Association of long-term exposure to air pollution with chronic sleep deprivation in South Korea: A community-level longitudinal study, 2008-2018

Long-term exposure to PM2.5 and mortality in a national cohort in South Korea: effect modification by community deprivation, medical infrastructure, and greenness

BACKGROUND

Long-term exposure to PM2.5 has been linked to increased mortality risk. However, limited studies have examined the potential modifying effect of community-level characteristics on this association, particularly in Asian contexts. This study aimed to estimate the effects of long-term exposure to PM2.5 on mortality in South Korea and to examine whether community-level deprivation, medical infrastructure, and greenness modify these associations.

METHODS

We conducted a nationwide cohort study using the National Health Insurance Service-National Sample Cohort. A total of 394,701 participants aged 30 years or older in 2006 were followed until 2019. Based on modelled PM2.5 concentrations, 1 to 3-year and 5-year moving averages of PM2.5 concentrations were assigned to each participant at the district level. Time-varying Cox proportional-hazards models were used to estimate the association between PM2.5 and non-accidental, circulatory, and respiratory mortality. We further conducted stratified analysis by community-level deprivation index, medical index, and normalized difference vegetation index to represent greenness.

RESULTS

PM2.5 exposure, based on 5-year moving averages, was positively associated with non-accidental (Hazard ratio, HR: 1.10, 95% Confidence Interval, CI: 1.01, 1.20, per 10 µg/m3 increase) and circulatory mortality (HR: 1.22, 95% CI: 1.01, 1.47). The 1-year moving average of PM2.5 was associated with respiratory mortality (HR: 1.33, 95% CI: 1.05, 1.67). We observed higher associations between PM2.5 and mortality in communities with higher deprivation and limited medical infrastructure. Communities with higher greenness showed lower risk for circulatory mortality but higher risk for respiratory mortality in association with PM2.5.

CONCLUSIONS

Our study found mortality effects of long-term PM2.5 exposure and underlined the role of community-level factors in modifying these association. These findings highlight the importance of considering socio-environmental contexts in the design of air quality policies to reduce health disparities and enhance overall public health outcomes.

Association between long-term PM2.5 exposure and risk of Kawasaki disease in children: A nationwide longitudinal cohort study

BACKGROUND

Based on previous studies suggesting air pollution as a potential risk factor for Kawasaki Disease (KD), we examined the association of long-term exposure to childhood fine particulate matter (PM2.5) with the risk of KD.

METHODS

We used National Health Insurance Service-National Sample Cohort data from 2002 to 2019, which included beneficiaries aged 0 years at enrollment and followed-up until the onset of KD or age 5 years. The onset of KD was defined as the first hospital visit record with a primary diagnostic code of M30.3, based on the 10th revision of the International Classification of Diseases, and with an intravenous immunoglobulin (IVIG) prescription. We assigned PM2.5 concentrations to 226 districts, based on mean annual predictions from a machine learning-based ensemble prediction model. We performed Cox proportional-hazards modeling with time-varying exposures and confounders.

RESULTS

We identified 134,634 individuals aged five or less at enrollment and, of these, 1220 individuals who had a KD onset and an IVIG prescription during study period. The average annual concentration of PM2.5 exposed to the entire cohort was 28.2 μg/m³ (Standard Deviation 2.9). For each 5 μg/m³ increase in annual PM2.5 concentration, the hazard ratio of KD was 1.21 (95% CI 1.05-1.39).

CONCLUSIONS

In this nationwide, population-based, cohort study, long-term childhood exposure to PM2.5 was associated with an increased incidence of KD in children. The study highlights plausible mechanisms for the association between PM2.5 and KD, but further studies are needed to confirm our findings.

Particulate matters (PM2.5, PM10) and the risk of depression among middle-aged and older population: analysis of the Korean Longitudinal Study of Aging (KLoSA), 2016-2020 in South Korea

BACKGROUND

There is a growing concern that particulate matter (PM) such as PM2.5 and PM10 has contributed to exacerbating psychological disorders, particularly depression. However, little is known about the roles of these air pollutants on depression in elderly. Therefore, this study aimed to examine the association between PM2.5 and PM10, and depression in the elderly population in South Korea.

METHODS

We used panel survey data, the Korean Longitudinal Study of Aging (KLoSA), administered by the Labor Institute during the study period of 2016, 2018, and 2020 covering 217 districts in South Korea (n = 7674). Annual district-specific PM2.5 and PM10 concentrations were calculated for the study period from the monthly prediction concentrations produced by a machine-learning-based ensemble model (cross-validated R2: 0.87), then linked to the people matching with year and their residential district. We constructed a generalized estimating equation (GEE) model with a logit link to identify the associations between each of the long-term PM2.5 and PM10 exposures and depression (CES-D 10) after adjusting for individual and regional factors as confounders.

RESULTS

In single-pollutant models, we found that long-term 10 [Formula: see text] increments in PM2.5 (OR 1.36, 95% CI 1.20-1.56) and PM10 (OR 1.19, 95% CI 1.10-1.29) were associated with an increased risk of depression in the elderly. Associations were consistent after adjusting for other air pollutants (NO2 and O3) in two-pollutant models. In addition, the impacts substantially differed by regions grouped by the tertile of the population density, for which the risks of particulate matters on depression were substantial in the middle- or high-population-density areas in contrast to the low-population-density areas.

CONCLUSIONS

Long-term exposure to PM2.5 and PM10 was associated with a higher risk of developing depression in elderly people. The impact was modified by the population density level of the region where they reside.