ECSS Paris 2023: OP-MH38
INTRODUCTION: High-intensity interval training (HIIT) effectively reduces fat mass (FM), including abdominal and visceral FM (1). Recent studies demonstrate that performing HIIT in hypoxia, compared to normoxia, enhances total and abdominal FM loss in individuals with overweight or obesity (2,3). However, the mechanisms underlying these body composition changes remain to be elucidated. This study therefore aimed to compare the acute effects of high-intensity interval exercise (HIIE) performed in hypoxia versus normoxia on oxygen consumption (VO₂) and lipid oxidation during the first two hours of recovery in normoxia. METHODS: Seven fasted participants (67 ± 3 years; body mass index: 31 ± 5 kg·m⁻²) completed two HIIE sessions (normoxia vs. hypoxia) on a cycle ergometer (WattBike). The first session was conducted under normoxia and consisted of 60 repetitions of (8s at 80-85% HRMax + 12s deceleration), with power output recorded. In the second session, performed under hypoxia, participants completed the same HIIE while maintaining the same power output as in normoxia, ensuring that both sessions were matched for external load. Each session began with a 20-minute pre-exercise metabolic assessment, followed by a 10-minute standardized warm-up under normoxic conditions. HIIE was then performed either in normoxia (normobaric room, 21% O₂) or hypoxia (normobaric room, 15% O₂). The 2-hour post-exercise recovery took place under normoxic conditions. Heart rate (HR) and rate of perceived exertion (RPE) were recorded throughout exercise. VO₂ and VCO₂ were measured, allowing for the calculation of the respiratory exchange ratio (RER) and energy expenditure (EE) before, during, and for two hours post-exercise in normoxia. Substrate oxidation (g·min⁻¹) was calculated during the recovery period. RESULTS: Both normoxic and hypoxic sessions induced similar mean HR (p = 0.24), VO₂ (p = 0.31), EE (p = 0.24), RER (p = 0.49), and RPE (p = 0.67) responses during exercise. Mean VO₂ (L·min⁻¹) was higher during the 2-hour recovery period than before exercise in both conditions (p = 0.02), with no session effect (p = 0.50). While 2-hour recovery EE did not differ between normoxic and hypoxic conditions (p = 0.50), lipid oxidation tended to be higher after HIIE performed in hypoxia (p = 0.06). CONCLUSION: These preliminary findings suggest that performing HIIE under hypoxic conditions may promote greater lipid oxidation during recovery compared to normoxia, despite similar energy expenditure. However, these results should be interpreted with caution and require confirmation with the full sample (n=15). REFERENCES 1. Maillard et al. Sports Medicine 48, 269-288 (2018). 2. Camacho-Cardenosa et al. Frontiers in Physiology 9, Article 60 (2018) 3. Camacho-Cardenosa et al. High Altitude Medicine & Biology 19, 356-366 (2018)
Read CV Annaëlle CouvertECSS Paris 2023: OP-MH38
INTRODUCTION: Intermittent hypoxic training aims to enhance exercise performance and health, commonly expressed as maximal oxygen uptake (VO2max). Currently applied methods are live-high train-low (LHTL), live-low train-high (LLTH), and passive hypoxic conditioning (PHC). Despite a substantial amount of studies published on the topic, no consensus exists on which method is effective in augmenting VO2max. In addition, factors (i.e., hypoxic dose, exposure times) driving development of VO2max most effectively are unknown. This work aimed to determine the effect of LHTL, LLTH, and PHC on VO2max in healthy participants, and identifying factors associated with the amplitude of change in VO2max. METHODS: We conducted a systematic review with random-effects meta-analysis and meta-regression. Studies were identified through PubMed, EMBASE, and Web of Science. We included controlled and uncontrolled studies, calculating weighted within-group mean changes and between-group standardised mean differences. Athlete and non-athlete populations were analysed separately. RESULTS: Of the 13248 identified studies, 147 were included for analysis, resulting in a sample size of 2668 participants. Of these participants, 1449 were considered athletes and 1219 were considered non-athletes. Meta-analyses indicated that LHTL (athletes: MD = 0.72; 95%CI = -0.23, 1.68; non-athletes: 1.06; -0.31, 2.43) and PHC (athletes: -0.54; -1.69, 0.61; non-athletes: 0.60; -0.75, 1.94) did not increase VO2max significantly more than control. LLTH did increase VO2max significantly more than control, both in athletes (1.17; 0.29, 2.05) and non-athletes (1.38; 0.61, 2.15). Multivariate meta-regression of all studies identified sample size to be significantly associated to the change in VO2max (B = -0.15; 95%CI = -0.25, -0.05). The risk of bias in the included studies was substantial. We did not find evidence for publication bias. CONCLUSION: LLTH showed a significant effect on VO2max in both athletic and non-athletic populations, while LHTL and PHC did not. Although a considerable number of studies on intermittent hypoxic training strategies exists, high-quality placebo-controlled trials are still warranted for definite conclusions. Further, future studies should target investigating which characteristics (i.e., length and magnitude of exposure) of the hypoxic exposure are most beneficial.
Read CV Dario KohlbrennerECSS Paris 2023: OP-MH38
INTRODUCTION: Impaired glycaemic control is a major risk factor for cardiovascular disease, the leading cause of death worldwide. Increasing physical activity is a key strategy to improve glycaemic control. The circadian system influences glucose metabolism, causing 24-hour fluctuations in plasma glucose with a peak later in the day. Metabolic responses may vary depending on the time of day during which exercise is performed. Evidence of diurnal variations in physical performance, combined with the timing of behaviours such as sleep and diet, suggests that the timing of exercise may influence adaptations and health outcomes. This study aimed to investigate the impact of exercise timing on glycaemic control and optimise metabolic health strategies. METHODS: Sixty non-diabetic adults (36% female, mean [standard deviation] age 68 [6] years, BMI 24.1 [2.7] kg/m²) participated in this double-blind, randomised controlled trial. Participants were assigned to exercise at 8:00, 12:00, 16:00 or 20:00 (E-08, E-12, E-16, E-20) for 12 weeks, performing two strength and one endurance session weekly. A two-hour oral glucose tolerance test was performed before and after the intervention following an overnight fast. Serum glucose was measured at fasting and 10, 20, 30, 60, 90 and 120 min after ingestion of 75g dextrose. Glucose response was quantified as area under the curve (AUC) using the trapezoidal method. Treatment effects over time were analysed using analysis of covariance with estimated marginal means, adjusted for sex, age, lean mass and fat mass. Effect sizes were standardised using baseline standard deviations. RESULTS: Fifty-two participants were analysed (E08: n=14, E-12: n=15, E-16: n=7, E-20: n=16), with most dropouts due to missing more than two serum glucose values. Exercise adherence was excellent with 93% of all sessions completed. AUC decreased more in the E-16 group than in the others, with effect sizes being E-08: -0.21 (-0.68 to 1.10), E-12: -0.29 (-0.56 to 1.15) and E-20: -0.30 (-1.15 to 0.54), all considered small. Negative effect sizes, indicating a reduction in AUC, are considered beneficial for metabolic health. However, there was considerable uncertainty about these effects. Comparisons between the remaining groups showed negligible effect sizes (< 0.10). CONCLUSION: The timing of exercise appears to influence metabolic adaptations, with different patterns observed between exercise groups. The results suggest that exercising at a time of day when glucose metabolism is less efficient (e.g. E-16) may lead to greater adaptations. However, the wide confidence intervals indicate considerable uncertainty in these results. Further research is needed to improve our understanding of the underlying metabolic mechanisms and to provide a scientific basis for integrating exercise timing into health and metabolic management strategies.
Read CV Fabienne BruggisserECSS Paris 2023: OP-MH38