OBJECTIVES There is limited information regarding the association between air pollution exposure and stroke incidence. Therefore, this study aimed to assess the associations between short-term exposure to ambient air pollutants and initial hospital admission for ischemic stroke. MATERIALS AND METHODS From the Korea National Health Insurance Service-National Sample Cohort 2002-2013 database in South Korea, 55,852 first hospital admissions for ischemic stroke were identified. A generalized additive Poisson model was used to explore the association between air pollutants, including particulate matter, sulfur dioxide, nitrogen dioxide, and carbon monoxide and admissions for ischemic stroke. RESULTS All air pollutant models showed significant associations with ischemic stroke in the single lag model. In all air pollutant models excluding particulate matter 10 μm, a significant association was found between nitrogen dioxide exposure and initial admission for ischemic stroke after adjusting for other pollutants. An increment of 10 μg/m3 in nitrogen dioxide concentration at lag 0 and 14 days corresponded to a 0.259% (95% confidence interval, 0.231-0.287%) and 0.110% (95% confidence interval, 0.097-0.124) increase in initial admission for ischemic stroke, respectively. CONCLUSIONS The exposure-response relationship between nitrogen dioxide and initial admissions for ischemic stroke was approximately linear, with a sharper response at higher concentrations. Short-term exposure to nitrogen dioxide was positively associated with initial hospital admission for ischemic stroke.
Association between Air Pollutants and Initial Hospital Admission for Ischemic Stroke in Korea from 2002 to 2013.
Jihye Song,Y. Lim,Inseok Ko,Jong-Yeup Kim,Dong-Kyu Kim
Published 2021 in Journal of Stroke & Cerebrovascular Diseases
ABSTRACT
PUBLICATION RECORD
- Publication year
2021
- Venue
Journal of Stroke & Cerebrovascular Diseases
- Publication date
2021-09-05
- Fields of study
Medicine, Environmental Science
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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