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

Autor: Hae Dong Woo, Dae Sub Song, Sun Ho Choi, Jae Kyung Park, Kyoungho Lee, Hui-Young Yun, Dae-Ryun Choi, Youn-Seo Koo, Hyun-Young Park
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Epidemiology and Health, Vol 44 (2022)
Druh dokumentu: article
ISSN: 2092-7193
DOI: 10.4178/epih.e2022071
Popis: 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.
Databáze: Directory of Open Access Journals