Relationship between the Army Two Mile Run Test and Maximal Oxygen Uptake

Abstract

Forty-four male (aged 20-51) and seventeen female (aged 20-37) subjects of various fitness and activity levels were evaluated on a two mile run for time and on a treadmill for maximal oxygen consumption. The coefficient of correlation between the treadmill maximal test and the two mile run test for all subjects was -0.91. Separate regression analyses for male and female data also displayed significant correlations (rm = -0.91, rf = -0.89). Stepwise multiple regression analysis of such anthropometric variables as age, height, weight, and % body fat demonstrated that, individually, none of these parameters significantly improved the predictability of both the male and female equations. However, inclusion of body weight in the male equation did improve the predictive accuracy (SEE = 3.31 to 2.69). The high degree of correlation demonstrated between VO2 max and two mile run time thus permits the estimation of either component with significant accuracy from the direct measurement of the other. This study confirms the usefulness and validity of the Army's 2 mile run for time test to indicate the level of aerobic fitness capacity when the test is properly supervised and the subjects are well-motivated. Keywords: Maximal 02 uptake, Aerobic fitness, Running performance, Predicted aerobic capacity.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1984
Accession Number
ADA153914

Entities

People

  • James A. Vogel
  • Michelle M. Murphy
  • Robert P. Mello

Tags

Communities of Interest

  • Biomedical
  • Human Systems

DTIC Thesaurus Topics

  • Accuracy
  • Biological Sciences
  • Body Weight
  • Coefficients
  • Confidence Limits
  • Data Analysis
  • Data Mining
  • Data Science
  • Databases
  • Inclusions
  • Information Science
  • Measurement
  • Military Personnel
  • Military Research
  • Physiology
  • Regression Analysis
  • Surveys

Fields of Study

  • Education

Readers

  • Exercise and Sports Science.
  • Regression Analysis.