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Effects of Air Quality Index and meteorological factors on cardiovascular and cerebrovascular mortality in Huizhou, China

A time-series analysis using distributed lag nonlinear models

Bibliographic Data

ID22084653
AuthorsYangling Zhou (Affiliated Hospital of Guizhou Medical University), Qiaoer Lin (Affiliated Hospital of Guizhou Medical University), Binhua Qin (Affiliated Hospital of Guizhou Medical University), Zhiwen Zheng (0000-0001-9756-5128, Affiliated Hospital of Guizhou Medical University), Xulin Chen (0009-0001-6693-571X, Affiliated Hospital of Guizhou Medical University), Renzhao Pang (The First Huizhou Affiliated Hospital of Guangdong Medical University), Richard Pang (0000-0003-4049-0641, Affiliated Hospital of Guizhou Medical University), Jingrong Huang (Affiliated Hospital of Guizhou Medical University), Yuanbin He (0000-0002-3331-7085, Affiliated Hospital of Guizhou Medical University), Shiyuan Shen (Guangdong Medical College), Qili Chen (0000-0002-9194-3236, Guangdong Medical College), Liuqing Peng (Guangdong Medical College), Shuai Jiang (0000-0002-3046-8689, Guizhou Provincial Meteorological Bureau), Caiming Li (0000-0002-8355-0109, Huizhou Central People's Hospital, corresponding author)
Year2025
Volume13
Pages1694321-1694321
Publication date2025-12-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2025.1694321
PMID41404563
OpenAlexW4416855313
LanguageEN
References cited22

Background: Air pollution exposure is recognized to exacerbate cardiovascular and cerebrovascular diseases (CVDs). This study investigated the association between the Air Quality Index (AQI) and CVD mortality in Huizhou, China, focusing on population-specific lag effects and interactions with meteorological factors. Methods: Daily CVD mortality data (2015-2021) from Huizhou were analyzed using distributed lag nonlinear models (DLNMs) and generalized additive models (GAMs) to assess AQI's relationship with mortality, with subgroup analyses by gender and age. Poisson regression, based on interaction theory, clarified joint effects of AQI and meteorological factors. Results: AQI ≥ 80 was associated with increased CVD mortality risk with lag effects. Cumulative lag peaks varied: total population (2 days, RR = 1.00156, 95% CI: 1.00077-1.00235), males (3 days, RR = 1.00188), females (1 day, RR = 1.00130), ≥65 years (1 day, RR = 1.00098), and 65 years (3 days, RR = 1.00455). Mean wind speed showed an antagonistic interaction with AQI (IRR = 0.92749, 95% CI: 0.89575-0.96035), reducing risk, while mean humidity had a synergistic effect (IRR = 1.05124, 95% CI: 1.01395-1.08989), exacerbating risk. Conclusion: AQI is positively associated with CVD mortality, with lag effects differing by population. Wind speed mitigates, and humidity amplifies, AQI-related risks. These findings support targeted early warning systems and preventive strategies for CVDs

Air quality index · Distributed lag · Humidity · Lag · Lag time · Nonlinear system · Wind speed · Air Quality and Health Impacts · Air Quality Monitoring and Forecasting · Climate Change and Health Impacts

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