Cheuvront Samuel N, Sollanek Kurt J, Kenefick Robert W
Sports Science Synergy, LLC, Franklin, MA, United States.
Department of Kinesiology, Sonoma State University, Rohnert Park, CA, United States.
Front Sports Act Living. 2023 Dec 4;5:1277070. doi: 10.3389/fspor.2023.1277070. eCollection 2023.
Recent success in predicting individual sweat losses from air temperature and energy expenditure measurements suggests a potential for forecasting individual sweat losses for future combinations of environment and exercise. The purpose of this study is to determine the plausibility of accurately forecasting exercise sweat losses from meteorological air temperature forecasts and individual running energy expenditure forecasts. The potential impact on plasma sodium is also estimated when setting drinking rates equal to forecast sweat losses.
Individual exercise sweat losses (equated to water needs) and energy expended while running were measured in 33 participants along with air temperature and compared with forecasts of the same. Forecast inputs were used in a web app to forecast exercise sweat losses for comparison with observed values. The bias between forecast and observed exercise sweat losses was used to calculate the potential drinking impact on plasma sodium.
The concordance correlation coefficient between forecast and observed values was 0.95, 0.96, and 0.91 for air temperature, energy expenditure, and exercise sweat losses, respectively, indicating excellent agreement and no significant differences observed via -test. Perfect matching of water intake to sweat losses would lower plasma sodium concentrations from 140 to 138 mmol/L; calculations using the 95% limits of agreement for bias showed that drinking according to forecast exercise sweat losses would alter plasma sodium concentrations from 140 to between 136 and 141 mmol/L.
The outcomes support the strong potential for accurately forecasting exercise sweat losses from commonly available meteorological air temperature forecasts and energy expenditure from forecast running distance.
近期通过测量气温和能量消耗来预测个体汗液流失取得了成功,这表明有潜力预测未来环境与运动组合下的个体汗液流失情况。本研究的目的是确定根据气象气温预报和个体跑步能量消耗预报准确预测运动汗液流失的合理性。在将饮水速率设定为等于预测的汗液流失量时,还估计了对血浆钠的潜在影响。
在33名参与者中测量了个体运动汗液流失量(等同于水分需求)、跑步时消耗的能量以及气温,并将其与相应的预测值进行比较。预测输入值被用于一个网络应用程序中,以预测运动汗液流失量并与观测值进行比较。预测的和观测的运动汗液流失量之间的偏差被用于计算饮水对血浆钠的潜在影响。
气温、能量消耗和运动汗液流失量的预测值与观测值之间的一致性相关系数分别为0.95、0.96和0.91,表明一致性极佳,经t检验未观察到显著差异。饮水摄入量与汗液流失量完全匹配会使血浆钠浓度从140 mmol/L降至138 mmol/L;使用偏差的95%一致性界限进行的计算表明,根据预测的运动汗液流失量饮水会使血浆钠浓度从140 mmol/L改变至136至141 mmol/L之间。
这些结果支持了根据常见的气象气温预报和预测跑步距离的能量消耗准确预测运动汗液流失量的强大潜力。