Urine color has been shown to be a viable marker of hydration status in healthy adults. Traditionally, urine color has been measured using a subjective color scale. In recent years, tristimulus colorimetry developed by the International Commission on Illumination (CIE L^*a^*b^*) has been widely adopted as the reference method for color analysis. In the L^*a^*b^* color space, L^* indicates lightness ranging from 100 (white) to 0 (black), while a^* and b^* indicate chromaticity. a^* and b^* are color directions: –a^* is the green axis, +a^* is the red axis, –b^* is the blue axis, and +b^* is the yellow axis. The L^*a^*b^* color space model is only accurately represented in three-dimensional space. Considering the above, the purpose of the current study was to evaluate urine color during different hydration states, with the results expressed in CIE L^*a^*b^* color space. The study included 28 healthy participants (22 males and 6 females) ranging between the age of 20 and 67 years (28.6 ± 11.3 years). One hundred and fifty-one urine samples were collected from the subjects in various stages of hydration, including morning samples after 7–15 h of water deprivation. Osmolality and CIE L^*a^*b^* parameters were measured in each sample. As the urine osmolality increased, a significant linear increase in b^* values was observed as the samples became more pronouncedly yellow (τ_b = 0.708). An increase in dehydration resulted in darker and significantly more yellow urine, as L^* values decreased in lightness and b^* values increased along the blue–yellow axis. However, as dehydration increased, a notable polynomial trend in color along the green–red axis was observed as a^* values initially decreased, indicating a green hue in slightly dehydrated urine, and then increased as urine became more concentrated and thus more dehydrated. It was determined that 74% of the variance seen in urine osmolality was due to CIE L^*a^*b^* variables. This newfound knowledge about urine color change along with the presented regression model for predicting urine osmolality provides a more detailed and objective perspective on the effect of hydration on urine color, which to our knowledge has not been previously researched.

To investigate how rapid changes in hydration affect urine color expressed in CIE L*a*b* colorspace. This study was a two-day crossover design where subjects (N = 30) came in one visit dehydrated, after a 15 h overnight fluid deprivation, and rapidly rehydrated by drinking at least 1000 mL of water in 2 h. On the other visit subjects reported euhydrated and then rapidly dehydrated 2% by walking (3 mph) in a heat chamber (100°F, 50% humidity) for 2 h. Urine samples on both days were collected pre- and post-dehydration/rehydration. Urine osmolality, urine specific gravity, subjective urine color and objective urine color expressed in CIE L*a*b* colorspace were measured. In the dehydration trial participants experienced a significant weight loss of approximately 2% of their starting, euhydrated body weight. The CIE urine color L*-value significantly decreased (−2.3 units) while the b*-value significantly increased (16 units). Subjective urine color significantly increased (1 unit). Urine osmolality increased (25 mmol/kg) and urine specific gravity increased (0.002 g/mL) between the pre- and post-dehydration conditions, however, neither of these changes were statistically significant. In the rehydration trial participants had a significant 1.5% increase in body weight after the ingestion of water. Significant increases were observed in the CIE urine color L*-value (7 units) and a*-value (1.1 units), while the b*-value significantly decreased (−24 units). Subjective urine color significantly decreased (−3 units). Urine osmolality (−600 mmol/kg) and urine specific gravity (−0.018 g/mL) significantly decreased between the pre- and post-rehydration conditions. Traditional markers of hydration, including urine osmolality and urine specific gravity, did not significantly change in the acute dehydration trial, suggesting that these values may not be responsive to rapid changes in hydration status. However, the CIE L*- and b*-values of urine color significantly decreased in the rapid dehydration trial and significantly increased in the rapid rehydration trial. Thus, the results of the current study suggest that urine color L*- and b*-values expressed in the CIE L*a*b* colorspace were more responsive to changes in hydration status during rapid dehydration than traditional indices of urine concentration and thus may be better markers under such conditions.

It is well known that there is a high concentration of lactate in sweat. Interest in measuring sweat lactate has arisen from its potential role in several clinical and sport performance applications. However, the effect of heat acclimation on sweat lactate concentration is still under debate. This is partly because sweat lactate concentration is greatly affected by sweat rate, which is known to increase during heat acclimation. Thus, to better understand this issue it is necessary to account for sweat rate - which has not been done previously in the literature. Therefore, the purpose of the current study was to determine the effect of heat acclimation on the relationship between sweat rate vs. sweat lactate concentration. Six subjects completed a 7-day heat acclimation protocol. The daily 2-h exercise bout was split into three 40-min intervals with exercise intensity increasing with each successive interval. This was done to induce three different sweat rates to determine the sweat rate vs. sweat lactate concentration relationship before and after heat acclimation for each participant. A 2 (heat acclimation) x 3 (sweat rate) repeated measures ANOVA was conducted to determine statistical significance. There was a significant (p < 0.05) decrease in the grand mean sweat lactate concentration over the course of seven days of heat acclimation from 17.0 ± 5.0 to 11.3 ± 1.1 mmol/L (p < 0.05). A significant (p < 0.05) heat acclimation x sweat rate ordinal interaction was also found. The results of the current study show that heat acclimation significantly decreases the sweat lactate concentration. In addition, there was a significant ordinal interaction which suggests that the impact of sweat rate on sweat lactate concentration is decreased following heat acclimation.

Heat exposure’s effect on glucose tolerance depends on the amount of body exposed, likely relating to autonomic nervous system balance. We assessed how partial-body heat exposure at two different levels of the lower extremities affects glucose tolerance and autonomic nervous system balance, measured via heart rate variability. We hypothesized feet-heating would improve glucose tolerance without affecting heart rate variability, while calf-heating would worsen glucose tolerance and decrease heart rate variability compared to a thermoneutral control condition. In a randomized, controlled, crossover trial, healthy participants’ ( N = 31, 23(3) years, 45% male) glucose tolerance was measured in (A) thermoneutral; (B) feet-heating; and (C) calf-heating conditions. Every 30 min for 2 h, blood glucose, heart rate, heart rate variability, tympanic temperature, thermal comfort scores, and blood pressure were measured. There were significant interactions between condition and time for blood glucose ( F (4.6,72.6) = 2.6, p = 0.036), heart rate ( F (3.4, 54.5) = 3.5, p = 0.017), heart rate variability ( F (4.3,63.2) = 7.5, p < .0001), tympanic temperature ( F (8, 268) = 2.4, p = 0.014), and thermal comfort scores ( F (8, 248) = 22.1, p < 0.0001). Calf-heating increased 90 min glucose (+12 (95% confidence interval, CI: 3–21) mg/dL, p = 0.013) and decreased heart rate variability throughout (mean decrease: 13%–22%, p < 0.007), while feet-heating lowered 90 min glucose (−7 (95% CI: −16 to +1) mg/dL, p = 0.090) without affecting heart rate variability ( p = 0.14–0.99). Blood pressure and body temperature were similar between conditions, but heart rate and thermal comfort scores increased with heating. Calf-heating worsens, while feet-heating may improve, glucose tolerance. Changes in heart rate variability coincided with changes in glucose tolerance despite unchanged body temperature. Whether heart rate variability can be used to monitor autonomic nervous system balance during heating to optimize its acute effect on glycemic indices should be further explored.