The weight, urine colour and thirst Venn diagram is an accurate tool compared with urinary and blood markers for hydration assessment at morning and afternoon timepoints in euhydrated and free-living individuals.

The weight, urine colour and thirst (WUT) Venn diagram is a practical hydration assessment tool; however, it has only been investigated during first-morning. This study investigated accuracy of the WUT Venn diagram at morning and afternoon timepoints compared with blood and urine markers. Twelve men (21 ± 2 years; 81·0 ± 15·9 kg) and twelve women (22 ± 3 years; 68·8 ± 15·2 kg) completed the study. Body mass, urine colour, urine specific gravity (USG), urine osmolality (UOSM), thirst and plasma osmolality (POSM) were collected at first-morning and afternoon for 3 consecutive days in free-living (FL) and euhydrated states. Number of markers indicating dehydration levels were categorised into either 3, 2, 1 or 0 WUT markers. Receiver operating characteristics analysis calculated the sensitivity and specificity of 1, 2 or 3 hydration markers in detecting dehydration or euhydration. Specificity values across morning and afternoon exhibited high diagnostic accuracy for USG (0·890-1·000), UOSM (0·869-1·000) and POSM (0·787-0·990) when 2 and 3 WUT markers were met. Sensitivity values across both timepoints exhibited high diagnostic accuracy for USG (0·826-0·941) and UOSM (0·826-0·941), but not POSM in the afternoon (0·324) when 0 and 1 WUT markers were met. The WUT Venn diagram is accurate in detecting dehydration for WUT2 and WUT3 based off USG, UOSM and POSM during first-morning and afternoon. Applied medical, sport and occupational practitioners can use this tool in field settings for hydration assessment not only at various timepoints throughout the day but also in FL individuals.

Comparison between digital and paper urine color to assess hydration status.

PURPOSE: The purpose of this study was to investigate associations between digital urine color and paper urine color with other urine indices to assess hydration status. METHODS: Twelve male subjects (mean ± standard deviation; age, 26 ± 8 years; body mass, 57.8 ± 5.3 kg; height, 177.5 ± 8.9 cm; VO2max, 57.8 ± 5.8 ml·kg-1·min-1) performed four exercise trials in the heat. Before and following exercise trials, subjects provide urine samples. Urine samples were measured using a digital urine color chart on a portable device screen. Urine samples were also assessed with urine specific gravity (USG), urine osmolality (UOsmo), and a validated paper urine color chart. RESULTS: There were extremely large associations found between digital urine color and paper urine color (r = 0.926, p < 0.001). Correlation coefficients showing associations with USG and UOsmo were similar between digital urine color (USG, r = 0.695, p < 0.001; UOsmo, r = 0.555, p < 0.001) and paper urine color (USG, r = 0.713, p < 0.001; UOsmo, r = 0.570, p < 0.001). Bland-Altman analysis indicated that no proportional bias was observed between digital and paper urine colors (bias, - 0.148; SD of bias, 0.492; 95% LOA, - 1.11, 0.817; p = 0.094). CONCLUSIONS: Strong associations were found between digital and paper urine colors with no proportional bias. Furthermore, the degree of associations with USG and UOsmo was similar between digital and paper urine color. These results indicate that digital urine color is a useful tool to assess hydration status and this method could be used as an alternative method to using paper urine color.

Overexertion and heat stress in the fire service: a new conceptual framework.

From the year 2000, the United States Fire Administration (USFA) has been recording all line-of-duty deaths in the fire service. Stress or overexertion caused 1096 out of 2598 total line-of-duty deaths in the United States from 2000 to 2021. Those deaths due to stress or overexertion were further classified as myocardial infarction (90%), cerebrovascular accident (6.8%), other (2.6%), and heat exhaustion (0.6%). Environmental heat exposure is a concern in firefighting, as firefighters work in extreme conditions, such as high ambient temperatures, while wearing protective clothing. Heat stress is not only hazardous to the cardiovascular system, but may accentuate muscle fatigue and overexertion. In addition, overexertion itself is related to increased incidence of musculoskeletal injuries, usually to the lower extremities. Further, there is a strong physiological mechanistic link to suggest that the increased occupational heat exposure and thermoregulatory strain firefighters experience may be a stressor that increases the risk of injuries. This commentary hopes to show the need for further research on the effects of occupational exposures and physiological strain in the fire service.

Countermovement jump, handgrip, and balance performance change during euhydration, mild-dehydration, rehydration, and ad libitum drinking.

Objective: To examine the effects of euhydration, mild-dehydration, rehydration, and ad libitum drinking on countermovement jump (CMJ), handgrip strength, and performance of balance error scoring system test (BESS). Methods: Eighteen healthy male subjects (mean[M]±standard deviation[SD]; age, 23±3y; body mass, 80.1 ± 9.7 kg; height, 175.8 ± 5.7 cm) participated in this study. Participants reported to the laboratory to perform CMJ, handgrip strength, and BESS with different hydration statuses (euhydrated, EUH; when they initially sensed thirst, THIRST; dehydrated, DEH; following 30 minutes of rehydration, REH; and following 24-h ad libitum drinking, AD). Results: CMJ at EUH (M±SD; 54.6 ± 3.0 cm) was significantly higher than DEH (52.8 ± 3.0 cm, p = 0.027) and REH (52.6 ± 2.8 cm, p < 0.001). However, there was no difference between DEH and REH (p = 0.643). CMJ at THIRST (54.9 ± 3.0 cm, p = 0.004) was higher than REH. Also, AD (53.8 ± 2.8 cm, p = 0.027) was higher than REH. In left handgrip strength, THIRST (48.6 ± 9.5 kg) was higher than EUH (46.7 ± 10.1 kg, p = 0.018), DEH (45.8 ± 10.0 kg, p = 0.013), REH (46.1 ± 9.5 kg, p = 0.004), and AD (47.1 ± 9.7 kg, p = 0.05). Additionally, in the single-leg stance on a foam pad, more BESS errors were found at THIRST (6 ± 2) compared to EUH (5 ± 2, p = 0.007) and AD (5 ± 2, p = 0.002). Conclusion: The findings of this study were: ∼2% of mild dehydration induced by 24-h fluid restriction decreased lower body power measured by CMJ, acute rehydration did not restore the loss of lower body power induced by dehydration, and ∼0.5-0.9% of dehydration did not decrease lower body power.

Changes in Hydration Factors Over the Course of Heat Acclimation in Endurance Athletes.

The purpose of this study was to examine the effect of heat acclimation (HA) on thirst levels, sweat rate, and percentage of body mass loss (%BML), and changes in fluid intake factors throughout HA induction. Twenty-eight male endurance athletes (mean ± SD; age, 35 ± 12 years; body mass, 73.0 ± 8.9 kg; maximal oxygen consumption, 57.4 ± 6.8 ml·kg-1·min-1) completed 60 min of exercise in a euhydrated state at 58.9 ± 2.3% velocity of maximal oxygen consumption in the heat (ambient temperature, 35.0 ± 1.3 °C; relative humidity, 48.0 ± 1.3%) prior to and following HA where thirst levels, sweat rate, and %BML were measured. Then, participants performed 5 days of HA while held at hyperthermia (38.50-39.75 °C) for 60 min with fluid provided ad libitum. Sweat volume, %BML, thirst levels, and fluid intake were measured for each session. Thirst levels were significantly lower following HA (pre, 4 ± 1; post, 3 ± 1, p < .001). Sweat rate (pre, 1.76 ± 0.42 L/hr; post, 2.00 ± 0.60 L/hr, p = .039) and %BML (pre, 2.66 ± 0.53%; post, 2.98 ± 0.83%, p = .049) were significantly greater following HA. During HA, thirst levels decreased (Day 1, 4 ± 1; Day 2, 3 ± 2; Day 3, 3 ± 2; Day 4, 3 ± 1; Day 5, 3 ± 1; p < .001). However, sweat volume (Day 1, 2.34 ± 0.67 L; Day 2, 2.49 ± 0.58 L; Day 3, 2.67 ± 0.63 L; Day 4, 2.74 ± 0.61 L; Day 5, 2.74 ± 0.91 L; p = .010) and fluid intake (Day 1, 1.20 ± 0.45 L; Day 2, 1.52 ± 0.58 L; Day 3, 1.69 ± 0.63 L; Day 4, 1.65 ± 0.58 L; Day 5, 1.74 ± 0.51 L; p < .001) increased. In conclusion, thirst levels were lower following HA even though sweat rate and %BML were higher. Thirst levels decreased while sweat volume and fluid intake increased during HA induction. Thus, HA should be one of the factors to consider when planning hydration strategies.

Relationship Between Heart Rate Variability and Acute:Chronic Load Ratio Throughout a Season in NCAA D1 Men's Soccer Players.

ABSTRACT: Sekiguchi, Y, Huggins, RA, Curtis, RM, Benjamin, CL, Adams, WM, Looney, DP, West, CA, and Casa, DJ. Relationship between heart rate variability and acute:chronic load ratio throughout a season in NCAA D1 men's soccer players. J Strength Cond Res 35(4): 1103-1109, 2021-The purpose of this study was twofold: (a) to examine the relationship between heart rate variability (HRV) and acute:chronic workload ratio (ACWR)-based training load (TL) metrics and (b) to examine relationships across various A:C ratio-based TL metrics. Heart rate variability in 23 male college soccer players (mean ± SD; age, 21 ± 1 years; body mass, 80.3 ± 5.8 kg; height, 181.9 ± 6.5 cm; %body fat, 11.9 ± 2.0%; and V̇o2max, 51.9 ± 5.0 ml·kg-1·min-1) was measured at 5 time points: week(W)1, W3, W7, W12, and W14 during the 2015 NCAA men's soccer season. Heart rate variability was calculated from beat to beat intervals using a heart rate monitor. Players donned a global position satellite-enabled device that measured the following TL metrics: session time (ST), Player Load (PL), PL·min-1, and total distance (TD). Acute:chronic workload ratio was calculated for each TL metric: ACWR-based ST (ACWRST), ACWR-based PL (ACWRPL), ACWR-based PL·min-1 (ACWRPLM), and ACWR-based TD (ACWRTD): ACWR = week average TLs/mo average (30 ± 1 days) TLs. Relationships between HRV and ACWR-based each TL metric were evaluated using mixed effects models. Tukey pairwise comparisons were used to examine differences between types of ACWR-based TL metrics. An increase in ACWRST significantly reduced HRV throughout a season (-7.4 ± 3.6 m·s-1; p = 0.04). There were significant differences between ACWRPLM and ACWRST, ACWRPL and ACWRTD at W1, ACWRPLM and ACWRST at W3 (p < 0.05). In conclusion, ACWRST, ACWRPL, and ACWRTD were significantly different from ACWRPLM. ACWRST was found to significantly predict HRV; higher ACWRST was significantly associated with lower HRV. Therefore, tracking of the ACWR using ST may help to optimize athlete's physiological state throughout a season.

Seasonal Accumulated Workloads in Collegiate Men's Soccer: A Comparison of Starters and Reserves.

ABSTRACT: Curtis, RM, Huggins, RA, Benjamin, CL, Sekiguchi, Y, Arent, S, Armwald, B, Pullara, JM, West, CA, and Casa, DJ. Seasonal accumulated workloads in collegiate men's soccer: a comparison of starters and reserves. J Strength Cond Res 35(11): 3184-3189, 2021-The purpose of this investigation was to quantify and compare player's season total-, match-, and training-accumulated workload by player status characteristics (i.e., starter vs. reserve) in American collegiate men's soccer. Global positioning system (GPS) and heart rate (HR)-derived workloads were analyzed from 82 collegiate male soccer athletes from 5 separate teams over the 2016 and 2017 seasons. Differences in total physical and physiological workloads (i.e., total distance, accelerations, and weighted HR-zone training impulse [TRIMP] score) as well as workloads over a range of intensity zones were examined using multilevel mixed models, with mean difference (MD) and effect size (ES) reported. Starters accumulated substantially more total distance (MD = 82 km, ES = 1.23), TRIMP (MD = 2,210 au, ES = 0.63), and total accelerations (MD = 6,324 n, ES = 0.66) over the season. Total accumulated distance in all velocity zones (ES [range] = 0.87-1.08), all accelerations zones (ES [range] = 0.54-0.74), and time spent at 70-90% HRmax (ES [range] = 0.60-1.12) was also greater for starters. Reserves accumulated substantially more total distance (MD = 20 km, ES = 0.43) and TRIMP (MD = 1,683 au, ES = 0.79) during training. Although reserves show elevated physical and physiological loads during training compared with starters, there is an imbalance in overall workloads between player roles, with starters incurring substantially more match and total seasonal workloads. These results indicate managing player workloads in soccer requires attention to potential imbalances between players receiving variable match times. Coaches and practitioners in collegiate men's soccer may consider implementing strategies to reduce discrepancies in loading between starters and reserves. Individualized monitoring of training and match workloads may assist in the implementation of more balanced load management programs.

The Relationships Between Perceived Wellness, Sleep, and Acute: Chronic Training Load in National Collegiate Athletics Association Division I Male Soccer Players.

ABSTRACT: Sekiguchi, Y, Curtis, RM, Huggins, RA, Benjamin, CL, Walker, AJ, Arent, SM, Adams, WM, Anderson, T, and Casa, DJ. The relationships between perceived wellness of, sleep of, and acute: chronic training load on National Collegiate Athletics Association division I male soccer players. J Strength Cond Res 35(5): 1326-1330, 2021-The purpose of this study was to investigate relationships between perceived wellness, sleep, and acute: chronic workload ratio (ACWR) throughout a collegiate men's soccer season. Sixty male collegiate soccer players (mean[M] ± SD; age, 21±2 year; body mass, 77.6 ± 6.5 kg; height, 180.1 ± 6.4 cm; body fat%, 9.9 ± 3.9% ; and V̇o2max, 53.1 ± 5.0 ml·kg-1·min-1) participated in this study. During each session, players used a heart rate and global positioning satellite-enabled chest strap to measure training impulse and ACWR. The ACWR values were trichotomized at the individual level giving an equal number of observations within each ACWR category of low, moderate, and high ACWR (M ± SD; low, 0.658 ± 0.23; moderate, 0.92 ± 0.15; and high, 1.17 ± 0.16). Stress, fatigue, and soreness levels were collected using 1-10 Likert scales and sleep duration, and sleep quality were measured by the Karolinska Sleep Diary. Stress, fatigue, soreness levels, and sleep quality were transformed to corresponding z-scores at the individual level. Fatigue levels were significantly higher when ACWR was high compared with low (mean difference [95% confidence intervals], effect size, p-value; 0.31 [0.21, 0.42], 0.29, p < 0.001) and moderate (0.14 [0.03, 0.24], 0.13, p = 0.01). Fatigue levels were also significantly higher when the ACWR was moderate compared with low (0.18 [0.07, 0.28], 0.16, p = 0.001). Soreness levels were significantly higher when the ACWR was high compared with low (0.25 [0.14, 0.36], 0.23, p < 0.001). Stress levels were significantly greater when the ACWR was high compared with low (0.19, [0.08, 0.29], 0.18, p < 0.001) and compared with moderate (0.15, [0.05, 0.25], 0.14, p = 0.004). There were no differences in sleep duration or sleep quality in different ACWR. The ACWR may be a useful tool to achieve an appropriate balance between training and recovery to manage daily fatigue and soreness levels in athletes.

The Relationship between %BML, Urine Color, Thirst Level and Urine Indices of Hydration Status.

INTRODUCTION: Dehydration is known to impair health, quality of daily life, and exercise performance [1]. While several methods are utilized to assess fluid balance, there is no gold standard to assess hydration status [2]. Cheuvront and Kenefick [3] suggested the use of a Venn diagram, which consists of % body mass weight (BML), urine color, and thirst level (WUT) to measure hydration status and fluid needs. However, no study to date has examined the relationship between the WUT criteria and hydration status measured by urine indices. OBJECTIVE: The purpose of this study was to investigate the relationships between urine-specific gravity (USG), urine osmolality (UOSM), and the WUT criteria. METHODS: Twenty-two females (mean ± SD; age, 20 ± 1 year; weight, 65.4 ± 12.6 kg) and twenty-one males (age, 21 ± 1 year; body mass, 78.7 ± 14.6 kg) participated in this study. First-morning body mass, urine color, USG, UOSM, and thirst level were collected for 10 consecutive days. First 3 days were utilized to establish a euhydrated baseline body weight. %BML >1%, urine color >5, and thirst level ≥5 were used as the dehydration thresholds. The number of markers that indicated dehydration levels was summed when each variable met each threshold. One-way ANOVA with Tukey pairwise comparison was used to assess the differences in USG and UOSM, followed by a calculation of effect size (ES). RESULTS: Figure 1 indicates the differences of UOSM based on the WUT criteria. For UOSM, "2 markers indicated" (mean [M] ± SD [ES], 705 ± 253 mOsmol [0.43], p = 0.018) was significantly higher than "1 marker indicated" (M ± SD, 597 ± 253 mOsmol). Additionally, "zero marker indicated" (509 ± 249 mOsmol) was significantly lower than "3 markers indicated" (M ± SD [ES], 761 ± 250 mOsmol, [1.01], p = 0.02) and "2 markers indicated" ([ES], [0.78], p = 0.004). However, there was no statistical difference between "3 markers indicated" ([ES], [0.65], p = 0.13) and "1 marker indicated." For USG, "3 markers indicated" (M ± SD [ES], 1.021 ± 0.007 [0.57], p = 0.025) and "2 markers indicated" (M ± SD [ES], 1.019 ± 0.010 [0.31], p = 0.026) were significantly higher than "1 marker indicated" (M ± SD, 1.016 ± 0.009). Additionally, "zero marker indicated" (1.014 ± 0.005) was significantly lower than "3 markers indicated" ([ES], [1.21], p = 0.005) and "2 markers indicated" ([ES], [0.54], p = 0.009). CONCLUSION: When 3 markers indicated dehydration levels, UOSM and USG were greater than euhydrated cut points. When 2 markers indicated dehydration levels, USG was higher than the euhydrated cut point. Additionally, UOSM and USG were significantly lower when zero or 1 marker indicated dehydration levels. Thus, the WUT criteria are a useful tool to assess hydration status. Athletes, coaches, sports scientists, and medical professions can use this strategy in the field settings to optimize their performance and health without consuming money and time.

The Validity and Reliability of Global Positioning System Units for Measuring Distance and Velocity During Linear and Team Sport Simulated Movements.

Huggins, RA, Giersch, GEW, Belval, LN, Benjamin, CL, Curtis, RM, Sekiguchi, Y, Peltonen, J, and Casa, DJ. The validity and reliability of GPS units for measuring distance and velocity during linear and team sport simulated movements. J Strength Cond Res 34(11): 3070-3077, 2020-This experimental study aimed to assess the validity and reliability of shirt-mounted 10-Hz global positioning system (GPS) units (Polar Team Pro) for measuring total distance (TD), constant velocity (VelC), and instantaneous velocity (VelI) during linear running and a team sport simulation circuit (TSSC). Fifteen male soccer athletes completed linear tasks (40 and 100 m) at various velocities: walk (W) (4.8-7.9 km·h), jog (J) (8.0-12.7 km·h), run (R) (12.9-19.9 km·h), and sprint (S) (>20.0 km·h) and a 120-m TSSC. Global positioning system validity and reliability for TD, VelC, and VelI were compared with criterion measures using 2 methods (a and b) of GPS raw data extraction. When measuring TD for the Polar Team Pro device, validity and reliability measures were <5% error at all velocities during the 40-m (with the exception of the S [%CV = 8.03]) and 100-m linear trial (both extraction methods) and TSSC. The GPS mean difference (±SD) for TD during the TSSC using extraction methods (a) and (b) was 0.2 ± 1.2 and 2.2 ± 2.2 m, respectively. The validity of the device in measuring VelC was significantly different (p < 0.05) at all velocities during the 40 m (exception W) and the 100 m, with effect sizes ranging from trivial to small (exception of 100 m S). VelI was similar (p > 0.05) at all velocities, except for the W (p = 0.001). The reliability of the device when measuring VelC during the 40 and 100 m was <5% CV; however, during the 100 m, VelI ranged from 1.4 to 12.9%. Despite trivial to large effect sizes for validity of TD, this device demonstrated good reliability <5% CV during linear and TSSC movements. Similarly, effect sizes ranged from trivial to large for VelC, and yet VelI reliability was good for VelC, but good to poor for VelI.

Contextual Factors Influencing External and Internal Training Loads in Collegiate Men's Soccer.

Curtis, RM, Huggins, RA, Benjamin, CL, Sekiguchi, Y, Adams, WM, Arent, SM, Jain, R, Miller, SJ, Walker, AJ, and Casa, DJ. Contextual factors influencing external and internal training loads in collegiate men's soccer. J Strength Cond Res 34(2): 374-381, 2020-This study investigated factors influencing training loads (TL) in collegiate men's soccer. Total distance, high-speed running distance (>14.4 km·h), high-intensity heart-rate zone duration (HI HRZ, >70% heart rate relative to maximum), and session rating of perceived exertion were assessed daily from 107 male soccer players competing for 5 National Collegiate Athletics Association Division I teams. Differences between athlete role (starter and reserve), position (defender, midfielder, and forward), season phase (preseason, in-season, and postseason), days relative to match (MD-1 to MD-5+), days between matches (<4, 4-5, >5 days), previous match outcome (win, loss, and draw), and upcoming opponent relative ranking (weaker, trivial, and stronger) were examined. Mean differences (MD) and effect sizes (ESs) with 90% confidence intervals were reported. There were trivial and insignificant differences by player role, position, or upcoming opponent strength, and small-moderate increases in preseason TL compared with in-season (ES [range] = 0.4-0.9). TLs were lower for MD-1 and higher for MD-5+ (ES [range] = 0.4-1.3) when compared with MD-2-4. External loads (ES = -0.40 ± 0.20) were less after wins compared with losses. TLs are increased in the preseason, when training sessions occur greater than 5 days from a match and after losses. Contextualizing factors affecting TLs has implications for developing workload prescription and recovery strategies.

Does Dehydration Affect the Adaptations of Plasma Volume, Heart Rate, Internal Body Temperature, and Sweat Rate During the Induction Phase of Heat Acclimation?

Clinical Scenario: Exercise in the heat can lead to performance decrements and increase the risk of heat illness. Heat acclimation refers to the systematic and gradual increase in exercise in a controlled, laboratory environment. Increased duration and intensity of exercise in the heat positively affects physiological responses, such as higher sweat rate, plasma volume expansion, decreased heart rate, and lower internal body temperature. Many heat acclimation studies have examined the hydration status of the subjects exercising in the heat. Some of the physiological responses that are desired to elicit heat acclimation (ie, higher heart rate and internal body temperature) are exacerbated in a dehydrated state. Thus, euhydration (optimal hydration) and dehydration trials during heat acclimation induction have been conducted to determine if there are additional benefits to dehydrated exercise trials on physiological adaptations. However, there is still much debate over hydration status and its effect on heat acclimation. Clinical Question: Does dehydration affect the adaptations of plasma volume, heart rate, internal body temperature, skin temperature, and sweat rate during the induction phase of heat acclimation? Summary of Findings: There were no observed differences in plasma volume, internal body temperature, and skin temperature following heat acclimation in this critically appraised topic. One study found an increase in sweat rate and another study indicated greater changes in heart rate following heat acclimation with dehydration. Aside from these findings, all 4 trials did not observe statistically significant differences in euhydrated and dehydrated heat acclimation trials. Clinical Bottom Line: There is minimal evidence to suggest that hydration status affects heat acclimation induction. In the studies that met the inclusion criteria, there were no differences in plasma volume concentrations, internal body temperature, and skin temperature. Strength of Recommendation: Based on the Oxford Centre for Evidence-Based Medicine Scale, Level 2 evidence exists.

Relationships between resting heart rate, heart rate variability and sleep characteristics among female collegiate cross-country athletes.

Even though sleep has been shown to be influenced by athletes' training status, the association with resting heart rate and heart rate variability remains unclear. The purpose of this study was to compare the changes in and relationships between resting heart rate, heart rate variability and sleep characteristics across a female collegiate cross-country season. Ten NCAA Division I collegiate female cross-country athletes (mean ± SD; age, 19 ± 1 year; height, 167.6 ± 7.6 cm; body mass, 57.7 ± 10.2 kg; VO2max , 53.3 ± 5.9 ml kg-1  min-1 ) participated in this study. Resting heart rate, heart rate variability and the percentage of time in slow wave sleep were captured using a wrist-worn multisensor sleep device throughout the 2016 competitive cross-country season (12 weeks). Linear mixed-effects models and magnitude-based inferences were used to assess differences between each week. Pearson product moment correlations were used to investigate relationships between variables. Resting heart rate at the end of the season, specifically during weeks 10-12 (mean ± SE; week 10, 48 ± 2; week 11, 48 ± 3; week 12, 48 ± 3), showed a practically meaningful increase compared to the beginning of the season, weeks 2-4 (week 2, 44 ± 2; week 3, 45 ± 2; week 4, 44 ± 2). Higher resting heart rate (r = 0.55) and lower heart rate variability (r = -0.62) were largely associated with an increase in percentage of time spent in slow wave sleep. These data suggest that when physiological state was impaired, meaning the physiological restorative demand was higher, the percentage of time in slow wave sleep was increased to ensure recovery. Thus, it is important to implement sleep hygiene strategies to promote adequate slow wave sleep when the body needs physiological restoration.

Effect of Heat Acclimatization, Heat Acclimation, and Intermittent Heat Training on Maximal Oxygen Uptake.

BACKGROUND: Maximal oxygen uptake (VO2max) is an important determinant of endurance performance. Heat acclimation/acclimatization (HA/HAz) elicits improvements in endurance performance. Upon heat exposure reduction, intermittent heat training (IHT) may alleviate HA/HAz adaptation decay; however, corresponding VO2max responses are unknown. HYPOTHESIS: VO2max is maintained after HAz/HA; IHT mitigates decrements in aerobic power after HAz/HA. STUDY DESIGN: Interventional study. LEVEL OF EVIDENCE: Level 3. METHODS: A total of 27 male endurance runners (mean ± SD; age, 36 ± 12 years; body mass, 73.03 ± 8.97 kg; height, 178.81 ± 6.39 cm) completed VO2max testing at 5 timepoints; baseline, post-HAz, post-HA, and weeks 4 and 8 of IHT (IHT4, IHT8). After baseline testing, participants completed HAz, preceded by 5 days of HA involving exercise to induce hyperthermia for 60 minutes in the heat (ambient temperature, 39.13 ± 1.37°C; relative humidity, 51.08 ± 8.42%). Participants were assigned randomly to 1 of 3 IHT groups: once-weekly, twice-weekly, or no IHT. Differences in VO2max, velocity at VO2max (vVO2), and maximal heart rate (HRmax) at all 5 timepoints were analyzed using repeated-measure analyses of variance with Bonferroni corrections post hoc. RESULTS: No significant VO2max or vVO2 differences were observed between baseline, post-HAz, or post-HA (P = 0.36 and P = 0.09, respectively). No significant group or time effects were identified for VO2max or vVO2 at post-HA, IHT4, and IHT8 (P = 0.67 and P = 0.21, respectively). Significant HRmax differences were observed between baseline and post-HA tests (P < 0.01). No significant group or time HRmax differences shown for post-HA, IHT4, and IHT8 (P = 0.59). CONCLUSION: VO2max was not reduced among endurance runners after HA/HAz and IHT potentially due to participants' similar aerobic training status and high aerobic fitness levels. CLINICAL RELEVANCE: HAz/HA and IHT maintain aerobic power in endurance runners, with HAz/HA procuring reductions in HRmax.

Eccentric muscle-damaging exercise in the heat lowers cellular stress prior to and immediately following future exertional heat exposure.

Muscle-damaging exercise (e.g., downhill running [DHR]) or heat exposure bouts potentially reduce physiological and/or cellular stress during future exertional heat exposure; however, the true extent of their combined preconditioning effects is unknown. Therefore, this study investigated the effect of muscle-damaging exercise in the heat on reducing physiological and cellular stress during future exertional heat exposure. Ten healthy males (mean ± Standard Definition; age, 23 ± 3 years; body mass, 78.7 ± 11.5 kg; height, 176.9 ± 4.7 cm) completed this study. Participants were randomly assigned into two preconditioning groups: (a) DHR in the heat (ambient temperature [Tamb], 35 °C; relative humidity [RH], 40%) and (b) DHR in thermoneutral (Tamb, 20 °C; RH, 20%). Seven days following DHR, participants performed a 45-min flat run in the heat (FlatHEAT [Tamb, 35 °C; RH, 40%]). During exercise, heart rate and rectal temperature (Trec) were recorded at baseline and every 5-min. Peripheral blood mononuclear cells were isolated to assess heat shock protein 72 (Hsp72) concentration between conditions at baseline, immediately post-DHR, and immediately pre-FlatHEAT and post-FlatHEAT. Mean Trec during FlatHEAT between hot (38.23 ± 0.38 °C) and thermoneutral DHR (38.26 ± 0.38 °C) was not significantly different (P = 0.68), with no mean heart rate differences during FlatHEAT between hot (172 ± 15 beats min-1) and thermoneutral conditions (174 ± 8 beats min-1; P = 0.58). Hsp72 concentration change from baseline to immediately pre-FlatHEAT was significantly lower in hot (-51.4%) compared to thermoneutral (+24.2%; P = 0.025) DHR, with Hsp72 change from baseline to immediately post-FlatHEAT also lower in hot (-52.6%) compared to thermoneutral conditions (+26.3%; P = 0.047). A bout of muscle-damaging exercise in the heat reduces cellular stress levels prior to and immediately following future exertional heat exposure.

The Influence of Energy Balance and Availability on Resting Metabolic Rate: Implications for Assessment and Future Research Directions.

Resting metabolic rate (RMR) is a significant contributor to an individual's total energy expenditure. As such, RMR plays an important role in body weight regulation across populations ranging from inactive individuals to athletes. In addition, RMR may also be used to screen for low energy availability and energy deficiency in athletes, and thus may be useful in identifying individuals at risk for the deleterious consequences of chronic energy deficiency. Given its importance in both clinical and research settings within the fields of exercise physiology, dietetics, and sports medicine, the valid assessment of RMR is critical. However, factors including varying states of energy balance (both short- and long-term energy deficit or surplus), energy availability, and prior food intake or exercise may influence resulting RMR measures, potentially introducing error into observed values. The purpose of this review is to summarize the relationships between short- and long-term changes in energetic status and resulting RMR measures, consider these findings in the context of relevant recommendations for RMR assessment, and provide suggestions for future research.

Storing urine samples with moisture preserves urine hydration marker stability up to 21 days.

INTRODUCTION: To assess hydration status, hydration markers [urine color, osmolality, and urine-specific gravity (USG)] are used. Urine color, osmolality, and USG have shown to be stable for 7, 7, and 3 days, respectively, at 4 °C. However, refrigeration could produce a dry environment which enhances evaporation and potentially affects urine hydration markers. PURPOSE: To examine the effect of duration and moisture on urine markers with refrigeration. METHODS: 24 participants provided urine samples between 9 and 10 AM. Urine color, osmolality, and USG were analyzed within 2 h (baseline). Then, each urine sample was divided into two urine cups and placed in a storage container with (moisture condition) and without (no moisture condition) water bath at 3 °C. Hydration markers were analyzed at day 1(D1), D2, D7, D10, D14, and D21. A two-way ANOVA (time x condition) and repeated-measures ANOVA on time were performed to examine differences. RESULTS: No significant (p > 0.05) condition x time effect was observed for urine color (p = 0.363), urine osmolality (p = 0.358), and USG (p = 0.248). When urine samples were stored in moisture condition, urine color (p = 0.126) and osmolality (p = 0.053) were stable until D21, while USG was stable until D2 (p = 0.394). CONCLUSION: When assessing hydration status, it appears that the urine color and osmolality were stable for 21 days, while USG was stable for 2 days when stored with moisture at 3 °C. Our results provide guidelines for practitioners regarding urine storage duration and conditions when urine cannot be analyzed immediately.

Plasma Proteomics-Based Discovery of Mechanistic Biomarkers of Hyperbaric Stress and Pulmonary Oxygen Toxicity.

Our aim was to identify proteins that reflect an acute systemic response to prolonged hyperbaric stress and discover potential biomarker pathways for pulmonary O2 toxicity. The study was a double-blind, randomized, crossover design in trained male Navy diver subjects. Each subject completed two dry resting hyperbaric chamber dives separated by a minimum of one week. One dive exposed the subject to 6.5 h of 100% oxygen (O2) at 2ATA. The alternate dive exposed the subjects to an enhanced air nitrox mixture (EAN) containing 30.6% O2 at the same depth for the same duration. Venous blood samples collected before (PRE) and after (POST) each dive were prepared and submitted to LC-MS/MS analysis (2 h runs). A total of 346 total proteins were detected and analyzed. A total of 12 proteins were significantly increased at EANPOST (vs. EANPRE), including proteins in hemostasis and immune signaling and activation. Significantly increased proteins at O2PRE (vs. O2POST) included neural cell adhesion molecule 1, glycoprotein Ib, catalase, hemoglobin subunit beta, fibulin-like proteins, and complement proteins. EANPOST and O2POST differed in biomarkers related to coagulation, immune signaling and activation, and metabolism. Of particular interest is (EANPOST vs. O2POST), which is protective against oxidative stress.

Environmental Stress Symptoms during Heat Acclimatization, Heat Acclimation, and Intermittent Heat Training.

BACKGROUND: Athletes training in heat experience physiological and perceptual symptoms that risk their safety and performance without adaptation. PURPOSE: We examined the changes in environmental symptoms, assessed with the Environmental Symptoms Questionnaire (ESQ), during heat acclimatization (HAz), heat acclimation (HA), and intermittent heat training (HT). METHODS: Twenty-seven participants (mean ± standard deviation [M ± SD], age of 35 ± 12 y, VO2max of 57.7 ± 6.8 mL·kg-1·min-1) completed five trials involving 60 mins of running (60% vVO2max) followed by a 4 km time trial in heat (M ± SD, temperature of 35.5 ± 0.7 °C, humidity of 46.4 ± 1.5%). The trials occurred at baseline, post-HAz, post-HA, at week 4 of HT (post-HT4), and at week 8 of HT (post-HT8). The participants completed HT once/week (HTMIN), completed HT twice/week (HTMAX), or did not complete HT (HTCON). ESQ symptoms, thermal sensation (TS), and heart rate (HR) were measured pre- and post-trial. RESULTS: Post-ESQ symptoms improved post-HA (3[0.40, 4.72], p = 0.02) and post-HAz (3[0.35, 5.05], p = 0.03) from baseline. During HT, symptoms improved in the HTMAX group and worsened in the HTMIN and HTCON groups. Symptoms improved in the HTMAX group versus the HTCON group at post-HT8 (4[1.02, 7.23], p = 0.012). Higher TS and HR values were weakly associated with ESQ symptoms during HT (r = 0.20, p = 0.04), only explaining 20% of variance. CONCLUSIONS: ESQ symptoms improved during HAz, HA, and HT 2x/week. ESQ symptoms were not statistically correlated with HR during exercise heat stress. TS was not sensitive to detecting adaptation and did not subjectively change. The ESQ may be valuable in monitoring adaptation and may contribute to performance post-acclimation.

Relationships Between WUT (Body Weight, Urine Color, and Thirst Level) Criteria and Urine Indices of Hydration Status.

BACKGROUND: A Venn diagram consisting of percentage body mass loss, urine color, and thirst perception (weight, urine, thirst [WUT]) has been suggested as a practical method to assess hydration status. However, no study to date has examined relationships between WUT and urine hydration indices. Thus, the purpose of this study was to investigate relationships between urine specific gravity, urine osmolality, and the WUT criteria. HYPOTHESIS: Urine specific gravity and urine osmolality indicate hypohydration when the WUT criteria demonstrate hypohydration (≥2 markers). STUDY DESIGN: Laboratory cohort study. LEVEL OF EVIDENCE: Level 3. METHODS: A total of 22 women (mean ± SD; age, 20 ± 1 years; mass, 65.4 ± 12.6 kg) and 21 men (age, 21 ± 1 years; body mass, 78.7 ± 14.6 kg) participated in this study. First morning body mass, urine color, urine specific gravity, urine osmolality, and thirst level were collected for 10 consecutive days in a free-living situation. Body mass loss >1%, urine color >5, and thirst level ≥5 were used as the dehydration thresholds. The number of markers that indicated dehydration levels were counted and categorized into either 3, 2, 1, or 0 WUT markers that indicated dehydration. One-way analysis of variance with Tukey pairwise comparisons was used to assess the differences in urine specific gravity and urine osmolality between the different number of WUT markers. RESULTS: Urine specific gravity in 3 WUT markers (mean ± SD [effect size], 1.021 ± 0.007 [0.57]; P = 0.025) and 2 WUT markers (1.019 ± 0.010 [0.31]; P = 0.026) was significantly higher than 1 WUT marker (1.016 ± 0.009). Urine mosmolality in 2 WUT markers (705 ± 253 mOsmol [0.43]; P = 0.018) was significantly higher than 1 WUT (597 ± 253 mOsmol). Meeting at 3 WUT resulted in specificity of 0.956 and at 0 WUT resulted in sensitivity of 0.937 for urine osmolality>700mOsm. CONCLUSION: These results suggest that when 3 WUT markers are met, urine specific gravity and urine osmolality indicated hypohydration and 0 WUT represents a high likelihood of euhydration. 1 and 2 WUT values are indeterminate of hydration status. The WUT criterion is a useful tool to use in field settings to assess hydration status when first morning urine sample was used. CLINICAL RELEVANCE: Athletes, coaches, sports scientists, and medical professionals can use WUT criteria to monitor dehydration with reduced cost and time.