Dynamic model predicting overweight, obesity, and extreme obesity prevalence trends.
Bottom Line: Mechanistic insights can be provided from a mathematical model.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.This trend has important implications in accurately evaluating the impact of various anti-obesity strategies aimed at reducing obesity prevalence.
Affiliation: Center for Quantitative Obesity Research, Montclair State University, Montclair, New Jersey, USA.Show MeSH
Related in: MedlinePlus
Mentions: Modeling this flow requires identification of the mechanisms which increase or decrease the population within each BMI classification. The mechanisms considered in the developed model appear as a flowchart in Figure 1. Each compartment depicted in Figure 1 represents a state variable or more importantly, a variable we desire a prediction for over time. Table 1 lists each term of the differential equation model that describes the flow from and to each compartment as depicted in Figure 1.
Affiliation: Center for Quantitative Obesity Research, Montclair State University, Montclair, New Jersey, USA.