GENUD "Growth, Exercise, Nutrition and Development" Research Group, Universidad de Zaragoza, 50009 Zaragoza, Spain.
Department of Physiatry and Nursing, Faculty of Health Sciences (FCS), Universidad de Zaragoza, 50009 Zaragoza, Spain.
Int J Environ Res Public Health. 2023 Feb 16;20(4):3454. doi: 10.3390/ijerph20043454.
This paper aims to elaborate a decision tree for the early detection of adolescent swimmers at risk of presenting low bone mineral density (BMD), based on easily measurable fitness and performance variables. The BMD of 78 adolescent swimmers was determined using dual-energy X-ray absorptiometry (DXA) scans at the hip and subtotal body. The participants also underwent physical fitness (muscular strength, speed, and cardiovascular endurance) and swimming performance assessments. A gradient-boosting machine regression tree was built to predict the BMD of the swimmers and to further develop a simpler individual decision tree. The predicted BMD was strongly correlated with the actual BMD values obtained from the DXA (r = 0.960, < 0.001; root mean squared error = 0.034 g/cm). According to a simple decision tree (74% classification accuracy), swimmers with a body mass index (BMI) lower than 17 kg/m or a handgrip strength inferior to 43 kg with the sum of both arms could be at a higher risk of having a low BMD. Easily measurable fitness variables (BMI and handgrip strength) could be used for the early detection of adolescent swimmers who are at risk of suffering from low BMD.
本文旨在基于易于测量的体能和运动表现变量，为青少年游泳运动员制定一个用于早期检测低骨密度（BMD）风险的决策树。使用双能 X 射线吸收法（DXA）对 78 名青少年游泳运动员的髋部和全身进行 BMD 测定。参与者还接受了体能（肌肉力量、速度和心血管耐力）和游泳表现评估。建立了梯度提升机回归树来预测游泳运动员的 BMD，并进一步开发了一个更简单的个体决策树。预测的 BMD 与 DXA 获得的实际 BMD 值高度相关（r = 0.960，<0.001；均方根误差 = 0.034 g/cm）。根据一个简单的决策树（74%的分类准确率），体质量指数（BMI）低于 17 kg/m 或双臂握力低于 43 kg 的游泳运动员可能存在低 BMD 的高风险。易于测量的体能变量（BMI 和握力）可用于早期检测存在低 BMD 风险的青少年游泳运动员。
