Association between polyphenol intake and breast Cancer risk by menopausal and hormone receptor status

There is limited evidence of phenolic compounds acting as protective agents on several cancer types, including breast cancer (BC). Nevertheless, some polyphenol classes have not been investigated and there is a lack of studies assessing the effect on menopausal status and hormone receptor status as influenced by these compounds. The objective of this study is to evaluate the association between the intake of all polyphenol classes in relation to the BC risk by menopausal and hormone receptor status. We used data from a population-based multi-case-control study (MCC-Spain) including 1472 BC cases and 1577 controls from 12 different regions of Spain. The odds ratios (ORs) with 95% CI were calculated using logistic regression of mixed effects by quartiles and log2 of polyphenol intakes (adjusted for the residual method) of overall BC, menopausal and receptor status. No associations were found between total intake of polyphenols and BC risk. However, inverse associations were found between stilbenes and all BC risk (ORQ4 vs. Q1: 0.70, 95%CI: 0.56-0.89, Ptrend = 0.001), the consumption of hydroxybenzaldehydes (ORQ4 vs. Q1: 0.75, 95%CI: 0.59-0.93, Ptrend = 0.012) and hydroxycoumarins (ORQ4 vs. Q1: 0.73, 95%CI: 0.57-0.93; Ptrend = 0.005) were also inversely associated. The intake of stilbenes, hydroxybenzaldehydes and hydroxycoumarins can contribute to BC reduction risk on all menopausal and receptor statuses

Validation of self-reported perception of proximity to industrial facilities: MCC-Spain study

Background: Self-reported data about environmental exposures can lead to measurement error. Objectives: To validate the self-reported perception of proximity to industrial facilities. Methods: MCC-Spain is a population-based multicase-control study of cancer in Spain that recruited incident cases of breast, colorectal, prostate, and stomach cancer. The participant's current residence and the location of the industries were geocoded, and the linear distance between them was calculated (gold standard). The epidemiological questionnaire included a question to determine whether the participants perceived the presence of any industry at ≤1 km from their residences. Sensitivity and specificity of individuals' perception of proximity to industries were estimated as measures of classification accuracy, and the area under the curve (AUC) and adjusted odds ratios (aORs) of misclassification were calculated as measures of discrimination. Analyses were performed for all cases and controls, and by tumor location, educational level, sex, industrial sector, and length of residence. Finally, aORs of cancer associated with real and self-reported distances were calculated to explore differences in the estimation of risk between these measures. Results: Sensitivity of the questionnaire was limited (0.48) whereas specificity was excellent (0.89). AUC was sufficient (0.68). Participants with breast (aOR(95%CI) = 2.03 (1.67;2.46)), colorectal (aOR(95%CI) = 1.41 (1.20;1.64)) and stomach (aOR(95%CI) = 1.59 (1.20;2.10)) cancer showed higher risk of misclassification than controls. This risk was higher for lower educational levels (aOR15 years (95%CI) = 0.56 (0.36;0.85)). The use of self-reported proximity vs. real distance to industrial facilities biased the effect on cancer risk towards the nullity. Conclusions: Self-reported distance to industrial facilities can be a useful tool for hypothesis generation, but hypothesis-testing studies should use real distance to report valid conclusions. The sensitivity of the question might be improved with a more specific formulation