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.
[1] SES as a confounder: Does distance
from a transplant center impact liver transplant waitlisting rate? SES is a
confounder in this case because transplant centers tend to be located in urban
areas. SES impacts distance from a transplant center because patients with low
incomes tend to live in more rural areas with less access to advanced care. It
also impacts waitlisting rate because these patients tend to present with more advanced
disease, and if they have any social or medical contraindications at the time
of evaluation for transplant, they are less likely to be listed.
[2] SES as an effect modifier: Compared with patients who are listed at more than one transplant center, do patients listed at a single center have lower rates of transplant? In this case SES (as an aggregate of many individual factors) is an effect modifier: the patients who are listed at multiple centers tend to have an advantage over those listed at single centers. The multiply listed patients also tend to be affluent, white, and privately insured.
[3] SES as a mediator: Race and live donor liver transplant. The majority of patients who undergo live donor liver transplant at UCSF are white. SES is a mediator of this discrepancy as patients need to have medical literacy and a support network with the ability to take time off work in order to navigate the live donor liver transplant process.
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 am interested in living donor liver transplantation and the association between education and LDLT rates is of particular interest. I suspect race may be an effect modifier this case. I would approach this by comparing highest level of education among LDLT and DDLT recipients as collected on transplant candidate forms from the United Network for Organ Sharing national data and then looking at this relationship by race.