Mark G Orr1, Sandro Galea2, Matt Riddle3, George A Kaplan4. 1. Social and Decision Analytics Laboratory-Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Arlington, VA. Electronic address: morr9@vbi.vt.edu. 2. Department of Epidemiology, Columbia University, New York, NY. 3. Decision and Information Science, Argonne National Laboratory, Lemont, IL. 4. Department of Epidemiology, University of Michigan, Ann Arbor, MI.
Abstract
PURPOSE: Understanding how to mitigate the present black-white obesity disparity in the United States is a complex issue, stemming from a multitude of intertwined causes. An appropriate but underused approach to guiding policy approaches to this problem is to account for this complexity using simulation modeling. METHODS: We explored the efficacy of a policy that improved the quality of neighborhood schools in reducing racial disparities in obesity-related behavior and the dependence of this effect on social network influence and norms. We used an empirically grounded agent-based model to generate simulation experiments. We used a 2 × 2 × 2 factorial design that represented the presence or absence of improved neighborhood school quality, the presence or absence of social influence, and the type of social norm (healthy or unhealthy). Analyses focused on time trends in sociodemographic variables and diet quality. RESULTS: First, the quality of schools and social network influence had independent and interactive effects on diet behavior. Second, the black-white disparity in diet behavior was considerably reduced under some conditions, but never completely eliminated. Third, the degree to which the disparity in diet behavior was reduced was a function of the type of social norm that was in place; the reduction was the smallest when the type of social norm was healthy. CONCLUSIONS: Improving school quality can reduce, but not eliminate racial disparities in obesity-related behavior, and the degree to which this is true depends partly on social network effects.
PURPOSE: Understanding how to mitigate the present black-white obesity disparity in the United States is a complex issue, stemming from a multitude of intertwined causes. An appropriate but underused approach to guiding policy approaches to this problem is to account for this complexity using simulation modeling. METHODS: We explored the efficacy of a policy that improved the quality of neighborhood schools in reducing racial disparities in obesity-related behavior and the dependence of this effect on social network influence and norms. We used an empirically grounded agent-based model to generate simulation experiments. We used a 2 × 2 × 2 factorial design that represented the presence or absence of improved neighborhood school quality, the presence or absence of social influence, and the type of social norm (healthy or unhealthy). Analyses focused on time trends in sociodemographic variables and diet quality. RESULTS: First, the quality of schools and social network influence had independent and interactive effects on diet behavior. Second, the black-white disparity in diet behavior was considerably reduced under some conditions, but never completely eliminated. Third, the degree to which the disparity in diet behavior was reduced was a function of the type of social norm that was in place; the reduction was the smallest when the type of social norm was healthy. CONCLUSIONS: Improving school quality can reduce, but not eliminate racial disparities in obesity-related behavior, and the degree to which this is true depends partly on social network effects.
Authors: Neal Jeffries; Alan M Zaslavsky; Ana V Diez Roux; John W Creswell; Richard C Palmer; Steven E Gregorich; James D Reschovsky; Barry I Graubard; Kelvin Choi; Ruth M Pfeiffer; Xinzhi Zhang; Nancy Breen Journal: Am J Public Health Date: 2019-01 Impact factor: 9.308
Authors: Brent A Langellier; Usama Bilal; Felipe Montes; Jose D Meisel; Letícia de Oliveira Cardoso; Ross A Hammond Journal: Am J Prev Med Date: 2019-08 Impact factor: 5.043
Authors: Joel Gittelsohn; Elizabeth Anderson Steeves; Yeeli Mui; Anna Y Kharmats; Laura C Hopkins; Donna Dennis Journal: BMC Public Health Date: 2014-09-11 Impact factor: 3.295