Statistical Mechanics of Human Weight Change
John C. Lang, Hans De Sterck, Daniel M. Abrams
(Submitted on 29 Sep 2016)
In the context of the global obesity epidemic, it is important to know who becomes obese and why. However, the processes that determine the changing shape of Body Mass Index (BMI) distributions in high-income societies are not well-understood. Here we establish the statistical mechanics of human weight change, providing a fundamental new understanding of human weight distributions. By compiling and analysing the largest data set so far of year-over-year BMI changes, we find, strikingly, that heavy people on average strongly decrease their weight year-over-year, and light people increase their weight. This drift towards the centre of the BMI distribution is balanced by diffusion resulting from random fluctuations in diet and physical activity that are, notably, proportional in size to BMI. We formulate a stochastic mathematical model for BMI dynamics, deriving a theoretical shape for the BMI distribution and offering a mechanism to explain the ongoing right-skewed broadening of BMI distributions over time. The model also provides new quantitative support for the hypothesis that peer-to-peer social influence plays a measurable role in BMI dynamics. More broadly, our results demonstrate a remarkable analogy with drift-diffusion mechanisms that are well-known from the physical sciences and finance.