Combining Four Self-assessed Measurements Accurately Detects Low Vs. High Urine Concentration In Wildland Firefighters

PURPOSE: Optimizing hydration may help wildland firefighters maintain performance capacity. This study aimed to determine if a combination of simple hydration self-assessment measurements could help to classify a low vs. high 24-hour urine concentration in which a low concentration suggests a good hydration status. METHODS: A stepwise logistic regression was run including twelve hydration markers as noted below Table 1 to predict a low urine concentration (USG ≤ 1.012, “euhydrated”) vs. a high urine concentration (USG ≥1.013, “underhydrated”). Variables were retained in the model based on significance (P ≤ 0.10), and practical relevance, aiming for a high diagnostic ability, based on area under the curve (AUC), sensitivity, and specificity. For the final model, each variable was scored 0/1, with a higher score suggesting a lower urine concentration. Risk score quadrants were plotted to determine the urine concentration score cut-off, and then a cross table was generated to show the best model fit. RESULTS: A total of 58 participants (age: 30 ± 6 years, 90% male) provided data resulting in a 4-item model, suggesting that a score of 0-2 resulted in a high, and score of 3-4 resulted in a low urine concentration, respectively. The items included self-reported fluid intake (sex-dependent, male ≥3.8 L, female ≥2.7 L scored as 1 vs 0 for lower volume), urine frequency (≥7 scored as 1 vs 0 for lower frequency), morning void urine volume (≥4 fl oz, or 120 mL, scored as 1 vs 0 for lower volume), and morning urine color (color 1-2 scored as 1 vs 0 for colors 3-7). This model had a good overall diagnostic ability (AUC = 87%) and classified 78% of the samples correctly with high sensitivity (0.90) to identify a low urine concentration, and moderate specificity (0.64) to identify a high urine concentration (Table 1). CONCLUSION: This new model has a very high sensitivity to determine a low urine concentration, indicating adequate hydration over a 24-hour period or fluid intake should be adjusted. Table 1. - The classification of actual urine concentration vs. hypothesized urine concentration based on a 4-item self-assessment model with a cut-off value of ≤1.012 USG in n=58 wildland firefighters, including true positive, false negative, true negative and false positive classifications, specificity and sensitivity. Low USG ≤1.012 High USG ≥1.013 Total Score 3-4 “Hypothesizing a low urine concentration”, % (n) 47% (27) 17% (10) 64% (37) Score 0-2 “Hypothesizing a high urine concentration”, % (n) 5% (3) 31% (18) 36% (21) (sub)Total, % (n) 52% (30) 48% (28) 100% (58) Hypothesized low concentration (Positive, n) TP FP Sensitivity 27 10 90% Hypothesized high concentration (Negative, n) FN TN Specificity 3 18 64% Note. The Chi-square analysis including a low vs. high urine concentration vs. hypothesized urine concentration was not significantly different (χ2 (1) = 1.180, P=0.277) suggesting a balanced distribution within this 2x2 table.TP= True Positive; FP= False Positive; FN= False Negative; TN= True Negative; Sensitivity (correctly classifying having a low USG) = TP / (TP+FN); Specificity (correctly classifying having a high USG) = TN / (TN+FP).The 4-item model was selected after regression analysis including the following variables: Body weight change, thirst (willing to drink water, thirst intensity, and thirst distress in the morning), self-reported fluid intake, urine color (measured with a paper color chart and a 3D color chart), self-reported 24-hour urine frequency, morning sample urine volume, morning void duration in seconds, heart rate and blood pressure in rest). Supported by: FEMA FP&S Research Award: EMW-2022-FP-00082