Calorie restriction causes multiple beneficial metabolic adaptations linearly related with the degree of weight loss in non-obese individuals: Results of CALERIE, a multicenter randomised controlled trial

Abstract

BACKGROUND & AIMS: Understanding the temporal association and relative power of anthropometric, body composition and energy metabolism measurements of calorie restriction (CR) in predicting metabolic and hormonal adaptations is important, given the clinical and public health implications of excess weight and adiposity. METHODS: Anthropometric (body weight, BMI, waist circumference), body composition (body fat and lean mass by DXA), energy metabolism (leptin and total daily energy intake by doubly labelled water [DLW]) markers and an extensive assessment of cardiometabolic, inflammatory and hormonal risk factors were obtained in 191, 21–50 year old non-obese (BMI 22·0–27·9 kg/m2) women and men, who participated in the 2-yr CALERIE randomized clinical trial. Pairwise correlations for each adiposity and energy metabolism measure were calculated against each other and against each metabolic parameter. In addition, spline and linear regression models were developed to determine a threshold effect of adiposity and energy metabolism measures to trigger changes in metabolic parameters. RESULTS: Among the progressively more sophisticated measures of adiposity, body weight is the variable that is most strongly correlated with cardiometabolic and inflammatory outcomes during CR-induced weight loss in young and middle-aged non-obese men and women. Waist circumference and DXA body fat are not superior to body weight or BMI in detecting these biological modifications. We did not find a specific threshold in weight loss to be exceeded for changes in metabolic and inflammatory adaptations to occur. Even small reductions in body weight cause a significant decline in serum T3 levels, a predictor of post-CR weight regain. CONCLUSIONS: Calorie restriction with adequate nutrition causes multiple beneficial cardiometabolic and hormonal adaptations that are linearly related with the degree of weight loss in non-obese individuals. Once a baseline has been established, tracking changes in body weight is sufficient to monitor improvements in metabolic health.