摘要
背景:人体是1个不规则的几何体,难于对其体积进行测量。目的:建立以身高、体质量为自变量,人体体积为因变量的多种回归方程。进行大学男生身体体积计算模型的优选。设计:单一样本单因素分析。对象:于2003-01/2004-10选择浙江工商大学18～22岁男生共24名为观察对象。方法:测量男生的身高、体质量和身体体积。身高、体质量指标的测量均采用国家认定的体质测试仪器进行测量。身体体积指标采用自制的直径为0.95m、高为1.20m的铁容器,容器内安装1个有高度的刻度标记,将水灌入一定的高度,让学生慢慢地完全浸入水中,记录其高度差测量结果。人体体积穴m3雪=穴0.95÷2雪2×3.14159×高度差。进行测量数据的统计计算。以身高、体质量为自变量,以人体体积为因变量,运用体育科研数据统计处理系统软件包,建立二元回归方程,并完成回归方程的优选。主要观察指标:学生身高、体质量和身体体积测量数据与各种回归方程的计算结果。结果:①建立计算人体体积的二元回归方程:y=0.00616+0.000022×身高+0.000756×体质量。②人体体积的一元回归方程及方程的优选:线性方程为y=0.0008×体质量+0.0092;对数方程为y=0.0508ln穴体质量雪-0.1524;乘幂方程为y=0.0018×体质量0.8409;指数方程为y=0.0258×e0.0126x;复相关系数R2=0.9921～0.9973,均比较接近1,说明模型预测的人体体积值与实际的人体体积值呈高度相关眼r>r0.001穴24-2雪熏P<0.001演;4种模型预测值与实际值无差异。③从测量和计算的简便性分析,在5种回归方程中,线性方程最优。④人体体积指标与体质系列指标呈高度相关的指标涵盖身体形态、身体机能和身体素质指标。结论:人体体积指标在体质研究中是不可忽视的重要指标之一。从测量、计算的简便性和方程线性的拟合度分析,一元线性回归方程最优。
BACKGROUND： Human body is an irregular geometrical one, so it is very difficult to measure its volume. OBJECTIVE： To establish a multiple regressive equation by taking body height and body mass as the independent variables and body volume as the dependent variable, and select optimally the body volume calculative model of male college students. DESIGN： A single-sample univariate analysis. PARTICIPANTS： Twenty-four male students aged 18-22 years were selected from Zhejiang Gongshang University between January 2003 and October 2004. METHODS： The body height, body mass and body volume of the male students were measured. The indexes of body height and body mass were measured with the nationally-recognized fitness test instrument, and the indexes of body volume were measured with a self-made iron container with a diameter of 0.95 m and height of 1.20 m. There was a mark scale for height in the container, water was infused to a fixed height, then the student slowly immersed himself into the water completely and the height difference was recorded. Body volume （m^3）=（0.95÷2）^2×3.141 59×height difference. The measured data were statistically calculated. A regression equation in two unknowns was established by taking body height and body mass as the independent variables and body volume as the dependent variable with the systematic software for statistical treatment of physical education scientific research data, and the optimal selection of the regression equa- tion was completed. MAIN OUTCOME MEASURES： The measured data of body height, body mass and body volume and the calculative results of the regression equations were observed. RESULTS： ① A regression equation in two unknowns for calculating body volume was established： y=0.006 16＋0.000 022×body height＋0.000 756×body mass. ② A regression equation in one unknown for body volume and its optimal selection： The linear equation was y=0.000 8×body mass＋0.0092, the logarithm equation was y=0.050 8 Ln（body mass） -0.1524, the power equation was y=0.001 8×body mass ^0.8409, the exponent equation was y=0.0258×e^0.0126x, and the multiple correlation coefficient R^2=0.9921-0.9973, all were close to 1, indicating that the body volume predicted by models was highly correlated with the actual one [r0.001（24-2）, P〈0.001]. The predicted values of the 4 models had no difference from the actual one. ③ Linear equation had the best simplicity in measurement and calculation in the 5 regression equations. ④ The indexes of physical quality, which were highly correlated with body volume, were body shape, physical function and physical quality. CONCLUSION： The index of body volume is one of the important index- es, which cannot be neglected in the study of physical quality. Analyzing from the simplicity of measurement and calculation and the linear goodness-of-fit of equation, the regression equation in one unknown is the best.
出处
《中国临床康复》
CSCD
北大核心
2005年第40期134-136,共3页
Chinese Journal of Clinical Rehabilitation
