Dados Bibliográficos

AUTOR(ES) S. Oh , J. Oh , Madeline Rieders , Hannah Rieders , Jinan Moumneh , Julia Asfour , M. Siegel , Richard Braden
AFILIAÇÃO(ÕES) Tufts University
ANO 2017
TIPO Book
CITAÇÕES 3
ADICIONADO EM 2025-08-14
MD5 02518BE6C3A183E20BFB2769BF4CA1DD

Resumo

Introduction Structural racism is strongly related to racial health disparities. However, surprisingly few studies have developed empirical tools to measure structural racism. In addition, the few measures that have been employed have only considered structural racism at the neighborhood level. To expand upon previous studies, this paper uses a novel measure to measure structural racism at the county level for the non-Hispanic Black population. Methods We used confirmatory factor analysis to create a model to measure the latent construct of structural racism for 1181 US counties. The model included five indicators across five dimensions: racial segregation, incarceration, educational attainment, employment, and economic status/wealth. Structural equation modeling and factor analysis were used to generate 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 county. We demonstrated the utility of this measure by demonstrating its strong correlation with Black-White disparities in firearm homicide rates. Results Our calculations revealed striking geographic differences across counties in the magnitude of structural racism, with the highest values generally being observed in the Midwest and Northeast. Structural racism was significantly associated with higher Black firearm homicide rates, lower White homicide rates, and a higher Black-White racial disparity in firearm homicide. Conclusions These new measures can be utilized by researchers to relate structural racism to racial health disparities at the county level.

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