Evidence from numerous epidemiological studies for the relationship between mental disorder and sleep quality was inconclusive and few studies assessed the modification effect of exposure to ambient air PM (particulate matter with an aerodynamic diameter ≤ 1.0 µm) on this association. In this study, 27,572 participants aged 18-79 years from The Henan Rural Cohort study were included in the final analyses. The Patient Health Questionnaire-2 (PHQ-2) and Generalized Anxiety Disorder-2 (GAD-2) scales were used to estimate the frequency of depression and anxiety symptoms of all participants, respectively. The Pittsburgh Sleep Quality Index (PSQI) scale was used to assess night sleep quality and PSQI global score (GSC) ≥ 6 was classified as poor sleep quality. The three-year average exposure concentration of PM before the baseline survey was determined as long-term exposure concentration of ambient PM. Logistic regression model was conducted to estimate the independent or joint effect of depression/anxiety symptoms and ambient PM exposure on poor sleep quality. In the adjusted models, the odds ratios (ORs) and 95% confidence intervals (95% CIs) of poor sleep quality associated with depression and anxiety symptoms were 3.75 (3.37, 4.17) and 3.42 (3.06, 3.81), respectively, and that associated with long-term exposure to PM was 1.06 (1.03, 1.09). An interaction effect was observed between anxiety symptoms score and PM concentration on poor sleep quality. With the increment of PM concentration, the association was strengthened between depression/anxiety symptoms and poor sleep quality. Besides, compared with the reference group, the ORs (95% CIs) of poor sleep quality in those with comorbidity of depression and anxiety symptoms were 4.98 (3.95, 6.29), 5.23 (3.98, 6.87), 5.76 (4.42, 7.49), and 5.58 (3.83, 8.14), respectively, from the first to the fourth quartile level of the PM concentration. These findings suggested that long-term exposure to PM strengthened the association of depression/anxiety symptoms with poor sleep quality in rural China.

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http://dx.doi.org/10.1016/j.ecoenv.2021.111932DOI Listing

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