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Appendix D:
Risk Assessment—Exposure to Environmental Tobacco Smoke and Lung Cancer

James Robins

This authored appendix was prepared by Dr. James Robins of the Harvard University School of Public Health. The material was not considered by the committee largely because of lack of time, nor was it reviewed by the Natioal Research Council. It gives an approach to risk assessment that considers both the epidemiologic data and some measures of exposure to the constituents of ETS. It is included as an addendum of this report and is presented here as one possible way to integrate the data contained in the remainder of the report.

INTRODUCTION

In Chapter 12, the results of 13 epidemiologic studies are summarized. Each study provided an estimate of the ratio of the lung cancer mortality rate among nonsmokers who answered “yes” to a question like “Is your spouse a smoker?” (hereafter called “exposed” individuals) to the mortality rate among nonsmokers who answered “no” to that question (hereafter called “unexposed” individuals). A weighted average of the 13 study-specific rate ratios is roughly 1.3. In this appendix, we assume that a weighted average of 1.3 is causally related to differences in environmental tobacco smoke (ETS) exposure between “exposed” and “unexposed” individuals and not to bias (e.g., misclassification of smokers as nonsmokers—see Chapter 12).



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Environmental Tobacco Smoke: Measuring Exposures and Assessing Health Effects Appendix D: Risk Assessment—Exposure to Environmental Tobacco Smoke and Lung Cancer James Robins This authored appendix was prepared by Dr. James Robins of the Harvard University School of Public Health. The material was not considered by the committee largely because of lack of time, nor was it reviewed by the Natioal Research Council. It gives an approach to risk assessment that considers both the epidemiologic data and some measures of exposure to the constituents of ETS. It is included as an addendum of this report and is presented here as one possible way to integrate the data contained in the remainder of the report. INTRODUCTION In Chapter 12, the results of 13 epidemiologic studies are summarized. Each study provided an estimate of the ratio of the lung cancer mortality rate among nonsmokers who answered “yes” to a question like “Is your spouse a smoker?” (hereafter called “exposed” individuals) to the mortality rate among nonsmokers who answered “no” to that question (hereafter called “unexposed” individuals). A weighted average of the 13 study-specific rate ratios is roughly 1.3. In this appendix, we assume that a weighted average of 1.3 is causally related to differences in environmental tobacco smoke (ETS) exposure between “exposed” and “unexposed” individuals and not to bias (e.g., misclassification of smokers as nonsmokers—see Chapter 12).

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Environmental Tobacco Smoke: Measuring Exposures and Assessing Health Effects Wald and Ritchie (1984) have shown that “unexposed” individuals have, on average, 8.5 ng/ml of cotinine in their urine. Since virtually the only source of cotinine or nicotine in body fluids is tobacco products, primarily through tobacco smoke exposures, it follows that “unexposed” individuals are exposed to ETS. For this reason, whenever we refer to such “unexposed” subjects, we place the word “unexposed” in quotation marks. If the “unexposed” subjects have, in fact, been exposed to ETS, the observed relative risk of 1.3 would be an underestimate of the true adverse effect of ETS on “exposed” individuals. The correct measure of the adverse effect of ETS on “exposed” individuals would be the ratio of the lung cancer mortality rate in “exposed” individuals to the rate in truly unexposed individuals (which we shall call the true relative risk in the “exposed”). In Section D-1, we use the data collected by Wald and Ritchie (1984) on levels of urinary cotinine in “exposed” and “unexposed” individuals to estimate this true relative risk by two different methods. In Section D-2, we combine the existing epidemiologic data on active smokers with data on nonsmokers exposed to ETS to estimate the ETS exposure of an average nonsmoker in cigarette-equivalents per day. Additionally, we compare this estimate to independent estimates of ETS exposure based on (1) levels of respirable suspended particulates (RSP), benzo[a]pyrene (BaP), and N-nitrosodimethylamine (NDMA) in ETS and in mainstream smoke and (2) levels of urinary cotinine and nicotine in active smokers and nonsmokers. In Section D-3, we compute how many of the lung cancer deaths estimated to occur among (lifelong) nonsmoking persons in 1985 might be attributable to ETS. The estimate is made separately for women and for men. Many environmental exposures are regulated to a level where the anticipated lifetime risk of death attributable to exposure is less than 1 in 100,000 or 1 in 1,000,000. In Section D-4, we consider whether the lifetime risk of death (from lung cancer) attributable to ETS among nonsmokers with moderate ETS exposure is in excess of 1 in 100,000. (Although we do not estimate the lifetime risk of death attributable to ETS from causes other than lung cancer, this does not imply that we believe that lung cancer is the only cause of mortality influenced by ETS exposure. The decision to restrict the analysis to lung cancer mortality reflects the fact

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Environmental Tobacco Smoke: Measuring Exposures and Assessing Health Effects that the data necessary to perform an adequate quantitative risk assessment for causes of death other than lung cancer do not exist.) In discussions of the health effects of ETS exposure, one should consider the effect on exsmokers of breathing other people’s cigarette smoke, since exsmokers have given up smoking, presumably to protect their health. Therefore, in Section D-4 we estimate, for exsmokers, the lifetime risk of death from lung cancer attributable to breathing other people’s cigarette smoke. The sections D-1 to D-4 give nontechnical expositions of the issues. A separate Technical Discussion Section provides additional technical support and mathematical background. In order to make quantitative estimates of the lung cancer risk attributable to ETS, numerical values must be chosen for a large number of parameters. When there are either no data or inconsistent data as to the magnitude of an important parameter, results are reported for a range of plausible values (i.e., a sensitivity analysis is performed). Summary of Main Results Under the Assumption That the Summary Rate Ratio of 1.3 Is Causal We summarize our main results. We caution the reader that the proper interpretation of these results requires that one read Section D-1 to D-4 and the discussion section that follows. The estimated true relative risk for “exposed” individuals lies between 1.41 and 1.87. For “unexposed” individuals, the estimated true relative risk lies between 1.09 and 1.45. The number of (actively smoked) cigarettes effectively inhaled by a nonsmoker living with a smoking spouse lies in the range of 0.36–2.79 cigarettes/day. If the spouse is a nonsmoker, however, the estimated number lies between 0.12 to 0.93 cigarettes/day. Of the roughly 7,000 lung cancer deaths estimated to have occurred among lifelong nonsmoking women in 1985, between 1,770 and 3,220 may be attributable to ETS. Of the roughly 5,200 lung cancer deaths estimated to have occurred among lifelong nonsmoking males in 1985, between 720 and 1,940 may be attributable to ETS. The estimated lifetime risk of lung cancer attributable to ETS in a nonsmoker with moderate ETS exposure lies between 390 and 990 in 100,000. The estimated lifetime risk of lung cancer attributable to other people’s cigarette smoke for an exsmoker who

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Environmental Tobacco Smoke: Measuring Exposures and Assessing Health Effects smoked one pack per day from age 18 to 45 and was moderately exposed to other people’s cigarette smoke lies between 520 and 2,030 per 100,000. D-1 ESTIMATION OF THE TRUE RELATIVE RISK Method 1 The first method for estimating the true relative risk relies on two assumptions: The excess relative risk in a nonsmoker is proportional to the lifetime dose of ETS. That is, if an individual’s dose of ETS (at all ages) were doubled, his excess relative risk would be doubled. At every age, “exposed” subjects have been exposed to ETS at a rate 3 times that of “unexposed” subjects. A factor of 3 was selected to reflect the empirical observation that the concentration of cotinine in the urine of nonsmokers with smoking spouses is about 3 times that of nonsmokers without smoking spouses (Wald and Ritchie, 1984). These two assumptions imply that the excess (true) relative risk in “exposed” individuals is 3 times that of “unexposed” individuals. Hence, in the absence of bias, the summary rate ratio of 1.3 equals the ratio of the true relative risk in “exposed” individuals to that in “unexposed” individuals. Therefore, where x and 3x are the excess true relative risks in “unexposed” and “exposed” individuals, respectively. Solving for x gives x= 0.18 and, thus, the true relative risk in “exposed” and “unexposed” individuals of 1.54 and 1.18, respectively. If we used the summary rate ratio of 1.14 from only the U.S. studies (see Chapter 12), we estimate the true relative risk in “exposed” and “unexposed” individuals to be 1.23 and 1.08, respectively. It is likely that the second assumption above may be inappropriate (see Remark 4 in the Technical Discussion). For instance, it is unlikely that the ETS exposure in childhood is 3 times greater in subjects who later married smokers, i.e., “exposed” subjects, than in subjects who later married nonsmokers, i.e., “unexposed” subjects. If it is not appropriate, then another approach is necessary. This approach is outlined in Method 2, which follows.

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Environmental Tobacco Smoke: Measuring Exposures and Assessing Health Effects Method 2 Method 2 relies on the following two assumptions: Assume that (a) cigarette smoke influences the rates of the first- and fourth-stage cellular events in a five-stage multistage cancer process (Day and Brown, 1980; Brown and Chu, in press); (b) ETS affects the same two stages; and (c) the ratio of the relative magnitude of the effect (on a multiplicative scale) on stage 4 to that of stage 1 is the same for ETS and mainstream smoke. If we let β1 and β4 represent the magnitude of the effect on the first and fourth stages, respectively, then (c) implies that β4/β1 is the same for ETS and mainstream smoke. Assume the observed overall summary rate ratio of 1.3 is the ratio of the true relative risk in “exposed” subjects to that in “unexposed” subjects at age 70 (see Remark 3 in the Technical Discussion). It is possible to estimate the true relative risk in “exposed” and “unexposed” study subjects, given two additional pieces of information (see Remark 8 in the Technical Discussion). First, we require an estimate of the ratio β4/β1. An estimate of β4/β1 can be obtained by fitting the above multistage cancer model to data on the lung cancer experience of active smokers. In particular, an estimate of 0.0124 is obtained by fitting the multistage model to the continuing smoker data among British physicians given by Doll and Peto (1978). Brown and Chu (in press) obtained an estimate of 1.8, derived by fitting the multistage model to data from a large European case-control study of lung cancer. These two estimates of β4/β1, however, differ from one another by 150-fold. A third estimate of β4/β1 was computed, based on the following considerations. The estimate of β4/β1 from Doll and Peto (1976) fails to adequately account for the rapid fall off in relative risk in British physicians upon cessation of smoking. Since a larger ratio of β4/β1 will be associated with a more rapid fall off of risk when smoking is stopped (especially among smokers of relatively few cigarettes a day), we computed the maximum estimate of β4/β1 that was statistically consistent (at the 5% level) with the continuing smoker data in Doll and Peto (1978). This estimate was 0.225. Rather than choose among these estimates, we performed a sensitivity analysis using the three estimates of

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Environmental Tobacco Smoke: Measuring Exposures and Assessing Health Effects β4/β1 of 0.0124, 1.8, and 0.225 (see Remark 5 in the Technical Discussion). Second, we require, at each age, an estimate of the age-specific ETS exposure of “exposed” and “unexposed” study subjects relative to the current ETS exposure of an average adult nonsmoker whose spouse is a nonsmoker. Information does not exist to answer questions such as “How many times greater (or less) was the past ETS exposure in average “exposed” subjects from age 0 to 20 than the current ETS exposure of an average adult nonsmoker with a nonsmoking spouse?” Therefore, a sensitivity analysis was performed using 30 different choices for the lifetime exposure histories of “exposed” and “unexposed” subjects (relative to the current ETS exposure of an adult nonsmoker without a smoking spouse). The choice of exposure histories was influenced by the following general considerations. Smaller differences postulated between the lifetime ETS exposures of “exposed” and “unexposed” individuals will be associated with larger estimates of the true relative risk. (Having an observed rate ratio as large as 1.3 when there is truly only a small difference in dose between the “exposed” and “unexposed” subjects would imply that ETS is a potent carcinogen.) Therefore, we tried to select some exposure histories that would modestly underestimate the true difference in exposures between the “exposed” and “unexposed” study subjects and others that would modestly overestimate this difference. The rationale for our particular choices of the 30 exposure histories is given in Remark 7. Thirty possible exposure histories are given in Table D-1. Remark 6 in the technical discussion describes how to read the exposure histories from this table. Table D-2 gives the maximum and minimum estimates of the true relative risk among the “exposed” and “unexposed” for each choice of β4/β1, over the 30 exposure histories. The column denoted “all” gives the overall maximum and minimum as the choice of both β4/β1 and exposure history varies. The most striking finding is that the estimate of the excess (true) relative risk for “exposed” individuals varies only twofold, from 0.41 to 0.87, and includes the estimate, 0.54, obtained with Method 1. All estimates exceed the uncorrected value of 0.30. Estimates of the excess true relative risk in the “unexposed” range from 0.09 to 0.45. Because of the possibility that the 30 exposure histories are not representative of those in Japan and Greece, two

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Environmental Tobacco Smoke: Measuring Exposures and Assessing Health Effects TABLE D-1 Thirty Population Exposure Histories in Various Age Groupsa Value of a, b, or c Population Subgroup Age 0–20 yr Age 20–55 yr Age 55–70 yr pa f1a f2a pb f1b f2b pc f1c f2c 1 E Ē 0.39 0.25 1.53a 1.53 0.3 0.3 1.0 1.0 3.0 1.0 — — 0.5 1.0 3.0 1.0 3.0 — 2 E Ē 0.44 0.18 1.53 1.53 0.3 0.3 1.0 1.0 1.5 0.15 — — 0.5 1.0 3.0 1.0 2.0 — 3 E Ē 0.44 0.18 1.53 0.75 0.3 0.15   0.5 1.0 3.0 1.0 1.0 — 4 E Ē 0.44 0.18 0.75 0.75 0.15 0.15   5 E Ē 0.44 0.18 1.0 0.5 0.6 0.3 aIn units of d0. NOTATION: E=“Exposed”; Ē=“Unexposed”. Population Exposure History (a, b, c)=(1, 2, 3), has paE=0.39, paĒ=0.25, f1aE=f1aĒ=1.53, f2aE=f2aĒ=0.3, pbE=pbĒ=1.0, f1bE=1.5, f1bE=0.15, pcE=0.5, pcĒ=1.0, f1cE=3, f2cE=1, f1cĒ=1. The interpretation follows. INTERPRETATION: 39% of E-individuals were exposed to ETS dose rate 1.53 d0 and 61% to 0.3 d0 from ages 0–20. 25% of Ē subjects were exposed to 1.53 d0 and 75% to 0.3 d0. From 20–55, all E-subjects were exposed to 1.5 d0, all Ē subjects to 0.15 d0. From 55–70, 50% of E-subjects were exposed to 3 d0 and 50% to 1 d0. All Ē-subjects were exposed to 1 d0.

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Environmental Tobacco Smoke: Measuring Exposures and Assessing Health Effects TABLE D-2 Estimated Ranges for the True Relative Risks (RR) in “Exposed” and “Unexposed” Subjects Rate Ratioa Group β4/β1 All 0.0124 0.225 1.8 1.3 “Exposed” 1.41–1.87b (321)–(113)d 1.41–1.87c (321)–(113) 1.43–1.72 (321)–(113) 1.43–1.64 (321)–(113) “Unexposed” 1.09–1.45 (321)–(113) 1.09–1.45 (321)–(113) 1.10–1.34 (321)–(113) 1.11–1.27 (321)–(113) 1.14 “Exposed” 1.19–1.35 (321)–(113) — — — “Unexposed” 1.04–1.18 (321)–(113) — — — aAssume causal summary rate ratio. bRange of RR over 30 exposure histories and three values of β4/β1. cRange of RR over 30 exposure histories. dExposure histories (a, b, c) at which minimum and maximum, respectively, occur [see Table D-1 for definition of exposure histories (a, b, c)]. of the countries in which epidemiologic studies were conducted, we repeated the analysis using the overall summary rate ratio of 1.14 from the U.S. studies. In this case the overall range in the estimates of the true relative risk was 1.19 to 1.35 in the “exposed” and 1.04 to 1.18 in the “unexposed.” D-2 THE CARCINOGEN-EQUIVALENT NUMBER OF ACTIVELY SMOKED CIGARETTES INHALED DAILY BY PASSIVE SMOKERS: COMPARISONS OF EPIDEMIOLOGIC WITH DOSIMETRIC ESTIMATES In this section we attempt to estimate the number of cigarettes, d0, that would have to be actively smoked to deliver to the lung of the smoker a dose of active carcinogen equal to the daily pulmonary dose of carcinogen (attributable to ETS) of an average adult nonsmoker with a nonsmoking spouse. Roughly speaking, d0 is the (lung) carcinogen-equivalent number of (actively smoked) cigarettes inhaled daily by an average adult nonsmoker with a nonsmoking spouse. Under the assumptions of Method 2, we saw that knowledge of β4/β1 and of the relative exposure histories of “exposed” and “unexposed” study subjects was sufficient to estimate the true

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Environmental Tobacco Smoke: Measuring Exposures and Assessing Health Effects relative risks. If we also have an independent estimate of β1, we can estimate d0 as well (see Remark 8). Each of our three methods of deriving an estimate for β4/β1 from data on active smokers also produces an estimate of β1. In particular, estimates of β1 of 2.93, 0.803, and 0.14 are associated with β4/β1 of 0.0124, 0.225, and 1.8, respectively. Some conflicting results need to be resolved, however. For any given level of smoking, the relative risk estimated from the British physicians data (Doll and Peto, 1978) is greater than that estimated from the American Cancer Society’s follow-up data on a million Americans (Hammond, 1966) or from the multicenter European case-control lung cancer data (Lubin et al., 1984; Brown and Chu, in press). The relative risks in these latter two studies are consistent with one another and will here be treated as identical. Doll and Peto (1981) suggest that these differences in relative risk may be real differences, attributable in part to the different way cigarettes are smoked in Britain and other countries. To bring the British data in line with the other data, we adjusted our estimates of β1 from the Doll and Peto data as follows. Separately, for the β4/β1 of 0.0124 and 0.225 (both based on the British physicians data), we computed the value of β1 that would be necessary for an individual smoking 25 cigarettes per day since age twenty to have the same lung cancer incidence at age 65 as would follow if β4/β1=1.8, β1=0.14 (based on the European case-control data). This gives adjusted estimates of 1.41 and 0.46 for β1, corresponding to values for β4/β1 of 0.0124 and 0.225, respectively. These values are approximately half those previously estimated from the British physicians data. In our sensitivity analysis we use both the adjusted and unadjusted estimates of β1 (see Remark 9). Estimates of d0 are given in Table D-3. Under the assumption that the summary rate ratio of 1.3 is causal, estimates of d0 vary about eightfold from 0.12 to 0.93 cigarettes per day. For a given pair of values of β1 and β4/β1, the variation in d0 over the 30 exposure histories is only about twofold. When we use the summary estimate of 1.14 from the U.S. studies in lieu of the summary estimate of 1.3, our estimates of d0 are diminished accordingly. We next compare the above estimates of d0, which are based on the epidemiologic data, with estimates based on the dosimetric measurements reported in Chapters 2 and 7. Estimates of d0 based on dosimetric calculations are given in Table D-4. In Table D-4 we

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Environmental Tobacco Smoke: Measuring Exposures and Assessing Health Effects TABLE D-3 Estimated Range for d0, the Carcinogen-Equivalent Number of (Actively Smoked) Cigarettes Inhaled Daily by Subjects Without a Smoking Spouse β4/β1: All 0.0124 1.8   0.225 β1: All 2.93 1.41 0.14 0.803 0.46 Rate ratio 1.3a 0.12–0.93b (311)–(123)c 0.12–0.27d (311)–(123) 0.24–0.57 (311)–(123) 0.48–0.89 (311)–(423) 0.26–0.53 (311)–(123) 0.46–0.93 (311)–(123) 1.14 0.05–0.47 (311)–(123)   aAssured causal rate ratio. bRange of d0 in cigarettes/day over 30 exposure histories and all (β4/β1, β1). cExposure history where maximum and minimum occurred. dRange of d0 over 30 exposure histories. TABLE D-4 Estimates of d0 Based on Various Constituents of ETS in Cigarettes/Day Constituent Range NDMA 0.17–3.75 BaP 0.0084–1.89 RSP 0.0001–0.005 give an estimated range for d0 under the assumptions that the ratio of the pulmonary (tissue) dose of active carcinogen in nonsmokers without smoking spouses to the pulmonary dose in active smokers is equal to the ratio of the pulmonary dose of BaP, NDMA, or RSP in the same populations. The estimates in Table D-4 are based on (1) the dosimetric measurements given in Table 2–10 and Chapter 7 and (2) the daily number of hours of self-reported ETS exposure among nonsmokers without smoking spouses (Wald and Ritchie, 1984; Friedman et al., 1983). Details of the calculations used to produce Table D-4 are given in Remark II of the Technical Discussion. The dosimetry of the biomarkers nicotine and cotinine is more complicated and is discussed in Remark 12. There is a serious problem in reconciling the estimate of d0 (Table D-4) based on BaP with that based on RSP, since RSP is often assumed to be a good surrogate for polycyclic hydrocarbons such as BaP. The estimate derived from the BaP measurements is

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Environmental Tobacco Smoke: Measuring Exposures and Assessing Health Effects several orders of magnitude higher. A possible, although unlikely, explanation is that the measurements of BaP levels in ETS (summarized in Table 2–10) inappropriately reflect total environmental BaP, which includes contributions from cooking, coal burning, and other sources, and that the contribution of BaP from ETS to total BaP is of the order of 2% or less. The large uncertainty in d0 seen in Table D-4 restricts the utility of these dosimetric calculations, especially given the lack of knowledge concerning the identity of the active carcinogens in ETS and mainstream smoke. In fact, the limitations of our dosimetric data may be even more serious than Table D-4 would lead one to believe. Specifically: the range of values entered in Table D-4 for NDMA could actually be orders of magnitude too high (see step 4 of Remark 11), the range of values for RSP and BaP do not reflect differences between the particulate phase of ETS and that of mainstream smoke with regard to deposition sites, clearance rates, and particle size, the range of values given for BaP in Table D-4 could be orders of magnitude too high if, as discussed above, the BaP entries in Table 2–10 represent the total environmental BaP inhaled by a nonsmoker, and the ratio of urinary nicotine (or cotinine) in nonsmokers to that in active smokers may not reflect, even qualitatively, the ratio of the biologically effective dose of active lung carcinogen absorbed by nonsmokers to the dose absorbed by active smokers (see Remark 12). D-3 ESTIMATING THE NUMBER OF LUNG CANCER DEATHS IN NONSMOKERS IN 1985 ATTRIBUTABLE TO ETS An estimate of the total number of lung cancer deaths among lifelong nonsmoking women in 1985 is ∑t I0(t)N(t), where N(t) is the number of nonsmoking women at risk at age t in 1985 and I0(t) is the age-specific lung cancer death rate among nonsmoking women in 1985. Data on I0(t) are given in Garfinkel (1981) for 1972; thus, this may be somewhat inaccurate for 1985. National Health Interview Survey data on N(t) were made available from

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Environmental Tobacco Smoke: Measuring Exposures and Assessing Health Effects would be the more appropriate values to use. For these reasons, we report results for all five of the combinations of β4/β1 and β1 given in Table D-3. Remark 10: Adjusting for the ETS Exposure of Active Smokers In estimating β1 and β4 from active-smoker data neither we nor Brown and Chu (in press) took account of the fact that in those studies active smokers (and the comparison groups of nonsmokers) were themselves breathing other peoples’ cigarette smoke. If 3d0 is of the order of 3 or more cigarettes per day (as in Table D-3), a proper analysis (and thus proper estimates of β1, β4, and d0) would require refitting the active-smoking data taking account of ETS exposure. We have not done so here. We expect that the effect on our estimates of the true relative risk in “exposed” and “unexposed” subjects using Method 2 would not be great (because of the insensitivity of these estimates to uncertainty in β1/β4). On the other hand, the effect on our estimates of d0 may be more pronounced. Further study is required. Remark 11: Estimation of d0 from Dosimetry The estimates of d0 given in Table D-4 are obtained in step 5 of the following sequence of calculations. 1. For the ETS constituents BaP and NDMA we estimated the weight of each constituent inhaled directly by an active smoker from the mainstream smoke of a single cigarette by using the mid-point of the range given in the mainstream weight column in Table 2–10 (i.e., 25 and 30 ng for NDMA and BaP, respectively). (The weights entered in the mainstream weight column of Table 2–10 are averages based on cigarettes whose mainstream-smoke tar content, as measured by a smoking machine, varied between 16 and 30 milligrams.) 2. We estimated the weight of each of the above constituents inhaled daily by a nonsmoker with a nonsmoking spouse by multiplying by 1.07 the range of values given under the ETS weight column in Table 2–10. (1.07 is our estimate of the average number of hours of daily ETS exposure occurring in nonsmokers with nonsmoking spouses. Nonsmokers without smoking spouses report that they are exposed, on average, to ETS between 5 (Table 6, Friedman et al., 1983) and 10 hours a week (Wald and Ritchie, 1984). Our value of 7.5 hours/week (=1.07 hours/day) is the average of the above estimates. We could have chosen to multiply

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Environmental Tobacco Smoke: Measuring Exposures and Assessing Health Effects the value of 1.07 by a factor of up to 2, since most components of ETS decay with a half-life of approximately 1 hour when smoking ceases, assuming approximately one air change per hour and little plating out onto surfaces.) 3. For each constituent we divided the endpoints of the weight ranges calculated in Step 2 by the weight estimated in Step 1. The resulting range of values is, for each constituent, an estimate of the number of cigarettes that would have to be actively smoked in order that the weight of the constituent in the directly inhaled mainstream smoke would equal the weight of the constituent (attributable to ETS) inhaled daily by an average nonsmoker with a nonsmoking spouse. We shall call this number I0m. 4. We next estimated for each constituent the number of cigarettes whose mainstream smoke would have to be directly inhaled by an active smoker to deliver to the lungs a dose of the constituent equal to the daily (biologically effective) pulmonary dose (attributable to ETS) of a nonsmoker with a nonsmoking spouse. We refer to this number as d0m. For BaP we multiplied the endpoints of the range for I0m by one-seventh. This reflects the fact that BaP is in the particulate phase and, as discussed in Chapter 7, a rough estimate of the deposition rates for particulates in ETS and in mainstream smoke is 10% and 70%, respectively. [This calculation ignores important differences between the ETS and mainstream particulate phases in terms of deposition site, clearance rates, and particle size. Thus, even if BaP were the active carcinogen in ETS and mainstream smoke, d0m, as calculated above, could conceivably be quite different from the true value of d0m defined in terms of the biologically effective dose for producing lung cancer.] For NDMA we assumed d0m=I0m. The rationale for this decision is that NDMA is in the vapor phase in both ETS and mainstream smoke. We therefore assumed that the pulmonary absorption of NDMA per nanogram inhaled was the same for mainstream smoke and ETS. (This assumption may be inadequate, since NDMA is water soluble and thus will dissolve in mucous membrances before reaching the lungs. Therefore, the fraction of inhaled NDMA that reaches the lungs may well be up to several orders of magnitude greater in active smokers (whose intake is via deep inhalations taken through the mouth) than in nonsmokers (whose intake is largely via shallow inhalations taken through the nose). If so, our estimate of d0m would need to be reduced by

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Environmental Tobacco Smoke: Measuring Exposures and Assessing Health Effects the appropriate factor. We have not made any such adjustment here. d0m for RSP was calculated as follows. In Chapter 7 it was calculated that the amount of tar deposited in the lungs after 8 hours of ETS exposure would be about 0.005%–0.26% of that deposited in the lungs of an active smoker of 20 cigarettes containing 14 mg tar each. Thus, the upper limit of the range for d0m (in terms of 20 mg tar cigarettes) equals (14/20)×0.26×10−2× 20×1.07/8=8.2×10−5=0.005. The total range is 0.0001=0.005. 5. In what follows we estimate for each of the constituents NDMA, BaP, and RSP the number of cigarettes that would have to be actively smoked to deliver to the smoker a (biologically effective) pulmonary dose of the constituent equal to the daily pulmonary dose (attributable to ETS) of a nonsmoker married to a nonsmoking spouse. This number we will call . The * as a symbol serves to distinguish this definition of d0 from that in Section D-2. for a given constituent is equivalent to d0 as defined in Section D-2 if, as assumed in Table D-4, the constituent is the active lung carcinogen in ETS and mainstream smoke or, more generally, if for the constituent is equal to d0 for the unknown active carcinogen. For the constituents RSP, BaP, and NDMA we first estimated the difference between the total pulmonary dose attributable to a single actively smoked nonfilter cigarette and the fraction of that pulmonary dose attributable to the directly inhaled mainstream smoke. This difference includes contributions from the plume of sidestream smoke, the plume of exhaled mainstream smoke, and the ETS subsequently derived from the plumes of sidestream and exhaled mainstream smoke. We shall call this difference the nonmainstream (pulmonary) dose of the constituent. How does the magnitude of the nonmainstream (pulmonary) dose to a smoker compare to the pulmonary dose of the constituent absorbed by a nonsmoker without a smoking spouse in the Wald and Ritchie study (1984) during that nonsmoker’s 1.07 hours of daily exposure? We have no empirical data that directly bear on this question. Nonetheless, we shall assume that the ratio, f, of the dose to the smoker from the nonmainstream smoke of a single cigarette to the daily dose (attributable to ETS) to a nonsmoker with a nonsmoking spouse is between 0.1 and 2. We believe the ratio could be as high as 2 because the active smoker is much more likely to directly inhale the highly concentrated plumes of sidestream and exhaled mainstream smoke. (In fact, the ratio could possibly be a

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Environmental Tobacco Smoke: Measuring Exposures and Assessing Health Effects good deal higher than 2.) This ratio could be as low as 0.1 if active smokers rarely directly inhale the plumes of smoke and during the hour in which a nonsmoker with a nonsmoking spouse is exposed to ETS, the average smoker density is 4, with each smoker smoking 2.5 cigarettes per hour. (This is a rather high smoker density and 0.1 may therefore be somewhat too low an estimate.) It is a straightforward algebraic exercise to show that the relationship between and d0m is The minimum of the range of d0 (equivalently, ) values given in Table D-4 (for each constituent) was computed by plugging into the above formula the minimum of the range of d0m estimated in step 4, and f=2. The maximum of the d0 range in Table D-4 was computed by plugging in the maximum of d0m and f=0.1. The ranges calculated for essentially equal those for d0m, with the exception that both endpoints of the d0m range for NDMA were reduced by approximately 40% and the upper endpoint for BaP was reduced 25%. Remark 12: Dosimetry Based on Urinary Nicotine or Cotinine In this remark we consider whether it is reasonable to take the ratio of urinary nicotine (or cotinine) in nonsmokers to that in active smokers as a proxy for the ratio of the biologically effective dose (attributable to ETS) of the active lung carcinogen in nonsmokers to the biologically effective dose in active smokers. In aged ETS, nicotine is largely in the vapor phase. Nicotine is water soluble. Thus, presumably most of the nicotine in aged ETS dissolves in the mucous membranes of the upper airways and diffuses directly into the bloodstream. Thus, little of the inhaled nicotine from aged ETS reaches the lower respiratory tract. Therefore, urinary and blood nicotine in nonsmokers should roughly reflect the total amount of inhaled nicotine. In contrast, nicotine in mainstream and sidestream smoke and in fresh ETS is largely in the particulate phase. Therefore, most of the nicotine directly inhaled in mainstream smoke by a smoker reaches the lower respiratory tract (and from there the bloodstream) since the deposition fraction for particulates in mainstream smoke is 70% with most deposition occurring in the lower respiratory tract.

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Environmental Tobacco Smoke: Measuring Exposures and Assessing Health Effects Therefore, if (1) the true carcinogen is in the vapor phase in both ETS and mainstream smoke, (2) the true carcinogen is in the particulate phase in both ETS and mainstream smoke, or (3) the true carcinogen is in the particulate phase in mainstream smoke, the vapor phase in ETS, and is, in addition, water soluble (so that the total dose of the carcinogen from ETS greatly exceeds the pulmonary dose), then serious questions must be raised about the appropriateness of the ratio of urinary nicotine (or cotinine) in nonsmokers to that in active smokers to approximate the ratio of the biologically effective lung dose of the active carcinogens in nonsmokers to the lung dose in active smokers. Remark 13: Estimating Lung Cancer Deaths Attributable to ETS Among Lifelong Nonsmokers in 1985 As in the Garfinkel et al. (1985) study, we use “exposed” to mean ever-“exposed”, since one cannot calculate a population attributable number from case-control studies in which individuals who are ever-“exposed” but not currently-“exposed” are excluded. If we assume that Assumption 1a and Equation D-5 hold with c(70)=3, then RR(70|E) and RR(70|Ē) are 1.54 and 1.18, respectively, based on a summary rate ratio of 1.3. We would then need to assume, for example, that RR(t|E) and RR(t|Ē) do not depend on t. Using this approach we obtain an attributable number of 2,010 in nonsmoking women. In contrast, the naive approach, which ignores the ETS exposure of “unexposed” individuals by assuming RR(70|E)=1.3 and RR(70|Ē)=1.0, gives an attributable number of 1,150. The second approach supposes that assumptions of Method 2 in Section D-2 hold. We then choose a value for exposure history (a, b, c) and β4/β1 which, given that γ(70|E)/γ(70|Ē)=1.3, allows us to calculate β1d0 from Equation D-10. Knowledge of β1d0, then, allows us to calculate, from equation D-9, RR(t|E) and RR(t|Ē) for all t (not just t=70). The third approach is to assume that the first assumptions under Method 2 concerning the multistage cancer model hold but not to assume that RR(70|E)/RR(70|Ē)=1.3. We then must select a value of β1 and d0 in order to estimate β1d0 and, given (a, b, c) Remark 14: Estimating the Lifetime Risk of Lung Cancer Due to ETS where λ(u) is the all-cause mortality rate in 1985 among nonsmoking women of age u (and we are following the standard convention of using current, i.e. 1985, mortality

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Environmental Tobacco Smoke: Measuring Exposures and Assessing Health Effects rate). We estimated λ(u) for female nonsmokers by multiplying the all-cause age-specific mortality rates (for female nonsmokers) given in Hammond (1966) by the ratio of the overall U.S. age-specific female death rates in 1985 (all smoking categories) to those rates in 1962. Furthermore, γEXCESS(t)=γ0(t)[RREXCESS(t)], where γ0(t) is the incidence of lung cancer death at t in the absence of all exposure, and RREXCESS(t) is the excess relative risk for lung cancer due to exposure history M. γ0(t)=[1−AF(t)]I0(t) where AF(t) and I0(t) are as defined above. From Equation D-9 we can obtain an estimate of RREXCESS(t)= RR(t)−1 for given values of β1d0 and β4/β1 and choice of exposure history M. It follows that, under the assumption that the observed rate ratio of 1.3 is causal, we can then obtain an estimate of AF(M) for t0=45 for each choice of exposure history (a, b, c) and value of β4/β1, since, using Equation D-10, we obtain an estimate of β1d0 from which, in turn, we obtain an estimate of AF(t) and RREXCESS(t). Remark 15 In estimating AF(M) in ex- and current smokers, RREXCESS(t) can be estimated from Equation D-9 for a given value of exposure history (a, b, c), β4/β1, and β1 under the assumption that the rate ratio of 1.3 is causal. (Knowledge of β1 is necessary so that we can estimate from Equation D-10 the value of d0 rather than simply β1d0.) γ0(t) is estimated as for nonsmokers. To estimate the all-cause mortality rate among exsmokers and continuing smokers we used the data in Hammond (1966) as described for nonsmokers, except for smokers of 20 cigarettes per day we used an average of the age-specific all-cause mortality rates in Hammond for smokers of 1–19 and >19 cigarettes per day; and for exsmokers we used both their smoking rates while smoking and the number of years since quitting (as a time-dependent covariate) to enter Hammond’s table at the proper place. Missing values in Hammond’s table were filled in by linear interpolation or extrapolation. Remark 16 Under Assumption 1a, RREXCESS(t) would be the same for exsmokers and nonsmokers who had the same history of exposure to other people’s cigarette smoke. But if we assume that cigarette smoke affects two stages of a multistage cancer model, then, for an exsmoker, the quadratic terms in Equation D-9 cannot be ignored. As such, a small increment in dose due to breathing other people’s cigarette smoke will have a larger absolute effect

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Environmental Tobacco Smoke: Measuring Exposures and Assessing Health Effects on the age-specific-mortality rate of the exsmoker than of the nonsmoker. Effects of Bias We now consider the following three questions. In deriving our summary estimates of 1.3 we amalgamated studies that compared ever-“exposed” to never-“exposed” subjects with studies that compared currently-“exposed” to never-“exposed” subjects. Does this introduce an important bias? In Remark 17 below, we show that it does not. Second, under the assumption that our multistage model is correct, Assumption 1a is false, since Equation D-8 has a quadratic dose term. Nonetheless, for calculating the true relative risk in “exposed” and “unexposed” subjects, is Assumption 1a an adequate approximation? Third, should case-control studies of the relationship between childhood ETS exposure and lung cancer have greater power to detect an ETS effect than case-control studies of adult ETS exposure? In particular, does the failure of Garfinkel et al. (1985) to find an effect of childhood exposure cast doubt on the validity of our 13 epidemiologic studies of adult ETS exposure? We will show in Remark 19 that when one takes into account the inevitable misclassification of childhood ETS exposure occurring some 60 years previously, the observed relative risk expected from a case-control study of childhood ETS exposure could be as low as 1.01 and would be no greater than 1.3. Thus, it is not surprising Garfinkel et al. found no effect of childhood exposure. Remark 17 It is clear that the same causal parameter is not being estimated in studies in which the “exposed” group is ever-“exposed” as in studies in which the exposed group is currently-“exposed” individuals. Yet, our summary value of 1.3 was based on amalgamating estimates of RR(t|E)/RR(t|Ē) from these two different types of studies. To estimate the magnitude of the bias associated with this amalgamation, we proceeded as follows. Consider studies with exposure history of the form (a,b,1). For each choice of (a, b) and β4/β1 we obtain, from Equation D-10, an estimate of β1d0, say, β1d0(a, b, β4/β1), if we can assume RR(t|E)/RR(t|Ē) is 1.3 for such studies. For each β1d0(a, b, β4/β1) we estimated, using Equation D-10, RR(t|E)/RR(t|E) for a study with exposure history (a,b,3). The maximum value of RR(t|E)/RR(t|Ē) estimated in

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Environmental Tobacco Smoke: Measuring Exposures and Assessing Health Effects this way for studies with exposure history (a,b,3) was 1.39 (associated with β4/β1=1.8, of course). Given the confidence interval of (1.12,1.49) reported in Chapter 12 for the amalgamated parameter RR(t|E)/RR(t|Ē), it follows that any bias due to improperly amalgamating these two types of studies will be small compared to sampling error. Remark 18 Conditional on the assumption that our multistage model holds for lung cancer, we can test the adequacy of Assumption 1a. Let and RR′(70|E) be the estimates of β1d0 and RR(70|E) obtained by removing the quadratic term (in β1d0) from the numerator and denominator of Equation D-10. Now, since Equation D-9, modified so that the quadratic term in β1d0 is eliminated, is a linear excess relative risk model, it follows that Assumption 1a is an adequate approximation if the estimates and RR′(70|E) do not differ greatly from the estimates, β1d0 and RR(70|E), based on the unmodified Equation D-10. We therefore estimated max[RR′(70|E)−RR(70|E)] as (a, b, c) and β4/β1 varied. The maximum was 0.05. Thus, the linear approximation of Assumption 1a is probably adequate. Remark 19 We now estimate the maximum and minimum relative risk (at age 70) we would expect to observe in a case-control study of ETS exposure in childhood (controlling for ETS exposure in adult life) under the assumption that our multistage model for lung cancer is correct. To do so, we perform a sensitivity analysis over the possible exposure histories of the “exposed” and “unexposed” study subjects in such a case-control study. In particular, we assume that (1) for all study subjects the exposure rate from ages 20 to 70 years was 2d0; (2) the false-positive and false-negative rates for the exposure “at least one parent smoked” were 0.15 and 0.3, respectively; and (3) exposure rate from 0 to 20 in the truly “exposed” (i.e., among those who did have a smoking parent) to the truly “unexposed” was, in units of d0, one of the following: 1.53 to 0.3, 0.75 to 0.15, 1.0 to 0.6, or 1.0 to 0.05. It only remains necessary to choose values for β4/β1 and β1d0. For each of our three choices of β4/β1, we let β1d0 range over the values found previously (using Equation D-10) as (a, b, c) varied. The maximum relative risk was 1.26, which occurred with exposure rates of 1.53 and 0.3d0 in the exposed and unexposed, respectively, β4/β1=0.0124, and the value of β1d0 (computed using Equation D-10) based on (a, b, c)=(1,2,3). The minimum relative

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Environmental Tobacco Smoke: Measuring Exposures and Assessing Health Effects risk was 1.01. Even when we unrealistically assumed that both the false-positive and false-negative rates for exposure misclassification were 0, the maximum relative risk was only 1.51. Thus, it is not surprising that Garfinkel et al. (1985) failed to detect an effect of childhood exposure in his case-control study. References Brown, C.C., and K.C.Chu. Use of multistage models to infer stage affected by carcinogenic exposure: Example of lung cancer and cigarette smoking. J. Chron. Dis., in press. Correa, P., L.W.Pickle, E.Fontham, Y.Lin, and W.Haenszel. Passive smoking and lung cancer. Lancet 2:595–597, 1983. Coultas, D.B., J.M.Samet, C.A.Howard. G.T.Peake, and B.J.Skipper. Salivary cotinine levels and passive tobacco smoke exposure in the home. Am. Rev. Respir. Dis. 133:A157, 1986. Day, N.E., and C.C.Brown. Multistage models and primary prevention of cancer. J. Natl. Cancer Inst. 64:977–989, 1980. Doll, R.D., and R.Peto. Mortality in relation to smoking: 20 years’ observations on male British doctors. Br. Med. J. 2:1525–1536, 1976. Doll, R.D., and R.Peto. Cigarette smoking and bronchial carcinoma: Dose and time relationships among regular smokers and lifelong non-smokers. J. Epidemiol. Comm. Health 32:303–313, 1978. Doll, R.D., and R.Peto. The Causes of Cancer: Quantitative Estimates of Avoidable Risks of Cancer in the United States Today. J. Natl. Cancer Inst. 66:1191–1308, 1981. Friedman, G.D., D.Pettiti, and R.D.Bawol. Prevalence and correlates of passive smoking. Am. J. Public Health, 73:401–405, 1983. Garfinkel, L. Time trends in lung cancer mortality among nonsmokers and a note on passive smoking. J. Natl. Cancer Inst. 66:1061–1066, 1981. Garfinkel, L., O.Auerbach, and L.Joubert. Involuntary smoking and lung cancer: A case-control study. J. Natl. Cancer Inst. 75:463–469, 1985. Hammond, E.C. Smoking in relation to the death rates of one million men and women. Nat. Cancer Inst. Monogr. 19:127–204, 1966. Hirayama, T. Cancer mortality in nonsmoking women with smoking hushands on a large-scale cohort study in Japan. Prev. Med. 13:680–690, 1984. Hirayama, T. Non-smoking wives of heavy smokers have a higher risk of lung cancer: a study from Japan. Br. Med. J. 282:183–185, 1981. Jarvis, M.J., M.A.H.Russell, C.Feyerabend, J.R.Eiser, M.Morgan, P. Gammage, and E.M.Gray. Passive exposure to tobacco smoke: Saliva cotinine concentrations in as representative population sample of nonsmoking schoolchildren. Br. Med. J. 291:927–929, 1985. Jarvis, M.J., H.Tunstall-Pedoe, C.Feyerabend, C.Vesey, and Y.Saloojee. Biochemical markers of smoke absorption and self reported exposure to passive smoking. J. Epidemiol. Comm. Health 38:355–339, 1984. Lubin, J.H., W.J.Blot, and F.Berrino, et al. Patterns of lung cancer risk among filter and nonfilter cigarette smokers. Int. J. Cancer 33:569–576, 1984.

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Environmental Tobacco Smoke: Measuring Exposures and Assessing Health Effects Matsukura, S., T.Taminato, N.Kitano, Y.Seino, H.Hamada, M.Uchihashi, H.Nakajima, and Y.Hirata. Effects of environmental tobacco smoke on urinary cotinine excretion in nonsmokers. N. Engl. J. Med. 311:828–832, 1984. Trichopoulos, D., A.Kalandidi, and L.Sparros. Lung cancer and passive smoking: Conclusion of Greek study. Lancet 2:677–678, 1983. Wald, N.J., and C.Ritchie. Validation of studies on lung cancer in nonsmokers married to smokers. Lancet 1:1067, 1984.

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