Obesity and its resulting diseases are estimated to affect over twenty percent of the American population. While there are various strategies to lose excess weight, caloric restriction is considered the most effective natural weight loss intervention. However, the results of diet induced weight loss are modest and it is suspected that patient dietary adherence is largely responsible. To assess the role of adherence on weight loss, experimental study design should include methods to monitor dietary intake. Current valid methods for assessing dietary intake require extensive clinical visits or subject confinement. Both methods are expensive and not feasible for extended periods of time. Therefore, there is a critical need for an affordable, non-invasive, accurate method to monitor subject intake during weight loss. We propose to meet this need through application of a validated energy balance model.
Three specific aims are proposed: (1) To rigorously develop a computational model that estimates individual ongoing energy intake during weight loss. (2) To validate the computational model through comparison with existing clinical measurements of dietary intake. (3) To determine markers of successful adherence from application of the model to existing weight loss datasets. To accomplish these aims, we have assembled an experienced multi-disciplinary team of obesity researchers and mathematicians. The proposed model is positioned to change current practices for determining patient dietary adherence and provide vital information for understanding the national obesity problem.

Public Health Relevance

Caloric restriction is the most effective natural lifestyle intervention known to reduce weight and improve blood pressure, cholesterol levels, and other markers of health. Diet induced weight loss requires individuals to follow prescribed caloric restrictions;however, current methods to determine actual patient food consumption are either expensive or unreliable. The proposed mathematical approach will eliminate these challenges for determining dietary intake during weight loss.

National Institute of Health (NIH)
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Academic Research Enhancement Awards (AREA) (R15)
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Kidney, Nutrition, Obesity and Diabetes (KNOD)
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Everhart, James
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Montclair State University
Biostatistics & Other Math Sci
Schools of Arts and Sciences
United States
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Thomas, Diana M; Ivanescu, Andrada E; Martin, Corby K et al. (2015) Predicting successful long-term weight loss from short-term weight-loss outcomes: new insights from a dynamic energy balance model (the POUNDS Lost study). Am J Clin Nutr 101:449-54
Thomas, Diana M; Martin, Corby K; Redman, Leanne M et al. (2014) Effect of dietary adherence on the body weight plateau: a mathematical model incorporating intermittent compliance with energy intake prescription. Am J Clin Nutr 100:787-95
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Thomas, Diana M; Weedermann, Marion; Fuemmeler, Bernard F et al. (2014) Dynamic model predicting overweight, obesity, and extreme obesity prevalence trends. Obesity (Silver Spring) 22:590-7
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Dawson, John A; Hall, Kevin D; Thomas, Diana M et al. (2014) Novel mathematical models for investigating topics in obesity. Adv Nutr 5:561-2
Dawson, John A; Hall, Kevin D; Thomas, Diana M et al. (2014) Novel mathematical models for investigating topics in obesity. Adv Nutr 5:561-2
Archer, Edward; Lavie, Carl J; McDonald, Samantha M et al. (2013) Maternal inactivity: 45-year trends in mothers' use of time. Mayo Clin Proc 88:1368-77
Thomas, Diana M; Bredlau, Carl; Bosy-Westphal, Anja et al. (2013) Relationships between body roundness with body fat and visceral adipose tissue emerging from a new geometrical model. Obesity (Silver Spring) 21:2264-71
Thomas, D M; Martin, C K; Lettieri, S et al. (2013) Can a weight loss of one pound a week be achieved with a 3500-kcal deficit? Commentary on a commonly accepted rule. Int J Obes (Lond) 37:1611-3

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