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 μm (PM10) and ≤2.5 μm (PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO)] and exposure duration [short- (<30 days) and long-term (≥30 days)]. Test for homogeneity based on Cochran's Q and I2 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), O3 (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 PM2.5 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.

Air pollution exposure and depression : A comprehensive updated systematic review and meta-analysis / E. Borroni, A.C. Pesatori, V. Bollati, M. Buoli, M. Carugno. - In: ENVIRONMENTAL POLLUTION. - ISSN 0269-7491. - 292:Pt A(2022 Jan 01), pp. 118245.1-118245.27. [10.1016/j.envpol.2021.118245]

Air pollution exposure and depression : A comprehensive updated systematic review and meta-analysis

E. Borroni;A.C. Pesatori
;
V. Bollati;M. Buoli;M. Carugno
2022

Abstract

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 μm (PM10) and ≤2.5 μm (PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO)] and exposure duration [short- (<30 days) and long-term (≥30 days)]. Test for homogeneity based on Cochran's Q and I2 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), O3 (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 PM2.5 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.
Air pollution; Depression; Meta-analysis; Particulate matter; Systematic review
Settore MED/44 - Medicina del Lavoro
29-set-2021
Article (author)
File in questo prodotto:
File Dimensione Formato  
Borroni_EnvironPoll_2021.pdf

accesso aperto

Tipologia: Publisher's version/PDF
Dimensione 8.29 MB
Formato Adobe PDF
8.29 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/875865
Citazioni
  • ???jsp.display-item.citation.pmc??? 0
  • Scopus 18
  • ???jsp.display-item.citation.isi??? 15
social impact