Cavedon Valentina, Sacristani Franco, Sandri Marco, Zancanaro Carlo, Milanese Chiara
Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy -
Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.
J Sports Med Phys Fitness. 2023 Apr;63(4):558-565. doi: 10.23736/S0022-4707.22.14355-0. Epub 2022 Oct 28.
In karate, high percentages of fat mass (%FM) are often associated with poor sport performance. Dual-energy X-ray absorptiometry (DXA) can accurately measure the %FM (%FM-DXA), but it may not be practical in some sport settings, where anthropometry has long been used as an alternative. This study aimed to explore the ability of sixteen available anthropometric equations to estimate the %FM (%FM-AE) in karate athletes using the %FM-DXA as the criterion. Furthermore, two population-specific predictive equations to estimate the %FM-DXA were developed from anthropometric measurements.
Forty-six male athletes aged 21.7±3.8 years underwent anthropometry and a whole-body DXA scan.
The results showed that in male karate athletes all the considered anthropometric equations are mostly inaccurate in estimating the %FM-DXA within a range of the limits of agreement in the Bland-Altman analysis, which ranged from 6.43% to 13.37%. Regression analysis yielded two statistically significant models (P<0.001 for both) to predict the %FM-DXA. In the first model (cross-validated estimation of R=0.85), the predictors were the abdominal, triceps, calf, and biceps skinfolds and in the second model (cross-validated estimation of R=0.77), the predictor was the sum of nine skinfolds (i.e., biceps, triceps, subscapular, chest, axilla, suprailiac, abdominal, anterior thigh and calf skinfolds).
These results underlined the need for sport-specific anthropometric equations to accurately estimate the %FM-DXA in male karate athletes. The two predictive anthropometric equations presented in this study provided a promising tool for professionals dealing with body composition in this athletic population to accurately estimate the %FM-DXA by means of anthropometry.
在空手道运动中,高体脂率(%FM)常与运动表现不佳相关。双能X线吸收法(DXA)能够准确测量体脂率(%FM-DXA),但在某些运动场景中可能并不实用,长期以来人体测量学一直被用作替代方法。本研究旨在以%FM-DXA为标准,探究16种现有的人体测量学方程估算空手道运动员体脂率(%FM-AE)的能力。此外,还根据人体测量数据开发了两个针对特定人群的预测方程来估算%FM-DXA。
46名年龄在21.7±3.8岁的男性运动员接受了人体测量和全身DXA扫描。
结果表明,在男性空手道运动员中,在布兰德-奥特曼分析的一致性界限范围内(范围为6.43%至13.37%),所有考虑的人体测量学方程在估算%FM-DXA时大多不准确。回归分析得出两个具有统计学意义的模型(两者P均<0.001)来预测%FM-DXA。在第一个模型中(交叉验证估计R=0.85),预测变量为腹部、肱三头肌、小腿和肱二头肌皮褶厚度;在第二个模型中(交叉验证估计R=0.77),预测变量为九个皮褶厚度之和(即肱二头肌、肱三头肌、肩胛下、胸部、腋窝、髂嵴上、腹部、大腿前侧和小腿皮褶厚度)。
这些结果强调了需要针对特定运动的人体测量学方程来准确估算男性空手道运动员的%FM-DXA。本研究中提出的两个预测人体测量学方程为处理该运动员群体身体成分的专业人员提供了一个有前景的工具,可通过人体测量学准确估算%FM-DXA。