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. 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.

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. During the study period, the exposure dataset of 85,018 individuals (38,306 men and 46,712 women) whose examination dates were recorded were obtained. According to the definition of exposure period, the dataset was combined with the data on short-term, mid-term, and long-term exposure to air pollutants and the meteorological indices. Calculation of the daily merged dataset's average air pollution linked by si-gun-gu and geocode units showed similar results. This study generated a daily average of meteorological indices and air pollution exposure dataset for all regions including rural and remote areas in Korea for 11 years. It is expected to provide a platform for the researchers studying the health impact of air pollution and climate change on the representative population and area, which may facilitate the establishment of local health care plans by understanding the residents' health status at the local as well as national level.

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. The analysis was performed using a generalized linear model stratified by sex, age, and presence of diabetes. We assessed the changes in FBG and HbA1c associated with exposures to particulate matter (PM10), fine particulate matter (PM2.5), and nitrogen dioxide (NO2) after controlling for confounders. RESULTS: There were 1110 participants with diabetes (557 in male and 553 in female). Overall, the FBG level increased by 7.83 mg/dL (95% confidence interval [CI]: 2.80-12.87) per interquartile range (IQR) increment of NO2, 5.32 mg/dL (95% CI: 1.22-9.41) per IQR increment of PM10 at a moving average of 0-6 days, and 4.69 mg/dL (95% CI: 0.48-8.91) per IQR increment of PM2.5 at a moving average of 0-5 days. HbA1c increased by 0.57% (95% CI: 0.04-1.09) per IQR increment of PM10 at a moving average of 0-60 days and 0.34% (95% CI: 0.04-0.63) per IQR increment of PM2.5 at a moving average of 0-75 days. The change in FBG and HbA1c increased more in the diabetic group, especially in males aged 65 years or more. There was a strong association between elevation in diabetes-related parameters and exposure to air pollution. CONCLUSIONS: Our study provides scientific evidence supporting that short- and mid-term exposure to air pollution is associated with changes in biological markers related to diabetes. This finding suggests that the impact of air pollution should be reflected in chronic disease management when establishing local health care policies.

Space-Time Relationship between Short-Term Exposure to Fine and Coarse Particles and Mortality in a Nationwide Analysis of Korea: A Bayesian Hierarchical Spatio-Temporal Model.

Previous studies have shown an association between mortality and ambient air pollution in South Korea. However, these studies may have been subject to bias, as they lacked adjustment for spatio-temporal structures. This paper addresses this research gap by examining the association between air pollution and cause-specific mortality in South Korea between 2012 and 2015 using a two-stage Bayesian spatio-temporal model. We used 2012-2014 mortality and air pollution data for parameter estimation (i.e., model fitting) and 2015 data for model validation. Our results suggest that the relative risks of total, cardiovascular, and respiratory mortality were 1.028, 1.047, and 1.045, respectively, with every 10-µg/m3 increase in monthly PM2.5 (fine particulate matter) exposure. These findings warrant protection of populations who experience elevated ambient air pollution exposure to mitigate mortality burden in South Korea.

Reduced sulfur compounds in ambient air surrounding an industrial region in Korea.

The atmospheric concentrations of several reduced sulfur compounds (RSCs) including H(2)S, CH(3)SH, DMS, CS(2), and DMDS were measured concurrently from a series of field campaigns covering multiple locations in the surroundings of a large industrial region (August 2004 to September 2005). These field studies have been designed and undertaken to inspect the concentrations of RSCs in ambient air. The RSC concentrations were found to occur in a highly variable range. H(2)S (1.06 +/- 2.07 ppb) was found to be the most abundant RSC followed by CS(2) (0.84 +/- 0.54 ppb), DMDS (0.36 +/- 1.21 ppb), DMS (0.24 +/- 0.83 ppb), and CH(3)SH (0.11 +/- 0.23 ppb). The RSC levels measured at the study area were comparable to those observed previously from other polluted environmental settings. When these RSC data were examined further in terms of spatial (industrial vs. non-industrial sites) and seasonal (summer vs. winter seasons) grouping schemes, differences in their concentration levels were statistically insignificant in most cases. In contrast, there were fairly strong variations in temporal patterns over a diurnal cycle. If these RSC concentration data were converted to diagnose the malodor strengths, their effects were in most cases insignificant with minor contribution towards odor nuisances.