JMIR Publications

ABSTRACT

Background:

Studies investigating the impact of racial segregation on health have reported mixed findings and tended to focus on neighborhood racial composition. These studies use varying racial composition measures, such as census tracts or investigator-adapted questions, which are currently limited to assessing one dimension of neighborhood racial composition.

Objective:

To propose a novel racial segregation measure: the Pictorial Racial Composition Measure (PRCM).

Methods:

The PRCM is a 10-item questionnaire of pictures representing social environments across adolescence and adulthood: neighborhoods and blocks (adolescent and current), schools and classrooms (junior high and high school), workplace, and place of worship. Cognitive interviews (n=10) and surveys (n=549) were administered to medically underserved patients at a primary care clinic at the Barnes-Jewish Hospital. Development of the PRCM occurred across pilot and main phases. For each social environment and survey phase (pilot and main), we computed positive vs. negative pairwise comparisons: (1) Mostly Black vs. all other categories, (2) Half Black vs. all other categories, and (3) Mostly White vs. all other categories. We calculated the following validity metrics for each pairwise comparison: sensitivity, specificity, correct classification rate, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio, false positive rate, and false negative rate.

Results:

For each social environment, “Mostly Black” and “Mostly White” dichotomizations generated better validity metrics relative to the “Half Black” dichotomization.

Conclusions:

These findings suggest that the pictorial measures for all social environments perform fairly well. The PRCM can serve as a uniform measure across disciplines, capture multiple social environments over the life course, and be administered during one study visit. The PRCM also provides an added window into understanding how structural racism has impacted underserved communities and may inform equitable intervention and prevention efforts to improve lives.