A Novel Method to Predict Carbohydrate and Energy Expenditure During Endurance Exercise Using Measures of Training Load

IF 9.3 1区 医学 Q1 SPORT SCIENCES Sports Medicine Pub Date : 2024-11-01 DOI:10.1007/s40279-024-02131-z
Jeffrey A. Rothschild, Stuart Hofmeyr, Shaun J. McLaren, Ed Maunder
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Abstract

Background

Sports nutrition guidelines recommend carbohydrate (CHO) intake be individualized to the athlete and modulated according to changes in training load. However, there are limited methods to assess CHO utilization during training sessions.

Objectives

We aimed to (1) quantify bivariate relationships between both CHO and overall energy expenditure (EE) during exercise and commonly used, non-invasive measures of training load across sessions of varying duration and intensity and (2) build and evaluate prediction models to estimate CHO utilization and EE with the same training load measures and easily quantified individual factors.

Methods

This study was undertaken in two parts: a primary study, where participants performed four different laboratory-based cycle training sessions, and a validation study where different participants performed a single laboratory-based training session using one of three exercise modalities (cycling, running, or kayaking). The primary study included 15 cyclists (five female; maximal oxygen consumption [\(\dot{V}\)O2max], 51.9 ± 7.2 mL/kg/min), the validation study included 21 cyclists (seven female; \(\dot{V}\)O2max 53.5 ± 11.0 mL/kg/min), 20 runners (six female; \(\dot{V}\)O2max 57.5 ± 7.2 mL/kg/min), and 18 kayakers (five female; \(\dot{V}\)O2max 45.6 ± 4.8 mL/kg/min). Training sessions were quantified using six training load metrics: two using heart rate, three using power, and one using perceived exertion. Carbohydrate use and EE were determined separately for aerobic (gas exchange) and anaerobic (net lactate accumulation, body mass, and O2 lactate equivalent method) energy systems and summed. Repeated-measures correlations were used to examine relationships between training load and both CHO utilization and EE. General estimating equations were used to model CHO utilization and EE, using training load alongside measures of fitness and sex. Models were built in the primary study and tested in the validation study. Model performance is reported as the coefficient of determination (R2) and mean absolute error, with measures of calibration used for model evaluation and for sport-specific model re-calibration.

Results

Very-large to near-perfect within-subject correlations (r = 0.76–0.96) were evident between all training load metrics and both CHO utilization and EE. In the primary study, all models explained a large amount of variance (R2 = 0.77–0.96) and displayed good accuracy (mean absolute error; CHO = 16–21 g [10–14%], EE = 53–82 kcal [7–11%]). In the validation study, the mean absolute error ranged from 16–50 g [15–45%] for CHO models to 53–182 kcal [9–31%] for EE models. The calibrated mean absolute error ranged from 9–20 g [8–18%] for CHO models to 36–72 kcal [6–12%] for EE models.

Conclusions

At the individual level, there are strong linear relationships between all measures of training load and both CHO utilization and EE during cycling. When combined with other measures of fitness, EE and CHO utilization during cycling can be estimated accurately. These models can be applied in running and kayaking when used with a calibration adjustment.

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利用训练负荷量预测耐力运动中碳水化合物和能量消耗的新方法
背景体育营养指南建议碳水化合物(CHO)的摄入量应根据运动员的具体情况而定,并根据训练负荷的变化进行调节。我们的目的是:(1)量化运动过程中 CHO 和总能量消耗(EE)与不同持续时间和强度的训练过程中常用的非侵入性训练负荷测量方法之间的双变量关系;(2)建立和评估预测模型,利用相同的训练负荷测量方法和易于量化的个体因素来估算 CHO 利用率和 EE。方法本研究分两部分进行:一项是初级研究,参与者在实验室进行四次不同的自行车训练;另一项是验证研究,不同参与者在实验室进行一次训练,使用三种运动方式(自行车、跑步或皮划艇)中的一种。主要研究包括 15 名自行车运动员(5 名女性;最大耗氧量为 51.9 ± 7.2 mL/kg/min),验证研究包括 21 名自行车运动员(7 名女性;最大耗氧量为 53.5 ± 11.0 mL/kg/min)、20 名跑步者(6 名女性;\(\dot{V}\)O2max 57.5 ± 7.2 mL/kg/min)和 18 名皮划艇运动员(5 名女性;\(\dot{V}\)O2max 45.6 ± 4.8 mL/kg/min)。使用六种训练负荷指标对训练课程进行量化:两种使用心率,三种使用功率,一种使用感觉用力。有氧(气体交换)和无氧(净乳酸累积、体重和氧气乳酸当量法)能量系统的碳水化合物用量和 EE 分别测定,然后相加。重复测量相关性用于研究训练负荷与 CHO 利用率和 EE 之间的关系。使用一般估计方程对 CHO 利用率和 EE 进行建模,同时使用训练负荷以及体能和性别指标。模型在主要研究中建立,并在验证研究中进行测试。模型的性能以决定系数(R2)和平均绝对误差的形式报告,校准措施用于模型评估和特定运动模型的重新校准。结果所有训练负荷指标与 CHO 利用率和 EE 之间都存在明显的、非常大甚至接近完美的受试者内相关性(r = 0.76-0.96)。在主要研究中,所有模型都能解释大量方差(R2 = 0.77-0.96),并显示出良好的准确性(平均绝对误差;CHO = 16-21 g [10-14%],EE = 53-82 kcal [7-11%])。在验证研究中,CHO 模型的平均绝对误差范围为 16-50 克 [15-45%] ,EE 模型的平均绝对误差范围为 53-182 千卡 [9-31%]。结论在个体水平上,所有训练负荷测量值与自行车运动中 CHO 利用率和 EE 之间都存在很强的线性关系。当与其他体能测量指标相结合时,骑自行车时的 EE 和 CHO 利用率可以准确估算。这些模型经校准调整后可用于跑步和皮划艇运动。
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来源期刊
Sports Medicine
Sports Medicine 医学-运动科学
CiteScore
18.40
自引率
5.10%
发文量
165
审稿时长
6-12 weeks
期刊介绍: Sports Medicine focuses on providing definitive and comprehensive review articles that interpret and evaluate current literature, aiming to offer insights into research findings in the sports medicine and exercise field. The journal covers major topics such as sports medicine and sports science, medical syndromes associated with sport and exercise, clinical medicine's role in injury prevention and treatment, exercise for rehabilitation and health, and the application of physiological and biomechanical principles to specific sports. Types of Articles: Review Articles: Definitive and comprehensive reviews that interpret and evaluate current literature to provide rationale for and application of research findings. Leading/Current Opinion Articles: Overviews of contentious or emerging issues in the field. Original Research Articles: High-quality research articles. Enhanced Features: Additional features like slide sets, videos, and animations aimed at increasing the visibility, readership, and educational value of the journal's content. Plain Language Summaries: Summaries accompanying articles to assist readers in understanding important medical advances. Peer Review Process: All manuscripts undergo peer review by international experts to ensure quality and rigor. The journal also welcomes Letters to the Editor, which will be considered for publication.
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