Highest oxygen consumption prediction by forced vital capacity in athletes
Abstract
Abstract Purpose Static spirometry parameters may offer practical alternatives to estimate maximum oxygen consumption (V̇O 2max ) in athletic populations. This study evaluated forced vital capacity (FVC) as a predictor of V̇O 2max across different sports, developing prediction equations for field-based assessment. Methods Four hundred twenty-two athletes (324 males, 98 females; age 22.9 ± 8.5 years) from cycling ( n = 123), swimming ( n = 68), triathlon ( n = 60), multisport ( n = 83), and other sports ( n = 88) performed spirometry and maximal incremental testing. V̇O 2max was directly measured using breath-by-breath gas analysis. LASSO regression identified predictors, with Bland–Altman analysis assessing agreement. Results FVC and gender emerged as significant predictors ( R 2 = 0.690, P < 0.001). The equation V̇O 2max (L·min −1 ) = (FVC × 0.61) + (Gender × 0.86) yielded SEE = 0.65 L·min −1 . Including additional variables (Maximum voluntary ventilation, body weight, age) marginally improved prediction ( R 2 = 0.712) but reduced practical utility. Coefficient of variation between measured and predicted values was 12.1%. Sport-specific analysis revealed highest predictive accuracy in swimmers ( R 2 = 0.893). Conclusion FVC provides reasonable population-level V̇O 2max estimates in athletes, though individual predictions require caution given substantial unexplained variance (31%). Sport-specific equations, particularly for swimming populations, enhance predictive accuracy. These findings offer practical screening tools for coaches lacking access to metabolic testing equipment, though direct measurement remains the gold standard for individual assessment.
Fields of Study & Subjects
Cardiovascular and exercise physiology
Sports Performance and Training
Cardiovascular Effects of Exercise
Publication details
- Journal / source
- European Journal of Applied Physiology
- Publisher
- Springer Science and Business Media LLC
- Volume
- 126
- Issue
- 6
- Pages
- 3191–3200
- Publication date
- 7 February 2026
- Language
- EN