Delaney Jace A, Thornton Heidi R, Scott Tannath J, Ballard David A, Duthie Grant M, Wood Lisa G, Dascombe Ben J
Applied Sport Science and Exercise Testing Laboratory, University of Newcastle, Ourimbah, NSW, Australia.
Int J Sports Physiol Perform. 2016 Mar;11(2):261-6. doi: 10.1123/ijspp.2015-0244. Epub 2015 Jul 27.
High levels of lean mass are important in collision-based sports for the development of strength and power, which may also assist during contact situations. While skinfold-based measures have been shown to be appropriate for cross-sectional assessments of body composition, their utility in tracking changes in lean mass is less clear.
To determine the most effective method of quantifying changes in lean mass in rugby league athletes.
Body composition of 21 professional rugby league players was assessed on 2 or 3 occasions separated by ≥6 wk, including bioelectrical impedance analysis (BIA), lean-mass index (LMI), and a skinfold-based prediction equation (SkF). Dual-X-ray absorptiometry provided a criterion measure of fat-free mass (FFM). Correlation coefficients (r) and standard errors of the estimate (SEE) were used as measures of validity for the estimates.
All 3 practical estimates exhibited strong validity for cross-sectional assessments of FFM (r > .9, P < .001). The correlation between change scores was stronger for the LMI (r = .69, SEE 1.3 kg) and the SkF method (r = .66, SEE = 1.4 kg) than for BIA (r = .50, SEE = 1.6 kg).
The LMI is probably as accurate in predicting changes in FFM as SkF and very likely to be more appropriate than BIA. The LMI offers an adequate, practical alternative for assessing in FFM among rugby league athletes.
在对抗性运动中,高水平的瘦体重对于力量和爆发力的发展很重要,在接触性情况下也可能有所帮助。虽然基于皮褶厚度的测量方法已被证明适用于身体成分的横断面评估,但其在追踪瘦体重变化方面的效用尚不清楚。
确定量化橄榄球联盟运动员瘦体重变化的最有效方法。
对21名职业橄榄球联盟球员的身体成分进行了2至3次评估,每次评估间隔≥6周,评估方法包括生物电阻抗分析(BIA)、瘦体重指数(LMI)和基于皮褶厚度的预测方程(SkF)。双能X线吸收法提供了无脂肪质量(FFM)的标准测量值。相关系数(r)和估计标准误差(SEE)用作估计有效性的指标。
所有3种实际估计方法在FFM的横断面评估中均表现出很强的有效性(r>.9, P<.001)。与BIA(r=.50,SEE=1.6 kg)相比,LMI(r=.69,SEE 1.3 kg)和SkF方法(r=.66,SEE=1.4 kg)的变化分数之间的相关性更强。
LMI在预测FFM变化方面可能与SkF一样准确,而且很可能比BIA更合适。LMI为评估橄榄球联盟运动员的FFM提供了一种充分、实用的替代方法。