Impact of data analysis methods for maximal fat oxidation estimation during exercise in sedentary adults Data analysis maximal fat oxidation

摘要

The maximal fat oxidation (MFO), and the exercise intensity that elicits MFO (Fat(max)), are considered excellent markers of fat metabolism during exercise. Besides individual's biological characteristics (e.g. fed state, physical fitness level, sex, or age), data selection and analysis can affect MFO and Fatmax estimations, yet the effect is unknown. We investigated (i) the impact of using a pre-defined time interval on MFO and Fat(max) estimation, and (ii) the impact of applying 2 different data analysis approaches (measured-values vs. polynomial-curve) on MFO and Fat(max) estimations in sedentary adults. A total of 151 (97 women) sedentary adults aged 29.2 +/- 13.2 years old participated in the study. We assessed MFO and Fatmax through a walking graded exercise test using indirect calorimetry. We pre-defined 13 different time intervals for data analysis, and the estimation of MFO and Fat(max) were performed through the measured-values and the polynomial-curve data analysis approaches. There were significant differences in MFO across pre-defined time intervals methods (P = 0.7). We observed significant differences in MFO between measured-values and the polynomial-curve data analysis approaches across the time intervals methods selected (all P = 0.2). In conclusion, our results revealed that there are no differences in MFO and Fat(max) across different time intervals methods selected using the polynomial-curve data analysis approach. We observed significant differences in MFO between measured-values vs. polynomial-curve data analysis approaches in all the study time intervals, whereas no differences were detected in Fatmax. Therefore, the use of polynomial-curve data analysis approach allows to compare MFO and Fat(max) using different time intervals in sedentary adults.