Survival-related Selection Bias in Studies of Racial Health Disparities: The Importance of the Target Population and Study Design

Abstract

The impact of survival-related selection bias has not always been discussed in relevant studies of racial health disparities. Moreover, the analytic approaches most frequently employed in the epidemiologic literature to minimize selection bias are difficult to implement appropriately in racial disparities research. This difficulty stems from the fact that frequently employed analytic techniques require that common causes of survival and the outcome are accurately measured. Unfortunately, such common causes are often unmeasured or poorly measured in racial health disparities studies. In the absence of accurate measures of the aforementioned common causes, redefining the target population or changing the study design represents a useful approach for reducing the extent of survival-related selection bias. To help researchers recognize and minimize survival-related selection bias in racial health disparities studies, we illustrate the aforementioned selection bias and how redefining the target population or changing the study design can be useful.

Figure

Causal diagram for the target and study population in the researcher’s original cross-sectional study that depicts the relationship between race and Z infection, where S=1 is an indicator of remaining alive in the target population to be included in the study population, U is an unmeasured factor, and a box denotes conditioning. In the researcher’s original cross-sectional study, the target population is Black and White residents of City X born in 1936 and the study population is all Black and White City X residents who were born in 1936 and were living when study enrollment occurs in 2016. If the target population in the researcher’s study were simply redefined (i.e., changed) to be the study population (i.e., Black and White City X residents who were born in 1936 and are living at enrollment in 2016), then S=1 is now an indicator of remaining alive in City X to be included in both the target population and study population.