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To reduce the adverse consequences of exertion-related and acute intentional dehydration research has focused on monitoring hydration status. This investigation: 1) compared sensitivity of urine specific gravity (U_sg), urine osmolality (U_osm) and a criterion measurement of hydration, plasma osmolality (P_osm), at progressive stages of acute hypertonic dehydration and 2) using a medical decision model, determined whether U_sg or U_osm accurately reflected hydra-tion status compared to P_osm among 51 subjects tested throughout the day. Incremental changes in P_osm were observed as subjects dehydrated by 5% of body weight and rehydrated while U_sg and U_osm showed delayed dehydration-related changes. Using the medical decision model, sensitivity and specificity were not significant at selected cut-offs for U_sg and U_osm. At the most accurate cut-off values, 1.015 and 1.020 for U_sg and 700 m_osm/kg and 800 m_osm/kg for U_osm, only 65% of the athletes were correctly classified using U_sg and 63% using U_osm. P_osm, U_sg, and U_osm appear sensitive to incremental changes in acute hypertonic dehydration, however, the misclassified outcomes for U_sg and U_osm raise concerns. Research focused on elucidating the factors affecting accurate assessment of hydration status appears warranted.

Although dehydration of ≥ 2% body weight (BW) loss significantly impairs endurance performance, dehydration remains prevalent among athletes and may be owing to a lack of knowledge in relation to fluid requirements. The aim of this study was to assess the hydration status of university/club level athletes (n = 430) from a range of sports/activities (army officer cadet training; bootcamp training; cycling; Gaelic Athletic Association camogie, football and hurling; golf; hockey; netball; rugby; running (sprinting and endurance); Shotokan karate and soccer) immediately before and after training/competition and to assess their nutritional knowledge. Urine specific gravity (USG) was measured immediately before and after exercise and BW loss during exercise was assessed. Nutritional knowledge was assessed using a validated questionnaire. 31.9% of athletes commenced exercise in a dehydrated state (USG >1.020) with 43.6% of participants dehydrated posttraining/competition. Dehydration was particularly prevalent (>40% of cohort) among karateka, female netball players, army officer cadets, and golfers. Golfers that commenced a competitive 18 hole round dehydrated took a significantly higher number of strokes to complete the round in comparison with their euhydrated counterparts (79.5 ± 2.1 vs. 75.7 ± 3.9 strokes, p = .049). Nutritional knowledge was poor among participants (median total score [IQR]; 52.9% [46.0, 59.8]), albeit athletes who were euhydrated at the start of exercise had a higher overall score in comparison with dehydrated athletes (55.2% vs. 50.6%, p = .001). Findings from the current study, therefore, have significant implications for the education of athletes in relation to their individual fluid requirements around exercise.

Runners are unlikely to consume fluid during training bouts increasing the importance of recovery rehydration efforts. This study assessed urine specific gravity (U_SG) responses following runs in the heat with different recovery fluid intake volumes. Thirteen male runners completed 3 evening running sessions resulting in approximately 2,200 ± 300 ml of sweat loss (3.1 ± 0.4% body mass) followed by a standardized dinner and breakfast. Beverage fluid intake (pre/postbreakfast) equaled 1,565/2,093 ml (low; L), 2,065/2,593 ml (moderate; M) and 2,565/3,356 mL (high; H). Voids were collected in separate containers. Increased urine output resulted in no differences (p > .05) in absolute mean fluid retention for waking or first postbreakfast voids. Night void averages excluding the first void postrun (1.025 ± 0.008; 1.013 ± 0.008; 1.006 ± 0.003), first morning (1.024 ± 0.004; 1.015 ± 0.005; 1.014 ± 0.005), and postbreakfast (1.022 ± 0.007; 1.014 ± 0.007; 1.008 ± 0.003) U_SG were higher (p < .05) for L versus M and H respectively and more clearly differentiated fluid intake volume between L and M than color or thirst sensation. Waking (r = -0.66) and postbreakfast (r = -0.71) U_SG were both significantly correlated (p < .001) with fluid replacement percentage, but not absolute fluid retention. Fluid intake M was reported as most similar to normal consumption (5.6 ± 1.0 on 0–10 scale) after breakfast and equaled 122 ± 16% of sweat losses. Retention data suggests consumption above this level is not warranted or actually practiced by most runners drinking ad libitum, but that periodic prerun U_SG assessment may be useful for coaches to detect runners that habitually consume low levels of fluids between training bouts in warm seasons.

This investigation determined if 3 levels of controlled caffeine consumption affected fluid-electrolyte balance and renal function differently. Healthy males (mean ± standard deviation; age, 21.6 ± 3.3 y) consumed 3 mg caffeine · kg⁻¹ · d⁻¹ on days 1 to 6 (equilibration phase). On days 7 to 11 (treatment phase), subjects consumed either 0 mg (C0; placebo; n = 20), 3 mg (C3; n = 20), or 6 mg (C6; n = 19) caffeine · kg⁻¹ · d⁻¹ in capsules, with no other dietary caffeine intake. The following variables were unaffected (P > 0.05) by different caffeine doses on days 1, 3, 6, 9, and 11 and were within normal clinical ranges: body mass, urineosmolality, urine specific gravity, urine color, 24-h urine volume, 24-h Na⁺ and K⁺ excretion, 24-h creatinine, blood urea nitrogen, serum Na⁺ and K⁺, serum osmolality, hematocrit, and total plasma protein. Therefore, C0, C3, and C6 exhibited no evidence of hypohydration. These findings question the widely accepted notion that caffeine consumption acts chronically as a diuretic.

The aim of this study was to compare daily hydration profiles of competitive adolescent swimmers and less active maturation- and sex-matched controls. Hydration profiles of 35 competitive adolescent swimmers (male n = 18, female n = 17) and 41 controls (male n = 29, female n = 12) were monitored on 4 consecutive days. First morning hydration status was determined independently by urine specific gravity (USG) and urine color. Changes in fluid balance were estimated during the school day and in training sessions after adjusting for self-reported urine losses and fluid intake. Urinalyses revealed consistent fluid deficits (USG >1.020, urine color ≥5) independent of activity group, sex, and day of testing (hypohydration in 73–85% of samples, p > .05). Fluid balance and intake were observed over typical school days in males and females from the 2 groups. During training, male swimmers lost more fluid relative to initial body mass but drank no more than females. Although both activity groups began each testing day with a similar hydration status, training induced significant variations in fluid balance in the swimmers compared with controls. Despite minimal fluid losses during individual training sessions (<2% body mass), these deficits significantly increased fluid needs for young swimmers over the school day.

This study investigated the relationship between changes in upon-waking body mass (BM) and changes in urine specific gravity (U_sg) and urine color (U_col) from 1 day to the next. Throughout the 5-day investigation, healthy adolescent Singaporean athletes (n = 66) had their upon-waking, bladder-voided BM measured. A small aliquot of the first bladder void each day was collected and analyzed for U_sg and U_col, the latter by both an investigator (IU_col) and individual participants (SU_col). Results revealed a significant inverse relationship between changes in BM and changes in U_sg (p = .003) and U_col (p = .001). On average, U_sg and U_col changed by ~0.003 units and ~1 color (across a 9-unit scale), respectively, with every 1% change in BM from 1 day to the next. There was a stronger relationship between U_sg and IU_col (r = .82, p < .001) than between U_sg and SU_col (r = .60, p < .001). These results suggest that the degree of fluid deficit may be predicted from the U_sg measurements among moderately hypohydrated athletes. In addition, training athletes to interpret and use the U_col chart is recommended.