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Integrated dataset of the Korean Genome and Epidemiology Study cohort with estimated air pollution data

Public concern about the adverse health effects of air pollution has grown rapidly in Korea, and there has been increasing demand for research on ways to minimize the health effects of air pollution. Integrating large epidemiological data and air pollution exposure levels can provide a data infrastr...

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Autores principales: Woo, Hae Dong, Song, Dae Sub, Choi, Sun Ho, Park, Jae Kyung, Lee, Kyoungho, Yun, Hui-Young, Choi, Dae-Ryun, Koo, Youn-Seo, Park, Hyun-Young
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society of Epidemiology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9849844/
https://www.ncbi.nlm.nih.gov/pubmed/36108673
http://dx.doi.org/10.4178/epih.e2022071
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author Woo, Hae Dong
Song, Dae Sub
Choi, Sun Ho
Park, Jae Kyung
Lee, Kyoungho
Yun, Hui-Young
Choi, Dae-Ryun
Koo, Youn-Seo
Park, Hyun-Young
author_facet Woo, Hae Dong
Song, Dae Sub
Choi, Sun Ho
Park, Jae Kyung
Lee, Kyoungho
Yun, Hui-Young
Choi, Dae-Ryun
Koo, Youn-Seo
Park, Hyun-Young
author_sort Woo, Hae Dong
collection PubMed
description Public concern about the adverse health effects of air pollution has grown rapidly in Korea, and there has been increasing demand for research on ways to minimize the health effects of air pollution. Integrating large epidemiological data and air pollution exposure levels can provide a data infrastructure for studying ambient air pollution and its health effects. The Korean Genome and Epidemiology Study (KoGES), a large population-based study, has been used in many epidemiological studies of chronic diseases. Therefore, KoGES cohort data were linked to air pollution data as a national resource for air pollution studies. Air pollution data were produced using community multiscale air quality modeling with additional adjustment of monitoring data, satellite-derived aerosol optical depth, normalized difference vegetation index, and meteorological data to increase the accuracy and spatial resolution. The modeled air pollution data were linked to the KoGES cohort based on participants’ geocoded residential addresses in grids of 1 km (particulate matter) or 9 km (gaseous air pollutants and meteorological variables). As the integrated data become available to all researchers, this resource is expected to serve as a useful infrastructure for research on the health effects of air pollution.
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spelling pubmed-98498442023-01-26 Integrated dataset of the Korean Genome and Epidemiology Study cohort with estimated air pollution data Woo, Hae Dong Song, Dae Sub Choi, Sun Ho Park, Jae Kyung Lee, Kyoungho Yun, Hui-Young Choi, Dae-Ryun Koo, Youn-Seo Park, Hyun-Young Epidemiol Health Data Profile Public concern about the adverse health effects of air pollution has grown rapidly in Korea, and there has been increasing demand for research on ways to minimize the health effects of air pollution. Integrating large epidemiological data and air pollution exposure levels can provide a data infrastructure for studying ambient air pollution and its health effects. The Korean Genome and Epidemiology Study (KoGES), a large population-based study, has been used in many epidemiological studies of chronic diseases. Therefore, KoGES cohort data were linked to air pollution data as a national resource for air pollution studies. Air pollution data were produced using community multiscale air quality modeling with additional adjustment of monitoring data, satellite-derived aerosol optical depth, normalized difference vegetation index, and meteorological data to increase the accuracy and spatial resolution. The modeled air pollution data were linked to the KoGES cohort based on participants’ geocoded residential addresses in grids of 1 km (particulate matter) or 9 km (gaseous air pollutants and meteorological variables). As the integrated data become available to all researchers, this resource is expected to serve as a useful infrastructure for research on the health effects of air pollution. Korean Society of Epidemiology 2022-09-07 /pmc/articles/PMC9849844/ /pubmed/36108673 http://dx.doi.org/10.4178/epih.e2022071 Text en ©2022, Korean Society of Epidemiology https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Data Profile
Woo, Hae Dong
Song, Dae Sub
Choi, Sun Ho
Park, Jae Kyung
Lee, Kyoungho
Yun, Hui-Young
Choi, Dae-Ryun
Koo, Youn-Seo
Park, Hyun-Young
Integrated dataset of the Korean Genome and Epidemiology Study cohort with estimated air pollution data
title Integrated dataset of the Korean Genome and Epidemiology Study cohort with estimated air pollution data
title_full Integrated dataset of the Korean Genome and Epidemiology Study cohort with estimated air pollution data
title_fullStr Integrated dataset of the Korean Genome and Epidemiology Study cohort with estimated air pollution data
title_full_unstemmed Integrated dataset of the Korean Genome and Epidemiology Study cohort with estimated air pollution data
title_short Integrated dataset of the Korean Genome and Epidemiology Study cohort with estimated air pollution data
title_sort integrated dataset of the korean genome and epidemiology study cohort with estimated air pollution data
topic Data Profile
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9849844/
https://www.ncbi.nlm.nih.gov/pubmed/36108673
http://dx.doi.org/10.4178/epih.e2022071
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