Full Citation
Title: Using a Latent Variable Method to Develop a Composite, Multidimensional Measure of Structural Racism at the City Level
Citation Type: Journal Article
Forthcoming?: Yes
ISBN:
ISSN: 2197-3792
DOI: 10.1007/s40615-023-01695-2
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Abstract: Introduction Although 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. Methods We used confrmatory factor analysis to model the latent construct of structural racism for 776 U.S. cities. The model included six indicators across fve 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 ft. 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 frearm homicide rates. Results There were profound diferences in the magnitude of structural racism across cities. There were also striking diferences in the magnitude of the racial disparity in frearm homicide across cities. Structural racism was a signifcant predictor of the magnitude of these racial disparities in frearm homicide. Each one standard deviation increase in the structural racism factor score increased the frearm homicide rate ratio by a factor of approximately 1.2 (95% confdence interval, 1.1-1.3). Conclusions These new measures can be utilized by researchers to relate structural racism to racial health disparities at the city level.
Url: https://link.springer.com/article/10.1007/s40615-023-01695-2
User Submitted?: No
Authors: Siegel, Michael; Rieders, Madeline; Rieders, Hannah; Moumneh, Jinan; Asfour, Julia; Oh, Jinseo; Oh, Seungjin
Periodical (Full): Journal of Racial and Ethnic Health Disparities
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Pages: 1-13
Data Collections: IPUMS NHGIS
Topics: Health, Population Data Science, Race and Ethnicity
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