Air pollution exposure and multimorbidity patterns: evidence from a national cohort study in China

Background: Multimorbidity prevalence in China has been rising annually and has emerged as a major health challenge. While air pollution contributes to individual Noncommunicable diseases (NCDs), its impact on distinct multimorbidity patterns remains unclear. Methods: This prospective cohort study analyzed 36,144 participants from the China Family Panel Studies (2010–2022) without baseline multimorbidity. Among 6,839 individuals (18.9%) who developed multimorbidity during median 8-year follow-up, latent class analysis identified distinct disease patterns. Fine-Gray subdistribution hazard models assessed associations between eleven air pollutants (PM2.5, PM10, O3, NO2, SO2, CO, and five PM2.5 components) and pattern-specific multimorbidity. Results: Four multimorbidity patterns emerged: Musculoskeletal-Dominant (3.4%), Cardiopulmonary (3.4%), Cardiovascular-Metabolic (9.5%), and Digestive-Dominant (2.6%). In single-pollutant models, PM10 showed consistent adverse effects (sHR 1.12–1.48), while cold-season O3 demonstrated protective associations (sHR 0.66–0.78). After multi-pollutant adjustment, PM10 remained the strongest risk factor across all patterns (sHR 1.71–2.47). Both cold- and warm-season O3 maintained protective associations (sHR 0.43–0.82). PM2.5 retained significance only for Cardiovascular-Metabolic pattern (sHR 1.13, 95% CI: 1.05–1.21). Dose-response analyses revealed non-linear relationships with threshold effects. Conclusions: Air pollutants demonstrate heterogeneous associations with multimorbidity patterns, with PM10 as a universal risk factor. These findings highlight the need for pattern-specific approaches in environmental health research and air quality policy development.