Clark R Randall, Bartok Cynthia, Sullivan Jude C, Schoeller Dale A
University of Wisconsin Hospital Sports Medicine Center, Madison, WI 53711, USA.
Med Sci Sports Exerc. 2004 Apr;36(4):639-47. doi: 10.1249/01.mss.0000121942.84630.6c.
The National Collegiate Athletic Association (NCAA) requires prediction of minimum weight (MW) for collegiate wrestlers. The rule was implemented to minimize unhealthy weight loss practices and requires assessment of body composition before the competitive season.
This study cross-validated the body composition methods of dual energy x-ray absorptiometry (DXA), leg-to-leg bioelectrical impedance analysis (BIA), hydrostatic weighing (HW), and skinfolds (SF) for predicting MW using a four-component criterion (4C).
Criterion MW was calculated by the 4C model using independent measurement of body density (BD), bone mineral content (BMC), and total body water (TBW). Subjects were 53 Division I athletes from the University of Wisconsin (mean +/- SD; age = 19.7 +/- 1.3 yr, height = 176.2 +/- 7.4 cm, weight = 75.6 +/- 8.9 kg). Accuracy, precision, and systematic bias were examined in the predictions.
There were no significant differences in mean MW from HW (70.5 +/- 7.3 kg, P = 0.57), SF (70.5 +/- 7.2 kg, P = 0.29) BIA (70.6 +/- 7.6 kg, P = 0.39), DXA (70.3 +/- 7.5, P = 0.97), and the 4C criterion (70.3 +/- 7.4 kg). The regression for the relationships between 4C and HW (y = 0.994 x HW + 0.077 kg), 4C and SF (y = 1.003 x SF-0.437 kg), 4C and DXA (y = 0.942 x DXA + 4.034 kg), and 4C and BIA (y = 0.896 x BIA + 6.987 kg) did not significantly deviate from the line of identity. Pure error (PE) values ranged from 1.34 kg for HW to 3.08 kg for BIA.
Comparable means, high correlations, regression lines that did not significantly deviate from the line of identity, and no systematic bias were found. However, the methods differed widely in precision. The best precision, based on SEE and PE values, were seen in the HW and SF methods. In conclusion, this rigorous four-component cross-validation study supports the NCAA methods as the most accurate and precise MW prediction methods in this sample.
美国国家大学体育协会（NCAA）要求预测大学摔跤运动员的最低体重（MW）。该规定的实施是为了尽量减少不健康的减重行为，并要求在比赛赛季前评估身体成分。
本研究对双能X线吸收法（DXA）、腿对腿生物电阻抗分析（BIA）、水下称重（HW）和皮褶厚度（SF）等身体成分测量方法进行交叉验证，以使用四成分标准（4C）预测最低体重。
使用独立测量的身体密度（BD）、骨矿物质含量（BMC）和总体水（TBW），通过4C模型计算标准最低体重。研究对象为来自威斯康星大学的53名一级运动员（均值±标准差；年龄=19.7±1.3岁，身高=176.2±7.4厘米，体重=75.6±8.9千克）。对预测中的准确性、精密度和系统偏差进行了检验。
HW法（70.5±7.3千克，P = 0.57）、SF法（70.5±7.2千克，P = 0.29）、BIA法（70.6±7.6千克，P = 0.39）、DXA法（70.3±7.5，P = 0.97）和4C标准法（70.3±7.4千克）得出的平均最低体重无显著差异。4C与HW之间的回归关系（y = 0.994×HW + 0.077千克）、4C与SF之间的回归关系（y = 1.003×SF - 0.437千克）、4C与DXA之间的回归关系（y = 0.942×DXA + 4.034千克）以及4C与BIA之间（y = 0.896×BIA + 6.987千克）的回归关系均未显著偏离恒等线。纯误差（PE）值范围从HW法的1.34千克到BIA法的3.08千克。
研究发现各方法的均值具有可比性、相关性高、回归线未显著偏离恒等线且无系统偏差。然而，各方法在精密度上差异很大。基于标准误（SEE）和PE值，HW法和SF法的精密度最佳。总之，这项严格的四成分交叉验证研究支持NCAA的方法是该样本中最准确、精密的最低体重预测方法。
