Literature DB >> 30922184

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

Francisco J Amaro-Gahete1,2, Guillermo Sanchez-Delgado2, Juan M A Alcantara2, Borja Martinez-Tellez2,3, Francisco M Acosta2, Jørn W Helge4, Jonatan R Ruiz2.   

Abstract

The maximal fat oxidation (MFO), and the exercise intensity that elicits MFO (Fatmax), 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 Fatmax estimation, and (ii) the impact of applying 2 different data analysis approaches (measured-values vs. polynomial-curve) on MFO and Fatmax 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 Fatmax 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 Fatmax 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 Fatmax (all P ≥ 0.2). In conclusion, our results revealed that there are no differences in MFO and Fatmax 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 Fatmax using different time intervals in sedentary adults.

Entities:  

Keywords:  Fat; MFO; fat metabolism; indirect calorimetry; peak fat oxidation; substrate oxidation

Mesh:

Year:  2019        PMID: 30922184     DOI: 10.1080/17461391.2019.1595160

Source DB:  PubMed          Journal:  Eur J Sport Sci        ISSN: 1536-7290            Impact factor:   4.050


  10 in total

1.  Comment on: "Assessment of Metabolic Flexibility by Means of Measuring Blood Lactate, Fat, and Carbohydrate Oxidation Responses to Exercise in Professional Endurance Athletes and Less-Fit Individuals".

Authors:  Jordi Monferrer-Marín; Ainoa Roldán; Pablo Monteagudo; Cristina Blasco-Lafarga
Journal:  Sports Med       Date:  2022-03-14       Impact factor: 11.928

Review 2.  Beyond the Calorie Paradigm: Taking into Account in Practice the Balance of Fat and Carbohydrate Oxidation during Exercise?

Authors:  Jean-Frédéric Brun; Justine Myzia; Emmanuelle Varlet-Marie; Eric Raynaud de Mauverger; Jacques Mercier
Journal:  Nutrients       Date:  2022-04-12       Impact factor: 6.706

3.  Optimizing Maximal Fat Oxidation Assessment by a Treadmill-Based Graded Exercise Protocol: When Should the Test End?

Authors:  Francisco J Amaro-Gahete; Guillermo Sanchez-Delgado; Jørn W Helge; Jonatan R Ruiz
Journal:  Front Physiol       Date:  2019-07-23       Impact factor: 4.566

4.  Association of basal metabolic rate and fuel oxidation in basal conditions and during exercise, with plasma S-klotho: the FIT-AGEING study.

Authors:  Francisco J Amaro-Gahete; Alejandro De-la-O; Lucas Jurado-Fasoli; Jonatan R Ruiz; Manuel J Castillo
Journal:  Aging (Albany NY)       Date:  2019-08-07       Impact factor: 5.682

5.  Association between sleep quality and time with energy metabolism in sedentary adults.

Authors:  Lucas Jurado-Fasoli; Sol Mochon-Benguigui; Manuel J Castillo; Francisco J Amaro-Gahete
Journal:  Sci Rep       Date:  2020-03-12       Impact factor: 4.379

6.  Effect of a 12-Week Concurrent Training Intervention on Cardiometabolic Health in Obese Men: A Pilot Study.

Authors:  Francisco J Amaro-Gahete; Jesús G Ponce-González; Juan Corral-Pérez; Daniel Velázquez-Díaz; Carl J Lavie; David Jiménez-Pavón
Journal:  Front Physiol       Date:  2021-02-11       Impact factor: 4.566

7.  Caffeine increases maximal fat oxidation during a graded exercise test: is there a diurnal variation?

Authors:  Mauricio Ramírez-Maldonado; Lucas Jurado-Fasoli; Juan Del Coso; Jonatan R Ruiz; Francisco J Amaro-Gahete
Journal:  J Int Soc Sports Nutr       Date:  2021-01-07       Impact factor: 5.150

8.  Dihydrocapsiate does not increase energy expenditure nor fat oxidation during aerobic exercise in men with overweight/obesity: a randomized, triple-blinded, placebo-controlled, crossover trial.

Authors:  Francisco J Osuna-Prieto; Francisco M Acosta; Unai A Perez de Arrilucea Le Floc'h; Blanca Riquelme-Gallego; Elisa Merchan-Ramirez; Huiwen Xu; Juan Carlos De La Cruz-Márquez; Francisco J Amaro-Gahete; Jose A Llamas-Elvira; Eva M Triviño-Ibáñez; Antonio Segura-Carretero; Jonatan R Ruiz
Journal:  J Int Soc Sports Nutr       Date:  2022-07-19       Impact factor: 4.948

9.  Impact of Ageing on Female Metabolic Flexibility: A Cross-Sectional Pilot Study in over-60 Active Women.

Authors:  Jordi Monferrer-Marín; Ainoa Roldán; Pablo Monteagudo; Iván Chulvi-Medrano; Cristina Blasco-Lafarga
Journal:  Sports Med Open       Date:  2022-07-30

10.  Inter-Day Reliability of Resting Metabolic Rate and Maximal Fat Oxidation during Exercise in Healthy Men Using the Ergostik Gas Analyzer.

Authors:  Lidia Robles-González; Jorge Gutiérrez-Hellín; Millán Aguilar-Navarro; Carlos Ruiz-Moreno; Alejandro Muñoz; Juan Del-Coso; Jonatan R Ruiz; Francisco J Amaro-Gahete
Journal:  Nutrients       Date:  2021-11-29       Impact factor: 5.717

  10 in total

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