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.
A. Account for SES as a mediator. In this analysis, we believe that SES is associated with racial-ethnic differences and it is a mediator of the outcome of health disparities via a causal pathway. When we evaluate SES as a mediator we are trying to better clarify the relationship between race/ethnicity and the health disparity outcome. Through mediation analysis we understand how much of the outcome is mediated through SES.
B. Account for SES as a confounder. For this to occur there is an association between (1) race/ethnicity and the disparity AND (2) SES and the disparity. There must also be an association between race/ethnicity and SES. Finally, SES cannot be caused by race. In this model there is an association between race/ethnicity and SES. There appears to be a relationship between racial/ethnic group and health disparities, however, the driver is through the SES and not through the racial/ethnic differences. As such, we adjust for SES in our model and when we do this, the association between race/ethnicity and health disparities goes away. Thus, the SES is confounding the association.
C. Account for SES as Contextual variable: In this scenario the impact on health disparities is via the social group that a person belongs to. As such, SES can be a contextual variable because people in the same neighborhood have similar SES. In this example the effect of group level properties (i.e., local grocery store options, prevalence of fast food restaurants in a neighborhood) can be the etiology of the health disparity and since it is on the neighborhood level SES is a contextual variable
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 contextual effect I would be interested in in the impact of air pollution on the development of chronic lung allograft dysfunction after transplantation. Some patients are exposed to higher levels of air pollution given the proximity to traffic and freeways. This is often in the lower SES neighborhoods or the lower education neighborhoods. You could do this by creating two groups (1) urban population in high air pollution area – and lower SES (2) Rural population with matched SES. Then you could look at the incidence of lung dysfunction across the two populations.
3. Respond to one other person's post on the forum with a comment or suggestion.
I think Rebecca's assessment of SES with traffic injury is very interesting. I am wondering about the type of traffic injury you are considering and if it may be interesting to split it up into freeway injury and local street injury to differentiate neighborhood from all cause traffic injury.