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.
a) SES as a confounder: One research question looking at SES as a confounder would be in examining the relationship between NAFLD (non-alcoholic fatty liver disease) and cirrhosis. People with lower SES are more likely to drink alcohol, which we know leads to increased rates of cirrhosis. People with lower SES have less access to healthy foods, which leads to weight gain, and higher risk for developing NAFLD.
b) SES as an effect modifier: What is the impact of race/ethnicity on development of liver cancer? Liver cancer incidence has been rising, while incidence rates of other cancers have been declining. SES can impact the ability of patients to access care. Those who are at high risk for liver cancer (i.e. patients with cirrhosis or chronic hepatitis B) should have screening ultrasounds every 6 months to monitor for incident development of liver cancer. However, those who have lower SES may not have health insurance or ability to pay for this frequent monitoring or take time off to get the test done. Therefore, SES is an effect modifier between race/ethnicity and liver cancer.
c) SES as a mediator: Does an online patient navigation portal providing evidence-based information in English, Vietnamese, Chinese improve cancer care for Vietnamese and Chinese patients in an academic center? This study would examine the role of language (as a measure of SES) as a mediator since we are looking at whether mitigating language disparities would improve outcomes for cancer patients along the pathway between patient navigation and cancer outcomes.
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 studying the role of race/ethnicity and development of NAFLD (non-alcoholic fatty liver disease). Since NAFLD is common in patients with diabetes and patients with diabetes have more severe cases of NAFLD. Given that there are disparities in diabetes by race/ethnicity, I imagine that there are also disparities in NAFLD by race/ethnicity. NAFLD is becoming a more common cause of cirrhosis and more needs to be done to prevent the development of NAFLD in high risk patients. I would use National Ambulatory Health Care Data database (NAMCS) to look at rates of NAFLD by race and ethnicity. I would look at unadjusted logistic regression models. I would then use adjusted logistic regression models. I would look for potential mediators and interactions and compare these to the unadjusted models.
3. Respond to one other person's post on the forum with a comment or suggestion.
I responded to Hunter Holt’s forum.