Circulating levels of 25-hydroxyvitamin D and risk of breast cancer : a nested case-control study

Introduction: Experimental evidence suggests a protective role for circulating 25-hydroxyvitamin D (25(OH) D) in breast cancer development, but the results of epidemiological studies have been inconsistent. Methods: We conducted a case-control study nested within two prospective cohorts, the New York University Women's Health Study and the Northern Sweden Mammary Screening Cohort. Blood samples were collected at enrollment, and women were followed up for breast cancer ascertainment. In total, 1,585 incident breast cancer cases were individually-matched to 2,940 controls. Of these subjects, 678 cases and 1,208 controls contributed two repeat blood samples, at least one year apart. Circulating levels of 25(OH) D were measured, and multivariate odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using conditional logistic regression. Results: No association was observed between circulating levels of 25(OH) D and overall breast cancer risk (multivariate-adjusted model OR = 0.94, 95% CI = 0.76-1.16 for the highest vs. lowest quintile, ptrend = 0.30). The temporal reliability of 25(OH)D measured in repeat blood samples was high (intraclass correlation coefficients for season-adjusted 25(OH) D > 0.70). An inverse association between 25(OH) D levels and breast cancer risk was observed among women who were = 45 years of age (ORQ5-Q1 = 0.48, 95% CI = 0.30-0.79, ptrend = 0.01) or premenopausal at enrollment (ORQ5-Q1 = 0.67, 95% CI = 0.48-0.92, ptrend = 0.03). Conclusions: Circulating 25(OH) D levels were not associated with breast cancer risk overall, although we could not exclude the possibility of a protective effect in younger women. Recommendations regarding vitamin D supplementation should be based on considerations other than breast cancer prevention

Measurement Error and Environmental Epidemiology: a Policy Perspective

PURPOSE OF REVIEW: Measurement error threatens public health by producing bias in estimates of the population impact of environmental exposures. Quantitative methods to account for measurement bias can improve public health decision making. RECENT FINDINGS: We summarize traditional and emerging methods to improve inference under a standard perspective, in which the investigator estimates an exposure response function, and a policy perspective, in which the investigator directly estimates population impact of a proposed intervention. SUMMARY: Under a policy perspective, the analysis must be sensitive to errors in measurement of factors that modify the effect of exposure on outcome, must consider whether policies operate on the true or measured exposures, and may increasingly need to account for potentially dependent measurement error of two or more exposures affected by the same policy or intervention. Incorporating approaches to account for measurement error into such a policy perspective will increase the impact of environmental epidemiology