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GIS-based Association Between PM10 and Allergic Diseases in Seoul: Implications for Health and Environmental Policy

PURPOSE: The role of PM10 in the development of allergic diseases remains controversial among epidemiological studies, partly due to the inability to control for spatial variations in large-scale risk factors. This study aims to investigate spatial correspondence between the level of PM10 and allerg...

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Autores principales: Seo, SungChul, Kim, Dohyeong, Min, Soojin, Paul, Christopher, Yoo, Young, Choung, Ji Tae
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Academy of Asthma, Allergy and Clinical Immunology; The Korean Academy of Pediatric Allergy and Respiratory Disease 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4695406/
https://www.ncbi.nlm.nih.gov/pubmed/26540499
http://dx.doi.org/10.4168/aair.2016.8.1.32
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author Seo, SungChul
Kim, Dohyeong
Min, Soojin
Paul, Christopher
Yoo, Young
Choung, Ji Tae
author_facet Seo, SungChul
Kim, Dohyeong
Min, Soojin
Paul, Christopher
Yoo, Young
Choung, Ji Tae
author_sort Seo, SungChul
collection PubMed
description PURPOSE: The role of PM10 in the development of allergic diseases remains controversial among epidemiological studies, partly due to the inability to control for spatial variations in large-scale risk factors. This study aims to investigate spatial correspondence between the level of PM10 and allergic diseases at the sub-district level in Seoul, Korea, in order to evaluate whether the impact of PM10 is observable and spatially varies across the subdistricts. METHODS: PM10 measurements at 25 monitoring stations in the city were interpolated to 424 sub-districts where annual inpatient and outpatient count data for 3 types of allergic diseases (atopic dermatitis, asthma, and allergic rhinitis) were collected. We estimated multiple ordinary least square regression models to examine the association of the PM10 level with each of the allergic diseases, controlling for various sub-district level covariates. Geographically weighted regression (GWR) models were conducted to evaluate how the impact of PM10 varies across the sub-districts. RESULTS: PM10 was found to be a significant predictor of atopic dermatitis patient count (P<0.01), with greater association when spatially interpolated at the sub-district level. No significant effect of PM10 was observed on allergic rhinitis and asthma when socioeconomic factors were controlled for. GWR models revealed spatial variation of PM10 effects on atopic dermatitis across the sub-districts in Seoul. The relationship of PM10 levels to atopic dermatitis patient counts is found to be significant only in the Gangbuk region (P<0.01), along with other covariates including average land value, poverty rate, level of education and apartment rate (P<0.01). CONCLUSIONS: Our findings imply that PM10 effects on allergic diseases might not be consistent throughout Seoul. GIS-based spatial modeling techniques could play a role in evaluating spatial variation of air pollution impacts on allergic diseases at the sub-district level, which could provide valuable guidelines for environmental and public health policymakers.
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spelling pubmed-46954062016-01-01 GIS-based Association Between PM10 and Allergic Diseases in Seoul: Implications for Health and Environmental Policy Seo, SungChul Kim, Dohyeong Min, Soojin Paul, Christopher Yoo, Young Choung, Ji Tae Allergy Asthma Immunol Res Original Article PURPOSE: The role of PM10 in the development of allergic diseases remains controversial among epidemiological studies, partly due to the inability to control for spatial variations in large-scale risk factors. This study aims to investigate spatial correspondence between the level of PM10 and allergic diseases at the sub-district level in Seoul, Korea, in order to evaluate whether the impact of PM10 is observable and spatially varies across the subdistricts. METHODS: PM10 measurements at 25 monitoring stations in the city were interpolated to 424 sub-districts where annual inpatient and outpatient count data for 3 types of allergic diseases (atopic dermatitis, asthma, and allergic rhinitis) were collected. We estimated multiple ordinary least square regression models to examine the association of the PM10 level with each of the allergic diseases, controlling for various sub-district level covariates. Geographically weighted regression (GWR) models were conducted to evaluate how the impact of PM10 varies across the sub-districts. RESULTS: PM10 was found to be a significant predictor of atopic dermatitis patient count (P<0.01), with greater association when spatially interpolated at the sub-district level. No significant effect of PM10 was observed on allergic rhinitis and asthma when socioeconomic factors were controlled for. GWR models revealed spatial variation of PM10 effects on atopic dermatitis across the sub-districts in Seoul. The relationship of PM10 levels to atopic dermatitis patient counts is found to be significant only in the Gangbuk region (P<0.01), along with other covariates including average land value, poverty rate, level of education and apartment rate (P<0.01). CONCLUSIONS: Our findings imply that PM10 effects on allergic diseases might not be consistent throughout Seoul. GIS-based spatial modeling techniques could play a role in evaluating spatial variation of air pollution impacts on allergic diseases at the sub-district level, which could provide valuable guidelines for environmental and public health policymakers. The Korean Academy of Asthma, Allergy and Clinical Immunology; The Korean Academy of Pediatric Allergy and Respiratory Disease 2016-01 2015-07-25 /pmc/articles/PMC4695406/ /pubmed/26540499 http://dx.doi.org/10.4168/aair.2016.8.1.32 Text en Copyright © 2016 The Korean Academy of Asthma, Allergy and Clinical Immunology • The Korean Academy of Pediatric Allergy and Respiratory Disease http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Seo, SungChul
Kim, Dohyeong
Min, Soojin
Paul, Christopher
Yoo, Young
Choung, Ji Tae
GIS-based Association Between PM10 and Allergic Diseases in Seoul: Implications for Health and Environmental Policy
title GIS-based Association Between PM10 and Allergic Diseases in Seoul: Implications for Health and Environmental Policy
title_full GIS-based Association Between PM10 and Allergic Diseases in Seoul: Implications for Health and Environmental Policy
title_fullStr GIS-based Association Between PM10 and Allergic Diseases in Seoul: Implications for Health and Environmental Policy
title_full_unstemmed GIS-based Association Between PM10 and Allergic Diseases in Seoul: Implications for Health and Environmental Policy
title_short GIS-based Association Between PM10 and Allergic Diseases in Seoul: Implications for Health and Environmental Policy
title_sort gis-based association between pm10 and allergic diseases in seoul: implications for health and environmental policy
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4695406/
https://www.ncbi.nlm.nih.gov/pubmed/26540499
http://dx.doi.org/10.4168/aair.2016.8.1.32
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