%0 Journal Article
%T Long-term effects of fine particulate matter components on depression among middle-aged and elderly adults in China: A nationwide cohort study.
%A Liu X
%A Li Y
%A Xie W
%A Hu M
%A Li S
%A Hu Y
%A Ling K
%A Zhang S
%A Wei J
%J J Affect Disord
%V 361
%N 0
%D 2024 Sep 15
%M 38917887
%F 6.533
%R 10.1016/j.jad.2024.06.066
%X <B>BACKGROUND: </B>Fine particulate matter (PM2.5) has been implicated in various health concerns. However, a comprehensive understanding of the specific PM2.5 components affecting depression remains limited.<BR><B>METHODS: </B>This study conducted a Cox proportional-hazards model to assess the effect of PM2.5 components on the incidence of depression based on the China Health and Retirement Longitudinal Study (CHARLS). Participants with 10-item Center for Epidemiologic Studies Depression Scale (CESD-10) score of 10 or higher were classified as exhibiting depression.<BR><B>RESULTS: </B>Our findings demonstrated a significant positive correlation between long-term exposure to black carbon (BC), sulfate (SO42-), and organic matter (OM) components of PM2.5 and the prevalence of depression. Per 1 Interquartile Range (IQR) increment in 3-year average concentrations of BC, OM, and SO42- were associated with the hazard ratio (HR) of 1.54 (95 % confidence intervals (CI): 1.44, 1.64), 1.24 (95%CI: 1.16, 1.34) and 1.25 (95%CI: 1.16, 1.35). Notably, females, younger individuals, those with lower educational levels, urban residents, individuals who were single, widowed, or divorced, and those living in multi-story houses exhibited heightened vulnerability to the adverse effects of PM2.5 components on depression.<BR><B>CONCLUSIONS: </B>Firstly, pollutant data is confined to subjects' fixed addresses, overlooking travel and international residence history. Secondly, the analysis only incorporates five fine particulate components, leaving room for further investigation into the remaining fine particulate components in future studies.<BR><B>CONCLUSIONS: </B>This study provides robust evidence supporting the detrimental impact of PM2.5 components on depression. The identification of specific vulnerable populations contributes to a deeper understanding of the underlying mechanisms involved in the relationship between PM2.5 components and depression.