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Updated: May 10, 2026

Determining the Contribution of the Energy Systems During Exercise
Published on: March 20, 2012
Optimizing Metabolic Assessment: Maximal Fat Metabolism, Lactate Dynamics, and Cardiorespiratory Determinants at
1School of Life and Health Sciences, Birmingham City University, Birmingham, England, UK, bcu.ac.uk.
Aims/Objectives:
Accurate metabolic exercise testing is essential for assessing cardiometabolic health in both athletes and clinical populations with prediabetes and diabetes. This study investigated whether and how fat, carbohydrates and lactate diagnostics are influenced by ergometry testing pedaling frequency.
Methods:
This randomized cross-over repeated-measures trial, examined human participants for cardiorespiratory oxygen uptake ( ) and carbon dioxide production ( ), and blood lactate concentration (BLC), using two separate incremental load ergometry exercise tests until exhaustion, at higher versus lower cycling pedaling frequencies of 100 and 50 revolution per minute (RPM). Metabolic diagnostics of fatty acid oxidation (FAO), carbohydrates oxidation (CHO), maximal FAO (MFO) and associated MFO intensity (Fatmax) were estimated by stoichiometric equations and compared at 100 versus 50 RPM.
Results:
Higher , , BLC and CHO and lower FAO were found for all submaximal intensities at 100 RPM than at 50 RPM (all p < 0.01). Fatmax power output was significantly lower (83.7 ± 20.3 vs. 99.8 ± 25.8 W, p < 0.05, effect size d = 0.70) at 100 than at 50 RPM. However, pedaling frequency-dependent effects reflected nonsignificant changes in MFO (0.58 ± 0.16 vs. 0.52 ± 0.15 g.min-1, p = 0.12, d = 0.39), and also in the corresponding BLC at MFO (1.70 ± 0.45 vs. 1.30 ± 0.39 mmol.L-1, p = 0.06, d = 0.9).
Conclusions:
Metabolic assessments should prioritize absolute MFO and BLC dynamical changes over Fatmax intensities, when interpreting fat-oxidation capacity, particularly under varying pedaling frequencies. By jointly characterizing blood-based and respiratory-based diagnostics under different exercise assessment conditions, this study helps improve the reliability of diagnosing the metabolic status in both healthy individuals and patients with metabolic disease.
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