Study On Predicting Anaerobic Threshold Of College Students Based On Cardiac Function,Blood And Body Composition Indexes

ObjectiveBy studying the correlation between resting heart function,blood,body composition and anaerobic threshold(AT),this paper explores the physiological mechanism of its correlation with anaerobic threshold,establishes a mathematical model to predict anaerobic threshold,improves the accuracy of anaerobic threshold prediction,provides a theoretical basis for evaluating aerobic endurance and guiding college students scientific fitness,and also provides a theoretical basis for the application of noninvasive cardiac output monitoring technology in sports heart monitoring It provides experimental basis for further application in the field.MethodsIn this study,266 subjects(134 males and 132 females)were recruited from five universities in Beijing.Using random number generator,the subjects were divided into two groups: modeling group(male 97,female 103),validation group(male 37,female 29).The modeling group was divided into regular exercise group(77 males and 33 females)and infrequent exercise group(20 males and 70 females).Venous blood was drawn to measure blood indexes,gas metabolism and resting heart function were monitored by cortexmetalyzer3 b system and American Cheetah NICOM system,and at was measured by linear incremental exercise program.The collected data were analyzed and processed by SPSS statistical software.Through correlation analysis,the indexes with significant linear correlation with anaerobic threshold were selected as independent variables,at as dependent variables,and multiple linear stepwise regression was used to establish the regression equation for predicting anaerobic threshold of college students based on quiet heart function and blood body composition indexes,and goodness of fit test and regression test were carried out for the established equation.Result1.There were significant gender and exercise differences in HR,SBP,CP,SV,TPRI,SVI,CO and TFC(P < 0.05).Nonparametric test showed that the quiet CO,SV,TPRI and SBP of boys were significantly higher than those of girls,while CP and vet were significantly lower than those of girls(P < 0.05);the quiet SV and SVI of exercise group were significantly higher than those of ordinary group,and HR was significantly lower than that of ordinary group(P < 0.05).2.The blood indexes of college students: TC,RBC,HDL,HGB,HCT,T have significant gender and exercise differences(P < 0.05).The results of nonparametric test showed that RBC,HGB,HCT and T of boys were significantly higher than those of girls(P < 0.05),while TC and HDL of girls were significantly higher than those of boys(P < 0.01);there was no significant difference in these indexes among different exercise background groups(P > 0.05).3.The body composition indexes of college students: the percentage of fat in trunk,upper body,lower body,upper limb,thigh,whole body tissue and area,thigh and lower body fat,trunk,upper body,lower body,upper limb,thigh,whole body muscle mass have significant gender differences(P < 0.05).The results of nonparametric test showed that: the muscle mass of trunk,upper body,lower body,upper limb,thigh and whole body of male students were significantly higher than that of female students(P < 0.05),and the results of exercise group and ordinary group were consistent;while the regional fat percentage of upper limb,thigh,trunk,upper body,lower body and whole body and the fat content of upper limb and thigh of exercise group were significantly lower than that of female students(P < 0.05)The results were consistent with those of normal group.4.Pearson and Spearman correlation analysis was used to analyze all indexes of resting heart function,blood and body composition and anaerobic threshold,and the indexes with significant linear correlation were selected.Then the partial correlation analysis was conducted to control the influence of exercise,gender and weight.The results showed that: quiet heart function index: SV,TFC,SVI,blood index: EO%,body composition index: trunk,upper body,lower body,upper limb,thigh,whole body muscle content and anaerobic threshold were positively correlated,and the correlation was statistically significant(P < 0.05);HR,HCT,HGB,body,upper body,lower body,upper limb,thigh,body tissue and regional fat percentage,fat content were negatively correlated with anaerobic threshold,and the correlation was statistically significant(P < 0.05).5.Finally,we selected 10 indexes with significant linear correlation of anaerobic threshold: HR,SV,SVI,TFC,blood index: HGB,HCT,EO%,body composition index: percentage of body fat,body fat(kg),body muscle(kg)and body weight,exercise into multiple linear regression analysis,and finally got the most representative and best fit Excellent regression equation: ?vo2AT = 0.372 + 0.022 * body weight-0.022 * body fat percentage-0.004 * TFC + 0.171 * exercise condition + 0.004 * quiet SV(R2 = 0.715,P < 0.01;exercise condition value(regular exercise = 1,infrequent exercise = 0)).6.In the validation group,the predictive value of at was slightly higher than the measured value,but the difference between them was not statistically significant(P > 0.05),which indicated that the predictive value was basically consistent with the measured value.Conclusion1.Quiet SV,SVI,TFC and whole body muscle content were positively correlated with anaerobic threshold;HR,HGB,HCT,whole body fat and percentage of whole body fat were negatively correlated with anaerobic threshold.2.After correcting other factors,SV was positively correlated with VO₂AT;Body fat percentage and resting TFC were negatively correlated with VO₂AT.3.The goodness of fit test of the predictive equation based on resting heart function,blood and body composition is good,and the predictive value is basically consistent with the measured value,which can better predict the anaerobic threshold of college students in China.