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.

Background: In South Korea, the epidemiological characteristics of children and adolescents infected with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) have not been reported to date. The purpose of this study was to identify major epidemiological characteristics and transmission patterns of coronavirus disease 2019 (COVID-19) in children and adolescents. Methods: This study was conducted through a system integrated in an epidemiological investigation by the Korea Disease Control and Prevention Agency from January 20, 2020, to June 5, 2021. We analyzed the epidemiological characteristics of 14,967 children and adolescents with COVID-19 according to the age groups and transmission age patterns of 3721 infector-infectee pairs in South Korea. Results: Among the total confirmed COVID-19 cases, 14,967 patients were aged 0-18 years. The most affected age group among children and adolescents were those aged 16-18 years (3589, 24.0%). For all age groups, the infection route through friends and family members (31.9%) was the highest. For the contact age pattern analysis, infection from infectors aged 30-49 years to infectees aged 0-12 years showed a statistically significant relation (p <0.001) compared to that in other age groups. On the other hand, among the infectees aged 13-15 years and 16-18 years were significantly related with adolescents aged 10-19 years (p <0.05). Conclusion: These results suggest that adolescents aged 13-18 years were more infected with COVID-19 than those aged 0-12 years. Furthermore, they are particularly more likely to be infected by friends and family members. Besides, in patients aged 13-18 years, transmission of SARS-CoV-2 was more common from adolescents to adolescents than from adults to adolescents. This research will provide scientific evidence for school policies and vaccine strategies for COVID-19 prevention in children and adolescents.

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.

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OBJECTIVESAir 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.METHODSData 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. Levels of exposure were divided into five quintiles according to the annual concentration of nitrogen dioxide (NO2), and were analyzed using a single-pollutant model using NO2 concentration only, and a multi-pollutant model adjusted for the concentration of particulate matter <10 μm in diameter.RESULTSAnalysis of men and women in various age groups showed the highest odds ratio (OR) for subjective stress level at the highest NO2 concentration quintile in men and women aged 30–64 years (men: 2.91; 95% confidence interval [CI], 2.12 to 4.01; women: 1.82; 95% CI, 1.32 to 2.51). As the NO2 concentration quintile increased, the OR increased. Men showed higher ORs than women in all strata.CONCLUSIONSIn the present study, annual NO2 concentrations were found to be associated with subjective stress levels. This association was especially clear among socioeconomically active men and women aged 30-64 years.