ArticleBMC public health2025
Air pollution exposure and multimorbidity patterns: evidence from a national cohort study in China.
Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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2 citing papers in PubMed.
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10 authors.
Funding
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Abstract
backgroundMultimorbidity 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.
methodsThis 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.
resultsFour 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.
conclusionsAir 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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