Highest oxygen consumption prediction by forced vital capacity in athletes

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.

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.

FVC and gender emerged as significant predictors (R² = 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 (R² = 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 (R² = 0.893).

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.