INTRODUCTION: Racial residential segregation has been shown to affect the absolute levels of racial disparities in a wide variety of health outcomes in the USA but it is not known whether changes in segregation also influence these racial health disparities. This study examines the relationship between changes in racial residential segregation over four decades (1980-2020) and trends in racial disparities in early mortality (under age 65) rates among non-Hispanic Black and non-Hispanic White persons across a wide range of health outcomes in 220 metropolitan statistical areas (MSAs) during the period 2001-2018. METHODS: Using the CDC WONDER Underlying Cause of Death database, we derived annual estimates of race-specific death rates and rate ratios for each MSA. We used latent trajectory analysis to examine the relationship between the level of segregation and changes in segregation over time in an MSA and trends in death rate disparities in that MSA. RESULTS: The trajectory analysis resulted in a linear, three group model in which trajectory Groups 1 and 2 had decreasing trends in the ratios of Black to White death rates over time while in Group 3, the disparity remained almost constant over time. Increases in the level of segregation in an MSA from 1980 to 2000 were significantly associated with the likelihood that the MSA was in Group 3 and experienced no improvement in racial health disparities in mortality over time. CONCLUSION: This paper provides new evidence that changes in segregation are related to trends in racial health disparities in mortality rates over time.
Introduction Structural racism is increasingly being recognized as a fundamental cause of racial health disparities. We used a novel measure of structural racism at the state level to examine the relationship between structural racism and disparities in death rates from firearm homicide, infant mortality, HIV, diabetes, stroke, hypertension, asthma, and kidney disease between non-Hispanic Black and non-Hispanic White people in the United States. Methods We used confirmatory factor analysis to measure the latent construct of structural racism for all 50 states. The model included seven indicators across the structural racism domains of residential segregation, economic status/employment, education, incarceration, political participation and representation, environmental racism, and racial equity inclusion. Weights for each of the indicators were determined by examining alternative models and selecting the model with the best fit statistics. The resulting factor scores, representing the level of structural racism in each state across the seven domains, were then used as predictor variables in a series of linear regressions with the ratio of Black to White death rates for each health outcome as the dependent variables. Results We found significant relationships between higher levels of the latent structural racism measure and greater disparities between non-Hispanic Black and non-Hispanic White people in age-adjusted death rates for firearm homicide, infant mortality, HIV, asthma, and obesity. The magnitude of this relationship was greatest for firearm homicide, with each one standard deviation increase in a state's structural racism factor score being associated with an increase of 4.54 (95% CI, 2.91-6.17) in that state's Black-White firearm homicide rate ratio. Conclusions This research provides further evidence that structural racism is a fundamental cause of racial health disparities and that to repair these inequities, macro-level changes in societal structures, institutions, resource allocation, representation, and power will be necessary.
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 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. RESULTS: There 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). CONCLUSIONS: These new measures can be utilized by researchers to relate structural racism to racial health disparities at the city level.
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.
Gun Violence , Homicide , Systemic Racism , Humans , Black or African American , Racial Groups , United States , White , Firearms
