Predicted Heat Strain (PHS) model and the sweat loss in an extremely hot climate

Research output: Contribution to conferenceAbstract

Abstract

Introduction: The aim was to study if the evaporative water loss can be predicted enough accurately for hydration recommendations by ISO 7933 – Predicted Heat Strain (PHS) model during a student laboratory exercise in an extremely hot environment.

Method: Twelve young healthy students (8 males and 4 females), unacclimatized to heat, were exposed in a climatic chamber at 50˚C, 30% relative humidity and 0.4 m·s-1 air velocity for 45 minutes. They had a mean (SD) age of 25.1 (2.6) years, height 175.6 (6.9) cm, weight 72.3 (11.0) kg, VO2max 54.9 (6.5) mL·min-1·kg-1, and HRmax 194 (6) bpm. The men and women performed bicycling for 6-minutes at workloads of 150 and 100 Watts (W), when the metabolic rates (M) calculated found 363 and 290 W·m-2, respectively. Moreover, the students did step test at 60 steps·min-1 for 5-minutes with estimated M being 215 W·m-2. They were standing most of the time (34 min) (M = 80 W·m-2). Time weighted average M for males and females were 133 and 123 W·m-2, respectively, for the whole exposure duration. Clothing insulation, Icl = 0.4 clo and moisture permeability index, im = 0.42 were input to PHS model simulation. The actual water loss by evaporation was determined by subject’s dressed body weight difference before and after exposure.

Results: The actual mean (SD) total water evaporated was 461.3 (176.7) g. The predicted total water loss was 427.4 (39.2) g by the PHS model. There was no significant (p = .514) difference between the actual and the predicted water loss. However, the original estimation of evaporative sweat was found only 270.1 g.

Conclusions: These results suggest that it is challenging to predict the water loss in continuous extreme heat exposure at 50˚C using ISO 7933 – PHS model. It should be used cautiously to predict the dehydration, and plan for drinking in extremely hot climates.

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Authors
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Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Other Engineering and Technologies

Keywords

  • Water loss, sweat loss, Prediction models, Dehydration, Recommendation
Original languageEnglish
Publication statusPublished - 2019 Jul 11
Publication categoryResearch
Peer-reviewedYes
EventInternational Conference on Environmental Ergonomics 2019 - Amsterdam, Netherlands
Duration: 2019 Jul 72019 Jul 12

Conference

ConferenceInternational Conference on Environmental Ergonomics 2019
CountryNetherlands
CityAmsterdam
Period2019/07/072019/07/12