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

空气污染暴露与多种疾病共存模式:来自中国一项全国性队列研究的证据

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Abstract

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.

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