Geoff B Dougherty1, Sherita H Golden2, Alden L Gross3, Elizabeth Colantuoni4, Lorraine T Dean3. 1. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland. Electronic address: geoffd@jhu.edu. 2. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland; Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland. 3. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland. 4. Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Abstract
INTRODUCTION: Structural racism has attracted increasing interest as an explanation for racial disparities in health, including differences in adiposity. Structural racism has been measured most often with single-indicator proxies (e.g., housing discrimination), which may leave important aspects of structural racism unaccounted for. This paper develops a multi-indicator scale measuring county structural racism in the U.S. and evaluates its association with BMI. METHODS: County structural racism was estimated with a confirmatory factor model including indicators reflecting education, housing, employment, criminal justice, and health care. Using Behavioral Risk Factor Surveillance Survey data (2011-2012) and a mixed-effects model, individual BMI was regressed on county structural racism, controlling for county characteristics (mean age, percentage black, percentage female, percentage rural, median income, and region). Analysis occurred 2017-2019. RESULTS: The study included 324,572 U.S. adults. A 7-indicator county structural racism model demonstrated acceptable fit. County structural racism was associated with lower BMI. Structural racism and black race exhibited a qualitative interaction with BMI, such that racism was associated with lower BMI in whites and higher BMI in blacks. In a further interaction analysis, county structural racism was associated with larger increases in BMI among black men than black women. County structural racism was associated with reduced BMI for white men and no change for white women. CONCLUSIONS: The results confirm structural racism as a latent construct and demonstrate that structural racism can be measured in U.S. counties using publicly available data with methods offering a strong conceptual underpinning and content validity. Further study is necessary to determine whether addressing structural racism may reduce BMI among blacks.
INTRODUCTION: Structural racism has attracted increasing interest as an explanation for racial disparities in health, including differences in adiposity. Structural racism has been measured most often with single-indicator proxies (e.g., housing discrimination), which may leave important aspects of structural racism unaccounted for. This paper develops a multi-indicator scale measuring county structural racism in the U.S. and evaluates its association with BMI. METHODS: County structural racism was estimated with a confirmatory factor model including indicators reflecting education, housing, employment, criminal justice, and health care. Using Behavioral Risk Factor Surveillance Survey data (2011-2012) and a mixed-effects model, individual BMI was regressed on county structural racism, controlling for county characteristics (mean age, percentage black, percentage female, percentage rural, median income, and region). Analysis occurred 2017-2019. RESULTS: The study included 324,572 U.S. adults. A 7-indicator county structural racism model demonstrated acceptable fit. County structural racism was associated with lower BMI. Structural racism and black race exhibited a qualitative interaction with BMI, such that racism was associated with lower BMI in whites and higher BMI in blacks. In a further interaction analysis, county structural racism was associated with larger increases in BMI among black men than black women. County structural racism was associated with reduced BMI for white men and no change for white women. CONCLUSIONS: The results confirm structural racism as a latent construct and demonstrate that structural racism can be measured in U.S. counties using publicly available data with methods offering a strong conceptual underpinning and content validity. Further study is necessary to determine whether addressing structural racism may reduce BMI among blacks.
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