Ben Brahim Mehdi, Sal-de-Rellán Alejandro, Hernaiz-Sánchez Ariadna, Yasin Hussain, García-Valverde Adrián
Department of Health and Physical Education, Prince Sultan University, Riyadh, Saudi Arabia.
Faculty of Health Sciences, Universidad Isabel I, Burgos, Spain.
Front Psychol. 2023 Oct 12;14:1250913. doi: 10.3389/fpsyg.2023.1250913. eCollection 2023.
Anthropometric measures such as the body mass index (BMI), reciprocal ponderal index (RPI), and waist-to-height ratio (WHR) have been proposed as predictors of physical fitness. This study aimed to identify the differences in explanatory capacity and fit of BMI, RPI, and WHR on physical fitness, which involves jumping, sprinting, change of direction, and aerobic capacity, by adjusting the polynomial regression.
A sample of 297 healthy, recreationally active male university students between 18 and 20 years old was recruited for this study. Anthropometric measurements (height: 174.09 ± 6.27 cm, weight: 78.98 ± 20.27 kg, waist circumference: 93.74 ± 14.56 cm) were taken for each participant. Jumping tests (squat jump, countermovement jump), sprinting tests (20 m sprint), agility tests (agility T-test), and aerobic/endurance tests (6 min walk test, VAM-EVAL test) were performed. Nonlinear quadratic regression models were used to assess the relationship between the jump, sprint, and fitness test scores and the anthropometric indices. The models were compared based on R-squares and Bayesian Information Criterion (BIC). The significance level was set at < 0.05.
The results showed that all the indices predicted a portion of the variance because all variables and index relationships were significant. Regarding the fitted models, the Bayesian Information Criterion showed that BMI was the best indicator of performance, although the RPI was better for VO.
These findings may be of great interest to practitioners because it appears that anthropometric measures can be used to predict physical fitness in certain tests although the accuracy raises any concerns.
诸如身体质量指数（BMI）、倒数 ponderal 指数（RPI）和腰高比（WHR）等人体测量指标已被提议作为身体素质的预测指标。本研究旨在通过调整多项式回归来确定BMI、RPI和WHR在身体素质（包括跳跃、短跑、方向变化和有氧能力）方面的解释能力和拟合度差异。
本研究招募了297名年龄在18至20岁之间、健康且有休闲运动习惯的男性大学生作为样本。对每位参与者进行人体测量（身高：174.09±6.27厘米，体重：78.98±20.27千克，腰围：93.74±14.56厘米）。进行了跳跃测试（深蹲跳、反向运动跳）、短跑测试（20米短跑）、敏捷性测试（敏捷T型测试）和有氧/耐力测试（6分钟步行测试、VAM-EVAL测试）。使用非线性二次回归模型评估跳跃、短跑和体能测试分数与人体测量指标之间的关系。根据决定系数（R²）和贝叶斯信息准则（BIC）对模型进行比较。显著性水平设定为<0.05。
结果表明，所有指标都预测了一部分方差，因为所有变量和指标关系都是显著的。关于拟合模型，贝叶斯信息准则表明BMI是表现的最佳指标，尽管RPI对VO更优。
这些发现可能会引起从业者的极大兴趣，因为似乎人体测量指标可用于在某些测试中预测身体素质，尽管其准确性存在一些问题。
