4.4 Article

Systems Thinking and Simulation Modeling to Inform Childhood Obesity Policy and Practice

期刊

PUBLIC HEALTH REPORTS
卷 132, 期 -, 页码 33S-38S

出版社

SAGE PUBLICATIONS INC
DOI: 10.1177/0033354917723601

关键词

childhood obesity; obesity policy; systems modeling

资金

  1. Georgia Department of Public Health
  2. Robert W. Woodruff Foundation
  3. Georgia Health Foundation

向作者/读者索取更多资源

Objectives: In 2007, 31.7% of Georgia adolescents in grades 9-12 were overweight or obese. Understanding the impact of policies and interventions on obesity prevalence among young people can help determine statewide public health and policy strategies. This article describes a systems model, originally launched in 2008 and updated in 2014, that simulates the impact of policy interventions on the prevalence of childhood obesity in Georgia through 2034. Methods: In 2008, using information from peer-reviewed reports and quantitative estimates by experts in childhood obesity, physical activity, nutrition, and health economics and policy, a group of legislators, legislative staff members, and experts trained in systems thinking and system dynamics modeling constructed a model simulating the impact of policy interventions on the prevalence of childhood obesity in Georgia through 2034. Use of the 2008 model contributed to passage of a bill requiring annual fitness testing of schoolchildren and stricter enforcement of physical education requirements. We updated the model in 2014. Results: With no policy change, the updated model projects that the prevalence of obesity among children and adolescents aged <= 18 in Georgia would hold at 18% from 2014 through 2034. Mandating daily school physical education (which would reduce prevalence to 12%) and integrating moderate to vigorous physical activity into elementary classrooms (which would reduce prevalence to 10%) would have the largest projected impact. Enacting all policies simultaneously would lower the prevalence of childhood obesity from 18% to 3%. Conclusions: Systems thinking, especially with simulation models, facilitates understanding of complex health policy problems. Using a simulation model to educate legislators, educators, and health experts about the policies that have the greatest short- and long-term impact should encourage strategic investment in low-cost, high-return policies.

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