Critical environmental limits for young, healthy adults (PSU HEAT Project)

Abstract

Critical environmental limits are those combinations of ambient temperature and humidity above which heat balance cannot be maintained for a given metabolic heat production, limiting exposure time, and placing individuals at increased risk of heat-related illness. The aim of this study was to establish those limits in young (18–34 yr) healthy adults during low-intensity activity approximating the metabolic demand of activities of daily living. Twenty-five (12 men/13 women) subjects were exposed to progressive heat stress in an environmental chamber at two rates of metabolic heat production chosen to represent minimal activity (MinAct) or light ambulation (LightAmb). Progressive heat stress was performed with either 1) constant dry-bulb temperature (T_db) and increasing ambient water vapor pressure (P_a) (P_crit trials; 36°C, 38°C, or 40°C) or 2) constant P_a and increasing T_db (T_crit trials; 12, 16, or 20 mmHg). Each subject was tested during MinAct and LightAmb in two to three experimental conditions in random order, for a total of four to six trials per participant. Higher metabolic heat production (P < 0.001) during LightAmb compared with MinAct trials resulted in significantly lower critical environmental limits across all P_crit and T_crit conditions (all P < 0.001). These data, presented graphically herein on a psychrometric chart, are the first to define critical environmental limits for young adults during activity resembling those of light household tasks or other activities of daily living and can be used to develop guidelines, policy decisions, and evidence-based alert communications to minimize the deleterious impacts of extreme heat events.

NEW & NOTEWORTHY Critical environmental limits are those combinations of temperature and humidity above which heat balance cannot be maintained, placing individuals at increased risk of heat-related illness. Those limits have been investigated in young adults during exercise at 30% V̇o_2max, but not during metabolic rates that approximate those of light activities of daily living. Herein, we establish critical environmental limits for young adults at two metabolic rates that reflect activities of daily living and leisurely walking.

INTRODUCTION

The average temperature of the Earth has been steadily increasing for several decades and is expected to continue increasing throughout the 21st century (1). Along with the increase in average global temperatures, the frequency, duration, and severity of heat waves have increased (2). Epidemiological data support a strong association between heat waves and excess mortality. During the Chicago heat wave in 1995, there were ∼700 excess deaths compared with the same days in the previous year (3). In 2003, a heat wave of nine consecutive days in France was estimated to have caused nearly 15,000 excess deaths (4). Excess mortality was increased in California by 4.3% for every 5.6°C increase in apparent temperature when temperatures were above the 90th percentile (5). In 15 cities across Europe, an increase in apparent temperature of 1°C above a threshold temperature unique to each city was associated with a ≥2% increase in mortality (6). Together, these data illustrate the critical need for research targeted toward understanding the environmental conditions associated with heat- and humidity-related morbidity and mortality.

Critical environmental limits are defined as those combinations of environmental conditions (temperature and humidity) above which heat balance cannot be maintained for a given metabolic heat production (7–11). A time-intensive, progressive heat stress protocol was developed by Belding and Kamon (12) to determine critical ambient water vapor pressures (P_crit) at 36°C during exercise at various intensities and air movement velocities. That protocol was refined by our laboratory and used to identify critical environmental limits for prolonged heat exposure in various populations or clothing ensembles across a range of ambient dry-bulb temperatures (T_db) and water vapor pressures (P_a) (7–10, 13, 14), primarily at moderate work intensities within the context of industrial settings.

Empirically derived critical environmental limits can be plotted on a psychrometric chart and used to develop evidence-based alert communication, policy decisions, triage for impending heat events, and implementation of other safety interventions during extreme heat events. Previous data from our laboratory have established critical environmental limits for young men and women (10) and older unacclimated women (14) during exercise at 30% V̇o_2max — a work rate that reflects the intensity associated with an 8-h work day in many industrial settings (15). However, critical environmental limits during very light physical activity, approximating the intensity of daily activities such as household tasks or leisurely walking, have yet to be established. To develop targeted policy and safety interventions to mitigate the impact of future heat events, it is important to establish critical environmental limits for various subpopulations during physical activity at metabolic work rates that are relevant among free-living adults. That is the overarching goal of the PSU HEAT (Human Environmental Age Thresholds) project. Although aged populations are most at risk in extreme environments, it is important to first establish these limits for young healthy adults to establish a baseline for comparative purposes.

Therefore, the purpose of this investigation was to establish critical environmental limits for healthy young adults at two low metabolic intensities that reflect activities of daily living and slow walking. We hypothesized that critical environments would be shifted downward and leftward on a psychrometric chart at higher compared with lower rates of metabolic heat production. By establishing psychrometric limits in a young, healthy population, the findings of this study will be used against which to compare future studies in vulnerable populations.

METHODS

Subjects

All experimental procedures received ethics approval from the Institutional Review Board at The Pennsylvania State University and conformed to the guidelines set forth by the Declaration of Helsinki. After all aspects of the experiment were explained, oral and written informed consent was obtained. Twenty-five healthy men (n = 12) and women (n = 13) aged 18– 34 yr were tested at two light levels of activity in two to three environmental conditions, in random order, for a total of four to six trials per participant.

All subjects were healthy, normotensive (blood pressure was measured using brachial auscultation after 10 min quiet rest), nonsmokers, and not taking any medications that might affect the physiological variables of interest in this study. No attempt was made to control for menstrual status or contraceptive use. Acclimatization status was not accounted for (“see LIMITATIONS”). Maximal aerobic capacity (V̇o_2max) was determined with the use of open-circuit spirometry (Parvo Medics TrueOne 2400, Parvo, UT) during a maximal graded exercise test performed on a motor-driven treadmill. During the experiments, clothing was standardized with subjects wearing thin, short-sleeved cotton tee-shirts, a sports bra for women, shorts, socks, and walking/running shoes.

Testing Procedures

Experimental trials were conducted on separate days with at least 72 h between visits. Participants were asked to abstain from caffeine consumption for at least 12 h, and alcohol consumption or vigorous exercise for 24 h, before arrival for experimental trials. Upon arrival at the laboratory, participants provided a urine sample to ensure euhydration, defined as urine specific gravity ≤ 1.020 (USG; PAL-S, Atago, Bellevue, WA) (16). Subjects performed light activity in an environmental chamber at two intensities reflecting the metabolic demand of minimal physical activity (MinAct) or light ambulatory activity (LightAmb) (17, 18). Subjects cycled on a cycle ergometer (Lode Excalibur, Groningen, The Netherlands) against zero resistance at a cadence of 40–50 rpm for MinAct trials and walked on a motor-driven treadmill at a speed of 2.2 mi/h and grade of 3% for LightAmb trials. All experiments began between the hours of 0800 h and 1500 h; thus, although minor differences in absolute core temperature may have existed due to time of testing (19), the biophysics of heat exchange, and therefore the critical environmental conditions, was unlikely to have been affected by circadian rhythm.

During P_crit trials, T_db was held constant at either 36°C, 38°C, or 40°C. During T_crit trials, P_a was held constant at either 12, 16, or 20 mmHg. After a 30-min equilibration period, either the T_db (T_crit tests) or the P_a (P_crit tests) in the environmental chamber was increased in a stepwise fashion (1°C or 1 mmHg every 5 min), whereas chamber T_db and subject gastrointestinal temperature (T_gi) and HR were monitored. During each experiment, subjects pedaled or walked continuously until a clear rise in T_c was observed. With no forced air movement in the environmental chambers, air movement velocity has been measured at 0.45 m/s (10).

Measurements

Gastrointestinal temperature telemetry capsules (VitalSense, Philips Respironics, Bend, OR) were provided for subjects to ingest 1–2 h before reporting to the laboratory in accordance with previously published data indicating that ingestion times ranging from 1 to 12 h before use do not influence the precision of T_gi data (20). T_gi data were continuously measured and transmitted to a PowerLab data acquisition system and LabChart signal processing software (ADInstruments, Colorado Springs, CO) using an Equivital wireless physiological monitoring system (Equivital Inc., New York, NY). We have previously demonstrated excellent concurrence between rectal and gastrointestinal temperatures for the determination of the T_c inflection point (ICC = 0.93) (11).

Skin temperature was measured continuously (iButton, Whitewater, WI) at four sites: chest (T_ch), arm (T_arm), thigh (T_th), and lower leg (T_leg). A weighted mean skin temperature (${\overline{\text{T}}}_{\text{sk}}$) was calculated (21) as

$${\stackrel{-}{\mathrm{T}}}_{\mathrm{s}\mathrm{k}}=0.3\cdot {\mathrm{T}}_{\text{ch}}+0.3\cdot {\mathrm{T}}_{\text{th}}+0.2\cdot {\mathrm{T}}_{\text{arm}}+0.2\cdot {\mathrm{T}}_{\text{leg}}.$$ (1)

Oxygen consumption (V̇o₂; L/min) and respiratory exchange ratio (RER; unitless) were determined at two time points (5 and 60 min after the onset of exercise) using indirect calorimetry (Parvo Medics TrueOne 2400, Parvo, UT). Metabolic rate [M; Watts (W)], normalized to body surface area, was calculated from V̇o₂ and RER (22) as

$$M=\dot{\mathrm{V}}{\mathrm{O}}_2\cdot \frac{\left[\left(\left(\frac{\text{RER}-0.7}{0.3}\right)\cdot 21.13\right)+\left(\left(\frac{1.0-\text{RER}}{0.3}\right)\cdot 19.62\right)\right]}{60}\cdot \mathrm{1,000}\cdot {A_D}^{-1},$$ (2)

where A_D is the Dubois surface area (m²). For treadmill walking trials, external work (W; W/m²) was calculated as

$$W=9.81\cdot {\text{m}}_{\text{b}}\cdot {\text{v}}_{\text{w}}\cdot {\text{ F}}_{\text{g}}\cdot {\text{ A}}_{\text{D}}{}^{-1},$$ (3)

where m_b is the body mass (kg), V_w is the walking velocity (m/min), and f_g is the fractional grade of the treadmill (22). For cycling trials, W was assumed to be zero. Net metabolic heat production (M_net) was calculated as M − W.

To compare work rates in terms of metabolic equivalents (METs) to previous data (17) detailing the metabolic costs of various household tasks, METs were calculated using V̇o₂ in mL·kg⁻¹·min⁻¹, assuming a resting V̇o₂ of 3.5 mL·kg⁻¹·min⁻¹ (23), as

$$\mathrm{M}\mathrm{E}\mathrm{T}\mathrm{s}=\frac{\dot{\mathrm{V}}{\mathrm{O}}_2}{3.5}.$$ (4)

Dry heat exchange via radiation and convection (W·m⁻²) was determined as

$$\left(R+C\right)=h_{r+c}\cdot ({\mathrm{T}}_{\text{db}}-{\stackrel{-}{\mathrm{T}}}_{\text{sk}}),$$ (5)

where h_r+c (in W·m⁻²·°C⁻¹) is the combined radiative and convective heat transfer coefficient and T_db–${\overline{\text{T}}}_{\text{sk}}$ represents the temperature gradient between the ambient air and the skin. In this study, h_r+c was determined for each subject by using the formula

$$h_{r+c}=6.5\cdot {\left(\text{treadmill speed in m}\cdot {\text{s}}^{-1}\right)}^{0.39}+4.7,$$ (6)

where 6.5·(treadmill speed in m·s⁻¹)^0.39 is the convective coefficient for treadmill walking and 4.7 is the radiative coefficient for indoor environments.

Heat storage (S; W·m⁻²) was calculated as

$$S=\left(\Delta {\overline{\text{T}}}_{\text{b}}\cdot \Delta t^{-1}\right)\cdot \left(0.97\text{ W}\cdot \text{h}\cdot {\text{kg}}^{-1}\cdot °{\text{C}}^{-1}\right)\cdot ({\text{m}}_{\text{b}}\cdot {\text{A}}_{\text{D}}^{-1}),$$ (7)

where 0.97 W·h·kg⁻¹·°C⁻¹ is the specific heat of the body and Δ${\overline{\text{T}}}_{\text{b}}$ represents the change in mean body temperature measured over the time period (Δt in h) between 30 min and the time at which the critical T_es inflection point was observed. The equation for Δ${\overline{\text{T}}}_{\text{b}}$ (°C), which is a function of the change in T_es and ${\overline{\text{T}}}_{\text{sk}}$, was

$$\mathrm{\Delta }{\stackrel{-}{\mathrm{T}}}_{\mathrm{b}}={\left(0.9\cdot {\text{T}}_{\text{es}}+0.1\cdot {\stackrel{-}{\mathrm{T}}}_{\text{sk}}\right)}_{\text{critical point}}-{\left(0.9\cdot {\text{T}}_{\text{es}}+0.1 \cdot {\stackrel{-}{\mathrm{T}}}_{\text{sk}}\right)}_{\min \hspace{0.17em}30}.$$ (8)

Maximal evaporative capacity of the environment (E_max in W·m⁻²) was calculated as

$$E_{\text{max}}=K_e^{\text{′}}\cdot v^{0.6}\cdot ({\text{P}}_{\text{s},\text{sk}}-P_{\text{a}}),$$ (9)

where v was assumed to be 0.45 m/s based on past studies that used the same environmental chambers (10, 14). At each critical environmental condition, the evaporative cooling required to maintain thermal balance (E_req) equals E_max, i.e.,

$$M_{\text{net}}\pm \left(\text{R}+\text{C}\right)\pm \text{S}=E_{\text{max}}.$$ (10)

And the heat balance equation can be solved for K_e^′. This solution assumes a fully wetted skin surface, a requirement that, as expected, was met only in the P_crit tests.

Sweat rate was determined from the loss of nude body mass on a scale accurate to ±10 g. Fluid intake was prohibited between the initial and final measurements of nude body mass.

Determination of T_crit and P_crit

Figure 1 provides a representative tracing of the time course of gastrointestinal temperature (T_gi), dry-bulb temperature (T_db), and ambient water vapor pressure (P_a) for a MinAct trial with increasing T_db. After an initial rise, T_gi typically began to plateau after 30–40 min and remained at an elevated, relative steady state [a slow rise in T_gi is observed in some unacclimated subjects, constituting positive heat storage (10)] proportional to metabolic heat production, as T_db or P_a was systematically increased in a stepwise fashion as described previously. A clear T_gi inflection was observed in all cases except in one subject during a 38°C P_crit MinAct trial, for which data were excluded. The critical T_db or P_a was characterized by a subsequent upward inflection of T_gi from steady state, which was selected graphically from the raw data. A line was drawn between the data points, starting at the 30th min. A second line was drawn from the point of departure from the T_gi equilibrium phase slope. The average T_db or P_a for the 2 min immediately preceding the inflection point was defined as the critical T_db or P_a, respectively. Inflection points were determined by visual inspection, as previously reported (10, 11, 14). We have previously demonstrated excellent intrarater reliability for the determination of the T_c inflection point (ICC = 0.93) (11).

Figure 1.

Representative tracing of the time course of core temperature (gastrointestinal temperature, T_gi), dry-bulb temperature (T_db), and ambient water vapor pressure (P_a) for a MinAct trial with increasing T_db. Lines are drawn through data points in the bottom panel to demonstrate the stepwise progression of T_db. The T_gi inflection point represents the combination of environmental conditions above which heat stress becomes uncompensable and a stable core temperature can no longer be maintained. In this case, the T_gi inflection point (i.e., critical dry bulb temperature, T_crit) occurs at T_db = 46.1°C.

Psychrometric loci were plotted on a standardized psychrometric chart from the mean data for combinations of T_db and P_a (“see Fig. 2 in RESULTS”). To construct isothermal lines as a continuation of the curves plotted on a psychrometric chart from empirically derived data (“see Fig. 2 in RESULTS”), we calculated the slope of the line using ${\overline{\text{T}}}_{\text{sk}}$ and mean K_e^′·v^0.6 values determined in this study (10, 14) as

$$-\text{ψ}=h_{\text{r}+\text{c}}\cdot {\left(K_e^{\text{′}}\cdot v^{0.6}\right)}^{-1}.$$ (11)

Figure 2.

A standard psychrometric chart showing empirically derived mean critical environmental limits (symbols and solid lines) for light ambulatory activity (LightAmb; open circles) and minimal activity (MinAct; filled circles) trials. The larger dashed lines with arrows at the top left portion of the curves are isothermal lines from biophysical modeling of heat exchange, as described in methods. Smaller dashed lines denote the lower bounds of the 95% confidence interval for each condition. Critical environmental limits were significantly lower (i.e., shifted downward and to the left; P < 0.001) in LightAmb compared with MinAct across all environmental conditions tested.

Because the calculation of K_e′ is dependent upon fully wetted skin, slopes were calculated for 36°C and 38°C P_crit trials only. Isothermal lines were constructed using the average of the two slopes for each exercise intensity.

Statistical Analysis

An a priori power analysis using an effect size of 1.2, based on previously published P_crit data (13, 14), suggested that seven subjects would yield sufficient statistical power (power ≥ 0.8, α = 0.005) to detect significant differences in T_crit and P_crit between exercise intensities. Because each subject completed trials in multiple conditions, but not every condition, we opted to perform separate paired-samples t tests (SPSS, v. 9.4, SAS Institute, Inc., Cary, NC) to compare M_net, sweat rate, and V̇o₂ data between environmental conditions and exercise intensities. Similarly, differences in T_crit and P_crit due to exercise intensity were analyzed using paired-samples t tests. For metabolic heat production, sweat rates, and V̇o₂, to account for multiple comparisons within and between physical activity intensities among environmental conditions (30 comparisons), significance was accepted at α = 0.002. For critical environmental limits, to account for multiple comparisons between physical activity intensities (6 comparisons), significance was accepted at α = 0.008. Data are reported as means ± SD except in Fig. 2 which is presented with mean data and 95% confidence intervals (CI).

RESULTS

Subject Characteristics

Subject characteristics are presented in Table 1. Subjects were recruited to be representative of the population in this age group with respect to body size, adiposity, and aerobic fitness. There were no subject sample differences in age, height, weight, A_D, A_D·kg⁻¹, or V̇o_2max among trial conditions (all P ≥ 0.05).

Table 1.

Subject characteristics

Characteristic	Means ± SD	Range
Age, yr	24 ± 4	18–34
Height, m	1.72 ± 0.1	1.57–1.98
Weight, kg·m−2	71 ± 12	52–98
AD, m2	1.84 ± 0.20	1.50–2.31
AD·kg−1, m2·kg−1	0.026 ± 0.002	0.022–0.029
V̇o2max, mL·kg−1·min−1	49 ± 12	30–79

n = 25; 12 M/13 W. A_D, DuBois body surface area; A_D·kg⁻¹, body surface area-to-mass ratio; V̇o_2max, maximal oxygen consumption.

Metabolic Heat Production, Sweat Rate, and V̇o₂

The grand means (i.e., mean for all trials across environmental conditions) for M_net (82.9 ± 12.5 W·m⁻² vs. 133.3 ± 14.8 W·m⁻²), sweat rate (142.8 ± 80.2 g·m⁻²·h⁻¹ vs. 230.8 ± 84.9 g·m⁻²·h⁻¹), percent body mass loss (0.70 ± 0.42% vs. 1.04 ± 0.44%), and V̇o₂ (0.46 ± 0.10 L·min⁻¹ vs. 0.80 ± 0.16 L·min⁻¹) were lower for MinAct compared with LightAmb (all P < 0.0001). Likewise, METs (unitless) were lower in MinAct compared with LightAmb (1.81 ± 0.26 vs. 3.19 ± 0.30; P < 0.0001). Summary data for metabolic heat production, sweat rate, and V̇o₂ within each trial are presented in Table 2. There were no differences in M_net (P ≥ 0.16), sweat rate (P ≥ 0.05), percent body mass loss (P > 0.002), or V̇o₂ (P > 0.12) among environmental conditions for either MinAct or LightAmb intensities. M_net (all P < 0.0001) and V̇o₂ (P ≤ 0.002) were lower during MinAct trials compared with LightAmb trials. Sweat rate was significantly lower in MinAct compared with LightAmb trials in 36°C and 20 mmHg conditions (P ≤ 0.001). However, sweat rates were marginally, but not significantly, different between MinAct and LightAmb within all other environmental conditions (P ≥ 0.02). Percent body mass loss was different between MinAct and LightAmb only in 36°C and 12 mmHg conditions (P ≤ 0.006).

Table 2.

Sex distribution, metabolic heat production, sweat rates, and V̇o₂ for each experimental condition (means ± SD)

	36°C	38°C	40°C	20 mmHg	16 mmHg	12 mmHg
Sex
MinAct	4 M / 5 W	5 M / 3 W	4 M / 5 W	6 M / 3 W	4 M / 5 W	4 M / 5 W
LightAmb	4 M / 5 W	5 M / 4 W	4 M / 5 W	6 M / 3 W	4 M / 5 W	4 M / 5 W
Mnet, W·m−2
MinAct	77.9 ± 15.7	82.6 ± 17.1	80.4 ± 8.5	81.5 ± 11.4	87.7 ± 10.7	87.4 ± 12.3
LightAmb	128.5 ± 17.5*	136.0 ± 15.8*	133.5 ± 13.2*	130.3 ± 10.3*	134.4 ± 14.5*	137.3 ± 18.7*
SR, g·m−2·h−1
MinAct	117.1 ± 84.5	179.7 ± 105.4	147.5 ± 70.4	103.9 ± 41.2	140.9 ± 62.2	171.8 ± 98.2
LightAmb	211.9 ± 68.6*	273.6 ± 107.3	262.6 ± 87.4	187.4 ± 37.9*	205.7 ± 74.3	243.3 ± 101.7
V̇o2, L·min−1
MinAct	0.41 ± 0.11	0.47 ± 0.11	0.43 ± 0.07	0.46 ± 0.10	0.49 ± 0.09	0.47 ± 0.11
LightAmb	0.73 ± 0.15*	0.80 ± 0.17*	0.80 ± 0.16*	0.82 ± 0.15*	0.80 ± 0.14*	0.79 ± 0.18*
BML, %
MinAct	0.55 ± 0.44	0.81 ± 0.52	0.80 ± 0.42	0.50 ± 0.19	0.66 ± 0.30	0.86 ± 0.53
LightAmb	0.98 ± 0.45*	1.33 ± 0.48	1.22 ± 0.40	0.71 ± 0.15	0.93 ± 0.41	1.09 ± 0.45*

BML, body mass loss; LightAmb, light ambulatory activity; M, men; m_net, metabolic heat production; MinAct, minimal activity; SR, sweat rate; W, women. * P < 0.002 compared with MinAct.

Critical Environmental Limits

Figure 2 depicts critical environmental loci plotted on a standard psychrometric chart with lower bounds of the 95% CI. Heat stress is compensable in environmental conditions that are below and to the left of each line. In every environmental condition, psychrometric limits were shifted downward and leftward for LightAmb compared with MinAct trials (all P < 0.001). Summary data for T_db, P_a, and relative humidity (RH) are presented in Table 3. During P_crit trials, RH at the T_c inflection point was higher during MinAct compared with LightAmb (P ≤ 0.002). Conversely, during T_crit trials, RH at the inflection point was lower during MinAct compared with LightAmb (P ≤ 0.005). Lower RH in MinAct compared with LightAmb during T_crit trials was a function of higher T_db at a given P_a.

Table 3.

Environmental conditions at the core temperature inflection point for each experimental condition (means ± SD)

	36°C	38°C	40°C	20 mmHg	16 mmHg	12 mmHg
Tdb, °C
MinAct	36.0 ± 0.2	37.9 ± 0.3	40.0 ± 0.2	43.8 ± 2.0	47.3 ± 1.6	50.6 ± 2.0
LightAmb	35.9 ± 0.1	38.0 ± 0.3	40.1 ± 0.4	38.9 ± 1.0*	43.0 ± 1.5*	44.5 ± 2.4*
Pa, mmHg
MinAct	29.6 ± 2.2	29.8 ± 2.3	27.7 ± 2.4	19.7 ± 0.7	16.3 ± 0.4	12.0 ± 0.4
LightAmb	24.6 ± 1.7*	22.6 ± 1.0*	20.7 ± 1.8*	20.0 ± 0.4	16.1 ± 0.2	12.1 ± 0.5
RH, %
MinAct	66.4 ± 5.4	60.5 ± 5.1	50.2 ± 4.3	29.2 ± 2.8	20.3 ± 1.5	12.7 ± 1.5
LightAmb	55.5 ± 3.9*	45.5 ± 2.7*	37.3 ± 3.3*	38.4 ± 1.8*	24.9 ± 2.0*	18.6 ± 3.3*

LightAmb, light ambulatory activity; MinAct, minimal activity; p_a, water vapor pressure; RH, relative humidity; T_db, dry-bulb temperature. *P < 0.005 compared with MinAct.

DISCUSSION

The PSU HEAT Study is an ongoing project designed to determine critical environmental limits beyond which thermal balance with the environment is not possible. Although the overarching goal of PSU HEAT is to determine such untenable environments for aged and other vulnerable populations, the purpose of this study was to establish critical environmental limits for the maintenance of heat balance in young, healthy adults during very low-intensity physical activity that approximates the metabolic demand of activities of daily living or leisurely walking. As expected, our findings demonstrated that critical environmental limits are shifted toward lower combinations of temperature and humidity as M_net is increased. The lower bounds of the 95% confidence intervals theoretically provide upper limits below which most young, healthy adults can maintain a steady state, albeit elevated, core temperature at these low metabolic rates. The data from this study may be used to develop evidence-based alert communications, policy decisions, triage for impending heat events, and implementation of other safety interventions during extreme heat events for healthy, young adults.

Progressive heat stress protocols have been used extensively to determine safe upper limits of heat and humidity for industry work in various clothing ensembles (9, 24–27). Only one study has established psychrometric limits for young, healthy adults wearing clothing similar to that of the present study (10), which was meant to more closely simulate the clothing that would likely be worn in the heat during activities of daily living. In that study, however, subjects walked at an intensity equal to 30% of V̇o_2max because that intensity reflects the intensity associated with an 8-h work day in industry settings, as well as many self-paced activities in young, healthy adults. For the current study, we included mild physical activity at metabolic rates that approximate those of light activities of daily living such as gardening or leisurely walking. Indeed, the metabolic cost of the LightAmb (∼0.8 L/min; ∼3.2 METs) and MinAct (∼0.45 L/min; ∼1.8 METs) trials in this study closely resembled the metabolic costs of self-selected walking speed and various household tasks (e.g., watering or fertilizing the lawn), respectively, in young and older adults (17, 18). As such, these findings provide the most relevant data to date regarding safe upper limits for heat stress exposure in free-living healthy, young adults.

When the critical limits for heat balance are plotted on a psychrometric chart, the curvilinear relation between water vapor pressure and dry-bulb temperature is explained by the transition from fully wetted skin at the upper left portion of the curve to free evaporation at the lower right portion of the curve. The slope is constrained in the upper left portion of the curve because a relatively small water vapor pressure gradient between the skin and the environment limits the maximal capacity for evaporative cooling. In hotter, drier ambient environments (i.e., the lower right aspect of the curve), the limit to heat balance is defined by maximal sweating capacity, resulting in a more vertical slope, particularly at higher metabolic rates. As demonstrated by Fig. 2, the slope of the line in hot, dry ambient conditions becomes steeper during LightAmb compared with MinAct trials. The wider and more linear nature of that portion of the curve in MinAct trials can be explained by significantly lower metabolic heat production, and therefore a lower requirement for evaporative heat loss, but only marginally different sweating rates with free evaporation. A similar widening of the curve at lower ambient water vapor pressures has been demonstrated in heat acclimated compared with unacclimated young women working at similar metabolic rates (14), explained by increased sweating rates in the acclimated women.

Potential Limitations

No attempt was made in this study to account for heat acclimatization. However, subjects were tested throughout the year, with enough participants being tested during each season to eliminate the potential for acclimatization status to influence differences between experimental conditions. Future research will examine the impact of seasonality/heat acclimatization on critical environmental limits in a larger cohort of young men and women.

We likewise did not attempt to control for menstrual cycle or contraceptive use in female participants. Although absolute T_c varies across the menstrual cycle, the change in T_c during exercise in the heat is unaffected (28). Similarly, T_c profiles during exercise in the heat are similar across menstrual phases (11). Thus, it is unlikely that the observed critical environmental limits were influenced by not controlling for menstrual cycle or contraceptive use.

Finally, this study was not powered to assess potential sex differences in critical environmental limits. However, a long-term goal of the PSU HEAT project is to test enough participants to determine whether sex differences exist.

Perspectives and Significance

The present investigation was focused solely on establishing critical environmental limits in young, healthy adults during physical activity at two low metabolic rates. Age-related impairments in thermoregulatory function (29, 30), as well as increased morbidity and mortality in older adults during extreme heat events (29, 31, 32), are well-established. However, there has been minimal investigation into the specific environmental conditions above which older adults are at increased risk heat-related illness. Only one study has demonstrated critical environmental limits in older (62–80 yr) unacclimated women during 30% V̇o_2max exercise (14). There has yet to be investigation of those psychrometric limits in older men and women during physical activity that approximates the metabolic demand of light activities of daily living. The data presented herein provide a point of comparison against which future research will answer the question: in what combinations of environmental conditions do age differences in thermoregulatory function result in greater heat loads in older adults, thus placing them at increased risk of heat-related morbidity and mortality?

GRANTS

This work was supported by National Institutes of Health (NIH) Grant R01 AG067471 (to W.L.K.) and NIA Grant T32 AG049676 (to D.J.V.).

DISCLOSURES

No conflicts of interest, financial or otherwise, are declared by the authors.

AUTHOR CONTRIBUTIONS

S.T.W. and W.L.K. conceived and designed research; S.T.W., R.M.C., and D.J.V. performed experiments; S.T.W. and R.M.C. analyzed data; S.T.W., R.M.C., and W.L.K. interpreted results of experiments; S.T.W. prepared figures; S.T.W. drafted manuscript; S.T.W., R.M.C., D.J.V., and W.L.K. edited and revised manuscript; S.T.W., R.M.C., D.J.V., and W.L.K. approved final version of manuscript.