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 PM_2.5 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 PM_2.5 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 PM_2.5 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 PM_2.5 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 μ g / m 3 increments in PM_2.5 (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 PM_2.5 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. [ABSTRACT FROM AUTHOR]