Prediction of functional aerobic capacity without exercise testing

Abstract

The purpose of this study was to develop functional aerobic capacity prediction models without using exercise tests (N-Ex) and to compare the accuracy with Astrand single-stage submaximal prediction methods. The data of 2,009 subjects (9.7% female) were randomly divided into validation (N = 1,543) and cross-validation (N = 466) samples. The validation sample was used to develop two N-Ex models to estimate V̇O_2peak. Gender, age, body composition, and self-report activity were used to develop two N-Ex prediction models. One model estimated percent fat from skinfolds (N-Ex %fat) and the other used body mass index (N-Ex BMI) to represent body composition. The multiple correlations for the developed models were R = 0.81 (SE = 5.3 ml·kg⁻¹ -min⁻¹) and R = 0.78 (SE = 5.6 ml·kg⁻¹·min⁻¹). This accuracy was confirmed when applied to the cross-validation sample. The N-Ex models were more accurate than what was obtained from V̇O_2speak estimated from the Astrand prediction models. The SEs of the Astrand models ranged from 5.5–9.7 ml·kg⁻¹-min⁻¹. The N-Ex models were cross-validated on 59 men on hypertensive medication and 71 men who were found to have a positive exercise ECG. The SEs of the N-Ex models ranged from 4.6–5.4 ml·kg⁻¹·min⁻¹ with these subjects. An analysis of subsamples of the cross-validation sample showed that the accuracy of the models was upheld with all but subjects with a V̇O_2speak ≥ 55 ml·kg⁻¹·min⁻¹. this confirmed that the N-Ex models were more accurate than established submaximal treadmill prediction models and are appropriate for about 96% of the adult population.