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Individual and joint associations of long-term exposure to air pollutants and cardiopulmonary mortality: a 22-year cohort study in Northern China

BACKGROUND: Evidence on the associations between long-term exposure to multiple air pollutants and cardiopulmonary mortality is limited, especially for developing regions with higher pollutant levels. We aimed to characterise the individual and joint (multi-pollutant) associations of long-term expos...

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Detalles Bibliográficos
Autores principales: Huang, Wenzhong, Zhou, Yang, Chen, Xi, Zeng, Xiaowen, Knibbs, Luke D., Zhang, Yunting, Jalaludin, Bin, Dharmage, Shyamali C., Morawska, Lidia, Guo, Yuming, Yang, Xueli, Zhang, Liwen, Shan, Anqi, Chen, Jie, Wang, Tong, Heinrich, Joachim, Gao, Meng, Lin, Lizi, Xiao, Xiang, Zhou, Peien, Yu, Yunjiang, Tang, Naijun, Dong, Guanghui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10398602/
https://www.ncbi.nlm.nih.gov/pubmed/37547049
http://dx.doi.org/10.1016/j.lanwpc.2023.100776
Descripción
Sumario:BACKGROUND: Evidence on the associations between long-term exposure to multiple air pollutants and cardiopulmonary mortality is limited, especially for developing regions with higher pollutant levels. We aimed to characterise the individual and joint (multi-pollutant) associations of long-term exposure to air pollutants with cardiopulmonary mortality, and to identify air pollutant that primarily contributes to the mortality risk. METHODS: We followed 37,442 participants with a mean age of 43.5 years in four cities in northern China (Tianjin, Shenyang, Taiyuan, and Rizhao) from January 1998 to December 2019. Annual particulate matter (PM) with diameters ≤2.5 μm (PM(2.5)), ≤10 μm (PM(10)), sulfur dioxide (SO(2)) and nitrogen dioxide (NO(2)) were estimated using daily average values from satellite-derived machine learning models and monitoring stations. Time-varying Cox proportional hazards model was used to evaluate the individual association between air pollutants and mortality from non-accidental causes, cardiovascular diseases (CVDs), non-malignant respiratory diseases (RDs) and lung cancer, accounting for demographic and socioeconomic factors. Effect modifications by age, sex, income and education level were also examined. Quantile-based g-Computation integrated with time-to-event data was additionally applied to evaluate the co-effects and the relative weight of contributions for air pollutants. FINDINGS: During 785,807 person-years of follow-up, 5812 (15.5%) died from non-accidental causes, among which 2932 (7.8%) were from all CVDs, 479 (1.3%) from non-malignant RDs, and 552 (1.4%) from lung cancer. Long-term exposure to PM(10) (mean [baseline]: 136.5 μg/m(3)), PM(2.5) (mean [baseline]: 70.2 μg/m(3)), SO(2) (mean [baseline]: 113.0 μg/m(3)) and NO(2) (mean [baseline]: 39.2 μg/m(3)) were adversely and consistently associated with all mortality outcomes. A 10 μg/m(3) increase in PM(2.5) was associated with higher mortality from non-accidental causes (hazard ratio 1.20; 95% confidence interval 1.17–1.23), CVDs (1.23; 1.19–1.28), non-malignant RDs (1.37; 1.25–1.49) and lung cancer (1.14; 1.05–1.23). A monotonically increasing curve with linear or supra-linear shape with no evidence of a threshold was observed for the exposure-response relationship of mortality with individual or joint exposure to air pollutants. PM(2.5) consistently contributed most to the elevated mortality risks related to air pollutant mixture, followed by SO(2) or PM(10). INTERPRETATION: There was a strong and positive association of long-term individual and joint exposure to PM(10), PM(2.5), SO(2), and NO(2) with mortalities from non-accidental causes, CVDs, non-malignant RDs and lung cancer in high-exposure settings, with PM(2.5) potentially being the main contributor. The shapes of associations were consistent with a linear or supra-linear exposure-response relationship, with no lower threshold observed within the range of concentrations in this study. FUNDING: 10.13039/501100012166National Key Research and Development Program of China, the 10.13039/501100004543China Scholarship Council, the 10.13039/501100001809National Natural Science Foundation of China, 10.13039/501100003453Natural Science Foundation of Guangdong Province.