ECSS Paris 2023: OP-PN20
INTRODUCTION: 400-m sprinting relies on predominantly anaerobic metabolism. The aerobic contribution is estimated to 40% of the total energy contribution [1]. The concept of the anaerobic speed reserve (ASR) integratively considers aerobic and anaerobic properties, defined as the velocity difference between maximal sprinting speed (MSS) and maximal aerobic speed (MAS). The corresponding Speed Reserve Ratio (SRR) was initially introduced to determine 800-m elite athletes’ performance profiles and types [2]. In this regard, profiling of 400-m athletes considering their relationship to personal best (PB) are missing. We aimed at investigating the contribution of endurance and speed capabilities of 400-m elite sprinters to their PB in order to improve sprint diagnostics and training programming. METHODS: The ASR of 18 sprinters (elite female, n=7, 23±2 years, 400-m-PB: 53.0±1.3s; elite male, n=5, 23±3 years, 400-m PB: 46.7±1.0s; highly-trained female, n=6, 20±3 years, 400-m-PB: 57.6±2.5s) was assessed. Using a laser velocity guard (LAVEG), MSS was determined as instantaneous velocity during a 60-m all-out sprint. Maximal oxygen uptake (VO2max) and velocity at VO2max (MAS) was determined through ramp test on a treadmill. Additionally, fixed lactate threshold at 4-mmol/L blood lactate (vL4) was determined in the laboratory using an incremental step test. Profiles of three athlete subgroups were created. The SRR (MSS/MAS) was calculated according to Sandford and colleagues [1]. RESULTS: Strong statistically significant negative correlations with PB were found for maximal sprinting speed (r = -0.96, p < 0.001) and maximal aerobic speed (r = -0.74, p < 0.001). Moderate statistically significant negative correlation with PB was found for vL4 (r = -0.60, p = 0.008) but not for VO2max (r = -0.46, p = 0.053). Using a multiple linear regression, a model was created to generate the following prediction (R2 = 0.96, Residual standard error = 0.97): PB [s] = 113.6815 -5.1122MSS [m/s] - 2.6023MAS [m/s] + ε A very low variance inflation factor of 1.61 indicates a low risk of multicollinearity. The standardized beta weights for MSS and MAS are -0.80 and -0.27, respectively. Adding vL4 and/or VO2max to this initial model did not increase model fit (Likelikood ratio test: p ≥ 0.412). Subgroups of 400-m sprinter types were defined by SRR: 200-400 m ≥ 1.75, 400 m ≤ 1.74 to ≥ 1.66, 400-800 m ≤ 1.65. CONCLUSION: Sprinting Speed is the best predictor of 400-m performance. MAS should be used rather than VO2max alone as MAS has a better negative relationship to 400-m PBs. Calculating SRR can be useful for identifying an athlete’s 400-m profile, potentially facilitating individualized training prescriptions. Future research is needed to test individualized training prescriptions based on ASR diagnostics. Training programs for aerobic speed improvements that do not impair sprinting speed are crucial. [1] Spencer & Gastin (2001) Med Sci Sports Exerc [2] Sandford et al. (2019) Int J Sports Physiol Perform
Read CV Steffen RiestenpattECSS Paris 2023: OP-PN20
INTRODUCTION: In elite sports, the determination of anaerobic glycolytic performance (νLa.max) is becoming increasingly popular. νLa.max is determined e.g. in sprint tests, where firstly glycolysis is maximally activated, followed by the calculation of the quotient between the difference of peak blood lactate (Lapeak) and resting lactate (Larest), and the difference between exercise time and alactic time is calculated. Unintentional variations in lactate levels, such as elevated Larest levels, may affect vLa.max results because of their high impact on the numerator in this calculation. Aim: To evaluate the effects of variations in carbohydrate availability and Larest on VLamax. METHODS: Twenty-one subjects (13 male, 8 female; age: 23.1 ± 2.0 years, height: 177.1 ± 8.4 cm, weight: 74.2 ± 11.9 kg) completed five 15-second running sprint tests on five separate testing days under five different conditions: baseline: Larest ≤1.5 mmol·L-1; lactate+: Larest ≥2.5 mmol·L-1; CHO-: carbohydrate intake: ≤1g·kg-1 BW · d-1 for three days; CHO+: carbohydrate intake: ≥9g·kg-1 BW · d-1 for one day; and acuteCHO: 500ml juice sparkling water beverage. Specifically, after a 10-min warm-up, subjects rested until reaching specified Larest. Subjects then carried out a 15s maximal sprint on a running track. Blood lactate was determined every minute until minute 10’ after the sprint. A Friedman ANOVA with Dunn’s post hoc test was used to assess differences between conditions and time points. Statistical significance was accepted at p<0.05. Data are presented as mean ± standard deviation. RESULTS: νLa.max (mmol · L-1 · s-1) was 0.59 ± 0.09 in baseline, 0.51 ± 0.01 in lactate+, 0.53 ± 0.1 in CHO-, 0.54 ± 0.1 in CHO+ and 0.57 ± 0.1 in acuteCHO. Significant differences were observed between νLa.max values from baseline and lactate+ (p<0.001) and baseline and CHO- (p<0.05). The mean delta (∆) value, consisting of the difference between Larest and Lapeak (mmol · L-1), was 6.91 ± 1.0 in baseline, 5.99 ± 1.26 in lactate+, 6.15 ± 1.19 in CHO-, 6.32 ± 1.23 in CHO+ and 6.67 ± 1.25 in acuteCHO. Significant differences were identified between ∆baseline and ∆lactate+ (p<0.01), ∆baseline and ∆CHO- (p<0.05), as well as ∆baseline and ∆CHO+ (p<0.05). CONCLUSION: Variations in carbohydrate intake and Larest levels may lead to a reduction in net accumulated lactate levels in a νLa.max test. Therefore, careful consideration and adjustment of test methodology are necessary to avoid underestimating νLa.max in athletes.
Read CV Frederik SchünemannECSS Paris 2023: OP-PN20
INTRODUCTION: The maximum fat oxidation rate (MFO) has been suggested to provide useful information regarding endurance training status in athletes, but also as an index of metabolic health in untrained populations. Training in hypoxia is a popular method used by athletes for the purpose of performance enhancement and is emerging as a therapeutic intervention to improve cardiometabolic health. It is known that the addition of hypoxia induces a shift towards carbohydrate utilization, however the few studies that examined fat oxidation in hypoxia reported equivocal results. This may be due to differences in the methods used to normalize relative intensity. The aim of this study was to evaluate MFO matched intensity relative to the respiratory compensation point (RCP) in both normoxia (NORM) and hypoxia (HYPO). METHODS: Seventeen recreationally active adults (5F/12M; age: 36.2±7.4 yr; weight: 76.6±13.1 kg) performed a ramp and a step test, in NORM (FiO2≈21%) and HYPO (FiO2≈13.5%), on separate days. The gas exchange threshold (GET), RCP and VO2peak were determined from the ramp tests. The step test involved 6 constant load stages (4-8 min) matched for intensity relative to the RCP in each condition. Indirect calorimetry was used to estimate MFO rate during the step test. Each participant’s diet, fasting hours, and testing time were consistent between conditions. Paired t-tests and a 2-way ANOVA were used to examine differences between NORM and HYPO. Pearson correlation was used to assess the relationship between MFO and GET. RESULTS: Fat oxidation rate was decreased in HYPO across all stages (main effect of condition: P<0.001; η_p^2=0.64). Subsequently a 25% decrease in MFO in HYPO (0.26 ±0.08g.min-1) compared to NORM (0.35±0.08g.min-1; P<0.001; d=1.24) was observed. %VO2peak where MFO occurred was similar in HYPO (39±21%) and NORM (39±21%; p=0.97), however the correlation between MFO and GET (as %VO2peak) was not significant in either NORM (r = 0.3; P>0.05) or HYPO (r = 0.07; P>0.05). CONCLUSION: MFO was markedly decreased in hypoxia during step incremental cycling where each workload was normalized to RCP. Furthermore, the decrease in fat oxidation was apparent at all workloads and was greater than expected from the lower absolute exercise intensity. This suggests the reduced fat oxidation was not fully accounted for by a decrease in absolute workrate alone, but there was an independent effect of reduced oxygen availability. Hypoxia did not alter the relative intensity, as a percentage of VO2peak where the MFO occurred.
Read CV Youmna HassaneinECSS Paris 2023: OP-PN20