Meeting Abstract

67.6  Thursday, Jan. 6  A new multivariate model for predicting daily energy expenditure in active human populations OCOBOCK, C*; PONTZER, H; GOOKIN, J; BAYNES, S; Washington University in St. Louis; Washington University in St. Louis; The National Outdoor Leadership School; The National Outdoor Leadership School cjocoboc@artsci.wustl.edu

How can one most accurately model and predict human daily energy expenditure? Numerous studies have explored and modeled the individual variables that make up total energy expenditure such as thermoregulatory and activity costs. However, few have taken the approach of treating these variables as interacting entities, nor built a model tested by data collected from highly active, morphologically variable humans in natural environments. In this study, we built a multivariate model predicting daily energy expenditure based on the interaction among basal metabolism, thermoregulation, and activity levels as they are affected by both morphology and climate. This model was then tested using empirical data collected from healthy, highly active adults participating in a National Outdoor Leadership School course. Daily energy expenditure (kCal/day) was measured over a six day period using the doubly labeled water and flex-heart rate methods. Daily activity, including hiking and rigorous rock climbing, and daily caloric intake were also measured during this period. Resting metabolism measurements and flex-heart rate calibrations were performed using oxygen consumption and carbon dioxide production both before and after subjects participated on their course. This model provides a road map for highlighting the variables with the greatest predictive power enabling more accurate estimations of human daily energy expenditure.