1 Health Sciences Research, Mayo Foundation, Rochester, MN.
2 Division of Epidemiology, University of Minnesota, Minneapolis, MN.
Received for publication July 30, 2001; accepted for publication May 24, 2002.
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ABSTRACT |
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body mass index; cohort studies; fat body; histology; lung neoplasms; risk factors; women
Abbreviations: Abbreviations: BMI, body mass index; ICD-O, International Classification of Diseases for Oncology; SEER, Surveillance, Epidemiology, and End Results.
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INTRODUCTION |
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The three main histologic subtypes of lung cancer include squamous cell carcinoma, adenocarcinoma, and small cell carcinomas (7), all of which arise from epithelial cells. Incidence rate patterns of the three subtypes differ over time and support the concept of differing mechanisms of lung carcinogenesis for the various histologic types (8), although these differences over time may be partly due to changes in diagnostic and pathologic methods (8). In the 19731977 Surveillance, Epidemiology, and End Results (SEER) program report, squamous cell carcinomas were found to be twice as common as adenocarcinomas in US males, while adenocarcinomas were slightly more common in women (7). By the mid-1980s, the excess rate of squamous cell carcinomas was only 40 percent in men, while adenocarcinomas were 50 percent more common in women (7).
The goals of the present analysis were to update earlier Iowa Womens Health Study analyses to include 7 additional years of follow-up and to determine whether anthropometric factors were differentially associated with histologic types of lung cancer. BMI and BMI at age 18 years were included to investigate the association of overall body fat with lung cancer incidence, waist/hip ratio and waist circumference were included to examine the association of central body fat, and height was included as a "control" anthropometric factor not hypothesized to influence lung cancer. Earlier studies have suggested that adenocarcinoma of the lung is less closely associated with smoking (7) than are squamous and small-cell lung cancer and has the highest probability of being influenced by non-tobacco-related causes, including hormonal effects of body fat distribution. Thus, our a priori hypothesis was that adenocarcinoma of the lung was the most likely to be associated with high levels of abdominal fat.
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MATERIALS AND METHODS |
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Rates of lung cancer among responders were somewhat lower than those among nonresponders (10). Self-reported questionnaire items included reproductive factors, height, current weight, educational level, medication use, alcohol consumption, smoking habits, and family history of cancer. Environmental tobacco exposure was not ascertained. Also included was a semiquantitative food frequency questionnaire with 127 food items and other questions related to nutrient intake. Physical activity was ascertained through three questions about participation in leisure exercise and, if any, the frequency of moderate-intensity and high-intensity activities. These responses were combined to create a three-level activity score (low, medium, and high) that has been shown to be predictive of coronary artery disease (11). Body circumferences (waist and hips) were measured by using a paper tape measure mailed with the questionnaire. Measurements obtained by this method have been shown to be both accurate and reliable (12). Waist/hip ratio (waist circumference/hip circumference) and BMI (weight (kilograms)/height (meters) squared) were calculated from these data. Follow-up questionnaires were mailed in 1987, 1989, 1992, and 1997 to update vital status and current address. Deaths were ascertained by annual linkage to the Iowa death certificate database, supplemented by linkage to the National Death Index.
Exclusions and cancer incidence
Women reporting, at baseline, previous cancers other than skin cancer (n = 3,830) were excluded. The total cohort at risk for incident lung cancer included 38,006 women. When analyses included dietary variables, women were considered to have given "improbable" responses and were therefore excluded if 30 or more items on the food frequency questionnaire were left blank or if their responses resulted in extreme energy intake values (<600 or 5,000 kcal/day) (n = 2,785). Incident lung cancer cases occurring in 19861998 were identified through the State Health Registry of Iowa, part of the National Cancer Institutes SEER program (13). A computer match was performed annually between the list of cohort members and the records of Iowans for whom incident cancer was listed in the registry by using combinations of first, last, and maiden names; zip code; birth date; and Social Security number. Data regarding the diagnoses and pathology were abstracted by registry personnel from medical records and pathology reports according to SEER protocol (13) and were coded by using the International Classification of Diseases for Oncology (ICD-O), second edition (14). The histologic subtypes recorded in the cancer registry were grouped as follows: small cell lung cancer (ICD-O codes 80418044), squamous cell lung cancer (ICD-O codes 80508076), and adenocarcinoma of the lung (ICD-O morphology codes 81408380 and 84808481). Those lung cancer cases not considered to belong to these three categories were not included in the histologic subtype analyses.
Analysis
The length of follow-up for each woman in the study was calculated as the time from completion of the baseline questionnaire to the date of lung cancer diagnosis, date of a move from Iowa, or date of death. If none of these events applied, follow-up continued through December 31, 1998. Relative risks and 95 percent confidence intervals were calculated with Cox proportional hazards regression models. We first examined the risk of lung cancer by using a set of predetermined potential confounding variables. These variables included smoking status, pack-years of smoking, physical activity score, educational status, beer consumption, alcohol consumption, dietary fat intake, saturated fat intake, total energy intake, and intake of whole grains, fruit, and vegetables.
All variables found to be significantly associated with lung cancer were included as covariates in subsequent analyses. We then assessed the overall association of lung cancer separately with each of the following anthropometric measures: BMI, waist/hip ratio, BMI at age 18 years, waist circumference, and height. Each variable was categorized on the basis of quintiles, and relative risks were calculated by using the lowest category as the referent group. We calculated tests for trend by ordering the categories from lowest to highest and including this variable as a linear variable in a proportional hazards regression model.
Next, we evaluated whether smoking modified the effect of the anthropometric measures on lung cancer risk by checking the statistical significance of the interaction between these measures and smoking status. For ease of interpretation, the original set of main effects and interactions was then multiplied by a contrast matrix that allowed for direct comparison of anthropometrics within each level of family history but that did not change the overall fit of the model.
The main effects of anthropometrics were then evaluated separately for the following three lung cancer cell types: small cell carcinoma, squamous cell carcinoma, and adenocarcinoma. In these analyses, the outcome variable was incident lung cancer of the specific cell type of interest, and all other types of lung cancer were considered censored observations. We determined whether risk ratios for exposures of interest differed according to histologic type by using a competing risk form of Cox proportional hazards analysis (15). This approach enabled us to specifically model and test the unordered interaction between a given risk factor (modeled as a covariate) and histologic type (included as a stratum variable).
For all Cox proportional hazards analyses, survival was modeled as a function of age, since age is a better predictor of lung cancer risk than is length of follow-up time in this study (16). Each model included as covariates the statistically significant, potentially confounding variables mentioned earlier. To account for the effects of smoking as completely as possible, analyses also included both pack-years (modeled as a continuous spline function) and smoking status (current, former, never) as covariates.
We were concerned that fitting separate models for each of the five anthropometric measures would not adequately account for the effects of the other anthropometric variables. For instance, the association between lung cancer risk and BMI at age 18 years could be confounded by current BMI. Thus, we fit additional models, further adjusting for a subset of the anthropometric measures. Many anthropometric variables were highly correlated with one another (table 1). As a result, variables were individually selected for each model after screening for colinearity by using Spearman rank correlations. When two or more highly correlated variables were included in the same model, special care was taken to examine goodness of model fit and precision of parameter estimates. Specific adjustments for each anthropometric exposure are given as footnotes to the tables in this paper. All statistical tests were two sided, and all analyses were carried out by using the SAS (SAS Institute, Inc., Cary, North Carolina) and S-PLUS (Mathsoft, Inc., Seattle, Washington) software systems.
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RESULTS |
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In general, associations of factors with lung cancer that were evident in previous Iowa Womens Health Study cohort analyses continued to be found in this analysis. For example, smoking, pack-years of smoking, and beer consumption were associated with increased lung cancer risk (table 2). Increasing physical activity was associated with decreased risk of subsequent lung cancer. Higher fruit intake per week was associated with lower risk of lung cancer (p-trend = 0.03). No other dietary factors examined were associated with risk (data not shown). The associations with fruit (17) and beer (18) are consistent with previous reports from this cohort. Because of the method of statistical modeling used, information on the association of age with lung cancer risk is not presented in table 2. However, increasing age was associated with increasing risk of lung cancer, as expected. Compared with women aged 5559 years, women aged 6064 or older than 65 years had a 10 percent or 30 percent increased risk of lung cancer, respectively.
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DISCUSSION |
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Unlike the previous analysis, which concluded that "the inverse association of body mass index with lung cancer can be explained by smoking status" (1, p. 600), we found that BMI remained significantly inversely associated with lung cancer after multivariate adjustment. In addition, because cigarette smoking is associated with decreased body weight (19), we examined whether the inverse BMIlung cancer association was explained by confounding from cigarette smoking. This did not appear to be the case, because the association between BMI and lung cancer was of the same magnitude even for women who had never smoked cigarettes. In the earlier report (1), although women never smokers in the highest tertile of BMI were 50 percent less likely to develop lung cancer compared with women in the lowest tertile of BMI (relative risk = 0.68), the estimate did not exclude 1.0 and the test for trend was not statistically significant. In case some of the difference between the two reports was caused by the use of different BMI category cutpoints (tertiles instead of quintiles), we recalculated the estimates by using the same category cutpoints. On the basis of these recalculations, women never smokers in the lowest BMI tertile were half as likely to have developed lung cancer compared with women in the highest BMI tertile (relative risk = 0.52, 95 percent confidence interval: 0.28, 0.95; p-trend = 0.03). Women in the middle tertile were at similarly decreased risk of lung cancer (relative risk = 0.58, 95 percent confidence interval: 0.33, 1.02). Other differences between this report and the previous one include 363 additional cases and 7 additional years of follow-up.
It is possible that the inverse association with high BMI becomes gradually evident with time so that, although not statistically significant earlier, after additional follow-up and with the increased statistical power from additional cases, the effect becomes apparent. A similar latency was seen in a cohort of Finnish men (4); the protective effect of increasing levels of BMI became more distinct after 10 years of follow-up.
As with any multivariate analysis, one must be careful to understand the correlation between variables. In the current study, the correlation of anthropometric indices ranged from 0.1 to 0.8, raising two major issues. First, when multicollinearity exists, sampling variability of parameter estimates tends to be larger (20). In the initial multivariate models, prior to adjustment for other anthropometric factors, standard errors for the waist circumference parameter estimates ranged from 0.13 to 0.14. After adjustment for other anthropometric variables, the standard errors were larger than before but still quite reasonable (standard errors ranged from 0.14 to 0.22). A second implication of multicollinearily is that the individual parameter estimates cannot be interpreted as estimating the effect of the exposure on the outcome risk while all other covariates are held fixed. Because correlated variables vary simultaneously, one must consider the variables at the same time. BMI should be included in the multivariate model because it fits the classic definition of a confounder for the relation between waist circumference and lung cancer risk, in that it is strongly associated with both the exposure (waist circumference) and the outcome (lung cancer). Indeed, the interpretation of the waist circumference effect (made within the constraints of the second implication defined above) is intriguingthat an association exists between lung cancer risk and location of adiposity even after accounting for the amount of adiposity.
An elevated risk of lung cancer associated with lower levels of BMI has been reported in both case-control (2, 3) and cohort (4, 5) studies. More recently, however, a case-control study among former (>10 years since cessation of smoking) and never smokers found that persons in the upper octile of BMI had a twofold greater risk of lung cancer (6). These authors explained the results as due to the large number of nonsmokers (n = 188) included in the analyses. Although the present study included about only half that number (n = 81), our estimates appear quite stable and support a protective role of high BMI against lung cancer. Unfortunately, we could not examine the impact of environmental tobacco exposure on this association.
Another important finding of our study was that the highest level of waist circumference was positively associated with risk of lung cancer, but only after adjustment for BMI. Conversely, waist/hip ratio was not associated with lung cancer before or after adjustment for BMI. This difference may be explained by the fact that waist circumference is more strongly associated with BMI than is waist/hip ratio; therefore, one would expect the association with waist circumference to show the largest increase after adjustment for BMI. Other than the previous report from the Iowa Womens Health Study that used waist/hip ratio as an indicator for centralized versus peripheral fat (1), we know of no other group that has examined risk of lung cancer associated with fat distribution. This is the first known report of a positive association between waist circumference and risk of lung cancer. However, it is quite likely that this association is at least partly due to residual effects of cigarette smoking; the association was strongest among current smokers, and cigarette smoking has been shown to be associated with increased levels of abdominal fat (19). It is also possible that a higher waist circumference in a smoker is a marker for greater levels of smoking and other poor lifestyle habits that might contribute to carcinogenicity. Examples of such poor habits might include poor levels of physical activity, poor diet, and infrequent preventive health care visits.
One of the primary goals of this study was to examine the association of anthropometric factors stratified by histologic type. As far as we are aware, this is the first report of such an analysis. Quintiles of BMI were inversely related to risk of all histologic subtypes of lung cancer. Women in the highest (vs. lowest) quintile of BMI were 40 percent less likely to develop small cell carcinoma or adenocarcinoma of the lung and more than 75 percent less likely to develop squamous cell carcinoma. The inverse association of BMI was still evident for adenocarcinoma of the lung, even among never smokers. We were unable to stratify the analysis by cigarette smoking for all histologic subtypes because there were too few cases of squamous and small cell histologic types among nonsmokers to permit such an analysis. Thus, we were not able to completely eliminate the possibility that the decreased risk was due to the residual effect of cigarette smoking on BMI. However, on the basis of the data for all lung cancers, this possibility seems unlikely.
The effect of large waist circumference was also examined across specific histologic subtypes. Earlier studies had suggested that adenocarcinoma was least closely associated with smoking (7) and would have the highest probability of being influenced by non-tobacco-related causes, including hormonal effects of body fat distribution. Thus, we expected a priori that adenocarcinoma of the lung was most likely to be associated with a high level of abdominal fat. However, we found that waist circumference was associated with small cell and squamous cell carcinoma but not with risk of adenocarcinoma of the lung.
We must acknowledge that multiple factors were examined and that these results may reflect a chance association. However, the finding is not without biologic plausibility. The physiologic effects of high levels of abdominal fat may exacerbate the toxic pathways leading to squamous and small cell carcinoma of the lung. It has been hypothesized that all lung cancers arise from similar cells but that the specific promoters present at the time in the surrounding cellular environment determine which histologic subtype actually develops (8). Cigarette smoke is known to increase abdominal fat (21), and there are numerous known physiologic effects of abdominal adiposity (22). For example, it has been linked to increased levels of free fatty acids, insulin, and unbound androgens and estrogens. It is unclear whether any of these effects or some other physiologic effect of abdominal adipose might be important in promoting cells to develop into squamous or small cell carcinoma rather than adenocarcinoma. However, it is interesting that squamous and small cell carcinomas both tend to develop centrally in the lung, whereas adenocarcinomas tend to be located in the peripheral lung tissue. It may be that some factor linked to high levels of abdominal fat is found primarily in the central portion of the lung and promotes carcinogenesis in initiated cells toward either small cell or squamous cell carcinoma.
Both waist circumference and waist/hip ratio are indices of central adiposity. However, in this analysis, only waist circumference was associated with risk of lung cancer overall or for a particular histologic subtype of lung cancer. This finding was somewhat surprising, since waist/hip ratio was associated with risk of lung cancer in this cohort in the earlier analysis (1). One possible explanation may be that waist circumference has been shown to be a more accurate estimator of central adiposity than waist/hip ratio (23, 24). The other anthropometric factors examined, height and BMI at age 18 years, were not associated with risk of lung cancer in general or with histologic subtypes of lung cancer.
For this study, cases of lung cancer were collected by the State Health Registry of Iowa, part of the National Cancer Institutes SEER program (13). Although desirable, no centralized pathology review was feasible. However, one of the SEER registries conducted a pathology review of a subset of lung cancer cases from 1970 to 1972 and from 1980 to 1981 (25) and found that, for the cell types discussed in this paper, there was generally good agreement between the initial pathology reading and the review reading. A strength of this study is the homogeneity of the at-risk population included. Nearly all were postmenopausal women, which is an advantage when examining factors such as body weight and fat distribution that change around and after menopause. We did not collect information on exposure to secondhand smoke and were unable to control for it in these analyses.
In conclusion, this study raises the possibility that waist circumference may be differentially associated with histologic subtypes of lung cancer. There were too few cases among nonsmokers to eliminate the possibility that these results were due to the residual effects of smoking. However, these results may reflect increased activation of chemicals from cigarette smoke in those who have an increased waist circumference.
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ACKNOWLEDGMENTS |
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NOTES |
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REFERENCES |
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