Introduction
It is unequivocal that increasing human activities have led to warming the atmosphere, ocean, and land. Widespread and rapid changes in the atmosphere, ocean, cryosphere, and biosphere have occurred (Legg, Reference Legg2021). The scale of the recent changes across the climate system is unprecedented over many centuries to many thousands of years (Legg, Reference Legg2021). These changes are suggested to have serious consequences for human health, including renal function loss, dermatological malignancies, tropical infections, pregnancy complications, allergies, and cardiovascular and pulmonary morbidity and mortality (Atwoli et al., Reference Atwoli, Baqui, Benfield, Bosurgi, Godlee, Hancocks and Norman2021; Haines & Ebi, Reference Haines and Ebi2019; Rocque et al., Reference Rocque, Beaudoin, Ndjaboue, Cameron, Poirier-Bergeron, Poulin-Rheault and Witteman2021).
Over the last few years it has been suggested that mental health may also be affected by these rapidly occurring climate changes. A recent seminal review describes how mental health may be affected by climate change through four different pathways (Clayton, Reference Clayton2021). First, discrete events, such as natural disasters can have a direct impact on mental health. There is suggestive evidence that floods, heatwaves, tornados and hurricanes, wildfires, and earthquakes may be associated with increased rates of post-traumatic stress and depression, substance use disorders, suicidal thoughts, and important risk factors, such as domestic abuse (Cénat, McIntee, & Blais-Rochette, Reference Cénat, McIntee and Blais-Rochette2020; Chan & Rhodes, Reference Chan and Rhodes2014; Chen & Liu, Reference Chen and Liu2015; Dai et al., Reference Dai, Chen, Lai, Li, Wang and Liu2016). Second, mental health can be affected by gradual changes, such as rising sea levels and higher temperatures. Although the causal mechanisms are not clear, higher temperatures, for example, have been associated with more aggression and higher suicide rates (Clayton, Reference Clayton2021). Pollution and the ‘greenhouse’ effect associated with the burning of fossil fuels may also have consequences for mental health. Third, climate change may affect existing physical and social systems, and these changes may have an indirect effect on mental health. For example, the occupational structure and agricultural conditions may change in communities, resulting in economic uncertainties for some groups. Migration may also be the result of areas becoming less inhabitable or disappearing altogether (Clayton, Reference Clayton2021). The fourth pathway refers to the perception of climate change, with anecdotal reports of ‘climate anxiety’, for example in parents who are worried about their children's future and young adults who are reluctant to procreate because of fear about the future (Clayton, Reference Clayton2021). Solastalgia, the distress caused by the transformation and degradation of one's home environment, is a comparable phenomenon that is somewhat better examined, although it is still mostly unclear what it exactly is and how it affects mental health (Galway, Beery, Jones-Casey, & Tasala, Reference Galway, Beery, Jones-Casey and Tasala2019). If climate change does indeed have impact on mental health, it is important to include this in the future projections of global mental health and, if possible, measures should be taken to prevent or treat these increasing numbers of patients with mental disorders.
Over the past decade, the number of meta-analyses of studies examining the impact of climate change on mental health has increased exponentially. That is a positive development, as replication increases knowledge about the impact of climate change. However, the published meta-analyses all have a specific focus, for example on one mental health problem, such as posttraumatic stress disorder (PTSD) (e.g. Chan & Rhodes, Reference Chan and Rhodes2014; Dai et al., Reference Dai, Chen, Lai, Li, Wang and Liu2016; Rezayat et al., Reference Rezayat, Sahebdel, Jafari, Kabirian, Rahnejat, Farahani and Nour2020), suicide (e.g. Jahangiri, Yousefi, Mozafari, & Sahebi, Reference Jahangiri, Yousefi, Mozafari and Sahebi2020), or autism spectrum disorders (ASDs) in children (Chun, Leung, Wen, McDonald, & Shin, Reference Chun, Leung, Wen, McDonald and Shin2020; Dutheil et al., Reference Dutheil, Comptour, Morlon, Mermillod, Pereira, Baker and Bourdel2021). Other meta-analyses focus on specific events (e.g. Chen & Liu, Reference Chen and Liu2015; Dai et al., Reference Dai, Chen, Lai, Li, Wang and Liu2016), on one specific country (e.g. Hosseinnejad et al., Reference Hosseinnejad, Yazdi-Feyzabadi, Hajebi, Bahramnejad, Baneshi, Sarabi and Zolala2022; Sepahvand, Hashtjini, Salesi, Sahraei, & Jahromi, Reference Sepahvand, Hashtjini, Salesi, Sahraei and Jahromi2019), or one polluting substance (Forns et al., Reference Forns, Verner, Iszatt, Nowack, Bach, Vrijheid and Høyer2020). Because of the focus on specific subjects, an overview of the whole field is lacking. Furthermore, an increasing number of meta-analyses is not always positive, because it is not uncommon for meta-analyses on the same research question to reach different conclusions, even when published within the same year (Solmi, Correll, Carvalho, & Ioannidis, Reference Solmi, Correll, Carvalho and Ioannidis2018). Such discrepancies unavoidably lead to confusion and debate among policy makers and researchers (Solmi et al., Reference Solmi, Correll, Carvalho and Ioannidis2018). Umbrella reviews – a systematic review of all systematic reviews and/or meta-analyses on a given topic – allow a higher-level synthesis of the evidence and a better recognition of the uncertainties, biases, and knowledge gaps, compared to single meta-analyses (Ioannidis, Reference Ioannidis2009, Reference Ioannidis2017). An umbrella review on environmental and climate-related determinants of mental health is important, because when it is found that mental health is indeed affected, this would be an additional reason to stop the warming of the atmosphere, ocean, and land as soon as possible.
We conducted an umbrella review of meta-analyses examining environmental and climate-related determinants of mental health. In this review, we focused on three major environmental and climate-related determinants that (1) potentially have a major impact on mental health; (2) represent different, non-overlapping domains, and (3) cover as much as possible of the possible environmental and climate-related determinants.
We defined climate events as ‘discrete episodes of extreme weather or unusual climate conditions, often associated with deleterious impacts on society or natural systems, defined using some metric to characterize either the meteorological characteristics of the event or the consequent impacts’ (Stott et al., Reference Stott, Christidis, Otto, Sun, Vanderlinden, van Oldenborgh and Yiou2016). We also used the taxonomy of climate events developed by Stephenson, Diaz, and Murnane (Reference Stephenson, Diaz and Murnane2008), including tropical cyclones, hurricanes, extratropical cyclones, convective phenomena (including tornadoes and severe thunderstorms), mesoscale phenomena (such as polar lows, resulting in e.g. extreme wind speeds and precipitation), floods, drought, heat waves, cold waves, and fog. In this study we also included natural events that may not be directly influenced by the climate such as landslides. Pollution was defined as the addition of any substance (solid, liquid, or gas) or any form of energy (such as heat, sound, or radioactivity) to the environment at a rate faster than it can be dispersed, diluted, decomposed, recycled, or stored in some harmless form (Nathanson, Reference Nathanson2022). The major kinds of pollution, usually classified by environment, are air pollution, water pollution, and land pollution. The impact of green spaces was operationalized as the impact of exposure to the natural environment on mental health problems (Roberts, van Lissa, Hagedoorn, Kellar, & Helbich, Reference Roberts, van Lissa, Hagedoorn, Kellar and Helbich2019).
The domains we choose were also relevant for a separate report by the United Nations Environment Programme (UNEP) (in preparation), that included a modeling study examining the impact of these domains on the costs of global mental health. The three specific subjects that are examined in this umbrella review are (1) the impact of climate events on mental health; (2) the impact of pollution on mental health; and (3) the association between green spaces and mental health, as an indicator of the impact of urbanization on mental health.
Methods
Search strategy and selection criteria
We used an umbrella review methodology to systematically collect and review all available meta-analyses examining the potential association between climate change, pollution, green spaces, and mental health. We followed general guidelines for conducting and reporting umbrella reviews (Ioannidis, Reference Ioannidis2009, Reference Ioannidis2017; Papatheodorou, Reference Papatheodorou2019; Solmi et al., Reference Solmi, Correll, Carvalho and Ioannidis2018). The protocol for this meta-analysis was registered at the Open Science Framework (Cuijpers, Reference Cuijpers2021).
We conducted systematic searches on 17 June 2021 in three bibliographic databases: PubMed, PsycINFO, and Embase. We first developed a general search string for climate change, pollution, and green spaces, in which we combined text and key words for these subjects with text and key words for mental health and mental disorders. We limited the results to systematic reviews and meta-analyses. Because the impact of climate events (such as tornados, landslides, heatwaves, etc.) may not be captured by key words related to climate change, we conducted separate searches for these events. In these searches we combined text and key words for climate events with text and key words for mental health and mental disorders and again limited the results to meta-analyses and systematic reviews. The full search strings are available in online Supplement S1. All records were read by two independent researchers and we retrieved the full-text of all studies that were selected for retrieval by one or both researchers.
In this umbrella review we included (a) meta-analyses that reported (b) the association between climate events, green spaces, or pollution and mental health or mental disorders, and (c) in which at least one analysis included more than five comparisons (in order to have a reasonable impression of the association). We included any kind of climate event and pollution as defined in the Introduction, including specific substances, and pollution of air, soil, and water. Any mental health problem or mental disorder was included. Because of limited resources, we excluded studies on the association between climate change and intelligence, as well as on dementia and cognitive decline. Only studies in English were included. No other exclusion criteria were applied.
All full text papers were read by two independent researchers and the decision to include or exclude was based on consensus. Disagreements were solved through discussion. Because no disagreements remained after the discussions, it was not needed to consult a third, senior author.
Quality assessment
The quality of the included meta-analyses was assessed with the AMSTAR 2, a critical appraisal tool for systematic reviews (Shea et al., Reference Shea, Reeves, Wells, Thuku, Hamel, Moran and Kristjansson2017). AMSTAR-2 critically assesses 16 core characteristics of systematic reviews (online Supplement S2). All assessments of these criteria were conducted by two independent researchers and disagreements were solved by discussion or, when needed, discussed with a third reviewer.
Data extraction
We extracted the following data from the included meta-analyses: the examined climate-related factor (climate event, pollution, specific substance, green spaces, etc.), the design of the included studies in the meta-analysis, the number of included studies, the aggregated number of participants in the primary studies (when reported), the population, and the instrument used to measure the quality of primary studies. We also extracted the mental health outcome, a summary of the pooled outcomes, the significance of the outcomes, the level of heterogeneity [I 2 and its 95% confidence interval (CI)], and (when reported) the outcomes of the analyses examining publication bias. When I 2 or its 95% CI were not reported, we calculated them with the value of χ2 and degrees of freedom (if available), using the Heterogi module in STATA SE (version 16.1 for Mac). The general characteristics of the meta-analyses were extracted by one reviewer. The outcomes were extracted by one reviewer whose extraction was validated by a second reviewer, who independently extracted 25% of the data. An agreement index of 96.3% between the two reviewers was reached.
Integration of findings
We offer a narrative overview of the identified associations between indicators for climate change, pollution, and green spaces and indicators for mental health and mental disorders.
Results
Selection and inclusion of studies
We examined the abstracts and titles of 575 records (519 after removal of duplicates). The full-texts of 221 studies were retrieved and assessed for eligibility, from which 197 were excluded. A total of 24 meta-analyses met the inclusion criteria, two for green spaces and natural environments, 11 for pollution, and 13 for climate events (with two meta-analyses included in multiple categories). The PRISMA flowchart is presented in Fig. 1.
Fig. 1. PRISMA flowchart for the inclusion of studies. *One study (Heo et al., Reference Heo, Lee and Bell2021) was included in both pollution and climate events, and another study (Generaal et al., Reference Generaal, Hoogendijk, Stam, Henke, Rutters, Oosterman and Timmermans2019) was included in both pollution and green spaces.
Characteristics of included meta-analyses
The main characteristics of the 24 included meta-analyses are summarized in Table 1. All identified reviews were relatively recent, published until 2021 and with searches covering from databases' inception to 2021. The total number of primary studies included in the meta-analyses ranged from 5 to 64. The total sample sizes varied among meta-analyses, with the largest analysis including 758 997 participants. The most frequently used design in the included primary studies was cross-sectional, but other common designs included case-control studies, cohorts, case-crossover designs, and time-series analyses. Two of the included studies were not systematic reviews, but performed meta-analyses on outcome data from large European (Forns et al., Reference Forns, Verner, Iszatt, Nowack, Bach, Vrijheid and Høyer2020) and Dutch cohorts (Generaal et al., Reference Generaal, Hoogendijk, Stam, Henke, Rutters, Oosterman and Timmermans2019). More details of the included meta-analyses are reported in online Supplement S3.
Table 1. Selected characteristics of included meta-analyses
ADHD, attention deficit/hyperactivity disorder; ASD, autism spectrum disorder; CO, carbon monoxide; MA, meta-analysis; NO2, nitrogen dioxide; NOx, nitrogen oxide; O3, ozone; PAHs, polycyclic aromatic hydrocarbons; PFAS, perfluoroalkyl substances; PFOA, perfluorooctanoic acid; PFOS, perfluorooctane sulfonate; PM, particulate matter; PTSD, posttraumatic stress disorder; SO2, sulfur dioxide; SR, systematic review; MH, Mental health.
a This study is included in the categories of Climate events and Pollution.
b This study is not a systematic review, but because they did combine different datasets we decided to include it.
c This study is included in the categories of Pollution and Green spaces.
Quality of included meta-analyses
The AMSTAR-2 ratings for each of the 24 included meta-analyses are presented in Table 2, and the aggregated ratings across all reviews are reported in Fig. 2. The specification of PICO was judged as adequate for all studies. The majority of the meta-analyses did not register a protocol (n = 16; 67%), did not justify the selection of study designs (n = 17; 71%), did not investigate sources of funding (n = 18; 75%), and did not provide a list of excluded studies with reasons (n = 22; 92%). Comprehensiveness of the literature search was rated as ‘partial yes’ in the majority of reviews (n = 15; 63%), while only two reviews obtained a complete positive rating. Two reviewers independently selected studies and extracted data in 15 (63%) and 13 (54%) meta-analyses, respectively. Most of the reviews described in great (n = 14; 58%) or sufficient (n = 10; 42%) detail the included studies, and investigated sources for heterogeneity (n = 22; 92%) and publication bias (n = 17; 71%). Above half of them utilized appropriate statistical methods for analyses (n = 15; 63%), particularly those reporting on pollution. Risk of bias was adequately assessed in 19 meta-analyses (79%), but only 7 (29%) of these assessed all relevant criteria. The impact of risk of bias on the effect estimates (or inclusion of only studies at low risk) was examined in 10 (42%) meta-analyses, and 15 (62%) accounted for the risk of bias when interpreting or discussing the results. The vast majority of meta-analysts declared their conflicts of interest (n = 21; 88%).
Fig. 2. Aggregated AMSTAR-2 ratings for included meta-analyses.
Table 2. AMSTAR-2 ratings and quality assessment instruments used in the meta-analyses
a The total is calculated with ‘Y’ counting as 1 point, and ‘PY’ counting as 0.5 points.
Quality assessment instruments: AHRQ, Agency for Healthcare Research and Quality; CASP, Critical Appraisal Skills Programme 2004/2006 assessment tool; EPHPP, Effective Public Health Practice Project; GRADE, Grading of Recommendations Assessment; Development and Evaluation; JBI, Joanna Briggs Institute checklist; NOS, Newcastle–Ottawa Quality Scale; OHAT, OHAT Risk of Bias Rating Tool for Human and Animal Studies; QUADAS-2, Quality Assessment of Diagnostic Accuracy Studies Tool (revised); SIGN, Scottish International Guideline Network checklist; STROBE, Strengthening the Reporting of Observational Studies in Epidemiology Checklist.
AMSTAR-2 items: (1) adequate definition of PICO, (2) methods established before the review, (3) an explanation for the selection of study design to be included, (4) comprehensiveness of the search strategy, (5) study selection by at least two reviewers, (6) data extraction by at least two reviewers, (7) list of excluded studies with reasons, (8) detailed description of included studies, (9) assessment of risk of bias in included studies, (10) reported sources of funding for the included studies, (11) appropriate methods for pooling results, (12) assessment of the impact of risk of bias on the outcomes, (13) discussion of the impact of risk of bias on results, (14) sources of heterogeneity are explored, (15) assessment of publication bias, (16) reporting potential conflict of interest for the review.
The overall confidence in the results was high for none of the studies (zero or one non-critical weakness), for three the confidence was moderate (more than one weakness, but no critical flaws), and for the other studies the confidence was low to critically low. The three studies with moderate confidence were on climate events (Liu et al., Reference Liu, Varghese, Hansen, Xiang, Zhang, Dear and Capon2021) and on pollution (Hegewald et al., Reference Hegewald, Schubert, Freiberg, Romero Starke, Augustin, Riedel-Heller and Seidler2020; Lam et al., Reference Lam, Sutton, Kalkbrenner, Windham, Halladay, Koustas and Newschaffer2016).
Climate events and mental health
The outcomes reported in the 13 included meta-analyses examining the association between climate events and mental health are summarized in Table 3. We will present the results according to the methodology used, with meta-analyses of pre-post designs first, followed by meta-analyses of estimates of point prevalences of mental disorders (separately for cut-off scores on self-report measures and diagnostic interviews), then meta-analyses of studies with time-series and case-cross-over designs, and finally meta-analyses of correlations between the level of exposure to disasters and mental health outcomes.
Table 3. Outcomes of meta-analyses: climate events
ADHD, attention deficit/hyperactivity disorder; ASD, autism spectrum disorder; k, comparisons included in the analysis; N, number of participants; OR, odds ratio; prop, proportion; PTSD, posttraumatic stress disorder; r, correlation; RR, risk ratio; SMD, standardized mean difference.
a Publication bias: NS indicates not significant; (E) indicates Egger's test; (B) indicates Begg and Mazumbar's test; Susp. (F) indicates suspected publication bias based on funnel plot inspection; Not Susp. (F) indicates that publication bias is not suspected based on funnel plot inspection; NA indicates not available. Underlined values are significant.
One meta-analysis examined the impact of various natural disasters (earthquakes, floods, hurricanes, tsunamis, wildfires, etc.) on psychological distress and mental disorders, and included studies that compared exposed to non-exposed people, as well as studies with measurements before and after the event (Beaglehole et al., Reference Beaglehole, Mulder, Frampton, Boden, Newton-Howes and Bell2018). The studies with both pre-test and post-test assessments are especially informative about the actual number of cases triggered by the events. Six included studies that used a pre-post design found a non-significant standardized mean difference (SMD) of 0.32 (95% CI −0.06 to 0.70) on psychological distress. Only two included studies with a pre-post design were available for measuring the impact on mental disorders, which were too few for providing reliable estimates of the impact.
Eight meta-analyses aimed at examining the pooled prevalence of mental disorders after a climate event (Cénat et al., Reference Cénat, McIntee and Blais-Rochette2020; Chen & Liu, Reference Chen and Liu2015; Dai et al., Reference Dai, Chen, Lai, Li, Wang and Liu2016; Hosseinnejad et al., Reference Hosseinnejad, Yazdi-Feyzabadi, Hajebi, Bahramnejad, Baneshi, Sarabi and Zolala2022; Jahangiri et al., Reference Jahangiri, Yousefi, Mozafari and Sahebi2020; Liang, Zeng, Liu, Xu, & Liu, Reference Liang, Zeng, Liu, Xu and Liu2021; Rezayat et al., Reference Rezayat, Sahebdel, Jafari, Kabirian, Rahnejat, Farahani and Nour2020; Sepahvand et al., Reference Sepahvand, Hashtjini, Salesi, Sahraei and Jahromi2019). However, they pooled prevalence rates based on different cut-off values from different self-report measures, which is a crucial methodological error, because these estimates indicate different variables and should not be combined in a meta-analysis (Levis et al., Reference Levis, Yan, He, Sun, Benedetti and Thombs2019).
Two meta-analyses reported the prevalence of PTSD according to a diagnostic interview. One found a prevalence of diagnosed PTSD after floods of 16% (95% CI 0.11–0.21) (Chen & Liu, Reference Chen and Liu2015), the other reported a prevalence of PTSD in children and adolescents after earthquakes and floods of 20.8% between 0 and 6 months after the event, 14.6% at 6–12 months, and 16.3% at 12–18 months (Rezayat et al., Reference Rezayat, Sahebdel, Jafari, Kabirian, Rahnejat, Farahani and Nour2020).
Two meta-analyses of mostly time-series designs and case-crossover studies examined the association between heat exposure and mental health problems. One found a significant risk ratio (RR) of 1.09 (95% CI 1.06–1.13) for the association between daily suicide rates and an increase in temperature of 7.1°C (Heo, Lee, & Bell, Reference Heo, Lee and Bell2021). The other (Liu et al., Reference Liu, Varghese, Hansen, Xiang, Zhang, Dear and Capon2021) found an overall RR of 1.02 (95% CI 1.01–1.03) for mental health-related mortality for each degree Celsius increase in temperature, and 1.01 (95% CI 1.007–1.015) for mental health-related morbidity. It should be noted that this meta-analysis scored relatively high on AMSTAR-2 (moderate confidence).
Two other studies examined the correlation between the level of exposure to disasters and mental health outcomes. One found a significant correlation between the severity of exposure and PTSD after hurricane Katrina (r = 0.27; 95% CI 0.17–0.36) (Chan & Rhodes, Reference Chan and Rhodes2014). The other found significant correlations for internalizing (r = 0.18; 95% CI 0.14–0.22), and for externalizing problems (r = 0.08; 95% CI 0.03–0.14) (Rubens, Felix, & Hambrick, Reference Rubens, Felix and Hambrick2018).
Pollution and mental health
The outcomes reported in the 11 included meta-analyses examining the association between pollution and mental health are summarized in Table 4. We will present the results according to the different polluting substances, starting with the most examined substance.
Table 4. Outcomes of meta-analyses: pollution and green spaces
ADHD, attention deficit/hyperactivity disorder; ASD, autism spectrum disorder; CO, carbon monoxide; k, comparisons included in the analysis; N, number of participants; NO2, nitrogen dioxide; NOx, nitrogen oxide; OR, odds ratio; O3, ozone; PAHs, polycyclic aromatic hydrocarbons; PFOA, perfluorooctanoic acid; PFOS, perfluorooctane sulfonate; PM, particulate matter; PTSD, posttraumatic stress disorder; r, correlation; RR, risk ratio; SMD, standardized mean difference; SO2, sulfur dioxide.
a Publication bias: NS indicates not significant; (E) indicates Egger's test; (B) indicates Begg and Mazumbar's test; Susp. (F) indicates suspected publication bias based on funnel plot inspection; Not Susp. (F) indicates that publication bias is not suspected based on funnel plot inspection.
Particulate matter (PM) is a complex mixture that is usually classified into PM2.5 (<2.5 μm in diameter) and PM10 (<10 μm) (Chun et al., Reference Chun, Leung, Wen, McDonald and Shin2020). One analysis of eight Dutch cohorts found a significant pooled prevalence of depression [odds ratio (OR) = 1.07] per 0.2 × 10−5 increase in PM2.5 absorbance (Generaal et al., Reference Generaal, Hoogendijk, Stam, Henke, Rutters, Oosterman and Timmermans2019), and two other meta-analyses also reported small but significant associations at the shorter (<6 months) and longer terms (>6 months) (ORs = 1.10 and 1.06) (Braithwaite, Zhang, Kirkbride, Osborn, & Hayes, Reference Braithwaite, Zhang, Kirkbride, Osborn and Hayes2019; Zeng, Lin, Liu, Liu, & Li, Reference Zeng, Lin, Liu, Liu and Li2019). One meta-analysis reported a significant association between depression and PM10 at the very short term (<2 weeks) (OR = 1.03) (Zeng et al., Reference Zeng, Lin, Liu, Liu and Li2019).
Other pollutants were found to be significantly associated with depression: nitrogen dioxide (NO2; OR = 1.04), carbon monoxide (CO; OR = 1.01); and sulfur dioxide (SO2; OR = 1.03). Moreover, a significant association was also found between noise from aircrafts and depression (OR = 1.14).
Several meta-analyses found significant associations between pollutants and ASD when the mothers were exposed during pregnancy: PM2.5 (ORs ranging from 1.06 to 2.32), PM10 (OR = 1.07), ozone (O3; OR = 1.03 and RR = 1.05), NO2 (OR = 1.02), and solvents (OR = 1.03). One study found a lower risk for ASD and pesticides (OR = 0.83). Other meta-analyses found a significant association between PM10 and suicide (RR = 1.02) and between NO2 and suicide (RR = 1.03).
No other significant associations between pollution and mental disorders were found in the included meta-analyses.
Green spaces and mental health
The results of the two meta-analyses examining the association between green spaces and mental health are reported in Table 4. One pooled analysis of eight Dutch cohort studies found a significant negative association between 30% increase of green space in the neighborhood and depression (OR = 0.94), and a significant association between grade of urbanization (mean number of addresses per km2 within a radius of 1 km) and depression (OR = 1.05) (Generaal et al., Reference Generaal, Hoogendijk, Stam, Henke, Rutters, Oosterman and Timmermans2019). The other meta-analysis included a wide range of designs (randomized, non-randomized, parallel groups, etc.), and found a significant effect size (SMD = 0.30) for reduction of depressive mood after short-term exposure to natural environments (Roberts et al., Reference Roberts, van Lissa, Hagedoorn, Kellar and Helbich2019).
Discussion
We conducted an umbrella review of meta-analyses investigating the association between climate events, pollution, and green spaces on the one hand, and any mental health symptoms or disorders on the other. We included 24 meta-analyses, all relatively recent, which analyzed mainly cross-sectional and case-control studies. The 13 meta-analyses examining the impact of climate events on mental health suggested that there may be an association between such events and mental health, although the exact contribution of these events to the prevalence cannot be established based on these studies. Only two meta-analyses used a diagnostic interview to establish the presence of mental disorders, seven pooled different measures for mental health problems incorrectly, and only six primary studies used a pre-post design, which can be used as a good indication for the impact of climate events on mental health problems. Although it seems obvious that traumatic events like climate events result in increased levels of mental health problems, these methodological problems make it impossible to assess the exact size of the impact.
The 10 meta-analyses focusing on the impact of pollution on mental health, found that some substances are associated with mental health problems, especially depression and ASD in children of mothers exposed to substances. However, all associations were very small and in many studies no corrections were applied for other characteristics of the populations, making these associations highly uncertain. PM2.5 was examined in most studies, but other substances that were examined included PM10, NO2, O3, SO2, CO, solvents, styrene exposure, and noise. All associations were small and because unmeasured confounders may further reduce the strength and level of significance of the association, these findings should be considered with caution.
We only found two meta-analyses examining green spaces and natural environments (Generaal et al., Reference Generaal, Hoogendijk, Stam, Henke, Rutters, Oosterman and Timmermans2019; Roberts et al., Reference Roberts, van Lissa, Hagedoorn, Kellar and Helbich2019). Both meta-analyses found a small but significant association between green spaces and reduction of mental health symptoms, but the observational nature of many of the primary studies as well as the potential for risk of bias limit confidence in these findings.
Research on the impact of climate events has demonstrated considerable methodological limitations. It is difficult to indicate whether a climate event is caused by climate change or that it is a natural fluctuation. It is also difficult to examine the impact of a climate event on mental health, because this requires at least a measurement before the event and one after, and then the causality is still unclear because other changes may have taken place at the same time that have (partly) caused the changes in mental health. Many studies simply examine correlations between for example pollution and a mental health outcome. Although some studies do adjust for confounders, the number of confounders is usually limited and there is no way to exclude the possibility that an association is in fact caused by a third, unknown variable, especially when the effect size of the identified association is small. Most studies also measured mental health with self-report measures, while such scales cannot reliably indicate the presence of a mental disorder. Studies based on mental disorders assessed with the gold standard, diagnostic interviews, are hardly done, also because the costs and logistic challenges of such studies are considerable. Based on our umbrella review it is not possible to indicate how much support is available for the four different pathways of how climate can have an impact on mental health.
The results of this study need to be counterbalanced weighing new insights it offers and limitations that remain challenging for generalizability of the findings. The strengths include a rigorous approach to umbrella reviews and the inclusion of a considerable number of studies. However, this study also has some important limitations that have to be taken into consideration. One important limitation is that we only included meta-analyses with at least five studies. That threshold is arbitrary because the strength of evidence does not only depend on the number of studies, but also on the size of the study, the design, and the quality. However, we had to limit the scope of this umbrella review to make the rapid scoping of the evidence manageable and we believe that a threshold of five studies does give good indications for the state of research in a particular area. A second important limitation is that the quality of the included meta-analyses was not optimal. The overall confidence in the results was high for none of the studies, and moderate for only three of the 24 included meta-analyses. The confidence in the other meta-analyses was low to critically low. This means that the results of all meta-analyses should be considered with caution because of limited quality. Another limitation is that the impact of climate events, pollution, and green spaces change over time, and while most included meta-analyses were conducted over the past few years, it cannot be examined whether the impact of these changes has increased over time.
This umbrella review shows that very little good evidence is available on the association between mental health on the one hand and climate events, pollution, and green spaces on the other hand. Because of the devastating impact climate events can have on human lives, there should be no doubt that they result in increased mental health problems. However, the current evidence gives no clear indication of how large that increase is. More research with better designs and assessments are clearly needed to get a better overview of the implication of these developments for mental health. This information is needed to develop strategies to reduce the impact of such events on mental health.
In conclusion, in this umbrella review we found some evidence for an association between climate events and mental health, especially post-traumatic stress, but also depression and anxiety. We also found some evidence for an association between pollution and aspects of mental health, especially depression, suicide and autism spectrum disorders. Finally, we found some indications for an association between green spaces and depression. However, more high-quality research is needed to verify all these associations. Given how rapidly the natural world is changing around us and the policy impetus to reflect and revisit human footprint on natural environment, improving design, measurement, and carrying out evidence informed environmental mental health studies would be important.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/S0033291722003890
Financial support
This umbrella review was financially supported by the United Nations Environment Programme, Washington, DC.
Conflict of interest
None of the authors report any conflicts of interest.
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