1. What are 3 different ways to account for SES in a analytic models when investigating racial/ethnic health disparities? Briefly discuss the interpretations/implications of each approach as it relates to understanding health disparities by race/ethnicity.
SES can be considered as an effect mediator in which any association between race/ethnicity and a particular health outcome/disparity are essentially entirely driven by differences in SES within the study cohort. In this context we are considering the extent to which differences associated with race/ethnicity would not exist without differences in socioeconomic status.
SES can be considered as an effect modifier wherein different components of SES may augment an effect between race/ethnicity and a health outcome/disparity. This is considered, for example, in assessing the extent to which the magnitude of a causal relationship between race/ethnicity and a particular health outcome changes with differences in socioeconomic status across the race/ethnicity group.
Considering SES as a contextual variable considers the extent to which SES within a particular group, for example a neighborhood, may function separately from individual mediating or modifying effects. This is explored when neighborhood socioeconomic status is connected to health outcomes, for example, via access to healthy foods (food deserts) or proximity to health care resources.
2. Describe a potential effect modifier, mediator, or contextual variable (for definition of contextual variable, see Diez-Roux reading) for an association of interest to you and relevant to health disparities. For example, for investigating the association between education and hypertension, I might be interested in evaluating whether the association between years of education and hypertension is different for Black men than for White men. Describe how you would study whether this relationship exists.
One potential contextual variable of interest to me potentially related to health disparities is neighborhood socioeconomic status in the setting of performance of follow-up radiology examinations. Differences in neighborhood socioeconomic status may contribute to any observed associations between race/ethnicity and differences in whether or not a recommended follow-up examinations are performed as well as any time lapse. I would study this possible relationship by including this particular contextual variable along with a range of modifiers and mediators in a Cox proportional hazards model.
3. Respond to one other person's post on the forum with a comment or suggestion.
I found the proposal regarding the association between SES and risk of traffic-related injury to be very compelling and I think the question of how to go about quantitatively measuring the effects of political capital is fascinating. I’m wondering if there may be a way to more directly measure the effects of government resource allocation in this context, for example to calculate the dollars spent in a particular neighborhood on traffic improvements as a percentage of all tax dollars spent on traffic improvements in a city.