Diet and exercise can successfully cause significant weight loss in obese individuals, but most people eventually regain their lost weight. Weight regain is likely due to a return to the former lifestyle and it is unclear what permanent changes would be required to maintain lost weight. In other words, if an obese person wishes to achieve a specified goal weight then how would their diet or physical activity have to permanently change to maintain their goal weight? A quantitative answer to this question at the outset of an obesity intervention could help both the patient and physician assess whether long-term adherence to the calculated lifestyle change is a realistic proposition. Such a calculation was not possible prior to the development of our recent mathematical model. Our mathematical model accounted for the decreased energy requirements at a reduced body weight and incorporates the nonlinear relationship between body fat and lean mass changes. We used the model to calculate the expected change of steady-state body weight loss arising from given changes of dietary energy intake and physical activity. Conversely, the model equations were also solved for the energy intake change required to maintain a particular body weight loss. The model was developed using data from 8 longitudinal weight loss studies representing 157 subjects with initial body weights ranging from 68-160 kg and stable weight changes between -7 and -54 kg. The model provided the first realistic calculations of body weight and composition change as well as the dietary modifications required for weight loss maintenance. Importantly, the model was implemented using standard spreadsheet software and can therefore be widely used by physicians and weight management professionals. In another project, we investigated patients with advanced cancer that experience debilitating involuntary weight loss. This wasting condition, called cachexia, is associated with a variety of metabolic changes that affect macronutrient and energy balance. Our computational model was recently used to integrate the available clinical data about how the known metabolic derangements (e.g., increased proteolysis, lipolysis, and gluconeogenesis) synergized with reduced energy intake to result in a progressive loss of body weight, fat mass and lean tissue. We also used the model to quantify the contribution of hepatomegaly to the elevated metabolic rate observed in patients with advanced colon cancer. Importantly, our model helps us understand the mechanisms of body weight change in this complex and serious disorder where it would be prohibitively difficult and invasive to attempt a comprehensive clinical study. Finally, we continue to develop a computational model of human macronutrient metabolism and have conducted several validation studies using a variety of published data on the metabolic responses to overfeeding, underfeeding, and isocaloric changes in dietary macronutrients. The model is beginning to be deployed as a clinical research tool in collaboration with NIH clinical investigators to help design prospective studies as well as plan and track clinical weight management programs. This model was recently used to design an NIH clinical protocol investigating how the body responds to selective reduction of dietary fat or carbohydrates.

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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
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
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
Freedhoff, Yoni; Hall, Kevin D (2016) Weight loss diet studies: we need help not hype. Lancet 388:849-51
Lobstein, Tim; Jackson-Leach, Rachel; Moodie, Marjory L et al. (2015) Child and adolescent obesity: part of a bigger picture. Lancet 385:2510-20
Ferrannini, Giulia; Hach, Thomas; Crowe, Susanne et al. (2015) Energy Balance After Sodium-Glucose Cotransporter 2 Inhibition. Diabetes Care 38:1730-5
Dietz, William H; Baur, Louise A; Hall, Kevin et al. (2015) Management of obesity: improvement of health-care training and systems for prevention and care. Lancet 385:2521-33
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
Hall, Kevin D; Bemis, Thomas; Brychta, Robert et al. (2015) Calorie for Calorie, Dietary Fat Restriction Results in More Body Fat Loss than Carbohydrate Restriction in People with Obesity. Cell Metab 22:427-36

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