ISSN:
1439-6327
Keywords:
Multiple linear regression equation
;
Maximal aerobic power
;
Analysis of variance
;
Multiple correlation
;
Product moment correlation
Source:
Springer Online Journal Archives 1860-2000
Topics:
Medicine
Notes:
Summary An attempt has been made to evolve some simple multiple linear regression equations for the prediction of $$\dot V_{{\text{O}}_{\text{2}} }$$ max from body weight, time for 3.2 km run and exercise dyspnoeic index (DIstd Ex%). The predictor variables have been selected by examining the product moment correlations of body weight, relative body weight indices, time for 3.2 km run, chest expansion, height, and DIstd Ex% with $$\dot V_{{\text{O}}_{\text{2}} }$$ max, based on data collected on 320 healthy Indian males (17–22 years). It has been observed that body weight, time for 3.2 km run and DIstd Ex% attained maximum correlations with $$\dot V_{{\text{O}}_{\text{2}} }$$ max. Thus, two regression equations with two and three predictor variables have been established in this paper to predict $$\dot V_{{\text{O}}_{\text{2}} }$$ max. The first regression equation yielded a multiple correlation of 0.608 (P〈0.001) with a standard error of 0.214 l·min−1. In this equation, body weight and time for 3.2 km run were considered as significant predictors. To increase the precision of this equation, another multiple linear regression equation based on body weight, time for 3.2 km run and DIstd Ex% as predictors has been developed. This equation yielded a multiple correlation of 0.658 (P〈0.001) with a standard error of 0.204 l·min−1. Applications of these regression equations will be of practical importance to biomedical scientists engaged in the development of a simple procedure for indirect assessment of $$\dot V_{{\text{O}}_{\text{2}} }$$ max, and may serve well as preliminary screening procedures for personnel selection.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF01015223
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