年轻女性肌肉局部生物电阻抗分析参数与在等速测力计上进行多组运动的表现之间的关系。

Aryanne H. Fukuoka, Núbia M. Oliveira, Catarina N. Matias, Débora A. Guariglia, Gil Guerra-Júnior, Ezequiel M. Gonçalves
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引用次数: 0

摘要

本研究旨在验证大腿肌肉局部生物电阻抗分析(ML-BIA)参数的变化与多组运动成绩之间的关系。样本由 30 名女大学生(22.1 ± 3.2 岁)组成。使用频率为 50 KHz 的四极生物电阻抗装置评估了 ML-BIA 参数,包括局部肌肉阻力(ML-R)、电抗(ML-Xc)和相位角(ML-AngF)。多组训练方案使用等动测力计进行。在身体成分方面,使用双 X 射线吸收测定法评估了总瘦软组织和腿部瘦软组织(LST)。在比较运动前后的 ML-BIA 参数和大腿围度时,采用了配对样本的学生 t 检验。在控制总和腿部 LST 的情况下,进行了线性回归分析,以验证 ∆ML-PhA 是否能单独预测三组运动的峰值扭矩。ML-R(∆ = 0.02 ± 1.45 Ω;p = 0.001;E.S = 0.19)、ML-Xc(∆ = 2.90 ± 4.12 Ω;p = 0.043;E.S = 0.36)和大腿周长(∆ = 0.82 ± 0.60 厘米;p = 0.001;E.S = 0.19)存在差异。
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Association between muscle-localized bioelectrical impedance analysis parameters and performance in a multi-set exercise on the isokinetic dynamometer in young women

This study aimed to verify the relationship between changes in thigh muscle-localized bioelectrical impedance analysis (ML-BIA) parameters and performance in a multiple-set exercise. The sample consisted of 30 female university students (22.1 ± 3.2 years). The ML-BIA parameters, including localized muscle resistance (ML-R), reactance (ML-Xc), and phase angle (ML-AngF), were evaluated using a tetrapolar bioelectric impedance device operating at a frequency of 50 KHz. The multiple sets protocol was performed with an isokinetic dynamometer. For body composition, total and leg lean soft tissue (LST) were evaluated using dual X-ray absortiometry. Student's t-test for paired samples was used to compare the ML-BIA parameters and thigh circumference pre and postexercise. Linear regression analysis was performed to verify the ∆ML-PhA as a predictor of peak torque for the three sets alone while controlling for total and leg LST. There were differences in the ML-R (∆ = 0.02 ± 1.45 Ω; p = 0.001; and E.S = 0.19), ML-Xc (∆ = 2.90 ± 4.12 Ω; p = 0.043; and E.S = 0.36), and thigh circumference (∆ = 0.82 ± 0.60 cm; p < 0.001; and E.S = 0.16) pre- and post-multiple sets. ΔML-PhA was a predictor of performance in the first set (p = 0.002), regardless of total and leg LST. However, the ΔML-PhA lost its explanatory power in the other sets (second and third), and the variables that best explained performance were total and leg LST. The ML-BIA (ML-R and ML-Xc) parameters were sensitive and changed after the multiple sets protocol, and the ΔML-PhA was a predictor of performance in the first set regardless of the total and leg LST.

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