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Accurate estimation of skeletal muscle mass (SMM) is important for body composition assessment in Brazilian Jiu-Jitsu (BJJ) athletes owing to body mass classification and force production implications. This study compared the validity, reliability, and agreement of three predictive equations-Kim, McCarthy, and Sagayama-for estimating total SMM (expressed in kilograms) in male BJJ athletes. Twenty-two male BJJ athletes (mean age: 33.1 ± 7.5 years; body mass: 78.4 ± 9.6 kg; height: 171.8 ± 6.4 cm) underwent DXA-derived body composition analysis. SMM was estimated using the Kim, McCarthy, and Sagayama equations. Statistical analyses included repeated-measures ANOVA, stepwise linear regression, Pearson's correlation, intraclass correlation coefficient (ICC), coefficient of variation (CV%), and Bland-Altman plots. The mean SMM estimated by the Kim equation was 28.95 ± 4.92 kg (95% CI: 26.89-31.00 kg), by the McCarthy equation, 27.39 ± 4.96 kg (95% CI: 25.32-29.47 kg), and by the Sagayama equation, 27.72 ± 3.71 kg (95% CI: 26.16-29.27 kg). The Kim equation yielded significantly higher SMM values than McCarthy (mean difference = 1.55 kg, < 0.0001), while Sagayama and McCarthy did not differ significantly. Stepwise regression identified the Kim equation as a strong predictor of Sagayama SMM values ( = 0.851; = 0.724; RMSE = 2.0 kg; = 52.369; < 0.001), although with proportional underestimation (slope = 0.642). Reliability was acceptable for all equations (ICC > 0.79), and the Sagayama equation demonstrated the lowest CV% (13.4%, 95% CI: 9.44%-17.36%). Bland-Altman analysis revealed systematic biases, particularly for the Kim equation. All three equations provided accurate validity and reliability for estimating absolute SMM (kg) in BJJ athletes. However, the McCarthy and Sagayama equations showed less bias and greater agreement by DXA, supporting their use for accurate quantification of SMM in this population. Their validation with magnetic resonance imaging is needed.
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http://dx.doi.org/10.3389/fnut.2025.1595259 | DOI Listing |
Cureus
August 2025
Faculty of Health Sciences, Kumamoto Health Science University, Kumamoto, JPN.
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Rehabilitation Unit, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128 Rome, Italy.
Brazilian Jiu-Jitsu (BJJ) is a physically demanding sport associated with a notable risk of musculoskeletal injuries. Understanding injury patterns, rehabilitation approaches, and psychological readiness to return to sport (RTS) is essential for prevention and management strategies. This study aimed to investigate injury characteristics among Italian BJJ athletes, assess their rehabilitation processes and psychological recovery, and identify key risk factors such as belt level, body mass index (BMI), and training load.
View Article and Find Full Text PDFFront Nutr
July 2025
Programa de Investigación en Deporte, Sociedad y Buen Vivir (DSBv), Universidad de Los Lagos, Osorno, Chile.
Accurate estimation of skeletal muscle mass (SMM) is important for body composition assessment in Brazilian Jiu-Jitsu (BJJ) athletes owing to body mass classification and force production implications. This study compared the validity, reliability, and agreement of three predictive equations-Kim, McCarthy, and Sagayama-for estimating total SMM (expressed in kilograms) in male BJJ athletes. Twenty-two male BJJ athletes (mean age: 33.
View Article and Find Full Text PDFPLoS One
July 2025
Institute of Psychology, University of Opole, Opole, Poland.
Previous research on aggression in martial arts and combat sports (MA&CS) has shown mixed results. Some studies showed that MA&CS training lowers aggression levels, while other studies found it increases aggression or has no effect. To explain better this inconsistency, this study used latent class analysis to identify distinct subgroups of MA&CS practitioners based on aggression levels and related demographic and sports factors.
View Article and Find Full Text PDFJ Orthop Surg (Hong Kong)
May 2025
Nicolaas Institute of Constructive Orthopaedic Research & Education Foundation for Arthroplasty & Sports Medicine at Medistra Hospital, Jakarta, Indonesia.
The orthopedic field is on the brink of a significant transformation-a shift from retrospective analysis to real-time decision-making fueled by data. The dependence on historical trends or long-term studies is yielding to an era where data flows dynamically, allowing medical professionals to adjust protocols instantly. This isn't just an evolution; it's a revolution.
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