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 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.

Establishment of the Korea National Health and Nutrition Examination Survey air pollution study dataset for the researchers on the health impact of ambient air pollution.

To provide a nationwide representative dataset for the study on health impact of air pollution, we combined the data from the Korea National Health and Nutrition Examination Survey with the daily air quality and weather data by matching the date of examination and the residential address of the participants. The database of meteorological factors and air quality as sources of exposure data were estimated using the Community Multiscale Air Quality model. The linkage dataset was merged by three ways; administrative district, si-gun-gu (city, county, and district), and geocode (in latitude and longitude coordinate units) based on the participants' residential address, respectively.

Impacts of ambient air pollution on glucose metabolism in Korean adults: a Korea National Health and Nutrition Examination Survey study.

Background: Exposure to air pollution was reported to affect glucose metabolism, increasing the risk of diabetes mellitus. We conducted an epidemiological study on glucose metabolism and air pollution by exploring the levels of fasting blood glucose (FBG) and hemoglobin A1c (HbA1c) with changes in ambient air quality, depending on the characteristics of the susceptible population.

Methods: We carried out a cross-sectional analysis of a nationally representative sample of 10,014 adults (4267 in male and 5747 in female) from the Korea National Health and Nutrition Examination Survey in 2012 and 2013 along with data from the Korean Air Quality Forecasting System.

Ambient air quality and subjective stress level using Community Health Survey data in Korea.

Objectives: Air pollution causes various disease in exposed populations, and can lead to premorbid health effects manifested as both physical and psychological functional impairment. The present study investigated the subjective stress level in daily life in relation to the level of air pollution.

Methods: Data from the Community Health Survey (2013), comprising 99,162 men, and 121,273 women residing in 253 healthcare administrative districts, were combined with air pollutant concentration modelling data from the Korean Air Quality Forecasting System, and were stratified by subjective stress levels into five strata for multiple logistic regression.