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Department of Nutrition, Simmons College [T. T. F.]; Departments of Nutrition [T. T. F., E. B. R., W. C. W.], Epidemiology [D. J. H., D. S., G. A. C., E. B. R., W. C. W.], Biostatistics [D. S.], and the Harvard Center for Cancer Prevention [D. J. H., G. A. C., W. C. W.], Harvard School of Public Health; and Channing Laboratory, Department of Medicine, Bringham and Womens Hospital and Harvard School of Medicine [D. J. H., G. A. C., W. C. W.], Boston, Massachusetts 02115
| Abstract |
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| Introduction |
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Human studies on alcohol consumption and risk of BCC are few. Two case-control studies did not find any association between alcohol intake and BCC, possibly because of crude classification of alcohol consumption and lack of adjustment for confounders (6 , 7) . In an unpublished study on fat intake and BCC, we observed a positive association with total alcohol when alcohol was included in regression models. Therefore, we conducted this exploratory analysis to assess the associations among intakes of total alcohol, specific alcoholic beverages, and risk of BCC in two large cohorts of men and women.
| Materials and Methods |
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HPFS.
In 1986, >52,000 male health professionals, between 40 and 75 years of age were recruited for a prospective study of diet, lifestyle, and disease. A questionnaire similar to the NHS has been sent to participants every 2 years. Completion of questionnaire has been >90% at each cycle, and reports of health information were accurate (8)
. Members of the HPFS cohort were eligible for this analysis if they completed the 1986 FFQ with <70 missing items and total energy between 800 and 4,200 kcal/day. Men with any cancer, including any skin cancer, diagnosis at baseline were excluded, leaving 42,617 for analysis.
Assessment of Nutrient Intake
Dietary intake information was collected using a FFQ designed to assess average food intake over the previous year. Cohort members were asked to choose from nine possible responses, from "never" to "more than six times a day" for each food. Alcoholic beverage intake was obtained separately for beer, red and white wine, and liquor, then converted to grams of alcohol per day, with one 12-fluid-ounce drink of beer equal to 13 grams of alcohol, one 4-fluid-ounce drink of red or white wine equal to 11 grams, and one 2-fluid-ounce drink of liquor or spirits equal to 14 grams. Total alcohol intake was obtained by summing the amount from specific alcoholic beverages. Information on intake of vitamin and mineral supplements was also collected.
FFQs were used to calculate total energy intake and intakes of other nutrients. Dietary data were collected in 1986 and 1990 for the NHS, and in 1986, 1990, and 1994 for the HPFS. Previous validation studies among members of the NHS and HPFS cohorts revealed good correlations between alcohol intake from FFQ and food records (9 , 10) . In the NHS, correlations coefficients were 0.81 for beer, 0.83 for wine, and 0.80 for liquor. In HPFS, correlations between dietary records and FFQ were 0.88 for beer, 0.83 for red wine, 0.78 for white wine, and 0.85 for liquor.
Case Ascertainment
The first diagnosis of BCC was obtained by self-report, shown previously to be 96% accurate in a sample of NHS (11)
. In NHS, the duration of case accrual was 8 years (19861994). In HPFS, 84% confirmation of self-reported BCC by medical records was obtained (12)
. The duration of case accrual was 10 years (19861996) in HPFS.
Statistical Analysis
We assessed the effect of total alcohol intake as well as alcohol from each specific beverage. We expressed intakes as cumulative averages to reduce within-person variation and to represent long-term intake. For example, in men, the average of 1986 and 1990 intake was used to model rates between 1990 and 1992, and so forth. The alcohol and BCC association was modeled with multivariate pooled logistic regression with 2-year intervals (13)
and cubic regression splines separately for each cohort. In the NHS, we adjusted for tendency to tan (5 categories), tendency to sunburn (5 categories), natural hair color (5 categories) at age 20, major ancestry (8 categories), and number of lifetime blistering sunburns (4 categories) and the use of sunscreen (yes, no, or "does not go out"), both assessed in 1980. We also adjusted for state of residence at age 15, a proxy for sun exposure in childhood, and current state of residence, a proxy for recent sun exposure. In the HPFS, we adjusted for major ancestry (6 categories), natural hair color at age 18 (5 categories), eye color (3 categories), tendency to burn or tan in adolescence (3 categories), state of residence at age 15, and current state of residence. In both cohorts, we also adjusted for age and BMI. Data from our group and others have shown BMI to have an independent inverse association with BCC (12
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. As failure to return FFQs may be associated with lifestyle behavior related to BCC risk, we created and adjusted for "missing FFQ" indicator variables. We also adjusted for smoking status, which may be a marker for general health-related behavior.
To investigate possible differential associations of alcohol intake and BCC by overall BCC risk profile, we computed a composite BCC multivariate risk score for each cohort member based on the adjusted effect estimates of potential confounders (15) . We then tested for interaction between alcohol intake and tertiles of the composite score. We also explored the role of timing of alcohol intake by allowing variable lag times between dietary assessment and BCC incidence.
After separate analyses for each cohort, the relative risks were pooled using a random effects model to provide a combined risk estimate (16) . We also tested for heterogeneity of the relative risks. Tests of trend were performed by assigning to each participant the median of the quintile to which they belonged and modeling this variable as a single continuous variable. Statistical analyses were performed with SAS, and all of the P are two-sided (17) .
| Results |
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We did not observe any significant difference in the association between total alcohol intake and BCC at different tertiles of the composite risk factor score (data not shown), nor a clear difference in association with different durations of lag time. These associations remained after additional adjustments for walking outdoors (additional sun exposure information), and vitamin intake, or excluding those with missing FFQ. They were also not affected by excluding person-time after the last physical examination among those who never became a case to minimize detection bias. The results also did not differ with or without controlling for smoking. In addition, excluding past heavy drinkers who later abstained did not change the results.
| Discussion |
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To our knowledge, this study is the first long-term prospective evaluation of alcohol consumption and risk of BCC. Our results are not in agreement with the few existing human studies. In a case-control study of men, current, past and nonalcohol drinkers did not differ in skin cancer incidence (6) . However, information bias was possible in this study, as both the cases and the interviewers were aware of the disease status. Also, this analysis did not appear to account for possible confounders. In another case-control study matched on age, sex, and skin type, there was no difference in consumption status (i.e., > or <15 years of use) between the cases with aggressive BCC and the controls (7) . Response rate was 46%, and the analysis was not additionally adjusted for potential confounders.
In various animal and in vitro models, alcohol was shown to have tumor-promoting effects and can generate free radicals (18) . Immunosuppression is a skin cancer risk factor as transplant patients have elevated risk for skin cancers, including BCC (19) . Alcohol may impair cell-mediated and humoral immunity (20) . Chronic alcohol consumption in rats resulted in thymus atrophy accompanied by a reduction of the antioxidant glutathione (20) .
The different associations observed among different alcoholic beverages may be attributable to a combination of effects from ethanol and other substances in the specific beverages. Wine contains phenolic compounds, and many of them have antioxidant activities (21) . Red wine has higher amounts of phenolic compounds than white wines and can acutely increase serum antioxidant activity after ingestion (22) . On the other hand, lower antioxidant activity is found in beer and distilled spirits (23) . Because phenolic compounds have anticarcinogenic effects in cell cultures and animal models (24) , this may account for the lack of increased risk that we observed with red wine in women.
The prospective nature of this analysis and the high follow-up rate render information and selection bias unlikely. Our repeated measures of intake reduced random within-person variation. Heavy drinkers may under-report alcohol intake, and this would underestimate any true association. If there were substantial under-reporting among heavy drinkers, then we would expect a flattened curve rather than an inverted "U" for total alcohol intake. In addition, the validity of alcohol intake assessment from our FFQ has shown to be highly valid and well correlated with plasma high-density lipoprotein cholesterol (9 , 10) .
In conclusion, we observed a modest positive association between total alcohol intake and risk of BCC in both men and women. However, a clear monotonic association was not present, and the associations with the specific alcoholic beverages varied. These findings suggest that alcohol per se may not be a causal factor, but rather that the findings may be attributable to other constituents of alcoholic beverages or to unmeasured confounding variables. UV radiation remains the strongest modifiable risk factor for BCC, and first-line prevention strategies should focus on minimizing sun exposure.
| Acknowledgments |
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| Footnotes |
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1 This work was supported by Grants HL35464, CA55075, and CA87969. ![]()
2 To whom requests for reprints should be addressed, at Department of Nutrition, Simmons College, 300 The Fenway, Boston, MA 02115. ![]()
3 The abbreviations used are: BCC, basal cell carcinoma; NHS, nurses health study; FFQ, food frequency questionnaire; HPFS, health professionals follow-up study; BMI, body mass index; RR, relative risk; CI, confidence interval. ![]()
Received 10/27/00; revised 5/ 8/02; accepted 5/30/02.
| References |
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