Abstract
INTRODUCTION: Field tests to estimate maximal oxygen consumption (VO2max) are an alternative to traditional exercise testing methods. Published field tests and their accompanying estimation equations account for up to 80% of the variance in VO2max with an error rate of ~4.5 ml.kg-1.min-1. These tests are limited to very specific age-range populations. The purpose of this study was to create and validate a series of easily administered walking and stepping field equations to predict VO2max across a range of healthy 18-79-year-old adults. METHODS: One-hundred-fifty-seven adults completed a graded maximal exercise test to assess VO2max. Five separate walking and three separate stepping tests of varying durations, number of stages, and intensities were completed. VO2max estimation equations were created using hierarchal multiple regression. Covariates including age, sex, body mass, resting heart rate, distance walked, gait speed, stepping cadence, and recovery heart rate were entered into each model using a stepwise approach. Each full model created had the same base model consisting of age, sex, and body mass. Validity of each model was assessed using a Jackknife cross-validation analysis, and percent bias and root mean square error (RMSE) were calculated. RESULTS: Base models accounted for ~72% of the total variance of VO2max. Full model variance ranged from ~79-83% and bias was minimal (<±1.0%) across models. RMSE for all models were approximately 4.5 ml.kg-1.min-1. Stepping tests performed better than walking tests by explaining ~2.5% more of the variance and displayed smaller RMSE. CONCLUSION: All eight models accounted for a large percentage of VO2max variance (~81%) with a RMSE of ~4.5 ml.kg-1.min-1. The variance and level of error of models examined highlight good group mean prediction with greater error expected at the individual level. All the models perform similarly across a broad age range, highlighting flexibility in application of these tests to a more general population.