Volume 4 Supplement 1

15th International Conference on Environmental Ergonomics (ICEE XV)

Open Access

The effect of heat acclimation or acclimatisation on physiological markers of heat adaptation: preliminary meta-analysis data

  • Christopher J Tyler1Email author,
  • Tom Reeve1,
  • Gary J Hodges2 and
  • Stephen S Cheung2
Extreme Physiology & Medicine20154(Suppl 1):A110

DOI: 10.1186/2046-7648-4-S1-A110

Published: 14 September 2015

Introduction

Exercise in the heat places a greater physiological strain upon the body than exercising in temperate conditions, so a number of strategies have been adopted to attenuate this strain. Heat acclimation (or acclimatisation) (HA) has regularly been reported to induce beneficial cardiovascular and thermoregulatory adaptations. However, the magnitudes of benefit reported range from none to substantial, and the differences reported may be due to a wide range of HA protocols being used. The aim of this meta-analysis was to quantify the magnitude of effect that HA has on key physiological markers of adaptation, and to see whether the magnitude of effect is related to the volume or intensity of heat stress experienced.

Methods

The PubMed database was searched (09/01/15) using the first-order search terms acclimation, acclimatization, acclimatisation and adaptation and second-order search terms heat, exercise, performance, capacity and training. Using the four-stage process identified in the PRISMA statement the initial number of results (9,369) was reduced to 92. Data (N, mean, SD) were extracted from these articles in duplicate or triplicate. A subset of the data (n = 46 manuscripts) is presented here; manuscripts were included if resting core temperature (Tcore), resting heart rate (HR), resting plasma volume (PV) and/or core temperature at sweat onset (Tsweat onset) data were reported. All HA protocols regardless of duration, frequency, ambient conditions or exercise modality were used. Hedge's g ( ± 95% CI) were calculated and Spearman's correlation analyses were performed between the effect size and total HA time (HAtime), and HA temperature (HAtemp).

Results

The 46 manuscripts reviewed used a mean (SD) of 9 (0) [range: 4 - 16] HA sessions separated by 0 (0) [0 - 1.5] days. Total HAtime was 868 (558) min [150 - 2,880], and the HAtemp and HAhumidity were 39 (5) °C [28 - 50] and 36 (16) % [14 - 86], respectively.

Conclusion

HA is an effective way to reduce resting Tcore and HR; increase resting PV, and lower the Tsweat onset. The magnitude of effect appears to be independent of HAtime or HAtemp for each of the 4 variables with the exception of Tsweat onset, which may be inversely related to HAtime; however, these latter data are derived from only 6 investigations.
Table 1

The effect of HA on resting Tcore, resting HR, resting PV and Tsweat onset.

 

Articles

Groups

N

Hedges g(95% CI)

Mean Δ

HAtime

HAtemp

Resting Tcore

35

40

372

-0.62 (-0.77, -0.47)

-0.17 ± 0.13 °C

r = -0.01NS

r = 0.02NS

Resting HR

21

27

247

-0.60 (-0.78, -0.41)

-5 ± 4 bpm

r = -0.20NS

r = -0.13NS

Resting PV

17

18

183

+0.57 (0.36, 0.79)

+3.5 ± 3.6 %

r = -0.37NS

r = -0.20NS

Tsweat onset

6

9

85

-0.88 (-1.17, -0.59)

-0.24 ± 1.3 °C

r = -0.83**

r = -0.29NS

** = P <0.01; NS = p = 0.07 - 0.50

Authors’ Affiliations

(1)
Department of Sport and Exercise Science, University of Roehampton
(2)
Environmental Ergonomics Laboratory, Department of Kinesiology, Brock University

Copyright

© Tyler et al.; 2015

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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