Bisakha Sen1. 1. Department of Healthcare Organization and Policy, University of Alabama at Birmingham, Ryals 330, 1665 University Blvd, Birmingham, Alabama, USA.
Abstract
OBJECTIVE: Racial disparities in obesity in the US are often assumed to reflect racial disparities in socio-economic status, diet and physical-activity. We present an econometric method that helps examine this by "decomposing" the racial gap in body-mass index (BMI) into how much can be explained by racial differences in "standard" predictors of BMI, and how much remains unexplained. METHODS: The Oaxaca-Blinder decomposition is widely used in other fields, but remains under-utilized in the obesity literature. We provide algebraic and graphical illustrations of the decomposition, and further illustrate it with an example using data for white and black respondents in Mississippi and Alabama. BMI is the outcome of interest. Predictor variables include income, education, age, marital status, children, mental health indicators, diet and exercise. RESULTS: The mean predicted gap in BMI between white and black men is small, statistically insignificant, and can be attributed to racial differences in the predictor variables. The mean predicted gap for women is larger, statistically significant, and <10% of it can be explained by differences in predictor variables. Implications of the findings are discussed. CONCLUSION: Wider application of this method is advocated in the obesity literature, to better understand racial disparities in obesity.
OBJECTIVE: Racial disparities in obesity in the US are often assumed to reflect racial disparities in socio-economic status, diet and physical-activity. We present an econometric method that helps examine this by "decomposing" the racial gap in body-mass index (BMI) into how much can be explained by racial differences in "standard" predictors of BMI, and how much remains unexplained. METHODS: The Oaxaca-Blinder decomposition is widely used in other fields, but remains under-utilized in the obesity literature. We provide algebraic and graphical illustrations of the decomposition, and further illustrate it with an example using data for white and black respondents in Mississippi and Alabama. BMI is the outcome of interest. Predictor variables include income, education, age, marital status, children, mental health indicators, diet and exercise. RESULTS: The mean predicted gap in BMI between white and black men is small, statistically insignificant, and can be attributed to racial differences in the predictor variables. The mean predicted gap for women is larger, statistically significant, and <10% of it can be explained by differences in predictor variables. Implications of the findings are discussed. CONCLUSION: Wider application of this method is advocated in the obesity literature, to better understand racial disparities in obesity.
Authors: Mustafa Hussein; Ana V Diez Roux; Mahasin S Mujahid; Theresa A Hastert; Kiarri N Kershaw; Alain G Bertoni; Ana Baylin Journal: Am J Epidemiol Date: 2018-07-01 Impact factor: 4.897
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