Dynamic Empirically Based Model for Understanding Future Trends in US Obesity Prevalence in the Context of Social Influences

Leah Frerichs, Ozgur M. Araz, Larissa Calancie, Terry T.K. Huang, Kristen Hassmiller Lich

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Objective: This study aimed to (1) identify mechanistic model structures that produced quality fit to historic obesity prevalence trends and (2) evaluate the sensitivity of future obesity prevalence to social transmission and nonsocial parameters. Methods: An age- and gender-structured compartmental model was used to describe transitions between weight status groups. Four model structures with different combinations of social transmission and nonsocial mechanisms were calibrated to match historic time series and assessed for quality of fit. Projections of overall obesity prevalence to 2052 were simulated, and sensitivity analyses were conducted. Results: The model structure that included only nonsocial mechanisms indicated that the overall obesity prevalence in the United States has already stabilized and will increase little more; however, it underestimated observed obesity prevalence since 2013. If social transmission mechanisms influence obesity, the model estimated continued increases in obesity prevalence, reaching 48.0% to 55.1% by 2050. Obesity prevalence was most sensitive to changes in the adult social transmission parameters, especially among women. Conclusions: The model projected that US obesity prevalence in the overall population will likely continue to increase for decades. The findings that obesity prevalence was most sensitive to adult parameters can be used to inform conversations about priorities for public health and health care programs and policies.

Original languageEnglish (US)
Pages (from-to)1671-1681
Number of pages11
JournalObesity
Volume27
Issue number10
DOIs
StatePublished - Oct 1 2019

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Endocrinology, Diabetes and Metabolism
  • Endocrinology
  • Nutrition and Dietetics

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