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Determining day‐to‐day human variation in indirect calorimetry using Bayesian decision theory

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What is the central question of this study? We sought to understand the day‐to‐day variability of human indirect calorimetry during rest and exercise. Previous work has been unable to separate… Click to show full abstract

What is the central question of this study? We sought to understand the day‐to‐day variability of human indirect calorimetry during rest and exercise. Previous work has been unable to separate human day‐to‐day variability from measurement error and within‐trial human variability. We developed models accounting for different levels of human‐ and machine‐level variance and compared the probability density functions using total variation distance. What is the main finding and its importance? After accounting for multiple levels of variance, the average human day‐to‐day variability of minute ventilation, CO2 output and O2 uptake is 4.0, 1.8 and 2.0%, respectively. This is a new method to understand human variability and directly enhances our understanding of human variance during indirect calorimetry.

Keywords: variation; indirect calorimetry; variability; day day; day

Journal Title: Experimental Physiology
Year Published: 2018

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