Validity of VO(2 max) in Predicting Blood Volume: Implications for the Effect of Fitness on Aging

Abstract

A multiple regression model was constructed to investigate the premise that blood volume (BV) could be predicted using several anthropometric variables, age, and maximal oxygen uptake (VO2max). To test this hypothesis, age, calculated body sur face area (height/weight composite), percent body fat (hydrostatic weight), and VO2max were regressed on to BV using data obtained from 66 normal healthy men. Results from the evaluation of the full model indicated that the most parsimonious result was obtained when age and VO2 max were regressed on BV expressed per kilogram body weight. The full model accounted for 52% of the total variance in BV per kilogram body weight. Both age and VO2max were related to BV in the positive direction. Percent body fat contributed, 1% to the explained variance in BV when expressed in absolute BV (ml) or as BV per kilogram body weight. When the model was cross validated on 41 new subjects and BV per kilogram body weight was reexpressed as raw BV, the results indicated that the statistical model would be stable under cross validation (e.g., predictive applications) with an accuracy of + or - 1,200 ml at 95% confidence. Our results support the hypothesis that BV is an increasing function of aerobic fitness and to a lesser extent the age of the subject. The results may have implication as to a mechanism by which aerobic fitness and activity may be protective against reduced BV associated with aging.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2000
Accession Number
ADA628399

Entities

People

  • David A. Ludwig
  • Victor A Convertino

Organizations

  • United States Army Institute of Surgical Research

Tags

Communities of Interest

  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Accuracy
  • Blood Volume
  • Body Weight
  • Cardiac Arrhythmias
  • Cardiovascular Diseases
  • Chemistry
  • Data Science
  • Death
  • Diseases And Disorders
  • Heart Diseases
  • Information Science
  • Measurement
  • North Carolina
  • Physical Activity
  • Regression Analysis
  • Statistics
  • Volume

Readers

  • Cardiovascular Physiology
  • Regression Analysis.
  • Trauma Surgery or Emergency Medicine.