Associations of Fine Particulate Matter Components With Acute Aortic Dissection: A Time‐Stratified Case‐Crossover Study
5 affiliations
- 1Department of Anesthesiology Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University Zhejiang China
- 2Li Ka Shing Faculty of Medicine School of Public Health, The University of Hong Kong Hong Kong SAR China
- 3The Second Clinical College of Guangzhou University of Chinese Medicine Guangzhou China
- 4Department of Traditional Chinese Medicine The Third Affiliated Hospital of Guangzhou Medical University Guangzhou Guangdong China
- 5Faculty of Medicine and Health The University of Sydney Sydney NSW Australia
Abstract
Background: Acute aortic dissection (AAD) is among the most life‐threatening cardiovascular emergencies. Ambient exposure to fine particulate matter (PM2.5) has been linked with AAD, particularly in urban areas. Yet the associations of key PM2.5 components with specific AAD subtypes remain insufficiently understood.
Methods: We used a time‐stratified case‐crossover design (2015–2023) in Hangzhou, China, investigating associations of major PM2.5 components with AAD and its Stanford subtypes. Conditional logistic regression and weighted quantile sum models were applied to explore associations of single and joint exposure to PM2.5 components with AAD, respectively. Stratified analyses based on age, sex, lifestyle factors, and existing comorbidities were performed.
Results: At lag 0 to 1 days, black carbon, organic matter, and sulfate were significantly associated with AAD, especially type A, while positive but nonsignificant associations were observed for type B. An interquartile range increase in black carbon, organic matter, and sulfate was associated with a 42% (odds ratio, 1.42 [95% CI, 1.15–1.75]), 35% (odds ratio, 1.35 [95% CI, 1.10–1.64]), and 36% (odds ratio, 1.36 [95% CI, 1.09–1.69]) increased risk of type A AAD, respectively. The weighted quantile sum model revealed significant joint associations of coexposure to major PM2.5 components with AAD and its type A, with black carbon contributing >50% to the joint associations. Age, smoking, alcohol consumption, and hypertension modified the PM2.5 components–AAD associations.
Conclusions: Precise regulation of ambient PM2.5 components, particularly black carbon, is necessary to mitigate AAD risk. Tailored clinical management is critical for susceptible populations during high‐pollution periods.
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BibTeX
@article{lei2026associations,
title = {{Associations of Fine Particulate Matter Components With Acute Aortic Dissection: A Time‐Stratified Case‐Crossover Study}},
author = {Min Lei and Renyue Ji and Shiqi Wang and Chunren Zhang and Qiang Tu and Yaping Zhang and Nianqiang Hu and Yijin Yu and Haisheng Wu},
journal = {Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease},
year = {2026},
month = sep,
doi = {10.1161/jaha.126.049278},
url = {https://doi.org/10.1161/jaha.126.049278},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Associations of Fine Particulate Matter Components With Acute Aortic Dissection: A Time‐Stratified Case‐Crossover Study
AU - Min Lei
AU - Renyue Ji
AU - Shiqi Wang
AU - Chunren Zhang
AU - Qiang Tu
AU - Yaping Zhang
AU - Nianqiang Hu
AU - Yijin Yu
AU - Haisheng Wu
PY - 2026
DA - 2026/09/09
JO - Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
DO - 10.1161/jaha.126.049278
UR - https://doi.org/10.1161/jaha.126.049278
AB - Background: Acute aortic dissection (AAD) is among the most life‐threatening cardiovascular emergencies. Ambient exposure to fine particulate matter (PM2.5) has been linked with AAD, particularly in urban areas. Yet the associations of key PM2.5 components with specific AAD subtypes remain insufficiently understood. Methods: We used a time‐stratified case‐crossover design (2015–2023) in Hangzhou, China, investigating associations of major PM2.5 components with AAD and its Stanford subtypes. Conditional logistic regression and weighted quantile sum models were applied to explore associations of single and joint exposure to PM2.5 components with AAD, respectively. Stratified analyses based on age, sex, lifestyle factors, and existing comorbidities were performed. Results: At lag 0 to 1 days, black carbon, organic matter, and sulfate were significantly associated with AAD, especially type A, while positive but nonsignificant associations were observed for type B. An interquartile range increase in black carbon, organic matter, and sulfate was associated with a 42% (odds ratio, 1.42 [95% CI, 1.15–1.75]), 35% (odds ratio, 1.35 [95% CI, 1.10–1.64]), and 36% (odds ratio, 1.36 [95% CI, 1.09–1.69]) increased risk of type A AAD, respectively. The weighted quantile sum model revealed significant joint associations of coexposure to major PM2.5 components with AAD and its type A, with black carbon contributing >50% to the joint associations. Age, smoking, alcohol consumption, and hypertension modified the PM2.5 components–AAD associations. Conclusions: Precise regulation of ambient PM2.5 components, particularly black carbon, is necessary to mitigate AAD risk. Tailored clinical management is critical for susceptible populations during high‐pollution periods.
SN - 2047-9980
ER -