1. Give an example of a research question for investigating racial/ethnic health disparities where: [1] SES is a confounder; [2] SES is an effect modifier; [3] SES is a mediator. Briefly discuss the interpretations/implications of each approach as it relates to understanding health disparities by race/ethnicity.
SES is a confounder:
One example could be a study looking at the causal effect of smoking on heart disease, where lower SES is causally related to behaviors that lead to higher rates of smoking and also causally related to having worse outcomes in cardiovascular disease
Smoking <- Stress <- SES -> Cardiovascular Disease
SES as an effect modifier:
One example could be the question of looking at how those exposed to contaminated drinking water in Flint, Michigan and development of Legionnaire’s disease. SES is not a confounder but rather an effect modifier because it allows those with SES to have higher rates of health care access to protect themselves from developing Legionnaire’s disease compared to those of lower SES.
Exposure to contaminated water in Flint, Michigan -> development of Legionnaire’s disease <- SES
SES as a mediator:
An example would be a study looking at the predictor of people who are arrested for selling drugs, those who have higher SES are less likely to have drug convictions due to having access to legal counsel. The SES mediates the outcome of drug conviction along the causal pathway.
Arrests for selling drugs -> SES -> convictions for drug offenses
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.
I would be interested in patients with opioid use disorder (OUD), what are the treatment access rates to medications like buprenorphine and methadone and would evaluate whether treatment access in different locations are different from African American patients than they are for other races/ethnicities. I would look at a national dataset of Emergency Room data across various parts of the country to look at who presents for OUD and to see if they’re being offered these medications. The aspect of race/ethnicity could then be looked at as a mediator in the analysis.