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

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Impact of data analysis methods for maximal fat oxidation estimation during exercise in sedentary adults Data analysis maximal fat oxidation. / Amaro-Gahete, Francisco J.; Sanchez-Delgado, Guillermo; Alcantara, Juan M. A.; Martinez-Tellez, Borja; Acosta, Francisco M.; Helge, Jorn W.; Ruiz, Jonatan R.

I: European Journal of Sport Science, Bind 19, Nr. 9, 2019, s. 1230-1239,.

Publikation: Bidrag til tidsskriftTidsskriftartikelfagfællebedømt

Harvard

Amaro-Gahete, FJ, Sanchez-Delgado, G, Alcantara, JMA, Martinez-Tellez, B, Acosta, FM, Helge, JW & Ruiz, JR 2019, 'Impact of data analysis methods for maximal fat oxidation estimation during exercise in sedentary adults Data analysis maximal fat oxidation', European Journal of Sport Science, bind 19, nr. 9, s. 1230-1239,. https://doi.org/10.1080/17461391.2019.1595160

APA

Amaro-Gahete, F. J., Sanchez-Delgado, G., Alcantara, J. M. A., Martinez-Tellez, B., Acosta, F. M., Helge, J. W., & Ruiz, J. R. (2019). Impact of data analysis methods for maximal fat oxidation estimation during exercise in sedentary adults Data analysis maximal fat oxidation. European Journal of Sport Science, 19(9), 1230-1239,. https://doi.org/10.1080/17461391.2019.1595160

Vancouver

Amaro-Gahete FJ, Sanchez-Delgado G, Alcantara JMA, Martinez-Tellez B, Acosta FM, Helge JW o.a. Impact of data analysis methods for maximal fat oxidation estimation during exercise in sedentary adults Data analysis maximal fat oxidation. European Journal of Sport Science. 2019;19(9):1230-1239,. https://doi.org/10.1080/17461391.2019.1595160

Author

Amaro-Gahete, Francisco J. ; Sanchez-Delgado, Guillermo ; Alcantara, Juan M. A. ; Martinez-Tellez, Borja ; Acosta, Francisco M. ; Helge, Jorn W. ; Ruiz, Jonatan R. / Impact of data analysis methods for maximal fat oxidation estimation during exercise in sedentary adults Data analysis maximal fat oxidation. I: European Journal of Sport Science. 2019 ; Bind 19, Nr. 9. s. 1230-1239,.

Bibtex

@article{c934b61b8c9d43b5bb7b3ab572822bdc,
title = "Impact of data analysis methods for maximal fat oxidation estimation during exercise in sedentary adults Data analysis maximal fat oxidation",
abstract = "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 < 0.001) 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",
keywords = "MFO, Fat(max), peak fat oxidation, substrate oxidation, indirect calorimetry, fat metabolism",
author = "Amaro-Gahete, {Francisco J.} and Guillermo Sanchez-Delgado and Alcantara, {Juan M. A.} and Borja Martinez-Tellez and Acosta, {Francisco M.} and Helge, {Jorn W.} and Ruiz, {Jonatan R.}",
year = "2019",
doi = "10.1080/17461391.2019.1595160",
language = "English",
volume = "19",
pages = "1230--1239,",
journal = "European Journal of Sport Science",
issn = "1746-1391",
publisher = "Taylor & Francis",
number = "9",

}

RIS

TY - JOUR

T1 - Impact of data analysis methods for maximal fat oxidation estimation during exercise in sedentary adults Data analysis maximal fat oxidation

AU - Amaro-Gahete, Francisco J.

AU - Sanchez-Delgado, Guillermo

AU - Alcantara, Juan M. A.

AU - Martinez-Tellez, Borja

AU - Acosta, Francisco M.

AU - Helge, Jorn W.

AU - Ruiz, Jonatan R.

PY - 2019

Y1 - 2019

N2 - 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 < 0.001) 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

AB - 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 < 0.001) 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

KW - MFO

KW - Fat(max)

KW - peak fat oxidation

KW - substrate oxidation

KW - indirect calorimetry

KW - fat metabolism

U2 - 10.1080/17461391.2019.1595160

DO - 10.1080/17461391.2019.1595160

M3 - Journal article

C2 - 30922184

VL - 19

SP - 1230-1239,

JO - European Journal of Sport Science

JF - European Journal of Sport Science

SN - 1746-1391

IS - 9

ER -

ID: 228693044