ECSS Paris 2023: OP-AP02
INTRODUCTION: The sex gap in endurance performance ranges from 8–12% across most sports and is greater in uphill events due to lower maximal oxygen uptake, lean-to-fat mass ratio, muscle mass, and fewer fast-twitch fibers in women1. Yet, sex-differences between females (F) and males (M) with similar absolute performance (e.g., same-race finishing time) remain unexplored, particularly in mountain sports. This study aimed to investigate these differences in recreational trail runners. METHODS: 53 runners (11 F, 42 M) completed a 26 km, 1920-m D+ trail race. Within 3-weeks before the race (Pre-), they performed i) anthropometrical measures; ii) a graded treadmill (slope 10%) running test to exhaustion to assess aerobic capacity, vertical velocities (Vv in vertical m per h, mv.h-1) and running energy cost (REv) at maximal (Max) and second ventilatory threshold (VT2); iii) knee extensors’ maximal voluntary contraction (MVC) and rate of force development (RFD). The weekly training volume (WTV) of the 3 months preceding the race was retrieved from a popular training platform. MVC and RFD were reassessed within 20 min after the race (Post-). From the total sample, F were matched to 11 M with similar performance, and sex-differences analyzed with unpaired Student’s t-tests. RESULTS: Race time of F and M was identical (246±28 min,p=0.994). No difference in WTV was found (335±135 vs 318±131 min, p=802). F presented lower body mass index (21.1±1.2 vs 23.3±1.5 kg.m-2,p=0.001), lean body mass (LBM) (47.5±4.0 vs 64.4±4.0kg,p=0.004), and higher fat mass (16.2±2.2 vs 11.3±4.2%,p=0.004). V̇O2 (ml.kg-1.min-1) was similar at Max and VT2 (53.5±4.3 vs 56.9±4.8,p=.139 and 48.6±3.6 vs 51.8±5.4 ml.kg-1.min-1,p=0.122), also when expressed relative to LBM ( V̇O2/kgLBM; Max: 63.7±4.7 vs 64.1±5.3,p=.922; VT2: 57.9±3.9 vs 58.4±5.2 ml.kgLBM-1.min-1,p=.870). Lower Vv and higher REv relative to LBM (REvLBM) were found in F at both Max (1030±98 vs 1127±83 mv.h-1,p=0.020 and 3.74±0.40 vs 3.42±0.27 ml.kgLBM-1.mv-1,p=0.040) and VT2 (896±92 vs 983±81 mv.h-1,p=0.020 and 3.91±0.34 vs 3.57±0.27 ml.kgLBM-1.mv-1,p=0.018). When normalized to LBM, MVC (11.3±1.9 vs 11.4±1.5 N·kgLBM⁻¹,p=0.960) and RFD (34.0±8.2 vs 33.8±6.2 N·kgLBM⁻¹,p=0.942) were comparable between sexes. However, the relative pre-to-post decline was lower in F for MVC (-4.1±15.8 vs -17.3±10%,p=0.032) and tended to be lower for RFD (-5.3±32.6 vs -26.3±17.2%,p=0.093). CONCLUSION: Despite comparable performance, training volume, and V̇O2/kgLBM, females had reduced vertical velocities at Max and VT2, likely due to higher REvLBM. These results suggest that the observed uphill sex-differences (9% in Vv in the present study) are not only due to lean-to-fat mass ratio. Moreover, females lower post-race decline in neuromuscular function confirms reduced muscle fatigability2. These findings suggest that women rely on different strategies to achieve similar performance, emphasizing the need for sex-specific training/pacing approaches. 1.Millet et al. (2025) 2.Besson et al.(2022)
Read CV Alexa CalloviniECSS Paris 2023: OP-AP02
INTRODUCTION: Middle-aged runners make up over half of all recreational runners [1] and are highly motivated to improve their endurance running performance [2]. Running economy plays a key role in endurance performance and can be enhanced by incorporating plyometric training into daily running routines [3]. Although improvements in running economy after plyometric training are suggested to be attributable to changes in muscle functions [4], kinematics [5], and running training modality/volume [6], it remains unclear which factors contribute the most in middle-aged runners. This study aimed to identify the key factors influencing the effects of plyometric training combined with daily running on running economy of middle-aged runners. METHODS: Thirty-five male endurance runners (30-50 years) performed plyometric training twice per week for 10 weeks. The program included countermovement jumps (CMJ), jump rope, and hopping. Participants were asked to maintain their regular running volume during the intervention. Measurements were taken before and after the intervention for muscle strength (knee extension/flexion, ankle dorsiflexion/plantarflexion torques), jump performance (CMJ, drop, and rebound jump), running-related variables (running economy and kinematics) at 80% velocity of V̇O2max. In addition, long-distance running (≥3000 m per session) and interval training (multiple runs of <3000 m per session) volumes before and during the intervention were obtained from participants’ training logs. A repeated-measures correlation analysis assessed relationships between changes in running economy and other variables, with p-values corrected using the Holm-Sidak method. Stepwise regression analysis was performed with the changes in running economy as a response variable and those of the variables that showed significant correlations with running economy changes (P<0.05) as independent variables. RESULTS: Plyometric training combined with daily running significantly improved running economy (3.8%, P=0.004). The change in running economy was significantly correlated with those in drop and rebound jump height and index (height/ground contact time), and interval training volume (r=-0.582 to -0.453, P≤0.007). Furthermore, the changes in drop jump height and interval training volume were identified as significant explanatory variables for the improvement in running economy (R2=0.338, P=0.006). CONCLUSION: Incorporating plyometric training into daily running effectively enhances the running economy in middle-aged runners. The magnitude of improvement in running economy is influenced by increases in drop jump height and interval training volume. These findings suggest that plyometric training programs should be designed to enhance drop jump height while incorporating more interval training to improve running economy efficiently. [1] Anderson et al. (2021) [2] Garasimuk et al. (2021) [3] Eihara et al. (2024) [4] Li et al., (2021) [5] Folland et al (2017) [6] González-Mohíno et al (2016)
Read CV Yuuri EiharaECSS Paris 2023: OP-AP02
INTRODUCTION: Cold and hot water immersion (CWI/HWI) are commonly used to mitigate post-exercise fatigability [1]. However, fatigue mechanisms are task-dependent, with the type of exercise influencing its causes and characteristics [2]. Given the specific mechanisms by which CWI and HWI may affect recovery [1], their efficacy in mitigating post-exercise fatigability may be task-dependent [3]. Therefore, this study aimed to investigate the effectiveness of CWI and HWI, compared to a placebo condition and passive rest, in mitigating fatigability following different running efforts. METHODS: On separate occasions, recreationally trained runners underwent different recovery interventions after performing either a 40-min continuous run at a velocity corresponding to the respiratory compensation point (vRCP) (CONT, n=12, maximal oxygen uptake: 48.5±3.4 mL/kg/min) or an intermittent run at a velocity 50% above vRCP (HIIT; n=10, maximal oxygen uptake: 49.5±4.5 mL/kg/min). The recovery interventions included cold water immersion (11°C, 15-min), hot water immersion (41°C, 45-min), immersion in colored water (placebo; 26°C, 10-min), or passive rest sitting on a chair (10-min). Before and up to 24 hours after exercise, cardiac parasympathetic activity, maximal voluntary contractions (MVCs) and evoked responses of the knee extensors were assessed using the twitch interpolation technique. Additionally, cardiorespiratory responses were monitored during a brief effort (3-min run at 80% of vRCP). A two-way repeated-measures ANOVA was used to evaluate the effects of the interventions in both CONT and HIIT conditions, and partial eta squared was calculated to estimate effect sizes (ES). Statistical significance was set at p<0.05. RESULTS: The ratio of the root mean square of electromyography activity of the vastus lateralis during MVCs to the amplitude of the evoked M-wave (RMS/M-wave) was higher 2 and 4 h after CONT when HWI was used, compared to placebo and passive rest (interaction effect, p=0.01, ES=0.18). In contrast, following HIIT, RMS/M-wave was higher 4 h post-exercise when CWI was used, compared to placebo and passive rest (interaction effect, p=0.01, ES=0.25). Furthermore, cardiac parasympathetic activity was higher 2 h after CONT and HIIT when CWI was used compared to placebo and passive rest (interaction effect, p<0.01, ES>0.27), and oxygen uptake during brief efforts was lower over 24 h after CONT and HIIT when HWI was used compared to placebo and passive rest (condition effect, p<0.01, ES>0.16). CONCLUSION: In conclusion, CWI seems to mitigate central fatigue after CONT, while HWI appears to mitigate central fatigue after HIIT. In both CONT and HIIT, CWI increases cardiac parasympathetic activity 2 h post-exercise, whereas HWI reduces oxygen uptake during brief submaximal efforts over the following 24 hours. 1. Versey et al. (2013) 2. Brownstein et al. (2021) 3. Thorpe (2021)
Read CV Yago DutraECSS Paris 2023: OP-AP02