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.
Confounder: Socioeconomic status is a potential confounder for rates of hospitalization among children with asthma. Poor air quality is known to contribute to the development of childhood asthma and asthma hospitalization. Low SES patients are more likely to live in areas with poor air quality, and are also more likely to be hospitalized due to other social factors (ex: inability to afford medications, unstable living environments that make use of daily controller medication difficult, difficulty with adherence to medication due to caregiver’s work or other family responsibilities, etc.)
Effect modifier: SES may be an effect modifier for adherence to medication among adolescents with chronic kidney disease. Adolescents are known to have the highest rates of nonadherence among all age groups due to complex developmental changes that occur during this life stage. Socioeconomic status may be an effect modifier for this phenomenon. Patients with higher socioeconomic status may have more social support from their parents, and their parents may have higher medical literacy when it come to their children’s need for medication.
Mediator: Children of color have lower access to living related renal transplant than White children. SES is known to be a mediator in this case, as more potential donors of color report that lost wages/taking time off of work is a major barrier to donation than White potential donors. The effect of race on access to living renal transplantation is significantly mitigated when adjusting for household income.
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.
For my specific area of interest, I would like to examine whether the association between pre-transplant non-adherence and access to preemptive transplant versus transplant after dialysis initiation is different for lower socioeconomic status adolescents and young adults when compared to higher SES patients in the same age group. I will be using the Children with Chronic Kidney Disease (CKiD) study database to examine this question. CKiD collects a large amount of sociodemographic data on their participants, including zipcode. I suspect that living in an area close to a pediatric transplant center (within 40 miles) versus living further from a transplant center will be associated with higher rates of preemptive transplantation. Proximity to a transplant center may be an effect modifier for patients with low SES status who will have more difficulty with transportation than those with higher SES status. I plan to use linear regression and other statistical methods to examine for interaction between SES and proximity to transplant center when examining access to transplantation.