1. Write a brief paragraph discussing what social determinants are most relevant to your area of research and why. Consider both structural stratifiers (e.g. income, education, etc) and intermediary determinants such as material and psychosocial circumstances, as described in the WHO reading. Explain why you chose the factors (might use Braveman article from last week to provide justification. The association could be reported in published research or it could be your hypothesized relationship. Consider whether how these factors might function over the lifecourse and/or intergenerationally.
My area of research is in exploring racial/ethnic and language based differences in healthcare outcomes and access to resources on discharge in hospital medicine. Thus far, we have had difficulty in controlling for structural stratifiers because of the retrospective data review and what is collected by our electronic medical record. The main "disparity" indicators we have utilized has been self-identified race, gender, and Limited English Proficiency status. The best proxy we have had for income or class has been insurance status (Medicaid vs Private vs uninsured) and housing status. Given that my specific interest is in developing models to analyze the relationship between race and outcomes, I think finding a proxy for all of the social determinants discussed in the WHO article would be important, including income, class, gender, occupation, and I also think wealth. It would also be important to consider how they change over time, but we have no proxy for this at this moment.
2. Write a brief paragraph describing the extent to which an socioecological framework incorporating issues related to social determinants has been applied to your area of research. Are there opportunities for improving our understanding of or approach to disparities in your area with a greater emphasis on a socioecological framework?
The socioecological framework is essential to my area of research as I am trying to explore the mediators of health disparities with a focus on race/ethnicity. The challenge is in incorporating into statistical models proxies for each of the levels of the socioecological model which is challenging to do in database research. One of my projects is looking at racial differences in opioids prescribed on discharge from the hospital. This is driven by public policy and organizational mandates, but the impact is inequitably spread on more marginalized groups and mediated by bias.