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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 (PM 10), fine particulate matter (PM 2.5), and nitrogen dioxide (NO 2) 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 NO 2 , 5.32 mg/dL (95% CI: 1.22-9.41) per IQR increment of PM 10 at a moving average of 0-6 days, and 4.69 mg/dL (95% CI: 0.48-8.91) per IQR increment of PM 2.5 at a moving average of 0-5 days. HbA1c increased by 0.57% (95% CI: 0.04-1.09) per IQR increment of PM 10 at a moving average of 0-60 days and 0.34% (95% CI: 0.04-0.63) per IQR increment of PM 2.5 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.

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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, <i>si-gun-gu</i> (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 <i>si-gun-gu</i> 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.