Association between exposure to heavy metals in atmospheric particulate matter and sleep quality: A nationwide data linkage study

Byung Kwon Kim, Changsoo Kim, Jaelim Cho

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Background: Recent studies have demonstrated that long-term exposure to particulate matter (PM) is associated with poor sleep quality. However, no studies have linked PM constituents, particularly heavy metals, to sleep quality. Objective: This study investigated the association between exposure to heavy metals in PM and sleep quality. Methods: We obtained nationwide data from the Korean Community Health Survey conducted in 2018 among adults aged 19–80 years. Sleep quality was evaluated using Pittsburgh Sleep Quality Index (PSQI). Poor sleep quality was defined as PSQI ≥5. One-year and three-month average concentrations of heavy metals (lead, manganese, cadmium, and aluminum) in PM with diameter ≤10 μm were obtained from nationwide air quality monitoring data and linked to the survey data based on individual district-level residential addresses. Logistic regression analyses were performed after adjusting for age, gender, education level, marital status, smoking status, alcohol consumption, history of hypertension, and history of diabetes mellitus. Results: Of 32,050 participants, 17,082 (53.3%) reported poor sleep quality. Increases in log-transformed one-year average lead (odds ratio, 1.14; 95% confidence interval, 1.08−1.20), manganese (1.31; 1.25−1.37), cadmium (1.03; 1.00−1.05), and aluminum concentrations (1.17; 1.10−1.25) were associated with poor sleep quality. Increases in log-transformed three-month average manganese (odds ratio, 1.13; 95% confidence interval, 1.09−1.17) and aluminum concentrations (1.28; 1.21−1.35) were associated with poor sleep quality. Conclusion: We showed for the first time that exposure to airborne lead, manganese, cadmium, and aluminum were associated with poor sleep quality. This study may be limited by self-reported sleep quality and district-level exposure data.

Original languageEnglish
Article number118217
JournalEnvironmental Research
Volume247
DOIs
Publication statusPublished - 2024 Apr 15

Bibliographical note

Publisher Copyright:
© 2024

All Science Journal Classification (ASJC) codes

  • Biochemistry
  • General Environmental Science

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