Assessment of low-to-moderate intensity physical activity thermogenesis in young adults using synchronized heart rate and accelerometry with branched-equation modeling

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Abstract

Low-to-moderate intensity physical activity thermogenesis is a highly variable and quantitatively important component of total energy expenditure that is difficult to assess outside the laboratory. Greater precision and accuracy in the measurement of this key contributor to energy balance is a research priority. We developed a laboratory-based protocol that simulated a range of low-to-moderate intensity physical activities. We characterized the bias and random (individual) error in estimating energy expenditure using combined accelerometry and heart rate (AHR) with branched-equation modeling and a simple motion sensor (pedometer) against an indirect calorimetry criterion. Twenty young adult subjects performed a 2-h laboratory-based protocol, simulating 6 low-to-moderate intensity physical activities interspersed with periods of rest. The physical activity level during the laboratory-based protocol reflected an energy expenditure toward the lower end of the active category. We found that AHR-derived energy expenditure showed no evidence of substantial fixed or proportional bias (mean bias 6%), whereas pedometer-derived energy expenditure showed both fixed and proportional bias (bias at minimum, mean, and maximum energy expenditure +11, -20, and -36%, respectively). It appears that AHR provides an accurate estimate of criterion energy expenditure whereas a simple motion sensor (pedometer) does not. It is noteworthy that AHR provides quantitative information about the nature and patterns of physical activity, such as the amount of time and/or energy spent engaged in physical activity above critical health-related thresholds. © 2006 American Society for Nutrition.

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Thompson, D., Batterham, A. M., Bock, S., Robson, C., & Stokes, K. (2006). Assessment of low-to-moderate intensity physical activity thermogenesis in young adults using synchronized heart rate and accelerometry with branched-equation modeling. In Journal of Nutrition (Vol. 136, pp. 1037–1042). American Institute of Nutrition. https://doi.org/10.1093/jn/136.4.1037

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