Framingham State Food Study

Many overweight and obese people can lose weight for a few months, but most have difficulty maintaining weight loss over the long term. One explanation for the poor long-term outcome of weight-loss diets relates to behavior, in that motivation to adhere to restrictive regimens typically diminishes with time. An alternative explanation is that weight loss elicits biological adaptations - specifically a decline in energy expenditure and an increase in hunger - that promote weight regain. The purpose of this study is to evaluate the effects of dietary composition on energy expenditure and risk for chronic diseases, while also exploring physiological mechanisms underlying these effects. The study will be performed in collaboration with Framingham State University, providing a novel and feasible method for feeding subjects in dining halls and monitoring compliance. Following 12±2% weight loss on a standard run-in diet, 150 adults (aged 18 to 65 years) will be randomly assigned to one of three weight-loss maintenance diets controlled for protein content (20% of energy) and varying widely in dietary carbohydrate-to-fat ratio: Low-carbohydrate (20% of energy from carbohydrate, 60% fat), Moderate- carbohydrate (40% carbohydrate, 40% fat), High-carbohydrate (60% carbohydrate, 20% fat). During the weight-loss maintenance phase, energy intake will be adjusted to prevent changes in body weight. The primary outcome will be change in total energy expenditure (indirect calorimetry using stable isotopes) through 20 weeks. Secondary outcomes during weight maintenance will include resting energy expenditure (indirect calorimetry using respiratory gas exchange), physical activity (accelerometry), measures of insulin resistance and skeletal muscle work efficiency, components of the metabolic syndrome, and hormonal and metabolic measures that might inform an understanding of physiological mechanisms. We also will assess weight change during a 2-week ad libitum feeding phase, as an objective measure of dietary effects on hunger. The analytic framework for addressing study hypothesis will be repeated-measures analysis of variance, with adjustment for covariates (sex, race, ethnicity, age, anthropometrics, insulin sensitivity and secretion, obesity-related genes). We also will test each covariate for effect modification (covariate × diet interaction).