Marcos S. Keefe

The purpose of this study was to determine whether the trajectory and magnitude of physiological adaptation to controlled work rate heat acclimation (HEAT) differ between male and female highly trained endurance runners, while comparing adaptations with work rate matched temperate exercise training (TEMP). Eighteen highly trained endurance runners (8 males, 10 females) completed two seven-session interventions consisting of HEAT (40°C, 35% relative humidity [RH]) and TEMP (22°C, 35% RH) in a randomized, counterbalanced crossover design. Each session consisted of 60 min of running at 50% of velocity at maximal oxygen uptake. Physiological adaptation was quantified as the change (Δ) relative to session 1 for core temperature (T _c ), skin temperature, heart rate (HR), whole-body sweat rate (WBSR), and plasma volume (PV). No intervention × sex × session interactions were observed for T _c , HR, or WBSR (p > 0.05), indicating that the trajectory of adaptation did not differ between sexes or interventions. Likewise, no sex differences in the overall magnitude of adaptation were observed for any HEAT outcome. Significant main effects of intervention demonstrated greater reductions in mean and peak T _c ; baseline, mean, and peak HR; as well as greater increases in WBSR during HEAT compared with TEMP (p < 0.05). PV did not change following either intervention. Male and female highly trained endurance runners exhibited comparable thermoregulatory and cardiovascular adaptation to controlled work rate heat acclimation. Although work rate matched temperate exercise induced partial physiological adaptation, environmental heat stress enhanced the overall adaptation magnitude without altering the adaptation trajectory between sexes.

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Background: Sleep is negatively affected by muscle-damaging exercise, but it remains unknown whether hot environmental conditions further affect sleep. Hypothesis: Sleep quality would decline, but sleep quantity would be longer after experiencing both heat exposure and EIMD. Study Design: Crossover study. Level of Evidence: Level 3. Methods: In a randomized, counterbalanced order, 10 healthy males (mean ± SD: age, 23 ± 3 years; body mass, 78.7 ± 11.5 kg; height, 176.9 ± 5 cm; lactate threshold [LT], 9.7 ± 1.0 km h ^-1 ) performed 30 min of downhill running (DHR) at -10% gradient at the LT in control (ambient temperature [ T _amb ], 20°C; relative humidity [RH], 20%) and hot conditions ( T _amb , 35°C; RH, 40%). Seven days later, participants performed a flat 45-min run in the heat at LT. Sleep parameters were collected from a wearable device the night after DHR, the following 6 nights, and the night of the 45-min flat run. Differences in sleep parameters between conditions following DHR, the subsequent 6 nights, and the night of the 45-min run were analyzed using repeated measures analysis of variance (ANOVA). Results: Following DHR, total sleep time (6.7 ± 0.7 h vs 5.2 ± 1.8 h; P = 0.040), rapid eye movement (REM; 1.7 ± 0.6 h vs 1.2 ± 0.7 h; P = 0.046), and slow-wave sleep (SWS; 1.6 ± 0.4 h vs 1.2 ± 0.5 h; P = 0.015) were greater in the hot condition. However, REM% and SWS% did not differ ( P > 0.05), indicating increases reflected longer sleep duration rather than altered architecture. Sleep efficiency, light sleep, resting heart rate, heart rate variability, and respiratory rate were also unchanged ( P > 0.05). No differences were observed across the subsequent 6 nights or after the flat run ( P > 0.05). Conclusion: Sleep duration increased on the night after muscle-damaging exercise in hot conditions, with greater REM and SWS reflecting longer sleep rather than altered architecture. Clinical Relevance: Individuals from various populations, including athletes, military, occupational workers, and the general public may participate in exercise under heat stress, requiring awareness of potential sleep disturbances following exercise in hot conditions.

Introduction: Oral rehydration reduces thirst sensation (TS), which may negatively affect autonomic function, measured by heart-rate variability (HRV). However, it is unclear if this effect is independent of hydration changes. This study examines whether TS influences autonomic function between intravenous and oral rehydration. Methods: Twelve males (mean ± SD; age, 29 ± 12 years; 74.7 ± 7.9 kg; 179.4 ± 7.0 cm; VO2_max, 49.8± 6.6 mL·kg⁻¹·min⁻¹) cycled at 55% VO_2max for 90 min followed by a 12 km time trial. Two experimental conditions were performed in a counterbalanced, randomized order; (a) the high thirst (HT) group were infused 25 mL of isotonic saline every 5 min via an intravenous tube, and (b) the low thirst (LT) group ingested 25 mL of water every 5 min. TS and heart rate were collected every 5 min. HRV was assessed pre exercise, post steady-state exercise, and post time trial. HRV parameters included time domain, frequency domain, and non-linear measures analyzed by two-way repeated measures ANOVA. Results: There was a significant time x condition for the root mean square of successive RR interval differences (RMSSD_log), high-frequency (HF) power, and SD1 (p < 0.05). In LT, RMSSD_log decreased from Pre to Mid (3.71 ± 0.61 ms to 2.53 ± 1.15 ms, p < 0.01) and Pre to Post (2.18 ± 0.90 ms, p < 0.01) but stabilized from Mid to Post (p = 0.39). High-frequency (HF) power in HT was maintained from Pre (3.7 ± 0.6 nu) to Mid (3.4 ± 0.8 nu, p = 0.21) but decreased from Pre to Post (2.5 ± 0.7 nu, p < 0.01) and Mid to Post (p < 0.01). LT decreased in HF power from Pre (3.7 ± 0.5 nu) to Mid (3.0 ± 0.8 nu, p < 0.01) and Pre to Post (3.0 ± 0.7 nu, p < 0.01); Mid and Post was maintained (p = 0.99). SD1, decreased in HT (Pre: 3.4 ± 0.4 ms, Mid: 2.0 ± 1.1 ms, Post: 1.1 ± 0.5 ms; all comparisons p < 0.05). In LT, SD1 decreased from Pre (3.4 ± 0.6 ms) to Mid (2.18 ± 1.15 ms, p < 0.01) and Pre to Post (1.83 ± 0.90 ms, p < 0.01), but stabilized Mid to Post (p = 0.39). Conclusion: Satiating thirst through oral rehydration increases parasympathetic activity post exercise, reducing stress and increasing recovery between exercise bouts. These findings have implications for optimizing rehydration strategies in sports and occupational settings.

Objectives: The WUT (weight, urine color, thirst) Venn diagram has been demonstrated as a practical tool for hydration assessment. However, no investigations have examined if there are sex differences in the accuracy of this method. Therefore, the purpose of this study was to explore potential sex differences in the accuracy of the WUT Venn diagram for hydration status determination. Methods: 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 color, urine specific gravity (USG), urine osmolality (UOSM), thirst level, and plasma osmolality (POSM) were collected at first-morning and afternoon visits for three consecutive days in free-living and euhydrated states. The number of markers indicating dehydration levels were categorized 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. Results: WUT2 and WUT3 resulted in high specificity values in comparison to USG (WUT2—male: 0.912, female: 0.949; WUT3—male: 0.991, female: 1.000), UOSM (WUT2—male: 0.901, female: 0.946; WUT3—male: 0.991, female: 1.000), and POSM (WUT2—male: 0.859, female: 0.896 WUT3; male: 0.977, female: 0.991). WUT1 resulted in high sensitivity values compared to USG (male: 0.931, female: 0.857), but varied between sexes for UOSM (male: 0.875, female: 0.794) and POSM (male: 0.469, female:0.536). Conclusions: The WUT Venn diagram accurately detects dehydration when two or three WUT markers are met in both males and females. The WUT Venn diagram accurately assesses hydration status in males and females, thus providing medical personnel and athlete support teams a cost-effective and time-efficient hydration testing tool.

Performing exercise in hot environmental conditions presents athletes with potential negative physiological and perceptual implications. Key constituents, such as fluid and electrolytes, are lost during sweating through the process of cooling the human body. The loss of electrolytes impairs exercise performance. Heat training is one strategy to combat sweat electrolyte loss, with decreased sweat electrolyte concentration being a main sudomotor adaptation. To measure sweat electrolyte concentration, two common assessment methods are typically utilized: whole-body washdown and regional sweat patch measurements. The effects of physiological adaptations and sweat electrolyte assessment methodology have been investigated; however, the importance of methodological differences between sweat electrolyte measurements following heat training has yet to be explored. This review explores the differences between sweat electrolyte measurement techniques following adaptations incurred with heat training. Future research directions are also provided.

Purpose: To investigate the effects of thirst on later hydration status, total water intake (TWI-MA), and its potential sex differences. Methods: Twelve men (mean ± standard deviation; age: 21 ± 2 years; mass: 81.0 ± 15.9 kg) and twelve women (age: 22 ± 3 years; mass: 68.8 ± 15.2 kg) visited the laboratory in the morning (first thing in the morning) and afternoon (2:00–4:00 p.m.) for three consecutive days under a free-living condition. At each visit, urine osmolality (U_OSM), urine specific gravity (USG), urine color (U_COL), body mass loss (BML), thirst, and plasma osmolality (P_OSM) were collected and analyzed. The participants recorded their food and fluid intake between the visits to determine TWI-MA. Linear regression was used to predict the effect of morning thirst on the afternoon hydration indices for all the participants, as well as for males and females separately. Results: Higher morning thirst predicted lower U_OSM (r² = 0.056, p = 0.045), USG (r² = 0.096, p = 0.008), U_COL (r² = 0.074, p = 0.021), and higher thirst (r² = 0.074, p = 0.021) in the afternoon. However, morning thirst did not predict afternoon BML, P_OSM, or TWI-MA (p > 0.05). In males, higher morning thirst predicted lower afternoon U_OSM (r² = 0.130, p = 0.031) and USG (r² = 0.153, p = 0.018). Additionally, higher morning thirst predicted higher TWI-MA (r² = 0.154, p = 0.018) in females. Conclusions: Morning thirst had a negligible impact on later hydration status, specifically with afternoon urine indices. Furthermore, higher thirst sensation did not impact BML, P_OSM, or TWI-MA. However, thirst sensation minimally contributed to drinking behavior in females. Overall, individuals may not rely solely on thirst sensation to manipulate their drinking behavior to optimize their fluid balance during their daily lives due to the complexity of thirst mechanisms.