Short and long-term energy intake patterns and their implications for human body weight regulation

Abstract

Adults consume millions of kilocalories over the course of a few years, but the typical weight gain amounts to only a few thousand kilocalories of stored energy. Furthermore, food intake is highly variable from day to day and yet body weight is remarkably stable. These facts have been used as evidence to support the hypothesis that human body weight is regulated by active control of food intake operating on both short and long time scales. Here, we demonstrate that active control of human food intake on short time scales is not required for body weight stability and that the current evidence for long term control of food intake is equivocal. To provide more data on this issue, we emphasize the urgent need for developing new methods for accurately measuring energy intake changes over long time scales. We propose that repeated body weight measurements can be used along with mathematical modeling to calculate long-term changes in energy intake and thereby quantify adherence to a diet intervention and provide dynamic feedback to individuals that seek to control their body weight.

Keywords: Body weight regulation; Energy balance; Energy intake; Feedback control; Food intake; Mathematical model.

Figure 1

Large daily fluctuations of energy intake and energy balance lead to little variation of body weight. (A) Daily energy intake data and computer simulated energy expenditure of a participant in the Beltsville one year dietary intake study [8]. (B) Weekly body weight data and computational model simulations illustrating the relative stability of body weight.

Figure 2

Simulated weight loss plateau and regain as a result of loss of diet adherence. (A) A prescribed 750 kcal/d reduction in baseline energy intake was predicted to result in a body weight trajectory falling within the green curves. However, weight loss typically plateaus after 6–8 months and is often followed by slow regain. (B) The gray curve shows the simulated daily energy intake changes underlying the body weight trajectory. The red curve is the 28 day moving average and the filled black circles and blue curves are the estimated average energy intake and its 95% confidence interval calculated using only the body weight data.

Figure 3

Schematic of a method for personalized model-based feedback control of body weight. Using individual anthropometric and demographic data, a personalized mathematical model of metabolism is created to plan a lifestyle intervention to achieve a goal body weight in a specified time frame. By monitoring body weight and physical activity repeatedly, adherence to the intervention can be calculated and used iteratively to provide quantitative feedback regarding revised body weight predictions or changes in the prescribed intervention required to achieve the body weight goal.

Figure 4

Hypothetical implementation of model-based feedback control of body weight. (A) After weight loss plateaued at 6 months, the control method was implemented to provide feedback on the loss of diet adherence and the revised diet prescription required to achieve the weight loss goal. (B) Continued monitoring of body weight allows for sustained monitoring of adherence to the prescribed intervention.