Obesity trend in the United States and economic intervention options to change it: A simulation study linking ecological epidemiology and system dynamics modeling
- PMID: 29857248
- PMCID: PMC6953626
- DOI: 10.1016/j.puhe.2018.01.013
Obesity trend in the United States and economic intervention options to change it: A simulation study linking ecological epidemiology and system dynamics modeling
Abstract
Objectives: To study the country-level dynamics and influences between population weight status and socio-economic distribution (employment status and family income) in the US and to project the potential impacts of socio-economic-based intervention options on obesity prevalence.
Study design: Ecological study and simulation.
Methods: Using the longitudinal data from the 2001-2011 Medical Expenditure Panel Survey (N = 88,453 adults), we built and calibrated a system dynamics model (SDM) capturing the feedback loops between body weight status and socio-economic status distribution and simulated the effects of employment- and income-based intervention options.
Results: The SDM-based simulation projected rising overweight/obesity prevalence in the US in the future. Improving people's income from lower to middle-income group would help control the rising prevalence, while only creating jobs for the unemployed did not show such effect.
Conclusions: Improving people from low- to middle-income levels may be effective, instead of solely improving reemployment rate, in curbing the rising obesity trend in the US adult population. This study indicates the value of the SDM as a virtual laboratory to evaluate complex distributive phenomena of the interplay between population health and economy.
Keywords: Employment rate; Income; Obesity; Simulation; System dynamics model.
Copyright © 2018 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.
Conflict of interest statement
Ethical statement
The authors have no conflict of interest. The study was based on secondary anonymous data in governmental open data repository systems.
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