Ambient Air Pollution and Hospitalizations for Ischemic Stroke
A Time Series Analysis Using a Distributed Lag Nonlinear Model in Chongqing, China
Dados Bibliográficos
| ID | 22069741 |
|---|---|
| Autores | Hao Chen (0000-0002-8873-8266, Chongqing Public Health Medical Center), Zheng Cheng (0000-0001-9873-5061, Chongqing Public Health Medical Center), Mengmeng Li (0000-0001-5093-386X, Chongqing Public Health Medical Center), Pan Luo (0000-0002-3923-2111, Chongqing Public Health Medical Center), Yong Duan (0000-0002-0557-7525, Chongqing Public Health Medical Center), Jie Fan (0000-0003-2441-5019, Chongqing Public Health Medical Center), Ying Xu (0000-0001-6344-9612, Chongqing Public Health Medical Center), Kexue Pu (0000-0002-2339-3316, Chongqing Medical University), Li Zhou (0000-0001-7132-5935, Chongqing Public Health Medical Center, autor correspondente) |
| Ano | 2022 |
| Volume | 9 |
| Páginas | 762597-762597 |
| Data de publicação | 2022-01-18 |
| Peer Reviewed | Sim |
| Open Access | Sim |
| Tipo | ARTICLE |
| Periódico | Frontiers in Public Health (JOURNAL) |
| Identificadores do periódico | ISSN: 2296-2565 • E-ISSN: 2296-2565 |
| Editora | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/fpubh.2021.762597 |
| PMID | 35118040 |
| OpenAlex | W4205984703 |
| Idioma | EN |
| Citações recebidas | 5 |
| Referências citadas | 29 |
Short-term exposure to air pollution has been associated with ischemic stroke (IS) hospitalizations, but the evidence of its effects on IS in low- and middle-income countries is limited and inconsistent. We aimed to quantitatively estimate the association between air pollution and hospitalizations for IS in Chongqing, China. This time series study included 2,299 inpatients with IS from three hospitals in Chongqing from January 2015 to December 2016. Generalized linear regression models combined with a distributed lag nonlinear model (DLNM) were used to investigate the impact of air pollution on IS hospitalizations. Stratification analysis was further implemented by sex, age, and season. The maximum lag-specific and cumulative percentage changes of IS were 1.2% (95% CI: 0.4–2.1%, lag 3 day) and 3.6% (95% CI: 0.5–6.7%, lag 05 day) for each 10 μg/m 3 increase in PM 2.5 ; 1.0% (95% CI: 0.3–1.7%, lag 3 day) and 2.9% (95% CI: 0.6–5.2%, lag 05 day) for each 10 μg/m 3 increase in PM 10 ; 4.8% (95% CI: 0.1–9.7%, lag 4 day) for each 10 μg/m 3 increase in SO 2 ; 2.5% (95% CI: 0.3–4.7%, lag 3 day) and 8.2% (95% CI: 0.9–16.0%, lag 05 day) for each 10 μg/m3 increase in NO 2 ; 0.7% (95% CI: 0.0–1.5%, lag 6 day) for each 10 μg/m 3 increase in O 3 . No effect modifications were detected for sex, age, and season. Our findings suggest that short-term exposure to PM 2.5 , PM 10 , SO 2 , NO 2 , and O 3 contributes to more IS hospitalizations, which warrant the government to take effective actions in addressing air pollution issues
Air pollution · Distributed lag · Generalized additive model · Lag · Lag time · Statistics · Time lag · Air Quality and Health Impacts · Air Quality Monitoring and Forecasting · Climate Change and Health Impacts · Demography · Mathematics · Medicine
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| Obras citantes distintas | 5 |
|---|---|
| Citações por ano | 1,25 |
| Intervalo de citações | 2022 - 2026 (5) |
| Velocidade de citação | current |
| Altamente citado | Não |
| Tipos de citação | Neutras: 5 |