GIS-based association between PM10 and allergic diseases in Seoul: Implications for health and environmental policy

Sung Chul Seo, Dohyeong Kim, Soojin Min, Christopher Paul, Young Yoo, Ji-Tae Choung

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

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 sub-districts. 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.

Original languageEnglish
Pages (from-to)32-40
Number of pages9
JournalAllergy, Asthma and Immunology Research
Volume8
Issue number1
DOIs
Publication statusPublished - 2016 Jan 1

Fingerprint

Environmental Policy
Health Policy
Atopic Dermatitis
Asthma
Environmental Health
Air Pollution
Poverty
Korea
Least-Squares Analysis
Seoul
Inpatients
Epidemiologic Studies
Outpatients
Public Health
Guidelines
Education

Keywords

  • Allergic rhinitis
  • Asthma
  • Atopic dermatitis
  • Particulate matter
  • Spatial analysis

ASJC Scopus subject areas

  • Immunology and Allergy
  • Immunology
  • Pulmonary and Respiratory Medicine

Cite this

GIS-based association between PM10 and allergic diseases in Seoul : Implications for health and environmental policy. / Seo, Sung Chul; Kim, Dohyeong; Min, Soojin; Paul, Christopher; Yoo, Young; Choung, Ji-Tae.

In: Allergy, Asthma and Immunology Research, Vol. 8, No. 1, 01.01.2016, p. 32-40.

Research output: Contribution to journalArticle

@article{a35ffaa4ac994d89aadf98b54be000a5,
title = "GIS-based association between PM10 and allergic diseases in Seoul: Implications for health and environmental policy",
abstract = "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 sub-districts. 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.",
keywords = "Allergic rhinitis, Asthma, Atopic dermatitis, Particulate matter, Spatial analysis",
author = "Seo, {Sung Chul} and Dohyeong Kim and Soojin Min and Christopher Paul and Young Yoo and Ji-Tae Choung",
year = "2016",
month = "1",
day = "1",
doi = "10.4168/aair.2016.8.1.32",
language = "English",
volume = "8",
pages = "32--40",
journal = "Allergy, Asthma and Immunology Research",
issn = "2092-7355",
publisher = "Korean Academy of Asthma, Allergy and Clinical Immunology",
number = "1",

}

TY - JOUR

T1 - GIS-based association between PM10 and allergic diseases in Seoul

T2 - Implications for health and environmental policy

AU - Seo, Sung Chul

AU - Kim, Dohyeong

AU - Min, Soojin

AU - Paul, Christopher

AU - Yoo, Young

AU - Choung, Ji-Tae

PY - 2016/1/1

Y1 - 2016/1/1

N2 - 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 sub-districts. 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.

AB - 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 sub-districts. 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.

KW - Allergic rhinitis

KW - Asthma

KW - Atopic dermatitis

KW - Particulate matter

KW - Spatial analysis

UR - http://www.scopus.com/inward/record.url?scp=84946771734&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84946771734&partnerID=8YFLogxK

U2 - 10.4168/aair.2016.8.1.32

DO - 10.4168/aair.2016.8.1.32

M3 - Article

AN - SCOPUS:84946771734

VL - 8

SP - 32

EP - 40

JO - Allergy, Asthma and Immunology Research

JF - Allergy, Asthma and Immunology Research

SN - 2092-7355

IS - 1

ER -