A Closer Look at the Bivariate Association between Ambient Air Pollution and Allergic Diseases: The Role of Spatial Analysis
- Authors
- Kim, Dohyeong; Seo, SungChul; Min, Soojin; Simoni, Zachary; Kim, Seunghyun; Kim, Myoungkon
- Issue Date
- 8월-2018
- Publisher
- MDPI
- Keywords
- allergic disease; air pollution; bivariate association; Geographic Information Systems; spatial analysis
- Citation
- INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, v.15, no.8
- Indexed
- SCIE
SSCI
SCOPUS
- Journal Title
- INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
- Volume
- 15
- Number
- 8
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/74199
- DOI
- 10.3390/ijerph15081625
- ISSN
- 1661-7827
- Abstract
- Although previous ecological studies investigating the association between air pollution and allergic diseases accounted for temporal or seasonal relationships, few studies address spatial non-stationarity or autocorrelation explicitly. Our objective was to examine bivariate correlation between outdoor air pollutants and the prevalence of allergic diseases, highlighting the limitation of a non-spatial correlation measure, and suggesting an alternative to address spatial autocorrelation. The 5-year prevalence data (2011-2015) of allergic rhinitis, atopic dermatitis, and asthma were integrated with the measures of four major air pollutants (SO2, NO2, CO, and PM10) for each of the 423 sub-districts of Seoul. Lee's L statistics, which captures how much bivariate associations are spatially clustered, was calculated and compared with Pearson's correlation coefficient for each pair of the air pollutants and allergic diseases. A series of maps showing spatiotemporal patterns of allergic diseases at the sub-district level reveals a substantial degree of spatial heterogeneity. A high spatial autocorrelation was observed for all pollutants and diseases, leading to significant dissimilarities between the two bivariate association measures. The local L statistics identifies the areas where a specific air pollutant is considered to be contributing to a type of allergic disease. This study suggests that a bivariate correlation measure between air pollutants and allergic diseases should capture spatially-clustered phenomenon of the association, and detect the local instability in their relationships. It highlights the role of spatial analysis in investigating the contribution of the local-level spatiotemporal dynamics of air pollution to trends and the distribution of allergic diseases.
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Collections - Graduate School > Department of Biomedical Sciences > 1. Journal Articles
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