Humans exercising in the heat: A review on sweat models and a comparison to recent experimental datasets.

Q1 Biochemistry, Genetics and Molecular Biology
Temperature Pub Date : 2025-06-05 eCollection Date: 2025-01-01 DOI:10.1080/23328940.2025.2508534
Robin de Korver, Boris R M Kingma, George Havenith, Kalev Kuklane, Glen P Kenny, Robert D Meade, Arjan J H Frijns
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Abstract

Sweating is a vital thermoregulatory mechanism in humans for maintaining thermal balance during exercise and exposure to hot environments. The development of models that predict sweat rate based on body temperature has been ongoing for over half a century. Here, we compared predicted water loss rates (WLR) from these models to actual observations collected during 780 participant-exposures in three independent laboratory-based experiments. In these experiments, male participants aged 19-50 years cycled or walked at various intensities (metabolic heat productions between 200 and 970 W), in air temperatures ranging from -40°C to 50°C, relative humidities (14% to 95%), and air velocities (<0.2 to 10 m/s), while wearing different clothing ensembles (thermal insulation 0.20 to 3.75 clo). The models' performances were evaluated by the coefficient of determination (R2) and Root Mean Square Error (RMSE). Performance varied greatly with a maximum R2 value of 0.5 and RMSE values ranging from 10.4 to 4.9 g/min. Models with a lower sweat onset core temperature setpoint performed better and most models generally underestimated the water loss at higher WLR. Optimization of the core and skin temperature setpoints suggests preferred core temperature setpoints within a narrow range (36.2°C to 36.6°C). Even with optimized inputs, R2 values were around 0.5, meaning only 50% of the variance in observed WLR was explained by the models. Better model consideration of relations between body temperature and sweat rate, and the incorporation of non-thermal exercise-induced sweat promotion, may reduce model underpredictions at higher exercise intensities.

人类在高温下运动:对汗液模型的回顾和与最近实验数据集的比较。
出汗是人体在运动和高温环境中维持热平衡的重要体温调节机制。基于体温预测出汗率的模型的发展已经持续了半个多世纪。在这里,我们将这些模型的预测失水率(WLR)与在三个独立的实验室实验中收集的780名参与者暴露的实际观察结果进行了比较。在这些实验中,年龄在19-50岁的男性参与者在不同强度(代谢热产生在200到970瓦之间)、气温从-40°C到50°C、相对湿度(14%到95%)、空气速度(2)和均方根误差(RMSE)下骑车或步行。性能变化很大,R2最大值为0.5,RMSE值在10.4到4.9 g/min之间。具有较低起汗核心温度设定值的模型表现更好,大多数模型通常低估了较高WLR时的水分损失。核心温度和皮肤温度设定值的优化建议首选核心温度设定值在窄范围内(36.2°C至36.6°C)。即使使用优化的输入,R2值也在0.5左右,这意味着观察到的WLR中只有50%的方差是由模型解释的。更好的模型考虑体温和排汗率之间的关系,并纳入非热运动诱导的排汗促进,可能会减少模型在高运动强度下的低估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Temperature
Temperature Medicine-Physiology (medical)
CiteScore
10.40
自引率
0.00%
发文量
37
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