Document Detail

An accurate VO2max nonexercise regression model for 18-65-year-old adults.
MedLine Citation:
PMID:  16739680     Owner:  NLM     Status:  MEDLINE    
The purpose of this study was to develop a regression equation to predict maximal oxygen uptake (VO2max) based on nonexercise (N-EX) data. All participants (N = 100), ages 18-65 years, successfully completed a maximal graded exercise test (GXT) to assess VO2max (M = 39.96 mL x kg(-1) x min(-1), SD = 9.54). The N-EX data collected just before the maximal GXT included the participant's age; gender; body mass index (BMI); perceived functional ability (PFA) to walk, jog, or run given distances; and current physical activity (PA-R) level. Multiple linear regression generated the following N-EX prediction equation (R = .93, SEE = 3.45 mL x kg(-1) x min(-1), % SEE = 8.62): VO2max (mL x kg(-1) x min(-1)) = 48.0730 + (6.1779 x gender; women = 0, men = 1) - (0. 2463 x age) - (0.6186 x BMI) + (0.7115 x PFA) + (0.6709 x PA-R). Cross validation using PRESS (predicted residual sum of squares) statistics revealed minimal shrinkage (R(p) = .91 and SEE(p) = 3.63 mL x kg(-1) x min(-1)); thus, this model should yield acceptable accuracy when applied to an independent sample of adults (ages 18-65 years) with a similar cardiorespiratory fitness level. Based on standardized beta-weights, the PFA variable (0.41) was the most effective at predicting VO2max followed by age (-0.34), gender (0.33), BMI (-0.27), and PA-R (0.16). This study provides a N-EX regression model that yields relatively accurate results and is a convenient way to predict VO2max in adult men and women.
Danielle I Bradshaw; James D George; Annette Hyde; Michael J LaMonte; Pat R Vehrs; Ronald L Hager; Frank G Yanowitz
Publication Detail:
Type:  Evaluation Studies; Journal Article; Validation Studies    
Journal Detail:
Title:  Research quarterly for exercise and sport     Volume:  76     ISSN:  0270-1367     ISO Abbreviation:  Res Q Exerc Sport     Publication Date:  2005 Dec 
Date Detail:
Created Date:  2006-06-02     Completed Date:  2006-08-16     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8006373     Medline TA:  Res Q Exerc Sport     Country:  United States    
Other Details:
Languages:  eng     Pagination:  426-32     Citation Subset:  IM    
Department of Exercise Sciences, Brigham Young University, Provo, Utah 84602, USA.
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MeSH Terms
Exercise Test
Linear Models
Middle Aged
Models, Biological*
Models, Statistical*
Oxygen Consumption / physiology*
Predictive Value of Tests
Reproducibility of Results

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