ArticleEuropean journal of nutrition2024
Validity of combined hydration self-assessment measurements to estimate a low vs. high urine concentration in a small sample of (tactical) athletes.
Article in European journal of nutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- The accuracy of a 4-item hydration self-assessment model to classify urine concentration using different cut-offs.Performance nutrition · 2026Article
- Hydration Assessment in Males and Females Using the WUT (Weight, Urine Color, and Thirst) Venn Diagram Compared to Blood and Urinary Indices.Nutrients · 2025Article
- A 3D color model reports urine color similarly to a printed color chart with similar accuracy to determine a low vs. high urine concentration.Performance nutrition · 2025Article
- Association between Urine Specific Gravity as a Measure of Hydration Status and Risk of Type 2 Diabetes: The Kailuan Prospective Cohort Study.Nutrients · 2024Article
- 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 British journal of nutrition · 2024Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeRelationships between body weight, urine color (Uc), and thirst level (WUT) have been proposed as a simple and inexpensive self-assessment method to predict dehydration. This study aimed to determine if this method also allowed us to accurately identify a low vs. high urine concentration in (tactical) athletes.
methodsA total of n = 19 Army Reserve Officer Training Corps cadets and club sports athletes (22.7 ± 3.8 years old, of which 13 male) were included in the analysis, providing morning body weight, thirst sensation, and Uc for five consecutive days. Each item received a score 0 or 1, resulting in a WUT score ranging from 0 (likely hydrated) to 3 (very likely dehydrated). WUT model and individual item outcomes were then compared with a ≥ 1.020 urine specific gravity (USG) cut-off indicating a high urine concentration, using descriptive comparisons, generalized linear mixed models, and logistic regression (to calculate the area under the curve (AUC)).
resultsWUT score was not significantly predictive of urine concentration, z = 1.59, p = 0.11. The AUC ranged from 0.54 to 0.77 for test days, suggesting a fair AUC on most days. Only Uc was significantly related to urine concentration, z = 2.49, p = 0.01. The accuracy of the WUT model for correctly classifying urine samples with a high concentration was 68% vs. 51% of samples with a low concentration, resulting in an average accuracy of 61%.
conclusionThis study shows that WUT scores were not predictive of urine concentration, and the method did not substantially outperform the accuracy of Uc scoring alone.
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