Causal effects of key air pollutants and meteorology on ischemic stroke onset: A convergent cross-mapping approach
Background: Evidence suggests that environmental factors may influence the risk of ischemic stroke(IS).11 ischemic stroke(IS). Nevertheless, the majority of existing research has concentrated on correlation analysis, with only a limited number of studies employing specific methodologies to investiga...
Saved in:
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-02-01
|
| Series: | Ecotoxicology and Environmental Safety |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0147651325001976 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Background: Evidence suggests that environmental factors may influence the risk of ischemic stroke(IS).11 ischemic stroke(IS). Nevertheless, the majority of existing research has concentrated on correlation analysis, with only a limited number of studies employing specific methodologies to investigate the causal dynamics of this relationship with external drivers. Method: In this study, we employed an approach known as convergent cross-mapping to identify and elucidate the causal effects of significant air pollutants and meteorological factors on the pathogenesis of IS. The city of Shouguang in the Shandong Peninsula region was selected for this study, primarily because of the environmental characteristics of the region and the notable prevalence of cases during the study period. Results: Key air pollutants and several meteorological factors in the region have a causal effects on IS. A general trend can be drawn. SO222 sulfur dioxide(SO2) (ρ = 0.215, ∂=0.016), PM2.533 Particulate matter with a diameter< 2.5 μm(PM2.5) (ρ = 0.077, ∂=0.002), and PM1044 Particulate matter with a diameter< 10 μm(PM10) (ρ = 0.058, ∂=0.0014) had a positive causal effects on IS,and relative humidity (ρ = 0.050, ∂=-0.009) tended to reduce the number of IS cases. Conclusion: Through this case study, a causal network was developed with the aim of integrating the study of the interactions between variables and providing a clear model to aid the management of IS. |
|---|---|
| ISSN: | 0147-6513 |