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Women and exertional heat illness: identification of gender specific risk factors.

As women enter into previously closed military occupational specialties, (1) they are likely to be exposed more to challenging and extreme conditions. For example, exercise in extreme environments could increase their risk for exertional heat illness (EHI) (2) and exertional heat stroke (EHS), the most extreme type of EHI and a fatal threat to Warfighters, (3-6) athletes, (7-9) and others who engage in physically demanding jobs. (10) EHS occurs during physical exertion, typically in a hot and humid environment, and is characterized by a rise in core body temperature (usually 40[degrees]C or more), accompanied by central nervous system dysfunction (eg, delirium, convulsions, coma) and sometimes multiple organ system failure. (11) Although EHS continues to be a significant threat to Warfighters' health, force readiness, and operational resources, (3,5) in most cases it is preventable, given our understanding of predisposing risk factors and proper implementation of safeguards. (5,12-15) Key risk factors include dehydration, lack of acclimatization, recent illness, (16,17) certain classes of medication, (18) and prior EHS. (3,13,14,16,17,19) Additionally, poor aerobic power and high percentage of body fat, two of the strongest risk factors for EHI in the military, (20-22) may be of particular concern for women.

Since men in combat military training typically engage in more physically demanding activities under many environmental conditions than women, the prevalence of EHS is higher in men than women. (3,4,23,24) In 2013, 324 cases of EHS and 1,701 additional EHI were reported in the US armed forces, which represented a decline in EHI over the previous few years. (3) The incidence rate of EHS was higher among men (0.24 per 1,000 person-years) than women (0.15). However, for all other EHI, women had a higher rate (1.30) than men (1.19). Thus, when baseline rates are corrected for gender participation, women have a slightly higher incidence of EHI (not EHS) than men, both in the military (3,4,25) and in the general population. (23,24)

Although men and women thermoregulate internal temperature in a similar manner, key sex differences exist in how they respond to heat. (26,27) Most notably, women have a higher baseline core temperature, (28,29) especially during the luteal phase of the menstrual cycle. (30,31) Thus, women begin to sweat at a higher core temperature than men. (32) Women typically have a lower body surface area, but a higher body surface area-to-mass ratio than men, which may provide more efficient body heat dissipation in certain environments (eg, very humid weather). (33) Taken together, these differences may place women at a slight advantage in hot and humid climates, and a slight disadvantage in hot and dry climates, relative to men. (32,33) However, the net effect of these sex differences on EHI risk is generally considered to be negligible, especially in comparison to larger differences in aerobic power and anthropometrics, particularly percentage of body fat. (26,30,31)

One approach to assessing the capacity to thermoregulate is to expose individuals to a designated heat challenge during exercise, and the Israeli heat tolerance test (HTT) is one valuable tool for use in the laboratory. The HTT, designed over decades of iterative studies, is used as a clinical test to guide return to duty decisions for Warfighters in the Israeli Defense Force (IDF) who have suffered an EHS event. (5,34) Between 2008 and 2010, 26% of men and 67% of women in the IDF who had been diagnosed with EHS (or EHS was suspected) were classified as heat intolerant by their criteria, (35) which suggests sex differences.

Importantly, the HTT was originally developed using male Warfighters. Thus, if their HTT is to be used in our military, and particularly as women enter combat military occupational specialties, it will be necessary to know how they respond to the HTT, with and without a prior EHI. Additionally, the IDF did not have data on either aerobic power or body composition, (35) which could be key in assessing risk of EHI. (20-22,36) Thus, the purposes of the present study were to examine the responses of men and women to the HTT and to compare their classification results. Additionally, we assessed both aerobic power and body composition to help explain any sex differences observed with the HTT.



Fifty-five male and 20 female participants were recruited from military and university communities to participate in a standardized HTT. Inclusion criteria included: (1) aged 18 to 45 years; (2) waist circumference less than 39.4 inches (100 cm); (3) systolic and diastolic blood pressure below 140 mmHg and 90 mmHg, respectively; (4) no previous history of malignant hyperthermia; (5) not pregnant or lactating; (6) not anemic; (7) not using glucose-lowering agents, prednisone, or beta blockers; and (9) not presently being treated for any mental health disorder. Participants included those with and without a history of EHI. Participants who had a previous clinically documented EHS (n=20, of which 19 were male) were tested 6 weeks or more after their EHS. Each participant underwent a thorough telephone health screen and on-site medical examination to ensure that inclusion criteria were met. All participants were informed of the study's purposes and procedures, and then provided written consent prior to participation. Approval was obtained from the Uniformed Services University Institutional Review Board, and the data presented herein are a subset of a larger study.

Baseline Screening and Anthropometric Testing

Participants underwent a medical examination, several anthropometric evaluations (body mass, height, waist circumference, and percentage of body fat), and a maximal aerobic graded exercise test to assess aerobic power. After completion of a medical history and other questionnaires, physiological measures of heart rate (HR), blood pressure (BP) (Criticare Systems Inc.; Waukesha, WI) and electrocardiographic activity (Philips StressVue Testing System with Trackmaster Full Vision Inc. Treadmill, Waltham, MA) were obtained at rest. Participant body mass was measured with a calibrated metric scale to the nearest 0.1 kg, and height was measured to the nearest 0.1 cm while the participant was wearing light clothing and no shoes. Body mass index was calculated from height and mass, and waist circumference was determined with a tape measure by standard techniques. (37) Body surface area and surface-to-mass ratio were calculated by standard methods. (38)

Percentage of body fat was determined using 2 techniques: skinfold measurements and bioelectrical impedance analysis (BIA). Skinfolds were used to allow comparison with previous analyses from the present study (36) and similar research. (39,40) The BIA was used due to concern about reliability/validity of skinfold measurements, especially for sex comparisons. Skinfold thickness was quantified with a skinfold caliper (Cambridge Scientific Industries Inc, Cambridge, MD) at 4 sites (biceps, triceps, subscapular, and suprailiac) on the right side of the body and BF% was computed by using the Durnin and Womersley calculation. (41) In order to combine data from a previous pilot study, (36) 3 skinfold sites were used for 36% of participants based on ACSM guidelines, (37) using chest, triceps, and subscapular for men, and triceps, abdomen, and suprailiac for women. The BIA was conducted using RJL Quantum II (RJL Systems, Clinton Township, Michigan), with participants lying down, arms at a 30[degrees] angle from body, and legs not touching. Based on recent research comparing BIA equations to estimate BF% among a military sample, (42) equations published by Segal et al (43) were selected (using the equations generalized across body fat levels). The correlation between the skinfold and BIA-derived BF% values was 0.76 (P<.001).

During the second visit, subjects underwent a standardized HTT, which consisted of walking on a treadmill for 2 hours in an environmental chamber as described below.

Determination of V[O.sub.2]max

The V[O.sub.2]max was determined by a maximal aerobic graded exercise test on a motorized treadmill through indirect calorimetry. Expired respiratory gases were collected continuously and analyzed by open-circuit spirometry (Oxycon Mobile portable system, Viasys Healthcare Inc, Yorba Linda, CA). The test used in this study, adapted from a protocol previously described by our laboratory, (44) consisted of a 5-minute warm-up (5.0 km/h and a 2.0% grade) followed by a running portion, at a constant speed of 7.7-13.7 km/h (based on HR achieved during warm-up), with incline starting at 0% and increasing 2.5% every 2 minutes, until the subject could no longer continue or V[O.sub.2] plateaued with an increase in workload.

Heat Tolerance Testing

All HTTs were conducted in the morning with participants wearing shorts and athletic shoes; none wore a t-shirt, but women wore a sports bra. The HTT consisted of walking on a treadmill at 5.0 km/hr at a 2% grade for 2 hours at 40[degrees]C and 40% relative humidity. Women were tested between days 3 and 9 of their follicular phase. To ensure adequate hydration before testing, urine specific gravity was measured with a hand held refractometer. If urine specific gravity was 1.02 units or more, the participant was provided water to hydrate until it was less than 1.02. Participants were instructed to void their bladder, and then nude body mass was measured. From this point on, all urine was collected in a 3.0 L polypropylene collection container. During the HTT, participants were permitted to hydrate with water ad libitum (up to one L/hr). Core temperature ([T.sub.c]) was measured by using a rectal thermometer inserted 10 cm beyond the anal sphincter; skin temperature was measured with skin sensors placed at 4 different sites (shoulder, chest, thigh, and calf). The [T.sub.c] was measured using either a thermistor-based system (64% of participants) (MEAS Temperature Probes (Measurement Specialties Inc, Dayton, OH) with Sensor Interface Box Model 93200 (Deban Enterprises Inc.; Beavercreek, OH)) or a thermocouple system for more recent participants (Type T Thermocouples with Thermes WiFi, Physitemp, Clifton, NJ). The HR was assessed by a Polar HR monitor (Polar Team 2 Pro, Polar USA Inc, Lake Success, NY). The HR, [T.sub.c] and skin temperatures were continuously monitored and recorded throughout the test; the physiological strain index was calculated from changes in final and baseline HR and [T.sub.c], as suggested by Moran et al. (45) Physiological strain index values range from 0-10, and are classified as follows: minimal (values of 0-2), low (3-4), moderate (5-6), high (7-8), and very high (9-10) strain. Sweat rate was estimated based on the difference in nude body mass before and after the test corrected for fluid intake and urine output. Most HTTs were conducted in the summer (49%), followed by the fall (24%), spring (20%), and winter (7%). Baseline and maximum physiological measures for HR and [T.sub.c] did not differ by season.

The HTT was discontinued if any participant met one of the following criteria: (1) [T.sub.c] greater than 39.5[degrees]C; (2) HR above 170 bpm; (3) experienced nausea, weakness, or dizziness; or (4) requested early test termination. Heat intolerance was defined as [T.sub.c] greater than 38.5[degrees]C, HR above 150 bpm, or failure to plateau, (5,34) with the latter defined by a rise in [T.sub.c] of greater than 0.45[degrees]C during the second hour of the HTT. (46)

Data Analyses

Sample characteristics are provided for men and women in Table 1, with independent-samples t tests used to identify differences between men and women, and heat tolerant vs heat intolerant participants. Cohen's d is used as a measure of effect size (small effect=0.2; moderate=0.5; and large>0.8).

Logistic regression models were developed to predict HTT performance. For the regression models, sex was entered into a first block, and additional predictors were entered into a second one. The primary HTT outcome was heat tolerance classification (with heat intolerance defined as [T.sub.c]>38.5[degrees]C or HR>150 bpm). To allow for a more granular assessment of heat tolerance, logistic regressions were also conducted to predict elevated [T.sub.c] (>38.5[degrees]C) and elevated HR (>150 bpm) separately.

Linear regression models were developed to predict continuous HTT outcomes. These additional models, even though similar to those above, were run because cutoffs for heat tolerance are being debated (47) and dichotomization reduces statistical power, especially with small sample sizes. Continuous HTT outcomes included maximal values for physiological strain index, HR, and [T.sub.c].


Demographic, anthropometric, and aerobic power characteristics are presented in Table 1. As expected, women had lower V[O.sub.2]max, body surface area, waist circumference, and body mass index and higher body surface area-to-mass ratio and BF% compared to men. Women were also 3.68 times more likely to be classified as heat intolerant than men (95% CI, 1.21, 11.24; %2=6.85, P<.01, d=0.63), such that 45% of women (9 out of 20) were intolerant, compared to 18% of men (10 out of 55). Sex differences in other HTT outcomes are presented in Table 2 and graphically in Figures 1 and 2. During the HTT, women demonstrated higher maximum HR than men ([t.sub.73]=2.27, P<.01, d=0.76); in contrast, sex differences between maximum [T.sub.c] did not reach statistical significance ([t.sub.73]=0.71, P>.05).

Heat intolerant participants (34% of sample) had lower V[O.sub.2]max ([t.sub.73]=2.28, P<.05, d=0.60) and higher BF% than heat tolerant ones, shown in Table 3. However, group differences in BF% were statistically significant for skinfold BF% ([t.sub.73]=2.30, P<.05, d=0.57), but not for BIA BF% ([t.sub.73]=1.51, P=. 15). Because V[O.sub.2]max and BF% were strongly correlated (skinfold: r=-0.55; BIA: r = -0.56; P<.001), they were assessed in separate regression models to predict HTT outcomes. For each regression, sex was entered into a first block (Block 1), followed by either V[O.sub.2]max (Block 2A), skinfold BF% (Block 2B), or BIA BF% (Block 2C).

In the logistic regression models (Table 4, column 1), sex initially predicted heat tolerance, however its effect became nonsignificant when V[O.sub.2]max and BF% were entered into the model. In the linear regression models, sex was related to maximum HR when it was the only variable; its effect also became nonsignificant in subsequent blocks. Meanwhile, the standardized beta-coefficients for V[O.sub.2]max as predictors of HRmax (assessed dichotomously and continuously) and maximal physiological strain index were much greater than sex (maximum HR: V[O.sub.2]max=-0.48 vs sex=0.14 and physiological strain index: V[O.sub.2]max=-0.34 vs sex=0.03). On the other hand, skinfold BF% only exceeded sex in relation to maximum HR (sex=0.14 vs skinfold BF%=0.28), and this did not hold for BIA BF% (sex=0.15 vs BIA BF%=0.03).


Our results suggest that although women are classified as heat intolerant to a greater extent than men, V[O.sub.2]max appears to account for most, if not all, of this sex difference. When heat tolerance was broken down into 2 components, HR and [T.sub.c], the sex findings held for HTT outcomes related to HR, but not [T.sub.c]. Thus, cardiovascular strain is far more important than thermal strain. This finding contributes to the literature by suggesting that a relatively fit, representative sample of a military population can be risk stratified for a military setting by participating in an HTT. (5) As women are integrated into combat military occupational specialties, risk profiles for exertional and physical injuries must be determined to assist in developing gender-specific training requirements, (2) as combat exposures will be gender neutral. The present study results suggest that when standard risk factors are controlled for, particularly aerobic power, women do not appear to be at greater risk for EHI than men.

Aerobic power and BF% serve key roles in thermoregulation, (48) risk for EHI, (14,19-21) and military performance. (49) Importantly, poor aerobic power and high BF% are the 2 most studied risk factors for EHI. (20-22) Even though aerobic power and body fat are strongly negatively correlated, they may both directly relate to EHI risk. (21,22) Individuals with poor aerobic power need to work at a higher relative intensity for a given workload than individuals with high aerobic power. This increases their relative physiological strain, which, in turn, decreases peripheral blood flow, hinders thermoregulation, and increases heat absorption. (14,50) Higher body fat also increases metabolic heat and hinders heat dissipation. (7,14) Since aerobic power and BF% also differ by sex, it is important to clarify their independent contributions to thermoregulation, especially as women are officially integrated into combat roles. In fact, proposed algorithms to stratify EHI risk typically include aerobic power and percentage of body fat. (22,51) These algorithms are useful screening tools for warfighters and athletes. But a full HTT is often warranted among EHS patients, (5) particularly when gradual return to physical activity may be problematic. (19,52)

Laboratory exercise studies have consistently demonstrated that sex differences in thermoregulation in the heat become minimal after controlling for aerobic power and body fat. (32,39,40,53,54) Other demographic differences in heat thermoregulation, such as age, may be explained by these factors as well. (55,56) Nevertheless, previous studies have used relatively small sample sizes and varied protocols, which make comparisons difficult. Protocols differ in exercise type (eg, walking, cycling), acclimatization procedures, and test conditions, depending on the particular research aims. Results from most studies indicate that women are not at a thermoregulatory disadvantage compared to men when matched for body composition and when performing tasks appropriate for their aerobic power level. In the military, fitness and body composition standards are often relative to sex, and in some military occupational specialties, physically demanding tasks cannot be customized to the Warfighter's sex. Certainly in the deployed setting, task assignment cannot be based on gender.

Combat fitness, as defined by Epstein et al, (2) is an individual's ability to effectively perform military-oriented tasks and be able to accomplish all aspects of a combat mission, while staying healthy and uninjured. Combat fitness requires not only the traditional aspects of fitness (cardiovascular endurance, muscular strength, and flexibility), but also neuromuscular motor (hand-eye coordination, agility, speed, and power) and environmental (heat acclimatization) fitness. To partially address these questions, each service and operational specialty is reevaluating occupational fitness requirements for gender neutrality, while at the same time maximizing successful outcomes, regardless of whether the service member is male or female.

Thermoregulatory differences between men and women can likely be attributed to physical characteristics rather than other inherent metabolic/ regulatory differences. (2) Given that women are at higher risk for EHI, efforts should focus on improving intrinsic and extrinsic modifiable risk factors. On average, when matched for age, men have greater lean body mass and less fat mass compared to women. (57) A smaller body mass and higher BF% will increase [T.sub.c]. (58) Additionally, when compared to men, women have lower relative and absolute aerobic power, which may contribute to earlier fatigue compared to men. (2) Clearly, sex differences in performance variables, such as muscle mass and V[O.sub.2]max, affect combat fitness. Cardiovascular and resistance training programs for women can improve physical performance through increases in strength, power, and endurance. (59) The challenge of operating in hot environments is compounded by the use of protective gear and body armor, which inhibit sweat evaporation and heat dissipation, and increase thermoregulatory and cardiovascular strain. Although performance requirement criteria may become gender-neutral for certain combat military occupational specialties, new training practices will be needed to help overcome modifiable sex differences.

Limitations to the present study include the sample size and debate regarding the IDF HTT. The number of women in the present study was larger than some previous studies, (32,33,35,39,40,53,54) but still somewhat limited. Future studies should include a greater number of female subjects to allow for more robust sex comparisons and the use of other statistical techniques such as propensity score matching/adjustment. (60) In addition, there is controversy with regard to the construct of heat tolerance in general (61) and the standardized use of the HTT in particular. (62) Alternatives to the IDF HTT include measuring heat tolerance over the course of a multiday acclimation protocol, (62) or customizing a HTT's exercise intensity to the individual being tested. (63) Since many of the EHI patients in the study visited the laboratory from other locations and were on temporary physical activity restrictions, it was not feasible to assess and control for heat acclimation status. More advanced techniques to measure BF% would have also benefitted the study due to concerns about validity and reliability of skinfolds and to a lesser degree BIA, which often vary across sex. (42) Additionally, other key variables, such as fluid and salt losses, may be important to consider. (64)

The IDF HTT remains the most widely used and clinically useful test to assess Warfighter return to duty following EHS, (5,52) as it simulates the conditions of many military EHI scenarios. (65) Importantly, it correlates with risk factors for EHS in the military, (36) for men and women. As women are integrated into combat military occupational specialties, their risk for EHS will increase, and physicians will have to decide whether to return them to duty following such an event. The IDF HTT can help, but research on how women perform has been lacking. Based on the present study and previous work by Druyan et al, (35) women demonstrate a much higher failure rate on the test. As with any high stake test, it is important to determine whether group differences are due to underlying differences in the latent variable. (66) Since the sex differences appear mostly attributable to aerobic power and perhaps BF%, they likely reflect women's increased risks for EHI. These findings should not be surprising to those familiar with human thermoregulation research, as they are consistent with a long line of previous research. (26-29,32,33,39,40) In the present context, however, these results will be crucial for physicians tasked with interpreting IDF HTT scores for men and women, and may inform broader military policy.

Josh B. Kazman, MS

Dianna L. Purvis, PhD

Yuval Heled, PhD

Peter Lisman, PhD

Danit Atias, PhD

Stephanie Van Arsdale, MS

Patricia A. Deuster, PhD, MPH


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Mr Kazman, Dr Purvis, Dr Lisman, Ms Van Arsdale, and Dr Deuster are with the Department of Military and Emergency Medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland.

Dr Heled and Dr Atias are with the Institute of Military Physiology, Heller Institute of Medical Research, Sheba Medical Center, Tel HaShomer, Israel.

Table 1. Participant Characteristics (mean [+ or -] SD) by Sex.

Variable                  Women (n=20)           Men (n=55)

Age (yrs)              28.6 [+ or -] 5.2     28.7 [+ or -] 6.3

Height (cm)            163.8 [+ or -] 5.5   178.3 [+ or -] 6.6 *

Weight (kg)            63.8 [+ or -] 7.5    84.3 [+ or -] 11.2 *

BMI (kg/[m.sup.2])     23.8 [+ or -] 2.5    26.5 [+ or -] 3.0 *

Body surface area      1.69 [+ or -] 0.11   2.02 [+ or -] 0.16 *

Body surface/mass      2.67 [+ or -] 0.16   2.41 [+ or -] 0.18 *


Skinfold BF%           28.4 [+ or -] 5.1    18.7 [+ or -] 5.1 *

BIA BF%                30.1 [+ or -] 21.6   21.6 [+ or -] 5.1 *

Waist circumference    72.4 [+ or -] 4.8    84.6 [+ or -] 7.0 *

V[O.sub.2]max          45.3 [+ or -] 6.8    52.3 [+ or -] 7.4 *

Variable                   All (n=75)

Age (yrs)              28.7 [+ or -] 6.0

Height (cm)            174.4 [+ or -] 9.0

Weight (kg)            78.8 [+ or -] 13.8

BMI (kg/[m.sup.2])     25.8 [+ or -] 3.1

Body surface area      1.93 [+ or -] 0.21

Body surface/mass      2.48 [+ or -] 0.21


Skinfold BF%           21.3 [+ or -] 6.7

BIA BF%                23.8 [+ or -] 6.2

Waist circumference    81.4 [+ or -] 8.5

V[O.sub.2]max          50.5 [+ or -] 7.8

BIA=bioelectrical impedance analysis
* P<.05

Table 2. Physiological Measurements (mean [+ or -] SD) During HTT
by Sex.

Variable                    Women (n=20)          Men (n=55)

Core Temperature,
[T.sub.c] ([degrees]C)

  Baseline [T.sub.c]     37.1 [+ or -] 0.4    36.9 [+ or -] 0.4

  Max [T.sub.c]          38.1 [+ or -] 0.4    38.1 [+ or -] 0.4

  [DELTA][T.sub.c        0.26 [+ or -] 0.19   0.28 [+ or -] 0.11
  (over min 60-120)]

Heart rate, HR (bpm)

  Baseline HR             76 [+ or -] 15.0    68 [+ or -] 12.1 *

  Max HR                 137 [+ or -] 20.1    122 [+ or -] 20.2

  [DELTA][HR.sub.         7.5 [+ or -] 7.2     4.6 [+ or -] 8.2
  (over min 60-120)]

Physiological strain      5.2 [+ or -] 1.4     4.7 [+ or -] 1.3

Sweat rate (L/h)         0.81 [+ or -] 0.28   1.10 [+ or -] 0.31

Variable                     All (n=75)

Core Temperature,
[T.sub.c] ([degrees]C)

  Baseline [T.sub.c]     37.0 [+ or -] 0.4

  Max [T.sub.c]          38.1 [+ or -] 0.4

  [DELTA][T.sub.c        0.27 [+ or -] 0.18
  (over min 60-120)]

Heart rate, HR (bpm)

  Baseline HR             70 [+ or -] 13.3

  Max HR                 126 [+ or -] 21.1

  [DELTA][HR.sub.         5.3 [+ or -] 8.0
  (over min 60-120)]

Physiological strain      5.3 [+ or -] 8.0

Sweat rate (L/h)         1.03 [+ or -] 0.33

* P<05
([dagger]) P<01

Table 3. Characteristics (mean [+ or -] SD) of Heat Tolerant versus
Heat Intolerant Participants.

                                          HTT Outcome

Independent Variable    Heat Tolerant   Heat Intolerant     t
                           (n=56)           (n=19)

V[O.sub.2max]           51.6 [+ or -]    47.0 [+ or -]    2.28 *
(mlx[kg.sup.                 7.5              7.9

Skinfold BF%            20.3 [+ or -]    24.3 [+ or -]    2.30 *
                             6.1              7.6

BIA BF%                 23.2 [+ or -]    25.7 [+ or -]     1.51
                             5.4              8.2

BMI (kg/[m.sup.2])      25.9 [+ or -]    25.2 [+ or -]     0.89
                             3.0              3.4

Body surface area       1.96 [+ or -]    1.85 [+ or -]     1.93
([m.sup.2])                 0.21             0.19

Body surface/mass       2.46 [+ or -]    2.54 [+ or -]     1.55
([m.sup.2]x                 0.21             0.22

Waist circumference     82.4 [+ or -]    78.2 [+ or -]     1.92
(cm)                         8.4              7.9

BIA indicates bioelectrical impedance analysis.

* P<05

Table 4. Adjusted Odds Ratios (95% CI) from Hierarchical
Logistic Regression Predicting Dichotomous HTT Outcomes.

                                      HTT Outcome

Independent Variable     Heat Tolerant      Core >38.5[degrees]C

Block 1
  Gender               3.7 (1.21-11.24) *     2.0 (0.56-6.90)

Block 2A
  Gender                2.5 (0.75-8.54)       1.7 (0.43-6.86)

V[O.sub.2]max           0.9 (0.87-1.02)       0.9 (0.90-1.07)

Block 2B
  Gender                2.2 (0.49-9.87)       1.1 (0.18-6.63)
  Skinfold BF%          1.1 (0.95-1.18)       1.1 (0.98-1.31)

Block 2C
  Gender                3.5 (0.82-15.09)      2.0 (0.39-10.54)
  BIA BF%               1.0 (0.90-1.12)       1.0 (0.88-1.13)

                              HTT Outcome

Independent Variable          HR >150 BPM

Block 1
  Gender                    3.5 (0.98-12.56)

Block 2A
  Gender                    1.5 (0.35-6.47)

V[O.sub.2]max          0.9 (0.76-0.96) ([dagger])

Block 2B
  Gender                    1.8 (0.33-10.16)
  Skinfold BF%              1.0 (0.89-1.13)

Block 2C
  Gender                    1.6 (0.30-8.19)
  BIA BF%                   1.1 (0.96-1.27)

BIA indicates bioelectrical impedance analysis.
* P<05
([dagger]) P<01
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Author:Kazman, Josh B.; Purvis, Dianna L.; Heled, Yuval; Lisman, Peter; Atias, Danit; Van Arsdale, Stephani
Publication:U.S. Army Medical Department Journal
Article Type:Report
Date:Apr 1, 2015
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