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3 Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109; 4 Department of Epidemiology, School of Public Health and Community Medicine, University of Washington, Seattle, WA 98195; 5 Division of Cancer Prevention and Population Sciences, Roswell Park Cancer Institute, Buffalo, NY 14263; and 6 Swedish Medical Center and Swedish Cancer Institute, Seattle, WA 98109
* To whom correspondence should be addressed. E-mail: mneuhous{at}fhcrc.org.
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ABSTRACT |
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Introduction |
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TOPABSTRACTIntroductionMethodsResultsDiscussionLITERATURE CITED |
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The bulk of epidemiologic research in relation to fat and cancer risk over the past 20 y has focused on these detrimental aspects of excess dietary fat (7). In this realm of research, prostate cancer has received considerable attention based on observations that global geographic variation in prostate cancer risk has a strong, positive correlation with fat intake (8). However, findings from recent case-control and cohort studies suggest that definitive public health recommendations are still not viable (9–11). One explanation for the inconsistent findings is that many previous studies have grouped all prostate cancers together, but evidence is increasing that aggressive and nonaggressive cancers differ in their etiology (12,13). Dietary factors may have a differential association with high- vs. low-grade disease, an observation that could be obscured when all prostate cancers are grouped as a single outcome. Additionally, variables such as family history or lifestyle habits may interact with diet to differentially affect risk. Whether fat intake increases prostate cancer risk remains an important area of research, since diet is a modifiable risk factor, unlike the well-established risk factors of age, race, and family history.
This study investigates associations of dietary fat, meat, and dairy foods with prostate cancer risk in the Carotene and Retinol Efficacy Trial (CARET) (14). We followed male participants from this randomized trial in a prospective manner since 1989. The longitudinal nature of CARET with its multiple assessments of diet and other exposures make this an important cohort in which to investigate these questions.
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Methods |
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TOPABSTRACTIntroductionMethodsResultsDiscussionLITERATURE CITED |
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Eligible CARET participants were: 1) men and women aged 50–69 y who were current or former heavy smokers (
20 pack-years of cigarette smoking; n = 14,254), 55.9% of whom were male; and 2) men aged 45–69 y who were current or former heavy smokers with occupational exposure to asbestos (n = 4060). Details about the design and primary results of CARET were previously published (14). The Institutional Review Boards of the Fred Hutchinson Cancer Research Center and each of the 5 other participating institutions approved all study procedures, and participants provided written informed consent. This report is restricted to the 12,025 male participants.
Prostate cancer cases—endpoints collection.
Health status, including any new cancers, was updated 5 times/y and all endpoints were verified. We conducted an augmented review of medical records and Surveillance Epidemiology and End Results (SEER) cancer registry files to obtain a Gleason score and stage of disease. "Aggressive prostate cancer" was defined as a Gleason score 7 and/or stage III/IV (distant) at diagnosis. All other prostate cancer cases were considered "nonaggressive." PSA data were not available to distinguish screen-detected vs. clinically detected cases. Noncases included all other men in the cohort, except those who reported a history of prostate cancer at baseline (n = 25).
Dietary assessment. Dietary intake over the previous year was assessed at baseline and every 2 y with a self-administered FFQ. For these analyses we used an unweighted mean of all FFQ that were completed prior to the prostate cancer diagnosis date for the cases and all FFQ for the noncases. This averaging approach reduced the within-person component of error and gave a more precise estimate of dietary parameters than could be obtained from a single FFQ (15).
The CARET FFQ was designed to be especially sensitive to the measurement of fat, fruits and vegetables, and associated nutrients. This FFQ was divided into 3 sections: 1) 7 adjustment questions on food types and preparation techniques (e.g., usual types of fat used in cooking and at the table), which were used to alter how the analysis software calculated the fat and fiber content of specific foods; 2) 110 line items with questions on the frequency of use over the last year (from "0 or <1/mo" to "2+/d" for foods and "6+/d" for beverages) and portion size (small, medium, or large, compared with the stated medium portion size); and 3) 2 summary questions on the usual consumption of fruits and vegetables and 1 summary question on use of fats and oils, which were necessary to reduce the measurement error biased toward overreporting food intake (16). The nutrient database was derived from the University of Minnesota Nutrition Coordinating Center (NCC) database (version 4.02, food and nutrient database version 30). Participants were excluded from dietary analyses if any page or section was not completed or if their reported energy intake was unreliable (<3348 kJ/d or >20,930 kJ/d) (17).
Smoking. Detailed data were collected on current smoking status and smoking history, including age at smoking initiation, total years smoked, and average number of cigarettes smoked per day. We considered several ways to model smoking in our analyses, but because former smoking vs. current smoking may have a slightly higher correlation with dietary intake and thus relatively stronger potential to confound associations of diet with prostate cancer risk, we modeled smoking as a dichotomous variable (former vs. current smoker at baseline). Preliminary analyses revealed that other approaches to characterizing smoking (e.g., pack-years) had no influence on the hazard ratios.
Other.
Age, sex, race/ethnicity, education, health history, height, and weight were collected at each participant's first CARET clinic visit and updated annually. BMI was calculated as weight(kg)/height(m)2. Family history of prostate cancer was defined as 1 first-degree relative with prostate cancer.
Statistical analyses. We used Cox proportional hazards models to estimate the associations of fat intake with prostate cancer incidence. Of 12,025 male CARET participants, 25 reported prostate cancer at baseline and were excluded. We also excluded 705 (5.9%) participants (including 73 prostate cancer cases) who did not have FFQ or covariate data. The Cox regression models were based on 811 prostate cancer cases and 10,419 noncases. The time metric for these models was the time from enrollment in CARET to the diagnosis of prostate cancer; or, for noncases, the date last known to be alive. The primary independent variables of total fat, percentage of energy from fat, specific fats (e.g., saturated fat), dairy foods, and red meats were categorized in the models as quartile indicator variables based on the distribution in the noncases. In each model, the lowest quartile served as the referent group. All models included adjustment for age, race, energy intake (log transformed to improve the normality of the distribution), BMI, family history of prostate cancer, and smoking status (former vs. current smoker). Linear trends across the quartiles were assessed using ordinal variables coded 1–4.
We used multiplicative interaction terms to investigate whether any observed associations between fat intake and prostate cancer risk differed by potential effect modifiers, including family history of prostate cancer, race, smoking status, and CARET intervention arm assignment (study vitamins vs. placebo). This was accomplished by creating cross-product terms of each potential modifier with dietary intake quartile variables. The likelihood ratio test assessed the significance of the interaction and was based on models with and without the effect modifier x the dietary quartile trend variable cross-product terms. In addition, because it has been hypothesized that many of the risk factors may differ between aggressive and nonaggressive prostate cancer, we also fit separate models for these 2 disease classifications.
The CARET intervention arm assignment was entered into each model as an indicator variable, but because the parameter estimates for the intervention arm assignment were neither significant nor influential on the hazard ratios, we omitted these terms from the final models. These decisions are consistent with previous CARET publications showing that the CARET study vitamins were not associated with prostate cancer risk (18). All statistical modeling was conducted using SAS (version 9.1). All tests are 2-sided and significance was determined at P < 0.05.
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Results |
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7 and 150 (22.3%) cases that were stage III/IV at diagnosis (Table 1). Prostate cancer cases tended to be slightly older, black, and report family history of prostate cancer compared to the noncases. There was no difference in CARET randomization assignment for cases vs. noncases.
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Dairy foods and meat are important sources of fat in the American diet. We hypothesized a priori that higher vs. lower consumption of these foods would be associated with increased risk of prostate cancer. Some data (Table 3) suggested that men with a family history of prostate cancer had an approximate halving in risk of the disease for higher intake of dairy foods compared to lower intake of dairy foods (HR = 0.47, 95% CI = 0.22–1.02, P-trend = 0.20). However, formal interaction tests were not statistically significant. These inverse associations were not observed for men without a family history of prostate cancer. Similarly, higher consumption of dairy foods was associated with a reduced risk of aggressive prostate cancer (HR = 0.59, 95% CI = 0.40–0.85, P-trend = 0.05). There was no association of dairy foods with non-aggressive prostate cancer risk. There was no association of red meat with total prostate cancer risk, nor were there any interactions with family history or disease severity. Hazard ratios for red meat intake and the risk of prostate cancer ranged from 0.76 to 1.62.
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Discussion |
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Several biological mechanisms support the results of this study. Fatty acids from the (n-6) family are ubiquitous in the U.S. food supply, but in this study, the most common sources included safflower, soybean, and corn oils (and foods that are made using these oils, such as potato chips, casseroles, baked goods, and fried foods), peanut butter, mayonnaise, salad dressings, and margarine. Consumption of (n-6) fatty acids stimulates the endogenous synthesis of arachidonic acid and its proinflammatory metabolic products, prostaglandins, leukotrienes, and thromboxanes (22). There is a growing consensus that inflammation is associated with many cancers, and recent intriguing data suggest that proliferative inflammatory lesions in the prostate may be precursors to prostate cancer (23). A diet high in proinflammatory substrates could increase the down-stream production of such lesions. In our study, (n-6) fatty acids were associated with risk only among men with a family history of prostate cancer. One explanation might be that men with a family history of prostate cancer have an altered ability to metabolize arachidonic acid and its products. For example, genetic variation in the production and activity of enzymes involved in the biosynthetic cascade of eicosanoid production increases the risk for developing colon polyps in humans and colon cancer in animals (24). A similar mechanism may be at work in individuals with a family history of prostate cancer.
Vitamin D has important preventive properties in relation to epithelial cancers. In particular, it has key functions related to cellular proliferation, cellular differentiation, T cell-mediated immunity, cell cycle arrest, and apoptosis (25). Very few foods contain appreciable amounts of vitamin D, but because all milk sold in the United States is fortified with vitamin D, milk is the primary dietary source of this nutrient for most Americans. In addition to vitamin D, milk contains conjugated linoleic acids (CLA). The metabolism and functions of this group of unsaturated fatty acid isomers are not completely understood, but, in both animal and human studies, they appear to enhance immune function (19), reduce tumor growth (26,27), and perhaps reduce abdominal body fat accumulation (20). Our data showed that dairy foods were protective for men with aggressive disease and for men with a family history of the disease or who were current smokers. In previous studies among healthy individuals, we and other investigators showed that, compared with nonsmokers, serum concentrations of vitamin D are 
10% lower in smokers (28–30). It is conceivable that for current smokers in CARET the higher consumption of dairy products may have helped offset any smoking-related deficiencies in vitamin D.
Our results are consistent with some, but not all, prospective studies on fat and fat-related foods as they relate to prostate cancer risk. In the Health Professionals' Follow-Up Study, total fat was associated with fatal, but not total, prostate cancer (31,32). When these investigators examined specific classes of fatty acids [(n-3) and (n-6)], they found no overall association of specific (n-3) or (n-6) fatty acids with prostate cancer risk. However, there was evidence for an increased risk for advanced prostate cancer for high vs. low consumption of 
-linolenic acid [18:3(n-3)] as well as evidence that risk estimates may differ for animal vs. plant sources of this fatty acid (2). In a separate publication, these researchers found an association of the Western dietary pattern (high intake of meat, high-fat dairy foods, refined grains) with prostate cancer risk (33). The Cancer Prevention Study II Nutrition Cohort followed over 65,000 middle-aged and elderly men from 1992 to 1999. They reported no association of dairy foods with prostate cancer risk, but a modest increase in risk (RR = 1.6, 95% CI = 1.1–2.3) for very high (2000 mg/d) vs. low (<700 mg/d) intake of calcium (34). Several other studies found that the consumption of dairy foods increased the risk for prostate cancer, but that there was a protective association for vitamin D (31,35,36). We did not examine vitamin D separately from dairy foods because the food database values for vitamin D are generally poor. We also did not have information on subject use of vitamin D supplements or exposure to sunlight. Because dairy foods are the primary source of vitamin D in the U.S. diet, and vitamin D supplements are seldom used by men (37), dairy measurement itself is likely a suitable exposure measure. In addition, among CARET participants, there was no significant difference in the use of whole-fat vs. nonfat or low-fat dairy products by cases compared with noncases. Our finding of no association of meat intake with prostate cancer risk, either overall or by race, differs from other studies (38). The Cancer Prevention II investigators reported a doubling of cancer risk for high vs. low meat consumption, but only among black men. The risk was highest for processed meats (11).
The strengths of our study include the prospective nature of the analysis, multiple measures of dietary assessment, endpoint ascertainment that utilized medical records and cancer registry files, and the large number of prostate cancer cases. Our study also has limitations. The CARET FFQ was not subject to a standard validation study by comparing results with another measure of self-reporting (e.g., records or recalls). However, recent studies suggest that, because most dietary assessment tools have correlated errors, validity coefficients may simply be measuring these errors (38,39). Further, all forms of dietary self-reporting are subject to random and systematic bias (39,40), and objective nutritional biomarkers may be preferable to dietary self-reporting because of such measurement error issues (41). We have planned nested case-control studies to examine plasma phospholipid fatty acids in relation to prostate cancer risk in CARET, and the resulting data will further our understanding of specific fats [i.e., (n-6)] and prostate cancer risk. However, there are a limited number of fatty acids that are valid biomarkers of intake and there are no known biomarkers for total fat, monounsaturated, or saturated fat intake (42). Thus, despite the limitations of FFQ, they remain an important assessment tool for the dietary assessment of nutrients without biomarkers. The CARET cohort was comprised of heavy smokers and former heavy smokers. Although the results from this study may not be generalizeable to all U.S. males, our findings are applicable to the millions of men who are current or former smokers, particularly those with a family history of prostate cancer. Further, we conducted many stratified analyses that may lead to finding significant associations by chance. However, we chose not to conduct formal tests of multiple comparisons that can increase the risk of a Type II error. Finally, as with any observational study, there may be residual confounding.
In conclusion, we found that (n-6) fatty acid intake is associated with increased risk of prostate cancer among current and former heavy smokers, but only in men with a family history of prostate cancer. Our findings also suggest that dairy foods protect against prostate cancer in current smokers, particularly for aggressive disease. Because these results differ from those published from other cohorts, and because dairy foods contain components that have been associated with both increased (calcium, fat) and decreased (CLA, vitamin D) risk of prostate cancer, caution should be exercised with regard to promoting or avoiding dairy intake as a prostate cancer preventive measure until further work can be completed.
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FOOTNOTES |
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2 Author disclosures: M. L. Neuhouser, M. J. Barnett, A. R. Kristal, C. B. Ambrosone, I. King, M. Thornquist, and G. Goodman, no conflicts of interest.
Manuscript received 19 January 2007. Initial review completed 14 February 2007. Revision accepted 13 May 2007.
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