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. 2013 Mar 4;591(Pt 11):2925–2935. doi: 10.1113/jphysiol.2012.248823

The evaporative requirement for heat balance determines whole-body sweat rate during exercise under conditions permitting full evaporation

Daniel Gagnon 1, Ollie Jay 2, Glen P Kenny 1
PMCID: PMC3690695  PMID: 23459754

Abstract

Although the requirements for heat dissipation during exercise are determined by the necessity for heat balance, few studies have considered them when examining sweat production and its potential modulators. Rather, the majority of studies have used an experimental protocol based on a fixed percentage of maximum oxygen uptake (%Inline graphic). Using multiple regression analysis, we examined the independent contribution of the evaporative requirement for heat balance (Ereq) and %Inline graphic to whole-body sweat rate (WBSR) during exercise. We hypothesised that WBSR would be determined by Ereq and not by %Inline graphic. A total of 23 males performed two separate experiments during which they exercised for 90 min at different rates of metabolic heat production (200, 350, 500 W) at a fixed air temperature (30°C, n= 8), or at a fixed rate of metabolic heat production (290 W) at different air temperatures (30, 35, 40°C, n= 15 and 45°C, n= 7). Whole-body evaporative heat loss was measured by direct calorimetry and used to calculate absolute WBSR in grams per minute. The conditions employed resulted in a wide range of Ereq (131–487 W) and %Inline graphic (15–55%). The individual variation in non-steady-state (0–30 min) and steady-state (30–90 min) WBSR correlated significantly with Ereq (P < 0.001). In contrast, %Inline graphic correlated negatively with the residual variation in WBSR not explained by Ereq, and marginally increased (∼2%) the amount of total variability in WBSR described by Ereq alone (non-steady state: R2= 0.885; steady state: R2= 0.930). These data provide clear evidence that absolute WBSR during exercise is determined by Ereq, not by %Inline graphic. Future studies should therefore use an experimental protocol which ensures a fixed Ereq when examining absolute WBSR between individuals, irrespective of potential differences in relative exercise intensity.

Key points

  • A relative exercise intensity (%Inline graphic) protocol is often used to compare absolute whole-body sweat rates (WBSRs) during exercise between participants of different aerobic capacity.

  • Under conditions permitting full evaporation, heat balance theory suggests that exercise intensity should be fixed to elicit the same rate of evaporation required for heat balance (Ereq).

  • Whole-body direct calorimetry was employed to measure WBSRs throughout 90 min of exercise across a range of air temperatures and rates of metabolic heat production.

  • Irrespective of ambient temperature and metabolic heat production, Ereq alone described ∼90% of all variability in WBSR during steady-state and non-steady-state exercise, whereas <2% of variation was independently described by %Inline graphic.

  • To perform an unbiased comparison of WBSRs (but not necessarily core temperature) between different individuals/groups under conditions allowing full evaporation, future studies should consider using a fixed Ereq irrespective of the %Inline graphic incurred.

Introduction

In 1938, a classic paper by Nielsen (1938) demonstrated that, in accordance with heat balance theory, the rate of evaporation from the skin (and therefore whole-body sudomotor activity) is directly determined by the evaporative requirement for heat balance. During the 1960s, however, two studies (Astrand, 1960; Saltin & Hermansen, 1966) suggested that the inter-individual variability in core temperature during exercise is diminished when exercise intensity is expressed relative to maximum oxygen consumption (i.e. %Inline graphic). These findings have since been cited as a rationale for the use of a fixed %Inline graphic as part of the experimental protocol (Boot et al. 2006; McEntire et al. 2006; Mora-Rodriguez et al. 2008), and led to the notions that a group working at a greater %Inline graphic would suffer ‘undue physiological strain’ (Bar-Or, 1998) and that heat loss responses are associated with relative exercise intensity (Rowland, 2008; Maughan et al. 2010). Experimental protocols employing exercise at a fixed %Inline graphic therefore became, and still remain, the most common approach to study sweat production during exercise.

The use of a protocol based on a fixed %Inline graphic, however, leads to different rates of metabolic heat production between independent groups which are not matched for absolute (in l min−1) Inline graphic (Gagnon et al. 2008; Jay et al. 2011). According to the heat balance equation, the group with the greater Inline graphic therefore necessitates a greater rate of sweat evaporation (and thus production) to offset the greater rate of metabolic heat production elicited by the experimental protocol. Although this flaw has been recognised on a number of occasions (Kenney, 1985; Bar-Or, 1998; Fritzsche & Coyle, 2000; Schwiening et al. 2011), the widespread use of experimental protocols based on a fixed %Inline graphic arguably limits our knowledge as to how various factors affect sweating during exercise, since it is difficult to determine whether observed differences in sweat production are truly associated with the non-repeated factors studied, or if they simply result from a greater rate of metabolic heat production and therefore a greater evaporative requirement for heat balance in a given group.

The use of a more appropriate experimental protocol based on the parameters of the heat balance equation therefore has important implications. According to these parameters, the same evaporative requirement for heat balance (Ereq) must be present between individuals/groups to provide a similar drive for sweat production during exercise. Such an approach has some historical support (Nielsen, 1938) and has been used in the development of fluid replacement guidelines (Shapiro et al. 1982; Gonzalez et al. 2009), the definition of safe work limits (ISO, 1989), and as a means of prescribing exercise intensity in a few studies (Kenney & Kamon, 1984; Bain et al. 2011; Cramer et al. 2012; Deren et al. 2012; Gagnon & Kenny, 2012). However, a fixed %Inline graphic has nonetheless been employed in the vast majority of past and current studies which examine potential differences in sweat production during exercise as a function of a wide range of factors such as age (Anderson & Kenney, 1987; Kenney & Anderson, 1988; Tankersley et al. 1991; Falk et al. 1992a,b; Meyer et al. 1992; Shibasaki et al. 1997; Inoue et al. 1999; Inbar et al. 2004; Rivera-Brown et al. 2006), ethnicity (Lee et al. 2011; Wakabayashi et al. 2011), fitness (Tankersley et al. 1991; Okazaki et al. 2002; Ichinose et al. 2009; Ichinose-Kuwahara et al. 2010; Mora-Rodriguez et al. 2010), injury/disease (McEntire et al. 2006, 2010; Goosey-Tolfrey et al. 2008; Stachenfeld et al. 2010), obesity (Dougherty et al. 2009, 2010) and sex (Paolone et al. 1978; Frye & Kamon, 1981; Horstman & Christensen, 1982; Keatisuwan et al. 1996; Ichinose-Kuwahara et al. 2010; Smith & Havenith, 2012).

Although the required evaporation for heat balance represents a relatively simple and intuitive concept, its use in human temperature regulation studies has not been widespread. This is perhaps due to the fact that no study has actually provided empirical data proving that the required evaporation for heat balance, as opposed to %Inline graphic, determines sweat production during exercise. The purpose of the present study was to use direct calorimetry and directly examine the independent contributions of the required evaporation for heat balance and of %Inline graphic to non-steady-state, as well as steady-state levels of whole-body sweat production, irrespective of exercise intensity and ambient temperature. We hypothesised that both non-steady-state and steady-state sweat production during exercise would be exclusively driven by the required evaporation for heat balance, and not by %Inline graphic.

Methods

Ethical approval

The experimental protocols were approved by the University of Ottawa Health Sciences and Science Research Ethics Board. The procedures conformed to the standards set by the Declaration of Helsinki and written informed consent was obtained from all volunteers prior to their participation in the studies.

Participants

A total of 23 male participants were recruited for two separate experiments. The characteristics of the 23 participants were as follows (mean ± standard deviation): age, 28 ± 10 years (range: 19–50); height, 181 ± 7 cm (range: 165–192); weight, 82.7 ± 8.7 kg (range: 70.5–101.8); body surface area, 2.03 ± 0.12 m2 (range: 1.82–2.27); body fat percentage, 18.0 ± 7.4% (range: 6.6–30.2); Inline graphic, 51.1 ± 6.7 ml kg−1 min−1 (range: 36.6–63.0). Participants were healthy, physically active, non-smoking and free of any known cardiovascular, metabolic and respiratory diseases. For the first experiment, eight male participants completed three experimental sessions during which exercise was performed at different rates of metabolic heat production (200, 350 and 500 W), while air temperature (30°C) and absolute humidity (∼1.3 kPa) remained unchanged. For the second experiment, 15 male participants completed three experimental sessions during which they exercised at a fixed rate of metabolic heat production of 290 W at three different ambient air temperatures (30°C, 35°C and 40°C), with a fixed absolute humidity of ∼0.8 kPa. Furthermore, a sub-group of seven participants performed a fourth experimental session at an ambient air temperature of 45°C with a fixed absolute humidity of ∼0.8 kPa. Some of the data from the second experiment, focusing on whole-body heat loss responses in young and middle-aged participants have been published elsewhere (Kenny et al. 2010).

Experimental design

All participants volunteered for one preliminary session, as well as the experimental sessions previously described. During the preliminary session, body height, mass and density as well as Inline graphic were determined. Body surface area was calculated from the measurements of body height and mass (DuBois & DuBois, 1916). Body density was measured using the hydrostatic weighing technique and used to calculate body fat percentage (Siri, 1956). Maximum oxygen uptake was determined by indirect calorimetry (MOXUS system, Applied Electrochemistry, Pittsburgh, PA, USA) during a progressive incremental exercise protocol performed on an upright seated constant-load cycle ergometer (Corival, Lode B.V., Groningen, the Netherlands). The protocol consisted of having participants cycle continuously at 80 r.p.m., at a starting work rate of 80 W for 2 min. The work rate was then increased by 20 W increments every minute until the participant could not maintain a pedalling cadence of at least 60 r.p.m. (Canadian Society for Exercise Physiology, 1986).

For the experimental sessions, the participants first changed into shorts and sandals upon arrival at the laboratory. They subsequently sat quietly for a 60 min instrumentation period at an ambient room temperature of ∼24°C. Following instrumentation, the participant entered the calorimeter, which was regulated at the appropriate ambient air temperature. The participants then rested in the upright seated posture for a 60 min pre-exercise period before performing 90 min of upright seated cycling. All experimental sessions were randomised, performed at the same time of day for a given participant, and separated by a minimum of 48 h. The participants were asked to drink 500 ml of water the night prior to, as well as the morning of, each experimental session and to refrain from ingesting alcohol and caffeine, and from exercising 24 h prior to experimentation. The participants were not heat acclimatised before performing the experimental sessions.

Measurements

The modified Snellen air calorimeter (height, 1.83 m; cylindrical diameter, 1.68 m; volume, 4000 l) was employed to directly measure whole-body evaporative and dry heat exchange (Reardon et al. 2006). Inflow and outflow values of absolute humidity obtained using high precision dew point hygrometry (RH Systems model 373H, Albuquerque, NM, USA) and temperature obtained using high precision thermistors (Black Stack model 1560, Hart Electronics, Fluke Corp., American Fork, UT, USA) were collected at 8 s intervals throughout the trials. Air mass flow through the calorimeter was estimated by differential thermometry over a known heat source (2 × 750 W heating elements) placed in the effluent air stream. The real-time data were displayed and recorded on a personal computer with LabVIEW software (Version 7.0, National Instruments, Austin, TX, USA). Evaporation of sweat from the skin surface (Esk) was subsequently calculated using the calorimeter outflow–inflow difference in absolute humidity, multiplied by the air mass flow and latent heat of vaporisation of sweat at 30°C (Wenger, 1972). Rate of dry heat exchange was subsequently calculated using the calorimeter outflow–inflow difference in air temperature, multiplied by the air mass flow and specific heat capacity of air.

Indirect calorimetry was used for the concurrent measurement of metabolic energy expenditure (M). Expired gas was analysed for oxygen (error of ±0.01%) and carbon dioxide (error of ±0.02%) concentrations using electrochemical gas analysers (AMETEK model S-3A/1 and CD 3A, Applied Electrochemistry, Pittsburgh, PA, USA) located outside of the calorimeter. Expired air was recycled back into the calorimeter to account for respiratory heat exchange. Before each session, gas mixtures of known concentrations were used to calibrate the gas analysers and a 3 l syringe was used to calibrate the turbine ventilometer. External work (W) on the upright seated cycle ergometer was measured from the resistance control unit located outside of the calorimeter.

Combined direct and indirect calorimetry were employed to measure the individual components of the human heat balance equation (IUPS Thermal Commission, 1987). The required rate of evaporation for heat balance was calculated as:

graphic file with name tjp0591-2925-m1.jpg

where Ereq is the required rate of evaporation for heat balance, M is the rate of metabolic energy expenditure, W is the rate of external work, R is the rate of radiant heat exchange, C is the rate of convective heat exchange, and K is the rate of conductive heat exchange. All units are in watts.

Rectal temperature was measured with a general purpose thermocouple temperature probe (Mallinckrodt Medical Inc., St Louis, MO, USA) inserted to a depth of 12 cm past the anal sphincter. Skin temperature was measured at the upper trapezius, chest, quadriceps and back calf using thermocouples (Concept Engineering, Old Saybrook, CT, USA) attached to the skin with surgical tape. Mean skin temperature was subsequently calculated using the weightings proposed by Ramanathan (1964). Temperature data, accurate to ±0.1°C, were collected using a data acquisition module (HP Agilent model 3497A; Agilent Technologies Canada Inc., Mississauga, ON, Canada) at a rate of one sample every 15 s.

Data analysis

A fundamental property of the modified Snellen air calorimeter is that it ensures 100% evaporation of the sweat produced, therefore providing a direct measure of whole-body sweat production (in g min−1) which was calculated as: evaporative heat loss (in W) multiplied by 60 s and divided by the latent heat of vaporisation of sweat at 30°C (2426 J (g sweat)−1). Evaporative heat loss increases in an exponential fashion during exercise, with a time constant of approximately 12 min and reaching steady state after 30 min of continuous exercise (Kenny et al. 2008). For statistical purposes, the whole-body Esk and sweat production data were therefore examined during both the non-steady-state (first 30 min, when Esk is increasing) and steady-state (last 60 min, when Esk remains relatively stable) periods of the 90 min exercise period.

Statistical analysis

A forward stepwise multiple linear regression analysis was employed to determine the contributions of Ereq and %Inline graphic to end-exercise whole-body Esk values, as well as to whole-body sweat rate during both the non-steady-state (first 30 min) and steady-state (last 60 min) portions of the exercise period. Independent variables were screened for collinearity, with levels of collinearity only considered acceptable and the regression model considered stable for tolerance values greater than 0.70. The rate of increase in whole-body Esk and calculated Ereq was characterised by determining the time constant (τ) of the response using an exponential, one-phase association non-linear regression analysis. The calorimetry data, as well as rectal and mean skin temperatures, were analysed across conditions within each experiment using a two-way ANOVA with the repeated factor of exercise time (levels: 2, 5, 8, 10, 15, 30, 45, 60, 75 and 90 min) and the repeated factor of rate of metabolic heat production (levels: 200, 350 and 500 W), or using the repeated factor of exercise time and the non-repeated factor of ambient temperature (levels: 30, 35, 40 and 45°C). Furthermore, a one-way repeated measures ANOVA was used for single time point comparisons between rates of metabolic heat production, and a non-repeated ANOVA was used for time point comparisons between air temperatures. When a significant main effect was observed, post hoc comparisons were carried out with the Holm–Bonferroni approach. The level of significance for all analyses was set at an α level of P≤ 0.05. Statistical analyses were performed using commercially available statistical software (SPSS 19.0 for Windows, SPSS Inc., Chicago, IL, USA). Curve fitting analysis was performed using GraphPad Prism 5.0 (GraphPad Software, La Jolla, CA, USA). Participant characteristics and environmental parameters are presented as mean ± standard deviation, while all other variables are reported as mean ± 95% confidence intervals.

Results

Fixed air temperature and increasing rate of metabolic heat production

Ambient air temperature did not significantly differ between experimental sessions (P= 0.221), averaging 30.17 ± 0.22°C. As such, rates of dry heat exchange (200 W: 61 ± 9 W; 350 W: 55 ± 9 W; 500 W: 46 ± 7 W) were similar between conditions (P= 0.065, Fig. 1A). By design, however, rate of metabolic heat production significantly differed between conditions (all P≤ 0.001), averaging 219 ± 12 W, 377 ± 18 W and 496 ± 13 W at the end of the 200, 350 and 500 W exercise periods, respectively. These rates of metabolic heat production represented 17 ± 2 (range: 15–23), 33 ± 4 (range: 30–39) and 45 ± 6 (range: 39–55) %Inline graphic. Rate of evaporative heat loss significantly differed between conditions (all P≤ 0.001), being greater with increasing rate of metabolic heat production (Fig. 1A). The rate at which evaporative heat loss increased was significantly quicker with increasing exercise intensity (main effect: P= 0.006, Table 1). Nonetheless, the change in rectal temperature significantly differed between conditions (all P≤ 0.001), the increase averaging 0.2 ± 0.1°C, 0.5 ± 0.1°C and 0.8 ± 0.1°C at the end of exercise performed at 200, 350 and 500 W, respectively. In contrast, mean skin temperature did not differ between conditions (P= 0.988), averaging 34.5 ± 0.7°C, 34.2 ± 0.6°C and 34.4 ± 0.5°C at the end of the 200, 350 and 500 W exercise periods, respectively.

Figure 1.

Figure 1

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Rates of metabolic heat production (M–W), evaporation from the skin surface (Esk) and dry heat exchange (R+C+K) during exercise performed either at increasing rates of metabolic heat production (200, 350, 500 W) and a fixed ambient temperature (30°C, A) or at increasing ambient temperatures (30, 35, 40, 45°C) and a fixed rate of metabolic heat production (290 W, B). For A, rate of dry heat exchange represents the mean of all three conditions, while rate of metabolic heat production in B represents the mean of all four conditions. Evaporative heat loss was significantly (P≤ 0.05) different between all metabolic heat production conditions in A. Evaporative heat loss and dry heat exchange were significantly (P≤ 0.05) different between all temperature conditions in B. Dashed line in B separates dry heat loss (positive) from dry heat gain (negative). Values are mean ± 95% confidence intervals. n, sample size.

Table 1.

Time constant of the evaporative heat loss response during exercise performed at varying requirements for heat loss

Esk Ereq
Conditions n τ (min) Amplitude (W) R2 τ (min) Amplitude (W) R2
200 W, 30°C 8 22.5 ± 9.0 108 ± 18 0.96 ± 0.01 2.1 ± 1.9 100 ± 23 0.82 ± 0.05
350 W, 30°C 8 11.5 ± 2.3* 261 ± 28* 0.98 ± 0.01 1.3 ± 0.4 265 ± 21* 0.92 ± 0.03
500 W, 30°C 8 9.1 ± 1.0* 383 ± 29*† 0.99 ± 0.01 1.2 ± 0.3 394 ± 8*† 0.97 ± 0.01
30°C, 290 W 15 19.2 ± 4.1 186 ± 13 0.94 ± 0.02 2.7 ± 1.4 166 ± 8 0.84 ± 0.05
35°C, 290 W 15 13.8 ± 2.8 187 ± 17 0.94 ± 0.01 1.7 ± 1.0 180 ± 10 0.85 ± 0.04
40°C, 290 W 15 10.2 ± 2.2 186 ± 19 0.94 ± 0.01 1.2 ± 0.7 187 ± 10‡ 0.85 ± 0.04
45°C, 290 W 7 8.9 ± 1.7 167 ± 22 0.94 ± 0.02 1.4 ± 0.5 187 ± 10 0.87 ± 0.04
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Values are mean ± 95% confidence intervals. *Significantly different from 200 W. †Significantly different from 350 W. ‡Significantly different from 30°C. Esk, rate of evaporation from the skin surface; Ereq, requirement for heat loss; n, sample size; τ, time constant.

Fixed rate of metabolic heat production and increasing air temperature

By design, the rate of metabolic heat production did not differ between conditions (P= 0.958), averaging 292 ± 4 W and representing 24 ± 4 %Inline graphic (range: 19–32) across all temperature conditions. In contrast, air temperature averaged 30.33 ± 0.23°C, 35.16 ± 0.35°C, 40.12 ± 0.40°C and 45.27 ± 0.07°C (all P≤ 0.001) during the 30, 35, 40 and 45°C exercise periods, respectively. As such, rate of dry heat exchange significantly differed between sessions (all P≤ 0.001), becoming more negative (representative of dry heat gain) with increasing air temperature (Fig. 1B). In parallel, rate of evaporative heat loss became significantly greater with increasing ambient air temperature (all P≤ 0.001, Fig. 1B). However, its rate of increase did not significantly differ between conditions (main effect: P= 0.111, Table 1). In contrast to the increasing exercise intensity conditions, the change in rectal temperature did not significantly differ between conditions (main effect: P= 0.479), the increase averaging 0.4 ± 0.1°C, 0.3 ± 0.1°C, 0.3 ± 0.1°C and 0.3 ± 0.1°C at the end of exercise performed at 30, 35, 40 and 45°C, respectively. In contrast, mean skin temperature was significantly greater with increasing air temperature (all P≤ 0.001), averaging 34.4 ± 0.3°C, 35.4 ± 0.2°C, 36.3 ± 0.2°C and 38.1 ± 0.8°C at the end of the 30, 35, 40 and 45°C exercise periods, respectively.

Regression analyses

Non-steady-state period (0–30 min of exercise)

Both non-steady-state Ereq (partial correlation coefficient [β] = 0.025, P < 0.001) and %Inline graphic (β=−0.045, P < 0.001) independently correlated with the rates of whole-body sweat rate observed during the first 30 min of exercise (adjusted coefficient of determination [R2] = 0.904). Alone, Ereq independently described 88.5% of the individual variability observed in whole-body sweat rate; however, %Inline graphic only independently described an additional 1.9% of the variance in whole-body sweat rate.

Steady-state period (30–90 min of exercise)

Ereq during exercise became greater with increases in both the rate of metabolic heat production (P≤ 0.001) and ambient temperature (P≤ 0.001). Whole-body sweat rate increased in direct proportion with Ereq, such that within a given ambient temperature, whole-body sweat rate increased linearly with increases in rate of metabolic heat production (Fig. 2). For a fixed rate of metabolic heat production, whole-body sweat rate also increased as a function of ambient temperature (Fig. 2). Overall, the conditions employed resulted in Ereq values that ranged from 131 to 487 W. Forward stepwise multiple regression analysis revealed that Ereq significantly correlated with the variance in end-exercise values of Esk (β= 0.947, P < 0.001), while %Inline graphic did not (β= 0.013, P= 0.690). End-exercise Ereq explained ∼95% of the variance in end-exercise Esk values (adjusted R2= 0.945, Fig. 3). Steady-state Ereq (β= 0.024, P < 0.001) and %Inline graphic (β=−0.020, P= 0.042) significantly correlated with the variance in steady-state whole-body sweat rate (adjusted R2= 0.933). However, %Inline graphic only marginally (0.3%) improved the regression model relative to the independent contribution of Ereq (adjusted R2= 0.930).

Figure 2.

Figure 2

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Mean whole-body sweat rate plotted as a function of rate of metabolic heat production during exercise performed at various combinations of rate of metabolic heat production (200, 290, 350, 500 W) and ambient temperature (30, 35, 40, 45°C). Note that whole-body sweat rate is determined by rate of metabolic heat production when exercise is performed at a fixed ambient temperature, whereas whole-body sweat rate is determined by ambient temperature when exercise is performed at a fixed rate of metabolic heat production. n, sample size.

Figure 3.

Figure 3

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Simple linear regression of end-exercise evaporative heat loss (left axis, measured directly) and whole-body sweat rate (right axis, calculated from evaporative heat loss) plotted as a function of the required evaporation for heat balance during exercise performed at various combinations of rate of metabolic heat production and ambient temperature. n, sample size.

Discussion

The current study examined the contribution of the required evaporation for heat balance and %Inline graphic in determining absolute whole-body sweat production during exercise performed across a range of exercise intensities and ambient temperatures. The required evaporation for heat balance was the only variable which independently explained the variation in end-exercise evaporative heat loss, and was the main variable which explained the variance in non-steady-state as well as steady-state whole-body sweat production. In contrast, %Inline graphic did not contribute independently to the variation in end-exercise evaporative heat loss, and only described a very small (<2%) amount of variability in non-steady-state and steady-state whole-body sweat rate. Furthermore, the correlation of %Inline graphic with the residual variance in whole-body sweat rate (non-steady state and steady state) was negative after accounting for the required evaporation for heat balance, which is opposite to conventional wisdom. The current study therefore provides a simple and conclusive proof of concept that the absolute required evaporation for heat balance, not %Inline graphic, determines absolute whole-body sweat production during exercise under conditions permitting full evaporation.

The importance of the current findings is linked to the fact that many studies (past and current) employ an experimental protocol based on a fixed %Inline graphic to examine potential differences in sweat production between individuals and as a function of non-repeated factors. The use of such a protocol almost certainly stems from the early studies of Astrand (1960) and Saltin & Hermansen (1966) which led to the long-held notion that core temperature during exercise is determined by %Inline graphic. In contrast, a number of earlier (Hardy & Dubois, 1937; Nielsen, 1938) and subsequent (Nielsen, 1968) studies clearly established that sweat production during exercise is driven by metabolic heat production and ambient temperature. In fact, some studies actually recognised that %Inline graphic is only related to sweat production during exercise through its association with rate of metabolic heat production and by extension the required evaporation for heat balance (Davies, 1979). Nonetheless, the vast majority of studies examining sweat production between independent groups have used experimental protocols in which exercise is performed at a fixed %Inline graphic (Paolone et al. 1978; Frye & Kamon, 1981; Horstman & Christensen, 1982; Anderson & Kenney, 1987; Kenney & Anderson, 1988; Tankersley et al. 1991; Falk et al. 1992a,b; Meyer et al. 1992; Keatisuwan et al. 1996; Shibasaki et al. 1997; Inoue et al. 1999; Okazaki et al. 2002; Inbar et al. 2004; McEntire et al. 2006, 2010; Rivera-Brown et al. 2006; Goosey-Tolfrey et al. 2008; Dougherty et al. 2009, 2010; Ichinose et al. 2009; Ichinose-Kuwahara et al. 2010; Mora-Rodriguez et al. 2010; Stachenfeld et al. 2010; Lee et al. 2011; Wakabayashi et al. 2011; Smith & Havenith, 2012). The main concern with this protocol is the different rates of metabolic heat production it produces between groups that are not matched for absolute (in l min−1) Inline graphic (Gagnon et al. 2008; Jay et al. 2011). In accordance with fundamental heat balance theory, our data clearly demonstrate that any differences observed in absolute sweat production in these situations cannot be solely attributed to potential physiological differences in temperature regulation between the groups studied, as they could be simply due to the differences in rate of metabolic heat production (and therefore the evaporative requirement for heat balance) elicited by a %Inline graphic experimental protocol.

The evaporative requirement for heat balance is not a new concept and has been used in a few studies, particularly those aimed at predicting sweat losses during exercise across a wide range of exercise intensities and environmental conditions (Shapiro et al. 1982; Gonzalez et al. 2009), as well as those examining inter-individual differences in local sweat rate (Bain et al. 2011). The evaporative requirement for heat balance represents a simple rearrangement of the heat balance equation (Gagge & Gonzales, 1996) by combining rate of metabolic heat production and dry heat exchange. As such, the evaporative requirement for heat balance more accurately represents the evaporation needed to offset the heat load created by the combination of metabolic heat production and dry heat exchange. This is particularly evident when examining Fig. 2, in which whole-body sweat production increases with both (1) increases in ambient temperature at a given rate of metabolic heat production, and (2) increasing rate of metabolic heat production at a given ambient temperature. These findings highlight the fact that it is not simply rate of metabolic heat production (i.e. absolute exercise intensity) by itself that determines sweat production during exercise, but rather the evaporative requirement for heat balance which also accounts for rate of dry heat exchange between the human body and a given environment. A good example is a comparison of the 290 W–35°C and 350 W–30°C conditions in Fig. 2, insofar that a similar rate of whole-body sweat production is achieved with different combinations of air temperature and metabolic heat production. It follows that the difference in dry heat loss between 35°C and 30°C equates to the difference in metabolic heat production thus yielding very similar Ereq values. This principle is further emphasised in Fig. 1B, where evaporative heat loss exceeds rate of metabolic heat production during exercise performed at 40°C and 45°C, as a result of the additional evaporation needed to offset the dry heat gain when ambient temperature exceeds mean skin temperature.

Although %Inline graphic did not independently contribute to the variation in end-exercise evaporative heat loss, it did significantly contribute, albeit minimally, to the description of the individual variability observed in both non-steady-state and steady-state whole-body sweat production. However, it is important to recognise that the contribution of %Inline graphic only marginally improved the overall regression model relative to the independent contribution of the evaporative requirement for heat balance. Independently, the required evaporation for heat balance explained 88.5 and 93.0% of the variance in non-steady-state and steady-state whole-body sweat rate, respectively, whereas %Inline graphic only described an additional 1.9 and 0.3% of variability in whole-body sweat rate. Furthermore, when examining the independent contribution of %Inline graphic, in direct opposition to previous assertions in the literature, it actually correlated negatively (β values: −0.045 and −0.020 for non-steady-state and steady-state analyses, respectively) with the residual variance in whole-body sweat production, suggesting that exercise at greater percentages of Inline graphic is associated with lower rates of whole-body sweat production. Although a clear explanation for this association is not readily apparent, these findings highlight the fact that %Inline graphic has a very weak independent association with non-steady-state and steady-state whole-body sweat rate and, if anything, has a negative relationship with these variables.

Experimental protocols based on a fixed %Inline graphic have been used in temperature regulation studies for the better part of the last 40 years. Considering that heat loss responses are associated with increases in body temperature (core and skin), it is perhaps not surprising that efforts were taken to find an experimental protocol which elicits similar increases in body temperature between independent groups, against which heat loss responses were compared. Although changes in core and mean skin temperatures stimulate the onset of sweat production and are used to evaluate the thermosensitivity of the response (Hammel, 1968), the level of sweat production achieved during exercise is dependent upon both physiological control systems (i.e. active system), and the biophysical requirements for heat balance (i.e. passive system). For example, studies have shown that similar rates of sweat production occur at a fixed required evaporation for heat balance despite wide variations in body temperature (Bain et al. 2011; Jay et al. 2011; Cramer et al. 2012). Furthermore, during the conditions of increasing ambient air temperature in the current study, whole-body sweat production increased as a function of the evaporative requirement for heat loss, yet changes in core temperature did not significantly differ at the end of each exercise period as the conditions employed resided within the prescriptive zone described by Lind (1963).

It is important to recognise that a fundamental characteristic of the Snellen direct calorimeter is to ensure full evaporation of all sweat produced on the skin surface, which provides direct and accurate measurements of whole-body sweat production. It should also be recognised that the current study was designed to only examine the contribution of the absolute required evaporation for heat balance (in W) to absolute whole-body sweat rate (in g min−1). As such, it is unknown whether the current findings can be applied to conditions which do not ensure 100% sweat evaporation and/or to measurements of local sweat rate which are adjusted for surface area. Furthermore, this study was not designed to examine whether absolute or relative exercise intensity determines core temperature and, as such, it is unknown whether the use of a fixed required evaporation for heat balance may diminish inter-individual variability in core temperature. Jay et al. (2011) suggested that the requirement for evaporative heat loss should be adjusted relative to body surface area (i.e. W m−2) or body mass (i.e. W kg−1) when examining local sweat rate and core temperature, respectively, between individuals of varying body surface area and body mass. Future studies are therefore needed to determine whether adjustments in the required evaporation for heat balance are needed when environmental conditions (e.g. high ambient water vapour pressure) and/or morphological factors (e.g. body mass and surface area) alter the evaporative efficiency of sweating, and when core temperature or local sweat rate are the main variables of interest.

Limitations of the present study include the fact that all of the participants were male; however, since heat balance principles are the same for both sexes, it seems unlikely that %Inline graphic would primarily determine sweat output in females when no such observation was apparent in males. The study was also not a complete repeated measures design, with only seven participants completing the highest air temperature (45°C) condition. Despite the laws of heat balance applying equally to all modes of heat stress, the data presented are limited to activity-induced heat stress. As such, the present findings cannot be currently extended to include a passive heat stress model. Finally, the Snellen direct calorimeter cannot dissociate the evaporation of moisture from the skin from the evaporation of moisture from the respiratory tract; therefore the whole-body sweat rate values reported include respiratory mass losses. However, the differences in respiratory mass loss between the highest and lowest metabolic rate is estimated to be ∼4% and may describe some of the variance that remained unexplained by the independent variables in our regression model.

The implications of the current study are simple, yet important: future studies aimed at examining potential physiological differences in absolute whole-body sweat rate as a function of any non-repeated factor should utilise a protocol which ensures a fixed required evaporation for heat balance, irrespective of the %Inline graphic incurred. For experiments conducted under fixed environmental conditions, an appropriate protocol would be to ensure a fixed rate of metabolic heat production (or rate of oxygen uptake) verified by indirect calorimetry as any potential differences in dry heat exchange between participants would contribute minimally in an absolute sense to the variability in the required evaporation for heat balance. For researchers without indirect calorimetry, a fixed external workload could be employed provided there are no differences in mechanical efficiency between conditions/groups. These approaches are no more difficult than ensuring that groups exercise at a fixed %Inline graphic, and have been used recently in determining the independent effect of fitness (Bain et al. 2011; Jay et al. 2011) and sex (Gagnon & Kenny, 2011, 2012) on sweat production during exercise in the heat. Finally, these approaches should be adopted irrespective of whether exercise periods are of long or short duration, as both non-steady-state and steady-state values of whole-body sweat production in the current study were determined by the required evaporation for heat balance.

Conclusion

The results of the current study provide simple, yet convincing evidence that absolute whole-body sweat production during exercise is determined by the absolute required evaporation for heat balance, and that %Inline graphic bears little influence. Independently, the required evaporation for heat balance explained ∼95% of the variance in end-exercise evaporative heat loss across a range of exercise intensities (200–500 W) and ambient temperatures (30–45°C). Furthermore, the required evaporation for heat balance explained over 88% and 93% of the variation in non-steady-state and steady-state whole-body sweat production, respectively. In contrast, %Inline graphic did not contribute independently to the variation in end-exercise whole-body evaporative heat loss, and only described an additional 0.3% and 2% of variance in non-steady-state and steady-state whole-body sweat production, respectively, that was not already described by the required evaporation for heat balance. These results therefore provide the basis for future studies to employ an experimental protocol which ensures a fixed absolute required evaporation for heat balance when examining absolute whole-body sweat production as a function of non-repeated factors such as age, ethnicity, fitness, injury/disease, obesity and sex.

Acknowledgments

The current work was supported by grants from the Workplace Safety and Insurance Board of Ontario (06005, G.P.K.), the Natural Sciences and Engineering Research Council (RGPIN-298159-2009, G.P.K.) and Leaders Opportunity Fund from the Canada Foundation for Innovation (22529, G.P.K. and O.J.). G.P.K. is supported by a University of Ottawa Research Chair. The authors acknowledge the contributions of Dr Lucy Dorman and Dr Joseph Maté during data collection.

Author contributions

All authors contributed to the conception and design of the experiments, to the collection, analysis and interpretation of data, as well as to the drafting and critical revising of the manuscript. All authors have approved the final version of the manuscript. All experiments were performed at the University of Ottawa.

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