ECSS Paris 2023: CP-PN10
INTRODUCTION: Omega-3 fatty acids, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), are essential nutrients that play a crucial role in modulating inflammation, supporting muscle recovery, and promoting adaptation to physical exercise. The Omega-3 Index (O3I), defined as the percentage of EPA and DHA in erythrocyte membranes relative to total fatty acids, is a reliable marker of the bodys omega-3 status. Numerous studies have emphasized the benefits of omega-3 supplementation for muscle repair and inflammation reduction; however, little attention has been given to natural changes in O3I resulting from structured, long-term training interventions, particularly in the context of strength training where adaptive changes in muscle tissue occur. The aim of this study was to determine the impact of a 12-week strength training intervention on O3I levels in athletes and to examine the relationship between changes in O3I and selected muscle strength parameters. O3I levels were assessed before and after the training intervention to determine whether training adaptations were associated with modifications in O3I that could potentially influence muscle function. METHODS: In this study, young adults (aged 18–30 years) with less than one year of training experience were randomly assigned to either a training group (n=35) or a control group (n=11). The training group completed 36 sessions over 12 weeks (three sessions per week), while the control group maintained their regular lifestyle without additional training. All participants performed identical exercises with controlled total volume and average intensity to ensure consistency across sessions. A minimum attendance of 90% was required. O3I levels were measured at baseline and after the intervention, and muscle strength was assessed using a Kistler force platform (evaluating peak force, relative peak force, and force at 150, 200, and 250 milliseconds) and the Biodex system (measuring maximum muscle torque of the knee and elbow joints at 95° and 135°). RESULTS: Results showed that O3I values did not differ significantly between the training and control groups, with both groups exhibiting levels below the recommended optimal range. Changes in O3I after the 12-week strength training intervention were associated with a slight increase in maximum muscle torque in the knee and elbow joints; however, these correlations were relatively weak. No significant changes were observed in other muscle strength parameters. CONCLUSION: The results indicate that participants in the training group exhibited similar O3I values compared to the non-training group. While there is some correlation between O3I and muscle strength parameters, it is relatively weak and requires further research to better understand the mechanisms underlying this relationship. Additionally, educating athletes on the importance of omega-3 fatty acids and their potential impact on performance and recovery should be emphasized as part of their nutritional guidance.
Read CV Marta KluczekECSS Paris 2023: CP-PN10
INTRODUCTION: Recent studies suggest meal sequencing as an effective way to stabilize postprandial blood glucose and insulin levels. However, its effects on energy metabolism and fatigue recovery in endurance athletes are unknown. This study explores the impact of meal sequencing on endurance athletes in challenging conditions, aiming to improve training and competition strategies. METHODS: Eleven male cyclists (16±1.45 years, BMI 22.4±1.95) were randomly assigned to either a mixed meal (Mix) or protein/fat before carbohydrate (PFC) pattern, with a 7- day washout. After a 12-hour fast, subjects had breakfast, rested for two hours, cycled for two hours at 70% VO2max, and completed a 7km sprint in a hot, humid room. Lunch was consumed 30 minutes post-sprint, followed by four hours of rest before re-entering the hot room for an exhaustive cycling at 85% VO2max. Basal measurements were taken before breakfast. Post-meal glucose was monitored every 15 minutes using the Abbott FreeStyle Libre, and metabolic data were collected every 30 minutes using a cardiopulmonary function tester. During cycling, glucose, heart rate, core temperature, subjective fatigue levels, and gas were collected at regular intervals. Venous blood was drawn immediately, 30 minutes, and 120 minutes post-lunch for NEFA, insulin, and GLP-1 analysis. RESULTS: Meal sequence did not significantly impact blood glucose levels or AUC between groups, though PFC showed a trend toward higher glucose levels. Key differences emerged at multiple time points: glucose rose faster initially but declined afterward in Mix, while PFC surpassed Mix 45 minutes to one hour post-meal, remaining higher for up to four hours and into cycling. RER and carbohydrate energy supply ratio showed significant interaction effects. Post-7K sprint, PFC trended toward higher carbohydrate energy supply rates, ratio, and RER. At 30 minutes post-lunch (LH30), PFC had a lower RER and higher fat energy supply ratio and rate, though not statistically significant. Insulin levels were significantly higher in Mix immediately post-lunch (LH0), but PFC showed a greater increase at LH120. GLP-1 levels showed no significant differences. PFC had a smaller decrease in NEFA at LH30 compared to Mix. Fatigue indicators and cycling performance revealed no significant differences (7K: Mix 636±55, PFC 631±26; 85% VO2max: Mix 524±168 , PFC 590±191 seconds), though PFC trended toward longer cycling times at 85% VO2max, with mixed individual performance outcomes. CONCLUSION: The PFC meal pattern helps reduce postprandial insulin and glucose fluctuations, enhances fat oxidation for energy, and sustains stable glucose levels over time. This stability may support prolonged energy during exercise and delays fatigue. Furthermore, after exhaustive exercise, this pattern may boost muscle glycogen resynthesis by extending insulin stimulation, enabling rapid recovery and improving subsequent endurance performance.
Read CV bei wangECSS Paris 2023: CP-PN10
INTRODUCTION: Carbohydrate (CHO) supplementation during exercise is crucial to optimise athletic performance. Energy gels and bars are commonly used to provide rapid CHO by rapid digestion, absorption, and oxidation. While the effects of different sugar compositions – such as simple versus complex sugars and combinations of sugars, such as glucose-fructose – can influence digestion rates, how popular supplements perform in practice is less understood. This study examined the speed of delivery of three popular CHO supplements: a glucose-fructose-based energy bar (Voom Pocket Rocket; VOOM), a maltodextrin-based gel (SIS Go Isotonic; SIS), and a glucose-fructose hydrogel (Maurten Gel 160; MAU). METHODS: Sixteen healthy male Tier 2 runners, cyclists, and triathletes (mean ± SD) (aged 23 ± 4.2 years; height 182.03 ± 6.5 cm; weight 79.5 ± 8.3 kg; BMI 23.81 ± 1.2 kg/m²) completed a modified 60-minute oral glucose tolerance test at Lancaster University’s Human Performance Laboratory. This preregistered trial (NCT06375577) was approved by Lancaster University Medical School Research Ethics Committee (LMS-24-Dean-1). A baseline blood sample was taken following a 2-hour fast, before providing 45 g of CHO from VOOM, SIS, or MAU. Venous blood samples were taken at 5-minute intervals via antegrade-venous cannulation for 60 minutes for glucose and electrolytes (sodium, potassium, chloride). Substrate utilisation was assessed through indirect calorimetry via the respiratory quotient (RQ). Data were analysed for normality using Shapiro-Wilk. Parametric data was analysed via repeated measures ANOVA, while non-parametric data were analysed using the Friedman test. Significance was defined as p < 0.05. RESULTS: CHO oxidation per 5-minute interval was different between CHO supplements (p = 0.03), with VOOM exhibiting greater mean CHO oxidation (2.1 ± 0.3 g·min−1) compared to SIS (1.5 ± 0.4 g·min−1) and MAU (1.7 ± 0.3 g·min−1). Total CHO oxidation was significantly greater in VOOM than SIS (24.6 ± 7.4 g vs 17.8 ± 8.6 g, respectively, p = 0.01) but not MAU (MAU 20.1 ± 6.4 g, p > 0.05). Conversely, total fat oxidation was suppressed to a greater extent for VOOM than SIS (SIS 9.5 ± 3.4 g, VOOM 7.37 ± 2.29 g, p = 0.007) but not MAU (8.45 ± 3.36 g, p > 0.05). The mean RQ was greater for VOOM (0.86 ± 0.06) than MAU (0.84 ± 0.07) and SIS (0.83 ± 0.07) (X2 (38) = 187.8, p < 0.0001). No significant differences were observed in mean peak glucose (VOOM 6.6 ± 1.2 mmol/L, MAU 6.2 ± 1.1 mmol/L, SIS 6.4 ± 1.15 mmol/L) and time to glucose peak (VOOM 31.3 ± 14.0 min, MAU 39.1 ± 12.3 min, SIS 33.1 ± 11.1 min) or in electrolyte levels across supplements (p > 0.05). CONCLUSION: These results suggest that the VOOM glucose-fructose Pocket Rocket delivers CHO as quickly, or perhaps even quicker, than maltodextrin or glucose-fructose energy gels, providing athletes with an effective alternative for carbohydrate supplementation.
Read CV Ewan DeanECSS Paris 2023: CP-PN10