The Centersfor Disease Control currently estimates that approximately 67%of the US adult population is overweight, with body mass index (BMI) between 25 and 29.9and34%is obese (BMI>30). BMI levels above 25 have been linked to diseases and health related consequences such as coronary heart disease, type 2 diabetes, cancers (endometrial, breast, and colon), hypertension, dyslipidemia, stroke, liver and gallbladder disease, sleep apnea and respiratory problems,osteoarthritis, and gynecological problems[66].
In fact, it is estimated obesity related diseases currently account for approximately 9.1%of total national health care costs[66] With such a large proportion of the population considered overweight, mathematical models can provide intuition, insight, and solutions for eective weight loss and weight loss maintenance [2,4{6,18,19,31,32,53,55].
Thesedierential equation models apply state variables that track the quantity of macronutrients that provide energy, namely, carbohydrates, protein, and fat. The common goal of the models is to predict weight change as a result of changes in dietary intake and/or energy expenditure.
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A Simple Model Predicting Individual Weight Change in Humans
