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COVID-19 Working Paper: Obesity Prevalence Among U.S. Adult Subpopulations During the First Year of the COVID-19 Pandemic

Author

Listed:
  • Ehmke, Mariah D.
  • Restrepo, Brandon J.

Abstract

Data from the 2011–20 Behavioral Risk Factor Surveillance System were leveraged to estimate obesity disparities prior to the spring 2020 arrival of the Coronavirus (COVID-19) pandemic and during the first year of the pandemic, and then intra-pandemic changes in adult obesity rates were estimated across various population subgroups. Adult obesity was modeled as a function of various demographic and socioeconomic characteristics—household composition, urbanicity, Census region, age, race, gender, income, and education—over pre-pandemic and pandemic periods using a linear regression model estimated by ordinary least squares. The regression coefficients were then used to calculate the pre-pandemic and intra-pandemic obesity rates for the overall population and by subpopulation. Overall U.S. adult obesity prevalence was significantly higher during the first year of the pandemic by 1.3 percentage points (pp). This amounts to an obesity increase of 3.2 percent when compared with an obesity rate of 40.7 percent over the pre-pandemic period from January 1, 2019, to March 12, 2020. The net societal increase in early pandemic obesity rates was not evenly distributed across subpopulations. Obesity rates significantly increased by a larger amount for adults in subgroups with a lower accumulation of long-term human capital (such as education and skills) and greater potential need for institutional and societal support. Intra-pandemic obesity growth rates were significantly higher by 5.6 percent among adults with annual household incomes that qualified for benefits from the Supplemental Nutrition Assistance Program (SNAP) and by 7.3 percent for adults whose education level was below a high school diploma. Higher intra-pandemic growth rates for obesity were also observed for young adults (aged 20–39) (5.6 percent) and adults aged 20 years or older living in the West Census region and west to the Pacific Ocean, which includes all States from Montana, Wyoming, Colorado, and New Mexico (7.6 percent).

Suggested Citation

  • Ehmke, Mariah D. & Restrepo, Brandon J., 2023. "COVID-19 Working Paper: Obesity Prevalence Among U.S. Adult Subpopulations During the First Year of the COVID-19 Pandemic," Administrative Publications 340802, United States Department of Agriculture, Economic Research Service.
    • Handle: RePEc:ags:uersap:340802
    DOI: 10.22004/ag.econ.340802
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    References listed on IDEAS

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    1. Cawley, John & Maclean, Johanna Catherine & Hammer, Mette & Wintfeld, Neil, 2015. "Reporting error in weight and its implications for bias in economic models," Economics & Human Biology, Elsevier, vol. 19(C), pages 27-44.
    2. Wells, Jonathan C.K. & Marphatia, Akanksha A. & Cole, Tim J. & McCoy, David, 2012. "Associations of economic and gender inequality with global obesity prevalence: Understanding the female excess," Social Science & Medicine, Elsevier, vol. 75(3), pages 482-490.
    3. Ver Ploeg, Michele & Mancino, Lisa & Lin, Biing-Hwan, 2007. "Food and Nutrition Assistance Programs and Obesity: 1976-2002," Economic Research Report 55965, United States Department of Agriculture, Economic Research Service.
    4. Okrent, Abigail & Zeballos, Eliana, 2022. "COVID-19 Working Paper: Consumer Food Spending Changes During the COVID-19 Pandemic," Amber Waves:The Economics of Food, Farming, Natural Resources, and Rural America, United States Department of Agriculture, Economic Research Service, vol. 2022(Administr), December.
    5. John Cawley, 2004. "The Impact of Obesity on Wages," Journal of Human Resources, University of Wisconsin Press, vol. 39(2).
    6. Okrent, Abigail & Zeballos, Eliana, 2022. "COVID-19 Working Paper: Consumer Food Spending Changes During the COVID-19 Pandemic," USDA Miscellaneous 333545, United States Department of Agriculture.
    7. Anca M. Grecu & Kurt W. Rotthoff, 2015. "Economic growth and obesity: findings of an Obesity Kuznets curve," Applied Economics Letters, Taylor & Francis Journals, vol. 22(7), pages 539-543, May.
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