Predictive Value of Cardiopulmonary Exercise Testing (CPET)-Derived Indicators for Cardiometabolic Risk Factors in an Occupational Population: A Prospective Cohort Study

Objective To investigate the association between cardiopulmonary function indicators derived from cardiopulmonary exercise testing (CPET) and incident cardiometabolic risk factors (CMRFs) in an occupational population, and to identify the optimal CPET-based predictive indicators/models for CMRFs. Methods A single-center prospective cohort study was conducted. A total of 126 occupational adults (59.2% male; mean age: 41.2 ± 8.5 years) who underwent health check-ups at the Health Management Center of Beijing Zhongguancun Hospital from January 2022 to June 2025 were enrolled. Inclusion criteria included age 28-60 years, fixed occupation for ≥1 year, no severe cardiopulmonary diseases/malignant tumors/hepatic/renal failure, ability to complete CPET, and informed consent. Exclusion criteria included ≥3 pre-existing CMRFs, recent use of metabolism/cardiopulmonary function-affecting drugs, loss to follow-up, and acute diseases/major surgery during follow-up. CPET indicators included peak oxygen consumption (VO₂peak, mL/kg/min), anaerobic threshold (AT, mL/kg/min), peak heart rate (HRpeak, beats/min), and oxygen pulse (O₂pulse, mL/beat). CMRFs (hypertension, hyperglycemia, dyslipidemia, overweight/obesity) were defined based on standard criteria. Multivariate Logistic regression analyzed the association between CPET indicators and CMRF risk; receiver operating characteristic (ROC) curves evaluated predictive efficacy. Results During 2-year follow-up, 40.5% (n=51) of participants developed CMRFs. The case group (with CMRFs) had higher age, sedentary occupation proportion, smoking rate, and levels of systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting plasma glucose (FPG), total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), body mass index (BMI), and HRpeak, but lower regular exercise rate, high-density lipoprotein cholesterol (HDL-C), VO₂peak, AT, and O₂pulse (all P<0.05). After adjusting for confounding factors (age, gender, occupation type, smoking), reduced VO₂peak (per 5 mL/kg/min decrease; OR=1.86, 95% CI: 1.52–2.28, P<0.001) and AT (per 5 mL/kg/min decrease; OR=1.63, 95% CI: 1.31–2.02, P<0.001) were independent CMRF risk factors. Subgroup analysis showed stronger predictive effect of VO₂peak in sedentary workers (OR=2.13, 95% CI: 1.68–2.70, P<0.001). The combination of VO₂peak and AT had the highest predictive efficacy (AUC=0.783, 95% CI: 0.751–0.815), superior to single indicators (VO₂peak: AUC=0.721; AT: AUC=0.685; both P<0.05). Conclusion CPET-derived VO₂peak and AT are valuable predictors of CMRFs in occupational populations, especially in sedentary workers. The combined VO₂peak+AT model serves as a practical tool for CMRF screening and risk stratification in occupational health management.