This investigation aimed to assess whether the alternative method of estimating the maximal accumulated oxygen deficit (MAOD) can detect changes in energy system contribution in different substrate availabilities. Following a graded exercise test to determine maximal oxygen uptake intensity (iVO), 26 recreational runners performed a time to exhaustion effort (TTE) as baseline at 110% iVO. The same TTE was performed in fasting state, then, a muscle glycogen depletion protocol was executed. Subsequently, participants received a low-carbohydrate diet and beverages containing high (H-CHO, 10.8±2.1 g·kg), moderate (M-CHO, 5.6±1.1 g·kg), or zero (Z-CHO, 0.24±0.05 g·kg) carbohydrates. Another TTE was performed 24 h later. Each energy system contribution was assessed. Generalized linear mixed models were used for statistical analysis (p<0.05). H-CHO increased relative anaerobic capacity (slope effect [baseline -intervention]x[H-CHO - M-CHO]) due to the relative lactic contribution maintenance (slope effect [baseline - intervention]x[H-CHO - Z-CHO] or [H-CHO - M-CHO]) and increase in relative alactic contribution (6.3±3.5 kJ·min). The aerobic contribution was lower (- 8.7±4.0 kJ·min), decreasing performance (- 34±16 s) for H-CHO. M-CHO and Z-CHO maintained anaerobic capacity due to increase in alactic contribution (slope effect [fasting - intervention]x[M-CHO - H-CHO]; and Z-CHO was 7.3±3.4 kJ·min higher than baseline). Fasting increased relative alactic (2.9±1.7 kJ·min) but decreased aerobic contribution (- 3.3±2.3 kJ·min), impairing performance (- 17±12 s). In conclusion, MAOD can detect changes in energy system supply in different nutritional states. Therefore, participant's nutritional state must be considered prior to conducting the test.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1055/a-2373-0102 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!