and salesmen, 10, 4 and 8 percent, respectively). In addition, 2 percent mentioned they also had worked at factories, 4 percent were farmers and fishermen, and 8 percent worked in offices. Of those nonsmokers ever engaged in occupations known to carry likely high exposure to asbestos (i.e., shipbuilding, pipefitters), or likely low exposure to asbestos (i.e., plumber, construction, duckworker, autorepair, and electrician), or engaged in any occupation which fell in the category of 'possibly exposed' (See the detailed list in the Covat~iates section in 3.6), only those subjects who were reportedly ever engaged in shipbuilding trades (n=95) had a significant increased risk [multivariate RR=9.7 (95% CI=1.3-71.3)]. The number of years men and vomen were ever exposed to asbestos were grouped by tertiles of those ever exposed (i.e., the categories being 1-5 years, 6- 15 years, and 16+ years of exposure) and compared with those who reportedly were never exposed to asbestos at work. Table 29 shows the deaths, person- years and rate ratios for men an~ women separately and combined in the last column. Among the 9,664 exposed CPS II participants, 8,316 (or 86 percent)

92 I I I I I | ! ! ! reported the number of years exposed; out of the 14 deaths among nonsmokers ever exposed to asbestos, only 12 had information on years of exposure. Multivariate rate ratios showed in the third, six and nine columns of table 29, indicate that the rate ratios increase with longer exposure; however, did not follow a consistent increasing trend. The risk of lung cancer among nonsmokers exposed to asbestos in this study increased to 3. i for those who worked up to five years.as compared to nonsmokers unexposed to asbestos and then decreased to 1.2 for those who worked 5 to 16 years and remained at 1.2 among those who worked more than twenty years. Among women there was a non-statistically significant increasing trend of lung cancer risk by years of self- reported exposure to asbestos (p---0.15), but not for men (p=0.66). Self-reported occupational exposure to asbestos was a potential confounder of the ETS and lung cancer association, so we included asbestos in multivariate analysis. Preexisting chronic lung disease Medical history of any obstructive pulmonary disease (asthma, chronic bronchitis, or emphysema) or tuberculosis, or a combination of all of these conditions was not associated with the risk of lung cancer for men and women combined (RR=I.0 (95% CI=0.7-1.5)]. However, among men there was a statistically significant increased risk (RR=2.1, 95%CI=1.3-3.6), whereas among women, there was no association (RR=0.6, 95%CI=0.4-1.2). The interaction term of gender and history of chronic lung disease, when adjusting for all other covariates was statistically significant (LRz24e=t =9.2, p---0.002). This apparent effect of reported medical history of preexisting lung disease on the risk of lung cancer among nonsmokers in CPS II was heavily influenced by the history of chronic bronchitis. There was an increased risk of lung cancer among nonsmoking men with a history of chronic bronchitis [multivariate RR=3.8 (95% CI=1.8-7.8)], and there was none among women [0.6 (95% CI--0.2-1.4)]. 0 O~ Co O~ 0 O~ 0 I I

Table 29. Lung cancer rate ratios among nonsmokers by years of occupational exposure to asbes!.os, and gender, CPS II,1982-1989 Deaths Years of Deaths Men- RR* Deaths Wome RR* Men All person- RR** exposure among Years (95% among n- (95% CI) and years (95% CI) Men CI) Women Years Women None 108 745,894 1.0 240 1,9910 356 2,737,057 1.0 163 28,925 Ever 8 40,638 1.5 6 2.3 14 69,562 ! .8 (0.7-3. l ) ( 1.0-5.3) ( 1. 1-3.2) 1-5 yrs 6 12,793 3.6 1 7,456 1.9 7 20,249 3.1 _ (1.5-8.4) -. (0,3- - (1.-4-6.8) 13.4) 6-15 yrs 1 9,708 1.1 ! 9,280 1.3 2 18,988 1.2 (0.2-7.8) (0.2-9.5) (0.3-4.8) 16+ yrs 1 13,158 0.6 2 6,890 2.8 3 20,048 1.2 (0.1-4.2) (0.7- (0.4-3.9) • ,,,., 11.2) p for trend 0.66 0.15 0.23 Missing 0 4,979 2 5,298 2 10,,27.7 (n=392,058; 168 were exposed but had vague data on number of years e~Posed) *Adjusted for age, schooling, 'race', consumption of foods containing earotenoids, total fat as a nutrient index, history of chronic lung disease, and ETS. ** In addition adjusted for gender. ~890~9890~

94 Diet: foods containing carotenoids and total fat After controlling for other covariates, a reduction in the risk: of lung cancer was observed among nonsmokers with the highest reported frequency of consumption of a combination of the following foods containing carotenoids: carrots, squash and corn, green leafy vegetables, cabbage, broccoli and Brussels sprouts, tomato, and fruits andjnices. There was a borderline significant trend of decreasing risk of death from lung cancer by increasing frequency of wee~y intake of these food items (LRZ2d.f=L=3.043, p value for trend=0.0811). Nonsmokers who were in the upper quintile of the distribution of total fat intake (as nutrient index) had a statistically significant increased risk of lung cancer as compared to those in the lowest category, after adjusting for all other covariates (age, 'race', gender, schooling, history of lung disease, frequency of consumption of foods containing carotenoids, and occupational exposure to asbestos). There was a statistically significant dose-response relationship between the risk of lung cancer among nonsmokers by increasing level of total fat intake (LRZ2df=L=4.695, p value for trend=0.0302). There was a weak positive correlation between the frequency of consumption of foods containing carotenoids and total dietary fat intake (rxy=0.29). The partial correlation coefficient controlling for schooling, age, gender, was essentially unchanged (rxylZ 1 ,z2,..Zp=0.30). Other risk factors Nonsmokers who had ever been occupationally exposed to ionizing radiation showed a non-statistically significant increased risk of lung cancer [multivariate RR=I.6 (95% CI=0.7-3.5)] (Table 30). No evidence was found of an increasing trend of years of self-reported occupational exposure to ionizing radiation, when those ever exposed where grouped by tertiles of years of exposure to ionizing radiation at work: the multivariate RR were 0.9 (95% CI=0.2-3.7), 1.1(95% CI--0.3--4.5), and 0.9 (95% CI=0.2-3.6), for the first, second and third tertiles, respectively. The p value for a test for trend was 0.9. 0 0 I I I I I I

95 I I I I I I I I I I I I I I Other occupational exposures to lung carcinogens such as formaldehyde, coal tar products, and chemicals, as recorded in CPS II questionnaire, were not associated with the risk of lung cancer among nonsmokers [multivariate RR=0.9 (95% CI---0.6-1.3)] (Table 30). Multivariate rate ratios on the covariates presented in this section arc summarized in table 30, and are all included in the model, along with self-reported ETS : age at interview grouped into nine five-year groups, gender, schooling and 'race' and history of chronic lung disease as dichotomous variables, frequency of consumption of foods containing carotenoids grouped into tertiles compared with no consumption of foods and vegetable, and total fat as a nutrient index grouped into quintiles. In addition, indicator variables were included for missing observations on 'race', schooling, and diet. As shown in table 30, multivariate Cox regression analysis shows that when smokers under 50 years of age were used as referent, the RR estimates increased monotonically by every five-year age period: .1.8, 2.9, 4.4, 6.1, 8.2, 14.6, 14.6, and 22.4 . Men had a 30% increased risk as compared to women [RR=I.3 (95% CI=1.0-1.6)]. Non-whites had a 50% increased risk of lung cancer as compared to whites [RR=I.5 (95% CI=1.1-2.2)]. Asbestos was associated with almost a two-fold increased risk ['RR=I.8 (95% CI=1.1-3.2)]. History of chronic lung disease was not associated with the risk of lung cancer among men and women together [RR-1.0 (95% CI= 0.7-1.5)]. Consumption of six groups of vegetables and fruits/juices was associated with a 30% decreased risk of lung cancer but showed no clear pattern of dose-response relationship. Subjects classified in the upper 20% of the distribution of intake of total fat as a nutrient index had a 70% increased risk of lung cancer;, the intake of fat showed a statistically significant increasing trend with lung cancer death risk. 0 0

96 Table 30. Risk ratios of lung cancer among nonsmoking CPS II participants by nonTET,,S.,kno,~n risk fa~t0rs' I I I I i | ! Multivariate § Risk Factors RR (95% C.I.) Aie g 6up <50 1.0 50-54 1.8 (I.0-3.0) 55-59 2.9 (1.8-4.7) 60-64 4.4 (2.7-7.0) 65-69 6.1 (3.8-9.9) 70-74 8.2 (5.0-13.3) 75-79 14.4 (8.8-23.9) 80-84 14.6 (8.1-26.6) 85+ 22.4 (I 1.6-43.6) Schooling 12 yrs. + 1.0 <12 yrs. 1.2 (0.9-1.5) Asbestos at work i .0 Never 1.8 (1.1-3.2) Ever Ionizing radiation at work Never 1.0 Ever 1.5 (0.7-3.5) Risk Factors Other occupational exposures to lung carcinogens* None Any Gender Multivariate § RR (95% C.I.) Women 1.0 Men 1.3 ( 1.0-1.6) Whites 1.0 Non-whites 1.5 ( 1. I-2.2) Frequency of consumption of carotenoid containing foods None 1.0 Seldom to 2/week 0.3 (0.1-0.8) 3 week 0.3 (0.1-0.7) >3 week 0.3 (0.1-0.7) p for trend 0.08 Total fat as nutrient intake in quintiles Least 1.0 2 1.2 (0.8-1.6) 3 1.3(0.9-1.8) 4 0.9 (0.6-1.3) Most 1.7 (1.2-2.3) p for trend 0.03 History of chronic lung disease None 1.0 Any of these: 1.0 (0.7-1.5) Tuberculosis 1. I (0.4-2.6) Emphysema 1.8 (0.8-4.2) Asthma 1.7 (0.9-3.6) Chronic bronchitis 1.2 (0.7-2.1) (n=392,226) § Cox regression models included age, gender, 'race', schooling, ETS, frequency of foods containing earotenoids, total fat as a nutrient index, history of chronic lung diseases, and occupational exposure to asbestos. * Self-reported occupational exposure to any of: coal tar, formaldehyde, and chemicals. 0 o~ o~ o~ o o~

I I I 97 I I I I I I I I I I I I I I I 7.3 Main exposure variables 7.3 a. Self-reported exposure to ETS Table 31 shows the deaths from lung cancer among CPS II nonsmokers by any versus none self-reported ETS exposure. There was no indication of an association between self-reported ETS and the risk of lung cancer among nonsmokers when this exposure .variable was treated as dichotomous (i.e., any versus 0 hours of exposure to ETS ). The rate ratio adjusted for the age-gender distribution of person-time was 0.8 (95%CI--'0.6-1.0). The unadjusted (i.e., confounded by age) rate ratio was 0.3. Table 31 displays the lung cancer death rates in persons with no versus any exposure to ETS at home, work or elsewhere. The age-standardized rate ratio for men was 0.8 (95% CI=0.6-1.2) and for women 0.9 (95% CI---0.7-1.3). The age-adjusted Mantel-Haenszel mortality rate ratios were 0.6 (95% CI=0.4-1.0) and 0.9 (95% CI=0.7-1.2) for men and women respectively. The age-gender adjusted Mantel-Haenszel rate Patio was 0.8 (95%CI=0.6-1.0). 7.3.b Dose-response analyses of self-reported ETS Table 32 presents the analysis by tertiles of self-reported hours of exposure to ETS (i.e., 1-2 hours, 3-5 hours and 6+ hours). Panel A of-table 32 summarizes the information on the total number of persons in each category. This part of the table presents the number of lung cancer deaths, person years, and lung cancer death rates, among men, and women, separately and then combined in the last column. Panel B breaks down the previous numbers by five-year age groups. Thus, when the comparison of lung cancer mortality rates was made by duration of daily exposure to ETS between nonsmokers unexposed to ETS (i.e., no self-

98 I reported ETS exposure) and nonsmokers most heavily exposed (i.e., those in the upper tertile or exposed for 6 and more hours to ETS), subjects in this exposure category of ETS had a 20% increased risk of lung cancer, after adjustment for age and gender [RRm-h= 1.2 95% CI=(0.9-1.7)] Comparisons of the lung cancer death rates by terfile of ETS exposure among men and women are presented in Figure 8. Further adjustment of the association between ETS exposure and the risk of lung cancer was then conducted via Cox regression by blocking for age (12 five- year groups) 'race' (whites versus non-whites), schooling (<12 years of education, vs 12+ years), gender, asbestos exposure (ever versus never), and a history of chronic lung disease (any versus none) as dichotmous variables, 3 indicator variables for the intake of foods containing carotenoids (grouping those who had one or more a week into tertiles), and 4 other indicators for total fat as a nutrient index (grouping all subjects by quintiles). This coding of the c~variates is the same used to obtain the estimates presented in table 30. The results of the stratified Cox regression analyses are presented in table 33, and they show that inclusion of the covariates did not materially alter the reported association, once the confounding effect of age was controlled (Cfr. table 32 versus table 33). A multivariate test for dose-response was then conducted using this categorization of self-reported ETS as an ordinal variable, and failed to reject the null hypothesis. Separate analyses were conducted for the number of hours of exposure to ETS at different settings (home, work and other places), using the approach of simple and stratified analysis by age described for the cumulative hours of exposure to ETS. These results are summarized in table 33, along with the multivariate results for all ETS. The findings were the same as for the cumulative measure. I I I I I ! I I I I i I I I I I

Table 31. Lung cancer death rates among CPS II nonsmokers by self-reported ETS (any versus none), 1982-1989 Men Women Level: 0 hours of Any 0 hours of Any ETS ETS ETS ETS Age group Deaths P-Y Rate Deaths P-Y Rate Deaths P-Y Rate Deaths P-Y Rate <50 1 33,932 3 2 87,246 2 3 133,717 2 1 208,117 0 50-54 0 40,625 0 4 92,511 4 9 131,105 7 9 172,103 5 55-59 0 48,610 0 4 95,551 4 7 158,650 4 14 179,550 8 60-64 6 52,560 11 10 78,917 13 15 175,460 9 15 153,614 10 65-69 16 56,440 28 11 53,144 21 19 171,875 11 11 98,310 11 70-74 20 49,773 40 6 26,448 23 28 147,678 19 I I 48,843 23 75-79 11 31,781 35 3 11,025 27 40 105,983 38 4 23,445 17 80-84 15 15,519 97 2 3,803 53 32 59,479 54 3 10,389 29 85+ 5 7,368 68 0 1,273 0 22 35,831 61 3 5,937 51 ..... Tota! 74 336,614 14" 42 449,918 12" 175 1,119,778 10" 71 900,309 10" (n=329,226) *Age-standardized rates to the CPS II population. RR any versus none both men and women (age-gender adjusted)=0.8 (95% CI=0.6-1.0) RR any versus none for men (age adj. for men)=0.6 (95% CI=0.4-1.0) RR any versus none for women (age adj. for women)=0.9 (95% CI=0.7-1.2) LE90~9890~ 1 I N / l 99 l I

'Fable 32. A. (Summary) Lung cancer deaths, nonsmokers and person-years and rates by self-reported ..... ,, ETS category amoug nonsmokers in CPS I1 Men ..... Women Total Exposure Deaths Person- Rate* Deaths Person- Rate* Deaths Person- Rate* Years x10-5 Years x10-5 Years x10-5 All subjecls [ 16 110,688 786,532 16 246 281,538 2,020,081 I I 362 392,226 2,806,613 12 0 Iiours of E'PS 74 48,175 336,614 15 175 157,258 !,119,778 I ! 249 205,433 1,456,392 12 I-2 l louts of ETS 20 36,820 264,812 9 29 55,810 404,565 8 49 92,630 669,378 9 3-5 llours of ETS 8 10,301 74,060 18 I ! 24,255 175,376 9 19 34,556 249,436 I 1 ~...6+ HoursofETS 14 15,392 111,046 .!.7 31 44,215 320,362 12 45 59,607 431,408 13 Table 32". B. Age ~listribution and lu,n.g cancer deat~ rates by UnexpOsed ' Men ......... Unexposed "W6men (0 hours of ETS (0 hours of ETS ,_. , self-reported ETS category Unexposed Subjects (0 hours of ETS exposure) exposure) exposure) Age group Person- Rates Person- Rates Person- Rates in years Deaths years at (%) 10-5 Deaths years at (%) 10-5 Deaths years at (%) 10-5 dsk dsk risk <50 ! 33,932 10.1 3 3 133,717 11.9 2 4 167,648 ! 1.5 2 50-54 0 40,625 12.1 0 9 131,105 I 1.7 7 9 171,730 11.8 5 55-59 0 48,610 14.4 0 7 158,650 ! 4.2 4 7 207,260 14.2 3 60-64 -6 52,560 15.6 I 1 15 175,460 15.7 9 21 228,020 15.7 9 65-69 16 56,444 16.8 28 19 171,875 15.3 I ! 35 228,319 15.7 15 70-74 20 49,774 ! 4.8 40 28 147,678 ! 3.2 19 48 197,452 13.6 24 75-79 11 31,781 9.4 35 40 105,983 9.5 38 51 137,764 9.5 37 80-84 15 15,519 4.6 97 32 59,479 5.3 54 47 74,998 5.1 63 85+ 5 7,370 2.2 68 22 35,831 3.2 61 27 43,200 3.0 62 Total 74 336,614 100.0 ....... m'h age'adj Ri~ '-- ! '0 ' *Age-adjusted to the CPS-II population 15" 175 1,119,778 100.0 11" 249 1,456,391 100.0 12" m-h age-adj RR= i.0 m-h "gender-agd'-adj RR= 1.0 100

l ...... Ex~J0sed Men" (1-2 hours of ETS Table 32. (continued) Exposed Subjects (1-2 hours of ETS exposure) Person- Deaths years at risk 3 142,242 21.2 7 129,456 19.3 7 134,008 20.0 l0 ! 13,806 17.0 7 78,098 11.7 l0 41,397 6.2 4 19,341 2.9 0 7,687 1.1 1. 3,345 0.5 49 669,378 100.0 " ExpoSed Women (1-2 hours of ETS exposure) exposure) Age group Person- Rates Person- Rates in years Deaths years at (%) 10-5 Deaths years at (%) 10-5 risk risk <50 2 47,965 18. I 4 1 94,276 23.3 1 50-54 2 52,918 20.0 4 5 76,538 i 8.9 7 55-59 I 55,079 20.8 2 6 78,929 19.5 8 60-64 5 46,170 17.4 ! ! 5 67,636 16.7 7 65-69 3 33,230 ! 2.5 9 4 44,868 ! I. 1 9 70-74 5 18,087 6.8 28 5 23,309 5.8 21 75-79 2 7,800 2.9 26 2 11,542 2.9 17 80-84 0 2,713 1.0 0 0 4,974 1.2 0 85+ 0 851 0.3 0 1 2,494 0.6 40 Total 20 264,812 100.0 9* 29 404,565 I00.0 8* Rates (%) IO-5 2 5 5 9 9 24 21 0 30 9* Men: m-h age-adj. RR=0.6 (95%CI=0.4-1.0) Women:m-h age-adj. RR=0.8 (95%CI=0.5-1..2) Both: m-h gender-age adj. RR=0.7(95%CI=0.5- ! .0) *Age-adjusted to the CPS-II population 6890z9sgoE I I 101 l

mm m mmm mm mm m mm mm Table 32. (continued) Exposed Men (3-5 hours of ETS exposure) Age group Person- Rates in years Deaths years at (%) 10-5 Deaths risk <50 0 15,754 2 ! .3 0 0 50-54 0 15,635 2 !. 1 0 0 55-59 1 15,840 21.4 6 2 60-64 3 12,593 17.0 24 1 65-69 2 7,985 10.8 25 1 70-74 0 3,840 5.2 0 3 75-79 0 1,651 2.2 0 0 80-84 2 528 0.7 379 2 85+ 0 234 0.3 0 2 Total 8 74,060 100.0 18" 11 Exposed Women Exposed Subjects (3-5 hours of ETS (3-5 hours of ETS exposure) exposure) Person- Rates Person- Rates years at (%) 10-5 Deaths years at (%) 10-5 risk risk 39,517 22.5 0 0 55,271 22.2 0 33,808 19.3 0 0 49,443 19.8 0 34,675 19.8 6 3 50,515 20.3 6 28,857 16.5 3 4 41,450 16.6 I0 18,981 10.8 5 3 26,966 10.8 11 10,302 5.9 29 3 14,143 5.7 21 5,341 3.0 0 0 6,992 2.8 0 2,440 1.4 82 4 2,968 1.2 135 1,455 0.8 137 2 1,689 0.7 118 175,376 100.0 9* 19 249,436 100.0 II* m-h age-adj. RR=I.i (95%CI=0.5-2.3) m-h age-adj. RR=0.7 (95%CI=0.4-1.3) m-h gender-age adj. RR=0.9(95%CI=0.5-i.4) *Age-adjusted to the CPS-II population olzg0gg$90g 102 m~

103 Table 32. (continued) Exposed Men Exposed Women (6+ hours of ETS (6+ hours of ETS exposure) exposure) Age group Person- Rates Person- Rates in years Deaths years at (%) 10-5 Deaths years at (%)- I0-5 risk risk <50 0 23,527 2 ! .2 0 0 74,324 23.2 0 50-54 2 23,958 21.6 8 4 61,754 19.3 6 55-59 2 24,632 22.2 8 6 65,945 20.6 9 60-64 2 20,154 18.1 10 9 57,122 17.8 16 65-69 6 1 ! ,929 10.7 50 6 34,462 10.8 ! 7 70-74 ! 4,521 4.1 22 3 15,232 4.8 20 75-79 1 1,575 1.4 64 2 6,562 2.0 30 80-84 0 563 0.5 0 1 2,975 0.9 34 85+ 0 188 0.2 0 0 1,988 0.6 0 Total 14 111,046 100.0 17" 31 320,362 I00.0 12" Exposed Subjects (6+ hours-of ETS exposure) Person- Deaths years at (%) risk Rates 10-5 0 97,850 22.7 0 6 85,712 19.9 7 8 90,576 21.0 9 I 1 77,276 17.9 14 12 46,390 10.8 26 4 19,752 4.6 20 3 8,137 1.9 37 1 3,538 0.8 28 0 2,176 0.5 0 45 431,408 100.0 13" " m-h age-adj. RR=I.4 (95%CI=0.7-2.5) m-h age-adj. RR=I.2 (95%CI=0.8-!.8) m-h gender-age adj. RR= 1.2(95%CI---0.9-1.7) *Age-adjusted to the CPS-II population I~90~9~90E

I04 CP$ II, 1982-1989 a) 1-2 hours versus 0 hours 20 • Figure 8. Mortality rates from lung cancer among nonsmokers, by tertiles of self-reported ETS exposure and among unexposed, Rate per 100,000 population <50 50- 55- 60- 65- 70- 75- 80- 85+ 54 59 64 69 74 79 84 Age group ~=~ 1-2 hours hours I I I I I I I I I I I

I I I I I b) 3-5 hours versus 0 hours L40 ~ m Rate per 100t/ 80 100,000 50 population 40 2O 0 <~0 50- 55- ~ 65- 7~ 7~- 8~ 85+ 54 59 ~ 59 74 79 84 Age group ~~ 3-5 ho~ ET$ ¢ 0 ho~ c) 6+ hours vers~ 0 hours Rate per 50 I0 ,0 0 / ~ 10 ~ - ~0 5~ 55- ~ 65- 7~ 75- 8~ 85+ ~ 59 ~ 69 74 79 84 Age group ~"~ 6+ hours hours 105

106 None of the rate ratios by increasing amount of hours of self-reported ETS exposure at home, work or elsewhere, displayed in table 33, showed a statistically significant slope of a linear trend using Cox recession analysis. Moreover, there is a consistent pattern of risk deficit for low self-reported ETS exposure categories. Table 33. Cox regression multivariate lung cancer rate ratios for ETS exposure, cumulative and for specific sites, by ender, among CPS II nonsmoking participants, 1982-1989. Men Women Total Hours Multivariate Multivariate Multivariate of exposure Rate Rado§ Rate Ratio§ Rate Ratio§§ source_ (95 (95 (95 All ETS 0 1.0 1.0 1.0 1-2 0.6 (0.4-1.1) 0.8 (0.6-1.3) 0.7 (0.5-1.0) 3-5 1.0 (0.4-2.0) 0.7 (0~4-1.3) 0.8 (0.5-1.3) 6 + hours 1.3 (0.7-2.4) 1.1 (0.8-1.7) 1.2 (0.8-1.7) Home 0 1.0 1.0 1.0 1-3 0.7 (0.2-2.0) 0.4 (0.2-1.0) 0.5 (0.2-1.0) 4-5 0.0 (0.0-NC) 0.7 (0.3-1.7) 0.6 (0.2-1.4) 6 + hours 0.5 (0.1-3.9) 1.3 (0.8-2.1) 1.2 (0.7-1.9) Work 0 1.0 1.0 1.0 1 0.7 (0.3-t.6) 0.9 (0.5-t.9) 0.8 (0.5-I.4) 2-6 1.0 (0.5-2.1) 1.1 (0.6-2.1) 1.1 (0.6-1.7) 7+ hours 1.8 (0.9-3.6) 1.0 (0.5-1.8) 1.2 (0.8-2.0) Other places 0 I 2 3 + hours 1.0 1.0 1.0 0.5 (0.3-1.0) 1.0 (0.6-1.7) 0.7 (0.5-1.1) 0.7 (0.2-2.2) 0.8 (0.3-2.2) 0.7 (0.4-1.6) I. 1 (0.4-3.0) 1.1 (0.5-2.5) 1.I (0.6-2.0) § Adjusted for age, race, education, intake of carotenoid-containing foods, total fat as a nutrient index, occupational exposure to asbestos and history of chronic lung diseuse. §§ Additionally adjusted for gender. 0 0 ! I I I

107 I I I I I I I I I I I I I I I 7.3.c. Spousal ETS The relationship between environmental tobacco smoke exposure from spousal smoking and lung cancer mortality among nonsmokers was then assessed. Exposure to ETS based on exposure by a nonsmoking spouse to tobacco smoke from a smoking spouse was further defined based on whether the spouse was a nonsmoker or ever smoked, if the spouse was a current or former smoker (i.e., if the nonsmoker was ever, current or formerly exposed to ETS from the smoking habits of spouse). Comparisons of lung cancer death rates by ETS exposure from ever versus never smoking spouses showed no indication of an increased risk: the Mantel-Haenszel age-gender adjusted rate ratios were 1.0 (95% CI=0.7-1.4) for all nonsmoking spouses, and 0.9 (95% CI--0.7-1.5) for husbands and 1.1 (95% CI=0.8-1.5) for nonsmoking wives, respectively. Table 34 shows lung cancer mortality associated with exposure and no exposure to ETS from current smoking spouses for men and women, separately, and by the nine five-year age groups. The fu,'st four columns of table 34 present the data for nonsmokers married to current smokers of any type of tobacco product; the last four present the corresponding data for nonsmokers married to nonsmokers. Examination of lung cancer death rates presented as person-years for spouses, of either gender, shown in Table 34, are not appreciably different whether they were exposed or unexposed to ETS from a current smoking spouse. For example, the death rate columns for these ETS-exposed spouses show no appreciable differences across age groups among men, though a slightly greater mortality was observed among older women, as is graphically presented in figure 9. For nonsmoking spouses married to current smokers of any type of tobacco the RR was slightly above unity [ RR(m-h)=l.2 (95% CI--0.8-1.9)] for men and women combined, after adjusting for the age and gender distribution. For men, marriage to a current smoker was not associated with an increased risk [R_R(m-

108 I h)=0.9 95% CI-0.4-1.9)]. The corresponding age-adjusted estimate for nonsmoking women married to a current smoker was 1.3 (95% CI=0.8-1.9). Nonsmokers married to former smokers had no increased risk of lung cancer: the age-adjusted estimate for men and women combined was 1.0 (95% CI=0.7- 1.3). This was true both for men and women in our study, with age-adjusted rate ratios of 0.9 (95% CI---0.5-1.6), and 1.0 (95% CI=0.7-I.5), respectively. Most of smoking spouses smoked cigarettes. The relationships described above regarding current smoking spouses were true also for current cigarette smoking spouses: men married to current cigarette smoking women had an age-adjusted rate ratio of 0.9 (95%CI=0.3-1.9), whereas women married to current cigarette smokers had an age-adjusted rate ratio of 1.2 (95%CI=0.7-2.0). The age-gender adjusted RR was i. 1 (95% "CI=0.7-1.7). I I I I I ! I I I I I I I I

I I I I- I I I i I i I I I I I I I I I09 1aisle J4. Age-specific tung cancer rates among nonsmokers by smoking status (current §-any type of tobacco vs. life-long nonsmokers) of the spouses, CPS II, 1982-1989. a. Men " Deafl~s PY among De.~tbs ' PY ~nong ...... Age Group among married to (%) Rate among roan'led to (%) married to curr~nt 105 married to never cun~nt smokers never smokers smokers smokers <50 0 9,133 14 0 1 64,314 12 2 50-54 i 12,593 20 8 1 88,297 17 1 55-59 0 13,568 21 0 4 97,670 19 4 60-64 4 11,509 18 35 12 91,288 17 13 65-69 2 8,760 14 23 23 78,696 15 29 70-74 0 5,031 8 0 18 55,503 11 32 75-79 0 2,180 3 0 8 30,941 6 26 80-84 0 701 1 0 9 13,672 3 66 85+ 0 177 0 0 3 5,083 1 59 Total 7 63,652 100 10" 79 525,464 100 14" § Excludes current smoking spouses with/acomplete smoking data. Age adjusted MH RR~3.9 (95% CI=0.3-1.9). *Age-adjusted to the CPS II population b. Women Deaths PY among Deaths PY among Age Group among married to (~) Ram among married to (%) Rate marriedto curr~nt 105 married to never 105 current smokers never smokers smokers smokers <50 0 77,591 21 0 2 108,378 21 2 50-54 4 72,473 19 6 6 94,967 18 6 55-59 7 76,798 20 9 8 94,598 18 8 60-64 14 66,410 18 21 8 85,095 16 9 65-69 3 45,069 12 7 7 66,320 13 11 70-74 7 24,182 6 29 13 41,303 8 31 75-79 5 10,575 3 47 6 20,762 4 29 80-84 3 3,249 i 92 1 7,534 I 13 85+ 0 727 0 0 0 2,105 0 0 Total 43 377,074 100 15" 51 521,062 100 11" '~'Excia~des current smoking spouses with incomplete cigarette smoking data Age adjusted MH RR"-I.3 (95% CI=0.8-1.9). *Age-adjusted to the CPS II population

Figure 9. a) Rates of lung cancer among nonsmoking men by smoking status of their wives, CPS 11 1982-1989 35 Rate per 2~0 100,000 population <50 50-54 55-59 60-64 65-69 70-74 75-79 80+ Age group --'~ Wife Currently --X-- Wife never Smoked smoked Figure 9. b) Rates of lung cancer among nonsmoking women by smoking status of their husbands, CPS 11 1982-1989 80 Rate per population 0 -~m"~~ I I I - I I +I I <50 50-54 55-59 ~ 65-69 70-74 75-79 813+ Age group Husband Currently --X-- Husband Smoked Never S rooked I I I I I ! ! I I I

111 I I I I I I I I I I I I i I Table 35 presents lung cancer deaths, person-years and lung cancer death rates among nonsmoking women exposed to ETS from pipe/cigar current smoking of their spouses, compared to those among women married to nonsmokers. Death rates for lung cancer among nonsmoking women married to current pipe/cigar smokers increased more rapidly after age 70, than in those married to nonsmoking husbands. However, the small numbers of deaths make age specific estimates unstable. Nevertheless, it seems that exposure to ETS from spousal pipe/cigar has a weak statistically insignificant effect on the risk of lung cancer. More details on the types of smoking habits of spouses of nonsmoking subjects and their risk of lung cancer is displayed in table 36, along with a summary of the results of spousal ETS analysis described above. The ftrst row of table 36 presents the number of lung cancer deaths and person-years among nonsmokers in the entire cohort. The second row presents those numbers for men and women married to nonsmokers, as the referent category for analyses of the effect of ETS from spousal smoking. Thereafter those numbers for each category of smoking spouses are given along with age and age-gender adjusted Mantel- Haenszel rate ratios, as well as multivariate rate ratios controlling for all relevant covariatcs included in analyses of self-reported ETS. Nonsmoking wives married to current cigarette, pipe and cigar smokers showed an elevated risk of lung cancer. Nonsmokers married to former smokers, except for cigar/pipe smoking spouses, did not have an increased risk of lung cancer.

t12 Table 35. Age-specific lung cancer rates among nonsmoking women by cigar/pipe smoking status (current vs. life-time nonsmokers) of their husbands, CPS II, 1982-1989. Deaths PY Deaths PY Age among among (%) Rate among among (%) Rate Group married married 105 married married 105 tO tO tO tO current current never never pipe/cigar smokers smokers smokers smokers <50 0 24,967 17 0 2 108,378 50-54 0 25,615 18 0 6 94,967 55-59 0 28,490 20 0 8 94,598 60-64 7 26,281 18 27 8 85,095 65-69 2 I8,945 13 11 7 66,320 70-74 5 11,096 8 45 13 41,303 75-79 3 5,526 4 54 6 20,762 80-84 1 1,918 1 52 1 7,534 85+ 0 494 0 0 0 2,105 21 2 18 6 18 8 I6 9 13 I1 8 31 4 29 1 13 0 0 Total 18 143,341 I00 15" 51 521,062 100 11" ..... ~gg~djusted Mantel-Haenszel RR= 1.3 (95% CI'--2-0.7-2.2). *Age-adjusted to the CPS rr population This relationship between current smoking of spouses and the risk of lung cancer did not change when 'race', schooling, history of lung disease, frequency of consumption of foods containing carotenoids, and occupational asbestos exposure were allowed into the Cox regression model, along with age, as shown in table 36, suggesting that there was no confounding by these covariates. 0 I I I I I I I I I I i I

i I I- I I I I I I I I I I I I I I lahle 36. A~soctatton Oetween smoking status~' type ot smoking o3 spouses nonsmoking CPS II sub,iects, and lung cancer risk. Husbands Wives Total Spouse smoked tobacco Deaths Person-Years Deaths Person-Years Deaths Person-Years Total 10'1 '~ '7i9,044' ' i64 Never 79 525,464 5 [ RRm-h* 1.0 RRCox§ 1.0 Ever ** (any 22 193,580 113 type) 0.9 (0.5-1.5) RRm-h* 0.9 (0.6-1.4) RRCox§ Current (any 8 67,689 44 385,676 type) 0.9 (0.3-1.9) 1.3 (0.8-1.9) RRm-h* 1.0 (0.5-2.0) 1.3 (0.8-1.9) RRCox§ Former (any 13 117,462 68 614,96 i type) 0.9 (0.5-1.6) 1.0 (0.7-1.5) RRm-h* I. I (0.6-2.8) I. I (0.7-1.6) RgCox§ Ever 22 193,580 74 709,944 Cigarettes R~m-h* 0.9 (0.5-1.5) 1.0 (0.7-1.5) RgCox§ 1.0 (0.5-2.0) I. I (0.8-1.6) unclass, ever I 8,429 I 23,236 smoker Current 7 63,652 25 233,743 cigarettes incomplete I 4,037 I 8,592 RRm-h* 0.9 (0.4-1.9) 1.3 (0.8-1.9) RRCox§ 1.0 (0.5-2.0) 1.3 (0.8-2.0) For~er I0 I03,945 44 414,146 cigarettes incomplete 3 13,517 3 30,227 Rgm-h* 0.9 (0.5-1.6) 1.0 (0.6-1.5) RRCox§ I. I (0.6-2.8) 1.2 (0.8-1.8) E vet 39 313,929 Cigar/Pipes m-h* 1.2 (0.8-1.8) Cox§ I. I (0.8-1.6) Current 18 143,341 m-h* I..3 (0.7-2.2) Cox 1.5 (0.8-2.9) Former 21 170,588 m-h* I. I (0.7-1.9) cox§ 1.3 (0.6-2.8) (.=3 i~, I0~) *M-a: age ~just~ using Man~l-~iae~zel 1,544,935 265 2,263,979 521,062 130 1,046,526 1.0 1.0 1.0 1.0 1,023,873 135 1,217,453 L~ (0.8-L5) l.t (0.8-t.5) 1.1 (0.8-1.6) 1.0 (0.8-1.4) 52 453,365 1.2 (0.8-1.9) 1.2 (0.8-1.8) 81 732,423 t.O (0.7-1.3) 1.0 (0.% 1.4) 96 903,524 1. I (0.7-1.4) 1.0 (0.7-t.8) 2 31,665 32 297,395 2 12,629 1. l (0.7-1.5) 1.2 (0.8-1.9) 54 518,091 6 39 43,744 0.9 (0.7-1.3) 1. I (0.7-1.9) 313,929 § Cox: multivariate regression using the proportional hazard model to control for age, gender (for estimates listed in last column), 'race' and schooling, asbestos, history of chronic lung disease, consumption of foods containing carotenoids, and total fat as nutrient index. **Includes 2 ever smokers with unelassifiable smoking (i.e., former or current cigarette smokers).

7.3.d. Relationship between lung cancer death and ETS exposure by amount, duration, and both The dose-response relationship between lung cancer death and ETS exposure was assessed in a variety of ways. We f'trst examined amount of ETS exposure by measuring the number of packs of cigarettes smoked by current or former cigarette smoking spouses. We also examined the number of years nonsmokers were exposed to ETS from the smoking of their spouses. Finally, we examined both amount and duration using pack-years as a measure of cumulative ETS exposure. For these three analyses, we included data about subjects whose spouses were ever cigarette smokers, as the ETS-exposed group, and subjects whose spouses were never smokers, as the referent group. Table 37 shows lung cancer deaths per person-years for ETS-exposed spouses and multivariate rate ratios by packs of cigarettes smoked by their spouses compared with the referent group of non ETS-exposed spouses. These estimates are presenied by gender and then combined for subjects exposed to a spouse who was either a current or a former smoker. The upper panel of the table presents the data to compare the rates among nonsmokers married to current smoking spouses, and the lower for former smoking spouses; rate ratios are presented by categories of amount of smoking grouped by packs of cigarettes. The risk of lung cancer among men married to current cigarette smokers only increased among those who smoked less than one pack [P,.R=2.0 (95%CI--0.9- 4.4)] but the rate ratios decreased for the categories of heaviest cigarette smoking. Among women there was also an increased risk for those exposed to ETS from less than one pack of cigarette smoking, and declined among those married to current heavy smokers. No consistent linear trend with amount currently smoked by spouses was found. I I I I 0 O~

m m Table 37. Lung Cancer Adjusted Rate Ratios (95% CI) among nonsmoking spouses according, to the amount of cigarette smoked by spouses*, CPS II, 1982-1989. Exposure Husbands Wives All Nonsmokers Packs of cigarettes: Deaths/PY multivariate RR Deaths/PY multivariate RR multivariate RR by current smokers (95% CI) (95% CI) (95% CI) Nonsmokers 79/525,464 1.0 51/521,062 1.0 1.0 <I pack 7/28,923 2.0 8/61,820 !.4 i.6 (0.94.4) (0.6-2.9) (0.9-2.7) 1 - i.9 packs 0/29,756 0 15/126,087 i.4 1.0 (0-NC) (0.8-2.6) (0.6-1.8) 2+ packs 0/4.973 0 2/45,836 0.6 0.5 (0-NC) (0.1-2.3) (0.1-2.0) p test for trend 0.26 0.66 0.90 by former smokers Deaths/PY multivadate RR Deaths/PY multivariate RR multivariate RR (95% CI) (95% CI) (95% CI) Nonsmokers 79/525,464 1.0 5 !/521,062 ! .0 1.0 < ! pack 5/64,258 0.6 10/I08,365 0.8 0.8 (0.3-1.6) (0.5:1.8) (0.5-1.4) 1 - i.9 packs 4/32,191 1.0 20/213,304 0.8 0.9 (0.3-2.8) (0.5-1.4) (0.6- !.4) 2+ packs 1/7,495 1.2 14/92,462 1.5 1.5 (0.2-1.9) (0.8-2.7) (0.8-2.6) p test for trend 0.74 0.58 0.72 a '--258,499) ~Only cigarette smokers (current and former) with complete data. Cox regressio.n model stratified for age, gender, 'race', schooling, total intake of foods containing carotenoids, total fat ntake, occupational exposure to asbestos and history of chronic lung disease. 8RgOE9890E m n m m m m m m m mm m m 115 mm ~m

I16 I I I I ! A possible problem with the aforementioned analysis is that some ETS-exposed spouses may have been previously married to someone who was not a smoker. Thus, it was decided to re-examine the realtionship between lung cancer mortality and ETS exposure by packs of cigarrettes smoked by spouses by restricting to an analysis of spouses married only once in their lifetime. Table 38 presents limg cancer deaths, person years and multvariate rate ratios by amount of cigarettes smoked by current or former smokers as was presented above for the full data set. The analysis is restricted to the 148,402 spouses married once and who had complete information on age at marriage. The same group of nonsmokers unexposed to ETS is the referent. Unlike in the previous analysis of the fulI data set of nonsmokers married to cigarette smokers, in this subset of spouses married once in their life-time, among nonsmokers married to former smokers, there is a slightly increased risk of lung eancer for those married to former smokers who smoked 2+ packs of cigarettes. However, there is no statistically significant trend: the p value of multivariate Cox regression analyses of the packs of cigarettes smoked by former smokers were 0.28 for men -decreasing trend, and 0.29 for women whose risks showed an increasing, but inconsistent trend, and 0.6 for both men and women. 0 O~ O~ 0 O~ I I I / I I

[___ l Table 38. Lung Cancer Adjusted Rate Ratios (95% CI) among nonsmoking spouses according to the amount of cigarette smoked by spouses* if married once and with data on age at marriage, CPS II, 1982-1989. Exposure Husbands Wives All Nonsmokers Packs of cigarettes: Deaths/PY multivariate RR Deaths/PY multivariate RR multivariate RR b~, current smokers (95% CI) (95% CI) (95% CI) Nonsmokers 46/314,944 1.0 30/31 ! ,333 i .0 i .0 < 1 pack 5/14,310 3.0 5/32,524 1.7 2.1 (1. 1-7.9) (0.7-4.4) ( !. 1-4.1 ) i - !.9 packs 0/15,054 0.0 10/69,060 1.6 !.2 (0.0-NC) (0.8-3.4) (0.6-2.3) 2+ packs 0/2,308 0.0 2/24,900 0.9 0.8 .... (0.0-NC) (0.2-3.9) (0..2-3.5) p test for trend 0.6 0.34 0.55 by former smokers Deaths/PY multivariate RR Deaths/PY multivariate RR multivariate RR (95% CI) (95% CI) (95% CI) Nonsmokers 46/314,944 ! .0 30/311,333 i .0 1.0 < I pack 1/34,042 0.2 4/61,677 0.6 0.5 (0.0-117) (0.2-1.8) (0.2-1.2) ! - !.9 packs 0/15,915 0,0 12/120,585 0.8 0.7 (O.O-NC) (0.4- 1.7) (0.3-1.4) 2+ packs i/3,559 2.8 i !/49,304 2.0 1.9 (0.4-21.6) (1.0-4.0) (1.0-3.7) p test for trend 0.28 0.29 0.6 (n=148,204) "" * Analyses restricted to nonsmoking spouses married to nonsmoking spouses and those married to cigarette smokers (and not other type of tobacco), with complete smoking data, married once at the time of interview, and with valid data on age at first marriage. § Cox regression model stratified for age, gender, 'race', schooling, total intake of foods containing earotenoids, total fat as nutrient index, occupational exposure to asbestos and histozy of chronic.lung disease. NC=not calculable l 1 I i I l l I l I I !!7 ml

118 The hypothesis of this study was submitted to a more severe test to take into account the time these spouses married once in their life-time spent together (i.e., whether or not these nonsmokers were exposed to ETS from the smoking habits of their spouses). The relationship between lung c;incer mortality and ETS exposure by duration was examined. To conduct these analyses, it was necessary to estimate the number of years nonsmokers were exposed to ETS from spousal cigarette smoking. For this variable, the referent groups represented spouses who were not exposed, either because thay were married to nonsmokers or to former smokers who quit smoking before marriage (i.e., in doing so, those nonsmokers were never exposed to the tobacco smoke of their spouses). This resulted in reclassifying from the exposed categories 4 percent of the person-time, and 1 death (0.8 percent) in this analytic cohort, to the unexposed category. Therefore, the specificity of classification of exposure to ETS was increased. Table 39 shows deaths per person-years for ETS- exposed spouses by duration, accounting for the eight covariates presented in table 30. Distribution of time in marriage are gender-specific. For estimates of the RR for both men and women, we used the combined distribution of time in marriage to smokers. Nonsmoking men married to smokers for 15 or more years did not have an increased risk of lung cancer, although there were fewer persons in these categories. Nonsmokers married up to 15 years to smoking wives had a 30 percent increased risk. We found no evidence that the rate ratios increased among nonsmoking men by time in marriage with smokers. However, rate ratios increased among women as the time in marriage from one to seventeen years to smokers, and then decreased slightly, in an erratic trend shown in table 39. | I I I I I ! I I I I I !

i i i Table 39. Lung Cancer Adjusted Rate Ratios (95% CI) among nonsmoking spouses according to time in marriage with current cigarette smoking spouses*, CPS II, 1982-1989. Hd~bafids Wives Both" Years married Deaths/PY mul[ivariate Years ""' ' Deaths/PY multivariate Years ..... "multivariate to smoker RR married to RR married to RR (95% CI) smoker (95% CI) smoker (95% CI) 0 years 46/329,905 1.0 0 years 30/334,946 1.0 0 years 1.0 (Nonsmokers and (Nonsmokers (Nonsmokers quittes before and quitters and quitters marriage) before marriage) belbre marriage) 1-15 1/22,101 0.4 1-17 13/107,681 1.5 1-17 1.2 (0.0-3.1) (0.8-3.0) (0.6-2.2) 1/29,918 1.2 14/112,761 1.3 18-29 i .2 (0.0-3.7) (0.7-2.6) (0.7-2.2) 5/18,208 0.7 ! 7/114,002 1.2 30+ 1.0 (0.2-2.7) (0.6-2.2) (0.6- !.8) 16-26 18-29 27+ 30+ test for trend 0.76 test for trend 0.49 test for trend 0.72 (n=148,204) * Analyses restricted to nonsmoking spouses married to nonsmoking spouses and those married to cigarette smokers (and not other type of tobacco), with complete smoking data, married once at the time of interview, and with valid data on age at first marriage. § Cox regression model stratified for age, gender, 'race', schooling, total intake of foods containing carotenoids, total fat as nutrient index, occupational exposure t.o asbestos and history of chronic lung disease. LS9OE9EgoE

120 Finally, the relationship between lung cancer deaths and ETS exposure was examined by both amount and duration. Pack-years, the exposure variable for this analysis, was created by multiplying the packs of cigarettes (i.e., amount) by the number of years of exposure (i.e., duration). For example 20 pack-years could have been reached during marriage for 20 years with a smoker who smoked one pack of cigarettes daily. This variable represents cumulative exposure to ETS over time. As mentioned above for time in marriage, for estimates of the RR for both men and women, we used the combined distribution of pack-years of smoking spousal. Table 40 presents lung cancer deaths, person-years, and rate ratios among nonsmoking men, women and then both men and women, by pack-years according to the quintiles of the distribution of pack-years of smoking of the spouses during marriage with further adjustment for the same confounders in table 30. Nonsmoking husbands were exposed to considerably less ETS from spousal smoking than nonsmoking wives. As was shown before fewer nonsmoking men fell into any of the categories of heavy spousal ETS from cigarette smoking (i.e., 15+ pack years), whereas, 32 percent of the nonsmoking women experienced such exposure and were evenly divided across the categories of pack-years of cigarette smoking of their cigarette smoking husbands. The multivariate rate ratios of lung cancer among nonsmoking men increased by cumulative exposure to ETS up to 22 pack-years of cigarette smoking, and then decreased. Thus no consistency in the variation of lung cancer risk and this measure of long-term ETS exposure was found among nonsmoking men. However, among women, the rate ratios increased consistenly by pack-years of cigarette smoking of theh" husbands, from 1.1 among slightly ETS exposed women, to 1. i among women exposed from 17 to 35 pack-years, and then roughly reached a 50% increased risk for women exposed from 36 pack-years and more. The associated p value for the multivariate test of linear trend was 0.14, thus failing to reject the null hypothesis of nolinear trend. r~ o 0~ I I I I I | I i I I I l I

121 | I- I I I I I I i I I I I I I I Pack-years of cigarette smoking during marriage, was not statistically significant associated with increasing risk of lung cancer of both nonsmoking husbands and wives (p=0.54) (Table 4-0).

Pack-years Table 40. Lung Cancer Adjusted Rate Ratios (95% CI) among nonsmoking spouses according to pack-Tears of spousal cigarette smoking, CPS H, 1982-1989. Husbands Wives Both Dcaths/PY multivaJ-iate'RR " Deaths/PY multivariate RR multivariate RR 0 46/329,905 ! -8 1/24,018 9-22 2/23.438 23+ 2/23,862 (95% CI) Pack-years (95% CI) (95% CI) 1.0 0 301334,946 ! .0 1.0 (0.1-2.9) (0.5-2.2) (0.6- 1.9) !.4 17-35 16/113,119 1.3 !.2 (0.5-4.2) (0.7-2.5) ~0.7-2. I) 0.5 36+ 18/IO9,0o6 1.5 I. ! (0, I-2,2) (0.8-2.8) (0.6- !.9) test for trend 0.54 test for trend p=0.14 p=0.54 (n= 148,204) * Analyses restricted to nonsmoking spouses married to nonsmoking spouses and those married to cigarette smokers (and not other type of tobacco), with complete smoking data, married once at the time of interview, and with valid data on age at first marriage. § Cox regression model stratified for age, gender, 'race', schooling, total intake of foods containing earotenoids, total fat as nutrient index, occupational exposure to asbestos and history of chronic lung disease. 122 0990~9~90~ Ill -| Ic- | II~ II I I-"| | | |

i I I 123 I I I I I I I I I I I I I I 7.4 Joint effects of ETS and asbestos exposure Further analyses were conducted to describe the effect of ETS among those subjects exposed to asbestos. Occupational exposure to asbestos was reported by only 2.5 percent of CPS II participants. As shown in Table 2I, asbestos exposure was reported three times more frequently by men than women. Using the CPS II cohort for analyses of self-reported ETS, we contrasted lung cancer death rates of grouping subjects by tertiles of self-reported ETS exposure and by ever or never exposed to asbestos. Nonsmokers heavily exposed to ETS ('e_6 hours) in 1982, and who had ever been exposed to asbestos at work, experienced a higher risk of lung cancer than expected if the effects of ETS and asbestos were independent. Table 41 shows the results of these analysis. The formal test for interaction in the multiplicative scale using the Cox regression model with both asbestos and ETS exposure variables (reduced model), controlling for age, schooling, gender, 'race', consumption of foods containing earotenoids, total fat as nutrient index, and history of lung disease, yielded a -2 In likelihood of 4125.88, and that with asbestos and ETS and the three interaction terms of asbestos and tertiles of ETS exposure (full model) was 4121.002, for a LRz3~,2=4.878 with an associated p value of 0.18. Nonsmoking men and women who reported 6 or more hours of exposure to ETS, and ever being exposed to asbestos had four times the risk of lung cancer [multivariate RR=4.5 (95%CI=0.4-48.7)] compared to those of nonsmoking CPS II participants who had neither of those environmental exposures. The multivariate association with asbestos alone was RR=I.5 (95%CI----0.7-3.2). I~) 0 0-~ O' O~

I I Table 41. Rate ratios (95% CI) for lung cancer among CPS II nons]noklng men and women according to exposure to ETS (cumulative at home, work, and elsewhere) and occupational exposure to asbestos. Exposure to ETS +6 hours 3-5 hours !-2 hours 0 hours Deaths Person-Years Deaths Person-Years Deaths Person-Years Person-Years at at risk at risk at risk Deaths risk Asbestos Yes 5 14,954 0 7,922 2 22,250 7 Rate* 33 x 10-5 0 11 x 10-5 24,436 16 x 10-5 RR 4.5 0 0.9 1.5 Cox§§ (0.4-48.7) (0.1-11.1) (0.7-3.2) Asbestos No 40 416,453 19 241,513 47 647,134 242 !,431,956 Rate* 13x10-5 llxl0-5 9x10-5 !1 x 10-5 RR Cox§ !. 1 0.8 0.8 1.0 (0.8-1.6) (0.5-1.4) (0.5-1.0) =Age adjusted to tile distribution of the CPS 11 population ~ Cox regression model stratified for age, gender, 'race', schooling, history of chronic lung disease, frequency of consumption of foods containing carotenoids, and total fat intake. ~990Z9~90~ .I 124 I

125 I I I I I I I I I I I I I I 7.5 Model Specification Proportional hazards modeling was the main analytic tool used in this study. Therefore, a valid question to ask is whether the proportional hazard assumption held. Univariate survival curves using Kaplan-Meier estimates for age, gender, • schooling, 'race', consumption of foods containing carotenois, and total fat, history of chronic lung disease, and occupational exposure to asbestos, all followed a pattern of parallel curves by follow-up time in CPS II. Since most analyses on ETS (either self-reported exposure or from spousal smoking) were. conducted while blocking for the covariates, we present univadate Kaplan-Meier estimates of survival for the main exposure variables themselves, displayed in figure 10.

126 I Figure 10. Log I-log(S)] curves for grouped data analyses of A. self-reported ETS Ll~(,.L~f(ka'vlvtl }t~lll~)| |i~lll|is -I| * A=unexposed, B=1-2 hours, C=3-5 hours, and D= 6+ hours of exposure to ETS. I I I I I I I I i I I

I I I 127 I I I I I I I I I I I I I I Figure 10 B. ETS from pack-years of spousal smoking L 'i | -I0 ' =1.I , 1 t~U.~UP Tile k~J LICA A---O, B=<7 pack-years, C=7-14 pack-years, and D= 15+ pack-years.

128 I We also conducted Poisson regTession analyses, an alternative choice of the Cox regression model. RR estimates from the Poisson model for self-reported ETS (upper tertile > 6 hours of ETS) and current spousal ETS from cigarette smokers were 1.2 (95% CI= 0.8-1.6) and 1.2 (95% CI----0.9-1.8), respectively. Thus, the general results from Poisson regression modeling, closely agree with those presented using the Cox regression model. 7.5 Leading causes of death in the cohort During the same period of follow-up among the 314, 108 nonsmoking participants in the the spousal ETS analytic cohort, there were 12,792 other deaths. Coronary heart disease was the leading cause of death in this g'roup, with 3,742 deaths (29.2 percent). The major causes of death according to ICD-9 codes are displayed in table 42. Table 42. Number of deaths from major smoking-related c__auses__a_m_0_ng nonsm0king spouses in the CPS II, 198.2-1989. Causes of death (ICD-9) Deaths % Ischemic heart disease (410-414) Stroke (430-438) Upper aerodigestive cancer -mouth, pharynx, larynx, and esophagus (140-150, 161) Other cancers (140-209) Lung cancer (162) Duodenal or gastric ulcer (531-534) Cirrhosis and alcoholism (57 I, 291,303) Hypertensive heart disease (401-405) Injuries ('E810-E988) Other medical causes (000-799) All causes 3,742 29.2 724 5.6 36 0.3 909 7.1 265 2.1 25 0.2 116 0.9 120 0.9 569 4.4 6,286 49. i 12,792 100.0 I I I I I I I I I I I i I

129 I I" I I I I I I I I I I I I I I Chapter 8: Discussion and Conclusions 8.1 Consistency Since t98 t, when the first study that examined the relationsbAp between ETS and lung cancer death was published (I-Iirayama, 1981), 35 other studies that have examined this same relationship have beech published (Appendix A and Table 2). Of these 36 studies, four are cohort studies and 32 ease-control. It is known that in case-control studies, in which the "information most times comes from the subject of proxy respondents after disease onset, knowledge of the disease could affect exposure data" (i.e., introducing a recall bias) (Rothman 1986). Cohort studies are less subject to recall bias and therefore lend themselves more than case-control studies to making inferences about cause and effect. Thus, although many published studies are available, only a few can be considered to have assessed the relationship between ETS and lung cancer risk in such a way that the measurement of ETS exposure preceds the occurrence of lung cancer. Of those four cohort studies on ETS and lung cancer, one included eight lung cancer cases (Butler 1988), another had nine (I-Iole t989), a third had 153 (Garfinkel 1981), and the largest had 174 lung cancer deaths (I-Iirayama 1981). Our study is the largest cohort study to assess the relationship between ETS and lung cancer death. Therefore, in this paper we report findings from the largest cohort study that are consistent with aggregated evidence that supports the existence of a relationship between cumulative ETS exposure and the risk of lung cancer among nonsmokers. This study makes use of a measure of exposure that combines duration and amount of exposure to ETS that had not been used before in previous cohort studies about the effect of ETS on lung cancer risk. This cumulative exposure to ETS, which is referred to as ETS exposure from pack-years of cigarette smoking of the spouse (Fontham 1991), attempts to estimate ETS long-term exposure. Because 90% of smokers smoke at home (1988 NHIS-OH, Table 1), spouses married to smokers are likely to be exposed to ETS in the home. Our measure of exposure reflects intensity and duration of exoosure to ETS during marriage, and may provide a more adequate measure of long-term ETS exposure. Therefore, this measure of exposure enabled us I

130 to estimate lung cancer risks a~bociated with increasingly greater ET3 exposure with regard to duration and amount. For example, in this study we found increasing lung cancer risks with increasing ETS exposure, with a 50% increased risk, although not statistically signficant, for the most exposed group versus those who were not exposed. In this study, we also found that this not statistically signficiant increased lung cancer risks associated with ETS exposure remained even after we adjusted for the effects of potentially confounding variables by means of Cox proportional hazards modeling. Most previously published studies that had examined the relationship between ETS exposure and lung cancer risk had not accounted for the effects of most known potentially confounding variables included in our models. Thus, questions had been raised about the possibility of spurious findings in past studies (Mantel 1992). In our study, we controlled for the effects of age, gender, socioeconomic status, race/ethnicity, fruit and vegetable intake, fat intake, occupational exposure to asbestos, and a history of chronic lung disease, and we still found that ETS exposure from pack- years of spousal smoking increased the risk of lung cancer. Therefore, our findings support the notion that the observed relationship is not the result of known confounding variables. All cohort studies on this issue have been based on lung cancer diagnosis from death certificates. As previously reported for lung cancer in the US, this approach provides a valid diagnostic tool for epidemiologic research (Percy 198 I). None of the previous studies verified their death certificate diagnoses with histopathologic data. Some have reviewed hospital records, and in one large case-control study histopathological slides were reviewed (Fontham 199 l). In our study, we verified death certificate diagnoses with cancer registry diagnoses on a 10 percent sample of lung cancer deaths (i.e., those of residents of SEER cancer registries areas). Most SEER cancer registry diagnoses (92%) are histopathologically confirmed (NCI-SEER t989). The proportion of the study subjects who died from lung cancer and resided in SEER cancer registries' areas, who were histologically confirmed was 86.2 percent. Seventy percent of all lung cancer deaths were adenocarcinomas. Thus, cases in our study are likely to have been primary lung cancer, and most were adenocarcinomas. ! I I l l I I I ,I I ! I '1 I ~0 0 (

131 I I" I I I l I I I I I I I I I I Adenocarcinomas are the specific histological type of lung cancer seen most often among nonsmokers. Although the information on specific histologic types was limited in our study, based upon the estimate of seventy percent of adenocarcinomas among the lung cancer deaths of nonsmokers, our findings of this study lend support to the hypothesis that a richer composition of SS in volatile carcinogen components more likely to reach the periphery of the lung would actually be responsible for the higher proportion of adenocareinomas among nonsmokers (Wynder 1983, Fontham 1991). Our findings on the association between ETS exposure from spousal smoking-and the risk of lung cancer agree with the combined estimate from 36 published studies, reporting a 20% increased risk of lung cancer among nonsmokers associated with this measure of exposure to ETS. In 1981 Garfinkel published the results of the second large prospective cohort study sponsored by the American Cancer Society, the Cancer Prevention Study I. This study.comprised a cohort of 1,078,894 men and women followed from 1960 to 1972. The CPS I analyses based on 153 Iung cancer deaths among nonsmoking women found a 20% percent increased risk of lung cancer, although this elevated risk was not statistically significant (95% CI=0.9-1.4) (Garfinkel 1981). Analysis of CPS I and CPS II agree in the magnitude of the effect of spousal smoking. As in most previous epidemiologic studies of ETS, we found a trend in the risk of lung cancer among nonsmoking wives with increasing levels of smoking by the husbands, although it was not statistically signficant. In contrast, for self-reported ETS we found no statistically significant evidence of an elevated risk among the ETS exposed individuals at interview. A case-control study by Kabat and Wynder found an association for self-reported ETS at work among men [3.1 (95% CI=I. 1-11.0)], but not women. In another case-control study that used self-reported ETS as one measure of exposure, Garfinkel et al. found no increasing trend with increasing exposure to ETS measured as number of hours of exposed to the smoke of others in the past, and the risk of lung cancer among nonsmoking women. This fact led the authors to conclude that "the lack of relationship when exposure was classified by

[32 .... hour~ exposed to smoke oL" others may have occurred because this variable does not accuratelv measure intensity of exposure". In this study, however, a two-fold increased risk was found for women whose husbands in the past smoked 20 or more cigarettes at home (Garfinkel 1985). Brownson et al. reported a 1.7 odds ratio for lung cancer for nonsmokers who had four or more hours of self-reported exposure to ETS in a small study of adenocarcinomas (Brownson 1987) but were unable to replicate their findings in a larger study (Brownson 1992). The negative findings of this study with respect to self-reported ETS exposure may well be due to misclassification of exposure since the questionnaire data on self- reported number of hours of exposure to ETS may reflect only current exposure and not the more biologically relevant past exposure. An important evidence of the possibility of such misclassification can be found in the decreased risk of persons in low self-reported ETS exposure categories. This might be due to the inclusion in the referent category (i.e., "0" hours or unexposed) of false negative unexposed persons particularly among those ,dith missing data on self-reported ETS exposure. Exposure to tobacco smoke from the spouse, as was measured in our study (i.e., self- reported smoking history of the spouse) probably provides a more reliable index of long-term and meaningful ETS exposure than current self-report ETS. This measure is not affected by dramatic changes in the prevalence of smoking seen since the 1960's in the US. It ensures that the smoker has a close relationship with the nonsmoker (i.e., spouse). Moreover, our measure of time in marriage takes into account the effective time spent with the smoker during marriage in such a way that if a smoker had quit smoking before marriage, nonsmokers were classified as unexposed to spousal smoking. By the same token, the time smoking spouses smoked in marriage was estimated to take into account the time since quitters stopped smoking. Our findings are generally consistent with those of other epidemiologic studies. Some case-control studies found an association with number of cigarettes or other measures of quantity usually smoked by husbands, but not with duration of spousal smoking (i.e., time living with a smoking spouse) (Hirayama 1984, Akiba 1986, Dalager 1986, Lam 1987, Inoue 1988), while the reverse was observed in some other epidemiologic ~0 O: O~ 0 O~ 0 I ! l ! I R

! I I I- I I I I I I I I I I I I I I I 133 studies tGao i987, Kaiandidi i990). The use of a combination of quantity and duration has been found associated in at least one other epidemiologic study (Fontham 1991). That study conducted by Fontham et al., is by far the best in this regard. The observations regarding the eft'ect of ETS among nonsmokers exposed to asbestos are consistent with those of other large epidemiologic studies which concluded that active smoking and asbestos act synergistically (Selikoff t968). This finding provides additional evidence in support of a causal relationship between ETS and lung carlcer. Some limitations of this study, such as statistical power and misclassification bias, are reviewed. 8.2 Study power The most obvious limitation of this study, shared with most other epidemiologic studies which have addressed this hypothesis, is limited power to detect with sufficient precision a RR on the order of 1.2 (i.e., the summary effect of ETS from 36 other studies). The power of the CPS II was approximately .50 percent for detecting this magnitude of association, as shown in table 43. If indeed ETS increases the risk of lung cancer among nonsmokers by less than 20 percent (e.g., I0 percent), then the power of this study to detect such association with sufficient precision would be only 20 percent. 0

[34 Table 43. Results of power calculations (binomial parameter p=0.5, the proportion of CPS II nonsmoking participants exposed to ETS, by M1 the total number of lung cancer deaths among nonsmokers Mortality Rate Po~') RatioSelf-reported ETS M 1=362 ........... 1.4 94. I 1.3 80.5 1.2 54. I 1. I 23.5 Spousal ETS M1=265 87.1 70.3 45.4 20.5 Thus, the lack of statistical significance in most analyses may reflect low statistical power. 8.3 Misclassification of self-reported ETS Misclassification of both self-reported and spousal ETS exposure might have affected the results of our study yielding a bias towards the null. A dilution of the effect from non-differential misclassification would obscure a weak association between ETS and lung cancer. If any misclassification occurred, probably it was non-differential (i.e., subjects who died from lung cancer were as likely to have misclassified themselves with respect to ETS exposure, as those who did not). Table 44 displays the results of using values in the range of 0.75-0.95 for specificity and sensitivity of classification of outcome or exposure variables in standard formulas (Kleinbaum 1982) to correct for misclassification of an observed association of 1.2 as observed in this study (Cf. Table 34, for nonsmoking wives comparing those married to nonsmokers versus those married to current smoking spouses). Each one of the parameters assumes the values in the x axis, while the others are assumed to have perfect validity. A meaningful adjustment for misclassification of ETS exposure would be necessary in the likely case of having classified exposure with a specificity below 90 percent. ! I ! I ! I I I I I I

i I I I- I I I I i I i I I I I i I I I 135 Table 44. Corrected RR from an observed value of 1.2 (using data from table 34, nonsmoking wives exposed to ETS from current spousal smoking), by degree of misclassification of ETS exposure{} Value of Specificity of Sensitivity of Exposure Parameer , Exposure .... 0.95 1.2 1.2 0.9 1.2 1.2 0.85 1.2 1.2 0.8 1.3 1.2 0.75 1.3 1.2 {}"Each p~ter ~h~ffes, while the c~er is held constan~ at 1 (i.e., perfect classification). In general subjects may have misclassified themselves with respect to their exposure status for the reasons discussed in 8.1. In addition, both refer to exposure during adulthood and thus do not take into account exposure during childhood. However, Fontham et al. study findings (1991) suggest that this source of bias probably is unimportant. Misclassification of relevant exposure to ETS, however, is more likely to have occurred for self-reported ETS than for .spousal smoking for the following five reasons. First, a large proportion of blanks in the CPS ]I ETS questionnaire section were interpreted as unexposed; this assumption may be unrealistic and therefore, augmented a dilution bias. Results of analyses restricted to those who had ftlled the three spaces provided for self-reported hours of ETS exposure (Table 45) showed that such dilution bias existed: the point estimate of the rate ratio of subjects with 6 and more hours of ETS exposure was 1.8 (95% CI---0.9-3.6). The rate ratio was found to be diluted upon inclusion of people with any blank for ETS, because when only those who left the three spaces blank were excluded, the rate ratio was 1.2 for those who were exposed for 6 or more hours to ETS. However, in that case the study had been conducted based on fewer deaths (i.e., 104, or 243, respectively), and therefore, would have had even less power. Those who left any space blank in the spaces provided to write down 0 O~ 0 O~

136 .... the number of hours exposed to E¥~ (and grouped with those who annotated zero hours) or had unquantifiable ETS data (and excluded from analysis) had a multivariate RR of 1.0 (95% CI=0.8-1.3) and 1.0 (95% CI=0.8-1.4), respectively, when compared with the rates of those who annotated zero hours in the three spaces. Table 45. Missings are Exposure to Unexposed ETS (n=362 deaths) Rate ratios § from ETS by different approaches dealing_with missing inform~atio~.on ETS Excludes Excludes ' missings in missings in all three any of fields three (n=243 fields deaths) (n=I04 deaths) 0 1.0 1.0 1.0 1-2 0.7 0.7 0.7 (0.5-1.0) (0.5- i. I) (0.4-1.2) 3-5 0.8 0.7 0.3 (0.5-1.2) (0.5-1.3) (0.1-1.9) 6+ hours 1.2 1.2 1.8 (0.8-1.7) (0.8-1.8) (0.9-3.6) § Adjusted for age, gender, race, education, intake of carotenoid-containing foods, total fat as a nutrient index, occupational exposure to asbestos and history of chronic lung disease. Second, a positive association between schooling with self-reported ETS, could be interpreted as proof of 'increased sensitivity' to the smoke of others among nonsmokers of higher SES. Based upon data from the 1988 NHIS-OH, and most other Smaller surveys and studies of ETS, we expec~ted to find that CPS II participants of relatively lower SES would have reported more ETS than those in. higher SES. Tables 21 and 22 show that there was a direct relationship between any self-reported exposure to ETS and years of education (i.e., higher educated participants reporting more exposure), whereas the opposite occurred with any spousal ETS. In table 46 we compared formal education with self-reported ETS status, and spousal smoking status (any versus none). For simplicity we restricted the comparison to the extremes of less than high school and college 0 0 ! I ! I ! I i I .I I I I ! I

I I I I I I I I I I I I I I I I I I i37 ~graduates and graduate school The resuits of this comparison clearly indicate that nonsmokers with higher education were more likely to report any ETS exposure, but less likely to be married to ever smokers, and suggests that self- reported ETS does not accurately reflect ETS exposure. Table 46. Comparison of any ETS exposure (self-reported or from spousal smoking) by years of education among CPS II nonsmokers, 1982. 16+ 62,731 56,10I 1.3 46,036 52,62I 0.9 Third, self-reported number of hours of ETS exposure does not necessarily reflect the intensity of ETS exposure, but duration to an undetermined amount of ETS. This limitation might contribute considerable misclassification of self- reported ETS. Fourth, as mentioned in 8.1, an indication that suggests such misclassifieation of ETS exposure is found in the results of self-reported ETS exposure itself. Unlike most spousal smoking analyses, there is a consistent pattern of deficit in the risk of lung cancer for the first and second tertile of self-reported ETS exposed, whether it is cumulative in the three settings, ETS at home, work or other places separately. These results are compatible with misclassification of an undetermined proportion of exposed who left blank spaces for hours of ETS exposure blank in the CPS II questionnaire. Last, the classification by self-reported ETS in 1982 has another inherent source of misclassification: that from the changing patterns of smoking (e.g., unexposed subjects in 1982 might have been exposed before if married to former smokers). Therefore, self-reported current ETS exposure does not assess long-term exposure, whereas smoking status of spouses might reflect exposure for many

i38 years, although it may still have iimited vaiidity (Garfinkei i98i, Frieaman I983). An estimate of the RR of lung cancer from ETS corrected for this downward misclassification bias, using the data available in NRC 1987 report which was RR=I.9 (Garm 1988). The EPA report included a correction for this bias (EPA 1992), and the pooled estimates were in the order of our metanalysis estimate (i.e., 1.2). Correcting for this downward bias would result in estimates of 1.2. GarfinkeI et al. pointed out, when reporting the findings of CPS I, that "Long- term effects of passive smoking are difficult to establish because of the problems of classification. It may be misleading to classify a woman as a passive smoker or not on the basis of her husband's smoking habit. Wives of nonsmokers may be more exposed to cigarette smoke of others than wives of cigarette smoking men; wives of smokers may be very little exposed to the cigarette smoke of their husbands or other" (Garfmkel 198 I). In the hypothetical situation of randomly misclassifying 10-25 percent of the study participants, any bias is towards the null: thetrue effect of ETS would be at least as great as the point estimate, and the size of the bias would range from -0.03 to -0.4. Notice that in the typical stituation the bias would have been around -0.06 (i.e., the true parameter 1.2), and that the bias is more sensitive to misclassification of exposure (i.e., nonsmoking spouses being truly smokers). If classification of subjects in this study had been 5 percent imperfect by the four parameters, the corrected RR would have been 1.2. 8.4 Confounding The decline of smoking in the US since the late 60's is reflected in the age distribution of either spousal ETS (particularly the prevalence of current smoking spouses), and self-reported ETS. Younger nonsmoking study subjects were more likely to have any ETS exposure than older persons in the analytic cohort of self-reported ETS. Since lung cancer rates increase exponentially with age, confounding by this variable occurred in the analyses of self-reported ETS. Data-based confounding (i.e., change in estimate) by SES and gender was not 0 O3 0~ 0 O~ I I I I I I I ,I I I I I

I I I I- I I I I I I I I I I I I I I 139 detected across the di~'~'erent an',dyses conducted in d~is ~tudy. However, estimates 'presented in this report are simultaneously adjusted for age, gender, 'race' and schooling as a proxy of SES. Uncontrolled confounding by age is unlikely to have occurred given the fact that in most analyses we grouped age by quinquennia, thus allowing variation within age levels. Inclusion of other variables in the Cox regression models did not affect the adjusted results reported in the previous chapter. No evidence of confounding by other risk factors such as the intake of foods containing carotcnoids, dietary fat, marital status, or history of ehronie lung disease, was found. 8.5 ETS-CH.D association is unexplained by miselassification of smoking status At the core of the Mantel-Lee bias argument against the scientific case for an ETS lung cancer and cardiovascular diseases association, is the contention that a very strong association of active smoking with those outcomes would be reflected by the misclassification of some smokers, more likely former smokers, among those selected into a study population .of nonsmokers. As shown in the NCR report and reproduced in an illustrative example above, the Mantel-Lee argument may be reasonable when discussing the ETS and lung cancer association, given the fact that the size of the effect (i.e., odds ratio) of active smoking on lung cancer risk is considerably large (22 among men in CPS if). This argument, however, cannot explain the association of CHD and ETS, as shown below. A review of the evidence from major cohort studies on active smoking and coronary heart mortality provides estimates of the RR that range from 1.58 to. 2.55 for current cigarette smokers (Fielding 1992). To set limits to the possible effect of the Mantel-Lee bias, we will follow the same approach illustrated in figure 3, but for the case of the ETS-coronary heart disease association. The same simplifying assumptions are used to provide the 0 0~

t40 figures: a closed coiaor~ of i miiiion subjects with aii observations except deaths from CHD, are censored at the end of the six-year follow-up, and deaths occurred at the mid-period. We assumed also a 3 percent misclassification of active smokers (Lee 1988). In addition, we assumed a CHI) mortality rate of 4.8 per 1000 subjects, with a 20 percent prevalence of current smokers, and a two-fold increased CI-ID death rate among smokers. It was found that misclassificafion of smoking status would not have a meaningful effect on the estimates of a such study (i.e., biasing the study from 1.0 to 1.03). The hypothesis of bias from misclassificafion of active smoking to explain the ETS lung cancer hypothesis as set forth by Mantel and Lee (Lee 1985) necessarily implies it should also explain the ETS-CHI) association. The number of reports on ETS and CHD has increased since this argument was fast presented in 1985 (Steenland 1992), and by refuting this statement, these studies further reduce the credibility of the argument of bias by misclassification of active smoking to explain the observed effects of ETS on lung cancer risk or any other major ETS- related disease. There is another major weakness of the Mantel-Lee or "active smoking misclassification bias", namely that most misclassified smokers are actually former smokers. The CI-[D-active-smoking relationship holds for current smokers and the increased risk is reduced by more than half by the end of the first year of cessation. Also, the risk of former smokers slowly approaches the risk of never smokers (Fielding 1992, US DHHS 1982). Therefore, the net effect of the potential bias argued by Mantel and Lee is negligible on the observed relationship between CHI) and ETS. Steenland made this point in a review of the ETS -CH]) association, noting that the effect of such bias would be about 2% (Steenland 1992). 1",3 0 0~ I I I I I I I ,I I I I I I ,I I

I I I I- I I I I I I I I I I I I I I 8.6 Causal Inference The research hypotheses outlined in the Introduction, cannot be rejected or verified on the basis of the results of a single study. The results of this study seem to support the hypothesis of a weak association of cumulative exposure to ETS with the risk of lung cancer among nonsmokers, increasing such risk by 20-30 percent. The lack of statistical significance of the estimates of the effect should not be confused with a null effect, because statistical significance depends heavily on numbers, and it has been shown that our study had little power to detect a RR of 1.2. In addition, a misclassification bias towards the null is likely to have taken place in this study, in an amount enough to dilute the RR estimate from t.3 to 1.2 (specificity <90%). It is not in the strength of the association that the ETS-lung cancer hypothesis finds support, ' but in other major criteria for causal inference in epidemiology. The time order of the observed association is a particular advantage of this study: the assessment of ETS exposure preceded the ascertainment of deaths. This criterion for causal inference is assured by the prospective nature of the study design. As discussed before, this design prevents the occurrence of recall bias. Consistency is the persistence of an association upon repeated test, and has two domains: survivability and replication (Susser 1991). Survivability stresses the number and severity of tests. This study adds survivability to the ETS and lung cancer hypothesis in at least the following ways. First, this study, controls more rigorously for age by using proportional hazards modeling and thus "stratifying" more finely for age, and at the same time it adjusted for SES, and many other potential confounders. Second, this study avoided the potential of recall bias more likely to occur in case- control studies. Last, this study also provided estimates for two independent sources of assessing ETS exposure: self-reported ETS and exposure from spousal smoking status, and the smoking status of spouses was doubly checked. Regarding repl!cability, most epidemiologic studies of lung cancer and ETS have consisted of non-smoking lung cancer cases among wives according to the smoking of o 0",

142 their husbands. The summary estimate from 37 epidemiologic studies, including this one, contrasting the risk of lung cancer of women according to their ETS exposure on the basis of their husband smoking status is still 1.2 (95% CI= 1. I-1.3). This study is consistent with a weak effect of ETS on the risk of lung cancer among nonsmokers. Based on previous knowledge of the joint effects of asbestos and tobacco smoke upon the risk of lung cancer, this study is a confirmation of the prediction that tobacco smoke involuntarily inhaled by nonsmokers exposed to asbestos will increase the risk of lung cancer above that of those exposed to either asbestos or ETS alone. Although based on few numbers, this study found suggestive evidence that this synergism might occur for both active smoking and ETS. It is important to note, at this point, that smoking spouses of CPS II nonsmokers smoked less than their counterparts of other US nationwide studies (e.g., Fontham 199 I). The distribution of pack-years indicates that only I percent of the entire cohort was exposed to 80+ pack years. The distribution of pack-years of CPS II smoking spouses of nonsmokers is skewed to the left with respect with to the SEER based case-control study population. Thus, the overall effect of ETS on lung cancer risk among nonsmokers is likely to be somewhat small because of the low level of ETS exposure in the cohort. Finally, the findings of this study are plausible in terms of pre-existing knowledge about the carcinogenicity of tobacco smoke components, in vitro and in vivo models, as weLl as from epidemiologic studies of active smoking. The biological plausibility of the ETS-lung cancer association is also well founded and it is based upon the evidence of harmful effects of ETS constituents leading to: I) an increased incidence of lower respiratory tract infections, additional episodes of asthma in children, reduced lung function, increased prevalence of middle ear infections and symptoms of upper respiratory tract infection in children (EPA 1992); and 2i an increased risk of CHD in adults in a similar pattern followed by active smoking (Steenland t992). Also, asbestos fibers increase cell proliferation and the occurrence of tumors (Kalburn 1992). Thus, this property of asbestos fibers added to the 0~ D~ 0~ I I I I. C I I I I I I I

I I I I- I I I I I I I I I I i I I I L43 genotoxicity properties of tobacco smoke are beneath the observed synergism of those two environmental hazards. [n summary, the following scientific facts lend biologic plausibility to the conclusion in epidemiologic studies like this that ETS causes lung cancer: 1) tobacco smoke from active smoking causes lung cancer as shown in epidemiologic studies, genotoxicity and animal data, 2) the same carcinogens found in MS and some other carcinogens perhaps more likely to reach the peripheral parts of the lung are present in ETS, 3) the levels at which ETS is present are consistent with those at which a risk is expected, 4) ETS is absorbed by nonsmokers in amounts at which a risk would be predicted, and 5) that the collective findings of epidemiologic studies like this one, strongly support a cause-effect relationship. 8.7 Conclusions 1. With respect to our first hypothesis, our study found that non-smokers exposed to ETS from current spousal smoking are at higher risk of fatal lung cancer than are non- smokers not exposed to ETS. However, we failed to provide precise estimates, and the 95% CI included the null value. Current spousal smoking increased the risk of lung cancer of non-smokers (both men and women) by 30% (0.8-1.9). Our study did not find an overall association with self-reported ETS exposiare. However, we found indication that missing data on reported hours of exposure to ETS may have introduced misclassification, thus biasing the results towards the null. 2. Our study found a weak dose-response relationship with pack-years of cigarettes smoked during marriage by husbands of nonsmoking women, but also this relationship was not statistically signficant (test for trend p---0.14). This relationship was not found for nonsmoking men. There was an 50 percent increased risk of of lung cancer among nonsmoking wives married to cigarette smoking husbands who smoked heavily during their marriage (36+ pack- years) [RR=I.5 (95% CI=0.8-2.8)]; these women represent the upper 17 percent of those married to ever cigarette smokers. l 0 O~ 0:~ I

t44 3. Consistent with the summary estimate of t.2 (95%CI=1.1-1.3) for the risk of nonsmoking women married to ever smokers from 36 published epidemiologic studies reviewed for this paper, this study reports an estimate of 1.3 for the risk of lung cancer among nonsmoking women married to current smokers (any type) (95% CI=0.8-1.9). 4. This study among nonsmoking CPS II participants suggests that there are greater than expected joint effects of ETS and occupational exposure to asbestos (p=0.18). If this relationship exists, it would resemble the known synergism between active smoking and asbestos. 5. The nonstatistically slgnificant association between ETS exposure from spousal smoking and the risk of lung cancer remained unchanged after adjustment for relevant potential confounders, and is not attributable entirely to misclassification of smoking status (i.e, misclassified smokers are included in a study restricted to nonsmokers). 6. Consistent with larger studies, a small validation study found that diagnosis of lung cancer from death certificates correctly classifies lung cancer deaths. Therefore, epidemiologic studies of lung cancer which rely on diagnosis from death certificates may still yield valid estimates of effect. I I I I I I I I I I I I i

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158 APPENDICES A References and Tables of published studies and Metanalysis of ETS-Lung Cancer B Abbreviations C CPS II Questionnaires and Instructions i ! I ! I I I I I I I I I I

Appendix A I Case-control study Authors: Trlchopoulos at Source: L~ncet. 1983 Country: Greece 2 Casa-conlrol sludy Authors: Chang &Fung Source: Grundmarm, t982 CounW:Hong Kong 3 Case-control sludy Authors: Corm,, et zl. Source: Lancet 1983 CounW: USA 4 Case-conlrol sludy Authors: Kaba! & Wynder Source: Cancer 1984 Country: USA 5 Case-control study Aulhors: Bultler at el. Source: Mlzell 1983 Counlry:USA Male-analysis 0l 36 studies on ETS-lung cancer ETS.Lung Cancer In CPS II Smoking habits of spouse CR Smoker Nonsmoker Total Cases 53 24 77 2.075 Controls 116 109 225 Total 169 133 302 In (OR) Vat In (OR)IN In(OR) WI'In(OR)I 0.73 0.07833 12.7666 9.31954 Smoking habits of spouse Smoker Nonsmoker Tolal Cases 34 50 84 0.752 Conlrols 66 73 139 Toter 100 123 223 Smoking habits of spouse Smoker NonSmoker Total Cases 1 7 14 3 I Conlrols 87 226 313 Total 104 240 344 Smoking habits of six)usa Smoker Nonsmoker Total Cases 18 t 8 36 Controls 20 17 37 Total 38 35 73 In (OR) Vat In (OR)IN In(OR) Wl'ln(OR)l -0.285 0.078262 12.7776 -3.639801 a:t In (OR) Vat In (OR}I/V In(OR) Wi'ln(OR)l 3.154 1.1486 0.146171 6.8413 7.859t84 ~ in (OR) Vat In (OR)I/V In(OR) Wl'ln(OR)l 0.85 -0.163 0.219935 4.54681 -0.738942 Smoking habits of spouse C~ Smoker Nonsmoker Total Ceres 38 14 52 0.814 Controls 220 66 286 Tolal 258 80 338 In (OR) Vat In (OR)t/V In(OR) Wl'ln(OR)i -0,205 0.117441 8.51489 -t.749333 Pago 1 ~690E~9890~,

9690~9~90~ Appe nd~x A Meta-analysls of 36 studies on ETS-lung cancer ETS-Lung Cance; In CPS II 6 Case-conlrol study Authors: Gatltnkal at al. So, u~ce: JNCI 1965 Country:USA 7 Case-control study Authors: Wu et Source: JNCI 1985 Count~/: USA 6 Case-control study Authors: Aktba et al. Source: Can Res 1988 Country: Japan 9 Case-control study Authors: DaMager et =d. Source: Can Res 1986 Country: USA tO Case-control study Authors: L~e a! al. Source: BJC 1966 Counm/: UK Smoking habits of spouse Smoker Nonsmoke¢ Total Ca~as 91 43 134 Controls 254 140 402 Total 345 191 536 Smoking habits of spouse Smoker Nonsmoker Total Cases ? ? 29 Controls ? ? 62 Total ? ? 91 Smoking hablts of spouse Smoker Nonsmoker Total Cases 76 3 7 t 13 Controls 197 163 360 Total 273 220 493 Smoking habits of spouse Smoker Nonsmoker Total Cases ? ? 48 Controls ? ? 466 Total ? ? 514 Smoking habits of spouse Smoker Nonsmoker Total Cases 30 1 7 4 7 Controls 59 37 96 Total 80 54 .143 CR In (OR) vat In (OR)IN In(OR) WI'In(OR)I 1.233 0.2095 0.044939 22.2526 4.6627498 C~ In (OR) Vat In (OR)IN In(OR) Wl°ln(OR)l 1.2 0.1823 0.140231 7.t311 1.3001532 (CI-0.6-2.5) CR in (OR) Vat In (OR)IN In(OR) WI°In(OR)i 1.908 0.6461 0.050726 19.7139 12.73713 C~ in (OR) Vat In (OR)IN In(OR) Wi'ln(OR)l 1.47 0.3853 0.11947 8.3703 3.2247627 (95% CI-0.76-2.63) (~ In (OR) Vat In (OR)IN In(OR) Wl'ln(On)l 1.107 0.1014 0.136133 7.34576 0.744~988 Page 2 B~III

m mm n m m mm m m m m m mm m m mm L690~9890~ Mall-analysis ol 36 sludle$ on ETS-lung cancer ETS-Lung C~,ncer In CPS II 11 Case.control study Authors: Gao at am. Source: IJC 1987 Country: China 12 Case-control study Authors: Brownson el el. Source: AJE 1987 Counvy: USA 13 Case-control study AuthOrs: Koo el el. Source: IJC 1967 Country: Hong Kong 14 Case-conb'ol study Authors: Pershagen et Source: AJE 1987 Country: Sweden 15 Case.control study Authors: Humble et el. Source: AJPH 1987 Counuy: USA Smoking habits ol spouse CEt Smoker Nonsmoker Total Cases 246 t 90 436 0.794 Controls 375 230 605 Total 621 420 1041 Smoking habtts ol spouse Smoker Nonsmoker Total CILSeS 4 1 5 1 9 Controls 6 4 t 4 7 Total 10 56 66 Smoking heb~.ts ol spouse Smoker Nonsmoker Tolal Cases 5 t 35 86 Controls 66 70 136 Total 117 105 222 Smoking habits of spouse Smoker Nonsmoker Tolal Cms 37 44 01 Conlrols 153 215 368 Total 190 259 449 In (OR) Vat In (OR)I/V In(OR) WI'In(OR)I -0.231 0.016343 61.1894 -14.10657 CR In (OR) Vat In (OR)I/V In(OR) Wl'ln(OR)i 1.022 0.6001 0.507724 1.96958 1.1818572 (]:] In (OR) Vat In (OR)I/V In(OR) Wl'ln(OR)l 1.545 0.4353 0.077617 12.8639 5.6085763 CR In (OR) V~ In (OR)IN In(OR) Wl'ln(OR)l 1.182 0.1669 0.060941 16.4092 2.7391618 Smoking hab~t~ ol spouse CR Smoker Non~T~oker Total Cases 20 8 29 3.203 Controls 128 164 292 Total 148 172 320 In (OR) Vat In (OR)I/V In(OR) Wl'ln(OR)i 1.1641 0.18091 5.29352 6.162334 m m m

Appendix A Meta,-analysle of 36 etud~es on ETS.bng cancer ETS-Lung Canc~' In CPS II 16 Smoking habits of spouse Case-control study Smoker Nonsmoker Total Authors: Lain et al, 1987 Cases 115 84 199 Source: BJC, 1987 Controls 152 183 335 Cou~V,/: Hong Kong Total 267 287 534 17 Smoking habits of spouse Case-control eludy Smoker Nonsmoker Tolal Author's: Lain & Chang Cases 37 23 60 Source: Smoking and Health t987Controls 64 80 t44 Cou~n/: Ho, ng Kong Total 101 103 204 1 8 Smoking haldls of spouse Case.control study Smoker Nonsmoker Total Aulhors: Shlmlzu. 1988 Cases 53 37 90 Source: Toh J Exp Mad 1988 Conlrols 9 ! 72 163 Country: Japan Tolal 144 109 253 19 Smoking hablls ol spouse Case-control sludy Smoker Nonsmoker Total Authors: Inoue 191~8 Cases 18 4 22 Source: Smoking and Hearlhot988Conlrols 30 1 7 47 Cell numbers from Lee, 1992 Total 48 21 69 20 Smoking habits of spouse Case-conl~'ol study Smokar Nonsmokar Total Authors: Gang, 1987 Cases 34 20 54 Source: Smoking and Health 1987Controls 41 52 93 Count~/: China Total 75 72 147 P~e4 CR in (OR) V~ in (OR)l/V In(OR) WI'In(OR)I 1.648 0.4997 0.032644 30.6336 15.308276 C~ in (OR) Vat in (OR)I/V In(OR) WI'In(OR)I 2.011 0.6986 0.09863 10.1389 7.0826849 C~ in (OR) Varin (OR]IN In(OR) Wl'ln(OR)l 1.133 0.1252 0.070773 14.1297 1.768766 CR in (OR) Vat in (OR)IN In(OR) Wi'ln(On)I 2.25 0.8109 0.343758 2.90903 2.3590176 C1-(0.91-7.1) CR in (OR) Vet In (OR)I/V In(OR) WI'In(OR)I 2.156 0.7683 0.123033 8.12792 6.2446766 '8690~9890~ m m

Appendix ^ 21 Case-control sludy Authors: Katada, 1988 Source: Gan No Rlnsho 1988 Count~/: 22 Case.conlrol study Aulhors: Svensson, 1989 Source: Acta Oncol 1989 Counuy: Sweden 23 Case.control study Authors: Sobue e,t el. 1990 Source: Gen No R~nsho 1990 Counlty: Japan 24 Case.control study Aulhors: Janedch el el. 1990 Source: IJE 1991 Ceils esl~maled horn EPA. 1992 CI from authors, p. 834 Count,n/: USA 25 Case-conlrol study Authors: Wu-Witllame 1990 Source: BJC1990 Country: China Male-analysis ol 36 studies on ETS-|ung cancer ETS-I.ung Cancer In CPS II Smoking h~bits of spouse CR Smoker Nonsmoker Total Cases 17.5 0.S 17 8.448 Conlrols 14.5 3.5 1 7 Tolal 32 .4 34 Smoking habits of spouse Smoker Nonsmoker Tolal Cases 24 10 34 Conlrols 114 60 174 Tolal 138 70 208 Smoking habits of spouse Smoker NonsmoP~r Total Cms 80 84 144 Controls 395 336 731 Total 475 400 875 Smoking habits of spouse Smoker Nonsmoker Total Cases 14 7 44 191 Controls 153 38 t 91 Tolal 300 82 382 In (OR} Va~ I~ (OR)t/V In(OR) Wl'ln(OR)l 2.134 2.411823 177.3 0.4026 1.263 0.2336 0.167105 0.41462 0.8847924 in (OR) Va~ in (OR)I/V In(OR) WI'In{OR}I 5.98425 1.3980101 CR in (OR) V~ in (OR)I/V ~(OR)WI'In(OR)I !.063 0.0614 0.033633 29.7326 1.8246736 UR0(~R 1.2773 tJ)wOR 0.8851 ~ in (OR) Vat in (OR)iN In(OR) WI'In(OR)I 0.93 -0.073 0.071378 14.0099 .I.016711 (Cl-0.55-1.57) Smoking h=t~tts o! spouse Smoker Nonsmoker Total Ccsas 205 212 417 Conlrols 331 271 602 Total 536 493 1019 C]~ ~ (OR) V= in (OR)IN in(OR)Wl*ln(OR)l 0.792 -0.234 0.016306 61.3263 -14.32435 Page 5 6690~:9890~

MeP-~nalysls of 38 studies on ETS-lung cancer Proposal ETS.Lung Cancer In CPS II 26 Case.conUol study Aulhors: Kid)at el id. 1990 Source: Toxicology Forum 1990 Counln/: USA Smoking habits o! spouse CR In (OR} Vat In (OR)I/V In(OR) Wl'ln(OR)l Smoker Nonsmoker Total Cases 48 41 89 1.026 0.0252 0.001825 16.1747 0.4076721 Controls 129 113 242 Tolal 177 154 331 27 Case.conl~ol study Authors: Kalandtdi et el. 1991 Source: EPA 1992, Lea t992 Country: Greeco Smokk~g habits o! spouse C]~ In (OR) Vat In (OR)INN In(OR) WI'Ir,(OR)I Smoker Nonsmoker Tolal. Cases 64 26 90 1.573 0.4528 0.089715 11.I465 5.0466929 Controls 72 46 118 Total 136 72 208 26 Smoking hal:dis o~ spouse Case-control study Smoker Nonsmoker Total Authors: Llu el al. 1991 Cases 45 9 54 Source: IJEE t991 Controls 176 26 202 CountJy: China Total 22 t 35 256 29 Smoking habits of spouse Case-conb, ol study Smoker Nonsmoker Total Authors: Fontham el el. 1991 Cases 294 126 420 Source: C~ul Epld Biota Prey 1991 Controls 492 288 780 Country: USA Tolal 786 414 1200 CR In (OR) Vat In (OR)IN In(OR) WI'!n(OR)I 0.739 -0.303 0,177477 5.63454 -1.706982 (~ kt (OR) Vat ~n (OR)t/V In(OR) Wl'ln(OR)l 1.366 0.3118 0.016843 59.3732 18.511359 30 Smoking habits of spouse Case-control study Smoker Nonsmoker Total Authors: Brownsonsl a1.1992 Cases 215 213 431 Source: AJPH 1992 Conlrols 698 568 ! t 66 Total 816 76! 1567 CR In (OR) Var in (OR)INN In(OR) Wi'ln(OR)l 0.972 -0.028 0.012715 78.6465 -2.223tt4 Page 6

m m m mm mm m m mm m m mm m m mm mm Apl~ndix A Mela-anslysls el 38 studies on ETS-lung cancer Proposal ET$-Lung Cancer In CPS II 3 t Smoking habits of spousa Case-control study Smoker Nonsmoker Total Aulhors: Slockwell0 1992 Cases ? ? 210 Source:JNCI, 1992 Controls ? ? 30 t Total ? ? 5! t CR in (OR) V=r I~ (OR}iNN In(OR) Wl'ln(OR|l 1.60 0.47 0.104496 9.56974 4.497914S (95% CI-0.8-3.0) Vat- -0.015 32 Smoking habits of spouse Case-control sludy Smoker Nonsmoker Tolal Authors: Llu, 1993 Cases 25 1 3 38 Source: AJE 1993 Conlrols 37 32 69 Tolal 62 45 107 CR in (OR) Var in (OR)t/V In(OR) Wl'ln(OR)l 1.663 0.5087 0.1752 5.70776 2.9037908 LIL 3.7778 LL 0.7322 Summary osllmetss ol 32 case-control studies Summm~ in OR (Precision-based}- 0.147 Summary OR (Precision-based),- 1,15g Summmry V~' (In OR) (Prectslon-b~sed)- 0.002 SummlM~t SD (in OR) (Pmclskm-ba~d}- 0.042 Total Total Total 5.990523 571.669 84.272461 Summary Lower 95% OR (Pmdslon-ba=ed)- 1.068 Summit/ Upper 95% OR (Pxeclslon-bazed)- 1,258 Page 7 T, OLOZgSg07--,

Appendix A 33 Cohort sludy Authors: Hlray~ma. 1981 Source: Lancet 1981 34 Cohort study Authors: Gadinket, 1981 Source: JNCI, 1983 35 Coho~t study Authors: Hole el al.o 1989 S~urce: BMJ 1989 36 Cohort Study Authors: Butler 1989 Source: Dissertation UCL~, 1988 Summary estlmalas of four cohort studtss Mats-analysis of 36 studies of~ ETa-lung cancer Proposal ETS-Lung Cancer In CPS II Cases Total Cases Total Ca~s Total Smoking habit~ of spouse ~2vtCl In(SMR)welghts Smoker Nonsmoker Tolal 142 32 174 1.5 0.4055 142 69645 21895 91540 Va~{SMR) 0.047 Smok~ h=bR= of spouse Smoker Nonsmoker Total ~ In(SMR)walghts 88 65 153 49487 127252 176739 1.17 0.157 88 Va~ {SMR) 0.018 Smoking habits of spouse Smoker Nonsmoker Total i:~ In(RR) weights 7 2 9 2.1 0,7419 7 1538 917 2455 Smoking habits of spouse FR Smoka~' Nonsmoker Tota, I In(RR) weights Cases 2 6 B 2.01 0.6981 2 Noncasee 3128 6071 9199 Total 3130 6077 9207 Ovara# In(RR)- 0.326285 Overall RR- 1.3858 Sum ol welghl=- 239 veralt V~'lance- 0.0042 Overatt SO- 0.0647 Summa~' Lower 95% RR (Preclskmobased)- 1.221 Summa~f Upper 95% RR (Prectsk:m-based}- 1.573 Tolal 239 WI'In(RR)i 57,576 0.0382923 W|°In(RR)I 13.8163 0,0267483 WI'In(RR|I 5.19356 0,6428571 WI'In(RR)I t.39827 0.6666667 Total 1.3745643 gOLOg9890Z ll I

~ ~ m m m m m mm m m m m Appendix A Meta-an~,lysls ol 36 f, tud~ef, on F.TS-$ung cancel P;oposal ETS-Lung Cancer in CPS II Summary over 36 studies Ovara, In (RR) o! 36 etudes. 0.200149 Ovarlll (RR) o~ 36 slud~as- 1.221585 S.mmary V~r (in RR) (Preclskm.based). 0.00~234 Summary SD (in RR) (Precision-based). 0.035122 Summa~f Lower 95% RR (Preclslon-based}o 1.14032! Summ~y Upper 95% RR (Precision-based)- 1.30564 Page 9 EOLOZgEgo~

Appendix B Abbreviations AC5 CHD CP5 ! CP$ I~ I~PA [ARC ~CD-9 NCHS NCI NRC SEER S$ US DHHS WHO An~rk~n Cmcc~ Soc/cty Coronary hem disca~ ~r ~ven~on S~y ~o~ A~ for R~h ~o~ ~on ofDi~ ~ ~cn (1~5) Mo~i~ ~d Mo~ W~y ~v~w M~ (~) N~ ~ for H~ Na~on~ ~ Nafio~ ~ ~ Nu~fion Nafio~ ~h ~ S~e~ ~i~olo~ S~no~ s~ Si~ to~ ~ ~ N~on~ ~S~ey 0 0~ ~0 0 0 i I I i I I I ,I I I I I

I I I I I I I I I I I I CANCER PREVENTION STUDY II ~ Group , QUESTIONNAIRE FOR MEN "'-. ~ .J Resea~c~No." l~No. Person No. I. Name; 2. Date o~ birth: Month~__ Year 3. Howold am you now? 4. Cummt weight wi~ indomdo~ng: ,, 5. Weight 1 year ~go~" 6. Height (without shoes): ft. , FAMILY HISTORY (IN RELATION TO CANCER): I. F~I ~ ~ Ib~owing treble ~ completely a~ pos~ for parents, Ixo<heP+ a.~d dste~. UST ONE B~ IF IF 0~, OlD ~ RE~ PER ~E: ~ G~ ~E P~ ~ IF ~," (Ck~e ~ ~ Stst~) THIS Pl~qSON? GIVE AT HAVE ~F_.R? (C,V~ O~) AGE OEATH (O¢~e 0~) SPECIFY WHAT TYPE OF CANCER AGE? 2. When you were born, a) Howoldwas your motheC? b) How old wasyour fatty'? HISTORY' OF DISEASES: b) Date o~ first 2. Place a ¢hec~.~al~ by the fo#owing dlse~ses o¢ If "yes," spec~ type and date(~) c~ operation(s): 6. How n~ny times have you had c~Ids o~ flu in the past twelw mo~ths? , O~ 0 0

DIET: 1. On the average, how many days per week do you eat the following foods? (if less than Once a week, ~ at lea.st twice a mo~tl'~ write II2-) Brussels spmuts...~ Chocolate __ 2. How many days a week do,you eat ~e fo(Iow~ng fried foods? Fded eggs,, Fr~ed haml~Jrgers Fried bacon or beef. Fded chicker~sh Other fried foods French fries~ DO NOT EAT FRIED F~.OS t-'] 3. Do you eat a vegetaxian d~et? I-] Yes ~-I No ff "ye.s," what bJpe at~d for how many yearz? ......... Has nero beec a major change in your diet in last lOysam? I-1Ye~ [] No If "yes," what was d~e charge? 5. ~) Do you now or h~we you eve~- added ~ sweetenerz (saccharin or cycdamates) to coffee. tea, or other ddnks or foed? b) If ever used artificial sweeteners, indicate amount pet day and for howlong. Packets: No. pc," day Yezr~ Orops: No. per day Yeats Ta~ets: No. perday ,, Yeats 6. Do you get your ddnldnc.~ water fmm:l-] Citysupf~y [] Palate wetl [] Other (spec~), 7. DO you add a~/substances to soften your drinldng water? [] Yes [] No 8. How many cups, glasses, or ddnk~ Of thes~ bever- :~ges do YO~ usually ddnk a day, and for how many yem's? (If yo,J no Io~je¢ drink :z listed beverage, or ~0ur pattern fl~ ch~ed in ~he ~ ten years, indi- cate pm,Ao~s and cu~ent amourC¢ If less than onoe a dWo but at least three tJn~s a week, write 1/2.) Whole milk (n<X sldm n~lk] 'Caffeinated coffee !Oecaffeinated coffee "re= Diet soda or diet iced tea HaKI Ik~uor MEDICATIONS AND VITAMINS: 1. How many times in the last mo~th have ~K~J used the fol~ a.,',d how Iortg have y~0~ used them? (If no~e, write 0; If used only occa.sior~ly, wrife V'damin A V'darnin E Mult~V'~rntns BkxKI Pressure Oiuretk~ (wate¢ p~lls) Heart VaJium Ubdum Prescription sleepir~ p~Ls O~ 0 0 O~ I I I i I I i ! I i I

I I I I I I I I I I I CURRENT PHYSICAL CONDITION:1. H~w much exemise do you get (wo~ ot piay)? [] None [] Si~ht [] Moderate [] Heavy 2. On the average, how many hou~ (~0 you ~eep each night? . 3. On the average, ~ many t~'nes = month do you have klsomni=? .[] None 4. Within the last month, have you no(P..ed: a)PalnfulorfrequentudnatJon? []Yes iT) N0 b) An unusual discharge from you¢ penis? 5. Do you noLice pa~n~ in your legs ~an you w.~dk which go a~ay ~e~ you ~e~? [] Yes [] No If "yes," how many yea~ ~ you had these pak~s? 6oAmyous~c~<attheWesanttJme? C]Yes []No If "yes," w~th whai disecse or cond~n? HABITS: 1. Whether or not you ,smoke, on the average, how many hour~ • day am you exposed ~ c~Jarette smoke of o~: At home ~ At work ,. 2. Do you now or have you ever smoked dgamttes. dgars or pipes, at least one a dcf fo~ one Lime? ~ Yes [] No if n~ver smoked, skip to questk~ 8. If you currently smoke c~gsmttes" dg~rs o~ p~pes" fill in the ~focm~Lioa below:. Average number ~a t~-gan smokin9 :INHALATION: loft=de moderately' Inhale dee~ Total years of smokin9 Ye~rs smoked filtered cigarettes Years smoked non*filtered dgamttes 4. Currant brand of dgamtts: b) [] Non-filter [] Rlter [] Mentt~ c) Years smoked this brand:. If, ~ou have quit smoking dgamttes" dgars or ~pes" fill in the intormalJon below:. i Average number smoked ~ day :Age began smok!r INHALATION: In~aled n~demzel), Inhaled deep~ Total yea~ smok~. , Yea~s smoked fiZter~,, dgam~e= Yearn smoked non-filtered dgerettes 6. Last brand of dgarette smoked: ....... a) Size:[] Regumr [] K~ng[] 100ram b) [] Nan-fitter[] Rlter [] Men~'x~ c) Yea~s smoked this brand: 7. Current and •x-cigarette smoker& fill in the following infom~t~n fO~. 1) The first brand smoked ~ulady;, and 2) The brand of cigarette ~rnoked for the longest pednd of time. 1. 1 2. . 8. Have you ever eta•wed robs:co at least once a week fo~ =t least one ye~? I"1 Yea [] No If "no," skip to question 9. a) Age began cttew~ng tobacco: b) How many times a week? c) For how many ye~s? d) DO yo~ sLill chew to03cco? ' [] Yes [] No 9. H~ve you ever used snuff at least orce= week for al leas= one year?. C] Yes I"1 No If'no," skip to "OieL" " • ) ~ began using snu~ b) How many Limes a week? c) For how many yeats? 4) Oo you sLi|! use snuff? ~ Yes [] No 0 0 0

OCCUPATIONS: 1. Wh~ is your current occup~dan ~ wh~t ~ ~r ~es? How m~, yea~: 2. Ifretimd, wt~tw~syouclastoccupwj~?.. 3. What olhe~job have you heid fo~ ~e longest pedod of time?. How many ye~: 4. W~t ~meof daydo you Oo yau wo~ r~ng st~? 5. How many h~Jts a week do you v,~or~ on: paid jobs . ~lu~tee4" ¢ In yo~" wock or dailylite, a~(wera) you regul~ly Coai Tax/PitcW~ Diesel F_~ne F.x~aust Fp, n~e~ Gasoline Exhaust Pestled e s,,H edok:~,~es Tex~le X-rays~Radio~ M~teda~ REMARKS: MISCELLANEOUS: |o Where were you born?, ~ ~ were youtpaten~ born? b) What warn you~ date,J o~ ~en,,k:e? ,to c) V~m did you serve? 9. What is lt~e most upaettlng event tl~t happened to you in about the last fiv~ yean? [] None 0 0 ,-,.I 0 O~ I I ! I I I I 1 I / I I I

I I I I I I I I I I I I I I I AMERICAN CANCER SOCIETY ~.~=.,,~. ~~ CANCER PREVENTION STUDY I! °'*. ~. I Reseatctmr No. QUESTIONNAIRE FOR WOMEN Unit No. Family No. 0a~e: 1. Name: .... 2. Date of birth: Month Year,~ 3. How o,~d am you now? , 4. Current weight with indoor doming: .... 5. We{ght 1 yesr a~jo: ..... 6, Height (without shoes): .... ~, in. FAMILY HISTORY (IN RELATION TO CANCER): I. RII in ~ follov~ table as corrcletely as poss~e for pamnt~, brothers and sister¢ IF DEAD. OlD THIS PERSON EVER ! tF'YES.- HAVE CANCER? SPECIFY (Ci~e O~e) TYPE OF CANCF.R Yea NO Yes No Yes No Ve= No Ye= .No ., Ye~ No b) How ofd was yo~ falt'~'? Whst pad of your body? 6. How many times have you had co~s o~ flu in the past twelve months?, 0 0 0

CURRENT PHYSICAL CONDITION: t. How much exercise do ~0u get (work or l:Way)? [] None [] Slight [] Moderate r] Heavy 2. On the ~rage. how many hours do ~ sleep each night? 3. On the average, how many times a month do You have insomnia? . ~ , r'l None 4. Within the last twelve montt~, ha~,e you noticed: a) A lump of thickening in your breast? [:]Yes nNo b) An unusual disc~e Imm your breast? [] Yes O No 5. Oo you notre pains in your legs whe(1 you walk whk:h go away w~nen you rest? []Yes [] No ff "yes," how many year~ have you had these pain~? 6. Am you sickatthe presenttJme? []Yes ONo If "yes," with what disease o~ conditJoo? MENSTRUAL AND REPRODUCTIVE HISTORY: 2. W'nat is your current menc~3~saJ status? 8S~g m~ men.~-ua~ng In ~se ~ ~t m~au~ b) ~ ~ (~) ~ ~u~ humor of d~s ~ 4. ff past menopause: a) Was your menopause: [] Nmur=l [] Artff'w=i~d b) Age when periods stopped completely? .... C) Did you hav~ excessive bleeding dudng menopause? [] Yes [] No 5. Hm~e you ever had or t~ed to ha~e ch~ren? nY~ •No If "no," skip to question g. 6. Have ~ e~r h~d difficulty beccx~ing pregnant? []Yes ONo if'yes," what was the mason? 7. How many times have you been pregna~? a) ~ age at ~0ur ~ pm<Jnancy?. b) Your age at ~:~Jr first live birth? ¢) Number of children born aJiv~?. d) Numbs' of stillbirths (carded 5 months or mo~)?. e) Number of misca.qiage= (canted less than 5 monthsl?. 8. Were you ever given DES (Dieth~lbestmO to peevent mLscantage? [::] Ye~ [] No =) At what age did you take it? ..... b) For I'mw malty months did you take it? . 9. Birt~ control meth<x:ls: Intimate your age when first used and number of years o! use. NONE OF THE ABOVE ~ Have YO~ ever taken ora~ ¢on~ptives (birth cont~ p~P=)? ~ ~ ~ No If~:~ ~q~ 11. ~e~ fi~t~m? b) ~ ~y ~ d~ ~ ~e mem?.~ 0 0", 0 0 C I I I

I I I I I I I I I I I I I I 3. Current and ex.smoke~: a) Do (did) you inhale? [] No, never O Slightly [] Moderately I-i Deeply b) Fill in the following information foe:. 1)The first beand smol~ed regularly. ~ 2}The brand of cigatelte smoked fo~ the longest period of t~me. DIET: 1. Onme average, how many days per week do you eat the following foods? (If less than once =week, Beef Raw vegetable= Pod¢ Canto Uve¢ Citrus fruits/Juices Ham Spaghetti/M~ca~ Fmh Wn~e r~e Smoked meats Wb~e bread~ls/ Frankfu~ecs/ Biscu~ Sausage Brown r~ce~Wh~e BuYer whea~Ba~ey Cheese Po|atoes Eg~s Oa~rnea~S~%-dded Green [ea~ wheat4~ran Tomatoes Co~d (Dry) cereaJs Brussels spmuts~ Chocolate 2. How many day~ a week do you eat the following fried foods? Fried eggs ~ Fded hamburgers Fded I~co~~ ~ beef Fried chicken~'~ Othe~ fried foods Fm~:J~ hies DO NOT EAT FRIED FOODS [] 3. Do y~u eat = vegetarian diet? l"l Yes O No If '~jes: what P/pc and foe how many yean~? 4. Has there been a ma/~or c~an~e in your diet in ttm last I0 yea~? [:::)Yes C:}No 5. a) DO you now o¢ h~ve you ever added attiflciaJ sweeteners (saccharin or cyclamates) to coffee. tee, o¢ O~ler drinks o¢ food? OYe~,c~m~W O~ ONe~,r amount p~ ~ and fo~ how long. Packets: No. per dW.~-..---.. Year~ Oro~=: No, per day,~ Yearn Tablets: No. per day Ye a.,~ , 6. DO ~:~u get your drinking w-~ter from: 0 City ~l:~ly [] Pnvate well [] Other (spec~) 7. ~ ~ add ~y su~s lo ~ ~r ddn~ 0 Y~ 0 NO 8. H~ m~y ~, gl~es, ~ ~ ~ ~ ~- ~es ~ ~ u~ly ddnk a day, ~ f~ ~ ~y ~es ~t~ ~[emi~(~s~m milk) ~et ~ ~ ~ ~ tee N~tet ~ ~ ~et ~ ddnk ~r H~ MEDICATIONS AND VITAMINS: 1. How many times in the last m<mt~ have ~tou used the following ~ how long hm~ you u,s~d them? If none, write O; If used orgy occadona~wdte 1/2.) Aspirin, Buffedn. Anacin V~tamin A ~rda,min C V'rtamin E Multi-Vffamins Brood Pr~.sure pills Diuretics (water pills) Tnymid mea~.~gons Heart medications Valium Libdum Proscription sleepin~ pdls Tagamet (fo~ ulcers) Other.

OCCUPATIONS: !. Wh~t is your current occupation a~d what am your ~uttes? ...... How many years: 2. I! re|i~ed, what w'~s your last occupation? 3. What o~etjob have you heal fo~t~a k~gest period of tLme?, paid ~ . ~oluntee" wo~ .... housewod~. 6. In you~wotkor d~ly life.am (were) ~ ~ulady REMARKS: MISCELLANEOUS: 1. Wt~ere were you born? 2. W1~em wet'e your pa~nLs boon? Fathe~ Mother: I I I I 1

I I I I I I I I I I I I I I AMERICAN CANCER SOCIETY CANCER PREVENTION STUDY' II INSTRUCCIONE$ PARA LOS ENTREVISTADORES INSTRUCCIONES GENERALES: ln.scdba a almdedm de diez fatnilias: Pot famillas se er~ande hogares deride hay rods de urm persona viviendo juntos como una familia. Cada familM debe re'me per Io menos una persona que teng~ rods de 45 afros. Pot favor haga un esfuerzo pot encocfaaf familias con pemonas entxe las edades de 50 a 50 ahos. Inscfiba sdamente aquellas familias las ¢ua~es usted esM bastan, te segum clue van permanecer en el mismo vedndado durante los p~ximos sels ~ $i usted puede inscribir rnds de" diez familias, pot favor h~jaJo. Pata ayudar a exlN'¢ar el propdsito y el plan de este estudio deje el pantleto "Cancer Pm.~=nlk~ Study II---Hoja Infon'na~va" con cada familia que ustedinscdba. En cade una de las familias que usted inscdba, pida ClUe cada miembro que sea mayorde 30 Ilene o co~teste et cuestionado, los adoque en un "Solxe Cocd~denciel," Io cierre y se Iode,,uelva a usted. Debido a Io extenso de este estudio es necesado identiftcaf carla ~ c(m una sede de nt~metos. Esto se expiica en el I:~UTab n~mem 3, abajo indicado. Pot re#of siga las ins~'tx:docms cuidadosemente. Despuds de recoger los cuestJonarios, Ilena el folleto de cuabo i:~ginas °Usta de Farnirm y Inscdtas." Induya en ~te el hombre y la direccidn de una persona que o:mozca a la ma~a de familias lnscdtas y que pueda reemplazado durante los p~xJmos seis atk~ si fuera ne:esario. Cuando dsto estd terminado meta los "SoOms Con~enda~eS" (con los cueslJonados campletos) en folleto "Usta de FamOus y Personas k~scdtas," asegt~m~o cort una gorna el/L~ca y co~elo sobm grande. Entregue todo el mateda~ terminado seg~n las ins~JCdOrmS que se INSTRUCCIONES DETALLADAS: 1. Revise et paquete pata aseguratse de que cordJenelo dguiente: a) sufidentes cues~o~ados paca hombres ('~npt~o eft ¢olo¢ azu0; b) sufldentes cu~ados para mujems ('m, tpmso an color INanco); c) suficient~s "Sdo~ Co~fKk, nda~es;" d) un folleto de cuatro I:~ginas "Usta de Familias y Personas Ina:dtas;" y e) suf~derttes'Hojas 2. En la Oltima pdgir~ de este folleto de instnx:cio¢~ enumere las fame'ms (hogares) en las que usted que riven iuntas como una familia y tambid, n inc~ a persocms soiteras que riven =dmt Vis~te a cada farn~T=a en su lista e inscdba so(amente aquellas que usl~d piensa estar~ an el dma durante los prbximos seis a/tos. Pr=da ClUe cada miembm mayor de lminta a/~o= liege el ~. No exduya auna familia si uno o dos ndembms se niegan a Ilenaf o no lenan el cu~ despuds que otms rdemb~:~s de la fa.mlia Io hayan Ilenado. 3. Para fac=Tt~r la ident~:addn a usted se le ha asignado un Ndrnero de Divisidn, un N(mero de Unidad, un Nt~mem de Gn~po y un N0mero de Enlz~wistado¢. Cop{e todos esos n0meros en todos ndmeros de ident/licaddn, su nontze y direcci~, yel notable y dimodd~ de un subs~tu~o que conozca a la rna, F~'a de las familias clue usted ha inscdto, en la parte de a~dba del f~eto "L~"la de Familias y Personas Inscdtas."

As~gnele un N0mero de Familia, a c~da f~milia que inscnba, siendo segunda Familia No. 2. etc. Aden',ds as~gnele un Nt]mem de Persona, a c~da persona que insc~ba en cada farnilia~ siendo un miembro de la t'amilia Pe~--=ona No. 1, otto siendo Perso~ No. 2, etc. Pot eiemplo, la pdmer~ familia (Familia No. 1) puede componerse de! Sef~r y Sef~c)ra Ldpez, su hiio de 35 a~os J(xge Ldpez, la suegra del Ser~ Lc~z, ia Sef~ora Rivera y un amigo, el Ser~" Ricardo Martfnez. Entonces, papa la Familia No. I, el Se~r Ldpez es Persona No. 1, La Se~ora Lbpez es Persona No. 2, Jorge I.bpez es Persona No. 3, La Se~,ora Rivera es Persona No. 4. y el Se~or Mattfnez es Persona No. 5. Oespuds, el Se~or y Set~'a Brown pueden set la Famitb. No. 2; dendo el Set, or Brown Persona No. 1 y ia Se~ora Brown Persona No. 2 en la familia. 4. Cua.ndo una persona acepte Ilenar et cueslionado, escdba el hombre de dl o ella y todos los r~meros de identificaci~n (indu)~=ndo elNdmero de FamEa y el N0mero de Persona) en la paste de arriba del cuesttonado. Tambidn escriba et nombre de ~l o ella y la dlreccl6n y todos los n~nems de iden~cack~ en e~ "S4:~:~e Cont'K~endal." Entrdguele el ¢uestiona,'b y d "Sobm ~ncial" ai patr~ante. El cuest~ortatto estzi, diserlado papa set Ilenado pot la persona y las contestaciones son ¢onfldenclales. Pida que el pa~pante Ilene et cuesdonado y luego lo meta en m sobre y lo selle. Usted es responsabte de mcoge~ ~s sobres sellados. Usted puede esper~ rrientras el pa,"tidpante complete e{ cues~ona~'io o, d usled Io ~'effere, puede dejar el cuestionado y ~resar rnds tarde a mcogerlo. 5. Trate de inscdbir a tc~as sus famil'~s y de recoger los cuesSonados co~etados en un pedodo de 6. Despuds de clue usted haya recogido los cuestlonados detodos las personas que usted ha inscrito, ya terminados, Ilene la "Lista de Familias y Personas I~," seg0n las instrucciones dadas en este folleto azuL 7. De.spuds de que haya completado todo, meta'Los Sobres ConF~enci~es" junto cc~ el f~lleto "Lista de Familias y Personas Inscdtas," asegum todo con una goma eldst~ca y pc~jaJo en el grande y devudlvalos seg0n las instn.cciones recib~as. OBJECTIVO Y PLAN DEL ESTUDIO: E~ primer Estudio Sobre la Pmvencidn de la Sociedad Americana Contra et C.dmce¢ se Ile'~ a (:~bo durante un per~odo de 13 afros, desde 1959-1972, y nos ayud~ a ide~tif~ca~ un nOmem de fac~res relacionados con e~ desano~lo de! cdncer, l~e hecho, mucho de Io que conocemos hoy sobre causas del cdncer ha. eurgido de @stos estudos epidemiok~icos. E] ~o N~'nem 1 de 1,1 ~n del Cdncer, pot ejemp~o, establed~ clue el ~umar dga~dlbs es una de las pdncipa~es ¢ausas del cdncer del pulrndn e impC~ a~ uso de~ taba¢o en el desarrollo de otros tipos de c:dncer y en las enfermedades del cocaz~ y vias respi'a~odas. Otms es~Jdios epidemic~icos hart vinculado aJ cdncej" de la piel a demasiada e~ • los F~oX, arsds-~:o o dertos tJpos de bmas ¢dtcer de la vejiga, a lTabajadoms expuestos a dertos pmcludos qufmicos y expos~ durante largo l~ernpo alas 5b~as de a.sbestcs. Esta~ so~ aJ~unos de ~ ~ ambiences clue pueden c~usar ~ Es ~amente a tra~ de la observ-~c~n de un ~'nplio r~mero de persanas durante un largo pe~od~ de t~em~o, coco pS~neamos hair en e~ Estudio N~mero II Para la Pmvenci~n del ~, que podemo~ descubdr muchos ob~s lactates y determine" cudles son perjud~:dales paJ~ la s~lud y cu~d~s no. En el Estudio II Para la l~nci~'t de~ ~__,dnce~ vamos a enfocar nue~tra atenc~ l~a los c~os que hs~ ocu .n~do desde nuestm pdme~ estu~o en nuestm esdo de rids, los pmduc~os que us~mos y en el arnbiente de nuest~o hogar y l~gar de em~o. Re~enter~ente, h~ habk~ un grin iriter~s en determinar el efecto de la s~.,arina, l~ntes I~= el cabello, ~ptivo~ drogas y medicamentos. El efecto de la expodc~ durante I I I I !

I I I I I I I I I I I I I contaminad0n del aim y del zgua, y los carcinbgenos en los lugams de empleo tarnbidn necesitan set cuestionados. Ei p~iblico y lacomun/dad cient~ca desea encontra~ la tazbn p<~-a el aumento en los ca.sos de cdnce~ en la poblaci~n negra y se~'la~ Io~ espeda~es de.sgos de cdncer ent,~e ot~.s minodas. El plan del nue~o Estudb Sobre es inscdb/r a rods de I l/empo. Como entrevistador toluntado, usted serd de gran ayuda en recopi~ infon'n,=~Z~n inves~a}Jva vita~. Manteni~=<~ose en contmto con las pemoc~s que ha inscdto e info~Tnando sobre ellos cada dos af~s, habrd suministrado a nuestros estadfsl~cos de sa/ud con informac~n sob~ cbmo los est~os de vida afectan la salud y qu~ factores aumentan o disminuyen las opodunidades de adquidr cdncer y (:~,ras enfermed~es. Este t~po de estudio ~ument~ nuestm co~dmiento sdore el cdncer y nos pecm~¢d, idenE~r aquellos factoms que c~usa~ cdncer y que pueden set" corttm~doso as( como aque(k:~s que no y sahrat miles de v~das. ALGUNAS PREGUNTAS QUE LE PODRAN HACER LAS PERSONAS QUE USTED INSCRIBA: R /.Po~'qud fur escogido par~ este estud~o? R. Neces~J'nos inscdbir un= ampii~ muesCa de diferente p~b~oo: personas de d~ferentes ed~des, ¢'eas geogrd~cas, razas, relig{ones, hdbitos, expo.s~k~tes y est~los de encontrammos cu~des grupos tienen de.~os mCs aJtos de contr~et" cdncer y cud/es los mc'Ls halos. R z, Est~ interesado ma~:~rrm, nte en personas con FL No, estamos interesados en todas las perso,'~, aquellas que est~ en buer, a saJud, asf como aquellas clue t~enen o hart tenido ¢dncer. R Mi hip de 25 afros ~ ccr~migo. ~,Por qu~ usted no de.sea que R. Estamos exduyendo m pe~ortas menoresde 30 afros pocque ellos no h~n ddo expuestos mbs frecuenda de( ¢dnce~" gene~mente aume"~ coot Im adad y no habd~ sufcie~te informaci&'~ para • estudia~ s~ inscdbimos I:~'~onas menores de 30 afros. R Nosotms sabemos ya que el fumar dgamlos causa ~ ~.Por qud necedtamos otto estudio? R. Los dga,'Tillos fumados ~om p<x rods de dncuenta millo~es de personas son considerabiemente diferentes de los fumados en la dpoca de nuestro pdmet esC, dio. Necesitamos determir, cr dga~dllos bajos en brea y nicot~na hart afect~o substandaknente los riesgos de saJud. Tambidn estamos investigando los efectos del fumar cigamllos en e~ ambiente de lugams de empleo y los posibles efectos de saJud del fumador de "segunda-rnano," ~'to es, el humo inhalado pot pe~o~'tas que no fiJman. R /.PO~lU~ me preguntO p(xmi n0mero de Seguro SociaJ? ~,No es eso ilega~? FL Damos su n0mero de Seguro S<x:ia~ es ex~ctamente vo~untado. AJ hacodo, nos ab, o~ra~ usted mucho l~empo, esfuerzo ydinem aJ veri~:a" nuestros a~chi,ms rods tarde (especiaJmente para persons con bs mismos hombres). Casu~mente, no es ilegel pedir su nOrnem, es ileg~l exlgfr,~do. R ~,Se mantendrd confidential I~ inf~b't en el cuestionado? R. S(. Ser~ ut~liz~dm solamente papa los pmpbsitos de la inves~o Nunc~ daremos informacidn sobre ningun~ persona en p~rl~cular y no dammos direcciones a ninguna mgencia po~ ningtin Ixopd~sito, cuaJqu{em que ~ste sea. ~.~ 0 CO 0"~ 0

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Appendix E. Bibliography of Epidemioiogic Studies of Lung Cancer and ETS L.is~..~ by clm:s'.olo~ic !. Hh-ayama T: Non-~noking wive~ of he•vy unoke~ have • higher incidence of lung caace~. study from Japan. BMJ 1981; 282: 183-185. " ' 2. Trichopoulos D. Ir~landidi A, Sparro~ I~ MacMahon B: Lung cancer and passive J Cancer 1951; 27: 1-4. 3. Garfinkel I.z Th'~e ~endx in lung cancer mortality among non-m~oken and a no~ on passive ~moking. J]~C~ 1981; 66 (6): 1061-1066. 4. Chang WC and Fung SC: Lung cancer in nonosmoke.~ in Hong Kong. I~ Grundmaan (~): Cancer Campaign Vol. 6. Cancer Epidemiology. Gustav ~her Vedag. Sm~zga~ H York. 1982, pp. 199-202. 5.Trichopoulos D. Kalandidi A and Spa-ms L: Lung cancer and passive smoking:. conclusion of Greek su~iy. Lancr~ 1983; ii: 677-678. 6. Con-ca P, Pickle LW0 Fomham ET, IAn Y, and Hacnszcl W: Plosive smoking and lung cancer. Lancet 1983; ii: 595-597. 7. Kabul GC tn¢[ Wynder EL: Lung car, oct in no~smoke~. Cancer I298~; 53: 121a,-I22L 8. Hkzyarna T: Cancer mortality in ~nsmoking wemcn w~h unoking husbands on large-scale cohor~ seedy in lapaa. P~v Med 1984; 13: 680-690. 9. Buffier PA. Pickle LW. Maso¢~ TJ, C.~ntant C.: The causes of lung cancer in Texas. Mkzell M and Cot•ca P:. Lung canc~:, causes ami ~tion. Vedag 198,t, pp. 83-99. l(}. Sandier DP: Passive in adukhoo:[ and, ca•leer risk. AlE I985; 12I (l): 37-48. l 1. Garfin~l L, Auerhach O, and Ioul~rt L: Involuntary smoking tnc[ lung ~ conm31 study./NCI t985; 12. Wu AH, Hen~c~on BE, Pike MC, Yu MC: Smoking a~ui othe.r ~ist" favors for lung cancer in women. £bfCl 1985; 74: 747-75L 13. Akiba $, [Cuo H, Blot WI: Passive smoking ~ lung canc~ among $apanese women. Can Rex I986; 46: 14. Dalagcr NA. Pickle LW, Mason "rl, Cot•ca p~ Fomham E'r, $temhagen A, Buftler PA, Zicglcr RC., Fraumuni JF Jr.: The relation of passive smoking and lung ca~ce~. 15. L~ PN. Charal~-rltin l, and And~'~ MR: Relationship of pas~ve smoking to ~ of. hmg cancer and od:er ~rnoklng-associatcd diteas¢~ Br.[ Cancer I986; ~4: 97- O I

I 16. Gao YT, Blot W~'. Zheng W. ershow AG, I-Isu CW. Levin LI, Zhsag R, Fraur~ni/F Jr.: Lung Cancer among chinese won~a. UC 1987; 40: 604.609. 17. Brownson RC. Reif IS. Keefe TI, Fergwon SW. and Priml IA: Risk f~-'~o¢~ adeaocarcinon~ of the lung. AJE 1987: 12~ (1): 2~-3~. 18. Koo LC. Ho/I-IC. Ho C: Me-cun:mcn~¢ of passive s~noking and ~dmate~ of lung cancer risk among non-smoking chine.~ ferrules./5C 1987; 39: 162-169. 19. Per~hagcn G. Hn~bec Z. ~nd Svens~o~ ~: l~ivc ~ra~king and lun~ ~ Swedish women. ~ 1987; 125 (I): 17-2~. 20. Hutoble CG. Samet ~v[. P~tha~¢ DR: ManY,go to s ~noke~ and lung c~ncer r~k. 1987: 77: 595.602. 21. L~m TH, Kung [TM. Wong CM. I.am WI~ Klccvcas ~ Saw D. H~t C., Sacvirame I'L Lain SY. Lo KK. and Chaa WC~ Smoking, p~.~-ive smoking histological type~ ~n lung c~cer in Hoag Kong Ch|ne~ women. Br~ Cancer 1987; 56: 6"/3-678. 22. ~ TH, Che~g ~ Pa~iv~ ~-aokiag i~ • t'Lck fac~orfer lung cancer in n~ver ~noking wom~n in Hong Kong. Smoking ~ad He.~lth. F.,L~vie, r. 1987, pp. 279-2gL 23. C~ng GY, Ling ZH. Wu GL: On ~he r~la6onship bctw~n sraoldng and female lung cancer. Smoking and Health. El~vier. 1987, pp. 483-486. 24. Inou~ R, Hirayama T: P~sive ~raokin~ ~d lung c~ace, r in women. Smoking Health. Elsevier. 1988, pp. 283-285. 2.5. Kamda H, Mikami R. Konishi R~ Ko~ma Y, a~i N~rita H: Effect o~ pa~iv~ in lung cancer de~elopmem in worn~n in ~he Hm-a ~gio¢~ Cran Ho P, insho 1988; 21-27. Tr'~a~|ated from texx in ~apan~ by M~. Yumt Imai. 26. Shimizu It, Modshita M, Mizuno K, Ma~uda T, Ogura Y, Santo M, Ni~himura M, Kunishima K. Yamamo~ M, His~raichi $, Tominag~ $: A ~-con~rol ~'udy of lung cancer in non,rooking women. Tohok'~ I exp Meal 1988; 134: 389-397. 27. Butler TL: The r~ladon~h~p of pasxiv~ smokin~ ~o v~riou~ health ou~:om~ Seven-Day Adven~u in Califotoim Dissera~ion. L~ An[~l~: UCLA. 1988. 28. Svea~on C, Pe~hag~a G, KIotoinek h Smoking ~d pa~iv¢ xtooking in lung cancer in wocnen. Acu~ Oncol 19g~ 2g: 62:~4~29. 29. Hole DI, GilIis CR. Chopra C, I-~wthom~ V'M: Passive smoking and ca~ior~spira~oq, health in a general populafio¢~ in ~he w¢~ of Scodaad. Br Med ~': 1989;, 299: 423-427. 30. Wu-WiHiam~ AH, Dai XD. Blot W, Xu Zy, Sun XW, Xiao HP, $~on¢ F~a[ YP, Er~how AG. Sun ,~, Fraumoni 1/: It., and Head~n'~on BE: Lung cancer among women in unrth-ea~t China. Brl Cancer 1990;, ~2: 982-987. 0 0 I 4 I ! I I I I i I

I I I I I I I I I I I I I I 3 L Janerich DT, Thompson WD, Varela L, G~nw;~d P. C'homst S, Tuc~ C, Z.~-nan MB, Melamed MR, Kiely ~ McKneally MI:: Lung cancer and exposure ~o ~obacco in the household. NEIM 1990;, 323: 632-636. 32. Sobuc T: Assoc/afion of indot" air pollu~on and lifestylc w~th lung cancer in Japan. LIE 1990; 19 (3) Suppl. : $62-$66. 33. Ka/andidi A, Ka~ouyunni K, Voropoulu N, Basta~ G, Saracci R, Trichopoulos D: Passive smoking and diet in the etiology of lung cunc~ among no~-smokets. Cancer causesanrlcontrol 1990; I: 15-2L 34. Liu Z, He X, Chapman RS: Smoking and other risk factot~ for lung cancer in Xuunwci, China. D'E 1991; 20 (I): 26-31. 35. F-ontham ET, Corr~a P, Wu-WiIILIn'd A, Reynolds P, Gteenberg P~, Bufflcr PA, Chen VW, Boyd P, Ale-man T, Austin DF, Liff JM, G~eenberg DS: Lung cancer in nonsrnokiag women: t multicenter case.conm31 study. Cancer EpidcrniololD', Biormrk~ and Prevent/on 1991: I: 35-43. 34. Kabat GC: Epidcrrfioingic studies of the relationship between passive smoking and lung cancer. Pn:scnu:d at the 1990 annual yarner ~po~ meet/ag of the Toxicology Form= in Washington DC. 35. Rcif.IS, Oglivc GK and Harris CK: Passive smoking and can/no lung cancer. AJE 1992; 125 0): 234-239. 36. Trichopoulos D, Mollo F, Tomatis L, Agapkos E, Delscdirnc L, Zav~tsaaois Kala~didi A, Kat.~ouyunni K. Riboll F., ~d Sancci R: Active and paxsive smoking and pathological indicators of lung cancer risk in an autopsy study..IAMA 1992; 268: 1677- 1701. 37. Stockwcll HG, Goldman AL, Lyman GH, Noss CI, Armstrong AW, Pinkham PA, Candslora EC, and Brusa MR: Eav/rmmen~ tobacco smoke and lung cancer risk in nonsrnoking women. JNCI 1992; 84: 1417-1422. 38. Brownson RC, Alavanja MCR, Hock IST. Loy TS: Passive smoking ~md lung canc~ in nonsmoking women. AJPH 1992; 82: 1525-1530. 39J..iu Q, Sasco A,I, RiboH F., and Hu MX: Indoor air pollution and lung cancer in Guangzhou, People's Republic of China. AJE 1993; 137: 145-154. 0 0

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