Abstract

The purpose of this study was to develop a regression equation to predict VO2max based on non-exercise (N-EX) data. All participants (N = 100), aged 18-65 years old, successfully completed a maximal graded exercise test (GXT) to assess VO2max (mean ± SD; 39.96 mL∙kg-¹∙min&sup-1; ± 9.54 mL∙kg-¹∙min-¹). 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∙kg-¹∙min-¹, %SEE = 8.62): VO2max (mL∙kg-¹∙min-¹) = 48.0730 + (6.1779 x gender) - (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 (Rp = .91 and SEEp = 3.63 mL∙kg-¹∙min-¹); thus, this model should yield acceptable accuracy when applied to an independent sample of adults (aged 18-65) with a similar cardiorespiratory fitness level. Based on standardized β-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.

Degree

College and Department

Life Sciences; Exercise Sciences

Rights

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