Estimation of maximal oxygen uptake by bioelectrical impedance analysis.
Previous non-exercise models for the prediction of maximal oxygen uptake VO(2max) have failed to accurately discriminate cardiorespiratory fitness within large cohorts. The aim of the present study was to evaluate the feasibility of a completely indirect method for predicting VO(2max) that was based on bioelectrical impedance analysis (BIA) in 66 young, healthy fit men and women. Multiple, stepwise regression analysis was used to determine the usefulness of BIA and additional covariates to estimate VO(2max) (ml min(-1)). BIA was highly correlated to VO(2max) (r = 0.914; P < 0.001) and entered the regression equation first. The inclusion of gender and a physical activity rating further improved the model which accounted for 88% of the variance in VO(2max) and resulted in a relative standard error of the estimate (SEE) of 7.2%. Substantial agreement between the methods was confirmed by the fact that nearly all the differences were within +/-2 SD. Furthermore, in contrast to previously published non-exercise models, no trend of a reduction in prediction accuracy with increasing VO(2max) values was apparent. It was concluded that a non-exercise model based on BIA might be a rapid and useful technique to estimate VO(2max), when a direct test does not seem feasible. However, though the present results are useful to determine the viability of the method, further refinement of the BIA approach and its validation in a large, diverse population is needed before it can be applied to the clinical and epidemiological settings.
Stahn
Alexander
A
Institute of Sports Medicine, University Hospital Charité, Campus Benjamin Franklin, Free University of Berlin, Germany. alexstahn@yahoo.com
Terblanche
Elmarie
E
Grunert
Sven
S
Strobel
Günther
G
D000328:Adult; D000886:Anthropometry; D001823:Body Composition; D017097:Electric Impedance; D015444:Exercise; D005260:Female; D006801:Humans; D008297:Male; D010101:Oxygen Consumption; D011237:Predictive Value of Tests; D012044:Regression Analysis; D015203:Reproducibility of Results; D012129:Respiratory Function Tests