Blood, Sweat, and Tears: Implications for Hydration Testing in Combat Sports—Investigating Body Mass Loss and Biomarker Changes

ABSTRACT Combat sports athletes often undergo rapid body mass loss (BML), which presents health risks. Hydration testing has been proposed as a possible solution to reduce or eliminate rapid BML. However, combat sports athletes may exhibit distinct physiological characteristics due to repeated expos...

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Veröffentlicht in:Scandinavian journal of medicine & science in sports 2024-08, Vol.34 (8), p.e14701-n/a
Hauptverfasser: Doherty, Colin S., Fortington, Lauren V., Barley, Oliver R.
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container_issue 8
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container_title Scandinavian journal of medicine & science in sports
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creator Doherty, Colin S.
Fortington, Lauren V.
Barley, Oliver R.
description ABSTRACT Combat sports athletes often undergo rapid body mass loss (BML), which presents health risks. Hydration testing has been proposed as a possible solution to reduce or eliminate rapid BML. However, combat sports athletes may exhibit distinct physiological characteristics due to repeated exposure to BML. Thus, traditional and emerging hydration biomarkers should be investigated to determine their potential suitability for field use in this cohort. This study examined whether BML can explain changes in serum and urine osmolality (SosmΔ, UosmΔ), tear osmolarity (TosmΔ), hematocrit (HctΔ), and urine‐specific gravity (USGΔ) after mild–moderate passive dehydration. Biomarker reliability was also assessed across two trials. Fifteen male and female combat sports athletes (age: 26.3 ± 5.3 years, body mass: 67.7 ± 9.9 kg) underwent a sauna protocol twice (5–28 days apart) aiming for 4% BML. The average BML in Trials 1 and 2 was 3.0 ± 0.7%. Regression analysis revealed that BML explained HctΔ (R2 = 0.22, p = 0.009) but not SosmΔ (R2 = 0.11, p = 0.079) or other biomarkers. Intraclass correlation coefficients (ICCs) were significant for all biomarkers except TosmΔ (ICC = 0.06, p = 0.37) and post‐Tosm (ICC = 0.04, p = 0.42); post‐Hct performed best (ICC = 0.82, p 
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Hydration testing has been proposed as a possible solution to reduce or eliminate rapid BML. However, combat sports athletes may exhibit distinct physiological characteristics due to repeated exposure to BML. Thus, traditional and emerging hydration biomarkers should be investigated to determine their potential suitability for field use in this cohort. This study examined whether BML can explain changes in serum and urine osmolality (SosmΔ, UosmΔ), tear osmolarity (TosmΔ), hematocrit (HctΔ), and urine‐specific gravity (USGΔ) after mild–moderate passive dehydration. Biomarker reliability was also assessed across two trials. Fifteen male and female combat sports athletes (age: 26.3 ± 5.3 years, body mass: 67.7 ± 9.9 kg) underwent a sauna protocol twice (5–28 days apart) aiming for 4% BML. The average BML in Trials 1 and 2 was 3.0 ± 0.7%. Regression analysis revealed that BML explained HctΔ (R2 = 0.22, p = 0.009) but not SosmΔ (R2 = 0.11, p = 0.079) or other biomarkers. Intraclass correlation coefficients (ICCs) were significant for all biomarkers except TosmΔ (ICC = 0.06, p = 0.37) and post‐Tosm (ICC = 0.04, p = 0.42); post‐Hct performed best (ICC = 0.82, p &lt; 0.001). Contingency tables with post‐Sosm (295 mOsm/kg) and post‐USG (1.020) cutoffs revealed an 80% true negative rate (TNR) and a 62% true positive rate (TPR). Increasing the Sosm cutoff to 301 mOsm/kg decreased the TNR to 52% but increased the TPR to 83%. Although blood parameters were most sensitive to BML, they could only explain 11%–22% of biomarker variation. The typical USG cutoff misclassified 42% of athletes postdehydration, and reliability was generally poor‐moderate. 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Intraclass correlation coefficients (ICCs) were significant for all biomarkers except TosmΔ (ICC = 0.06, p = 0.37) and post‐Tosm (ICC = 0.04, p = 0.42); post‐Hct performed best (ICC = 0.82, p &lt; 0.001). Contingency tables with post‐Sosm (295 mOsm/kg) and post‐USG (1.020) cutoffs revealed an 80% true negative rate (TNR) and a 62% true positive rate (TPR). Increasing the Sosm cutoff to 301 mOsm/kg decreased the TNR to 52% but increased the TPR to 83%. Although blood parameters were most sensitive to BML, they could only explain 11%–22% of biomarker variation. The typical USG cutoff misclassified 42% of athletes postdehydration, and reliability was generally poor‐moderate. 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Fortington, Lauren V. ; Barley, Oliver R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2781-1dc52cf14037858167f0eb3f9fa6ebf77676bf98e4595dafa1660265aca9e7643</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Adult</topic><topic>Athletes</topic><topic>Biomarkers</topic><topic>Biomarkers - blood</topic><topic>blood</topic><topic>Combat sports</topic><topic>dehydration</topic><topic>Dehydration - diagnosis</topic><topic>Female</topic><topic>Hematocrit</topic><topic>Humans</topic><topic>Hydration</topic><topic>Male</topic><topic>Martial Arts - physiology</topic><topic>Osmolar Concentration</topic><topic>passive heating</topic><topic>physiology</topic><topic>reproducibility</topic><topic>Reproducibility of Results</topic><topic>Specific Gravity</topic><topic>Steam Bath</topic><topic>Sweat - chemistry</topic><topic>Tears</topic><topic>urine</topic><topic>Urine - chemistry</topic><topic>Weight Loss</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Doherty, Colin S.</creatorcontrib><creatorcontrib>Fortington, Lauren V.</creatorcontrib><creatorcontrib>Barley, Oliver R.</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Physical Education Index</collection><collection>ProQuest Health &amp; 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Hydration testing has been proposed as a possible solution to reduce or eliminate rapid BML. However, combat sports athletes may exhibit distinct physiological characteristics due to repeated exposure to BML. Thus, traditional and emerging hydration biomarkers should be investigated to determine their potential suitability for field use in this cohort. This study examined whether BML can explain changes in serum and urine osmolality (SosmΔ, UosmΔ), tear osmolarity (TosmΔ), hematocrit (HctΔ), and urine‐specific gravity (USGΔ) after mild–moderate passive dehydration. Biomarker reliability was also assessed across two trials. Fifteen male and female combat sports athletes (age: 26.3 ± 5.3 years, body mass: 67.7 ± 9.9 kg) underwent a sauna protocol twice (5–28 days apart) aiming for 4% BML. The average BML in Trials 1 and 2 was 3.0 ± 0.7%. Regression analysis revealed that BML explained HctΔ (R2 = 0.22, p = 0.009) but not SosmΔ (R2 = 0.11, p = 0.079) or other biomarkers. Intraclass correlation coefficients (ICCs) were significant for all biomarkers except TosmΔ (ICC = 0.06, p = 0.37) and post‐Tosm (ICC = 0.04, p = 0.42); post‐Hct performed best (ICC = 0.82, p &lt; 0.001). Contingency tables with post‐Sosm (295 mOsm/kg) and post‐USG (1.020) cutoffs revealed an 80% true negative rate (TNR) and a 62% true positive rate (TPR). Increasing the Sosm cutoff to 301 mOsm/kg decreased the TNR to 52% but increased the TPR to 83%. Although blood parameters were most sensitive to BML, they could only explain 11%–22% of biomarker variation. The typical USG cutoff misclassified 42% of athletes postdehydration, and reliability was generally poor‐moderate. 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subjects Adult
Athletes
Biomarkers
Biomarkers - blood
blood
Combat sports
dehydration
Dehydration - diagnosis
Female
Hematocrit
Humans
Hydration
Male
Martial Arts - physiology
Osmolar Concentration
passive heating
physiology
reproducibility
Reproducibility of Results
Specific Gravity
Steam Bath
Sweat - chemistry
Tears
urine
Urine - chemistry
Weight Loss
Young Adult
title Blood, Sweat, and Tears: Implications for Hydration Testing in Combat Sports—Investigating Body Mass Loss and Biomarker Changes
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