This study examined the differences in fat and carbohydrate oxidation during running and cycling at the same relative exercise intensities, with intensity determined in a number of ways. Specifically, exercise intensity was expressed as a percentage of maximum workload (WLmax), maximum oxygen uptake (%VO2max), and maximum heart rate (%HRmax) and as rating of perceived exertion (RPE). Ten male triathletes performed maximal running and cycling trials and subsequently exercised at 60%, 65%, 70%, 75%, and 80% of their WLmax. VO2, HR, RPE, and plasma lactate concentrations were measured during all submaximal trials. Fat and carbohydrate oxidation were calculated from VO2 and VCO2 data. A 2-way ANOVA for repeated measures was used to determine any statistically significant differences between exercise modes. Fat oxidation was shown to be significantly higher in running than in cycling at the same relative intensities expressed as either %WLmax or %VO2max. Neither were there any significant differences in VO2max and HRmax between the 2 exercise modes, nor in submaximal VO2 or RPE between the exercise modes at the same %WLmax. However, heart rate and plasma lactate concentrations were significantly higher when cycling at 60% and 65% and 65–80%WLmax, respectively. In conclusion, fat oxidation is significantly higher during running than during cycling at the same relative intensity expressed as either %WLmax or %VO2max.
Search Results
You are looking at 1 - 3 of 3 items for
- Author: Benoit Capostagno x
- Refine by Access: All Content x
Higher Fat Oxidation in Running Than Cycling at the Same Exercise Intensities
Benoit Capostagno and Andrew Bosch
Standardized Versus Customized High-Intensity Training: Effects on Cycling Performance
Benoit Capostagno, Michael I. Lambert, and Robert P. Lamberts
Purpose:
To determine whether a submaximal cycling test could be used to monitor and prescribe high-intensity interval training (HIT).
Methods:
Two groups of male cyclists completed 4 HIT sessions over a 2-wk period. The structured-training group (SG; n = 8, VO2max = 58.4 ± 4.2 mL · min−1 · kg−1) followed a predetermined training program while the flexible-training group (FG; n = 7, VO2max = 53.9 ± 5.0 mL · min−1 · kg−1) had the timing of their HIT sessions prescribed based on the data of the Lamberts and Lambert Submaximal Cycle Test (LSCT).
Results:
Effect-size calculations showed large differences in the improvements in 40-km time-trial performance after the HIT training between SG (8 ± 45 s) and FG (48 ± 42 s). Heart-rate recovery, monitored during the study, tended to increase in FG and remain unchanged in SG.
Conclusions:
The results of the current study suggest that the LSCT may be a useful tool for coaches to monitor and prescribe HIT.
A Systematic Review of Submaximal Cycle Tests to Predict, Monitor, and Optimize Cycling Performance
Benoit Capostagno, Michael I. Lambert, and Robert P. Lamberts
Finding the optimal balance between high training loads and recovery is a constant challenge for cyclists and their coaches. Monitoring improvements in performance and levels of fatigue is recommended to correctly adjust training to ensure optimal adaptation. However, many performance tests require a maximal or exhaustive effort, which reduces their real-world application. The purpose of this review was to investigate the development and use of submaximal cycling tests that can be used to predict and monitor cycling performance and training status. Twelve studies met the inclusion criteria, and 3 separate submaximal cycling tests were identified from within those 12. Submaximal variables including gross mechanical efficiency, oxygen uptake (VO2), heart rate, lactate, predicted time to exhaustion (pTE), rating of perceived exertion (RPE), power output, and heart-rate recovery (HRR) were the components of the 3 tests. pTE, submaximal power output, RPE, and HRR appear to have the most value for monitoring improvements in performance and indicate a state of fatigue. This literature review shows that several submaximal cycle tests have been developed over the last decade with the aim to predict, monitor, and optimize cycling performance. To be able to conduct a submaximal test on a regular basis, the test needs to be short in duration and as noninvasive as possible. In addition, a test should capture multiple variables and use multivariate analyses to interpret the submaximal outcomes correctly and alter training prescription if needed.
