Prostate cancer risk factors in black and white men in the NIH-AARP Diet and Health Study

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Abstract
Background There are few prospective studies comparing race-specific associations between diet, nutrients, and health-related parameters, and prostate cancer risk. Methods Race-specific prostate cancer risk associations were examined among men in the National Institutes of Health (NIH)-AARP Diet and Health Study. We identified 1417 cases among black men (209 advanced), and 28,845 among white men (3898 advanced). Cox proportional hazards regression models estimated hazard ratios (HRs) and 95% confidence intervals (CIs). We also evaluated the cumulative change in the HR for black race following adjustment for each factor. Results Race-specific prostate cancer associations were similar in black and white men across disease subtypes only for history of diabetes (overall : HR = 0.77, 95% CI: 0.65–0.90 and HR = 0.72, 95% CI: 0.69–0.76, respectively; Pinteraction = 0.66). By contrast, there was a positive risk association with height for white men and inverse for black men (Pinteraction: non-advanced = 0.01; advanced = 0.04). This difference remained among men with at least 2 years of follow-up for non-advanced (Pinteraction = 0.01), but not advanced disease (Pinteraction = 0.24); or after adjustment for prostate cancer screening (non-advanced Pinteraction = 0.53, advanced Pinteraction = 0.31). The only other evidence of interaction with race was observed for dietary vitamin D intake and non-advanced disease, but only after adjustment for screening (Pinteraction = 0.02). Cumulative adjustment for each factor increased the HR for black race by 32.9% for overall cancer and 12.4% for advanced disease. Conclusions Our data suggest few of the dietary, nutrient, and health-related factors associated with prostate cancer risk in predominantly non-Hispanic white men were associated with risk in black men, and adjustment for these factors widen the black–white difference in risk. Larger studies of black men, particularly with prospective data, are needed to help identify risk factors relevant to this population.

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