Air pollution and daily emergency department visits for depression

Trajectories of depressive symptom and its association with air pollution: evidence from the Mr. OS and Ms. OS Hong Kong cohort study

BACKGROUND

Depression is a global health priority. Maintaining and delaying depressive symptoms in older adults is a key to healthy aging. This study aimed to identify depressive symptom trajectories, predictors and mortality, while also exploring the relationship between air quality and depressive symptoms in older adults in the Hong Kong community over 14 years.

METHODS

This study is a longitudinal study in Hong Kong. The target population was community-dwelling older adults over age 65. Depressive symptoms were measured by the Geriatric Depression Scale (GDS-15). Group-based trajectory model was used to identify heterogeneity in longitudinal changes over 14 years and examine the associations between baseline variables and trajectories for different cohort members using multinomial logistic regression. The Kaplan-Meier method was employed to conduct survival analysis and explore the variations in survival probabilities over time among different trajectory group. Linear mixed model was used to explore the relationship between air quality and depressive symptoms.

RESULTS

A total of 2828 older adults were included. Three different trajectories of depressive symptoms in older people were identified: relatively stable (15.4%), late increase (67.1%) and increase (17.5%). Female, more number of chronic diseases, poor cognitive function, and poor health-related quality of life (HRQOL) were significantly associated with other less favorable trajectories compared with participants with stable levels of depressive symptoms. The late increase group had a lower mortality rate than the relatively stable and increased groups. Lower baseline ambient air pollutant exposure to NO2 over 14 years was significantly associated with fewer depressive symptoms.

CONCLUSIONS

In this study, we found that a late increase in depressive symptoms was the predominant trend in older Chinese people in Hong Kong. Poorer HRQOL was predictive of less favorable trajectories of depressive symptoms. Ambient air pollution was associated with depressive symptoms. This novel observation strengthens the epidemiological evidence of longitudinal changes in depressive symptoms and associations with late-life exposure to air pollution.

Personality Traits, Burnout, and Psychopathology in Healthcare Professionals in Intensive Care Units-A Moderated Analysis

This study explored the associations between personality dimensions, burnout, and psychopathology in healthcare professionals in intensive care units (ICUs). This study further aimed to discern the differences in these relationships when considering the variables of critical care experience (less than 5 years, 5-10 years, and more than 10 years), profession (nurses versus intensivists), and the urban size of the city where the ICU is located (metropolitan cities versus smaller urban cities). This cross-sectional investigation's outcomes are based on data from 503 ICU personnel, including 155 intensivists and 348 nurses, in 31 ICU departments in Greece. Participants underwent a comprehensive assessment involving a sociodemographic questionnaire, the Eysenck Personality Questionnaire (EPQ), the Maslach Burnout Inventory (MBI), and the Symptom Checklist-90 (SCL-90). To analyze the interplay among critical care experience, burnout status, and psychopathology, a moderation analysis was conducted with personality dimensions (i.e., psychoticism, extraversion, and neuroticism) serving as the mediator variable. Profession and the urban size of the ICU location were considered as moderators influencing these relationships. Male healthcare professionals showed higher psychoticism levels than females, aligning with prior research. Experienced nurses reported lower personal achievement, hinting at potential motivation challenges for professional growth. Psychoticism predicted high depersonalization and low personal achievement. Neuroticism and psychoticism negatively impacted ICU personnel's mental well-being, reflected in elevated psychopathology scores and burnout status. Psychoticism appears to be the primary factor influencing burnout among the three personality dimensions, particularly affecting intensivists. In contrast, nurses are more influenced by their critical care experience on their mental health status.

The relationship between air pollution and depression and anxiety disorders - A systematic evaluation and meta-analysis of a cohort-based study

OBJECTIVE

To explore the correlation between air pollution and the onset of depression and anxiety disorders, to draw more comprehensive and integrated conclusions, and to provide recommendations for maintaining mental health and developing policies to reduce mental health risks caused by air pollution.

METHODS

Meta-analysis of cohort study articles exploring the relationship between air pollution and depression or anxiety disorders included in Pubmed, Web Of Science, CNKI, and Wan Fang database before October 31, 2022, and subgroup analysis of the association between air pollution and depression and anxiety disorders regarding the air pollutants studied, the study population, and Publication bias analysis and sensitivity analysis.

RESULTS

A total of 25 articles meeting the criteria were included in this study, including 23 articles examining the relationship between air pollution and depression and 5 articles examining the relationship between air pollution and anxiety disorders. The results of the meta-analysis were based on the type of pollutant and showed that there was a high degree of heterogeneity among the studies on the relationship between air pollution and depression and a significant heterogeneity among the studies on PM2.5 and the risk of anxiety disorders (I2 = 71%, p < .01), so a random-effects model was selected for the analysis. CO, O3, and SO2 and depression onset had combined RR values of 1.10 (1.00, 1.20), 1.06 (0.87, 1.29), 1.17 (1.06, 1.31), 1.19 (0.90, 1.58), 1.03 (0.99, 1.07), and 1.09 (0.97, 1.24), respectively, and PM2.5 and anxiety The combined RR value for morbidity was 1.10 (0.99, 1.22). The results of sensitivity analysis showed that the combined results were stable and reliable. The results of Egger regression method test showed that none of them had significant publication bias (p > .05).

LIMITATION

Combined exposure to air pollutants on depression and anxiety, further studies by other researchers are needed in the future.

CONCLUSIONS

PM2.5 and NO2 exposure, especially long-term exposure, may be associated with the onset of depression, and no association was found for the time being between PM10, CO, O3, SO2 exposure and depression and PM2.5 exposure and anxiety disorders.

Towards the new generation of courtyard buildings as a healthy living concept for post-pandemic era

COVID-19 has laid a context for holistic research and practical approaches towards health issues in buildings. This study focuses on one particular residential building type, which is a combination of a modern apartment building with private double-oriented terraces, and a traditional courtyard building. This principle improves several aspects of healthy buildings and contributes to address indoor-outdoor interactions, daylighting, and the use of natural ventilation. The purpose of this study is to determine the factors underlying a particular type of semi-outdoor space within building forms and to explain their microclimatic behavior in buildings. One solid model and twelve porous apartment buildings with different numbers of porous sides, and terrace widths are evaluated using computational fluid dynamics. The k-ε turbulence model is adapted to simulate airflow in and around a four-story building. CFD simulations were validated against the wind-tunnel measurements. Investigations indicated that increasing the number of porous sides reduces the internal mean and maximum ages of air by -15.75 and -36.84%, which means improved ventilation performance. However, it leaves a negative trace on ventilation of the semi-outdoor spaces. Meanwhile, increasing the width of the terraces enhances the ventilation performance by reducing the mean age of air in units, courtyards, and terraces by -20%, -20%, and -9%, respectively.

NEUROMETABOLOMIC IMPACTS OF MODELED WILDFIRE SMOKE AND PROTECTIVE BENEFITS OF ANTI-AGING THERAPEUTICS IN AGED FEMALE C57BL/6J MICE

Wildland fires have become progressively more extensive over the past 30 years in the US, and now routinely generate smoke that deteriorates air quality for most of the country. We explored the neurometabolomic impact that smoke derived from biomass has on older (18 months) female C57BL/6J mice, both acutely and after 10 weeks of recovery from exposures. Mice (N=6/group) were exposed to wood smoke (WS) 4 hours/day, every other day, for 2 weeks (7 exposures total) to an average concentration of 0.448mg/m 3 per exposure. One group was euthanized 24 hours after the last exposure. Other groups were then placed on 1 of 4 treatment regimens for 10 weeks after wood smoke exposures: vehicle; resveratrol in chow plus nicotinamide mononucleotide in water (RNMN); senolytics via gavage (dasatanib+quercetin; DQ); or both RNMN with DQ (RNDQ). Among the findings, the aging from 18 months to 21 months was associated with the greatest metabolic shift, including changes in nicotinamide metabolism, with WS exposure effects that were relatively modest. WS caused a reduction in NAD+ within the prefrontal cortex immediately after exposure and a long-term reduction in serotonin that persisted for 10 weeks. The serotonin reductions were corroborated by forced swim tests, which revealed an increased immobility (reduction in motivation) immediately post-exposure and persisted for 10 weeks. RNMN had the most beneficial effects after WS exposure, while RNDQ caused markers of brain aging to be upregulated within WS-exposed mice. Findings highlight the persistent neurometabolomic and behavioral effects of woodsmoke exposure in an aged mouse model.

Significance Statement

Neurological impacts of wildfire smoke are largely underexplored but include neuroinflammation and metabolic changes. The present study highlights modulation of major metabolites in the prefrontal cortex and behavioral consequences in aged (18 month) female mice that persists 10 weeks after wood smoke exposure ended. Supplements derived from the anti-aging field were able to mitigate much of the woodsmoke effect, especially a combination of resveratrol and nicotinamide mononucleotide.

Significant association between increased risk of emergency department visits for psychiatric disorders and air pollutants in South Korea

BACKGROUND

The association between air pollutants and psychiatric disorders has been investigated in many countries. However, results for the association between air pollutants and emergency room (ER) visits for psychiatric disorders are inconsistent. Further, systematic large-scale studies relating to the same are lacking, especially in South Korea.

OBJECTIVE

We aimed to investigate the acute and short-term cumulative effect of air pollutants on ER visits for psychiatric disorders in South Korea.

METHODS

The data on nitrogen dioxide (NO2) and particulate matter (PM2.5 and PM10) and ER visits due to nine representative psychiatric disorders were collected from eight major cities in South Korea for three years. We estimated the relative risk (RR) at lag 0 and a cumulative 11-day RR by increasing a 10-unit for PM and 0.01-unit for NO2 using the Distributed Lag Nonlinear Model.

RESULTS

During the study period, a total of 79,092 ER visits for psychiatric disorders were identified and tested for association with NO2, PM2.5, and PM10. The RR at lag 0 of depression per 0.01-unit increase in NO2 was the highest (3.127; 95% confidence interval [CI] 2.933 to 3.332) among the psychiatric disorders. The RRs at lag 0 of anxiety disorders per 10-unit increase in PM2.5 (1.709; 95% CI 1.424 to 2.053) and PM10 (2.168; 95% CI 1.957 to 2.403) were the highest among the psychiatric disorders.

SIGNIFICANCE

Air pollutants increased ER visits for psychiatric disorders with the highest RR of depression due to NO2 and anxiety disorder due to PM2.5 and PM10. These results contribute evidence to the positive association between ambient exposure to air pollution and aggravation of psychiatric disorders, indicating air pollution may be a modifiable risk factor in mental health management.

IMPACT STATEMENT

We investigated the effect of air pollution on emergency room visits caused by major psychiatric disorders in prominent cities in South Korea. Using the Distributed Lag Nonlinear Model, an advanced analysis method, we calculated the acute effect and short-term cumulative effect. Air pollutants increased ER visits for psychiatric disorders with the highest relative risk of depression due to NO2 and anxiety disorder due to PM2.5 and PM10. These results reveal an association between ambient exposure to air pollution and aggravation of psychiatric disorders and suggest that air pollution may be a modifiable risk factor in mental health management.

Affective disorder and brain alterations in children and adolescents exposed to outdoor air pollution

BACKGROUND

Childhood and adolescence are critical periods for the development of the brain. However, a limited number of studies have explored how air pollution may associate with affective symptoms in youth.

METHODS

We performed a comprehensive review of the existing research on the associations between outdoor air pollution and affective disorders, suicidality, and the evidence for brain changes in youth. PRISMA guidelines were followed and PubMed, Embase, Web of Science, Cochrane Library, and PsychINFO databases were searched from their inception to June 2022.

RESULTS

From 2123 search records, 28 papers were identified as being relevant for studying the association between air pollution and affective disorders (n = 14), suicide (n = 5), and neuroimaging-based evidence of brain alterations (n = 9). The exposure levels and neuropsychological performance measures were highly heterogeneous and confounders including traffic-related noise, indoor air pollution, and social stressors were not consistently considered. Notwithstanding, 10 out of the 14 papers provide evidence that air pollution is associated with increased risk of depression symptoms, and 4 out of 5 papers provide evidence that air pollution might trigger suicidal attempts and behaviors. Besides, 5 neuroimaging studies revealed decreased gray-matter volume in the Cortico-Striato-Thalamo-Cortical neurocircuitry, and two found white matter hyperintensities in the prefrontal lobe.

CONCLUSIONS

Outdoor air pollution is associated with increased risks of affective disorders and suicide in youth, and there is evidence for associated structural and functional brain abnormalities. Future studies should determine the specific effects of each air pollutant, the critical exposure levels, and population susceptibility.

Predicting daily emergency department visits using machine learning could increase accuracy

OBJECTIVE

Administrators and clinicians alike have attempted to predict emergency department visits for many years. The ability to predict or "forecast" ED visit volume can allow for more efficient resource allocation, including up-staffing or down-staffing, changing OR schedules, and predicting the need for significant resources. The goal of this study is to examine combinations of variables via machine learning to increase prediction accuracy and determine the factors that are most predictive of overall ED visits. As compared to a simple univariate time series model, we hypothesize that machine learning models will predict St. Joseph Mercy Ann Arbor's patient visit load for the emergency department (ED) with higher accuracy than a simple univariate time series model.

METHODS

Univariate time series models for daily ED visits, including ARIMA, Exponential Smoothing (ETS), and Facebook Inc.'s prophet algorithm were estimated as a baseline comparison. Machine learning models, including random forests and gradient boosted machines (GBM), were trained using data from 2017 to 2018. After final models were created, they were applied to the 2019 data to determine how well these models predicted actual ED patient volumes in data not utilized during the model fitting process. The accuracy of the machine learning and time series models were assessed based on out-of-sample predictive accuracy, compared using root mean squared error (RMSE).

RESULTS

Using root mean squared error (RMSE) to assess out-of-sample predictive accuracy of the models, the results showed that the random forest model was the most accurate at predicting daily ED visits in the 2019 test set, followed by the GBM model. These performed only slightly better than the simple exponential smoothing model predictions. The ARIMA model performed poorly in comparison. The day of the week (likely capturing differences between weekdays and weekends) was found to be the most important predictor of patient volumes. Weather-related features such as maximum temperature and SFC pressure appeared to capture some of the seasonality trends related to changes in patient volumes.

CONCLUSIONS

Machine learning models perform better at predicting daily patient volumes as compared to simple univariate time series models, though not by a substantial amount. Further research can help confirm these limited initial results. Gathering more training data and additional feature engineering could also be beneficial to training the models and potentially improving predictive accuracy.

Pediatric anxiety and daily fine particulate matter: A longitudinal study

Daily variations in ambient fine particulate matter (PM_2.5) could contribute to the morbidity of anxiety disorders in children and adolescents, but has not yet been studied longitudinally at a daily level. We tested this association using repeated weekly measures of anxiety symptom severity in a group of 23 adolescents with generalized anxiety disorder. After estimating ambient PM_2.5 concentrations using a validated model, we found that increased concentrations were significantly associated with increased anxiety symptom severity and frequency two, three, and four days later. PM_2.5 may be a novel, modifiable exposure that could inform population level interventions to decrease psychiatric morbidity.

Air pollution, depressive and anxiety disorders, and brain effects: A systematic review

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.

Exposure to coal ash and depression in children aged 6-14 years old

BACKGROUND

When coal is burned for energy, coal ash, a hazardous waste product, is generated. Throughout the world, over 1 billion tons of coal ash is produced yearly. In the United States, over 78 million tons of coal ash was produced in 2019. Fly ash, the main component of coal ash contains neurotoxic metal (loid)s that may affect children's neurodevelopment and mental health. The objective of this study was to investigate the association between fly ash and depressive problems in children aged 6-14 years old.

METHODS

Children and their parents/guardians were recruited from 2015 to 2020. Tobit regression and logistic regression were used to assess the association between coal fly ash and depressive problems. To determine fly ash presence, Scanning Electron Microscopy was conducted on polycarbonate filters containing PM10 from the homes of the study participants. Depressive problems in children were measured using the Depressive Problems DSM and withdrawn/depressed syndromic problem scales of the Child Behavior Checklist.

RESULTS

In covariate-adjusted Tobit regression models, children with fly ash on the filter had higher scores on the DSM Depressive Problems (3.13 points; 95% CI = 0.39, 5.88) compared with children who did not have fly ash on the filter. Logistic regression supported these findings.

CONCLUSION

Coal ash is one of the largest waste streams in the U.S, but it is not classified as a hazardous waste by the Environmental Protection Agency. To our knowledge, no studies have assessed the impact of coal ash on children's mental health. This study highlights the need for further research into the effects of coal ash exposure on children's mental health, and improved regulations on release and storage of coal ash.

Air pollution, investor sentiment and stock liquidity

With the aggravation of air pollution, the impact of air pollution on the stock market, especially from the perspective of investor sentiment, has been of great concern and widely discussed. Based on data from China's A-share listed firms from January 1, 2016, to December 31, 2020, the relationship between urban air pollution and stock liquidity of listed firms and the internal mechanism is examined. Firstly, based on local preference theory, we start by predicting the impact of air pollution on stock liquidity. We, then, build a regression model for air pollution and stock liquidity, introducing the intermediary effect model to detect the relationship between the two and its mechanism. Finally, by subdividing the samples, we discuss the differential impact of air pollution on stock liquidity under different circumstances. We found that when air pollution worsens it reduces stock liquidity. The results of the mechanism analysis show that investor sentiment plays an intermediary role in the process of air pollution affecting stock liquidity, and pessimism induced by air pollution can reduce stock liquidity. Heterogeneity test results show that there are differences in the impact of air pollution on stock liquidity between heavily polluting firms and non-heavily polluting firms, different industries, different city sizes, and different levels of air pollution, has a greater effect in non-heavily polluting enterprises, manufacturing and other industries, medium sized cities and light pollution. The results of this research have important reference value for environmental protection departments to establish and improve air pollution monitoring systems and for listed firms to improve stock liquidity and deal with the environmental financial risks appropriately.

Air pollution, residents' happiness, and environmental regulation: evidence from China

This study investigates the impact of air pollution on residents' subjective happiness, using data from the China General Social Survey for 2013, 2015, and 2017, regional air pollution, and socioeconomic indicators. We find that air pollution has a negative effect on residents' subjective happiness. Specifically, the average marginal effect of the logarithm of SO₂ emissions on happiness is -0.0099 and significant at the 1% level; namely, a one-unit increase in [Formula: see text] will reduce the likelihood of residents feeling happy by 0.99%. This negative effect is greater for those who have children, are old, or have a higher level of education. We also empirically test two mechanisms by which air pollution affects subjective happiness-depressed mood and leisure activities outside the home-and demonstrate that environmental regulation can moderate the negative impact of air pollution on happiness, but the moderating effects are nonlinear. Environmental governance investments are more effective at the low level, pollutant discharge fees are more effective at the medium level, and complaints about environmental pollution are more effective at the high level. As well as enriching theoretical insights into the relationship between air pollution and happiness, this study provides a valuable reference for developing more suitable policies in relation to environmental management and national happiness.

Impact of Environmental Pollutants on Gut Microbiome and Mental Health via the Gut–Brain Axis

Over the last few years, the microbiome has emerged as a high-priority research area to discover missing links between brain health and gut dysbiosis. Emerging evidence suggests that the commensal gut microbiome is an important regulator of the gut–brain axis and plays a critical role in brain physiology. Engaging microbiome-generated metabolites such as short-chain fatty acids, the immune system, the enteric nervous system, the endocrine system (including the HPA axis), tryptophan metabolism or the vagus nerve plays a crucial role in communication between the gut microbes and the brain. Humans are exposed to a wide range of pollutants in everyday life that impact our intestinal microbiota and manipulate the bidirectional communication between the gut and the brain, resulting in predisposition to psychiatric or neurological disorders. However, the interaction between xenobiotics, microbiota and neurotoxicity has yet to be completely investigated. Although research into the precise processes of the microbiota–gut–brain axis is growing rapidly, comprehending the implications of environmental contaminants remains challenging. In these milieus, we herein discuss how various environmental pollutants such as phthalates, heavy metals, Bisphenol A and particulate matter may alter the intricate microbiota–gut–brain axis thereby impacting our neurological and overall mental health.

Ambient ozone exposure and hospitalization for substance abuse: A time-stratified case-crossover study in Taipei

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, PM_2.5, 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.

An Evaluation of Risk Ratios on Physical and Mental Health Correlations due to Increases in Ambient Nitrogen Oxide (NOx) Concentrations

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.

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.

Association between prenatal exposure to ambient air pollutants and postpartum depressive symptoms: A multi-city cohort study

BACKGROUND

Women are vulnerable to depression during postpartum period. While several studies have shown associations between ambient air pollution exposure and depression in general population, there was few studies focused on the effect of various air pollutants on postpartum depression (PPD).

OBJECTIVE

This study is designed to explore the association between prenatal exposure to air pollutants and PPD, and to reveal the potential vulnerable exposure time point.

METHODS

The study enrolled 10,209 pregnant women who delivered between October 2019 and February 2021 in 5 participating hospitals from 3 cities in China. Edinburgh Postnatal Depression Scale (EPDS) was administered at 6 weeks postpartum to identify PPD symptoms. Associations between PPD symptoms and exposure levels in PM_2.5, PM_10, SO₂, CO, NO₂, and O₃ averaged over the whole pregnancy and each trimester were estimated using logistic regression models after adjusting for potential confounding factors. Distributed lag models (DLMs) were used to determine the relevant associations in each gestational week.

RESULTS

The risk for developing PPD symptoms was significant following a 10 μg/m³ increase in PM₁₀ (aOR = 1.47, 95%CI:1.36-1.59), NO₂ (aOR = 1.63, 95%CI:1.44-1.85), and 0.1 mg/m³ increase in CO (aOR = 2.31, 95%CI: 1.99-2.69) during the whole pregnancy. Similar results were also found in exposure during each trimester of pregnancy. Besides, SO₂ exposure during the second trimester was a major risk factor for developing PPD symptoms (aOR = 1.10, 95%CI:1.03-1.18). Consistent effects were also observed in DLMs, except for PM_2.5 and O₃, which showed no significant sensitive windows throughout pregnancy period.

CONCLUSION

Exposure to PM₁₀, CO, NO₂, and SO₂ in pregnancy is associated with increased risks of developing depression at 6 weeks postpartum. Our findings reveal the importance of air pollution control for preventing maternal mental health disorders among the public.

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

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 (PM_2.5), 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 PM_2.5 (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), PM_2.5 (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 PM_2.5 and depression, strengthened by the absence of heterogeneity and of relevant publication bias in both long- and short-term exposure studies. Should further investigations be designed, they should involve large sample sizes, well-defined diagnostic criteria for depression, and thorough control of potential confounding factors. Finally, studies dedicated to the comprehension of the mechanisms underlying the association between air pollution and depression remain necessary.

Relationship between chronic exposure to ambient air pollution and mental health in Korean adult cancer survivors and the general population

Background

Although a significant association between air pollution and mental health has been identified, few studies have addressed this relationship based on cancer diagnosis. This study investigated whether associations between long-term air pollution and mental health conditions differ based on whether the individual has been diagnosed with cancer.

Methods

Nationally representative data were used and a total of 38,101 adults were included in the analyses. We assessed mental health factors such as perceived stress, depressive symptoms, and suicidal ideation, and analyzed the associations between these factors and individuals’ annual average exposure to air pollutants, including particulate matter with an aerodynamic diameter ≤ 10 μm (PM₁₀), nitrogen dioxide, sulfur dioxide, and carbon monoxide.

Results

Compared with the general population, PM₁₀ exposure in cancer survivors predicted a higher risk of depressive symptoms (odds ratio [OR] =1.34; 95% confidence interval [CI] = 1.06–1.69) and suicidal ideation (OR = 1.29; 95% CI = 1.01–1.64). Notably, the statistically significant relationship between PM₁₀ exposure and suicidal ideation in cancer survivors disappeared after further adjustment for depressive symptoms (p = 0.3103). This pattern was also observed in the result of propensity score-matched analysis for comparison between cancer survivors and the general population.

Conclusions

This study provides the first evidence that cancer survivors with depressive symptoms may be more susceptible to suicidal ideation in the context of persistent PM₁₀ exposure.

Exposure to mine fire related particulate matter and mortality: A time series analysis from the Hazelwood Health Study

BACKGROUND

In 2014, the Morwell brown coal mine, located in the Latrobe Valley of South eastern Australia, caught fire covering nearby areas in plumes of smoke over a 6-week period.

AIMS

To investigate the association between exposure to mine fire related air pollution and the risk of mortality.

METHODS

Time series models were used to evaluate the risk of mortality during the first 30 days of the mine fire, when the smoke was most intense, and in the following six months. Associations were also investigated between mine fire related PM_2.5 and mortality.

RESULTS

During the 30-day mine fire period, there was an increased risk of death from injury in the most exposed town of Morwell, however no increased risk was observed for all-cause, cardiovascular or respiratory mortality. In the broader Latrobe Valley, males and residents aged 80 and above were at greatest risk of death from injury during the mine fire. In Morwell, during the six months after the mine fire there was an increased risk of all-cause mortality and death from Ischaemic Heart Disease (IHD). Males and residents aged 80 and above in the broader Latrobe Valley, were at increased risk of death from IHD six months after the fire.

CONCLUSIONS

Coal mine fire exposure was associated with an increase in injury deaths during the mine fire and cardiovascular deaths in the six months after the fire. These findings assist in identifying at risk groups, and improving targeted health advice for future air pollution exposures in the community.

Association of short-term exposure to air pollution with depression in patients with sleep-related breathing disorders

Air pollution is associated with sleep-related breathing disorders; however, the effects of air pollution on depression in patients with SRBDs remain unclear. A cross-sectional study was conducted to collect polysomnographic (PSG) data and Beck Depression Inventory-IA (BDI-IA) responses from 568 subjects with SRDBs in a sleep center in 2015 to 2017. Exposure to air pollution, including particulate matter with an aerodynamic diameter of ≤10 μm (PM₁₀), particulate matter with an aerodynamic diameter of ≤2.5 μm (PM_2.5), nitrogen (NO₂), sulfur dioxide (SO₂), carbon monoxide (CO) and ozone (O₃), in 1-month averages was collected. Associations of air pollution with the respiratory disturbance index (RDI), oxygen desaturation index (ODI), arousal index (ARI), sleep architecture, and BDI-IA were examined. We observed that interquartile range (IQR) increases in 1-month PM_2.5, PM₁₀, and NO₂ levels were respectively associated with 4.1/hour (h) (95% confidence interval (CI): 1.7/h to 6.4/h), 3.7/h (95% CI: 1.4/h to 6.0/h) and 1.9/h (95% CI: 0.1/h to 3.7/h) increases in the ARI. For sleep architecture, IQR increases in 1-month PM_2.5 and CO levels were respectively associated with a 6.2% (95% CI: 6.1% to 6.3%) increase in non-rapid eye movement sleep 1 (N1) and a 2.0% (95% CI: -3.8% to -0.1%) decrease in non-rapid eye movement sleep 2 (N2). For depression, an IQR change in the 1-month CO was associated a moderate/severe depressive status according to the BDI-IA (odds ratio, OR: 2.981, p < 0.05; 95% CI: 1.032 to 8.611). Short-term exposure to air pollution increased the risk of arousal and light sleep as well as depression in patients with SRBDs. The results suggest that SRBD patients could be a population at risk for depression due to short-term exposure to air pollution.

Relationship between fine particulate air pollution and hospital admissions for depression: a case-crossover study in Taipei

There are few apparent studies regarding the association between fine particulate matter (PM_2.5) air pollution and development of depression. Data obtained from epidemiological studies are inconsistent and controversial. The aim of this case-crossover study was to examine the association between short-term exposure to PM_2.5 alone and in combination with other pollutants and frequency of hospitalizations for depression from 2009 to 2013 in Taipei, Taiwan. In the single pollutant model without adjustment for other pollutants, 17% and 4% increase in admissions attributed to depression correlated with interquartile range (IQR) rise in PM_2.5 levels was noted on warm and cool days, respectively. Data were also analyzed using two-pollutant models and it was found that on warm days, the association continued to be significant after including one of the following pollutants: sulfur dioxide (SO₂), nitrogen dioxide (NO₂), ozone (O₃) or carbon monoxide (CO). On cool days, the significance was lost. In conclusion, the relationship between ambient outdoor PM_2.5 exposure and rates of hospitalization for depression appeared to be temperature dependent in Taipei. Further research is needed to verify these observations as well as to distinguish the relative contributions of PM_2.5 and temperature to development for hospital admissions for depression.

Urban Air Pollution and Mental Stress: A Nationwide Study of University Students in China

Background: Studies exploring the relationship between air pollution levels and mental stress have rarely been done, and no studies have been done comparing university student mental stress levels based on regional air pollution levels.

Objectives: The objective of this study was to evaluate the association between air pollution and mental stress among university students.

Methods: Participants were 11,942 students, who were identified through a multistage survey sampling process conducted in 50 universities. Regional air pollution levels were retrieved from a national database, and mental stress was measured using a perceived stress scale. Both unadjusted and adjusted methods were utilized in the data analyses.

Results: Mental stress prevalence was 36.9% (95% Confidence Interval: 24.4–49.5%). The final model indicated that regional air pollution levels were positively associated with students' mental stress.

Conclusions: This study provided new and direct evidence of the health hazards of air pollution. The findings underscore the need to develop and implement stringent environmental protection policies, while simultaneously raising public awareness of environmental protection.

A spatial epidemiology case study of mentally unhealthy days (MUDs): air pollution, community resilience, and sunlight perspectives

The main objective of this spatial epidemiologic research is to gain greater insights into the geographic dimension displayed by the different duration of mentally unhealthy days (MUDs) across U.S. counties. Mentally unhealthy days (MUDs) are studied in entire cross counties for year of 2014. Using Behavioural Risk Factor Surveillance System (BRFSS) data in 2014, we examine main factors of mental health hazard including health behaviour, clinical care, socioeconomic and physical environment, demographic, community resilience, and extreme climatic conditions. In this study, we take complex design factors such as clustering, stratification and sample weight in the BRFSS data into account by using Complex Samples General Linear Model (CSGLM). Then, spatial regression models, spatial lag and error models, are applied to examine spatial dependencies and heteroscedasticity. Results of the geographic analyses indicate that counties with lower air pollution (PM2.5), higher community resilience (social, economic, infrastructure, and institutional resilience), and higher sunlight exposure had significantly lower average number of MUDs reported in the past 30 days. These findings suggest that policy makers should take air pollution, community resilience, and sunlight exposure into account when designing environmental and health policies and allocating resources to more effectively manage mental health problems.

Climate change, environment pollution, COVID-19 pandemic and mental health

Converging data would indicate the existence of possible relationships between climate change, environmental pollution and epidemics/pandemics, such as the current one due to SARS-CoV-2 virus. Each of these phenomena has been supposed to provoke detrimental effects on mental health. Therefore, the purpose of this paper was to review the available scientific literature on these variables in order to suggest and comment on their eventual synergistic effects on mental health. The available literature report that climate change, air pollution and COVID-19 pandemic might influence mental health, with disturbances ranging from mild negative emotional responses to full-blown psychiatric conditions, specifically, anxiety and depression, stress/trauma-related disorders, and substance abuse. The most vulnerable groups include elderly, children, women, people with pre-existing health problems especially mental illnesses, subjects taking some types of medication including psychotropic drugs, individuals with low socio-economic status, and immigrants. It is evident that COVID-19 pandemic uncovers all the fragility and weakness of our ecosystem, and inability to protect ourselves from pollutants. Again, it underlines our faults and neglect towards disasters deriving from climate change or pollution, or the consequences of human activities irrespective of natural habitats and constantly increasing the probability of spillover of viruses from animals to humans. In conclusion, the psychological/psychiatric consequences of COVID-19 pandemic, that currently seem unavoidable, represent a sharp cue of our misconception and indifference towards the links between our behaviour and their influence on the "health" of our planet and of ourselves. It is time to move towards a deeper understanding of these relationships, not only for our survival, but for the maintenance of that balance among man, animals and environment at the basis of life in earth, otherwise there will be no future.

Childhood exposure to ambient air pollution and predicting individual risk of depression onset in UK adolescents

Knowledge about early risk factors for major depressive disorder (MDD) is critical to identify those who are at high risk. A multivariable model to predict adolescents' individual risk of future MDD has recently been developed however its performance in a UK sample was far from perfect. Given the potential role of air pollution in the aetiology of depression, we investigate whether including childhood exposure to air pollution as an additional predictor in the risk prediction model improves the identification of UK adolescents who are at greatest risk for developing MDD. We used data from the Environmental Risk (E-Risk) Longitudinal Twin Study, a nationally representative UK birth cohort of 2232 children followed to age 18 with 93% retention. Annual exposure to four pollutants - nitrogen dioxide (NO₂), nitrogen oxides (NO_X), particulate matter <2.5 μm (PM_2.5) and <10 μm (PM₁₀) - were estimated at address-level when children were aged 10. MDD was assessed via interviews at age 18. The risk of developing MDD was elevated most for participants with the highest (top quartile) level of annual exposure to NO_X (adjusted OR = 1.43, 95% CI = 0.96-2.13) and PM_2.5 (adjusted OR = 1.35, 95% CI = 0.95-1.92). The separate inclusion of these ambient pollution estimates into the risk prediction model improved model specificity but reduced model sensitivity - resulting in minimal net improvement in model performance. Findings indicate a potential role for childhood ambient air pollution exposure in the development of adolescent MDD but suggest that inclusion of risk factors other than this may be important for improving the performance of the risk prediction model.

Exposure to particulate matter, prenatal depressive symptoms and HPA axis dysregulation

BACKGROUND

The prevalence of depression during pregnancy is on the rise, affecting women's well-being and their children's health outcomes. Preliminary studies suggest that exposure to air pollution during pregnancy may play a role in development of depressive symptoms. In addition, pollution has been linked to dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis, our brain's primary stress response system. The purpose of this study was to examine the association of air pollution exposure during pregnancy to prenatal depressive symptoms. We also evaluated whether cortisol, the hormonal endpoint of HPA activation, mediated the relationship between exposure to pollution and prenatal depression.

METHODS

Women were recruited in obstetric clinics during their third trimester of pregnancy. They completed the Patient Health Questionnaire-9 to assess depression and provided salivary samples at 4 times during the day for 2 days. Four measures of cortisol were calculated from salivary assays: average cortisol level, cortisol awakening response (CAR), diurnal cortisol slope (DCS), and area under the curve (AUCG). We acquired data on particulate matter with a diameter of 2.5 μm (PM2.5) or less within each woman's residential area from public records of the air quality control district. Structural equation modeling was used to analyze the aims.

RESULTS

Increased prenatal exposure to PM2.5 across pregnancy was associated with more severe depressive symptoms during the 3rd trimester (β = 0.14, p = 0.02). Greater PM2.5 exposure also had significant relationships with both higher cortisol AUCG (β = 15.933, p = 0.005) and average cortisol levels (β = 0.018, p = 0.023) among women. However, no cortisol parameter appeared to mediate the relationship between PM2.5 exposure and depressive symptoms.

CONCLUSIONS

Findings suggest pregnancy may be a critical window of sensitivity to PM2.5 exposure that escalates depression risk and induces activation of the HPA axis, evidenced in greater overall cortisol concentration. Further research is needed to identify mechanisms underlying the effects of particulate matter, especially potential methylation of glucocorticoid or serotonin transporter genes that may elicit changes in both depression and the stress response system. In addition, assessment of depression appears warranted for pregnant women in regions known for high pollution.

Association between short-term ambient air pollution exposure and depression outpatient visits in cold seasons: a time-series analysis in northwestern China

Depression is known to be one of the most common mental disorders raising global concerns. However, evidence regarding the association between short-term air pollution exposure and risk of development of depression is limited. The aim of this was to assess the relationship between short-term ambient air pollution exposure and depression in outpatient visits in Xi'an, a northwestern Chinese metropolis. Data for air pollutants including particulate matter (PM₁₀), sulfur dioxide (SO₂), and nitrogen dioxide (NO₂) levels from October 1, 2010 to December 31, 2013 and number of daily depression outpatient visits (92,387 in total) were collected. A time-series quasi-Poisson regression model was adopted to determine the association between short-term air pollutant concentrations and frequency of outpatient visits for depression with different lag models. Consequently, 10 μg/m³ increase of SO₂ and NO₂ levels corresponded to significant elevation in number of outpatient-visits for depression on concurrent days (lag 0), and this relationship appeared stronger in cool seasons (October to March). However, the association of PM₁₀ was only significant in males aged 30-50 at lag 0. Evidence indicated that short-term exposure to ambient air pollutants especially in cool seasons might be associated with increased risk of outpatient visits for depression.

Outdoor Air Pollution and Depression in Canada: A Population-Based Cross-Sectional Study from 2011 to 2016

To assess whether exposure to increased levels of outdoor air pollution is associated with psychological depression, six annual iterations of the Canadian Community Health Survey (n ≈ 127,050) were used to estimate the prevalence of a major depressive episode (2011-2014) or severity of depressive symptoms (2015-2016). Survey data were linked with outdoor air pollution data obtained from the Canadian Urban Environmental Health Research Consortium, with outdoor air pollution represented by fine particulate matter ≤2.5 micrometers (μm) in diameter (PM_2.5), ozone (O₃), sulfur dioxide (SO₂), and nitrogen dioxide (NO₂). Log-binomial models were used to estimate the association between outdoor air pollution and depression, and included adjustment for age, sex, marital status, income, education, employment status, urban versus rural households, cigarette smoking, and chronic illness. No evidence of associations for either depression outcomes were found. Given the generally low levels of outdoor air pollution in Canada, these findings should be generalized with caution. It is possible that a meaningful association with major depression may be observed in regions of the world where the levels of outdoor air pollution are greater, or during high pollution events over brief time intervals. Future research is needed to replicate these findings and to further investigate these associations in other regions and populations.

THE ENERGY–POLLUTION–HEALTH NEXUS: A PANEL DATA ANALYSIS OF LOW- AND MIDDLE-INCOME ASIAN COUNTRIES

Increased consumption of nonrenewable energy sources may lead to more air pollution, resulting in negative health impacts in a society. The main purpose of this study is to investigate the relationship between fossil fuel energy consumption and health issues using generalized method of moments estimation technique for data from 18 Asian countries (both low- and middle-income) over the period 1991–2018. The findings demonstrate that fossil fuel energy consumption increases the risk of lung and respiratory diseases. In addition, the results demonstrate the significant effect of CO2 emissions and fossil fuel consumption on undernourishment and death rates. Furthermore, we find that increases in the gross domestic product per capita and healthcare expenditure may help reduce undernourishment and death ratio. The conclusion recommends that diversification of energy in low- and middle-income countries from too much reliance on fossil fuels to more renewable energy sources can improve energy insecurity, at the same time reduce greenhouse gas emissions and minimize the negative impacts on human health.

Short- and long-term exposure to air pollution and lack of sunlight are associated with an increased risk of depression: A nested case-control study using meteorological data and national sample cohort data

Previous studies have suggested an increased risk of depression related to air pollutants. This study investigated the relationship of air pollutant exposure and meteorological factors with depression. The Korean National Health Insurance Service-Health Screening Cohort from 2002 to 2013 was analyzed. In total, 25,589 depression participants were 1:4 matched with 102,356 control participants for age, sex, income, and region of residence. Depression was defined based on a diagnosis (ICD-10: F31-33) by a psychiatric physician. Meteorological factors and air pollutants including sulfur dioxide (SO₂) (ppm), nitrogen dioxide (NO₂) (ppm), ozone (O₃) (ppm), carbon monoxide (CO) (ppm), and particulate matter with an aerodynamic diameter <10 μm (PM₁₀) (μg/m³) during the 30 days and 365 days before the index date were analyzed for associations with depression using conditional logistic regression. Subgroup analyses were performed according to age, sex, income, and region of residence. The odds ratios (ORs) for depression were 1.05 (95% CI = 1.02-1.08) at 365 days for 1 h less of sunshine. The ORs for depression were 1.02 (95% CI = 1.01-1.03) and 1.03 (95% CI = 1.00-1.05) at 30 days and 365 days for PM₁₀ (10 μg/m³), respectively. The ORs for depression were 1.18 (95% CI = 1.04-1.35) and 1.25 (95% CI = 1.07-1.47) at 30 days and 365 days for CO (ppm), respectively. In the subgroup analyses, the overall results were consistent. However, statistical significance diminished in the younger, high-income, and urban resident subgroups. Both short- and long-term exposure to PM₁₀ and CO and a reduced duration of sunshine were related to an increased risk of depression.

A framework for estimating the United States depression burden attributable to indoor fine particulate matter exposure

Recently published exploratory studies based on exposure to outdoor fine particulates, defined as particles with a nominal mean diameter less than or equal to 2.5 μm (PM_2.5) indicate that the pollutant may play a role in mental health conditions, such as major depressive disorder. This paper details a model that can estimate the United States (US) major depressive disorder burden attributable to indoor PM_2.5 exposure, locally modifiable through input parameter calibrations. By utilizing concentration values in an exposure-response function, along with relative risk values derived from epidemiological studies, the model estimated the prevalence of expected cases of major depressive disorder in multiple scenarios. Model results show that exposure to indoor PM_2.5 might contribute to 476,000 cases of major depressive disorder in the US (95% confidence interval 11,000-1,100,000), approximately 2.7% of the total number of cases reported annually. Increasing heating, ventilation, and air conditioning (HVAC) filter efficiency in a residential dwelling results in minor reductions in depressive disorders in rural or urban locations in the US. Nevertheless, a minimum efficiency reporting value (MERV) 13 filter does have a benefit/cost ratio at or near one when smoking occurs indoors; during wildfires; or in locations with elevated outdoor PM_2.5 concentrations. The approach undertaken herein could provide a transparent strategy for investment into the built environment to improve the mental health of the occupants.

Association between particulate matter air pollution and risk of depression and suicide: a systematic review and meta-analysis

An increasing number of studies examined the potential effects of ambient particulate matter (PM: PM2.5 and PM10-PMs with diameters not greater than 2.5 and 10 μm, respectively) pollution on the risk of depression and suicide; however, the results have been inconclusive. This study aimed to determine the overall relationship between PM exposure and depression/suicide based on current evidence. We conducted a systematic review and meta-analysis of current available studies. Thirty articles (20 for depression and 10 for suicide) with data from 1,447,313 participants were included in the meta-analysis. For a 10 μg/m3 increase in short-term exposure to PM2.5, we found a 2% (p < 0.001) increased the risk of depression and a 2% (p = 0.001) increased risk of suicide. A 10 μg/m3 increase in long-term exposure to PM2.5 was associated with a more apparent increase of 18% (p = 0.005) in depression risk. In addition, a 10 μg/m3 increase in short-term exposure to PM10 was associated with a 2% (p = 0.003) increase in depression risk and a 1% (p = 0.002) increase in suicide risk. Subgroup analyses showed that associations between PM and depression were more apparent in people over 65 years and from developed regions. Besides, the study design and study quality might also have an impact on their associations. The meta-analysis found that an increase in ambient PM concentration was strongly associated with an increased risk of depression and suicide, and the associations for depression appeared stronger for smaller particles (PM2.5) and at a long-term time pattern.

Air Pollution and Central Nervous System Disease: A Review of the Impact of Fine Particulate Matter on Neurological Disorders

Background: It is widely known that the harmful effects of fine dust can cause various diseases. Research on the correlation between fine dust and health has been mainly focused on lung and cardiovascular diseases. By contrast, the effects of air pollution on the central nervous system (CNS) are not broadly recognized.

Findings: Air pollution can cause diverse neurological disorders as the result of inflammation of the nervous system, oxidative stress, activation of microglial cells, protein condensation, and cerebral vascular-barrier disorders, but uncertainty remains concerning the biological mechanisms by which air pollution produces neurological disease. Neuronal cell damage caused by fine dust, especially in fetuses and infants, can cause permanent brain damage or lead to neurological disease in adulthood.

Conclusion: It is necessary to study the air pollution–CNS disease connection with particular care and commitment. Moreover, the epidemiological and experimental study of the association between exposure to air pollution and CNS damage is critical to public health and quality of life. Here, we summarize the correlations between fine dust exposure and neurological disorders reported so far and make suggestions on the direction future research should take.

Examining the relationship between ambient carbon monoxide, nitrogen dioxide, and mental health-related emergency department visits in California, USA

Growing evidence suggests air pollutants may harm the central nervous system, potentially impacting mental health. However, such impacts of air pollutants on mental health and the sub-populations most affected remain poorly understood, especially in California. We examined the relationship between short-term ambient carbon monoxide (CO), nitrogen dioxide (NO₂), and mental health-related emergency department (ED) visits in California from 2005 to 2013. Daily mean concentrations of the pollutants were acquired from the U.S. Environmental Protection Agency Air Quality System Data Mart ground monitoring data. Moving averages of pollutant concentrations were linked to counts of ED visits obtained from the California Office of Statewide Health Planning and Development. Seven mental health outcomes, defined by International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes, were studied: all mental disorders, bipolar disorder, depression, schizophrenia, substance abuse, homicide/inflicted injury, and suicide/self-harm. Monitor-level associations were estimated with quasi-Poisson regression models and combined using random-effects meta-analysis. CO and NO₂ were found to be positively associated with ED visits due to homicide/inflicted injury, with the warm season (May-October) driving the CO association. An interquartile range (IQR) (0.28 ppm) increase in two-day average CO during the warm season was associated with a 3.13% (95% confidence interval (CI): 1.43, 4.84) elevation in risk of an ED visit due to homicide/inflicted injury (n = 122,749 ED visits). An IQR (10.79 ppb) increase in two-day average NO₂ was associated with a 2.60% (95% CI: 1.17, 4.05) elevation in risk of an ED visit due to homicide/inflicted injury (n = 206,919 ED visits). Subgroup analyses indicated children, Hispanics, and males were particularly vulnerable. Except for an inverse relationship between NO₂ and substance abuse, neither pollutant was robustly associated with visits due to other mental health morbidities. Our results suggest short-term elevations in CO and NO₂ may promote violent behavior. Further investigation in other populations and ranges of air pollution exposure is warranted.

Short-term effects of air pollution on cause-specific mental disorders in three subtropical Chinese cities

BACKGROUND

The effects of ambient air pollution on specific mental disorders are rarely studied, and the reported results are inconsistent.

OBJECTIVE

To assess the short-term effect of ambient air pollution on the morbidity of mental disorders in three subtropical Chinese cities.

METHODS

Daily concentrations of air pollution were averaged from 19 fixed monitoring stations across each city, and data on patients were collected from three psychiatric specialty hospitals. A time-series study combined with a generalized additive Poisson model was conducted to investigate the association between air pollution and mental disorders. The exposure-response relationships were explored and stratified analyses by age and sex were conducted.

RESULTS

A total of 1,133,220 outpatient visits were recorded in three subtropical cities (Huizhou, Shenzhen, and Zhaoqing). The number of daily outpatient visits for mental disorders increased with higher air pollutant (PM_2.5, PM₁₀, SO₂ and NO₂) concentrations, and the effect of NO₂ appeared to be consistently significant across the three cities, with excess risk (ER) of 4.45% (95% CI: 2.90%, 6.04%) in Huizhou, 7.94% (95% CI: 6.28%, 9.62%) in Shenzhen, and 2.19% (95% CI: 0.51%, 3.89%) in Zhaoqing, respectively, at lag03. We also observed significant effect of PM_2.5 at lag0 (ER = 1.20%, 95% CI: 0.28%, 2.13%), PM₁₀ at lag0 (ER = 0.99%, 95% CI: 0.36%, 1.62%), and SO₂ at lag0 (ER = 10.74%, 95% CI: 3.20%, 18.84%) in Shenzhen. For specific mental disorders, significant associations were found in all the air pollutants except between SO₂ and affective disorder and between PM_2.5 and schizophrenia. In addition, we found that air pollution exhibited stronger effects for males and adults (≥18 years).

CONCLUSION

Acute exposure to air pollution, especially NO₂, might be an important trigger of mental disorders.

Air Pollutants and Daily Hospital Admissions for Psychiatric Care: A Review

OBJECTIVE

Air pollution is a major environmental risk to health. Ambient (outdoor) air pollution in both cities and rural areas was estimated to cause 4.2 million premature deaths worldwide in 2016. In this review, the authors sought to briefly summarize original research investigating the short-term effects of air pollution exposure on mental health.

METHODS

A systematic search of the electronic databases PubMed, Scopus, and Web of Science was conducted (from any time until March 4, 2019) to identify research studies reporting associations between daily levels of air pollutants and daily admissions to hospitals or emergency departments (EDs) for psychiatric disorders and symptoms. A final set of 19 articles was reviewed.

RESULTS

The results of all selected studies showed statistically significant associations between daily hospital admissions and ED visits for mental disorders and daily levels of some or all air pollutants considered, including particulate matter (PM) of variable sizes (in micrometers given in subscripts; PM_2.5 and PM₁₀), sulfur dioxide, carbon monoxide, nitrogen oxide, and ozone. The strongest and more consistent evidence across studies was found for PM_2.5 and PM_10.

CONCLUSIONS

The results summarized in this review extend the evidence that air pollution may contribute either to worsening of psychiatric symptoms or to the decision to seek treatment for a large group of mental diseases and conditions, including severe psychiatric disorders such as schizophrenia and depression.

Attributable risks associated with hospital outpatient visits for mental disorders due to air pollution: A multi-city study in China

AIM

To determine the associations between outdoor air pollution and hospital outpatient visits for mental disorders in China.

METHODS

We obtained data of 111,842 hospital outpatient visits for mental disorders from the largest hospitals of 13 cities, China, between January 01, 2013 and December 31, 2015. We collected air pollutant data including particulate matter ≤2.5 µm in diameter (PM_2.5), particulate matter ≤10 µm in diameter (PM₁₀), nitrogen dioxide (NO₂), ozone (O₃) and sulphur dioxide (SO₂) from China National Environmental Monitoring Centre during the same period. We conducted a time-stratified case-crossover design with conditional logistic regression models to determine the associations.

RESULTS

A 10 µg/m³ increase in PM_2.5, PM₁₀, NO₂ and SO₂ was associated with a significant increase in hospital outpatient visits for mental disorders on the current day. When stratified by age, sex and season, the effects of PM_2.5 and NO₂ were robust among different subgroups at lag05 days. PM₁₀ showed positive associations in males, in cold season, and in depression patients. SO₂ showed positive associations in males, in cold season, and in anxiety patients. O₃ showed positive associations in females, in warm season, and in depression patients. Nearly one sixth hospital outpatient visits for mental disorders can be attributable to NO₂.

CONCLUSIONS

Short-term increase in PM_2.5, PM₁₀, NO₂, SO₂ and O₃ concentrations was significantly associated with exacerbation of mental disorders in China as indicated by increases in hospital outpatient visits. NO₂ had more serious health threat than other pollutants in terms of mental disorders. Our findings strongly suggest a need for more strict emission control regulations to protect mental health from air pollution.

Association between ozone air pollution levels and hospitalizations for depression in Taipei: a time-stratified case-crossover study

Epidemiologic studies reported an association between exposure to ambient air pollutants and increased mortality rate attributed to suicide and suicide attempts. The investigation sought to determine whether there is an association between short-term ambient ozone (O₃) level exposure and daily hospital admissions for depression in Taipei from 2009 to 2013 using a time-stratified case-crossover design. In our single-pollutant model (with no adjustment for other pollutants), the % increase in daily hospital admissions for depression was 12% on warm days and 30% on cool days, per interquartile range (IQR) rise in O₃ levels, respectively. Ozone levels were significantly correlated with daily number of depression admissions both on warm and cool days. In our two-pollutant models, O₃ levels remained significant after adjusting for other air pollutants, including particulate matter (PM₁₀, PM_2.5), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and carbon monoxide (CO) both on warm and cool days. Although O₃ levels tended to be higher on warm days, admissions for depression were higher on cool days, suggesting that the relationship between O₃ concentrations and depression may be affected by temperature. Further study is needed to better understand these findings.

Health and economic impacts of particulate matter pollution on hospital admissions for mental disorders in Chengdu, Southwestern China

The evidence for adverse effects of ambient particulate matter (PM) pollution on mental disorders (MDs) is limited, especially in developing countries. This study aimed to quantify both PM related health impacts and corresponding economic loses for overall and specific MDs in southwestern China. Data regarding 134,292 hospital admissions for MDs were collected from local Compulsory Medical Insurance Database in 2013-2017. A generalized additive model (GAM) was applied to estimate the exposure-response effects of PM pollution on hospital admissions for MDs. And the cost of illness method (COI) was adopted to further assess corresponding hospitalization costs and productivity loses. It was showed that PM pollution was significantly related to hospital admissions for overall and specific MDs. Each 10 μg/m³ increase in concentrations of PM₁₀ (particles with an aerodynamic diameters ≤10 μm), PM_2.5 (≤ 2.5 μm) and PMc (2.5 μm < c < 10 μm) at the cumulative lag03 day would be responsible for 3.25% (95%CI: 2.34-4.16%), 6.38% (95%CI: 4.79-7.97%), and 3.81% (95%CI: 2.13-5.50%) increments in daily hospital admissions for MDs, respectively. Stronger associations were observed in males, cool season and people over 45 years. During the study period, PM pollution brought 1453.18 million Yuan economic losses for overall MDs, accounting for 0.026% of local GDP. This study suggested that short-term exposure to PM pollution, especially to PM_2.5, was associated with increased hospital admissions for MDs in southwestern China. In addition, potential benefits of lowering PM concentrations are considerable.

A Scoping Review of Non-Occupational Exposures to Environmental Pollutants and Adult Depression, Anxiety, and Suicide

PURPOSE OF REVIEW

Despite a call for better understanding of the role of environmental pollutant influences on mental health and the tremendous public health burden of mental health, this issue receives far less attention than many other effects of pollutants. Here we summarize the body of literature on non-occupational environmental pollutant exposures and adult depression, anxiety, and suicide-in PubMed, Embase, Web of Science, and PsychINFO through the end of year 2018.

RECENT FINDINGS

One hundred twelve articles met our criteria for further review. Of these, we found 88 articles on depression, 33 on anxiety, and 22 on suicide (31 articles covered multiple outcomes). The earliest article was published in 1976, and the most frequent exposure of interest was air pollution (n = 33), followed by secondhand smoke (n = 20), metals (n = 18), noise (n = 17), and pesticides (n = 10). Other exposures studied less frequently included radiation, magnetic fields, persistent organic pollutants (POPs), volatile organic compounds, solvents, and reactive sulfur compounds. The current literature, although limited, clearly suggests many kinds of environmental exposures may be risk factors for depression, anxiety, and suicide. For several pollutants, important limitations exist with many of the studies. Gaps in the body of research include a need for more longitudinal, life-course studies, studies that can measure cumulative exposures as well as shorter-term exposures, studies that reduce the possibility of reverse causation, and mechanistic studies focused on neurotoxic exposures.

Association Between Ambient Air Pollution and Daily Hospital Admissions for Depression in 75 Chinese Cities

OBJECTIVE

Although the association between ambient air pollution and risk of depression has been investigated in several epidemiological studies, the evidence is still lacking for hospital admissions for depression, which indicates a more severe form of depressive episode. The authors used national morbidity data to investigate the association between short-term exposure to ambient air pollution and daily hospital admissions for depression.

METHODS

Using data from the Chinese national medical insurance databases for urban populations, the authors conducted a two-stage time-series analysis to investigate the associations of short-term exposure to major ambient air pollutants-fine particles (PM_2.5), inhalable particles (PM₁₀), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), and carbon monoxide (CO)-and daily hospital admission risk for depression in 75 Chinese cities during the period 2013-2017.

RESULTS

The authors identified 111,620 hospital admissions for depression in 75 cities. In the single-pollutant models, the effect estimates of all included air pollutants, with the exception of O₃, were significant at several lags within 7 days. For example, 10 μg/m³ increases in PM_2.5, PM₁₀, and NO₂ at lag01 were associated with increases of 0.52% (95% CI=0.03, 1.01), 0.41% (95% CI=0.05, 0.78), and 1.78% (95% CI=0.73, 2.83), respectively, in daily hospital admissions for depression. Subgroup, sensitivity, and two-pollutant model analyses highlighted the robustness of the effect estimates for NO₂.

CONCLUSIONS

The study results suggest that short-term exposure to ambient air pollution is associated with an increased risk of daily hospital admission for depression in the general urban population in China, which may have important implications for improving mental wellness among the public.

Association between short-term exposure to ambient air pollution and hospital visits for depression in China

Depression is one of the leading causes of disability, but the etiology remains unclear. Recently, it has been suggested that air pollution is a potential risk factor for depression. However, the results remained inconsistent. So we conducted this study to assess the association between short-term exposure to ambient air pollution and hospital visits for depression in China. Daily hospital visits for depression from January 18, 2013 to June 10, 2018 were extracted from a regional health information system (HIS) covered 1.34 million population in Ningbo, China. We collected daily air pollutant concentrations and meteorological data from environmental air quality monitoring sites and meteorological stations in the study area. Quasi-Poisson regression models with generalized additive models (GAM) were applied to explore the associations between air pollution and hospital visits for depression. Stratified analyses were also conducted by gender, age, and season to examine the effects modification. The results disclosed that air pollutants including PM_2.5, PM₁₀, SO₂, CO, and NO₂ were positively correlated with hospital visits for depression. The strongest effects all occurred on lag0 (the same) day, and the corresponding excess risks (ERs) were 2.59 (95%CI: 0.72, 4.49) for PM_2.5, 3.08 (95%CI: 1.05, 5.16) for PM₁₀, 3.22 (95%CI: 1.16, 5.32) for SO₂, 4.38 (95%CI: 1.83, 6.99) for CO, and 4.94 (95%CI: 2.03, 7.92) for NO₂ per IQR increase, respectively. The associations were found to be stronger in the elderly (≥65 years) and cold season. Furthermore, the effects of CO and NO₂ remained significant in most two-pollutant models, suggesting that traffic-related air pollutants might be more important triggers of depression.

Air Pollution and Emergency Department Visits for Mental Disorders among Youth

Although exposure to ambient air pollution has been linked to mental health problems, little is known about its potential effects on youth. This study investigates the association between short-term exposure to air pollutants and emergency department (ED) visits for mental health disorders. The National Ambulatory Care Reporting System database was used to retrieve ED visits for young individuals aged 8–24 years in Toronto, Canada. Daily average concentrations of nitrogen dioxide (NO₂), fine particulate matter (PM_2.5), and daily maximum 8 h ozone (O₃) were calculated using measurement data from seven fixed stations. A case-crossover (CC) design was implemented to estimate the associations between ED visits and air pollution concentrations. Mental health ED visits were identified using International Classification of Diseases 10th Revision (ICD-10) codes, with seven categories considered. Models incorporating air pollutants and ambient temperature (with lags of 0–5 days) using a time-stratified CC technique were applied. Multivariable regression was performed by sex, three age groups, and seven types of mental health disorders to calculate relative risk (RR). The RRs were reported for one interquartile range (IQR) change in the air pollutant concentrations. Between April 2004 and December 2015 (4292 days), there were 83,985 ED visits for mental-health related problems in the target population. Several exposures to air pollutants were shown to have associations with ED visits for mental health including same day exposure to fine particulate matter (IQR = 6.03 μg/m³, RR = 1.01 (95% confidence interval: 1.00–1.02), RR = 1.02 (1.00–1.03)) for all and female-only patients, respectively. One-day lagged exposure was also associated with ED visits for PM_2.5 (RR = 1.02 (1.01–1.03)), for nitrogen dioxide (IQR = 9.1 ppb, RR = 1.02 (1.00–1.04)), and ozone (IQR = 16.0 ppb, RR = 1.06 (1.01–1.10)) for males. In this study, urban air pollution concentration—mainly fine particulate matter and nitrogen dioxide—is associated with an increased risk for ED visits for adolescents and young adults with diagnosed mental health disorders.

The longitudinal relationship between exposure to air pollution and depression in older adults

BACKGROUND

Air pollution, especially PM_2.5 (particulate matter with a diameter of below 2.5 μm), has been recognized as a key environmental factor that affects mental health, but few studies have focused on its influence on older adults, who are a vulnerable group.

OBJECTIVE

This study focused on the influence of PM_2.5 on health-related behaviors, such as physical activities and social contact, to assess their role as mediators of depression among older adults in China.

METHODS

We used data (N = 24 623) from the CHARLS (China Health and Retirement Longitudinal Study) of 2011-2015. CES-D 10 (Center for Epidemiology Studies of Depression scale) was used to measure depression. Using multilevel linear models, we examined the relationships between the variables, with different times nested within the same individual and individuals nested within the cities.

RESULTS

Before mediators were added, depression symptoms among older adults increased with annual concentration of PM_2.5 (Coeff = 0.57, SE = 0.11). However, after the mediators were added, the coefficient of the annual concentration of PM_2.5 decreased (Coeff = 0.37, SE = 0.10). While both physical activities (Sobel test Z score = 2.37, P value = .02) and social contact (Z score = 7.33, P value = .00) mediated the relationship between PM_2.5 and depression, the mediating effects decreased with increasing PM_2.5 .

CONCLUSIONS

Exposure to PM_2.5 , therefore, increases depressive symptoms in older Chinese adults by decreasing their physical activities and social contact. Also, the positive effects of physical activities and social contact on depression decreased with increasing PM_2.5 concentrations.

Ambient air pollution and depression: A systematic review with meta-analysis up to 2019

Although epidemiological studies have evaluated the associations of ambient air pollution with depression, the results remained mixed. To clarify the nature of the association, we performed a comprehensive systematic review and meta-analysis with the Inverse Variance Heterogeneity (IVhet) model to estimate the effect of ambient air pollution on depression. Three English and four Chinese databases were searched for epidemiologic studies investigating associations of ambient particulate (diameter ≤ 2.5 μm (PM_2.5), ≤10 μm (PM₁₀)) and gaseous (nitric oxide (NO), nitrogen dioxide (NO₂), carbon monoxide (CO), sulfur dioxide (SO₂) and ozone (O₃)) air pollutants with depression. Odds ratios (OR) and corresponding 95% confidence intervals (CI) were calculated to evaluate the strength of the associations. We identified 22 eligible studies from 10 countries of the world. Under the IVhet model, per 10 µg/m³ increase in long-term exposure to PM_2.5 (OR: 1.12, 95% CI: 0.97-1.29, I²: 51.6), PM₁₀ (OR: 1.04, 95% CI: 0.88-1.25, I²: 85.7), and NO₂ (OR: 1.05, 95% CI: 0.83-1.34, I²: 83.6), as well as short-term exposure to PM_2.5 (OR: 1.01, 95% CI: 0.99-1.04, I²: 51.6), PM₁₀ (OR: 1.01, 95% CI: 0.98-1.04, I²: 86.7), SO₂ (OR: 1.03, 95% CI: 0.99-1.07, I²: 71.2), and O₃ (OR: 1.01, 95% CI: 0.99-1.03, I²: 82.2) was not significantly associated with depression. However, we observed significant association between short-term NO₂ exposure (per 10 µg/m³ increase) and depression (OR: 1.02, 95% CI: 1.00-1.04, I²: 65.4). However, the heterogeneity was high for all of the pooled estimates, which reduced credibility of the cumulative evidence. Additionally, publication bias was detected for six of eight meta-estimates. In conclusion, short-term exposure to NO₂, but not other air pollutants, was significantly associated with depression. Given the limitations, a larger meta-analysis incorporating future well-designed longitudinal studies, and investigations into potential biologic mechanisms, will be necessary for a more definitive result.

Association Between Occupational Physicochemical Exposures and Headache/Eyestrain Symptoms Among Korean Indoor/Outdoor Construction Workers

Background

Headache/eyestrain symptoms are common health problems that people experience in daily life. Various studies have examined risk factors contributing to headache/eyestrains, and physicochemical exposure was found to be a leading risk factor in causing such symptoms. The purpose of this study was to examine the relationship of headache/eyestrain symptoms with physicochemical exposure among Korean construction workers depended on worksite.

Methods

This study used data from the 4th Korean Workers Conditions Survey and selected 1,945 Korean construction workers as participants. Multivariable logistic regression analysis was used to determine the relationship.

Results

Exposure to vibrations among all construction workers affected the moderate exposure group [odds ratio (OR) 1.53, 95% confidence interval (CI) 1.01–2.32], the high exposure group (OR 1.77 95%CI 1.17–2.67), and the indoor high exposure group (OR 1.61, 95%CI 1.02-2.55) and among outdoor construction workers, the moderate group (OR 6.61, 95%CI 15.4–28.48) and the high group (OR 6.61, 95%CI 1.56–27.98). When exposed to mist, dust, and fumes, the indoor high exposure group was significantly affected (OR 1.63, 95%CI 1.07–2.47). All construction workers exposed to organic solvents were affected, high exposure group (OR 1.69, 95%CI 1.15–2.49) and indoor high exposure group (OR 1.77, 95%CI 1.08–2.89). The high exposure group in all construction worker (OR 1.70, 95%CI 1.20–2.42) and the indoor high exposure group (OR 1.83, 95%CI 1.17–2.89) also were affected by secondhand smoking exposure.

Conclusion

Many physicochemical exposure factors affect headache/eyestrain symptoms among construction workers, especially indoor construction workers, suggesting a deficiency in occupational hygiene and health environments at indoor construction worksites.