Effects of Different Carbohydrate Supplementation on Marathon for Amateur Runners: A Controlled Trial
This controlled trial involving amateur runners found that while high-carbohydrate supplementation (80 g/h) did not significantly reduce total marathon finish times compared to a moderate intake (50 g/h), it effectively delayed speed decline and improved pacing stability, particularly in sub-elite athletes, by maintaining glycemic stability during the race.
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Technical Summary: Effects of Different Carbohydrate Supplementation on Marathon Performance for Amateur Runners
Problem Statement
While the role of carbohydrates (CHO) in endurance performance is well-established, existing research primarily focuses on elite professional athletes. Strategies derived from professional contexts often face practical barriers for mass amateur runners, including gastrointestinal distress and individual tolerance limits. Furthermore, there is a lack of data regarding how different carbohydrate intake rates (specifically 50 g/h vs. 80 g/h) affect the pacing stability and glycemic profiles of amateur runners during a full marathon. This study addresses the need for individualized energy supplementation programs suitable for the general public to optimize energy management during prolonged intensity exercise.
Methodology
- Study Design: A controlled trial conducted during the 2023 Nanjing Marathon (a silver-standard IAAF event).
- Participants: 30 male amateur runners were recruited and categorized by skill level: "Elite" (sub-3:30 marathon or sub-1:45 half-marathon) and "Sub-elite" (sub-4:30 marathon or sub-2:15 half-marathon). They were randomly assigned to two supplementation groups:
- Normal-CHO (N): 50 g/h.
- High-CHO (H): 80 g/h.
- This resulted in four analytical groups: EH (Elite-High), EN (Elite-Normal), SH (Sub-elite-High), and SN (Sub-elite-Normal).
- Intervention Protocol:
- Runners utilized Continuous Glucose Monitoring (CGM) devices (Sibionics) for one week prior to and during the race.
- In-Race Nutrition: Participants consumed sports drinks (6g CHO per 100ml) at designated stations and energy gels (29g CHO per gel) based on a calculated formula to meet their target intake (50g/h or 80g/h). Bananas were permitted as a minor supplement; solid foods were otherwise restricted.
- Data Collection: Performance metrics (pace, finish time) were captured via sports watches. Blood glucose data was collected every 3 minutes via CGM.
- Statistical Analysis: Data was analyzed using multifactorial repeated-measures ANOVA to examine interactions between time (10-km intervals), skill level, and supplementation method. Pearson correlation coefficients were used to assess relationships between blood glucose variability and running speed.
Key Results
- Glycemic Stability: Both supplementation strategies (50 g/h and 80 g/h) successfully maintained blood glucose within normal ranges. No hypoglycemic events (<3.9 mmol/L) were observed in any group.
- Finish Times: While the High-CHO groups (EH and SH) demonstrated numerically faster finish times and average paces compared to the Normal-CHO groups, these differences did not reach statistical significance.
- Pacing Stability and Skill Level Interaction:
- A significant interaction was found between time and skill level. Elite runners maintained stable speeds throughout the race regardless of supplementation.
- Sub-elite runners showed distinct differences based on intake. The SN group (Sub-elite, Normal-CHO) experienced significant speed degradation starting in the 11–20 km interval. In contrast, the SH group (Sub-elite, High-CHO) maintained stable pacing during the 11–20 km interval, with significant speed decline only occurring in the final 10 km (31–40 km).
- Correlation Analysis:
- Absolute blood glucose levels showed a low correlation with running speed across the entire race.
- However, a moderate negative correlation was observed between blood glucose variability (fluctuation) and running speed during the latter stages of the race. Runners with more stable glucose profiles maintained better speeds in the second half.
Key Contributions
- Differentiation by Skill Level: The study highlights that while total finish time may not be significantly altered by higher carbohydrate intake for all amateurs, the timing of performance degradation is affected. High-carbohydrate intake (80 g/h) specifically delays the onset of speed decline in sub-elite runners during the early-to-mid stages (11–20 km).
- Glycemic Stability vs. Absolute Levels: The research provides evidence that for marathon runners, maintaining glycemic stability is more critical for preventing late-race performance decline than achieving higher absolute glucose concentrations, provided levels remain within the physiological normal range.
- Practical Application for Amateurs: The study validates that higher carbohydrate intake rates (up to 80 g/h) are feasible and beneficial for pacing stability in amateur runners, offering a strategy to mitigate early fatigue without necessarily guaranteeing a faster overall finish time.
Significance and Claims
The authors conclude that while high-carbohydrate supplementation (80 g/h) does not significantly reduce total finish time compared to a 50 g/h protocol, it offers a strategic advantage in pacing stability. Specifically, it effectively delays the onset of fatigue and significant speed decline in sub-elite runners during the critical early-to-mid stages of the marathon.
The study posits that the primary mechanism for this benefit is the maintenance of a stable fuel supply, which minimizes metabolic fluctuations and delays central fatigue. The authors emphasize that for amateur runners, the goal of carbohydrate supplementation should be viewed through the lens of maintaining consistent energy availability and glycemic stability rather than solely maximizing absolute glucose levels. The findings suggest that runners may benefit from higher intake levels to minimize metabolic variability, even if the statistical impact on total race time is modest.
Limitations
The authors acknowledge that the final sample size (n=30) was reduced due to non-finishers, which may limit the generalizability of the findings to the broader amateur population. Additionally, the study was limited to full-marathon distances and male participants, suggesting a need for future research across different race distances and demographics.
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