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Lim Y, Choi Y, Kang E, Jeong Y, Park J, Han HW. Association between short- and medium-term exposure to air pollutants and depressive episode using comprehensive air quality index among the population in South Korea. J Affect Disord 2024; 356:307-315. [PMID: 38574871 DOI: 10.1016/j.jad.2024.03.164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 02/23/2024] [Accepted: 03/28/2024] [Indexed: 04/06/2024]
Abstract
BACKGROUND Currently, air pollution is suggested as a risk factor for depressive episodes. Our study aimed to consider multiple air pollutants simultaneously, and continuously evaluate air pollutants using comprehensive air quality index (CAI) with depressive episode risk. METHODS Using a nationally representative sample survey from South Korea between 2014 and 2020, 20,796 participants who underwent health examination and Patient Depression Questionnaire-9 were included in the study. Six air pollutants (PM10, PM2.5, O3, CO, SO2, NO2) were measured for the analysis. Every air pollutant was standardized by air quality index (AQI) and CAI was calculated for universal representation. Using logistic regression, short- and medium-term exposure by AQI and CAI with the risk of depressive episode was calculated by odds ratio and 95 % confidence interval (CI). Furthermore, consecutive measurements of CAI over 1-month time intervals were evaluated with the risk of depressive episodes. Every analysis was conducted seasonally. RESULTS There were 950 depressive episodes occurred during the survey. An increase in AQI for short-term exposure (0-30 days) showed higher risk of depressive episode in CO, while medium-term exposure (0-120 days) showed higher risk of depressive episode in CO, SO2, PM2.5, and PM10. During the cold season, the exposure to at least one abnormal CAI within 1-month intervals over 120 days was associated with a 68 % (95 % CI 1.11-2.54) increase in the risk of depressive episode. CONCLUSIONS Short- and medium-term exposure of air pollution may be associated with an increased risk of depressive episodes, especially for cold season.
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Affiliation(s)
- Yohwan Lim
- Department of Biomedical Informatics, CHA University School of Medicine, CHA University, 335 Pangyo-ro, Seongnam 13448, Republic of Korea; Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, South Korea.
| | - Yunseo Choi
- Department of Biomedical Informatics, CHA University School of Medicine, CHA University, 335 Pangyo-ro, Seongnam 13448, Republic of Korea; Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, South Korea
| | - Eunseok Kang
- Department of Biomedical Informatics, CHA University School of Medicine, CHA University, 335 Pangyo-ro, Seongnam 13448, Republic of Korea; Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, South Korea
| | - Yeojin Jeong
- Department of Biomedical Informatics, CHA University School of Medicine, CHA University, 335 Pangyo-ro, Seongnam 13448, Republic of Korea; Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, South Korea
| | - Jihyeon Park
- Department of Biomedical Informatics, CHA University School of Medicine, CHA University, 335 Pangyo-ro, Seongnam 13448, Republic of Korea; Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, South Korea
| | - Hyun Wook Han
- Department of Biomedical Informatics, CHA University School of Medicine, CHA University, 335 Pangyo-ro, Seongnam 13448, Republic of Korea; Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, South Korea.
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Wang C, Qi Y, Chen Z. Explainable Gated Recurrent Unit to explore the effect of co-exposure to multiple air pollutants and meteorological conditions on mental health outcomes. ENVIRONMENT INTERNATIONAL 2023; 171:107689. [PMID: 36508748 DOI: 10.1016/j.envint.2022.107689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 11/03/2022] [Accepted: 12/08/2022] [Indexed: 06/17/2023]
Abstract
Mental health conditions have the potential to be worsened by air pollution or other climate-sensitive factors. Few studies have empirically examined those associations when we faced to co-exposures, as well as interaction effects. There would be an urgent need to use deep learning to handle complex co-exposures that might interact in multiple ways, and the model performance reinforced by SHapely Additive exPlanations (SHAP) enabled our predictions interpretable and hence actionable. Here, to evaluate the mixed effect of short-term co-exposure, we conducted a time-series analysis using approximately 1.47 million hospital outpatient visits of mental disorders (i.e., depressive disorder-DD, Schizophrenia-SP, Anxiety Disorder-AD, Bipolar Disorder-BD, Attention Deficit and Hyperactivity Disorder-ADHD, Autism Spectrum Disorder-ASD), with matched meteorological observations from 2015 through 2019 in Nanjing, China. The global insights of gated recurrent unit model revealed that most of input features with similar effect size caused the illness risk of SP and ASD increase, and most markedly, 73% of relative humidity, 44.6 µg/m3 of NO2, and 14.1 µg/m3 of SO2 at 5-year average level associated with 2.27, 1.14, and 1.29 visits increase for DD, SP, and AD, respectively. Both synergic and antagonistic effect among informative paired-features were distinguished from local feature dependence. Interestingly, variation tendencies of excessive visits of bipolar disorder when atmospheric pressure, PM2.5, and O3 interacted with one another were inconsistent. Our results provided added qualitative and quantitative support for the conclusion that short-term co-exposure to ambient air pollutants and meteorological conditions posed threats to human mental health.
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Affiliation(s)
- Ce Wang
- School of Energy and Environment, Southeast University, Nanjing 210096, PR China; State Key Laboratory of Environmental Medicine Engineering, Ministry of Education, Southeast University, Nanjing 210096, PR China.
| | - Yi Qi
- School of Architecture and Urban Planning, Nanjing University, No. 22 Hankoulu Road, Nanjing 210093, PR China
| | - Zhenhua Chen
- Department of Information, Affiliated Nanjing Brain Hospital, Nanjing Medical University, No. 264 Guangzhou Road, Nanjing 210029, RP China.
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Zundel CG, Ryan P, Brokamp C, Heeter A, Huang Y, Strawn JR, Marusak HA. Air pollution, depressive and anxiety disorders, and brain effects: A systematic review. Neurotoxicology 2022; 93:272-300. [PMID: 36280190 PMCID: PMC10015654 DOI: 10.1016/j.neuro.2022.10.011] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 10/12/2022] [Accepted: 10/19/2022] [Indexed: 11/05/2022]
Abstract
Accumulating data suggest that air pollution increases the risk of internalizing psychopathology, including anxiety and depressive disorders. Moreover, the link between air pollution and poor mental health may relate to neurostructural and neurofunctional changes. We systematically reviewed the MEDLINE database in September 2021 for original articles reporting effects of air pollution on 1) internalizing symptoms and behaviors (anxiety or depression) and 2) frontolimbic brain regions (i.e., hippocampus, amygdala, prefrontal cortex). One hundred and eleven articles on mental health (76% human, 24% animals) and 92 on brain structure and function (11% human, 86% animals) were identified. For literature search 1, the most common pollutants examined were PM2.5 (64.9%), NO2 (37.8%), and PM10 (33.3%). For literature search 2, the most common pollutants examined were PM2.5 (32.6%), O3 (26.1%) and Diesel Exhaust Particles (DEP) (26.1%). The majority of studies (73%) reported higher internalizing symptoms and behaviors with higher air pollution exposure. Air pollution was consistently associated (95% of articles reported significant findings) with neurostructural and neurofunctional effects (e.g., increased inflammation and oxidative stress, changes to neurotransmitters and neuromodulators and their metabolites) within multiple brain regions (24% of articles), or within the hippocampus (66%), PFC (7%), and amygdala (1%). For both literature searches, the most studied exposure time frames were adulthood (48% and 59% for literature searches 1 and 2, respectively) and the prenatal period (26% and 27% for literature searches 1 and 2, respectively). Forty-three percent and 29% of studies assessed more than one exposure window in literature search 1 and 2, respectively. The extant literature suggests that air pollution is associated with increased depressive and anxiety symptoms and behaviors, and alterations in brain regions implicated in risk of psychopathology. However, there are several gaps in the literature, including: limited studies examining the neural consequences of air pollution in humans. Further, a comprehensive developmental approach is needed to examine windows of susceptibility to exposure and track the emergence of psychopathology following air pollution exposure.
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Affiliation(s)
- Clara G Zundel
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University, Detroit, MI, USA.
| | - Patrick Ryan
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA; Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
| | - Cole Brokamp
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA; Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
| | - Autumm Heeter
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University, Detroit, MI, USA.
| | - Yaoxian Huang
- Department of Civil and Environmental Engineering, Wayne State University, 5050 Anthony Wayne Drive, Detroit, MI, USA.
| | - Jeffrey R Strawn
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA; Anxiety Disorders Research Program, Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA.
| | - Hilary A Marusak
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University, Detroit, MI, USA; Merrill Palmer Skillman Institute for Child and Family Development, Wayne State University, Detroit, MI, USA; Translational Neuroscience Program, Wayne State University, Detroit, MI, USA.
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Krewski D, Saunders-Hastings P, Larkin P, Westphal M, Tyshenko MG, Leiss W, Dusseault M, Jerrett M, Coyle D. Principles of risk decision-making. JOURNAL OF TOXICOLOGY AND ENVIRONMENTAL HEALTH. PART B, CRITICAL REVIEWS 2022; 25:250-278. [PMID: 35980104 DOI: 10.1080/10937404.2022.2107591] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Risk management decisions in public health require consideration of a number of complex, often conflicting factors. The aim of this review was to propose a set of 10 fundamental principles to guide risk decision-making. Although each of these principles is sound in its own right, the guidance provided by different principles might lead the decision-maker in different directions. For example, where the precautionary principle advocates for preemptive risk management action under situations of scientific uncertainty and potentially catastrophic consequences, the principle of risk-based decision-making encourages decision-makers to focus on established and modifiable risks, where a return on the investment in risk management is all but guaranteed in the near term. To evaluate the applicability of the 10 principles in practice, one needs to consider 10 diverse risk issues of broad concern and explore which of these principles are most appropriate in different contexts. The 10 principles presented here afford substantive insight into the process of risk management decision-making, although decision-makers will ultimately need to exercise judgment in reaching appropriate risk decisions, accounting for all of the scientific and extra-scientific factors relevant to the risk decision at hand.
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Affiliation(s)
- Daniel Krewski
- McLaughlin Centre for Population Health Risk Assessment, Faculty of Medicine, University of Ottawa, ON, Canada
| | - Patrick Saunders-Hastings
- McLaughlin Centre for Population Health Risk Assessment, Faculty of Medicine, University of Ottawa, ON, Canada
| | - Patricia Larkin
- McLaughlin Centre for Population Health Risk Assessment, Faculty of Medicine, University of Ottawa, ON, Canada
| | - Margit Westphal
- McLaughlin Centre for Population Health Risk Assessment, Faculty of Medicine, University of Ottawa, ON, Canada
| | | | - William Leiss
- McLaughlin Centre for Population Health Risk Assessment, Faculty of Medicine, University of Ottawa, ON, Canada
| | - Maurice Dusseault
- Department of Earth and Environmental Sciences, University of Waterloo, Waterloo, ON, Canada
| | - Michael Jerrett
- Department of Environmental Health Sciences, Fielding School of Public Health, UCLA, Los Angeles, CA, USA
| | - Doug Coyle
- School of Epidemiology and Public Health, University of Ottawa, ON, Canada
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Tsai SS, Chen CC, Chen PS, Yang CY. Ambient ozone exposure and hospitalization for substance abuse: A time-stratified case-crossover study in Taipei. JOURNAL OF TOXICOLOGY AND ENVIRONMENTAL HEALTH. PART A 2022; 85:553-560. [PMID: 35392774 DOI: 10.1080/15287394.2022.2053021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
A number of studies investigating the possibility that air pollutant exposures increases the risk of adverse effects on mental health including frequency of suicide and depression, is a major growing public health concern. Human data demonstrated that exposure to various ambient air contaminants including ozone (O3) adversely affected nervous system functions. It is also well-established that substance abuse produces central nervous system dysfunctions with resultant increase in suicide rates. However, the role of substance abuse in combination with O3 exposure on mental health remained to be determined. The aim of this investigation was to conduct a time-stratified case-crossover study to examine the possible correlation between short-term ambient O3 exposure and daily hospital admissions for substance abuse, including alcohol dependence syndrome and non-dependent abuse of drugs, in Taipei from 2009 to 2013. In our single pollutant model, a 35% rise in interquartile (IQR) O3 levels on cool days and a 12% elevation on warm days was associated with increase in mental health hospitalizations. In our two-pollutant models, O3 remained significantly associated with elevated number of hospitalizations after adding any one of possible air pollutants, PM10, PM2.5, SO2, NO2, and CO, to our model on cool and warm days. Data suggested that temperature may affect the association between outdoor ambient air O3 exposure and enhanced risk of hospitalization for substance abuse. Further study is needed to better understand these findings.
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Affiliation(s)
- Shang-Shyue Tsai
- Department of Healthcare Administration, I-Shou University, Kaohsiung, Taiwan
| | - Chih-Cheng Chen
- Department of pediatrics, College of Medicine, Kaohsiung Chang-Gung Memorial Hospital and Chang-Gung University, Kaohsiung, Taiwan
| | - Pei-Shih Chen
- Department of Public Health, College of Health Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Chun-Yuh Yang
- Department of Public Health, College of Health Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan
- National Institute of Environmental Health Sciences, National Health Research Institute, Miaoli, Taiwan
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An Evaluation of Risk Ratios on Physical and Mental Health Correlations due to Increases in Ambient Nitrogen Oxide (NOx) Concentrations. ATMOSPHERE 2022. [DOI: 10.3390/atmos13060967] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Nitrogen oxides (NOx) are gaseous pollutants contributing to pollution in their primary form and are also involved in reactions forming ground-level ozone and fine particulate matter. Thus, NOx is of great interest for targeted pollution reduction because of this cascade effect. Primary emissions originate from fossil fuel combustion making NOx a common outdoor and indoor air pollutant. Numerous studies documenting the observed physical health impacts of NOx were reviewed and, where available, were summarized using risk ratios. More recently, the literature has shifted to focus on the mental health implications of NOx exposure, and a review of the current literature found five main categories of mental health-related conditions with respect to NOx exposure: common mental health disorders, sleep, anxiety, depression, and suicide. All the physical and mental health effects with available risk ratios were organized in order of increasing risk. Mental health concerns emerged as those most influenced by NOx exposure, with physical health impacts, such as asthma, only beginning to surface as the fourth highest risk. Mental health conditions occupied seven of the top ten highest risk health ailments. The results summarized in this narrative review show that there are clear positive correlations between NOx and negative physical and mental health manifestations, thus strengthening the argument in support of the reduction in ambient NOx levels.
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Abstract
PURPOSE OF REVIEW There is increasing interest in the links between exposure to air pollution and a range of health outcomes. The association with mental health however is much less established. This article reviews developments in the field over the past 12 months, highlighting the evidence for causation, associations between multiple air pollutants and mental health outcomes, and assesses the challenges of researching this topic. RECENT FINDINGS Increasingly rigorous methods are being applied to the investigation of a broader range of mental health outcomes. These methods include basic science, neuroimaging, and observational studies representing diverse geographical locations. Cohort studies with linked high-resolution air pollutant exposure data are common, facilitating advanced analytic methods. To date, meta-analyses have demonstrated small and significant positive associations between long-term exposure to fine particulate matter and depressive symptoms and cognitive decline. Methodological complexities in measuring exposure and outcome pose ongoing difficulties for the field. SUMMARY Literature on this topic has recently seen an appreciable expansion. Work that better estimates daily exposure, controls for complex confounders, and is driven by hypotheses founded in candidate causal mechanisms would help clarify associations, and inform targeted interventions and policymakers.
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Lee KS, Kim G, Ham BJ. ORIGINAL ARTICLE: Associations of antidepressant medication with its various predictors including particulate matter: Machine learning analysis using national health insurance data. J Psychiatr Res 2022; 147:67-78. [PMID: 35026595 DOI: 10.1016/j.jpsychires.2022.01.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 12/23/2021] [Accepted: 01/03/2022] [Indexed: 10/19/2022]
Abstract
This study uses machine learning and population-based data to analyze major determinants of antidepressant medication including the concentration of particulate matter under 2.5 μm (PM2.5). Retrospective cohort data came from Korea National Health Insurance Service claims data for 43,251 participants, who were aged 15-79 years, lived in the same districts of Seoul and had no history of antidepressant medication during 2002-2012. The dependent variable was antidepressant-free months during 2013-2015 and the 30 independent variables for 2012 were included (demographic/socioeconomic information, health information, district-level information including PM2.5). Random forest variable importance, the contribution of a variable for the performance of the model, was used for identifying major predictors of antidepressant-free months. Based on random forest variable importance, the top 15 determinants of antidepressant medication during 2013-2015 included cardiovascular disease (0.0054), age (0.0047), household income (0.0037), gender (0.0027), the district-level proportion of recipients of national basic living security program benefits (0.0019), district-level social satisfaction (0.0013), diabetes mellitus (0.0012), January 2012 PM2.5 (0.0011), district-level street ratio (0.0010), drinker (0.0009), chronic obstructive pulmonary disease (0.0008), district-level economic satisfaction (0.0006), exercise (0.0005), March 2012 PM2.5 (0.0005) and November 2012 PM2.5 (0.0004). Besides these predictors, smoker and district-level deprivation index are found to be influential most widely, given that they ranked within the top 10 most often in sub-group analysis. In conclusion, antidepressant medication has strong associations with neighborhood conditions including socioeconomic satisfaction and the seasonality of particulate matter. Strong interventions for these factors are really needed for the effective management of major depressive disorder.
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Affiliation(s)
- Kwang-Sig Lee
- AI Center, Korea University College of Medicine, Seoul, South Korea
| | - Geunyeong Kim
- Korea University Graduate School of Policy Studies, Seoul, South Korea
| | - Byung-Joo Ham
- Department of Mental Health, Korea University College of Medicine, Seoul, South Korea.
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Ma Y, Wang W, Li Z, Si Y, Wang J, Chen L, Wei C, Lin H, Deng F, Guo X, Ni X, Wu S. Short-term exposure to ambient air pollution and risk of daily hospital admissions for anxiety in China: A multicity study. JOURNAL OF HAZARDOUS MATERIALS 2022; 424:127535. [PMID: 34879525 DOI: 10.1016/j.jhazmat.2021.127535] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2021] [Revised: 10/04/2021] [Accepted: 10/14/2021] [Indexed: 06/13/2023]
Abstract
The potential impact of short-term exposure to ambient air pollution on risk of anxiety remains uncertain. We performed a detailed evaluation based on data from national insurance databases in China. Daily hospital admissions for anxiety disorders were identified in 2013-2017 from the national insurance databases covering up to 261 million urban residents in 56 cities in China. A two-stage time-series study was conducted to evaluate the associations between short-term exposure to major ambient air pollutants, including fine particles, inhalable particles, nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone, and carbon monoxide, and risk of daily hospital admissions for anxiety. Significant associations between short-term exposures to ambient NO2 and SO2 and risk of daily hospital admissions for anxiety were found in the overall analysis. Per 10 μg/m3 increases in NO2 at lag0 and SO2 at lag6 were associated with significant increases of 1.37% (95% CI: 0.14%, 2.62%) and 1.53% (95% CI: 0.59%, 2.48%) in anxiety admissions, respectively. Stronger associations were found in the southern region and patients <65 years for SO2. Short-term exposure to ambient air pollution is associated with increased risk of anxiety admissions, which may provide important implications for promotion of mental health in the public.
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Affiliation(s)
- Yating Ma
- Institute of Social Psychology, School of Humanities and Social Sciences, Xi'an Jiaotong University, Xi'an, Shaanxi, China
| | - Wanzhou Wang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China
| | - Zichuan Li
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China
| | - Yaqin Si
- Beijing HealthCom Data Technology Co. Ltd, Beijing, China
| | - Jinxi Wang
- Shanghai Songsheng Business Consulting Co. Ltd, Shanghai, China
| | - Libo Chen
- Beijing HealthCom Data Technology Co. Ltd, Beijing, China
| | - Chen Wei
- Beijing HealthCom Data Technology Co. Ltd, Beijing, China
| | - Hualiang Lin
- Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Furong Deng
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China
| | - Xinbiao Guo
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China
| | - Xiaoli Ni
- Institute of Social Psychology, School of Humanities and Social Sciences, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
| | - Shaowei Wu
- Department of Occupational and Environmental Health, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.
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Borroni E, Pesatori AC, Bollati V, Buoli M, Carugno M. Air pollution exposure and depression: A comprehensive updated systematic review and meta-analysis. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 292:118245. [PMID: 34600062 DOI: 10.1016/j.envpol.2021.118245] [Citation(s) in RCA: 76] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 09/21/2021] [Accepted: 09/25/2021] [Indexed: 06/13/2023]
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.
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Affiliation(s)
- Elisa Borroni
- Department of Clinical Sciences and Community Health, University of Milan, via san Barnaba 8, 20122, Milan, Italy
| | - Angela Cecilia Pesatori
- Department of Clinical Sciences and Community Health, University of Milan, via san Barnaba 8, 20122, Milan, Italy; Epidemiology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, via san Barnaba 8, 20122, Milan, Italy.
| | - Valentina Bollati
- Department of Clinical Sciences and Community Health, University of Milan, via san Barnaba 8, 20122, Milan, Italy
| | - Massimiliano Buoli
- Department of Pathophysiology and Transplantation, University of Milan, Via Francesco Sforza 35, 20122, Milan, Italy; Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via Francesco Sforza 35, 20122, Milan, Italy
| | - Michele Carugno
- Department of Clinical Sciences and Community Health, University of Milan, via san Barnaba 8, 20122, Milan, Italy; Epidemiology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, via san Barnaba 8, 20122, Milan, Italy
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