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. In 2017, American Indian/Alaska Native individuals with T2DM were 2.5 times more likely to die from T2DM than non-Hispanic Whites (OMH, 2019). To investigate this health disparity, we might ask: What is the relationship of self-identified American Indian/Alaska Native race/ethnicity to increased T2DM mortality, when (some measure of) SES is adjusted for? This question indicates that SES may play a confounding role in the relationship of AI/ANàT2DM mortality, due to its relationship to both the exposure (AI/AN) and outcome (T2DM mortality) of interest. When we consider SES as a confounder in this question, we are looking to differentiate the potential contributions of AI/AN ethnicity and SES to T2DM mortality.
[2] SES as an effect modifier. How does T2DM mortality among self-identified American Indian/Alaska Native individuals differ by varying level of SES? Looking at SES as an effect modifier in the relationship of self-identified AI/AN ethnicity to T2DM mortality reflects an understanding that the magnitude of the effect of the “exposure” (AI/AN ethnicity) on the outcome (T2DM mortality) may either increase or decrease along with changes in various measures of SES, such as income or educational attainment. Analysis of effect modifiers can help us understand the complex ways that social determinants like SES can operate as protective or risk factors for disease outcomes, and target interventions accordingly.
[3] SES as a mediator. Does childhood socioeconomic status, income, or educational attainment mediate the effect of self-identified American Indian/Alaska Native race/ethnicity on mortality related to T2DM? Unlike confounders, which have a distinct causal relationship to an outcome, mediators are factors that lie along a causal pathway between an exposure and an outcome. Research that explores mediating factors therefore seeks to explicate the mechanisms by which more distal determinants, such as SES, shape more proximate risk/protective factors, such as access to nutritious food choices, access to preventative care, time and other resources to support physical activity, etc.
Office of Minority Health (2019, December 19). Diabetes and American Indians/Alaska Natives. Minority Population Profiles. https://minorityhealth.hhs.gov/omh/browse.aspx?lvl=4&lvlid=33
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.
Looking again at the association between rural residence (exposure) and potentially excess death from chronic lower respiratory diseases (outcome), I might consider race/ethnicity as a potential effect modifier, with an understanding that race/ethnicity may impact the magnitude of the effect of rural residence on CLRD mortality. A relevant research question might be: How does race/ethnicity impact the association of CLRD mortality to geographic residence? Interaction terms between location of residence (dichotomous urban/rural) and race/ethnicity (where the most socially advantaged group [White males] was the reference group) could be applied to a linear regression model of geographic residence and CLRD mortality.