Air Pollution and Emergency Department Visits for Mental Disorders among Youth

Ambient air pollution and the risk of violence in primary and secondary school settings: a cross-sectional study

BACKGROUND

Individual and social characteristics are attributed to violent behavior in schools, yet environmental hazards may play an understudied role. Ambient air pollution has been linked to neurological dysfunction that inhibits decision-making and may result in violent behavior in adult populations. However, little is known on how air pollution may be associated with violent behaviors in children.

METHODS

A cross-sectional ecologic study was designed to estimate the associations between air pollution (fine particulate matter, carbon monoxide, and nitrogen dioxide) with the occurrence of violent incidents and incidents involving a weapon among a cohort of children in Minnesota schools (2008-2012). Differences by urban and rural status of schools were also explored. Negative binomial regression models were developed to estimate incidence rate ratios (IRR) and incidence rate differences (IRD) to describe associations between air pollution and violent incidents in school settings.

RESULTS

Our results indicate that the highest levels of carbon monoxide, nitrogen dioxide and fine particulate matter concentrations were associated with increased violent disciplinary incidents. Among the total student population, the 4th quartile of carbon monoxide exposure was associated with an IRD of 775.62 (95% CI 543.2, 1008.05) violent incidents per 100,000 students per school year compared to schools in the lowest quartile of exposure. Comparing the 4th to the 1st quartiles of exposure, nitrogen dioxide and fine particulate matter had an IRD of 629.16 (95% CI 384.87, 873.46), and 510.49 (95% CI 274.92, 746.05) violent incidents per 100,000 students per school year respectively. Schools in urban settings shared a larger burden of violent incidents associated with air pollution compared to rural schools.

CONCLUSIONS

Modifying environmental pollutants surrounding school environments, particularly for high exposure communities, may be a novel tool for reducing violence and subsequent injuries in schools.

A stronger association of mental disorders with smaller particulate matter and a modifying effect of air temperature

Mental disorders (MDs) can be triggered by adverse weather conditions and particulate matter (PM) such as PM2.5 and PM10 (aerodynamic diameter ≤2.5 μm and ≤10 μm). However, there is a dearth of evidence on the role of smaller PM (e.g. PM1, aerodynamic diameter ≤1 μm) and the potential modifying effects of weather conditions. We aimed to collect daily data on emergency department visits and hospitalisations for schizophrenia-, mood-, and stress-related disorders in a densely populated Chinese city (Hefei) between 2016 and 2019. A time-stratified case-crossover analysis was used to examine the short-term association of MDs with PM1, PM2.5, and PM10. The potential modifying effects of air temperature conditions (cold and warm days) were also explored. The three size-fractioned PMs were all associated with an increased risk of MDs; however, the association differed between emergency department visit and hospitalisation. Specifically, PM1 was primarily associated with an increased risk of emergency department visit, whereas PM2.5 was primarily associated with an increased risk of hospitalisation, and PM10 was associated with an increased risk of both emergency department visit and hospitalisation. The PM-MD association appeared to be greatest (although not significant) for PM1 (odds ratio range: 1.014-1.055), followed by PM2.5 (odds ratio range: 1.001-1.009) and PM10 (odds ratio range: 1.001-1.006). Furthermore, the PM-MD association was observed on cold days; notably, the association between PM and schizophrenia-related disorders was significant on both cold and warm days. Our results suggest that the smaller the PM, the greater the risk of MDs, and that the PM-MD association could be determined by air temperature conditions.

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.

Environmental chemical exposures and mental health outcomes in children: a narrative review of recent literature

Background: Mental health is an important factor for children's overall wellbeing. National health statistics show that millions of children are diagnosed with mental health disorders every year, and evidence from studies on chemical pollutants like lead and bisphenols indicate that environmental exposures are linked to mental health illnesses in youth. However, the relationship between children's mental health and the environment is not well understood. This paper aims to review recent literature on prenatal and/or childhood environmental chemical exposures and mental health problems related to mood, anxiety, and behavior. This work also identifies areas of insufficient data and proposes suggestions to fill the data gaps. Methods: A narrative review was performed by searching Google Scholar and PubMed for literature published in the last 6 years (2017-2022), using search terms related to children, mental health, and environmental chemical exposure. Additional relevant studies were identified by screening the references in these papers. Results: A total of 29 studies are included in this review and results are summarized by chemical category: heavy metals, endocrine-disrupting chemicals, and pesticides. The majority of studies reported positive and significant associations between chemical exposures and child mental health outcomes including internalizing and externalizing behaviors. Conclusion: This review demonstrates that there is a growing body of literature that suggests developmental exposure to some environmental chemicals increases a child's risk of mood, anxiety, and behavior problems. Future research should expand on these findings to understand cumulative impacts, chemical mixtures, neurotoxic mechanisms, sex differences, and windows of vulnerability.

Premature mortality of people with severe mental illness: a renewed focus for a new era

This perspective article applies public health principles to improve the physical health of selected populations with mental disorders. Two preventable adverse outcomes, poorer physical health and premature mortality, are described across mental disorders. Evidence of the lifetime effects of adverse childhood experiences and inequalities is presented: these are the 'causes of the causes'. Seven drivers of physical disorders are illustrated that drive preventable deaths and as doctors, psychiatrists must lead from the front to reverse rising mortality. Evidence supports universal and selective interventions and even the most difficult challenges such as weight gain and opioid misuse are an opportunity for psychiatry to engage with individual patients and their organisations, public health colleagues, health systems and beyond. Interventions complement and do not replace existing clinical practices that reduce self-harm and prevent suicide. Mental health teams already do most of the work in this arena, and the case is made to refocus on physical health with task sharing. The top 10 recommendations within a personalised medicine framework are listed in this paper as a starting point.

Are there joint effects of different air pollutants and meteorological factors on mental disorders? A machine learning approach

Exposure to air pollutants is considered to be associated with mental disorders (MD). Few studies have addressed joint effect of multiple air pollutants and meteorological factors on admissions of MD. We examined the association between multiple air pollutants (PM_2.5, PM₁₀, O₃, SO₂, and NO₂), meteorological factors (temperature, precipitation, relative humidity, and sunshine time), and MD risk in Yancheng, China. Associations were estimated by a generalized linear regression model (GLM) adjusting for time trend, day of the week, and patients' average age. Empirical weights of environmental exposures were judged by a weighted quantile sum (WQS) model. A machine learning approach, Bayesian kernel machine regression (BKMR), was used to assess the overall effect of mixed exposures. We calculated excess risk (ER) and 95% confidence interval (CI) for each exposure. According to the effect of temperature on MD, we divided the exposure of all factors into different temperature groups. In the high temperature group, GLM found that for every 10 μg/m³ increase in O₃, PM_2.5 and PM₁₀ exposure, the ERs were 1.926 (95%CI 0.345, 3.531), 1.038 (95%CI 0.024, 2.062), and 0.780 (95% CI 0.052, 1.512) after adjusting for covariates. Temperature, relative humidity, and sunshine time also reported significant results. The WQS identified O₃ and temperature (above the threshold) had the highest weights among air pollutants and meteorological factors. BKMR found a significant positive association between mixed exposure and MD risks. In the low temperature group, only O₃ and temperature (below the threshold) showed significant results. These findings provide policymakers and practitioners with important scientific evidence for possible interventions. The association between different exposures and MD risk warrants further study.

Fine particle components and risk of psychiatric hospitalization in the U.S

BACKGROUND

There is a lack of evidence for the associations between atmospheric particle components exposure and psychiatric health. We aimed to identify the most toxic particle component(s) and source(s) related with psychiatric illness.

METHODS

Using Health Cost and Utilization Project (HCUP) State Inpatient Databases (SIDs), we analyzed the relative risk (RR) of psychiatric hospitalization associated with increased residential exposure to 14 particle components (Zn, V, Si, Pb, Ni, K, Fe, Cu, Ca, Br, sulfate (SO42-), nitrate (NO3-), organic carbon (OC), and elemental carbon (EC)). We covered the residents of eight U.S. states, who contributed to 5,012,041 psychiatric admissions over 2002-2018. Single component models were conducted via fitting zero-inflated negative binomial regression for each component with aggregated counts of total psychiatric hospitalizations per ZIP code per year as dependent variable. We used Nonnegative Matrix Factorization (NMF) to identify particle source factors and obtained the source-specific estimates. Generalized Weighted Quantile Sum (gWQS) Regression was applied to obtain an overall mixture effect. Separate but similar models were fitted for different age groups (<30 yrs. vs. ≥ 30 yrs) and psychiatric illness sub-categories to assess effect heterogeneity.

RESULTS

Sulfate, Fe, Pb and Zn were associated with the largest risk increases in single-component models. The biggest harmful associations were observed for metal industry source (high loadings of Pb and sulfate). For one quartile increase in components mixture score, we observed an adjusted RR of 1.24 (95 % CI, 1.21-1.26). Older population were more affected. We also observed higher increase in bipolar and psychotic admission risk for increased components source and mixture level.

CONCLUSION

Living in areas with higher levels of particle components was associated with increased risk of psychiatric hospitalization among the residents in eight U.S. states. Certain components (i.e. Pb, sulfate) and sources (metal industry) were the most related.

Fine particulate matter and daily hospitalizations for mental and behavioral disorders: A time-series study in Ho Chi Minh City, Vietnam

Various adverse health outcomes caused by particulate matter (PM) exposure has been documented, while the evidence for the adverse effects of PM exposure on mental and behavioral disorders (MBDs) is limited. To date, few epidemiological studies, especially in developing countries, have focused on these adverse effects. In the past decade, air pollution sources in Vietnam have noticeably increased, resulting to the elevated concentrations of ambient air pollutants particularly fine PM or PM with an aerodynamic diameter ≤2.5 μm (PM_2.5). Hence, investigating the short-term association between PM_2.5 and MBDs is worthwhile. In this study, a quasi-Poisson time-series regression analysis was used to investigate the association between PM_2.5 exposure and daily hospitalizations for MBDs to the Ho Chi Minh City Mental Health Hospital during 2017-2020. A natural cubic spline smooth function for time was used to screen out long-term and seasonality trends. Stratified analyses were also performed by sex, age, and season. During study period, 9,986 hospitalizations for MBDs were recorded and included in the analysis. Results suggested that a 10 μg/m³ daily increase in PM_2.5 concentration was associated with a statistically significant 2.96% (95% confidence interval: 0.23%-5.76%) increase in hospitalizations for MBDs. The effects of PM_2.5 exposure on hospital admissions were more pronounced in female patients and the middle-age group (35-59 years). This finding could increase awareness regarding prevention and minimization of MBDs on the public.

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.

Green space, air pollution, traffic noise and mental wellbeing throughout adolescence: Findings from the PIAMA study

BACKGROUND

Green space, air pollution and traffic noise exposure may be associated with mental health in adolescents. We assessed the associations of long-term exposure to residential green space, ambient air pollution and traffic noise with mental wellbeing from age 11 to 20 years.

METHODS

We included 3059 participants of the Dutch PIAMA birth cohort who completed the five-item Mental Health Inventory (MHI-5) at ages 11, 14, 17 and/or 20 years. We estimated exposure to green space (the average Normalized Difference Vegetation Index (NDVI) and percentages of green space in circular buffers of 300 m, 1000 m and 3000 m), ambient air pollution (particulate matter (PM₁₀ and PM_2.5), nitrogen dioxide, PM_2.5 absorbance and the oxidative potential of PM_2.5) and road traffic and railway noise (L_den) at the adolescents' home addresses at the times of completing the MHI-5. Associations with poor mental wellbeing (MHI-5 score ≤ 60) were assessed by generalized linear mixed models with a logit link, adjusting for covariates.

RESULTS

The odds of poor mental wellbeing at age 11 to 20 years decreased with increasing exposure to green space in a 3000 m buffer (adjusted odds ratio (OR) 0.78 [95% CI 0.68-0.88] per IQR increase in the average NDVI; adjusted OR 0.77 [95% CI 0.67-0.88] per IQR increase in the total percentage of green space). These associations persisted after adjustment for air pollution and road traffic noise. Relationships between mental wellbeing and green space in buffers of 300 m and 1000 m were less consistent. Higher air pollution exposure was associated with higher odds of poor mental wellbeing, but these associations were strongly attenuated after adjustment for green space in a buffer of 3000 m, traffic noise and degree of urbanization. Traffic noise was not related to mental wellbeing throughout adolescence.

CONCLUSIONS

Residential exposure to green space may be associated with a better mental wellbeing in adolescents.

The mental health of children and young people living in big cities in a revolving postpandemic world

PURPOSE OF REVIEW

The world's population is increasingly urban, with most children and young people growing up and living in cities. Evidence suggests that urbanicity is linked to an increased risk for the development of mental health disorders. Rather than an accumulation of risk factors, urbanization is a complex process that profoundly structures living conditions. In this sense, it is timely to discuss what are the social and structural determinants of mental health of children and young people in such settings.

RECENT FINDINGS

Three domains of determinants of mental health were selected for discussion: economics and living conditions, crime and violence, and urban layouts. For each, we debated realities faced by urban children and young people, providing an overview of recent evidence on implications for mental disorders and well being. We also discuss the potential impacts of the covid-19 pandemic on each domain, as well as recommendations for future action.

SUMMARY

Structural factors are of major relevance for the mental health of children and young people living in cities. The agenda of mental health promotion and prevention must include whole-of-society interventions aimed at improving living conditions, including economic and social capital, violence prevention and urbanistic planning.

Air pollution and increased number of psychiatric emergency room visits: A case-crossover study for identifying susceptible groups

BACKGROUND

Ambient particulate matter is a leading risk factor for disease globally. Particulate matter 10 (PM₁₀) and particulate matter 2.5 (PM_2.5) are derived from different sources, including operating motor vehicles as well as from industrial activities. In this study we investigate the association between increased concentrations of PM and total daily visits to the psychiatric emergency unit (PEV). Further, the aim is to identify specific risk groups who are more susceptible to the effects of air pollution exposure by studying sex, age, ongoing psychiatric follow-up and diagnoses of depression/anxiety or substance use.

MATERIAL AND METHODS

The sample was comprised of data from 2740 days to 81 548 PEVs at Sahlgrenska University Hospital in Gothenburg and daily mean concentrations of PM₁₀ and PM_2.5. A time-stratified case-crossover design was used to analyse associations between air pollution and PEVs.

RESULTS

Mean number of daily PEVs were 35 and sex distribution was even. PM exposure was associated with total PEV at lag 0 (the same day), by RR 1.016 (95% confidence interval [CI] 1.004-1.028) and RR 1.020 (95%CI 1.003-1.038) per 10 μg/m³ increase in PM₁₀ and PM_2.5, respectively. In females, PEV were increased at lag 0 and lag 1, and in males at lag 1 and lag 2. In the age-stratified analysis, PEVs significantly increased following PM exposure amongst individuals aged 35-65 years by lag 0-2 and in individuals who had contact with outpatient care at lag 0 to lag 1. There were no associations between air pollution and PEVs for any specific diagnostic group evaluated (amongst depression, anxiety and substance use disorder).

CONCLUSIONS

The results indicate that acute exposure to PM₁₀ and PM_2.5 may trigger acute worsening in mental health in both males and females, especially among 35-65 year old individuals. However, in subgroups of the most common psychiatric diagnoses, we did not observe statistically significant associations with PM exposure.

Air pollution and hospital admissions for critical illness in emergency department: a tertiary-center research in Changsha, China, 2016-2020

We aimed to comprehensively investigate the associations of air pollutants with hospital admissions for critical illness in ED. Patients with critical illness including level 1 and level 2 of the Emergency Severity Index admitted in ED of Changsha Central Hospital from January 2016 to December 2020 were enrolled. Meteorological and air pollutants data source were collected from the National Meteorological Science Data Center. A Poisson generalized linear regression combined with a polynomial distributed lag model (PDLM) was utilized to explore the effect of air pollution on hospital admissions for critical illness in ED. Benchmarks as references (25th) were conducted for comparisons with high levels of pollutant concentrations (75th). At first, lagged effects of all different air pollutants were analyzed. Then, based on the most significant factor, analyses in subgroups were performed by gender (male and female), age (< 45, 45-65, and > 65), disorders (cardiovascular, neurological, respiratory), and seasons (spring, summer, autumn, and winter). A total of 47,290 patients with critical illness admitted in ED were included. The effects of air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, O₃ and CO) on critical illness ED visits were statistically significant. Strong collinearity between PM_2.5 and PM₁₀ (r = 0.862) was found. Both single-day lag and cumulative-day lag day models showed that PM_2.5 had the strongest effects (lag 0, RR = 1.025, 95% CI 1.008-1.043, and lag 0-14, RR = 1.067, 95% CI 1.017-1.120, respectively). In both PM_2.5 and PM₁₀, the risks of critical illness in male, > 65 ages, respiratory diseases, and winter increased the most significant. Air pollutants, especially PM_2.5 and PM₁₀ exposure, could increase the risk of critical illness admission.

Gaseous air pollutants and hospitalizations for mental disorders in 17 Chinese cities: Association, morbidity burden and economic costs

The short-term morbidity effects of gaseous air pollutants on mental disorders (MDs), and the corresponding morbidity and economic burdens have not been well studied. We aimed to explore the associations of ambient sulfur dioxide (SO₂), nitrogen dioxide (NO₂), ozone (O₃) and carbon monoxide (CO) with MDs hospitalizations in 17 Chinese cities during 2015-2018, and estimate the attributable risk and economic costs of MDs hospitalizations associated with gaseous pollutants. City-specific relationships between gaseous pollutants and MDs hospitalizations were evaluated using over-dispersed generalized additive models, then combined to obtain the pooled effect. Concentration-response (C-R) curves of gaseous pollutants with MDs from each city were pooled to allow regional estimates to be derived. The morbidity and economic burdens of MDs hospitalizations attributable to gaseous pollutants were further assessed. A total of 171,939 MDs hospitalizations were included. We observed insignificant association of O₃ with MDs. An interquartile range increase in SO₂ at lag0 (9.1 μg/m³), NO₂ at lag0 (16.7 μg/m³) and CO at lag2 (0.4 mg/m³) corresponded to a 3.02% (95%CI: 0.72%, 5.38%), 5.03% (95%CI: 1.84%, 8.32%) and 2.18% (95%CI: 0.40%, 4.00%) increase in daily MDs hospitalizations, respectively. These effects were modified by sex, season and cause-specific MDs. The C-R curves of SO₂ and NO₂ with MDs indicated nonlinearity and the slops were steeper at lower concentrations. Overall, using current standards as reference concentrations, 0.27% (95%CI: 0.07%, 0.48%) and 0.06% (95%CI: 0.02%, 0.10%) of MDs hospitalizations could be attributable to extra SO₂ and NO₂ exposures, and the corresponding economic costs accounted for 0.34% (95%CI: 0.08%, 0.60%) and 0.07% (95%CI: 0.03%, 0.11%) of hospitalization expenses, respectively. Moreover, using threshold values detected from C-R curves as reference concentrations, the above mentioned morbidity and economic burdens increased a lot. These findings suggest more strict emission control regulations are needed to protect mental health from gaseous pollutants.

Cold Climate Impact on Air-Pollution-Related Health Outcomes: A Scoping Review

In cold temperatures, vehicles idle more, have high cold-start emissions including greenhouse gases, and have less effective exhaust filtration systems, which can cause up to ten-fold more harmful vehicular emissions. Only a few vehicle technologies have been tested for emissions below -7 °C (20 °F). Four-hundred-million people living in cities with sub-zero temperatures may be impacted. We conducted a scoping review to identify the existing knowledge about air-pollution-related health outcomes in a cold climate, and pinpoint any research gaps. Of 1019 papers identified, 76 were selected for review. The papers described short-term health impacts associated with air pollutants. However, most papers removed the possible direct effect of temperature on pollution and health by adjusting for temperature. Only eight papers formally explored the modifying effect of temperatures. Five studies identified how extreme cold and warm temperatures aggravated mortality/morbidity associated with ozone, particles, and carbon-monoxide. The other three found no health associations with tested pollutants and temperature. Additionally, in most papers, emissions could not be attributed solely to traffic. In conclusion, evidence on the relationship between cold temperatures, traffic-related pollution, and related health outcomes is lacking. Therefore, targeted research is required to guide vehicle regulations, assess extreme weather-related risks in the context of climate change, and inform public health interventions.

Air Pollution and Emergency Department Visits for Disease of the Genitourinary System

The aim of this study is to determine associations between ambient air pollution and the number of emergency department (ED) visits for diseases of the genitourinary tract in Toronto, Canada. We used the National Ambulatory Care Reporting System (NACRS) database to obtain the related ED visits and developed statistical models using daily data on ED visits, temperature, relative humidity, and outdoor air pollution concentration levels. The NACRS database contains data on hospital-based and community-based ambulatory care. The environmental data were retrieved from the National Air Pollution Surveillance (NAPS) program. The NAPS is the main source of ambient air quality data in Canada. We considered 2 air quality health indexes and 6 air pollutants: daily means of fine particulate matter PM_2.5, O₃, CO, NO₂, SO₂, and also maximum 8-hour average ozone. For every air pollutant, we fit 270 models (15 lags × 18 strata). We found that same-day air pollution concentrations have the highest number of statistically significantly positive associations with ED visits for genitourinary health outcomes. A total of 133 positive associations were identified over the 14 days lag. In subgroup (strata) analysis, females older than 60 years of age were found to have the most positive associations. In particular, nitrogen dioxide was found to be highly associated with ED visits for females over 60; an increase in NO₂ was associated with an increased relative risk (RR) of ED visits when lagged over 0, 1, and 2 days (RR = 1.040 [95% confidence interval: 1.028, 1.052], 1.020 [1.009, 1.032], and 1.025 [1.013, 1.036], respectively). The values of risks are reported for a 1 interquartile range increase in concentration (8.8 ppb). Our results suggest that urban ambient air pollution affect the number of ED visits due to genitourinary system conditions.

Ambient air pollution and emergency department visits in Toronto, Canada

To investigate the acute impact of various air pollutants on various disease groups in the urban area of the city of Toronto, Canada. Statistical models were developed to estimate the relative risk of an emergency department visit associated with ambient air pollution concentration levels. These models were generated for 8 air pollutants (lagged from 0 to 14 days) and for 18 strata (based on sex, age group, and season). Twelve disease groups extracted from the International Classification of Diseases 10th Revision (ICD-10) were used as health classifications in the models. The qualitative results were collected in matrices composed of 18 rows (strata) and 15 columns (lags) for each air pollutant and the 12 health classifications. The matrix cells were assigned a value of 1 if the association was positively statistically significant; otherwise, they were assigned to a value of 0. The constructed matrices were totalized separately for each air pollutant. The resulting matrices show qualitative associations for grouped diseases, air pollutants, and their corresponding lagged concentrations and indicate the frequency of statistically significant positive associations. The results are presented in colour-gradient matrices with the number of associations for every combination of patient strata, pollutant, and lag in corresponding cells. The highest number of the associations was 8 (of 12 possible) obtained for the same day exposure to carbon monoxide, nitrogen dioxide, and days with elevated air quality health index (AQHI) values. For carbon monoxide, the number of the associations decreases with the increasing lags. For this air pollutant, there were almost no associations after 8 days of lag. In the case of nitrogen dioxide, the associations persist even for longer lags. The numerical values obtained from the models are provided for every pollutant. The constructed matrices are a useful tool to analyze the impact of ambient air pollution concentrations on public health.

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.