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Smoking tntersetions with Occupation and Di.t / 387 lung cancer in both nten and women in Illrayallia's large-scale prospective study (Hirayama 1979) in relation to smoking an&avoidance of green-yellow vegetables, which was considered to be the risk factor of interest. The observed RR for men was close to the additive, whereas for women the observed RR exceeded both the additive and~ multiplicative models. The relationship between consumption of fruit and fruit juice was examined by Wang and Hammond (1985) using data from the American Cancer Society's 12-year follow-up study. Figure 7 shows the relative risk for lung cancer according to the number of days per week that fruit or fruit juice was consumed, with additional information on the regular use of vitamin supplements. The left half of the figure refers to all subjects while the analysis in the right half is restricted to current smokers of one pack or more per day: Lack of consumption of fruiti or fruit juice was seen to be a powerful risk factor for lung cancer in both groups. To examine the interaction between fruit consumption and smoking, however„it was necessary to recompute the RRs in relation to a common reference group. Figure 8 shows the result of this recalculation. Meavy smokers who consumed little or no I'ruit or juice 2•oi ALL SUBJECTS CURRENT SMOKERS OF 1.91 2 132 1.27 ONE PACK OR MORE DAILY 4r ::01~ I I' I II I I.o,~ I ~ ~, Io.l" r-__ID0VRUMNPLI.S: YN Y N Y N. Y' N YN Y N 0-2 3-4 5-7 0-2 3-4 5-7 FRUIT AND JUICE CONSUMPTION, DAYS/WEEK Figure 7 Relative risk for lung cancer among nearly 500;000 men survcycd~by American Cancer Society and'followed up 1960-1966„accurding to number of tunm pcr wcek subjcctscunsumed fruits or fruit juices, and whether or not subjects took regular vitamin supptements. Data from Wang, and Hammond (1985).

388 J S. 0. Stalmsm 0.0 FRUITS OR FRUIT JUICES DAYS PER WEEK ..~~. o-a ~. s. r H9 ~ 21-39 CIGARETTES CURRENTLY SMOKED PER DAY NON- SMOKER9 40+ Fiyure 8 Standardized mortality ratio for lung cancer among the same subjects as in Figure 7, according to number of cigarettes smoked per day (current smokers onty),and the number of times per week subjects oonsumed fruits or fruit juices. The reference group is men who smoked 20 cigarettes per day and who consumed fruits or juice 3-4 times per week. had RRs higher than those of frequent consumers. The joint risk was slightly greater than either additive or multiplicative, which in fact were equal~to each other because the relative risk in nonsmokers was indcpendent of the second factor (fruit and juice conswnption). DISCUSSION Table 7 compares the predictions front additive and multiplicative models in a number of the exaluplos eitcd'above, In four oll the studies cited, including two ufl asbestos-exposed workers, the multiplicative model seemed to predict the effect of jpin[ exposure. ln one study (avoidance of green-yellow vegctablcs; females oniy), the additive model appeared bests In two studies, the observed RR lay in bethween the two models, and in two others the prediction far exceeded evemthe muitiplica- tive model! It is important not to take su& findings too literally. This type of analysis is fairly new and is fraught with many methodological pitfalls. The most serious

Table 7 Additive Versus Multiplicative Models in Studies of Smoking, Other Exposures, and Cancer Exposures Outcome Observed Predicted References Smoking Other _ Ever smoked Asbestos insulator Lung cancer mortality Smoked 2+ packs/day Shipyard worker Lung cancer RR Ever smoked Underground miner Lung cancer RR Daily smoker Matcrial metal worker Cancer mortality Smoked 30+ cigarettes Occupational exposure to per day likely carcinogens Smoked 40+ cigarettes Drank 10+ whisky eyuiv per day alents/day Daily smoker Lack of grcen-ycllow vege- tables Smoked 40+ci6arettes 1=ruit or juice 0-2 tir»es/ wcek A.M., additive model; M.!st., multiplicative model Lung cancer mortality Stomach cancer mor- tality Lung cancer RR Oral cancer RR Lung cancer mortality, male Lunc cancer mortality, female Lung cancer RR A.M. M.M. 601.6 169.7 633.6 21.7 11.5 22.7 Hammond et al. t1979) Blot and Fraumeni (1981) 40.6 11.9 40.7 Damber and Larsson (1985) 851.7 496.8 497.5 Hirayama (1981) 142.1 127.3 258.2 Hirayama (1981) 400.3 244.3 264.9 Hirayama (1981) 20.0 12.5 27.5 Pastorino et al. (1984) 104.7 30.2 185.6 Mashberg et al. (1981) 79.5 84.1 147.8 Hirayanu (1979) 33.9 24.0 27.1 Hirayama (1979) 24.0 20.3 20.3 American Cancer Society (unpubl.)

390 /'S. D. Ste4lman problem~ is classification of exposure. Figure 9 shows the distribution of smoking and alcohol consumption in mouth cancer cases and controlfr reported by Wynder and Stellmam(1977). These exposures are highly correlated so that while any large study can be expected to observe statistically usefull numbcrs of nundrinking non- smokers and heavy-drinking heavy smokers the number of heavy-drinking non- smokers will invariably be very small (and subjects falling into that category by self: report possibly unreliable), making it difficult to estimate the parameter a in Table 1. Misclassification of just a few subjects can lead to a large bias in a, as well as in the predictions of the models. In such cases it is prudent to rely on qualitative examination of smoking- and second-factor specific rates or risks, as in the figures,, and not put too much weight on models. On the other hand, in such clear-cut cases as asbestos where there is no doubt as to the synergistic effect (Frank 1979), such information is of tremendous public health importance and is vital for establishing prevention strategies. The most challenging,task of all is to collect the needed data in the fusGplace. Table 8 shows the number of epidemiologic studies of tobacco-related diseases that ALCOHOL CONSUMPTION, OZ. Q! nMne„Occosanor ® 7.10c, '. a 10 0 12% . 2)~. 1t6~. 31 ~ 250 i2Q I t'il 22 cr.aM cn. tm..b cow. cor.wa. c.+.. Cax.rs cmn Camw Caxs MOrt-SM0KER5 I -© i- 20 21- 40 41, CIGARETTES SMOKED PER DAY Figure 9 Correlation of alcohol and tobacco consumptiun amung male mouth cancer caus and con- trols. Reprinted, with permission, from Wynder and Stellman (1i977).

Smoking Interactions w7th Occupation and Diet 1391 . Table 8 Smoking lnformation im32 Original Articles in Volume 26 of the Journal of Occu- pational Medicine (1984) on Epidemiology of Tobacco-related Diseases Subject matter Number of studies Number with smoking data Respiratory effects, including pulmonary function and radiographic testing 12 8 All cause SM R 5 0 Lung cancer 2 2 Coronary artery disease I 1 Reproductive outcomes 3 1 Sleep I I Reviews of studies which included tobacco- related outcomes 2' I Surveillance and'corporate medical programs 6 2 Total 32 16 were published in a recent volume (1984) of the Jouriwl of Occupational Medicine according to whether or not smoking information was also collected. Smoking data was available in only 16 of 32 such articles. These omissions were not necessarily the fault of the authors since many studies were based upon historicalisources in which no smoking data were present. Nevertheless, one obviously cannot study interactions between occupation and smoking data unless one has the smoking data first. Without such data, one cannot tell for certain to what extent smoking has in- fluenced the results. Similar remarks may be made concerning dietary studies. Figure 10 shows the distribution of smoking habits among men who scored high, mediuni, and low on scales which measured the frequency of consumption of foods high im vitamins A and C. Data were collected in 1982 by the American Cancer Society as parG of a follow-up study of over 1.2 million men and1women. Men who scored low on the vitamin scale were twice as likely to smoke cigarettes as men who scored! high. It is clear that any analysis of lung cancer mortality (or any other outcome which is thought to be related to vitamin A or C intake) must simultaneously control for cigarette smoking: REFERENCES Blot, W.J. and~ J.F. Fraumeni. 1!981. Cancer among shipyard workers. In Ban- bury report 9: Quantification of occuparional' cancer (ed. R. Peto and M. Schneiderman), p. 37. Cold~ Spring Harbor Laboratory,,Cold Spring Harbor,, New York.

392 / S. 0. Stollmen. VITAMIN-RICH FOODS L or+ M .dium Hiqh, NEVER SMOKED 1 n 76.8 1 27.6 I 31A REGULARLY CURRENT 19.4 14 7 CIGARETTE 27.5 . 45.8 45 5 FORMER 39.0 . CIGARETTE I PIPE/CIGAR 6 6 7.4 9.0 l . L Figure 10 Disttibution of smoking habits, adjusted for age among men ~surveyed in 1982 American Cancer Society follow-up study, according to whether they scored high, medium, or low on a scale which measures frequcncy of consumption of foods rich in vitamins A. and C:, Damber, L. and L.-G. Larsson. 11985. Underground mining, smoking, and lung can- cer: A case-control study in the iron ore municipalities in Northern Sweden. J. Natl. Cancer Inst. 74: 1207, Edling„ C. 1'982. Lung cancer and smoking ia a group of' iron ore miners. Am. J:, Ind: Med. 3: 191. Frank, A.L. 1979. Public health significance of smoking-asbestos interactions. Ann. N:Y: Acad. Sci. 330: 791. Hammond, E.C., l.J. Selikoff, and H. Seidman. 1979. Asbestos exposure, cigarette smoking and death rates. Ann. N. Y. Acad: Sci. 330: 473, Hirayama, T. 1979. Diet and cancer. Nutr. Cancer 1: 67. -. 1981. Proportion of cancer attributable to occupation obtained from a census, population-based, large cohort study in Japan. In Banbury report 9: Quantification of occupational cancer (ed. R. Peto and M. Schneiderman), p. 63l . Cold Spring Harbor Laboratory,, Coli1 Spring Ilarbor, New York.

Smoking Interactions with Occupation and Diet 1'393 Mashberg, A.,, I.. Garfinkrl, and S. Harris. l''tK1 Aic0linllas 3 priinary ri,k fnclur in oral squamous carcinoma. CA:A Cancer Journal jor Clinicians 31 : 146: Olsen, J., S. Sahreo, and U. Fasting. l'985, Interaction of alcohol and tobacco as risk factors in cancer of the laryngeal region. J. l:'piderninl: ('ontntunitv llealth 39: 165. Pastorino, U., F. Berrino, A. Gervasio, V. Pesenti, F. Riholi, and 1'. Crosigpani. 19841. Proportion of lung cancers due to occupational exposure. Int: J. Can- cer 33: 231. Radford, E.P. and K.G. St Clair Renard. 1984. Lung cancer in Swedish iron miners exposed to low doses of radon daughters. N. lingl. J. Med. 310: 1485.. Rothman, K.J. 1976. Causes. Am. J: Epidemiol. 104: 587. -. 1981. Occam's razor pares the choice among statistical models. A m. J. Epidemiol. 108: 347. Rothmani K.J.,, S. Greenland, and A.M. Walker. 1978. Concepts of interaction. Am: J. EpfdernioC 112: 467. Saracci, R. 1977'. Asbestos and lung cancer: An analysis of the epidemiological evidence on the asbestos-smoking interactiont Int. J: Cancer 20- 323. -. 1980: Interaction and synergism. Am. J. t'pidemiol, 112: 465_ Selikoff', 1J. 1981. Constraints in estimating occupational contributions to cur- rent cancer mortality in the United States. In Banbury report 9: Quantifica- tion of occupational cancer (ed. R. Peto and M. Schneiderman), p. 3. Cold Spring I larhor Laboratory, ('old Spring Ilarhori, New York. Stellman, S.D: and L. Garfinkel. 1984. Cancer mortality among woodworkers. Am. J. Ind. Med:, 5: 343. -. 1986. Smoking habits and' tar levels in a new American Cancer Society prospective study of 1,200,000 men and womcn~ J. Nutl: Cancer Inst. 76: 1057. U.S. Department of Health, F.ducation„and Welfare. 1979. Smoking and healtlt:, A report of'thc Surgeon General. U.S. Department uf Healt'h, Hducatiirn, and Welfare, Public Health Service„Office of the AssistanV Secretary for Health, Office on Smoking and Health, DHI?W Publication No. (I'HS)+79-50066. Walker, A.N. and K.1. Rothman. 1972. Models of varying parametric fnrm in ea,se- referunt studies. Ami J, L'prdcnziul. 115: I'9 Walter, S:D. and T.R. Holford. 1981. Additive, multiplicative, and other models for disease risks: Anr, J: lipidcminl: 108: 341. Wang, L.-D. and G.C: Ilammond. 1985. Lung cancer, truit, green salad, and vita- min pills. Chin. Med: J. 98: 206. Wynder, E.L. and S.D. Stelltnan. 1977. Comparative epidemiology' of tobacco- related cancers. Cancer Res. 37: 4608. -. 1979. ItnpacG of long-term filter cigarette usage on lung and! larynx cancer risk. A case-control study. J. Natl: Cancer Inst. 62: 471. COMMENTS TANNENBAUM: Jeff Harris has published a paper showing different! ways of analyzing the cigarette smoking data. I'm sure you're familiar with it. He

394 /, S. D. Stsllman showed that the cancers which appear at am earlier age as a result of risks, don't show up as dramatically when you use age standardization. When you just say what the relative risk is to cigarette smoking, you do not show that the deaths may also be occurring at an earlier age. STELLMAN: That's right. That's a problem, caused by our practice of age stan- dardization. When we do our initial runs we always analyze mortality by 5- year cohorts. But this generates stacks and stacks of paper, and we must have a way of summarizing the age-specific rates. Unless there are major obvious differences between the rates in different cohorts, we generally feel that combining them is a reasonable way of reducing the data; but obviously it can obscure data as well. WINKELSTEIN: I think,, generally speaking, that epidemiologists feel that en, vironmental associations get weaker as age goes up. This is a sort of general rule. Probably the reason is that people get sick in more ways as they get older; so there are more factors at work. Some specific factors are likely to show a lower association. TANNENBAUM: A paper was just published this year from Walter Willett, show- ing that even the consumption of green and yellow vegetables made a differ- ence, even above age 65. WINKELSTEQV: It may, but if you look at the Framingham data, for example, look at smoking in coronary disease, there's no association shown in people who entered the study after, the age of 45-in the cohort study. TANNENBAUM: You may be right. There may be some factors that may not make so much of a difference. For other factors it may make a difference. Actually, maybe that's part of the problem when you're dealing with two variables each of which may have an associated risk. ll guess one of the problems is that~ your model assumes that dose and time are contem• poraneous. STELLMAN: For cohort studies like the ones that we do, that is usually true. But in case-control studies, that is not often true; andl for mosti industrial cohort studies it is not true either. TANNENBAUM: No, but when you showed your analysis of whether it was an arithmetic or a multiplicative model, there were several different ex- posure models which you eoul& have used. I mean, where you have the two variables: A occurred' before B; A occurring at the same time as B; A oc- curring after B. STELLMAN: This is such an idealistic simplification of a terribly complex situa- tion that it's altnost embarrassing to present it that way.

Smoking Interactions with Occupation and Diet7 395 i TANNENBAUM: No, it's interesting. It's an interesting start. Let's take a specific case: wood workers and smoking. Is the number of years that they worked! as woodworkers overlapped with the number of years that they smoked? STELLMAN: Yes. CORREA: I think that the point that you are making is the sequence. If you have a promoter, it will show an effect only if it is present after an initiator and not if it is present before that factor. STELIMAN: For most of the examples that I presented, these exposures were contemporaneous for many years. So it's not like a two-stage skin painting experiment. In the United States, people in the generation we studied started smoking around the age of 20, and they smoked the resU of their lives. They died around 60 an& 70. So we have 40 years of smoking, and we have at least 30 years of the same occupation.. TANNENBAUM: So it is mostly that model, is what you're saying?' STELLMAN: That is correct. HOFFMANN': Do you have data, or are there too few cases on nasal' cancer in wood workers and their smoking haliits?. STELLMAN: Yes, there are data, but too few cases to analyze. The expected number of nasal cancers was 0:03, and the observed number was 2. So, the relative risk was very large, but the confidence limits were very wide. WINKEiSTEIN: I think that the point that Steve [Stellman] made is a very im- portant one. Epidemiologists musti begin to look at the joint action of factors, rather than spending so much of their, efforts on trying to separate out all of the actions.