Noninvasive assessment of energy expenditure in children.

This study establishes an affordable, simple, and noninvasive method to assess energy expenditure (EE) in children, an underrepresented group. The method is based on regression modeling, where prediction of oxygen consumption (VO(2)), a proxy of EE, was deduced from heart rate (HR) and several variables that adjusted for interindividual variability. Limb activities (arms vs. legs) and posture (sitting vs. standing) were represented in the regression as dichotomous covariates. The order of activities and intensities was randomized. Seventy-four children (aged 7-10 years), raised at sea-level (Seattle, WA), comprised the sample. Anthropometric measures were taken, and VO(2) and HR were measured for activities using the arms in sitting and standing positions (mixing and punching), as well as walking at different velocities on a treadmill. Repeated measures and least square regression estimation were used. HR, body mass, number of hours of physical activity per week (HPA), an interaction term between sitting and standing resting HR, and the two dichotomous variables, sex and limbs, were significant covariates; posture was not. Several equations were developed for various field uses. The equations were built from sea-level data, but ultimately this method could serve as a baseline for developing a similar approach in other populations, where noninvasive estimation of EE is imperative in order to gain a better understanding of children's energetic issues.