The Effect of Hydration on Urine Color Objectively Evaluated in CIE L^*a^*b^* Color Space

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.