There are several equations to predict maximum oxygen consumption ([latin capital V with dot above]O2max) from ergometric test variables on different ergometers. However, a similar equation using ventilatory thresholds of ergospirometry in a submaximal test on a cycle ergometer is unavailable. The aim of the present study was to assess the accuracy of [latin capital V with dot above]O2max prediction models based on indicators of submaximal effort. Accordingly, 4,640 healthy, nonathlete women ages 20 years and older volunteered to be tested on a cycle ergometer using a maximum incremental protocol. The subjects were randomly assigned to 2 groups: group A (estimation) and group B (validation). From the independent variables of weight in kilograms, the second workload threshold (WT2), and heart rate of the second threshold (HRT2), it was possible to build a multiple linear regression model to predict maximal oxygen consumption ([latin capital V with dot above]O2max = 40.302 - 0.497 [Weight] - 0.001 [HRT2] + 0.239 [WT2] in mL O2/kg/min-1; r = 0.995 and standard error of the estimate [SEE] = 0.68 mL O2/kg/min-1). The cross-validation method was used in group B with group A serving as the basis for building the model and the validation dataset. The results showed that, in healthy nonathlete women, it is possible to predict [latin capital V with dot above]O2max with a minimum of error (SEE = 1.00%) from submaximal indicators obtained in an incremental test.
© 2001-2026 Fundación Dialnet · Todos los derechos reservados