Please use this identifier to cite or link to this item: https://doi.org/10.3389/fphys.2019.00071
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dc.titleEfficacy of heat mitigation strategies on core temperature and endurance exercise: A meta-analysis
dc.contributor.authorAlhadad S.B.
dc.contributor.authorTan P.M.S.
dc.contributor.authorLee J.K.W.
dc.date.accessioned2020-10-16T07:26:01Z
dc.date.available2020-10-16T07:26:01Z
dc.date.issued2019
dc.identifier.citationAlhadad S.B., Tan P.M.S., Lee J.K.W. (2019). Efficacy of heat mitigation strategies on core temperature and endurance exercise: A meta-analysis. Frontiers in Physiology 10. ScholarBank@NUS Repository. https://doi.org/10.3389/fphys.2019.00071
dc.identifier.issn1664042X
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/177637
dc.description.abstractBackground: A majority of high profile international sporting events, including the coming 2020 Tokyo Olympics, are held in warm and humid conditions. When exercising in the heat, the rapid rise of body core temperature (Tc) often results in an impairment of exercise capacity and performance. As such, heat mitigation strategies such as aerobic fitness (AF), heat acclimation/acclimatization (HA), pre-exercise cooling (PC) and fluid ingestion (FI) can be introduced to counteract the debilitating effects of heat strain. We performed a meta-analysis to evaluate the effectiveness of these mitigation strategies using magnitude-based inferences. Methods: A computer-based literature search was performed up to 24 July 2018 using the electronic databases: PubMed, SPORTDiscus and Google Scholar. After applying a set of inclusion and exclusion criteria, a total of 118 studies were selected for evaluation. Each study was assessed according to the intervention's ability to lower Tc before exercise, attenuate the rise of Tc during exercise, extend Tc at the end of exercise and improve endurance. Weighted averages of Hedges' g were calculated for each strategy. Results: PC (g = 1.01) wasmost effective in lowering Tc before exercise, followed by HA (g = 0.72), AF (g = 0.65), and FI (g = 0.11). FI (g = 0.70) was most effective in attenuating the rate of rise of Tc, followed by HA (g = 0.35), AF (g = -0.03) and PC (g = -0.46). In extending Tc at the end of exercise, AF (g = 1.11) was most influential, followed by HA (g= -0.28), PC (g= -0.29) and FI (g = -0.50). In combination, AF (g = 0.45) was most effective at favorably altering Tc, followed by HA (g = 0.42), PC (g = 0.11) and FI (g = 0.09). AF (1.01) was also found to be most effective in improving endurance, followed by HA (0.19), FI (-0.16) and PC (-0.20). Conclusion: AF was found to be the most effective in terms of a strategy's ability to favorably alter Tc, followed by HA, PC and lastly, FI. Interestingly, a similar ranking was observed in improving endurance, with AF being the most effective, followed by HA, FI, and PC. Knowledge gained from this meta-analysis will be useful in allowing athletes, coaches and sport scientists tomake informed decisions when employing heatmitigation strategies during competitions in hot environments. © 2018 Oriental Scientific Publishing Company.
dc.publisherFrontiers Media S.A.
dc.sourceScopus
dc.subjectAerobic fitness
dc.subjectFluid ingestion
dc.subjectHeat acclimation
dc.subjectHeat acclimatization
dc.subjectPre-exercise cooling
dc.subjectThermoregulation
dc.typeArticle
dc.contributor.departmentPHYSIOLOGY
dc.description.doi10.3389/fphys.2019.00071
dc.description.sourcetitleFrontiers in Physiology
dc.description.volume10
dc.published.statePublished
dc.grant.id9015102335
dc.grant.fundingagencyMinistry of Defence, Singapore,ÿMINDEF
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