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[unreadable]; 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[unreadable] records bodily movement and energy expenditure through sensors that are attached to the body. The accuracy of measuring SPA and AEE with the IDEEA[unreadable] 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[unreadable] will be tested with equivalence tests and Bland-Altman regression analysis will be used to test if bias associated with the IDEEA[unreadable] 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.