Survey On Physical Fitness Levels And Energy Expenditure Modeling Based On Routine Physical Activities From College Students

Purpose: The purpose of this study was to analyze the relationship between physical activityand body health. The physical statues of college students were tested according to the contentof “college students’ physical health standards”. The energy expedition of several normalphysical activities were obtained by IC method, and physical activity volume predictionequations were established by using three-axis accelerometer, which to explore convenient,accurate and effective method to monitor physical activities.Methods:1.800no PE college students participated in the research. According to the“college students physical health standards”, the analysis was mainly from three aspects: bodyshape, bodily functions and physical quality, the test contents were divided into9subjects.The questionnaire was also used to investigate the whole situation of after class activities andphysical fitness.2.70students from the group were in the following test,50were chosen randomly in testgroup(male=25, female=25) and another20were in validation group(male=10, female=10).Participants wore MetaMax3B portable indirect calorimetry (IC) system, SensewareArmband three-axis accelerometer and polar heart rate monitor (HR) during performingphysical activities. Seven subjects were tested in the experiment, which were lie flat,walking(3.2km/h、4.0km/h、4.8km/h&5.2km/h), running(6.4km/h、7.0km/h、8.1km/h&9.0km/h), bend over a table, climbing steps(100-120steps/min), riding(10km/h、13km/h、15km/h&20km/h) and push up, accelerometry data was recorded in every test subject.Using the IC method as standard to measure energy expenditure (EE), accelerometry countsof axis Z (ACz), vector magnitude (VM) and heart rate (HR)as independent variables toestablish EE prediction equations. EE prediction equations also established based on3METs.The students in validation group pursued the accuracy testing in same order to verified theprediction equations.Results:1Results from “college students physical health standards” indicated collegestudents in bad physical condition, the bad performance of bodily functions and physicalquality were the main cause for the decline of physical healthy. By statistic of questionnaire, the lack of physical activities, pressure on studying and unhealthy living habits alsonegatively infected physical healthy. On the other hand, the incomprehensive of exerciseenvironment, lack of supervision and judgment facilities was another reason for theinsufficient of physical activities and decline of physical healthy.2The correlation between ACz and VM were significant different between activities, but ACzand VM of different speed in same activity had no significant difference. By correlationanalysis, EE prediction equations had high degree of fitting with independent variable of sex,BMI, HR, ACz and VM, and R2=0.7.3In this research, ten EE prediction equations were established based on overall EE,classified EE and METs EE. The equations of overall EE and walk/run EE were obviouslyimproved accuracy of physical activities EE prediction. The equations of overall EE andwalk/run EE were as follow:(1) overall EE prediction equations：W/min=－9.125288+0.004357*ACz+1.097599*SEX+0.2270181*BMI+0.057226*HRW/min=－12.27049+0.008815*VM+0.953711*SEX+0.2318533*BMI+0.0586115*HR(2) walk/run EE prediction equations：W/min=－18.78608+0.008212*ACz+2.058352*SEX+0.2000157*BMI+0.0474637*HRW/min=－8.849811+0.014097*VM+2.034297*SEX+0.1546967*BMI+0.0202001*HRConclusion:1College students need joint more physical activities to improve body healthy.2Based on three axis accelerometry data, BMI, HR and sex, the prediction equations hadhigher accuracy on physical activities EE prediction, which can be widely used in supervisionof college students daily physical activities.