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... Show moreThe 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 < 0.001) applying measured-values data analysis approach, while no statistical differences were observed when using polynomial-curve data analysis approach (P = 0.077). There were no differences in Fat(max) across pre-defined time intervals independently of the data analysis approach (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 <= 0.05), and no differences were observed in Fat(max) (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. Show less
Having valid and reliable resting energy expenditure (REE) estimations is crucial to establish reachable goals for dietary and exercise interventions. However, most of the REE predictive equations... Show moreHaving valid and reliable resting energy expenditure (REE) estimations is crucial to establish reachable goals for dietary and exercise interventions. However, most of the REE predictive equations were developed some time ago and, as the body composition of the current population has changed, it is highly relevant to assess the validity of REE predictive equations in contemporary young adults. In addition, little is known about the role of sex and weight status on the validity of these predictive equations. Therefore, this study aimed to investigate the role of sex and weight status in congruent validity of REE predictive equations in young adults. A total of 132 young healthy adults (67.4% women, 18-26 years old) participated in the study. We measured REE by indirect calorimetry strictly following the standard procedures, and we compared it to 45 predictive equations. The most accurate equations were the following: (i) the Schofield and the Food and Agriculture Organization of the United Nations/World Health Organization/United Nations (FAO/WHO/UNU) equations in normal weight men; (ii) the Mifflin and FAO/WHO/UNU equations in normal weight women; (iii) the Livingston and Korth equations in overweight men; (iv) the Johnstone and Frankenfield equations in overweight women; (v) the Owen and Bernstein equations in obese men; and (vi) the Owen equation in obese women. In conclusion, the results of this study show that the best equation to estimate REE depends on sex and weight status in young healthy adults. Show less
Klinken, J.B. van; Berg, S.A.A. van den; Dijk, K.W. van 2013
