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Asian J Kinesiol > Volume 16(1); 2014 > Article
The Official Journal of the Korean Academy of Kinesiology 2014;16(1):31-39.
DOI: https://doi.org/10.15758/jkak.2014.16.1.31     Published online January 31, 2014.
Development of V˙O 2 max Estimation and Validity Based on Body Index Variables for Adults
Yoo-Joung Jeon, Byung-Kun Lee, Jae-Hyeng Im
KAIST
Sangmyung University
Correspondence:  Jae-Hyeng Im,
Email: imjh@kaist.ac.kr
Received: 19 December 2013   • Accepted: 18 October 2014
Abstract

INTRODUCTION
The purpose of this study is to develop V˙O 2 max estimation model with body index variables such as gender, age, weight, height, BMI, and resting HR, and to verify prediction model bases on verification group.
METHOD
The subjects are consisted of 837 male and female subjects aged from 18 to 60, and they were separated into two groups randomly: 649 for sample group and 188 for cross-validation group. They went through maximal exercise testing using Bruce protocol and we ran applied multiple regression analysis to the sample group.
RESULT
Estimation prediction initially used gender, age, weight, height, BMI, and resting heart rate as independent variable, but only gender, age, weight, and height were chosen to be input variables. As the result, 2 models were developed, and both of them had good r value(0.66, 0.68, p<.01), low SEE%(14.32, 14.59, P<.01), and low %TE(5.89, 5.99, p<.01). In addition, multicolinearity didn't show on 2 models. Model 1 was V˙O 2 max(ml/kg/min) = 27.703 - 7.423 * (gender) - 0.067 * (age) - 0.232 * (weight) + 0.221 * (height). Model 2 was V˙O 2 max(ml/kg/min) = 64.543 - 9.397 * (gender) - 0.110 * (age) - 0.167 * (weight). For 2 models, Cross-validation also showed correlation between predicted and measured V˙O 2 max(r=0.56, 0.58, p<.01), and there was no significant difference(p=0.443, p=0.847) with very low %error(-18.8~12.2) and %TE(5.89, 5.99, p<.01).
CONCLUSION
V˙O 2 max estimation 2 model for adults were developed based on body index variables. As a result of verification, these model show valuable cross-validation. In the future studies, the higher prediction power model with questionnaire or convenient scientific methods should be developed.
Keywords: estimation of V


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