Using a Latent Variable Method to Develop a Composite, Multidimensional Measure of Structural Racism at the City Level

IntroductionAlthough structural racism is strongly related to racial health disparities, we are not aware of any composite, multidimensional measure of structural racism at the city level in the United States. However, many of the policies, programs, and institutions that create and maintain structural racism are located at the city level. To expand upon previous research, this paper uses a novel measure to measure structural racism at the city level for the non-Hispanic Black population.MethodsWe used confirmatory factor analysis to model the latent construct of structural racism for 776 U.S. cities. The model included six indicators across five dimensions: racial segregation, incarceration, educational attainment, employment, and economic status. We generated factor scores that weighted the indicators in order to produce the best model fit. The resulting factor scores represented the level of structural racism in each city. We demonstrated the utility of this measure by demonstrating its strong correlation with Black-White disparities in firearm homicide rates.ResultsThere were profound differences in the magnitude of structural racism across cities. There were also striking differences in the magnitude of the racial disparity in firearm homicide across cities. Structural racism was a significant predictor of the magnitude of these racial disparities in firearm homicide. Each one standard deviation increase in the structural racism factor score increased the firearm homicide rate ratio by a factor of approximately 1.2 (95% confidence interval, 1.1-1.3).ConclusionsThese new measures can be utilized by researchers to relate structural racism to racial health disparities at the city level.