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

Expose to volatile organic compounds is associated with increased risk of depression: A cross-sectional study

With increasing prevalence rate of depression by years, more attention has been paid to the influence of environmental pollutants on depression, but relationship between exposure to volatile organic compounds (VOCs) and depression is rarely studied. Therefore, this cross-sectional study use the National Center for Health Statistics (NHANES) database (2013-2016 years) to explore association between exposure to multiple VOCs and depression in general population. Multiple linear and logistic regression models were used to analyze the association between urinary VOC metabolism (mVOCs) and depression. To further analyze effect of multiple mVOCs mixed exposure, Bayesian kernel machine regression (BKMR) models were performed. A total of 3240 participants and 16 mVOCs were included in the analysis. Results showed that 10 mVOCs exposure were positively correlated with depression by multiple linear and logistic regression models, especially CYMA and MHBMA3, which also showed significant positive association with depression in BKMR model. Mixed exposure of multiple mVOCs was significantly positively correlated with depression. Gender differences were existed in effects of some VOCs concentrations on depression. AAMA, CYMA and MA had significant positive correlations with depression by women, and DHBMA had significant positive correlations with depression by men. Hence, this study showed that exposing to VOCs might have negative impacts on depression, and impact of CYMA and MHBMA3 on depression may be more evident, which provide new ideas for prevention and control of depression. But further research and exploration are needed to clarify the mechanism and influence factors of this relationship, to demonstrate the reliability of these relationship.

Short-Term Exposure to PM2.5 Chemical Components and Depression Outpatient Visits: A Case-Crossover Analysis in Three Chinese Cities

BACKGROUND

The association between specific chemical components of PM2.5 and depression remains largely unknown.

METHODS

We conducted a time-stratified case-crossover analysis with a distributed lag nonlinear model (DLNM) to evaluate the relationship of PM2.5 and its chemical components, including black carbon (BC), organic matter (OM), sulfate (SO42-), nitrate (NO3-), and ammonium (NH4+), with the depression incidence. Daily depression outpatients were enrolled from Huizhou, Shenzhen, and Zhaoqing.

RESULTS

Among 247,281 outpatients, we found the strongest cumulative effects of PM2.5 and its chemical components with the odd ratios (ORs) of 1.607 (95% CI: 1.321, 1.956) and 1.417 (95% CI: 1.245, 1.612) at the 50th percentile of PM2.5 and OM at lag 21, respectively. Furthermore, the ORs with SO42- and NH4+ at the 75th percentile on the same lag day were 1.418 (95% CI: 1.247, 1.613) and 1.025 (95% CI: 1.009, 1.140). Relatively stronger associations were observed among females and the elderly.

CONCLUSIONS

Our study suggests that PM2.5 and its chemical components might be important risk factors for depression. Reducing PM2.5 emissions, with a particular focus on the major sources of SO42- and OM, might potentially alleviate the burden of depression in South China.

Short-term exposure to ambient nitrogen dioxide and increased hospitalization burden for depression in China: a multicity analysis

Evidence for the increased hospitalization burden, including admissions, expenditures and length of hospital stay (LOS) for depression attributable to ambient nitrogen dioxide (NO2) is lacking. We investigated the associations between short-term exposure to ambient NO2 and attributable admissions, hospitalization expenditures and LOS for depression in 57 Chinese cities during 2013-2017 using a well-established two-stage time-series study approach. Short-term exposure to ambient NO2 was associated with significantly increased admissions, hospitalization expenditures and LOS for depression, and the attributable fractions were 6.87% (95% CI: 2.90%, 10.65%), 7.12% (3.01%, 11.04%) and 6.12% (2.59%, 9.50%) at lag02, respectively. The projected total attributable admissions, hospitalization expenditures and LOS for depression related to ambient NO2 at the national level were 23,335 (9,863, 36,181) admissions, 318.70 (134.43, 492.21) million CNY and 539.55 (227.99, 836.99) thousand days during the study period, respectively. Short-term exposure to ambient NO2 is associated with increased hospitalization burden for depression.

Air pollution associated with hospital visits for mental and behavioral disorders in Northeast China

Background

Related studies have found that air pollution is an important factor affecting mental and behavioral disorders. Thus, we performed this time-series study to evaluate the relationship between short-term exposure to ambient air pollutants and visits to hospital by patients with mental and behavioral disorders in northeastern China.

Methods

We used quasi-Poisson regression models and generalized additive models to probe the links between air pollution and mental and behavioral disorders. The possible influences were also explored stratified by season, age and gender.

Results

We found that sulfur dioxide (SO2) had a cumulative effect on mental and behavioral disorders at lag04-lag07 and had the greatest effect at lag07 [Relative risk (RR) = 1.068, 95%CI = 1.021-1.117]. Particulate matter of size 2.5 μm (PM2.5) and SO2 had a cumulative effect on depression and both had the largest effect at lag07 (RR = 1.021, 95%CI = 1.002-1.041; RR = 1.103, 95%CI = 1.032-1.178); SO2 also had a cumulative effect on anxiety disorders, with the largest effect at lag06 (RR = 1.058, 95%CI = 1.009-1.110). In the stratified analysis, people are more susceptible in the cold season compared to the warm season and females and the 18-60-year age group are more sensitive to air pollutants. It is suggested to strengthen management and preventive measures to decrease air pollution exposure.

Conclusion

This study found an association between increased concentrations of air pollutants and increased outpatient visits for mental and behavioral disorders. We recommend that preventive and protective measures should be strengthened in an effort to reduce exposure to air pollution in order to maintain physical and mental health.

Explainable Gated Recurrent Unit to explore the effect of co-exposure to multiple air pollutants and meteorological conditions on mental health outcomes

Mental health conditions have the potential to be worsened by air pollution or other climate-sensitive factors. Few studies have empirically examined those associations when we faced to co-exposures, as well as interaction effects. There would be an urgent need to use deep learning to handle complex co-exposures that might interact in multiple ways, and the model performance reinforced by SHapely Additive exPlanations (SHAP) enabled our predictions interpretable and hence actionable. Here, to evaluate the mixed effect of short-term co-exposure, we conducted a time-series analysis using approximately 1.47 million hospital outpatient visits of mental disorders (i.e., depressive disorder-DD, Schizophrenia-SP, Anxiety Disorder-AD, Bipolar Disorder-BD, Attention Deficit and Hyperactivity Disorder-ADHD, Autism Spectrum Disorder-ASD), with matched meteorological observations from 2015 through 2019 in Nanjing, China. The global insights of gated recurrent unit model revealed that most of input features with similar effect size caused the illness risk of SP and ASD increase, and most markedly, 73% of relative humidity, 44.6 µg/m³ of NO₂, and 14.1 µg/m³ of SO₂ at 5-year average level associated with 2.27, 1.14, and 1.29 visits increase for DD, SP, and AD, respectively. Both synergic and antagonistic effect among informative paired-features were distinguished from local feature dependence. Interestingly, variation tendencies of excessive visits of bipolar disorder when atmospheric pressure, PM_2.5, and O₃ interacted with one another were inconsistent. Our results provided added qualitative and quantitative support for the conclusion that short-term co-exposure to ambient air pollutants and meteorological conditions posed threats to human mental health.

Effects of ambient air pollution on outpatient visits for psoriasis in Wuhan, China: a time-series analysis

BACKGROUND

Psoriasis can be provoked by both external and internal factors. The effects of environmental factors on psoriasis remain unclear.

OBJECTIVES

To investigate the effects of air pollution on outpatient visits for psoriasis.

METHODS

A distributed lag nonlinear model following quasi-Poisson regression was used to evaluate the lag effects of air pollutants on psoriasis outpatient visits, adjusting for potential confounders. Stratified analyses were performed to identify potential effect modifications by sex, age and season.

RESULTS

In total, 13 536 outpatient visits for psoriasis were recorded in Wuhan, China from 1 January 2015 to 31 December 2019. In the single-pollutant model, exposures to particulate matter (PM) smaller than 2.5 μm (PM2.5), PM smaller than 10 μm (PM10), NO2 and SO2 were found to be significantly associated with increased daily psoriasis outpatient visits. For the largest effects, a 10-μg m-3 increase in concentrations of PM2.5 (lag1), PM10 (lag1), NO2 (lag0) and SO2 (lag3) corresponded to 0.32% [95% confidence interval (CI) 0.01-0.63], 0.26% (95% CI 0.05-0.48), 0.98% (95% CI 0.01-1.96) and 2.73% (95% CI 1.01-4.47) increases in psoriasis outpatient visits, respectively. In the two-pollutant model, only NO2 showed significant and stable effects on the outpatient visits for psoriasis.

CONCLUSIONS

Ambient air pollution, especially NO2, appears to be significantly associated with an increased risk of outpatient visits for psoriasis in Wuhan, China. Air pollution control and exposure prevention could be effective measures to relieve the symptoms of psoriasis among these patients.

Ambient air pollution exposure and depressive symptoms: Findings from the French CONSTANCES cohort

BACKGROUND AND AIM

Few studies have reported the association between air pollution exposure with different dimensions of depression. We aimed to explore this association across different dimensions of depressive symptoms in a large population.

METHODS

Data from the enrollment phase of the French CONSTANCES cohort (2012-2020) were analyzed cross-sectionally. Annual concentrations of particulate matter with a diameter < 2.5 µm (PM_2.5), black carbon (BC), and nitrogen dioxide (NO₂) from the land-use regression models were assigned to the residential addresses of participants. Total depressive symptoms and its four dimensions (depressed affect, disturbed interpersonal relations, low positive affect, somatic complaints) were measured using Centre of Epidemiologic Studies Depression questionnaire (CES-D). We reported results of negative binomial regression models (reported as Incidence Rate Ratio (IRR) and 95 % confidence interval (CI) for an interquartile range (IQR) increase in exposure), for each pollutant separately. Stratified analyses were performed by sex, income, family status, education, and neighborhood deprivation.

RESULTS

The study included 123,754 participants (mean age, 46.50 ± 13.61 years; 52.4 % women). The mean concentration of PM_2.5, BC and NO₂ were 17.14 µg/m³ (IQR = 4.89), 1.82 10^-5/m (IQR = 0.88) and 26.58 µg/m³ (IQR = 17.41) respectively. Exposures to PM_2.5, BC and NO₂ were significantly associated with a higher CES-D total (IRR = 1.022; 95 % CI = 1.002: 1.042, IRR = 1.027; 95 % CI = 1.013: 1.040, and IRR = 1.029; 95 % CI = 1.015: 1.042 respectively), and with depressed affect, and somatic complaints. For all pollutants, a higher estimate was observed for depressed affect. We found stronger adverse associations for men, lower-income participants, low and middle education groups, those living in highly deprived areas, and single participants.

CONCLUSION

Our finding could assist the exploration of the etiological pathway of air pollution on depression and also considering primary prevention strategies in the areas with air pollution.

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.

Air pollution in Delhi, India: It’s status and association with respiratory diseases

The policymakers need research studies indicating the role of different pollutants with morbidity for polluted cities to install a strategic air quality management system. This study critically assessed the air pollution of Delhi for 2016–18 to found out the role of air pollutants in respiratory morbidity under the ICD-10, J00-J99. The critical assessment of Delhi air pollution was done using various approaches. The mean PM_2.5 and PM₁₀ concentrations during the measurement period exceeded both national and international standards by a wide margin. Time series charts indicated the interdependence of PM_2.5 and PM₁₀ and connection with hospital visits due to respiratory diseases. Violin plots showed that daily respiratory disease hospital visits increased during the winter and autumn seasons. The winter season was the worst from the city’s air pollution point of view, as revealed by frequency analyses. The single and multi-pollutant GAM models indicated that short-term exposure to PM₁₀ and SO₂ led to increased hospital visits due to respiratory diseases. Per 10 units increase in concentrations of PM₁₀ brought the highest increase in hospital visits of 0.21% (RR: 1.00, 95% CI: 1.001, 1.002) at lag0-6 days. This study found the robust effect of SO₂ persisted in Delhi from lag0 to lag4 days and lag01 to lag06 days for single and cumulative lag day effects, respectively. While every 10 μg m^-3 increase of SO₂ concentrations on the same day (lag0) led to 32.59% (RR: 1.33, 95% CI: 1.09, 1.61) rise of hospital visits, the cumulative concentration of lag0-1 led to 37.21% (RR: 1.37, 95% CI:1.11, 1.70) rise in hospital visits which further increased to even 83.33% (RR: 1.83, 95% CI:1.35, 2.49) rise at a lag0-6 cumulative concentration in Delhi. The role of SO₂ in inducing respiratory diseases is worrying as India is now the largest anthropogenic SO₂ emitter in the world.

Urban air pollution and emergency department visits related to central nervous system diseases

Ambient air pollution has been associated with adverse neurological health outcomes. Ambient pollutants are thought to trigger oxidative stress and inflammation to which vulnerable populations, such as elderly may be particularly susceptible. Our study investigated the possible association between concentrations of ambient air pollutants and the number of emergency department (ED) visits for nervous system disorders among people residing in a large Canadian city. A time-stratified case-crossover study design combining data from the National Ambulatory Care Reporting System (NACRS) and the National Air Pollution Surveillance (NAPS) between 2004 and 2015 was used. Two air quality health indices were considered in additional to specific pollutants, including carbon monoxide (CO), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃) and fine particulate matter (PM_2.5). Weather condition data were included in the models. ED visits with a discharge diagnosis were identified using ICD-10 codes (G00-G99). The analysis was stratified by sex and age, also by seasons. The associations were investigated in arrays organized as 18 strata and 15 time lags (in days) for each pollutant. Overall, 140,511 ED visits were included for the analysis. Most ED visits were related to episodic and paroxysmal diagnoses (G40-G47, 64%), with a majority of visits for migraines (G43, 39%). Among females, an increase of 0.1ppm ambient CO was associated with an increased risk of paroxysmal diagnoses at day 1 (RR = 1.019 (95%CI 1.004–1.033)), day 6 (1.024 (1.010–1.039)) and day 7 (1.022 (1.007–1.036). PM_2.5 and SO₂, and air quality indices were similarly associated with ED visits for episodic and paroxysmal disorders in days 6 and 7. Findings highlight that ambient air pollution is associated with an increased number of ED visits for nervous system disorders, particularly visits for paroxysmal diagnoses.

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.

Attributable risk and economic cost of hospital admissions for depression due to short-exposure to ambient air pollution: A multi-city time-stratified case-crossover study

BACKGROUND

Depression has become the most common mental disease globally and is a strong predictor for suicide. Studies have indicated that exposure to high levels of air pollution increased the risk of depression, but evidence in human populations is still limited. At present, a few studies estimated the impact of multi-pollutants on hospitalization for depression in multi-city in areas with severe air pollution. We aimed to examine the association between short-term exposure to common ambient air pollutants and hospital admissions (HAs) for depression based on statistics of inpatients with depression in multi-city.

METHODS

The 10,459 records of HAs for depression from medical institutions in nine cities/prefectures, Sichuan Province, China, between January 1, 2017 and December 31, 2018 were collected. Air pollutant data including PM_2.5, PM₁₀, SO₂ and NO₂ from provincial ecological environment monitoring stations were obtained. Based on a time-stratified case-crossover design, we estimated the impact on relative risk (RR) of short-term exposure to air pollutants on hospitalization for depression, with stratification by sex, age, and economic level. The cost of illness method was used to further assess hospitalization costs.

RESULTS

The short-term exposure to air pollutants was positively associated with hospitalization for depression. The increase of air particulate matter (PM) had the strongest effect on lag 0 day (PM_2.5:1.037 (95% CI:1.022,1.052), PM₁₀:1.024 (95% CI:1.013,1.036)). The effects of SO₂ reached the peak on lag 2 day (1.317 (95% CI:1.151,1.507)). Women and older people were more likely to be affected by air pollutants and prone to depression (P = 0.013, P = 0.006). During the study period, the economic cost of hospitalization for depression caused by PM pollution was US$ 8.36 million.

LIMITATIONS

The air pollutant concentration level of the monitoring stations in the study area was regarded as personal pollutant exposure, which may not accurately reflect the patient's exposure level, resulting in a certain measurement error.

CONCLUSIONS

Short-term changes to ambient air pollution exposure may increase the risk of hospital admissions for depression and cause economic costs due to hospitalization.

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.

Fresh Air–Natural Microclimate Comfort Index: A New Tourism Climate Index Applied in Chinese Scenic Spots

Severe air pollution in China has caused significant tourism transformation for pursuing fresh air in microclimate tourism markets. Contemporary practices simply measure the air freshness of destinations and scenic spots using a single index, i.e., primarily negative oxygen ions (O2−). This index cannot comprehensively reveal scenic spots’ air freshness degree and determine the dynamic interactions between air freshness and scenic spots’ tourism development, thus inducing an illusion of air freshness for the target scenic spots. Meanwhile, the current fresh air index primarily ignores connections with the microclimate index of scenic spots and cannot provide a multidimensional index for scenic spots to take advantage of both air and microclimate resources for diverse tourism products and service production. Therefore, this study proposes a multidimensional index, the fresh air–natural microclimate comfort index (FAI-NMCI), connecting the fresh air index with the natural microclimate comfort index of scenic spots together from transdisciplinary and multidisciplinary perspectives. This study utilizes FAI-NMCI to measure four scenic spots of Fujian Province, and reveals in-depth results of scenic spots’ air freshness and natural microclimate comfort degree together. The results demonstrate that the four scenic spots in Fujian province of China had different levels of air freshness degree and natural microclimate comfort degree in 2018. The natural scenic spots were mostly distributed in Healing Fresh, Very Fresh, and Super Fresh levels of FAI with the most comfortable and comfortable levels of NMCI. The cultural scenic spots were mostly distributed in Relatively Fresh and Healing Fresh levels of FAI with the most comfortable and comfortable levels of NMCI. Meanwhile, the FAI-NMCI of natural and cultural scenic spots also had significant differences within 24 Jieqi, which will promote dynamic and creative utilization of those resources in microclimate tourism development.

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.

Long-term exposure to ambient air pollution and incidence of depression: A population-based cohort study in China

BACKGROUND

Long-term exposure to ambient air pollution was linked to depression incidence, although the results were limited and inconsistent.

OBJECTIVES

To investigate the effects of long-term air pollution exposure on depression risk prospectively in China.

METHODS

The present study used data from Yinzhou Cohort on adults without depression at baseline, and followed up until April 2020. Two-year moving average concentrations of particulate matter with a diameter ≤ 2.5 μm (PM_2.5), ≤10 μm (PM₁₀) and nitrogen dioxide (NO₂) were measured using land-use regression (LUR) models for each participant. Depression cases were ascertained using the Health Information System (HIS) of the local health administration by linking the unique identifiers. We conducted Cox regression models with time-varying exposures to estimate the hazard ratios (HRs) and 95% confidence intervals (95% CIs) of depression with each pollutant, after adjusting for a sequence of individual covariates as demographic characteristics, lifestyles, and comorbidity. Besides, physical activity, baseline potential depressive symptoms, cancer status, COVID-19 pandemic, different outcome definitions and air pollution exposure windows were considered in sensitivity analyses.

RESULTS

Among the 30,712 adults with a mean age of 62.22 ± 11.25, 1024 incident depression cases were identified over totaling 98,619 person-years of observation. Interquartile range increments of the air pollutants were associated with increased risks of depression, and the corresponding HRs were 1.59 (95%CI: 1.46, 1.72) for PM_2.5, 1.49 (95%CI: 1.35, 1.64) for PM₁₀ and 1.58 (95%CI: 1.42, 1.77) for NO₂. Subgroup analyses suggested that participants without taking any protective measures towards air pollution were more susceptible. The results remained robust in all sensitivity analyses.

CONCLUSIONS

Long-term exposure to ambient air pollution was identified as a risk factor for depression onset. Strategies to reduce air pollution are necessary to decrease the disease burden of depression.

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.

Acute Effects of Air Pollution on Ischemic Heart Disease Hospitalizations: A Population-Based Time-Series Study in Wuhan, China, 2017-2018

Evidence of the acute effects of air pollutants on ischemic heart disease (IHD) hospitalizations based on the entire population of a megacity in central China is lacking. All IHD hospitalization records from 2017 to 2018 were obtained from the Wuhan Information Center of Health and Family Planning. Daily air pollutant concentrations and meteorological data were synchronously collected from the Wuhan Environmental Protection Bureau. A time-series study using generalized additive models was conducted to systematically examine the associations between air pollutants and IHD hospitalizations. Stratified analyses by gender, age, season, hypertension, diabetes, and hyperlipidemia were performed. In total, 139,616 IHD hospitalizations were included. Short-term exposure to air pollutants was positively associated with IHD hospitalizations. The age group ≥76 was at higher exposure risk, and the associations appeared to be more evident in cold seasons. PM2.5 and PM10 appeared to have greater effects on males and those without hypertension or diabetes, whereas NO2 and SO2 had greater effects on females and those with hypertension or diabetes. The risk of IHD hospitalization due to air pollutants was greater in people without hyperlipidemia. Our study provides new evidence of the effects of air pollution on the increased incidence of IHD in central China.

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.

Acute associations between air pollution on premature rupture of membranes in Hefei, China

Numerous studies had focused on the association between air pollution and health outcomes in recent years. However, little evidence is available on associations between air pollutants and premature rupture of membranes (PROM). Therefore, we performed time-series analysis to evaluate the association between PROM and air pollution. The daily average concentrations of PM_2.5, SO₂ and NO₂ were 54.58 μg/m³, 13.06 μg/m³ and 46.09 μg/m³, respectively, and daily maximum 8-h average O₃ concentration was 95.67 μg/m³. The strongest effects of SO₂, NO₂ and O₃ were found in lag4, lag06 and lag09, and an increase of 10 μg/m³ in SO₂, NO₂ and O₃ was corresponding to increase in incidence of PROM of 8.74% (95% CI 2.12-15.79%), 3.09% (95% CI 0.64-5.59%) and 1.68% (95% CI 0.28-3.09%), respectively. There were no significant effects of PM_2.5 on PROM. Season-specific analyses found that the effects of PM_2.5, SO₂ and O₃ on PROM were more obvious in cold season, but the statistically significant effect of NO₂ was observed in warm season. We also found the modifying effects by maternal age on PROM, and we found that the effects of SO₂ and NO₂ on PROM were higher among younger mothers (< 35 years) than advanced age mothers (≥ 35 years); however, ≥ 35 years group were more vulnerable to O₃ than < 35 years group. This study indicates that air pollution exposure is an important risk factor for PROM and we wish this study could provide evidence to local government to take rigid approaches to control emissions of air pollutants.

Significance between air pollutants, meteorological factors, and COVID-19 infections: probable evidences in India

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease represents the causative agent with a potentially fatal risk which is having great global human health concern. Earlier studies suggested that air pollutants and meteorological factors were considered as the risk factors for acute respiratory infection, which carries harmful pathogens and affects the immunity. The study intended to explore the correlation between air pollutants, meteorological factors, and the daily reported infected cases caused by novel coronavirus in India. The daily positive infected cases, concentrations of air pollutants, and meteorological factors in 288 districts were collected from January 30, 2020, to April 23, 2020, in India. Spearman's correlation and generalized additive model (GAM) were applied to investigate the correlations of four air pollutants (PM2.5, PM10, NO2, and SO2) and eight meteorological factors (Temp, DTR, RH, AH, AP, RF, WS, and WD) with COVID-19-infected cases. The study indicated that a 10 μg/m3 increase during (Lag0-14) in PM2.5, PM10, and NO2 resulted in 2.21% (95%CI: 1.13 to 3.29), 2.67% (95% CI: 0.33 to 5.01), and 4.56 (95% CI: 2.22 to 6.90) increase in daily counts of Coronavirus Disease 2019 (COVID 19)-infected cases respectively. However, only 1 unit increase in meteorological factor levels in case of daily mean temperature and DTR during (Lag0-14) associated with 3.78% (95%CI: 1.81 to 5.75) and 1.82% (95% CI: -1.74 to 5.38) rise of COVID-19-infected cases respectively. In addition, SO2 and relative humidity were negatively associated with COVID-19-infected cases at Lag0-14 with decrease of 7.23% (95% CI: -10.99 to -3.47) and 1.11% (95% CI: -3.45 to 1.23) for SO2 and for relative humidity respectively. The study recommended that there are significant correlations between air pollutants and meteorological factors with COVID-19-infected cases, which substantially explain the effect of national lockdown and suggested positive implications for control and prevention of the spread of SARS-CoV-2 disease.

Association between short-term ambient air pollution and outpatient visits of anxiety: A hospital-based study in northwestern China

Anxiety, a common and devastating mental disorder, has raised widespread interests. The impacts of air pollution on physical health are well known, whereas few studies have explored the association of atmospheric pollution, especially short-term air pollution exposure, with the risk of anxiety disorders. In addition, there are increasing concerns in emerging evidence supporting a possible etiological link. Therefore, our aim was to evaluate the relationship between short-term exposure to atmospheric pollutants and anxiety outpatient visits in Xi'an, a city of northwestern China and a metropolis with relatively heavy air pollution. We collected the data of both daily outpatient visits and daily air pollution (SO₂, NO₂, and PM₁₀) between January 1, 2010 and January 31, 2016 (2222 days). To clarify the association between short-term ambient atmospheric pollution exposure and anxiety outpatient visits, an over-dispersed Poisson generalized additive model was applied by adjusting the day of the week and weather conditions (including temperature, humidity, sunlight hours, and rainfalls). Positive association between gaseous air pollutants (SO₂ and NO₂) and anxiety daily outpatient visits was observed. Moreover, the largest estimated values of both SO₂ and NO₂ were evidence at lag 03 (4-day moving average lag), with 10 μg/m³ increase corresponded to the increase of outpatient anxiety visits at 4.11% (95% CI: 2.15%, 6.06%) for SO₂ and 3.97% (95% CI: 1.90%, 6.06%) for NO₂. However, there was no differences in susceptibility to air pollutants between different genders as well as different ages. Taken together, short-term exposure to ambient air pollutants, especially gaseous air pollutants (NO₂ and SO₂), can be related to higher risk of anxiety outpatient visits.

Long-term exposure to ambient fine particulate matter originating from traffic and residential wood combustion and the prevalence of depression

Introduction

Air pollution has been suggested to be associated with depression. However, current evidence is conflicting, and no study has considered different sources of ambient particulate matter with an aerodynamic diameter below 2.5 µm (PM_2.5). We evaluated the associations of long-term exposure to PM_2.5 from road traffic and residential wood combustion with the prevalence of depression in the Helsinki region, Finland.

Methods

We conducted a cross-sectional analysis based on the Helsinki Capital Region Environmental Health Survey 2015–2016 (N=5895). Modelled long-term outdoor concentrations of PM_2.5 were evaluated using high-resolution emission and dispersion modelling on an urban scale and linked to the home addresses of study participants. The outcome was self-reported doctor-diagnosed or treated depression. We applied logistic regression and calculated the OR for 1 μg/m³ increase in PM_2.5, with 95% CI. Models were adjusted for potential confounders, including traffic noise and urban green space.

Results

Of the participants, 377 reported to have been diagnosed or treated for depression by a doctor. Long-term exposure to PM_2.5 from road traffic (OR=1.23, 95% CI 0.86 to 1.73; n=5895) or residential wood combustion (OR=0.78, 95% CI 0.43 to 1.41; n=5895) was not associated with the prevalence of depression. The estimates for PM_2.5 from road traffic were elevated, but statistically non-significant, for non-smokers (OR=1.38, 95% CI 0.94 to 2.01; n=4716).

Conclusions

We found no convincing evidence of an effect of long-term exposure to PM_2.5 from road traffic or residential wood combustion on depression.

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.

Chronic exposure to air pollution and risk of mental health disorders complicating pregnancy

BACKGROUND

Air pollution is associated with mental health in the general population, but its influence on maternal mental health during pregnancy has not been assessed.

OBJECTIVE

We evaluated the relationship between unspecified mental disorders complicating pregnancy and depression with average air pollution exposure during 3-months preconception, first trimester and whole pregnancy.

METHODS

Ambient air pollution was derived from a modified Community Multiscale Air Quality model and mental health diagnoses were based on electronic intrapartum medical records. Logistic regression models assessed the odds of unspecified mental disorder complicating pregnancy (n = 11,577) and depression (n = 9793) associated with an interquartile range increase in particulate matter (PM) less than 2.5 μm (PM_2.5), PM₁₀, carbon monoxide (CO), nitrogen dioxide (NO₂), nitrogen oxide (NO_x), sulfur dioxide (SO₂), and ozone (O₃). Pregnancies without mental health disorders were the reference group (n = 211,645). Models were adjusted for maternal characteristics and study site; analyses were repeated using cases with no additional mental health co-morbidity.

RESULTS

Whole pregnancy exposure to PM₁₀, PM_2.5, NO₂, and NO_x was associated with a 29%-74% increased odds of unspecified mental disorders complicating pregnancy while CO was associated with 31% decreased odds. Results were similar for depression: whole pregnancy exposure to PM₁₀, PM_2.5, NO₂, and NO_x was associated with 11%-21% increased odds and CO and O₃ were associated with 16%-20% decreased odds. SO₂ results were inconsistent, with increased odds for unspecified mental disorders complicating pregnancy and decreased odds for depression. While most findings were similar or stronger among cases with no co-morbidity, PM_2.5 and NO_x were associated with reduced risk and SO₂ with increased risk for depression only.

DISCUSSION

Whole pregnancy exposure to PM₁₀, PM_2.5, NO₂, and NO_x were associated with unspecified mental disorder complicating pregnancy and depression, but some results varied for depression only. These risks merit further investigation.

Ambient air pollution and hospital visits for peptic ulcer disease in China: A three-year analysis

BACKGROUND

Peptic ulcer disease (PUD) continued to be a source of significant morbidity and mortality worldwide. Recently, it has been reported that exposure to air pollution is a potential risk factor for PUD, but evidence on the association still remains inconsistent.

METHODS

We performed an ecological study to examine the association between short-term exposure to air pollution and daily hospital visits for PUD in Yinzhou, China from January 1st, 2017 to December 31st, 2019. Distributed lag nonlinear models were used to estimate the nonlinear and lag-response effects of air pollutants. Subgroup analyses stratified by sex, age and season were conducted to examine the effect modifications.

RESULTS

Overall, we found that short-term exposure to air pollution including SO₂, NO₂, CO, O₃ and PM_2.5 was significantly associated with hospital visits for PUD among all subjects. The lag-response effects of SO₂, NO₂ and O₃ varied at different concentrations and lag days. The cumulative risk ratios of CO and PM_2.5 showed nearly linear adverse effects and increased to maxima of 2.68 (95% CI: 1.49-4.78) and 2.40 (95% CI: 1.36-4.24) with their ranges from the references to the maximum concentrations, respectively. Moreover, the cumulative risks of particulate matters on hospital visits for PUD increased significantly in cold seasons, but not in warm seasons.

CONCLUSIONS

Our findings could provide growing evidence regarding the adverse health effects of air pollution on PUD, thereby strengthening the hypothesis that air pollutants have harmful impacts on digestive system.