Exploring Psychosocial Determinants Of Hydration Biomarkers In Young Adult Males

PURPOSE: Previous work has identified associations between attitudes about hydration and fluid intake behaviors, but the association between these psychosocial factors and hydration biomarkers has not been evaluated. The purpose of this study was to explore the relationship between psychosocial factors contributing to fluid intake (hydration-related knowledge, attitudes, and behaviors) and hydration biomarkers in young adult males. METHODS: Thirty males (mean ± SD; age, 23 ± 4 y; height, 175 ± 6 cm; weight, 79.8 ± 14.2 kg; body fat, 17.4 ± 9.4 %) collected 24 h urine samples for 4 consecutive days to assess mean urine volume (UVOL), urinary osmolality (UOSMO), urinary specific gravity (USG) and urine color (UCOL). A fasted blood draw was obtained on day 4 to assess serum copeptin. Participants also completed three validated surveys on day 4 to assess hydration knowledge (Hydration Knowledge Scale - K), attitudes (Hydration Facilitators and Barriers - A), and behaviors (Fluid Behavior Index - B). Outcomes from the K, A, and B questionnaires were used as continuous predictors of hydration biomarkers in separate regression models for each domain and hydration biomarker, respectively. RESULTS: Higher K was associated with higher UVOL (β = 0.061, [0.003, 0.120], p = 0.041), but no other hydration biomarker. More perceived barriers, specifically related to “Lack of Effort,” were associated with higher UOSMO (β = 38.5, [7.6, 69.1], p = 0.017), higher USG (β = 0.001, [0.000,0.002], p = 0.024), darker UCOL (β = 0.2 [0.01, 0.35], p = 0.038), but not UVOL (p = 0.569). No other barriers were associated with any hydration biomarkers (p > 0.05). Higher scores on the Fluid Behavior Index, reflective of behaviors associated with greater fluid consumption, were associated with lower UOSMO (β = -71.65, [-120.86, -22.43], p = 0.006), USG (β = -0.002, [-0.003, -0.004e-1], p = 0.011) and lower copeptin (β = -0.57, [-1.13, -0.02], p = 0.043), lighter UCOL (β = -0.4 [-0.6, -0.1], p = 0.008), but not UVOL (p = 0.07). CONCLUSIONS: Knowledge about hydration appears to have limited influence on hydration biomarkers, while behaviors captured by the Fluid Behavior Index (e.g., keeping a beverage within arm’s reach, drinking fluids even when not thirsty) were associated with improvements in hydration biomarkers in healthy, young males. This study was supported by Adams Sports Medicine Consulting LLC and Emerja Corporation, Inc.

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Journal
Medicine & Science in Sports & Exercise
Published
2024-09-16
DOI
https://doi.org/10.1249/01.mss.0001058148.49933.92
Primary Topic
Thermoregulation and physiological responses
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article
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article

Exploring Psychosocial Determinants Of Hydration Biomarkers In Young Adult Males

Jessica McNeil, Mitchell E. Zaplatosch, Lenka H. Shriver, Jesse N. L. Sims et al.
Medicine & Science in Sports & Exercise
Thermoregulation and physiological responses
article

Exploring Psychosocial Determinants Of Hydration Biomarkers In Young Adult Males

Jessica McNeil, Mitchell E. Zaplatosch, Lenka H. Shriver, Jesse N. L. Sims, Laurie Wideman, William M. Adams
article en

Abstract

PURPOSE: Previous work has identified associations between attitudes about hydration and fluid intake behaviors, but the association between these psychosocial factors and hydration biomarkers has not been evaluated. The purpose of this study was to explore the relationship between psychosocial factors contributing to fluid intake (hydration-related knowledge, attitudes, and behaviors) and hydration biomarkers in young adult males. METHODS: Thirty males (mean ± SD; age, 23 ± 4 y; height, 175 ± 6 cm; weight, 79.8 ± 14.2 kg; body fat, 17.4 ± 9.4 %) collected 24 h urine samples for 4 consecutive days to assess mean urine volume (UVOL), urinary osmolality (UOSMO), urinary specific gravity (USG) and urine color (UCOL). A fasted blood draw was obtained on day 4 to assess serum copeptin. Participants also completed three validated surveys on day 4 to assess hydration knowledge (Hydration Knowledge Scale - K), attitudes (Hydration Facilitators and Barriers - A), and behaviors (Fluid Behavior Index - B). Outcomes from the K, A, and B questionnaires were used as continuous predictors of hydration biomarkers in separate regression models for each domain and hydration biomarker, respectively. RESULTS: Higher K was associated with higher UVOL (β = 0.061, [0.003, 0.120], p = 0.041), but no other hydration biomarker. More perceived barriers, specifically related to “Lack of Effort,” were associated with higher UOSMO (β = 38.5, [7.6, 69.1], p = 0.017), higher USG (β = 0.001, [0.000,0.002], p = 0.024), darker UCOL (β = 0.2 [0.01, 0.35], p = 0.038), but not UVOL (p = 0.569). No other barriers were associated with any hydration biomarkers (p > 0.05). Higher scores on the Fluid Behavior Index, reflective of behaviors associated with greater fluid consumption, were associated with lower UOSMO (β = -71.65, [-120.86, -22.43], p = 0.006), USG (β = -0.002, [-0.003, -0.004e-1], p = 0.011) and lower copeptin (β = -0.57, [-1.13, -0.02], p = 0.043), lighter UCOL (β = -0.4 [-0.6, -0.1], p = 0.008), but not UVOL (p = 0.07). CONCLUSIONS: Knowledge about hydration appears to have limited influence on hydration biomarkers, while behaviors captured by the Fluid Behavior Index (e.g., keeping a beverage within arm’s reach, drinking fluids even when not thirsty) were associated with improvements in hydration biomarkers in healthy, young males. This study was supported by Adams Sports Medicine Consulting LLC and Emerja Corporation, Inc.

Medicine & Science in Sports & ExerciseVol. 56(10S)
University of North Carolina at Greensboro (US), Kennesaw State University (US), United States Olympic & Paralympic Committee (US)
Openalex Percentile: Top 79%
Thermoregulation and physiological responses
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