Diana M Thomas1, Corby K Martin1, Leanne M Redman1, Steven B Heymsfield1, Steven Lettieri1, James A Levine1, Claude Bouchard1, Dale A Schoeller1. 1. From the Center for Quantitative Obesity Research, Montclair State University, Montclair, NJ (DMT); the Pennington Biomedical Research Center, Baton Rouge, LA (CKM, LMR, SBH, and CB); the Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA (SL); Obesity Solutions, Mayo Clinic, Arizona State University, Phoenix, AZ (JAL); and Nutritional Sciences, University of Wisconsin, Madison, WI (DAS).
Abstract
BACKGROUND:Clinical weight loss in individuals typically stabilizes at 6 mo. However, validated models of dynamic energy balance have consistently shown weight plateaus between 1 and 2 y. The cause for this discrepancy is unclear. OBJECTIVE: We developed 2 mathematical models on the basis of the first law of thermodynamics to investigate plausible explanations for reaching an early weight plateau at 6 mo. DESIGN: The first model was an energy-expenditure adaptation model and was applied to determine the degree of metabolic adaptation required to generate this plateau. The second model was an intermittent lack-of-adherence model formulated by using a randomly fluctuating energy intake term accounting for intermittent noncompliance in dietary intake to reach this plateau. To set model variables, validate models, and compare free-living weight-loss patterns to in-residence supervised programs, we applied the following 4 different studies: The US NHANES 1999-2004, Comprehensive Assessment of Long-term Effects of Reducing Intake of Energy (CALERIE) weight-loss study, the Bouchard Twin overfeeding study, and the Minnesota Starvation Experiment. RESULTS: The metabolic adaptation model increased final weight but did not affect the predicted plateau time point. The intermittent lack-of-adherence model generated oscillating weight graphs that have been frequently observed in weight-loss studies. The model showed that a 6-mo weight-loss plateau can be attained despite what can be considered as high diet adherence. The model was programmed as a downloadable application. CONCLUSIONS: An intermittent lack of diet adherence, not metabolic adaptation, is a major contributor to the frequently observed early weight-loss plateau. The new weight-loss prediction software, which incorporates an intermittent lack of adherence, can be used to guide and inform patients on realistic levels of adherence on the basis of patient lifestyle.
RCT Entities:
BACKGROUND: Clinical weight loss in individuals typically stabilizes at 6 mo. However, validated models of dynamic energy balance have consistently shown weight plateaus between 1 and 2 y. The cause for this discrepancy is unclear. OBJECTIVE: We developed 2 mathematical models on the basis of the first law of thermodynamics to investigate plausible explanations for reaching an early weight plateau at 6 mo. DESIGN: The first model was an energy-expenditure adaptation model and was applied to determine the degree of metabolic adaptation required to generate this plateau. The second model was an intermittent lack-of-adherence model formulated by using a randomly fluctuating energy intake term accounting for intermittent noncompliance in dietary intake to reach this plateau. To set model variables, validate models, and compare free-living weight-loss patterns to in-residence supervised programs, we applied the following 4 different studies: The US NHANES 1999-2004, Comprehensive Assessment of Long-term Effects of Reducing Intake of Energy (CALERIE) weight-loss study, the Bouchard Twin overfeeding study, and the Minnesota Starvation Experiment. RESULTS: The metabolic adaptation model increased final weight but did not affect the predicted plateau time point. The intermittent lack-of-adherence model generated oscillating weight graphs that have been frequently observed in weight-loss studies. The model showed that a 6-mo weight-loss plateau can be attained despite what can be considered as high diet adherence. The model was programmed as a downloadable application. CONCLUSIONS: An intermittent lack of diet adherence, not metabolic adaptation, is a major contributor to the frequently observed early weight-loss plateau. The new weight-loss prediction software, which incorporates an intermittent lack of adherence, can be used to guide and inform patients on realistic levels of adherence on the basis of patient lifestyle.
Authors: D M Thomas; C K Martin; S Lettieri; C Bredlau; K Kaiser; T Church; C Bouchard; S B Heymsfield Journal: Int J Obes (Lond) Date: 2013-04-08 Impact factor: 5.095
Authors: Diana M Thomas; Dale A Schoeller; Leanne A Redman; Corby K Martin; James A Levine; Steven B Heymsfield Journal: Am J Clin Nutr Date: 2010-10-20 Impact factor: 7.045
Authors: Leonie K Heilbronn; Lilian de Jonge; Madlyn I Frisard; James P DeLany; D Enette Larson-Meyer; Jennifer Rood; Tuong Nguyen; Corby K Martin; Julia Volaufova; Marlene M Most; Frank L Greenway; Steven R Smith; Walter A Deutsch; Donald A Williamson; Eric Ravussin Journal: JAMA Date: 2006-04-05 Impact factor: 56.272
Authors: Carl Pieper; Leanne Redman; Susan Racette; Susan Roberts; Manju Bhapkar; James Rochon; Corby Martin; William Kraus; Sai Das; Donald Williamson; Eric Ravussin Journal: Clin Trials Date: 2011-03-08 Impact factor: 2.486
Authors: Corby K Martin; Leonie K Heilbronn; Lilian de Jonge; James P DeLany; Julia Volaufova; Stephen D Anton; Leanne M Redman; Steven R Smith; Eric Ravussin Journal: Obesity (Silver Spring) Date: 2007-12 Impact factor: 5.002
Authors: Diana M Thomas; Corby K Martin; Steven Heymsfield; Leanne M Redman; Dale A Schoeller; James A Levine Journal: J Biol Dyn Date: 2011-11 Impact factor: 2.179
Authors: Diana M Thomas; Andrada E Ivanescu; Corby K Martin; Steven B Heymsfield; Kaitlyn Marshall; Victoria E Bodrato; Donald A Williamson; Stephen D Anton; Frank M Sacks; Donna Ryan; George A Bray Journal: Am J Clin Nutr Date: 2014-12-24 Impact factor: 7.045
Authors: Johanna W Lampe; Ying Huang; Marian L Neuhouser; Lesley F Tinker; Xiaoling Song; Dale A Schoeller; Soyoung Kim; Daniel Raftery; Chongzhi Di; Cheng Zheng; Yvonne Schwarz; Linda Van Horn; Cynthia A Thomson; Yasmin Mossavar-Rahmani; Shirley Aa Beresford; Ross L Prentice Journal: Am J Clin Nutr Date: 2016-12-28 Impact factor: 7.045
Authors: Diane L Rosenbaum; Leah M Schumacher; Katherine Schaumberg; Amani D Piers; Monika E Gaspar; Michael R Lowe; Evan M Forman; Meghan L Butryn Journal: Clin Obes Date: 2016-03-29
Authors: Marian L Neuhouser; Mary Pettinger; Johanna W Lampe; Lesley F Tinker; Stephanie M George; Jill Reedy; Xiaoling Song; Bharat Thyagarajan; Shirley A Beresford; Ross L Prentice Journal: Am J Epidemiol Date: 2021-11-02 Impact factor: 4.897