Obesity and severe obesity forecasts through 2030.

Published

Journal Article

BACKGROUND: Previous efforts to forecast future trends in obesity applied linear forecasts assuming that the rise in obesity would continue unabated. However, evidence suggests that obesity prevalence may be leveling off. PURPOSE: This study presents estimates of adult obesity and severe obesity prevalence through 2030 based on nonlinear regression models. The forecasted results are then used to simulate the savings that could be achieved through modestly successful obesity prevention efforts. METHODS: The study was conducted in 2009-2010 and used data from the 1990 through 2008 Behavioral Risk Factor Surveillance System (BRFSS). The analysis sample included nonpregnant adults aged ≥ 18 years. The individual-level BRFSS variables were supplemented with state-level variables from the U.S. Bureau of Labor Statistics, the American Chamber of Commerce Research Association, and the Census of Retail Trade. Future obesity and severe obesity prevalence were estimated through regression modeling by projecting trends in explanatory variables expected to influence obesity prevalence. RESULTS: Linear time trend forecasts suggest that by 2030, 51% of the population will be obese. The model estimates a much lower obesity prevalence of 42% and severe obesity prevalence of 11%. If obesity were to remain at 2010 levels, the combined savings in medical expenditures over the next 2 decades would be $549.5 billion. CONCLUSIONS: The study estimates a 33% increase in obesity prevalence and a 130% increase in severe obesity prevalence over the next 2 decades. If these forecasts prove accurate, this will further hinder efforts for healthcare cost containment.

Full Text

Duke Authors

Cited Authors

  • Finkelstein, EA; Khavjou, OA; Thompson, H; Trogdon, JG; Pan, L; Sherry, B; Dietz, W

Published Date

  • June 2012

Published In

Volume / Issue

  • 42 / 6

Start / End Page

  • 563 - 570

PubMed ID

  • 22608371

Pubmed Central ID

  • 22608371

Electronic International Standard Serial Number (EISSN)

  • 1873-2607

International Standard Serial Number (ISSN)

  • 0749-3797

Digital Object Identifier (DOI)

  • 10.1016/j.amepre.2011.10.026

Language

  • eng