We continue to develop mathematical models of human metabolism and body weight dynamics. We partnered with the USDA to develop the NIH Body Weight Planner (http://BWPlanner.niddk.nih.gov) that allows users to make personalized calorie and physical activity plans to reach a goal weight within a specific time period and to maintain it afterwards. This technology was adopted as part of the USDA SuperTracker system that provides personalized meal plans based on the calorie results from the Body Weight Planner. SuperTracker is a free food, physical activity, and weight tracking tool from ChooseMyPlate.gov. We have extended our model of childhood growth to simulate normal development from birth through adulthood as well as the development of childhood obesity. This model is also being applied to better understand growth faltering with malnutrition. We used our model of adult macronutrient metabolism to successfully predict the results of a clinical research study involving the metabolic responses to selective restriction of dietary carbohydrates versus fat in adults with obesity. When simulating what might happen over longer periods, the model predicted relatively small differences in body fat loss with widely varying ratios of carbs to fat. Those results suggest the body may eventually minimize differences in body fat loss when diets have the same number of calories. We validated that our mathematical method provides accurate measurements of calorie intake changes by simply tracking peoples weight. The method was validated using data from 140 men and women who underwent a two-year calorie-restriction intervention. We 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 persons age, height and sex, and weight measurements gathered throughout the two-year study, we showed that, on average, the model-calculated changes in daily calorie consumption were within 40 calories of the DLW and DXA methods.

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9
Fiscal Year
2015
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U.S. National Inst Diabetes/Digst/Kidney
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Guo, Juen; Brager, Danielle C; Hall, Kevin D (2018) Simulating long-term human weight-loss dynamics in response to calorie restriction. Am J Clin Nutr 107:558-565
Hall, Kevin D; Kahan, Scott (2018) Maintenance of Lost Weight and Long-Term Management of Obesity. Med Clin North Am 102:183-197
Hall, Kevin D; Schoeller, Dale A; Brown, Andrew W (2018) Reducing Calories to Lose Weight. JAMA 319:2336-2337
Hall, Kevin D; Sanghvi, Arjun; Göbel, Britta (2017) Proportional Feedback Control of Energy Intake During Obesity Pharmacotherapy. Obesity (Silver Spring) 25:2088-2091
Hall, Kevin D; Guo, Juen (2017) Obesity Energetics: Body Weight Regulation and the Effects of Diet Composition. Gastroenterology 152:1718-1727.e3
Katan, Martijn B; de Ruyter, Janne C; Kuijper, Lothar D J et al. (2016) Impact of Masked Replacement of Sugar-Sweetened with Sugar-Free Beverages on Body Weight Increases with Initial BMI: Secondary Analysis of Data from an 18 Month Double-Blind Trial in Children. PLoS One 11:e0159771
MacLeod, Erin L; Hall, Kevin D; McGuire, Peter J (2016) Computational modeling to predict nitrogen balance during acute metabolic decompensation in patients with urea cycle disorders. J Inherit Metab Dis 39:17-24
Polidori, David; Sanghvi, Arjun; Seeley, Randy J et al. (2016) How Strongly Does Appetite Counter Weight Loss? Quantification of the Feedback Control of Human Energy Intake. Obesity (Silver Spring) 24:2289-2295
Freedhoff, Yoni; Hall, Kevin D (2016) Weight loss diet studies: we need help not hype. Lancet 388:849-51
MacLean, Paul S; Wing, Rena R; Davidson, Terry et al. (2015) NIH working group report: Innovative research to improve maintenance of weight loss. Obesity (Silver Spring) 23:7-15

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