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Journal Article Epublish 12 citations

PubMed: 38172858 DOI: 10.1186/s12940-023-01043-1

Particulate matters (PM, PM) 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.

Environ Health 23(1):4

Authors: Hyunkyung Park, Cinoo Kang, Ho Kim

Affiliations

  • Department of Public Health Sciences, Graduate School of Public Health, Seoul National University, 1 Gwanak-Ro, Gwanak-Gu, Seoul, 08826, Republic of Korea. National Evidence-Based Health Care Collaborating Agency, 400 Neungdong-Ro, Gwangjin-Gu, Seoul, 04933, Republic of Korea.
  • Department of Public Health Sciences, Graduate School of Public Health, Seoul National University, 1 Gwanak-Ro, Gwanak-Gu, Seoul, 08826, Republic of Korea.
  • Department of Public Health Sciences, Graduate School of Public Health, Seoul National University, 1 Gwanak-Ro, Gwanak-Gu, Seoul, 08826, Republic of Korea. Institute of Sustainable Development, Seoul National University, 1 Gwanak-Ro, Gwanak-Gu, Seoul, 08826, Republic of Korea.

Abstract

BACKGROUND

There is a growing concern that particulate matter (PM) such as PM and PM 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 and PM, 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 and PM concentrations were calculated for the study period from the monthly prediction concentrations produced by a machine-learning-based ensemble model (cross-validated R: 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 and PM 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 PM (OR 1.36, 95% CI 1.20-1.56) and PM (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 (NO and O) 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 and PM 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.

MeSH

Depression, Longitudinal Studies, Environmental Pollutants, Aging, Environmental Illness, Risk, Aged, Population Density, Air Pollutants, Particulate Matter

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