Metabolic costs of physiological heat stress responses - Q₁₀ coefficients relating oxygen consumption to body temperature

Introduction

Q₁₀ describes the influence of temperature on physiological processes as the ratio of the rate of a physiological process at a particular temperature to the rate at a temperature 10 °C lower [1]. In terms of rates of oxygen consumption (VO₂) related to rectal temperatures (t_re), this can be written as [2]:

$${\text{Q}}_{10}={\left(\text{V}{\text{O}}_2/\text{V}{{\text{O}}_2}_{,\text{ref}}\right)}^{10/\left(\text{tre}-\text{tre,ref}\right)}$$

(1a)

or equivalently,

$$\text{V}{\text{O}}_2=\text{V}{\text{O}}_{2,\text{ref}}.{Q_{10}}^{\left(\text{tre}-\text{tre,ref}\right)/10}$$

(1b)

Q₁₀ varies between 2 and 3 in biological systems [2], and Q₁₀ = 2 is applied in modelling the rate of metabolic heat production in relation to body temperature [3, 4]. This paper aims to determine Q₁₀ for the influence of body temperature on oxygen consumption for light work in warm environments.

Methods

Data originated from 216 laboratory experiments [5] consisting of individual series of 14 to 39 trials performed by eleven acclimatised semi-nude young males (I_cl=.1 clo) who walked 4 km.h^-1 on the level for at least 3 hours under different combinations of water vapour pressure (range 0.3 - 5.2 kPa) and air temperature (range 20 - 55 °C) with air velocity of 0.3 m.s^-1 and mean radiant temperature equal to air temperature. Mean values of t_re and VO₂ over the third hour of exposure were submitted to linear regression analyses, which were performed separately for the 11 individual series relating VO₂ directly to t_re and also using the logarithmised Eq. 1b (with t_re,ref = 36.8 °C). Overall regression parameters were calculated by random coefficient linear mixed models considering the correlation within the individual series. Q₁₀ coefficients were obtained as the exponentiated slopes of the fitted logarithmised Eq. 1b.

Results

Regression analyses showed a statistically significant (p < 0.01) increase of VO₂ with t_re (Figure 1A) with inter-individually varying slopes, which resulted in Q₁₀ values varying largely between 1 (indicating no influence of t_re on VO₂) and 10 (Figure 1B). The overall Q₁₀ was 2.1 with 95% confidence interval (CI) 1.3 - 3.5.

Figure 1

VO ₂ related to t _re with overall regression (solid, VO ₂ = 0.671+0.052(t _re -36.8)) and individual lines (dashed) for 11 participants (A), and Q ₁₀ with 95% CI for 11 individuals (open symbols) and for the total sample (filled symbol) with reference lines indicating the neutral value (Q ₁₀ = 1, dashed) and Q ₁₀ = 2 (solid) (B).

Discussion and conclusion

The results support the setting Q₁₀ = 2 [3, 4] under steady state conditions for light work in the heat, however, considerable intra- and inter-individual variability was observed.

Thus, the data base should be extended, also towards other workloads and populations (female, elderly).