大学生静息代谢率与体格发育的相关性研究

发布时间：2018-03-25 18:04

本文选题：静息代谢率　切入点：体格指标　出处：《现代预防医学》2017年22期

【摘要】：目的通过对大学生静息代谢率与体格发育的相关性研究,获得在校大学生静息代谢率的多重线性回归方程,为大学生膳食能量摄入与能量失衡相关疾病的预防提供参考依据。方法采用整群随机抽样方法,抽取广东省大学生1 450人,年龄18~26岁。对受试者分别进行静息代谢率(RMR)和体格指标的测定。以年龄、身高、体重、腰围、臀围、上臂围等为自变量,通过多重线性回归拟合出在校大学生的静息代谢率的回归方程。采用配对t检验验证所建立的回归方程。结果男大学生中,体重(r=0.830)、腰围(r=0.806)与静息代谢率相关性最大。建立的回归方程为RMR=4.244BW+7.451WC+6.401H+4.010HC+0.757UC+3.944A-881.245(P0.001,R2=0.838)。女大学生中,体重(r=0.926)、臀围(r=0.827)和静息代谢率相关最大。建立的回归方程为RMR=8.516BW+3.678H+5.551UC+2.984HC+1.030WC-341.119(P0.001,R2=0.896)。结论本次研究发现大学生静息代谢率与体格营养指标息息相关;在校大学生静息代谢率的多重线性回归方程的建立,可以更好地指导大学生维持能量平衡平衡膳食,降低能量失衡相关疾病的风险。
[Abstract]:Objective to study the correlation between resting metabolic rate and physical development of college students and to obtain multiple linear regression equations of resting metabolic rate. Methods A cluster random sampling method was used to select 1 450 college students from Guangdong province. The subjects were measured with resting metabolic rate (RMRs) and physical parameters. Age, height, weight, waist circumference, hip circumference and upper arm circumference were independent variables. The regression equation of resting metabolic rate of college students was fitted by multiple linear regression. The established regression equation was verified by paired t test. The regression equation was RMR=4.244BW 7.451WC 6.401H 4.010HC 0.757UC 3.944A-881.245P0.001R2. The regression equation was established as RMR=8.516BW 3.678H 5.551UC 2.984HC 1.030WC-341.119C P 0.001 R20.8960.Conclusion the resting metabolic rate of college students is closely related to the physical nutrition index. The establishment of multiple linear regression equations for resting metabolic rate of college students can better guide college students to maintain a balanced energy diet and reduce the risk of diseases related to energy imbalance.
【作者单位】：南方医科大学公共卫生学院;南方医科大学公共卫生学院预防医学实验教学中心;
【基金】：广东省大学生创新科研课题(201412121083、201712121111) 南方医科大学2014年度大学生创新创业训练计划项目(2013kw) 南方医科大学本科教学改革发展工程建设之特色教育教学改革项目(校教字[2013]84号)
【分类号】：R153

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