The individual and combined effects of air pollution mixtures on the risk of cardiovascular diseases in patients with Cardiovascular-Kidney-Metabolic syndrome at stages 0-3.

Abstract

This study aims to employ a prospective cohort design to quantitatively assess the association between exposure levels of common ambient air pollutants and the risk of cardiovascular disease (CVD) in patients across stages 0-3 of Cardiovascular-kidney-metabolic (CKM) syndrome. By doing so, it addresses a critical knowledge gap in environmental exposure research within this specific clinical context. We analyzed baseline differences between CVD cases/controls using descriptive statistics, parametric/nonparametric tests, and Pearson correlations for air pollutants (PM₁, PM2.5, PM₁₀, NO₂, O₃). Cox regression (Models 1-3, adjusting for sociodemographic/behavioral factors) and RCS assessed pollutant-CVD associations. WQS/qgcomp models evaluated mixture effects via weighted indices and directional weighting. Sensitivity analyses used BKMR, WQS-CVD exposure-response curves, and 2-year lag to address reverse causality. In single-pollutant analyses, per-interquartile range (IQR) increases in PM₁, PM₂.₅, PM₁₀, and NO₂ were associated with 30% (HR = 1.30, 95% CI 1.17-1.45), 35% (HR = 1.35, 95% CI 1.21-1.51), 52% (HR = 1.52, 95% CI 1.35-1.70), and 30% (HR = 1.30, 95% CI 1.17-1.45) elevations in CVD risk, respectively. No significant association was found for O₃. In mixture analyses, all three quantile g-computation (qgcomp) models linked combined pollutant exposure to significantly higher CVD risk (Model 1: HR = 1.10, 95% CI 1.04-1.17; Model 2: HR = 1.11, 95% CI 1.04-1.18; Model 3: HR = 1.12, 95% CI 1.05-1.19). PM₁₀ emerged as the dominant driver of the mixture effect. Higher exposure levels to ambient air pollutants are associated with an increased risk of cardiovascular disease in patients with Stage 0-3 CKM syndrome.