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Open AccessArticle

A Closer Look at the Bivariate Association between Ambient Air Pollution and Allergic Diseases: The Role of Spatial Analysis

1
School of Economic, Political and Policy Sciences, The University of Texas at Dallas, 800 W Campbell Road, Richardson, TX 75080, USA
2
Department of Environmental Health and Safety, College of Health Industry, Eulji University, 553 Sanseong-Daero, Sujeong-Gu, Seongnam-Si, Gyeonggi-Do 13135, Korea
3
Department of Medical Biochemistry & Molecular Biology, Korea University, Anam-dong, Seongbuk-gu, Seoul 136-701, Korea
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2018, 15(8), 1625; https://doi.org/10.3390/ijerph15081625
Received: 26 June 2018 / Revised: 22 July 2018 / Accepted: 30 July 2018 / Published: 1 August 2018
(This article belongs to the Special Issue Asthma Risk and Prevention)
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. View Full-Text
Keywords: allergic disease; air pollution; bivariate association; Geographic Information Systems; spatial analysis allergic disease; air pollution; bivariate association; Geographic Information Systems; spatial analysis
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Kim, D.; Seo, S.; Min, S.; Simoni, Z.; Kim, S.; Kim, M. A Closer Look at the Bivariate Association between Ambient Air Pollution and Allergic Diseases: The Role of Spatial Analysis. Int. J. Environ. Res. Public Health 2018, 15, 1625.

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