Journal of the International Society of Sports Nutrition最新文献

Background: Phenylcapsaicin (PC) may enhance high-intensity exercise performance by reducing perceived exertion, increasing mechanical output, and limiting muscle damage, making it potentially beneficial for CrossFit^® (CF) athletes.

Objective: To examine the acute effects of PC supplementation on performance, recovery, and metabolic responses during a CF session.

Methods: This study had a randomized, triple-blind, placebo-controlled crossover design. Fifty CF-trained athletes (50% women) ingested either 2.5 mg of PC or a placebo (PLA) 45 minutes before a standardized CF session, including a warm-up, weightlifting block, and WOD. Delayed-onset muscle soreness (DOMS) was assessed 24- and 48-hours post-session. Countermovement jump (CMJ) was evaluated pre- and post-session, while a deep squat at 70% 1RM was performed post-session. Throughout the session, heart rate, capillary lactate, rating of perceived exertion (RPE), and perceived recovery status (PRS) were monitored.

Results: Compared to PLA, PC improved squat performance at 70% 1RM in both load and repetitions (P ≤ 0.035), attenuated the decline in CMJ (P < 0.001), and maintained weightlifting performance over time (P interaction = 0.011), with significantly higher load in round 9 (P = 0.030). No differences were observed during the WOD (P interaction ≥ 0.826). DOMS was significantly lower in the PC group at both 24 h and 48 h (P = 0.030), while no group differences were found for lactate, RPE, PRS, or heart rate (P interaction ≥ 0.340). Analysis stratified by sex showed that PC reduced CMJ loss in men (P = 0.043) and increased squat load in women (P = 0.021).

Conclusion: In conclusion, acute PC supplementation enhances performance and recovery in CF athletes.

Background: Protein supplements are a popular category of dietary supplements among fitness enthusiasts and athletes. However, research providing definitive conclusions on the effects of protein on athletic performance and post-exercise recovery remains limited. Key factors, such as protein source, timing, and optimal dosage, require further investigation to clarify their impact.

Method: A systematic search across seven databases identified 6,129 studies, which were screened using the Covidence online tool. After independent selection, data extraction, and risk of bias assessment by two reviewers, 75 studies involving 1,206 athletes were included in the meta-analysis. A multilevel meta-analysis synthesized data from the included studies using a Bayesian hierarchical model with the brms package. Publication bias was assessed using a funnel plot generated with the PublicationBias package and by calculating the P value of Egger's test through the metafor package. Additionally, a moderation analysis with the brms package was conducted to examine the relationship between seven moderators and effect sizes.

Results: The results demonstrated that the effects of protein-carbohydrate supplements showed statistical significance in comparison to the placebo group [μ(SMD): 0.57, 95% CI: 0.2 to 0.93] in enhancing endurance performance. Pure protein supplements demonstrated statistically significant effects compared to the placebo group in both endurance performance [μ(SMD): 0.37, 95% CI: 0.02 to 0.71] and muscle strength [μ(SMD): 0.72, 95% CI: 0.18 to 1.27]. For post-exercise recovery, pure protein supplements also showed statistically significant effects compared to carbohydrate supplements for maintaining glycogen resynthesis [μ(SMD): 0.83, 95% CI: 0.21 to 1.46]. However, the results indicated that all significant effects were observed in randomized controlled trials where the energy intake between the intervention and control groups was not matched.

Conclusion: The effects of protein supplementation on athletic performance and post-exercise recovery appear to be limited. Protein supplements showed beneficial effects compared to no supplementation. However, all statistically significant results were derived from studies in which energy intake was not matched between groups. This suggests that the observed benefits may not be attributable to protein per se. An additional intake of 1 g/kg/day of protein from supplements, resulting in a total daily protein intake of approximately 2 g/kg/day, appears to be most effective for enhancing athletic performance.

Registration: Registered at the International Prospective Register of Systematic Reviews (PROSPERO) (identification code CRD42024608194).

Background: Exercise induced gastrointestinal (GI) symptoms affect a significant portion of endurance runners, resulting in discomfort and suboptimal performance. Protein intakes pre-exercise may have benefits; however, research investigating dietary intake prior to exercise suggests that many runners avoid foods high in protein before running to manage their GI symptoms. Unfortunately, clinical trials evaluating the effectiveness of this strategy are lacking. This study aimed to quantify exercise-induced GI symptoms, gut fullness, blood glucose response, and ratings of perceived exertion in response to low-protein (LP) and moderate-protein (MP) pre-exercise shake.

Methods: This single-blind crossover study involved 13 recreational runners (eight females, five males) who completed a 10 km treadmill run at 85% of their 10 km race pace after consuming a shake with carbohydrate and whey protein at either a low-protein (0.15 g/kg body mass) or moderate-protein (0.4 g/kg body mass) dose 60 minutes prior to exercise. Due to increased whey protein and standardized carbohydrate, the shakes had differing energy contents. GI symptoms were assessed pre-shake, 60 minutes post-shake, and post-run using a questionnaire and gut fullness was assessed pre-shake, 15-, 30-, and 60 minutes post-shake, and post-run using a visual analog scale. Blood glucose was measured pre-shake, 30- and 60 minutes post-shake, and post-run using a capillary blood sample and rating of perceived exertion was assessed following the 10 km run.

Results: Total symptoms experienced increased over time (p < 0.01) and were greater during the run than at fasting (p < 0.01) or post-shake (p = 0.01) but were not affected by protein content (p = 0.85). A significant increase in bloating severity was observed following the moderate-protein shake as compared to the low-protein shake during the run (0.54 vs 1.23; p = 0.03), but no other symptoms assessed were significantly impacted by the shake composition. Blood glucose was significantly higher at 30 minutes post-shake than at any other time; however, there was no difference between the shakes (p = 0.20). Gut fullness increased post-shake (p < 0.01) but did not differ significantly between the two conditions at any time point; however, remained above fasting at all time points only in the MP group. Rating of perceived exertion was not significantly different between the two conditions (low-protein = 14.9 ± 1.0; moderate-protein = 14.9 ± 0.7; p = 1.00).

Conclusions: Easily digestible protein sources up to 0.4 g/kg body mass consumed one hour before exercise are advised and generally well tolerated, though 0.4 g/kg body mass of protein was associated with increased bloating. However, protein intakes before exercise should be trialed prior to competition due to variations in individual tolerance.

Background: Sodium citrate (SC) can elevate extracellular buffering capacity, yet the intra-individual reliability of its blood bicarbonate ([HCO₃^-]) kinetics and gastrointestinal (GI) responses is unclear, limiting individualized dosing strategies.

Methods: Twelve healthy males (21 ± 1 yr) ingested a solution containing 0.5 g·kg^-1 SC on two visits 3-7 days apart. Capillary [HCO₃^-] was sampled at baseline and every 30 min to 240 min to derive baseline and peak [HCO₃^-], time to peak (TTP), time to exceed +5 and +6 mmol·L^-1 above baseline, and area under the curve (AUC). Reliability was quantified with ICC, typical error (TE), and CV; a Monte Carlo simulation estimated the probability of exceeding +5 and +6 mmol·L^-1 at each time point. GI symptoms (12-item questionnaire) were recorded concurrently.

Results: [HCO₃^-] rose significantly over time from 30 min in both visits (p < 0.001). Reliability was moderate for baseline [HCO₃^-] (ICC = 0.72 [0.25, 0.91]; CV = 3.5%) and AUC (ICC = 0.56; CV = 3.5%), but poor for peak [HCO₃^-] (ICC = 0.23 [-0.29, 0.68]; CV = 5.4%) and all time-based metrics, including TTP (ICC = 0.07; TE = 49.1 min; CV = 32.5%) and time to +5 and +6 mmol·L^-1. Simulation showed an ≥ 80% probability of exceeding +5 mmol·L^-1 from 120-240 min (83.9-85.8%), whereas +6 mmol·L^-1 peaked at 69.7% (150 min). GI symptoms were common, unchanged across visits, and moderately reliable for overall burden (ICC = 0.61; TE = 2.63; CV = 46.6%).

Conclusion: SC elicits a consistent group-level alkalosis, yet individual timing metrics are unreliable. Concentration-based indices are more stable for monitoring. Practically, a 2-3 h ingestion window maximizes the probability of achieving ≥+5 mmol·L^-1, but individual profiling is recommended where precise timing is critical.

Background: Psychological resilience significantly influences immune function and health outcomes in high-stress populations, yet mechanisms underlying nutrition-psychology-immunity interactions remain poorly understood. This study developed an individualized prediction model integrating dietary patterns with psychological and immune adaptations to inform personalized therapeutic approaches.

Methods: A retrospective cohort analysis examined 200 endurance athletes over 12 months using integrated datasets from NHANES athletic subcohort, UK Biobank, and training monitoring databases. Athletes were categorized into three dietary pattern groups (high-carbohydrate, high-protein, balanced micronutrient) based on their naturalistic dietary intake. This observational design examined associations between dietary patterns and health outcomes without manipulating participant diets. A hybrid LSTM-XGBoost machine learning architecture with SHAP analysis predicted individual responses based on psychological variables, immune markers (IL-6, TNF-α, CRP, IgA), and performance metrics. Statistical analyses controlled for multiple comparisons using Bonferroni correction. Non-normally distributed variables were log-transformed or analyzed using non-parametric methods. Mediation analyses examined psychological pathways linking dietary patterns to immune outcomes.

Results: Psychological resilience emerged as the primary predictor of dietary pattern response (SHAP importance = 0.342), with psychological improvements consistently preceding immune function recovery by 1-2 months. Three distinct resilience-based subgroups demonstrated different response trajectories: high resilience athletes achieved superior improvement rates (0.43 vs. 0.10 points/month) and reached plateau phases earlier (6.8 vs. 11.2 months) compared to low resilience individuals. The predictive model achieved exceptional performance metrics (91.2% sensitivity, 87.6% specificity) for identifying non-responders to dietary patterns. Mediation analysis revealed that 42.4% of the associations between dietary patterns and immune function operated through psychological pathways, with cortisol reduction serving as a critical mechanism.

Conclusions: Psychological resilience predicts responsiveness to dietary patterns through psychoneuroimmunological pathways. Baseline psychological assessment should guide personalized nutrition strategies in clinical populations experiencing chronic stress and immune dysfunction.

Background: Carbohydrate mouth rinsing (CHO-MR) during periods of fasting or low muscle glycogen availability could provide a more pronounced ergogenic effect compared to fed and high muscle glycogen conditions. However, there is little evidence investigating the efficacy of CHO-MR during periods of low muscle glycogen induced by ketogenic diets. Therefore, this study aimed to investigate the impact of CHO-MR vs. a placebo (PLA-MR) on cycling time trial performance in trained endurance cyclists following their habitual diet (HD) or a 5-day ketogenic diet (KD).

Methods: Eight participants completed baseline testing and four trial conditions. For each trial, participants adhered to either their HD or a KD for 5 consecutive days. During the first 4 days of each dietary phase, they tracked daily nutrition; additionally, they recorded morning fasting blood glucose and β-hydroxybutyrate (βHB) levels for the 4 days preceding and the morning of each trial. Each trial comprised a 33.6 km simulated time trial in which rinsing was performed for ten seconds at 7 km intervals.

Results: The 5-day KD significantly increased the time to completion (TTC) compared to HD (p < .001). Although no significant differences in TTC were detected between HD + CHO-MR and KD + CHO-MR (p = .670), CHO-MR did not restore KD performance to within 2% of HD conditions (±158 s; 4.8%). While a significant main effect for diet on morning fasted blood [βHB] (p = .001) was observed on day 5, it was not significantly associated with exercise time (r ₍₁₄₎ = -.442, p = .086). Post-exercise blood [glucose] was significantly higher in the HD + CHO-MR and HD + PLA-MR conditions compared to the KD + CHO-MR (p = .038 & p = .021), and KD + PLA-MR (p = .011 and p = .003) conditions, respectively.

Conclusion: The data indicate that repeated 6.4% CHO-MR during endurance cycling is insufficient to overcome performance impairments induced via a 5-day ketogenic diet. This suggests that peripheral substrate availability may constrain the hepatic glucose output in response to central nervous system cues. Further research is required to elucidate how peripheral glycogen stores, central neural drive, and ergogenic interventions interact under low-carbohydrate conditions.