Perinatal factors and breast cancer risk among Hispanics.

PURPOSE: This study assessed whether perinatal factors were associated with breast cancer among Hispanics, a group with fairly low incidence rates of breast cancer. METHODS: Data were used from a case-control study of breast cancer among Hispanics aged 30-79 conducted between 2003 and 2008 on the Texas-Mexico border. In-person interviews were completed with 188 incident breast cancer cases ascertained through surgeons and oncologists, and 974 controls (with respective response rates of 97% and 78%). RESULTS: Relative to birth weight 2500-3999g, there was no elevation in breast cancer risk for birth weight of ≥ 4000g (odds ratio [OR] 0.76, 95% confidence interval [CI] 0.47-1.21). CONCLUSIONS: The results tended to differ slightly from previous studies of this topic perhaps owing to the different hormonal milieu among Hispanics relative to Caucasians, African Americans and Asians in whom all previous studies of this topic have been conducted. Confirmation of these findings in larger studies may assist in determining how hormonal mechanisms responsible for breast cancer differ by ethnicity.

Analysis of an environmental exposure health questionnaire in a metropolitan minority population utilizing logistic regression and Support Vector Machines.

The goal of this study was to analyze a 54-item instrument for assessment of perception of exposure to environmental contaminants within the context of the built environment, or exposome. This exposome was defined in five domains to include 1) home and hobby, 2) school, 3) community, 4) occupation, and 5) exposure history. Interviews were conducted with child-bearing-age minority women at Metro Nashville General Hospital at Meharry Medical College. Data were analyzed utilizing DTReg software for Support Vector Machine (SVM) modeling followed by an SPSS package for a logistic regression model. The target (outcome) variable of interest was respondent's residence by ZIP code. The results demonstrate that the rank order of important variables with respect to SVM modeling versus traditional logistic regression models is almost identical. This is the first study documenting that SVM analysis has discriminate power for determination of higher-ordered spatial relationships on an environmental exposure history questionnaire.