DOI 10.1519/jsc.0000000000005129
Custom Regional Segmental Lower Limb Lean Soft Tissue Analysis in Male and Female Division I Athletes.
Аннотация
Joniak, KE, Moore, SR, Ladan, AN, Cantu, EI, Britton, ME, and Smith-Ryan, AE. Custom regional segmental lower limb lean soft tissue analysis in male and female Division I athletes. J Strength Cond Res 39(8): 868-874, 2025-Asymmetries in lean soft tissue (LST) may affect athlete availability and injury risk. Segmental custom regions of interest (C-ROI) analyses may reveal LST differences that could go undetected by whole limb analysis using dual energy x-ray absorptiometry (DXA). The purpose of the study was to describe a novel C-ROI LST segmental analysis method using DXA, and to characterize asymmetry across the sample and identify meaningful difference cut points for C-ROI segmental analyses in elite athletes. Full-body DXA testing was performed on 581 NCAA Division I athletes (46% female, mean ± SD ; Age = 20.2 ± 1.4 years, mass = 83.3 ± 26.0 kg) from August 2015 to July 2023. Custom regions of interest analyses were completed for glute, thigh, and calf segments on each leg. Regional percent differences ([segment LST difference]/[total segment LST/2] × 100) were calculated and meaningful differences were established from mean and standard deviations between limbs of each segment. The C-ROI method demonstrated high inter-reliability at each segment (intraclass correlation coefficient: 0.874-0.999). Average LST segmental limb differences for male athletes were (mean ± SD ): glute = 1.4 ± 4.4%, thigh = 0.3 ± 2.9%, calf = 0.6 ± 4.7%; and for female athletes: glute = 2.0 ± 4.4%, thigh = 0.3 ± 4.2%, calf = 0.8 ± 4.6%. Values >2 standard deviations for male athletes (glute: 10.2%, thigh: 6.1%, calf: 9.9%) and female athletes (glute: 10.9%, thigh: 8.6%, calf: 10.0%) seemed to be clinically meaningful. Using meaningful regional difference cut points may provide staff (i.e., athletic trainers, dietitians, and strength coaches) insight into acceptable LST asymmetries to better support athlete performance and return to play.
Предметные рубрики MeSH
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Обработка статьи · этапы, ошибки и управление
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История · было → стало
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