期刊
ENVIRONMENTAL POLLUTION
卷 292, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.envpol.2021.118245
关键词
Depression; Air pollution; Particulate matter; Systematic review; Meta-analysis
The study found an increased risk of depression associated with long-term exposure to PM2.5 and NO2, as well as short-term exposure to PM10, PM2.5, NO2, SO2, O-3, and CO. However, publication bias and high heterogeneity among studies may prevent firm conclusions, highlighting the need for further research with larger sample sizes and better control of potential confounding factors. Research dedicated to understanding the mechanisms underlying the association between air pollution and depression remains necessary.
We provide a comprehensive and updated systematic review and meta-analysis of the association between air pollution exposure and depression, searching PubMed, Embase, and Web of Sciences for relevant articles published up to May 2021, and eventually including 39 studies. Meta-analyses were performed separately according to pollutant type [particulate matter with diameter <= 10 mu m (PM10) and <= 2.5 mu m (PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O-3), and carbon monoxide (CO)] and exposure duration [short- (<30 days) and long-term (>= 30 days)]. Test for homogeneity based on Cochran's Q and I-2 statistics were calculated and the restricted maximum likelihood (REML) random effect model was applied. We assessed overall quality of pooled estimates, influence of single studies on the meta-analytic estimates, sources of between-study heterogeneity, and publication bias. We observed an increased risk of depression associated with long-term exposure to PM2.5 (relative risk: 1.074, 95% confidence interval: 1.021-1.129) and NO2 (1.037, 1.011-1.064), and with short-term exposure to PM10 (1.009, 1.006-1.012), PM2.5 (1.009, 1.007-1.011), NO2 (1.022, 1.012-1.033), SO2 (1.024, 1.010-1.037), O-3 (1.011, 0.997-1.026), and CO (1.062, 1.020-1.105). The publication bias affecting half of the investigated associations and the high heterogeneity characterizing most of the meta-analytic estimates partly prevent to draw very firm conclusions. On the other hand, the coherence of all the estimates after excluding single studies in the sensitivity analysis supports the soundness of our results. This especially applies to the association between PM (2.5) and depression, strengthened by the absence of heterogeneity and of relevant publication bias in both long- and short-term exposure studies. Should further investigations be designed, they should involve large sample sizes, well-defined diagnostic criteria for depression, and thorough control of potential confounding factors. Finally, studies dedicated to the comprehension of the mechanisms underlying the association between air pollution and depression remain necessary.
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