Counting calories can be tedious and is often inaccurate, even when using the latest nutrition apps or research tools. Now, a team of researchers led by NIDDK Senior Investigator Kevin Hall, Ph.D. has shown that a mathematical model of human metabolism provides accurate measurements of calorie intake changes by simply tracking the person’s weight.
The researchers validated their method using data from the NIH-funded CALERIE study
, in which 140 men and women underwent a two-year calorie-restriction intervention. The study investigators calculated changes in the number of calories the participants ate throughout the intervention using repeated doses of doubly-labeled water (DLW) and dual energy x-ray absorptiometry (DXA) scans, expensive laboratory techniques not widely available. Using only each person’s age, height and sex, and weight measurements gathered throughout the two-year study, Hall and his team found that, on average, the model-calculated changes in daily calorie consumption were within 40 calories of the DLW and DXA methods.
The math model, published in 2011
, was created to accurately forecast body weight changes when people alter their diet and exercise habits, a capability that was validated using data from multiple controlled-feeding studies. The model was also developed into a popular online simulation tool.
The model’s new application presents an alternative to self-report methods, which tend to greatly underestimate calories eaten, and laboratory measurements that cost thousands of dollars to obtain a single data point. The method can be used retrospectively in any study that collected repeated weight data and provides researchers with an inexpensive and accurate method to track changes in calorie consumption in near-real-time. Investigators are currently examining how to apply the method for use by the public.
Sanghvi A, Redman LM, Martin CK, Ravussin E,
Hall KD. Validation of an inexpensive and accurate mathematical method to measure long-term changes in free-living energy intake.
American Journal of Clinical Nutrition 2015 June; 101