ACSM Expert Consensus Statement on Exertional Heat Illness: Recognition, Management, and Return to Activity.

ABSTRACT: Exertional heat stroke is a true medical emergency with potential for organ injury and death. This consensus statement emphasizes that optimal exertional heat illness management is promoted by a synchronized chain of survival that promotes rapid recognition and management, as well as communication between care teams. Health care providers should be confident in the definitions, etiologies, and nuances of exertional heat exhaustion, exertional heat injury, and exertional heat stroke. Identifying the athlete with suspected exertional heat stroke early in the course, stopping activity (body heat generation), and providing rapid total body cooling are essential for survival, and like any critical life-threatening situation (cardiac arrest, brain stroke, sepsis), time is tissue. Recovery from exertional heat stroke is variable and outcomes are likely related to the duration of severe hyperthermia. Most exertional heat illnesses can be prevented with the recognition and modification of well-described risk factors ideally addressed through leadership, policy, and on-site health care.

Exertional heat stroke: nutritional considerations.

NEW FINDINGS: What is the topic of this review? The potential role of nutrition in exertional heat stroke. What advances does it highlight? Certain nutritional and dietary strategies used by athletes and workers may exert a protective effect the pathophysiological processes of exertional heat stroke, whereas others may be detrimental. While current evidence suggests that some of these practices may be leveraged as a potential countermeasure to exertional heat stroke, further research on injury-related outcomes in humans is required. ABSTRACT: Exertional heat stroke (EHS) is a life-threatening illness and an enduring problem among athletes, military servicemen and -women, and occupational labourers who regularly perform strenuous activity, often under hot and humid conditions or when wearing personal protective equipment. Risk factors for EHS and mitigation strategies have generally focused on the environment, health status, clothing, heat acclimatization and aerobic conditioning, but the potential role of nutrition is largely underexplored. Various nutritional and dietary strategies have shown beneficial effects on exercise performance and health and are widely used by athletes and other physically active populations. There is also evidence that some of these practices may dampen the pathophysiological features of EHS, suggesting possible protection or abatement of injury severity. Promising candidates include carbohydrate ingestion, appropriate fluid intake and glutamine supplementation. Conversely, some nutritional factors and low energy availability may facilitate the development of EHS, and individuals should be cognizant of these. Therefore, the aims of this review are to present an overview of EHS along with its mechanisms and pathophysiology, discuss how selected nutritional considerations may influence EHS risk focusing on their impact on the key pathophysiological processes of EHS, and provide recommendations for future research. With climate change expected to increase EHS risk and incidence in the coming years, further investigation on how diet and nutrition may be optimized to protect against EHS would be highly beneficial.

Wearable Sensors and Machine Learning for Hypovolemia Problems in Occupational, Military and Sports Medicine: Physiological Basis, Hardware and Algorithms.

Hypovolemia is a physiological state of reduced blood volume that can exist as either (1) absolute hypovolemia because of a lower circulating blood (plasma) volume for a given vascular space (dehydration, hemorrhage) or (2) relative hypovolemia resulting from an expanded vascular space (vasodilation) for a given circulating blood volume (e.g., heat stress, hypoxia, sepsis). This paper examines the physiology of hypovolemia and its association with health and performance problems common to occupational, military and sports medicine. We discuss the maturation of individual-specific compensatory reserve or decompensation measures for future wearable sensor systems to effectively manage these hypovolemia problems. The paper then presents areas of future work to allow such technologies to translate from lab settings to use as decision aids for managing hypovolemia. We envision a future that incorporates elements of the compensatory reserve measure with advances in sensing technology and multiple modalities of cardiovascular sensing, additional contextual measures, and advanced noise reduction algorithms into a fully wearable system, creating a robust and physiologically sound approach to manage physical work, fatigue, safety and health issues associated with hypovolemia for workers, warfighters and athletes in austere conditions.

ACSM Expert Consensus Statement on Exertional Heat Illness: Recognition, Management, and Return to Activity.

ABSTRACT: Exertional heat stroke (EHS) is a true medical emergency with potential for organ injury and death. This consensus statement emphasizes that optimal exertional heat illness management is promoted by a synchronized chain of survival that promotes rapid recognition and management, as well as communication between care teams. Health care providers should be confident in the definitions, etiologies, and nuances of exertional heat exhaustion, exertional heat injury, and EHS. Identifying the athlete with suspected EHS early in the course, stopping activity (body heat generation), and providing rapid total body cooling are essential for survival, and like any critical life-threatening situation (cardiac arrest, brain stroke, sepsis), time is tissue. Recovery from EHS is variable, and outcomes are likely related to the duration of severe hyperthermia. Most exertional heat illnesses can be prevented with the recognition and modification of well-described risk factors ideally addressed through leadership, policy, and on-site health care.

Wearable Sensors Incorporating Compensatory Reserve Measurement for Advancing Physiological Monitoring in Critically Injured Trauma Patients.

Vital signs historically served as the primary method to triage patients and resources for trauma and emergency care, but have failed to provide clinically-meaningful predictive information about patient clinical status. In this review, a framework is presented that focuses on potential wearable sensor technologies that can harness necessary electronic physiological signal integration with a current state-of-the-art predictive machine-learning algorithm that provides early clinical assessment of hypovolemia status to impact patient outcome. The ability to study the physiology of hemorrhage using a human model of progressive central hypovolemia led to the development of a novel machine-learning algorithm known as the compensatory reserve measurement (CRM). Greater sensitivity, specificity, and diagnostic accuracy to detect hemorrhage and onset of decompensated shock has been demonstrated by the CRM when compared to all standard vital signs and hemodynamic variables. The development of CRM revealed that continuous measurements of changes in arterial waveform features represented the most integrated signal of physiological compensation for conditions of reduced systemic oxygen delivery. In this review, detailed analysis of sensor technologies that include photoplethysmography, tonometry, ultrasound-based blood pressure, and cardiogenic vibration are identified as potential candidates for harnessing arterial waveform analog features required for real-time calculation of CRM. The integration of wearable sensors with the CRM algorithm provides a potentially powerful medical monitoring advancement to save civilian and military lives in emergency medical settings.

Quantitative model of hematologic and plasma volume responses after ascent and acclimation to moderate to high altitudes.

Despite decades of research, the magnitude and time course of hematologic and plasma volume (PV) changes following rapid ascent and acclimation to various altitudes are not precisely described. To develop a quantitative model, we utilized a comprehensive database and general linear mixed models to analyze 1,055 hemoglobin ([Hb]) and hematocrit (Hct) measurements collected at sea level and repeated time points at various altitudes in 393 unacclimatized men (n = 270) and women (n = 123) who spent between 2 h and 7 days at 2,500-4,500 m under well-controlled and standardized experimental conditions. The PV change (ΔPV) was calculated from [Hb] and Hct measurements during a time period when erythrocyte volume is stable. The results are 1) ΔPV decreases rapidly (~6%) after the 1st day at 2,500 m and [Hb] and Hct values increase by 0.5 g/dl and 1.5 points, respectively; 2) ΔPV decreases an additional 1%, and [Hb] and Hct increase an additional 0.1 g/dl and 0.2 points every 500-m increase in elevation above 2,500 m after the 1st day; 3) ΔPV continues to decrease over time at altitude, but the magnitude of this decrease and subsequent increase in [Hb] and Hct levels is dependent on elevation and sex; and 4) individuals with high initial levels of [Hb] and Hct and older individuals hemoconcentrate less at higher elevations. This study provides the first quantitative delineation of ΔPV and hematological responses during the first week of exposure over a wide range of altitudes and demonstrates that absolute altitude and time at altitude, as well as initial hematologic status, sex, and age impact the response.

Assessment of extracellular dehydration using saliva osmolality.

INTRODUCTION: When substantial solute losses accompany body water an isotonic hypovolemia (extracellular dehydration) results. The potential for using blood or urine to assess extracellular dehydration is generally poor, but saliva is not a simple ultra-filtrate of plasma and the autonomic regulation of salivary gland function suggests the possibility that saliva osmolality (Sosm) may afford detection of extracellular dehydration via the influence of volume-mediated factors. PURPOSE: This study aimed to evaluate the assessment of extracellular dehydration using Sosm. In addition, two common saliva collection methods and their effects on Sosm were compared. METHODS: Blood, urine, and saliva samples were collected in 24 healthy volunteers during paired euhydration and dehydration trials. Furosemide administration and 12 h fluid restriction were used to produce extracellular dehydration. Expectoration and salivette collection methods were compared in a separate group of eight euhydrated volunteers. All comparisons were made using paired t-tests. The diagnostic potential of body fluids was additionally evaluated. RESULTS: Dehydration (3.1 ± 0.5% loss of body mass) decreased PV (-0.49 ± 0.12 L; -15.12 ± 3.94% change), but Sosm changes were marginal (<10 mmol/kg) and weakly correlated with changes in absolute or relative PV losses. Overall diagnostic accuracy was poor (AUC = 0.77-0.78) for all body fluids evaluated. Strong agreement was observed between Sosm methods (Expectoration: 61 ± 10 mmol/kg, Salivette: 61 ± 8 mmol/kg, p > 0.05). CONCLUSIONS: Extracelluar dehydration was not detectable using plasma, urine, or saliva measures. Salivette and expectoration sampling methods produced similar, consistent results for Sosm, suggesting no methodological influence on Sosm.

Whole body sweat rate prediction: indoor treadmill and cycle ergometer exercise.

This article describes the development and validation of accurate whole body sweat rate prediction equations for individuals performing indoor cycle ergometer and treadmill exercise, where power output can be measured or derived from simple inputs. For cycle ergometry, 112 trials (67 participants) were used for model development and another 56 trials (42 participants) for model validation. For treadmill exercise, 171 trials (67 participants) were used for model development and another 95 trials (63 participants) for model validation. Trials were conducted over a range of dry-bulb temperature (20°C to 40°C), relative humidity (14% to 60%), and exercise intensity (∼40% to 85% of peak aerobic power) conditions, which were matched between model development and model validation. Whole body sweat rates were measured, and proprietary prediction models were developed (accounting for all relevant biophysical factors) and then validated. For model validation, mean absolute error for predicted sweating rate was 0.01 and 0.02 L·h-1 for cycle and treadmill trials, respectively. The 95% confidence intervals were modest for cycle ergometer (+0.25 and -0.22 L·h-1) and treadmill exercise (+0.33 and -0.29 L·h-1). The accounted for variance between predicted and measured values was 92% and 78% for cycle and treadmill exercise, respectively. Bland-Altman analysis indicated that zero and one predicted value exceeded the a priori acceptable level of agreement (equivalent to ±2% of total body mass in 3 h) for cycle and treadmill exercise, respectively. There were fewer trials with female subjects, but their values did not differ from those expected for males. This is the foremost study to develop and validate whole body sweat rate prediction equations for indoor treadmill and cycle ergometer exercise of moderate to high intensity. These prediction equations are publicly available for use (https://sweatratecalculator.com).NEW & NOTEWORTHY This study presents the development of new proprietary whole body sweat rate prediction models for people exercising indoors on a cycle ergometer or treadmill using simple input parameters and delivered through a publicly available online calculator: https://sweatratecalculator.com. In an independent validation group, the predictive models for both indoor cycling and treadmill exercise were accurate across moderate to high exercise intensities in temperate to hot conditions. These equations will enable individualized hydration management during physical training and exercise physiology experiments.

Whole body sweat rate prediction: outdoor running and cycling exercise.

Our aim was to develop and validate separate whole body sweat rate prediction equations for moderate to high-intensity outdoor cycling and running, using simple measured or estimated activity and environmental inputs. Across two collection sites in Australia, 182 outdoor running trials and 158 outdoor cycling trials were completed at a wet-bulb globe temperature ranging from ∼15°C to ∼29°C, with ∼60-min whole body sweat rates measured in each trial. Data were randomly separated into model development (running: 120; cycling: 100 trials) and validation groups (running: 62; cycling: 58 trials), enabling proprietary prediction models to be developed and then validated. Running and cycling models were also developed and tested when locally measured environmental conditions were substituted with participants' subjective ratings for black globe temperature, wind speed, and humidity. The mean absolute error for predicted sweating rate was 0.03 and 0.02 L·h-1 for running and cycling models, respectively. The 95% confidence intervals for running (+0.44 and -0.38 L·h-1) and cycling (+0.45 and -0.42 L·h-1) were within acceptable limits for an equivalent change in total body mass over 3 h of ±2%. The individual variance in observed sweating described by the predictive models was 77% and 60% for running and cycling, respectively. Substituting measured environmental variables with subjective assessments of climatic characteristics reduced the variation in observed sweating described by the running model by up to ∼25%, but only by ∼2% for the cycling model. These prediction models are publicly accessible (https://sweatratecalculator.com) and can guide individualized hydration management in advance of outdoor running and cycling.NEW & NOTEWORTHY We report the development and validation of new proprietary whole body sweat rate prediction models for outdoor running and outdoor cycling using simple activity and environmental inputs. Separate sweat rate models were also developed and tested for situations where all four environmental parameters are not available, and some must be subsequently estimated by the user via a simple rating scale. All models are freely accessible through an online calculator: https://sweatratecalculator.com. These models, via the online calculator, will enable individualized hydration management for training or recreational cycling or running in an outdoor environment.

Early Prediction of Impending Exertional Heat Stroke With Wearable Multimodal Sensing and Anomaly Detection.

We employed wearable multimodal sensing (heart rate and triaxial accelerometry) with machine learning to enable early prediction of impending exertional heat stroke (EHS). US Army Rangers and Combat Engineers (N = 2,102) were instrumented while participating in rigorous 7-mile and 12-mile loaded rucksack timed marches. There were three EHS cases, and data from 478 Rangers were analyzed for model building and controls. The data-driven machine learning approach incorporated estimates of physiological strain (heart rate) and physical stress (estimated metabolic rate) trajectories, followed by reconstruction to obtain compressed representations which then fed into anomaly detection for EHS prediction. Impending EHS was predicted from 33 to 69 min before collapse. These findings demonstrate that low dimensional physiological stress to strain patterns with machine learning anomaly detection enables early prediction of impending EHS which will allow interventions that minimize or avoid pathophysiological sequelae. We describe how our approach can be expanded to other physical activities and enhanced with novel sensors.

Biological and analytical variation of the human sweating response: implications for study design and analysis.

Appropriate quantification of analytical and biological variation of thermoregulatory sweating has important practical utility for research design and statistical analysis. We sought to examine contributors to variability in local forearm sweating rate (SR) and sweating onset (SO) and to evaluate the potential for using bilateral measurements. Two women and eight men (26 ± 9 yr; 79 ± 12 kg) completed 5 days of heat acclimation and walked (1.8 l/min VO(2)) on three occasions for 30 min in 40°C, 20% RH, while local SR and SO were measured. Local SR measures among days were not different (2.14 ± 0.72 vs. 2.02 ± 0.79 vs. 2.31 ± 0.72 mg·cm(2)·min(-1), P = 0.19) nor was SO (10.47 ± 2.54 vs. 10.04 ± 2.97 vs. 9.87 ± 3.44 min P = 0.82). Bilateral SR (2.14 ± 0.72 vs. 2.16 ± 0.71 mg·cm(2)·min(-1), P = 0.56) and SO (10.47 ± 2.54 vs. 10.83 ± 2.48 min, P = 0.09) were similar and differences were ≤ 1 SD of day-to-day differences for a single forearm. Analytical imprecision (CV(a)), within (CV(i))-, and between (CV(g))-subjects' coefficient of variation for local SR were 2.4%, 22.3%, and 56.4%, respectively, and were 0%, 9.6%, and 41%, respectively, for SO. We conclude: 1) technologically, sweat capsules contribute negligibly to sweat measurement variation; 2) bilateral measures of SR and SO appear interchangeable; 3) when studying potential factors affecting sweating, changes in SO afford a more favorable signal-to-noise ratio vs. changes in SR. These findings provide a quantitative basis for study design and optimization of power/sample size analysis in the evaluation of thermoregulatory sweating.

High skin temperature and hypohydration impair aerobic performance.

This paper reviews the roles of hot skin (>35°C) and body water deficits (>2% body mass; hypohydration) in impairing submaximal aerobic performance. Hot skin is associated with high skin blood flow requirements and hypohydration is associated with reduced cardiac filling, both of which act to reduce aerobic reserve. In euhydrated subjects, hot skin alone (with a modest core temperature elevation) impairs submaximal aerobic performance. Conversely, aerobic performance is sustained with core temperatures >40°C if skin temperatures are cool-warm when euhydrated. No study has demonstrated that high core temperature (∼40°C) alone, without coexisting hot skin, will impair aerobic performance. In hypohydrated subjects, aerobic performance begins to be impaired when skin temperatures exceed 27°C, and even warmer skin exacerbates the aerobic performance impairment (-1.5% for each 1°C skin temperature). We conclude that hot skin (high skin blood flow requirements from narrow skin temperature to core temperature gradients), not high core temperature, is the 'primary' factor impairing aerobic exercise performance when euhydrated and that hypohydration exacerbates this effect.

Hydration assessment using the cardiovascular response to standing.

The cardiovascular response to standing (sit-to-stand change in heart rate; SSΔHR) is commonly employed as a screening tool to detect hypohydration (body water deficit). No study has systematically evaluated SSΔHR cut points using different magnitudes or different types of controlled hypohydration. The objective of this study was to determine the diagnostic accuracy of the often proposed 20 b/min SSΔHR cut point using both hypertonic and isotonic models of hypohydration. Thirteen healthy young adults (8M, 5F) underwent three bouts of controlled hypohydration. The first bout used sweating to elicit large losses of body water (mass) (>3 % sweat). The second two bouts were matched to elicit 3 % body mass losses (3 % diuretic; 3 % sweat). A euhydration control trial (EUH) was paired with each hypohydration trial for a total of six trials. Heart rate was assessed after 3-min sitting and after 1-min standing during all trials. SSΔHR was compared among trials, and receiver operator characteristic curve analysis was used to determine diagnostic accuracy of the 20 b/min SSΔHR cut point. Volunteers lost 4.5 ± 1.1, 3.0 ± 0.6, and 3.2 ± 0.6 % body mass during >3 % sweat, 3 % diuretic, and 3 % sweat trials, respectively. SSΔHR (b/min) was 9 ± 8 (EUH), 20 ± 12 (>3 % sweat; P < 0.05 vs. EUH), 17 ± 7 (3 % diuretic; P < 0.05 vs. EUH), and 13 ± 11 (3 % sweat). The 20 beats/min cut point had high specificity (90 %) but low sensitivity (44 %) and overall diagnostic accuracy of 67 %. SSΔHR increased significantly in response to severe hypertonic hypohydration and moderate isotonic hypohydration, but not moderate hypertonic hypohydration. However, the 20 beats/min cut point afforded only marginal diagnostic accuracy.

Indicators to assess physiological heat strain - Part 1: Systematic review.

In a series of three companion papers published in this Journal, we identify and validate the available thermal stress indicators (TSIs). In this first paper of the series, we conducted a systematic review (registration: INPLASY202090088) to identify all TSIs and provide reliable information regarding their use (funded by EU Horizon 2020; HEAT-SHIELD). Eight databases (PubMed, Agricultural and Environmental Science Collection, Web of Science, Scopus, Embase, Russian Science Citation Index, MEDLINE, and Google Scholar) were searched from database inception to 15 April 2020. No restrictions on language or study design were applied. Of the 879 publications identified, 232 records were considered for further analysis. This search identified 340 instruments and indicators developed between 200 BC and 2019 AD. Of these, 153 are nomograms, instruments, and/or require detailed non-meteorological information, while 187 can be mathematically calculated utilizing only meteorological data. Of these meteorology-based TSIs, 127 were developed for people who are physically active, and 61 of those are eligible for use in occupational settings. Information regarding the equation, operating range, interpretation categories, required input data, as well as a free software to calculate all 187 meteorology-based TSIs is provided. The information presented in this systematic review should be adopted by those interested in performing on-site monitoring and/or big data analytics for climate services to ensure appropriate use of the meteorology-based TSIs. Studies two and three in this series of companion papers present guidance on the application and validation of these TSIs, to guide end users of these indicators for more effective use.

Indicators to assess physiological heat strain - Part 2: Delphi exercise.

In a series of three companion papers published in this Journal, we identify and validate the available thermal stress indicators (TSIs). In this second paper of the series, we identified the criteria to consider when adopting a TSI to protect individuals who work in the heat, and we weighed their relative importance using a Delphi exercise with 20 experts. Two Delphi iterations were adequate to reach consensus within the expert panel (Cronbach's α = 0.86) for a set of 17 criteria with varying weights that should be considered when adopting a TSI to protect individuals who work in the heat. These criteria considered physiological parameters such as core/skin/mean body temperature, heart rate, and hydration status, as well as practicality, cost effectiveness, and health guidance issues. The 17 criteria were distributed across three occupational health-and-safety pillars: (i) contribution to improving occupational health (55% of total importance), (ii) mitigation of worker physiological strain (35.5% of total importance), and (iii) cost-effectiveness (9.5% of total importance). Three criteria [(i) relationship of a TSI with core temperature, (ii) having categories indicating the level of heat stress experienced by workers, and (iii) using its heat stress categories to provide recommendations for occupational safety and health] were considered significantly more important when selecting a TSI for protecting individuals who work in the heat, accumulating 37.2 percentage points. These 17 criteria allow the validation and comparison of TSIs that presently exist as well as those that may be developed in the coming years.

Reference change values for monitoring dehydration.

BACKGROUND: Dehydration is a common medical problem requiring heuristic evaluation. Our aim was to develop a quantitative and graphical tool based on serial changes in either plasma osmolality (P(osm)), urine specific gravity (U(sg)), or body mass (B(m)) to aid in determining the probability that a person has become dehydrated. A secondary purpose was to validate use of the tool by dehydrating a group of volunteers. METHODS: Basic data were obtained from a recent study of biological variation in common hydration status markers. Four reference change values (RCV) were calculated for each variable (P(osm), U(sg), B(m)) using four statistical probabilities (0.80, 0.90, 0.95, and 0.99). The probability derived from the Z-score for any given change can be calculated from: Z=change/[2(1/2)(CV(a)(2)+CV(i)(2))(1/2)]. This calculation was simplified to require one input (measured change) by plotting the RCV against probability to generate both an empirical equation and a dual quantitative-qualitative graphic. RESULTS: Eleven volunteers were dehydrated by moderate levels (-2.1% to -3.5% B(m)). Actual probabilities were obtained by substituting measured changes in P(osm), U(sg), and B(m) for X in the exponential equation, Y=1-e(-K·X), where each variable has a unique K constant. Median probabilities were 0.98 (P(osm)), 0.97 (U(sg)), and 0.97 (B(m)), which aligned with 'very likely' to 'virtually certain' qualitative probability categories for dehydration. CONCLUSIONS: This investigation provides a simple quantitative and graphical tool that can aid in determining the probability that a person has become dehydrated when serial measures of P(osm), U(sg), or B(m) are made.

Thermal face protection delays finger cooling and improves thermal comfort during cold air exposure.

When people dress for cold weather, the face often remains exposed. Facial cooling can decrease finger blood flow, reducing finger temperature (T (f)). This study examined whether thermal face protection limits finger cooling and thereby improves thermal comfort and manual dexterity during prolonged cold exposure. T (f) was measured in ten volunteers dressed in cold-weather clothing as they stood for 60 min facing the wind (-15°C, 3 m s(-1)), once while wearing a balaclava and goggles (BAL), and once with the balaclava pulled down and without goggles (CON). Subjects removed mitts, wearing only thin gloves to perform Purdue Pegboard (PP) tests at 15 and 50 min, and Minnesota Rate of Manipulation (MRM) tests at 30 and 55 min. Subjects rated their thermal sensation and comfort just before the dexterity tests. T (f) decreased (p < 0.05 for time × trial interaction) by 15 min of cold exposure during CON (33.6 ± 1.4-28.7 ± 2.0°C), but not during BAL (33.2 ± 1.4-30.6 ± 3.2°C); and after 30 min T (f) remained warmer during BAL (23.3 ± 5.9°C) than CON (19.2 ± 3.5); however, by 50 min, T (f) was no different between trials (14.1 ± 2.7°C). Performance on PP fell (p < 0.05) by 25% after 50 min in both trials; MRM performance was not altered by cold on either trial. Subjects felt colder (p < 0.05) and more uncomfortable (p < 0.05) during CON, compared to BAL. Thermal face protection was effective for maintaining warmer T (f) and thermal comfort during cold exposure; however, local cooling of the hands during manual dexterity tests reduced this physiological advantage, and performance was not improved.

DEET insect repellent: effects on thermoregulatory sweating and physiological strain.

Insect repellents (e.g. N,N-diethyl-m-toluamide or DEET) applied to the skin can potentially interfere with sweat production and evaporation, thus increasing physiological strain during exercise-heat stress. The purpose was to determine the impact of 33% DEET lotion on sweating responses, whole body thermoregulation and thermal sensation during walking exercise in the heat. Nine volunteers (2 females, 7 males; 22.1 ± 4.9 years; 176.4 ± 10.0 cm; 79.9 ± 12.9 kg) completed 5 days of heat acclimation (45°C, 20% rh; 545 watts; 100 min/day) and performed three trials: control (CON); DEET applied to forearm (DEET(LOC), 12 cm(2)); and DEET applied to ~13% body surface area (DEET(WB),). Trials consisted of 30 min walking (645 watts) in 40°C, 20% rh environment. Local sweat rate (SR), onset and skin wettedness were measured in DEET(LOC), and heart rate (HR), rectal temperature (T (re)), skin temperature (T (sk)), RPE, and thermal sensations (TS) were measured during DEET(WB). No differences (p > 0.05) were observed between DEET(LOC) versus CON, respectively, for steady state SR (1.89 ± 0.44 vs. 2.09 ± 0.84 mg/cm(2)/min), SR area under the curve (46.9 ± 11.7 vs. 55.0 ± 20.8 mg/cm(2)), sweating onset, or skin wettedness. There were no differences (p > 0.05) in HR, T (re), T (sk), Physiological Strain Index, RPE or TS between DEET(WB) versus CON. DEET did not impact measures of local forearm sweating and when applied according to military doctrine, did not adversely impact physiological responses during exercise-heat stress. DEET can be safely worn during military, occupational and recreational activities in hot, insect infested environments.