Dynamic model predicting overweight, obesity, and extreme obesity prevalence trends

Authors


  • Funding agencies: This research was supported in part by National Institutes of Health grants R15 DK090739, U01DK094418, HL45670, the John W. Barton Sr. Chair in Genetics and Nutrition, and a NORC Center Grant # 2P30DK072476 entitled “Nutritional Programming: Environmental and Molecular Interactions” sponsored by NIDDK.

  • Disclosure: Bouchard: Claude Bouchard is a consultant for Weight Watchers International and a member of the Scientific Advisory Board of Pathway Genomics. Dhurandhar: The following Patents are granted or have been applied for: ([1]) patent number 6,127,113: Viral obesity methods and compositions; ([2]) patent number 6,664,050: Viral obesity methods and compositions; ([3]) patent number US 8,008,436B2, dated August 30, 2011: Adenovirus 36 E4orf1 gene and protein and their uses. Provisional patent filed: Adenovirus Ad36 E4orf1 protein for prevention and treatment of nonalcoholic fatty liver disease, July 2010; and ([4]) rovisional patent filed: Enhanced glycemic control using Ad36E4orf1 and AKT1 Inhibitor. January 2012. Thomas: Diana Thomas is a consultant for Jenny Craig.

  • Author contributions: Study concept and design: Thomas, Bouchard. Drafting of the manuscript: Thomas, Weedermann, Heymsfield, Bouchard. Critical revision of the manuscript for important intellectual content: Thomas, Weedermann, Fuemmeler, Martin, Dhurandhar, Bredlau, Heymsfield, Ravussin, Bouchard. Model development: Thomas, Weedermann, Dhurandhar, Ravussin, Bouchard. Mathematical analysis: Thomas, Weedermann. Mathematical simulations: Bredlau.

Abstract

Objective

Obesity prevalence in the United States appears to be leveling, but the reasons behind the plateau remain unknown. Mechanistic insights can be provided from a mathematical model. The objective of this study is to model known multiple population parameters associated with changes in body mass index (BMI) classes and to establish conditions under which obesity prevalence will plateau.

Design and Methods

A differential equation system was developed that predicts population-wide obesity prevalence trends. The model considers both social and nonsocial influences on weight gain, incorporates other known parameters affecting obesity trends, and allows for country specific population growth.

Results

The dynamic model predicts that: obesity prevalence is a function of birthrate and the probability of being born in an obesogenic environment; obesity prevalence will plateau independent of current prevention strategies; and the US prevalence of overweight, obesity, and extreme obesity will plateau by about 2030 at 28%, 32%, and 9% respectively.

Conclusions

The US prevalence of obesity is stabilizing and will plateau, independent of current preventative strategies. This trend has important implications in accurately evaluating the impact of various anti-obesity strategies aimed at reducing obesity prevalence.

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