1. What are 3 different ways to account for SES in an analytic model when investigating racial/ethnic health disparities? (describe a fourth for extra bonus points!). Briefly discuss the interpretations/implications of each approach as it relates to the interest in understand health disparities by race/ethnicity.
Mediation Analysis: Uses SES as a mediator for health disparities. Examining race/ethnicity and a selected out outcome a mediation analysis can examine the role of SES in that pathway.
Generalized Estimating Equation: Analytical method used to estimate parameters of unknown correlations used in Headen to examine clusters using log links.
Effect Measure: Creating models that deferrer at different levels. Models for race/ethnicity and SES can me compared using multiple level modeling.
2. Describe a potential effect modifier, mediator, or contextual variable (for definition of contextual variable, see first page of option Merlo reading) for an association of interest to you and relevant to health disparities. For example, for investigating the association between SES and maternal mortality, I might be interested in the contextual variable of exposure to violence in the neighborhood. Describe how you would study whether this relationship exists.
I am interested in examining prostate cancer disparities in Black men. I would examine contextual variable of a meat based diet consisting of grilling, BBQ, and frying meats.