Accounting for segregation in race/ethnic disparities research

Brisa Sanchez Speaker
Drexel University
Sunday, Aug 6: 2:05 PM - 2:30 PM
Invited Paper Session 
Metro Toronto Convention Centre 
Studying racial or ethnic disparities in medical research often involves using person-level race or ethnicity to define group membership and subsequently estimating regression-adjusted absolute or relative measures of between-group differences in a health outcome. However, research that uses individual-level race/ethnicity as a variable without considering racial segregation (or diversity) of study participant's residential neighborhoods generates biased inferences about racial/ethnic disparities because segregation confounds the role of individual-level race/ethnicity. As a result, such research incorrectly attributes racial/ethnic disparities to person-level characteristics or behaviors instead of community-level factors and their upstream determinants including structural racism. We will discuss the application of various statistical designs and analyses that can be deployed to account for residential segregation. Using an empirical example, we also show results that account for residential segregation (or diversity) tend to be robust to the choice of segregation or racial/ethnic diversity used.