The accuracy of a 4-item hydration self-assessment model to classify urine concentration using different cut-offs.

Background: Hydration is important for health and performance, but accurate self-assessment methods for active populations are limited. The study objective was to determine a model to classify by self-assessment a low vs. high 24-hour urine concentration, and to determine the accuracy of morning vs. afternoon assessments. The study describes the development and validation of a self-assessment model through exploratory modeling, using stepwise logistic regression. The aim was to determine which hydration markers predict urine specific gravity (using two different USG cut-offs: low ≤ 1.012, and high ≥ 1.020), in two intentionally overlapping 24-hour urine collections leading up to a morning and afternoon hydration self-assessment, and to assess its diagnostic accuracy based on the area under the curve (AUC). Results: A total of of Conclusion: This 4-item hydration self-assessment model classifies a low vs. high USG acceptable, with slightly higher accuracy in the afternoon. This insight may inform targeted hydration monitoring strategies in occupational settings, for example among WLFFs. Supplementary Information: The online version contains supplementary material available at 10.1186/s44410-026-00024-y.