Purpose of review: Dynamic interrelationships between food intake, energy expenditure, energy partitioning, and metabolic fuel selection underlie changes in body weight and composition. A quantitative understanding of these interrelationships is becoming increasingly important given the rise of the worldwide obesity epidemic and the widespread interest in weight management. This review describes how mathematical models offer a quantitative framework for integrating dynamic physiological and behavioral data underlying body weight dynamics in both humans and mice.
Recent findings: Mathematical models have provided important insights regarding the drivers of the obesity epidemic, how metabolism adapts to different diets, the predicted magnitude and variability of weight change, and why mouse models have obesity phenotypes. Because mathematical models are constrained by conservation laws, they can also be used to infer physiological variables that are difficult to measure directly.
Summary: Mathematical models can help improve our understanding of the dynamic energy and macronutrient imbalances that give rise to changes in body weight and composition over time. The model development process can also highlight important knowledge gaps and model simulations can help design and predict the results of key new experiments to fill those gaps.