Nomogram-Based Evaluation of Exercise Capacity Based on Metabolic Equivalents (METs), Age, Body Mass Index(BMI), and Waist Circumference

Abstract

Background/Purpose: Raw metabolic-equivalent (MET) cut-offs ignore how age and body size shape oxygen demand. The aim is derivation and validation of sex-specific nomograms that adjust treadmill MET performance for age, body-mass index (BMI) and waist circumference (WC). Methods: A prospective derivation cohort of 1 067 West-Eurasian adults who completed symptom-limited Bruce tests (January–December 2024) was analysed with multivariable linear regression (predictors: age, BMI, WC, sex). Internal validity used 1 000-fold bootstrap. External performance was assessed, without re-calibration, in an independent retrospective cohort of 900 tests from a separate laboratory. Results: Age, BMI and WC were independent determinants of absolute METs; smoking and resting heart rate were not. The model explained 24% of variance in women and 20% in men; optimism-corrected calibration was excellent (slope 0.99, intercept +0.08 METs). In the external cohort it retained good accuracy (R² = 0.32; SEE = 1.66 METs) and calibration (slope 1.06, intercept –0.84 METs). Compared with the age-only Gulati (women) and Morris (men) equations, the new model showed negligible bias (–0.12 ± 1.86 METs) and the lowest error (Brier 3.45 vs 11.21/9.68). Conclusions: Nomograms that integrate age, BMI and WC translate raw treadmill data into personalised, size-adjusted targets and flag values