? The research proposed in this Career Development Award consists of two projects. During Project 1, the accuracy of measuring spontaneous physical activity (SPA) and activity energy expenditure (AEE) with the Intelligent Device for Energy Expenditure and Activity (IDEEA(tm); MiniSun LLC, Fresno, CA) will be tested. SPA consists of the energy expended with bodily movement (e.g., fidgeting, changing posture) and it is measured in the metabolic chamber. AEE consists of the energy expended in all activities and it is measured with doubly labeled water (DLW). The IDEEA(tm) records bodily movement and energy expenditure through sensors that are attached to the body. The accuracy of measuring SPA and AEE with the IDEEA(tm) will be tested in a group of lean and overweight adults who spend 24 hours in a metabolic chamber and whose AEE is measured with DLW for a one-week free-living period. The accuracy of the IDEEA(tm) will be tested with equivalence tests and Bland-Altman regression analysis will be used to test if bias associated with the IDEEA(tm) is consistent across different levels of energy expenditure. The ability of SPA and AEE to predict weight loss during a two-year calorie restriction trial will also be tested with regression analysis, and moderating and mediating effects of gender and activity temperament will be tested. In addition, the ability of the amount of time spent engaging in, and the energy costs of, active and sedentary behaviors at baseline to predict weight loss will be tested. During Project 2, two data analytic techniques, cluster analysis and taxometric analysis, will be utilized to test for clusters and distinct groups of people (taxons) whose metabolic or behavioral/psycho social profile predisposes them to weight gain and obesity. Project 2 will rely on two sources of data: 1) an archival database of metabolic variables from Pima Indians and Caucasians, and 2) data from a two-year weight loss trial that includes both metabolic and behavioral/psychosocial variables. The ability of cluster and taxometric analyses to identify clusters or taxons of people who are predisposed to obesity will be tested by determining if these clusters or taxons predict weight loss during the two-year weight loss trial. Furthermore, these analyses represent a thorough test for the presence of a """"""""thrifty metabolic phenotype."""""""" The research outlined in this Career Development Award will provide a foundation for an independent research career. Moreover, this research will provide important information about the pathogenesis of obesity and whether distinct groups of people are predisposed to obesity, or if they differ from lean individuals on dimensional variables. The results of this study will provide important information on targets for interventions designed to alter energy balance and promote weight loss or weight gain prevention. ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
Type
Mentored Patient-Oriented Research Career Development Award (K23)
Project #
5K23DK068052-02
Application #
7184438
Study Section
Diabetes, Endocrinology and Metabolic Diseases B Subcommittee (DDK)
Program Officer
Podskalny, Judith M,
Project Start
2006-04-01
Project End
2010-03-31
Budget Start
2007-04-01
Budget End
2008-03-31
Support Year
2
Fiscal Year
2007
Total Cost
$80,360
Indirect Cost
Name
Lsu Pennington Biomedical Research Center
Department
Type
Organized Research Units
DUNS #
611012324
City
Baton Rouge
State
LA
Country
United States
Zip Code
70808
Correa, John B; Apolzan, John W; Shepard, Desti N et al. (2016) Evaluation of the ability of three physical activity monitors to predict weight change and estimate energy expenditure. Appl Physiol Nutr Metab 41:758-66
Sloan, Robert A; Sawada, Susumu S; Martin, Corby K et al. (2015) Combined association of fitness and central adiposity with health-related quality of life in healthy Men: a cross-sectional study. Health Qual Life Outcomes 13:188
Martin, C K; Nicklas, T; Gunturk, B et al. (2014) Measuring food intake with digital photography. J Hum Nutr Diet 27 Suppl 1:72-81
Apolzan, John W; Bray, George A; Smith, Steven R et al. (2014) Effects of weight gain induced by controlled overfeeding on physical activity. Am J Physiol Endocrinol Metab 307:E1030-7
Apolzan, John W; Bray, George A; Hamilton, Marc T et al. (2014) Short-term overeating results in incomplete energy intake compensation regardless of energy density or macronutrient composition. Obesity (Silver Spring) 22:119-30
Williamson, Donald A; Han, Hongmei; Johnson, William D et al. (2013) Modification of the school cafeteria environment can impact childhood nutrition. Results from the Wise Mind and LA Health studies. Appetite 61:77-84
Heymsfield, Steven B; Thomas, Diana; Martin, Corby K et al. (2012) Energy content of weight loss: kinetic features during voluntary caloric restriction. Metabolism 61:937-43
Williamson, Donald A; Champagne, Catherine M; Harsha, David W et al. (2012) Effect of an environmental school-based obesity prevention program on changes in body fat and body weight: a randomized trial. Obesity (Silver Spring) 20:1653-61
Thomson, Jessica L; Tussing-Humphreys, Lisa M; Martin, Corby K et al. (2012) Associations among school characteristics and foodservice practices in a nationally representative sample of United States schools. J Nutr Educ Behav 44:423-31
Martin, Corby K; Correa, John B; Han, Hongmei et al. (2012) Validity of the Remote Food Photography Method (RFPM) for estimating energy and nutrient intake in near real-time. Obesity (Silver Spring) 20:891-9

Showing the most recent 10 out of 46 publications