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

Diana M. Thomas, Marion Weedermann, Bernard F. Fuemmeler, Corby K. Martin, Nikhil V. Dhurandhar, Carl Bredlau, Steven B. Heymsfield, Eric Ravussin, Claude Bouchard

Research output: Contribution to journalArticle

37 Scopus citations

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.

Original languageEnglish
Pages (from-to)590-597
Number of pages8
JournalObesity
Volume22
Issue number2
DOIs
StatePublished - Feb 2014

Fingerprint Dive into the research topics of 'Dynamic model predicting overweight, obesity, and extreme obesity prevalence trends'. Together they form a unique fingerprint.

Cite this