Particulate matter pollution associated with schizophrenia hospital re-admissions: a time-series study in a coastal Chinese city

Environmental pollution and extreme weather conditions: insights into the effect on mental health

Environmental pollution exposures, including air, soil, water, light, and noise pollution, are critical issues that may implicate adverse mental health outcomes. Extreme weather conditions, such as hurricanes, floods, wildfires, and droughts, may also cause long-term severe concerns. However, the knowledge about possible psychiatric disorders associated with these exposures is currently not well disseminated. In this review, we aim to summarize the current knowledge on the impact of environmental pollution and extreme weather conditions on mental health, focusing on anxiety spectrum disorders, autism spectrum disorders, schizophrenia, and depression. In air pollution studies, increased concentrations of PM2.5, NO2, and SO2 were the most strongly associated with the exacerbation of anxiety, schizophrenia, and depression symptoms. We provide an overview of the suggested underlying pathomechanisms involved. We highlight that the pathogenesis of environmental pollution-related diseases is multifactorial, including increased oxidative stress, systematic inflammation, disruption of the blood-brain barrier, and epigenetic dysregulation. Light pollution and noise pollution were correlated with an increased risk of neurodegenerative disorders, particularly Alzheimer's disease. Moreover, the impact of soil and water pollution is discussed. Such compounds as crude oil, heavy metals, natural gas, agro-chemicals (pesticides, herbicides, and fertilizers), polycyclic or polynuclear aromatic hydrocarbons (PAH), solvents, lead (Pb), and asbestos were associated with detrimental impact on mental health. Extreme weather conditions were linked to depression and anxiety spectrum disorders, namely PTSD. Several policy recommendations and awareness campaigns should be implemented, advocating for the advancement of high-quality urbanization, the mitigation of environmental pollution, and, consequently, the enhancement of residents' mental health.

Effects of ambient air pollution on the hospitalization risk and economic burden of mental disorders in Qingdao, China

OBJECTIVE

The aim of this study was to examine the impacts of short-term exposure to air pollutants on hospitalizations for mental disorders (MDs) in Qingdao, a Chinese coastal city, and to assess the corresponding hospitalization risk and economic cost.

METHODS

Daily data on MD hospitalizations and environmental variables were collected from January 1, 2015, to December 31, 2019. An overdispersed generalized additive model was used to estimate the association between air pollution and MD hospitalizations. The cost of illness method was applied to calculate the corresponding economic burden.

RESULTS

With each 10 μg/m3 increase in the concentration of fine particulate matter (PM2.5) at lag05, inhalable particulate matter (PM10) at lag0, sulfur dioxide (SO2) at lag06 and ozone (O3) at lag0, the corresponding relative risks (RRs) and 95% confidence intervals (CIs) were 1.0182 (1.0035-1.0332), 1.0063 (1.0001-1.0126), 1.0997 (1.0200-1.1885) and 1.0099 (1.0005-1.0194), respectively. However, no significant effects of nitrogen dioxide (NO2) or carbon monoxide (CO) were found. Stratified analysis showed that males were susceptible to SO2 and O3, while females were susceptible to PM2.5. Older individuals (≥ 45 years) were more vulnerable to air pollutants (PM2.5, PM10, SO2 and O3) than younger individuals (< 45 years). Taking the Global Air Quality Guidelines 2021 as a reference, 8.71% (2,168 cases) of MD hospitalizations were attributable to air pollutant exposure, with a total economic burden of 154.36 million RMB.

CONCLUSION

Short-term exposure to air pollution was associated with an increased risk of hospitalization for MDs. The economic advantages of further reducing air pollution are enormous.

The impact of hazes on schizophrenia admissions and the synergistic effect with the combined atmospheric oxidation capacity in Hefei, China

OBJECTIVES

Currently, most epidemiological studies on haze focus on respiratory diseases, cardiovascular diseases, etc. However, the relationship between haze and mental health has not been adequately explored. The purpose of this study was to investigate the influence of hazes on schizophrenia admissions and to further explore the potential interaction effect with the combined atmospheric oxidative indices (O_x and O_x^wt).

METHODS

We collected 5328 cases during the cold season from 2013 to 2015 in Hefei, China. By integrating the Poisson Generalized Linear Models with the Distributed Lag Non-linear Models, the association between haze and schizophrenia admissions was evaluated. The interaction between hazes and two combined oxidation indexes was tested by stratifying hazes and O_x, and O_x^wt.

RESULTS

Haze was found to be significantly linked to an increased risk of hospitalization for schizophrenia, and a 9-day lag effect on schizophrenia (lag 3-lag 11), with the largest effect on lag 6 (RR = 1.080, 95% confidence interval (CI): 1.046-1.116). Males, females, and <40 y (people under 40 years old) were sensitive to hazes. Furthermore, in the stratified analysis, we found synergies between two combined oxidation indexes and hazes. The interaction relative risk (IRR) and relative excess risk due to interaction (RERI) between O_x and hazes were 1.170 (95% CI: 1.071-1.277) and 0.149 (95% CI: 0.045-0.253), respectively. For O_x^wt, the IRR and RERI were 1.179 (95% CI: 1.087-1.281) and 0.159 (95% CI: 0.056-0.263), respectively. It is noteworthy that this synergistic effect was significant in males and <40 y when examining the various subgroups in the interaction analysis.

CONCLUSIONS

Our findings suggest that exposure to haze significantly increases the risk of hospitalization for schizophrenia. More significant public health benefits can be obtained by prioritizing haze periods with high combined atmospheric oxidation capacity.

Air Pollution-Related Neurotoxicity Across the Life Span

Air pollution is a complex mixture of gases and particulate matter, with adsorbed organic and inorganic contaminants, to which exposure is lifelong. Epidemiological studies increasingly associate air pollution with multiple neurodevelopmental disorders and neurodegenerative diseases, findings supported by experimental animal models. This breadth of neurotoxicity across these central nervous system diseases and disorders likely reflects shared vulnerability of their inflammatory and oxidative stress-based mechanisms and a corresponding ability to produce brain metal dyshomeo-stasis. Future research to define the responsible contaminants of air pollution underlying this neurotoxicity is critical to understanding mechanisms of these diseases and disorders and protecting public health.

Effects of urban particulate matter on gut microbiome and partial schizophrenia-like symptoms in mice: Evidence from shotgun metagenomic and metabolomic profiling

BACKGROUND

Epidemiological evidence reported that particulate matter (PM) was associated with increased schizophrenia (SCZ) risk. Disturbance of gut microbiome was involved in SCZ. However, it remains unclear whether PM induces SCZ-like symptoms and how gut microbiome regulates them. Therefore, a multi-omics animal experiment was conducted to verify how urban PM induces SCZ-like behavior and altered gut microbiota and metabolic pathways.

METHODS

Using a completely random design, mice were divided into three groups: PM group, control group and MK801 group, which received daily tracheal instillation of PM solution, sterile PBS solution and intraperitoneal injection of MK801 (establish SCZ model), respectively. After a 14-day intervention, feces were collected for multi-omics testing (shotgun metagenomic sequencing and untargeted metabolomic profiling), followed by open field test, tail suspension test, and passive avoidance test. Besides, fecal microbiome of PM group and control group were transplanted into "pseudo-sterile" mice, then behavioral tests were conducted.

RESULTS

Similar to MK801 group, mice in PM group showed SCZ-like symptoms, including increased spontaneous activity, excitability, anxiety and decreased learning and spatial memory. PM exposure significantly increased the relative abundance of Verrucomicrobia and decreased that of Fibrobacteres et al. The metabolism pathways of estrogen signaling (estriol, 16-glucuronide-estriol and 21-desoxycortisol) and choline metabolism (phosphocholine) were significantly altered by PM exposure. Verrucomicrobia was negatively correlated with the level of estriol, which was correlated with decreased learning and spatial memory. Fibrobacteres and Deinococcus-Thermus were positively correlated with the level of phosphocholine, which was correlated with increased spontaneous activity, excitability and anxiety. Fecal microbiome transplantation from PM group mice reproduced excitability and anxiety symptoms.

CONCLUSIONS

Exposure to PM may affect composition of gut microbiome and alterations of estrogen signaling pathway and choline metabolism pathway, which were associated with partial SCZ-like behaviors. But whether gut microbiome regulates these metabolic pathways and behaviors remains to be determined.

Neurodevelopmental toxicity induced by PM2.5 Exposure and its possible role in Neurodegenerative and mental disorders

Recent extensive evidence suggests that ambient fine particulate matter (PM2.5, with an aerodynamic diameter ≤2.5 μm) may be neurotoxic to the brain and cause central nervous system damage, contributing to neurodevelopmental disorders, such as autism spectrum disorders, neurodegenerative diseases, such as Alzheimer's disease and Parkinson's disease, and mental disorders, such as schizophrenia, depression, and bipolar disorder. PM2.5 can enter the brain via various pathways, including the blood-brain barrier, olfactory system, and gut-brain axis, leading to adverse effects on the CNS. Studies in humans and animals have revealed that PM2.5-mediated mechanisms, including neuroinflammation, oxidative stress, systemic inflammation, and gut flora dysbiosis, play a crucial role in CNS damage. Additionally, PM2.5 exposure can induce epigenetic alterations, such as hypomethylation of DNA, which may contribute to the pathogenesis of some CNS damage. Through literature analysis, we suggest that promising therapeutic targets for alleviating PM2.5-induced neurological damage include inhibiting microglia overactivation, regulating gut microbiota with antibiotics, and targeting signaling pathways, such as PKA/CREB/BDNF and WNT/β-catenin. Additionally, several studies have observed an association between PM2.5 exposure and epigenetic changes in neuropsychiatric disorders. This review summarizes and discusses the association between PM2.5 exposure and CNS damage, including the possible mechanisms by which PM2.5 causes neurotoxicity.

Evaluation of the efficiency of a Venturi scrubber in particulate matter collection smaller than 2.5 µm emitted by biomass burning

Energy demand has increased worldwide, and biomass burning is one of the solutions most used by industries, especially in countries that have a great potential in agriculture, such as Brazil. However, these energy sources generate pollutants, consisting of particulate matter (PM) with a complex chemical composition, such as sugarcane bagasse (SB) burning. Controlling these emissions is necessary; therefore, the aim was to evaluate PM collection using a rectangular Venturi scrubber (RVS), and its effects on the composition of the PM emitted. Considering the appropriate use of biomass as an industrial fuel and the emerging need for a technique capable of efficiently removing pollutants from biomass burning, this study shows the control of emissions as an innovation in a situation such as the industrial one with the use of a Venturi scrubber in fine particle collection, in addition to using portable and representative isokinetic sampling equipment of these particles. The pilot-scale simulation of the biomass burning process, the representative sampling of fine particles and obtaining parameters to control pollutant emissions for a Venturi scrubber, meets the current situation of concern about air quality. The average collection efficiency values were 96.6% for PM_{> 2.5}, 85.5% for PM_1.0-2.5, and 66.9% for PM_{< 1.0}. The ionic analysis for PM_{< 1.0} filters showed potassium, chloride, nitrate, and nitrite at concentrations ranging from 20.12 to 36.5 μg/m³. As the ethanol and sugar plants will continue to generate electricity with sugarcane bagasse burning, emission control technologies and cost-effective and efficient portable samplers are needed to monitor particulate materials and improve current gas cleaning equipment projects.

Short-term effects of extreme meteorological factors on daily outpatient visits for anxiety in Suzhou, Anhui Province, China: a time series study

Anxiety disorders are a major public health concern in China. Previous studies have provided evidence for associations between ambient temperature and anxiety outpatient visits, but no studies have examined short-term effects of other meteorological factors such as sunshine duration, wind speed, and precipitation on increased anxiety outpatient visits. We aimed to assess the association between climatic factors and outpatient visits for anxiety in Suzhou, a city with a temperate climate in Anhui Province, China. Daily anxiety outpatient visits, meteorological factors, and air pollutants from 2017 to 2019 were collected. A quasi-Poisson generalized linear regression model combined with distributed lag non-linear model (DLNM) was used to quantify the effects of extreme meteorological factors (sunshine duration, wind speed, and precipitation) on anxiety outpatient visits. All effects were presented as relative risk (RR), with the 90th and 10th percentiles of meteorological factors compared to the median. Subgroup analyses by age and gender were performed to identify susceptible subgroups. A total of 11,323 anxiety outpatient visits were reported. Extremely low sunshine duration and low and high wind speed increased the risk of anxiety outpatient visits. The strongest cumulative effects occurred at lag 0-14 days, and the corresponding RRs of extremely low sunshine duration and low and high wind speed were 1.417 (95% CI: 1.056-1.901), 1.529 (95% CI: 1.028-2.275), and 1.396 (95% CI: 1.007-1.935), respectively. Subgroup analyses showed that males and people aged ≥45 years appeared to be more susceptible to the cumulative effects of extremely low sunshine duration. In addition, the adverse effects of extreme wind speed were more pronounced in the cold season. This study provides evidence that extreme climatic factors have a lagged effect on anxiety outpatient visits. In the context of climate change, these findings may help develop weather-based early warning systems to minimize the effects of extreme meteorological factors on anxiety.

Short-term exposure to air pollution is an emerging but neglected risk factor for schizophrenia: A systematic review and meta-analysis

OBJECTIVE

This meta-analysis aimed to explore the association between short-term exposure to air pollution and schizophrenia (SCZ)1, and investigate the susceptible population and the lag characteristics of different pollutants.

METHODS

A systematic review and meta-analysis was conducted by searching PubMed, Cochrane, Web of Sciences, and CNKI for relevant literature published up to 28 Feb 2022. Meta-analysis was performed separately to investigate the association of ambient particulates (diameter ≤ 2.5 μm (PM2.5)2, 2.5 μm < diameter < 10 μm (PMC)3, ≤10μm (PM10)4) and gaseous pollutants (nitrogen dioxide (NO2)5, sulfur dioxide (SO2)6, carbon monoxide (CO)7) with SCZ. Relative risk (RR)8 per 10 μg/m3 increase in air pollutants concentration was used as the effect estimate. Subgroup analyses were conducted by age, gender, country, median pollutant concentration, and median temperature.

RESULTS

We identified 17 articles mainly conducted in Asia, of which 13 were included in the meta-analysis. Increased risk of SCZ was associated with short-term exposure to PM2.5 (RR: 1.0050, 95 % confidence interval (CI)9: 1.0017, 1.0083), PMC (1.0117, 1.0023, 1.0211), PM10 (1.0047, 1.0025, 1.0070), NO2 (1.0275, 1.0132, 1.0420), and SO2 (1.0288, 1.0146, 1.0432) exposure. Subgroup analyses showed that females may be more susceptible to SO2 and NO2, and the young seem to be more sensitive to PM2.5 and PM10. Gaseous pollutants presented the immediate risk, and particulates showed the delayed risk.

CONCLUSIONS

The present meta-analysis suggests that short-term exposure to PM2.5, PMC, PM10, SO2, and NO2 exposure may be associated with an elevated risk of SCZ.

Effects of sunshine duration on daily outpatient visits for depression in Suzhou, Anhui Province, China

Previous epidemiological studies have reported seasonal variation patterns of depression symptoms, which may be influenced by bad weather conditions, such as a lack of sunlight. However, evidence on the acute effects of sunshine duration on outpatient visits for depression is limited, especially in developing countries, and the results are inconsistent. We collected daily outpatient visits for depression from the local mental health centre in Suzhou, Anhui Province, China, during 2017-2019. We defined the 5th and 95th sunshine percentiles as short and long sunshine durations, respectively. A quasi-Poisson generalized linear regression model combined with a distributed lag nonlinear model was used to quantitatively assess the effects of short and long sunshine durations on outpatient visits for depression. Stratified analyses were further performed by gender, age and number of visits to identify vulnerable populations. A total of 26,343 depression cases were collected during the study period. An approximate U-shaped exposure-response association was observed between sunshine duration and depression outpatient visits. The cumulative estimated relative risks (RRs) for short and long sunshine durations at lag 0-21 days were 1.53 [95% confidence intervals (CI): 1.14, 2.06] and 1.13 (95% CI: 0.88, 1.44), respectively. Moreover, a short sunshine duration was associated with a greater disease burden than a long sunshine duration, with attributable fractions (AFs) of 16.64% (95% CI: 7.8%, 23.89%) and 2.24% (95% CI: -2.65%, 5.74%), respectively. Subgroup analysis showed that males, people aged less than 45 years and first-visit cases may be more susceptible to a lack of sunlight. For a long sunshine duration, no statistically significant associations were found in any population groups. Our study found that a short sunshine duration was associated with an increased risk of depression. The government, medical institutions, family members and patients themselves should fully recognize the important role of sunlight and take active measures to prevent depression.

A cross-sectional analysis of registry data of severe mental disorders in Fuzhou, China: current status and prospects

OBJECTIVE

To investigate the proportion of registered cases relative to size, distribution characteristics, medication status, and management status of patients diagnosed with severe mental disorders (SMD) in Fuzhou. The medication status and management status were compared between patients in urban and non-urban areas to provide scientific evidence for improving SMD care, control, and treatment in primary health care institutions.

METHODS

Data (case types, demographic data, distribution data, medication status, and management status, etc.) of patients diagnosed with SMD in 12 districts, counties, and prefectures in the urban and non-urban areas of Fuzhou City were collected from October 2017 to September 2018. Three distributions (population, local, and districts/counties) were used to describe the proportion of registered cases relative to size and clinical characteristics of diagnosed SMD. Chi squared (χ2) test was used to compare the severity in urban and non-urban areas.

RESULTS

A total of 30,362 registered SMD patients were identified in Fuzhou City of which schizophrenia accounted for the highest number of cases (26,204, 86.31%), and paranoid psychosis had the least number of cases (47, 0.15%). Moreover, approximately half of SMD patients were 18 to 44 years old (45.38%). Close to one third of patients were farmers (30.23%), had a primary school or lower education level (54.17%), were poor, with most below the poverty line (55.35%). The proportion of diagnosed SMD relative to size was highest in Minqing County (0.53%) and lowest in Mawei District (0.38%). A total of 22,989 (75.72%) of the patients were taking medications, and only 17,509 (57.67%) were taking medications regularly. Moreover, the percentage of cases taking medications and those taking medications regularly were higher in urban areas than in non-urban areas (P<0.05). A total of 3065 patients were registered for management (10.09%). The managed proportion of SMD cases was higher in the urban areas than in the non-urban areas (P < 0.05).

CONCLUSION

Schizophrenia is a key disease for comprehensive care and control of severe mental disorders in Fuzhou. The management of severe mental disorders should focus on poor groups with low educational backgrounds. Drug usage and management are better in urban areas than in non-urban areas, and thus management should be enhanced in non-urban areas. The medication management and case management of patients with severe mental disorders in Fuzhou need further improvements.

Short-term effects and economic burden assessment of ambient air pollution on hospitalizations for schizophrenia

The evidence on the health and economic impacts of air pollution with schizophrenia is scarce, especially in developing countries. In this study, we aimed to systemically examine the short-term effects of PM_2.5 (particulate matter ≤ 2.5 μm in diameter), PM₁₀ (≤ 10 μm in diameter), NO₂ (nitrogen dioxide), SO₂ (sulfur dioxide), CO (carbon monoxide), and O₃ (ozone) on hospital admissions for schizophrenia in a Chinese coastal city (Qingdao) and to further assess the corresponding attributable risk and economic burden. A generalized additive model (GAM) was applied to model the impact of air pollution on schizophrenia, and the corresponding economic burden including the direct costs (medical expenses) and indirect costs (productivity loss). Stratified analyses were also performed by age, gender, and season (warm or cold). Our results showed that for a 10 μg/m³ increase in the concentrations of PM_2.5, PM₁₀, SO₂, and CO at lag5, the corresponding relative risks (RRs) were 1.0160 (95% CI: 1.0038-1.0282), 1.0097 (1.0018-1.0177), 1.0738 (1.0222-1.01280), and 1.0013 (1.0001-1.0026), respectively. However, no significant effect of NO₂ or O₃ on schizophrenia admissions was found. The stratified analysis indicated that females and younger individuals (< 45 years old) appeared to be more vulnerable, but no significant difference was found between seasons. Furthermore, 12.41% of schizophrenia hospitalizations were attributable to exposure to air pollution exceeding the World Health Organization (WHO) air quality standard, with a total economic burden of 89.67 million RMB during the study period. At the individual level, excessive air pollution exposure resulted in an economic burden of 8232.08 RMB per hospitalization. Our study found that short-term exposure to air pollutants increased the risk of hospital admissions for schizophrenia and resulted in a substantial economic burden. Considerable health benefits can be achieved by further reducing air pollution.

Air pollution and mental health: associations, mechanisms and methods

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.