Attributable risk and economic cost of hospital admissions for mental disorders due to PM2.5 in Beijing

Estimation of Attributable Risk and Direct Medical and Non-Medical Costs of Major Mental Disorders Associated With Air Pollution Exposures Among Children and Adolescents in the Republic of Korea, 2011-2019

BACKGROUND

Recent studies have reported the burden of attention deficit hyperactivity disorder [ADHD], autism spectrum disorder [ASD], and depressive disorder. Also, there is mounting evidence on the effects of environmental factors, such as ambient air pollution, on these disorders among children and adolescents. However, few studies have evaluated the burden of mental disorders attributable to air pollution exposure in children and adolescents.

METHODS

We estimated the risk ratios of major mental disorders (ADHD, ASD, and depressive disorder) associated with air pollutants among children and adolescents using time-series data (2011-2019) obtained from a nationwide air pollution monitoring network and healthcare utilization claims data in the Republic of Korea. Based on the estimated risk ratios, we determined the population attributable fraction (PAF) and calculated the medical costs of major mental disorders attributable to air pollution.

RESULTS

A total of 33,598 patients were diagnosed with major mental disorders during 9 years. The PAFs for all the major mental disorders were estimated at 6.9% (particulate matter < 10 μm [PM10]), 3.7% (PM2.5), and 2.2% (sulfur dioxide [SO2]). The PAF of PM10 was highest for depressive disorder (9.2%), followed by ASD (8.4%) and ADHD (5.2%). The direct medical costs of all major mental disorders attributable to PM10 and SO2 decreased during the study period.

CONCLUSION

This study assessed the burden of major mental disorders attributable to air pollution exposure in children and adolescents. We found that PM10, PM2.5, and SO2 attributed 7%, 4%, and 2% respectively, to the risk of major mental disorders among children and adolescents.

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.

Short-term effects of air pollutants on hospital admissions for asthma among older adults: a multi-city time series study in Southwest, China

Background

This study aimed to explore the relationship between air pollution and hospital admissions for asthma in older adults, and to further assess the health and economic burden of asthma admissions attributable to air pollution.

Methods

We collected information on asthma cases in people over 65 years of age from nine cities in Sichuan province, as well as air pollution and meteorological data. The relationship between short-term air pollutant exposure and daily asthma hospitalizations was analyzed using the generalized additive model (GAM), and stratified by gender, age, and season. In addition, we assessed the economic burden of hospitalization for air pollution-related asthma in older adults using the cost of disease approach.

Results

The single pollutant model showed that every 1 mg/m3 increase in CO was linked with an increase in daily hospitalizations for older adults with asthma, with relative risk values of 1.327 (95% CI: 1.116-1.577) at lag7. Each 10 μg/m3 increase in NO2, O3, PM10, PM2.5 and SO2, on asthma hospitalization, with relative risk values of 1.044 (95% CI: 1.011-1.078), 1.018 (95% CI: 1.002-1.034), 1.013 (95% CI: 1.004-1.022), 1.015 (95% CI: 1.003-1.028) and 1.13 (95% CI: 1.041-1.227), respectively. Stratified analysis shows that stronger associations between air pollution and asthma HAs among older adult in females, those aged 65-69 years, and in the warm season, although all of the differences between subgroups did not reach statistical significance. During the study period, the number of asthma hospitalizations attributable to PM2.5, PM10, and NO2 pollution was 764, 581 and 95, respectively, which resulted in a total economic cost of 6.222 million CNY, 4.73 million CNY and 0.776 million CNY, respectively.

Conclusion

This study suggests that short-term exposure to air pollutants is positively associated with an increase in numbers of asthma of people over 65 years of age in Sichuan province, and short-term exposure to excessive PM and NO2 brings health and economic burden to individuals and society.

Short-Term Ambient Air Pollution and Urticaria in Guangzhou, China: Estimating the Association and Population Attributable Fraction

Limited evidence is available regarding the association between acute exposure to ambient air pollutants and the risk of urticaria, even though the skin is an organ with direct contact with the external environment. This study utilized generalized additive models to investigate the association between particulate matter with an aerodynamic diameter smaller than 10 μm (PM10) and 2.5 μm (PM2.5), nitrogen dioxide (NO2) and sulfur dioxide (SO2), and daily outpatient visits for urticaria in Guangzhou, China from 2013 to 2017. We also estimated the attributable fraction of urticaria outpatient visits due to air pollution. A total of 216,648 outpatient visits due to urticaria occurred during the study period. All air pollutants were significantly associated with an increased excess risk of urticaria. Each 10 μg/m3 increase in PM2.5, PM10, NO2, and SO2 was associated with an increase of 1.23% (95% CI: 0.42%, 2.06%), 0.88% (95% CI: 0.28%, 1.49%), 3.09% (95% CI: 2.16%, 4.03%), and 2.82% (95% CI: 0.93%, 4.74%) in hospital visits for urticaria at lag05, respectively. It was estimated that 3.77% (95% CI: 1.26%, 6.38%), 1.91% (95% CI: 0.60%, 3.26%), 6.36% (95% CI: 4.38%, 8.41%), and 0.08% (95% CI: 0.03%, 0.14%) of urticaria outpatient visits were attributable to PM2.5, PM10, NO2, and SO2 using the World Health Organization's air quality guideline as the reference. Relatively stronger associations were observed during the cold season. This study indicates that short-term air pollution may play a significant role in outpatient visits for urticaria, and that such relationships could be modified by season.

Ecological correlation between short term exposure to particulate matter and hospitalization for mental disorders in Shijiazhuang, China

The associations between particulate matter (PM) and overall and specific mental disorders (MDs) are investigated using data from two general hospitals in Shijiazhuang, China, from January 2014 to December 2019. A longitudinal time series study, as one type of ecological study, is conducted using a generalized additive model to examine the relationship between short-term exposure to PM2.5, PM10, and daily hospital admissions for MDs, and further stratification by subtypes, age, and gender. A total of 10,709 cases of hospital admissions for MDs have been identified. The significant short-time effects of PM2.5 on overall MDs at lag01 and PM10 at lag05 are observed, respectively. For specific mental disorders, there are substantial associations of PM pollution with mood disorders and organic mental disorders. PM2.5 has the greatest cumulative effect on daily admissions of mood disorders and organic mental disorders in lag01, and PM 10 has the greatest cumulative effect in lag05. Moreover, the effect modification by sex or age is statistically significant, with males and the elderly (≥ 45 years) having a stronger effect. Short-term exposure to PM2.5 and PM10can be associated with an increased risk of daily hospital admissions for MDs.

Comparative Filtration Performance of Composite Air Filter Materials Synthesized Using Different Impregnated Porous Media

Indoor environment quality is currently a hot research topic. In this study, composite air filter materials were synthesized using different impregnated porous medium materials, and their filtration performance and structural parameters were analyzed. The results showed that composite filter materials' structures changed at the fibers' surfaces when synthesized using different porous medium material layers. The filtration efficiency of composite filter materials synthesized using different porous media reached a maximum 0.8 m/s filtration velocity, and PM₁₀, PM_2.5, and PM_1.0 increased by 1.67~26.07, 1.19~26.96, and 1.10~21.98%, respectively. The filtration efficiencies of reduced graphene oxide composite for PM₁₀, PM_2.5, and PM_1.0 were 21.26, 20.22, and 18.50% higher, respectively, than those of carbon black composite. In addition, the filtration efficiency of the composite material synthesized by reducing graphene oxide improved for 0 to 1.0 μm particulates and was more effective by comparison. Filtration efficiency and resistance were comprehensively considered during air filter use to provide useful values for the selection and preparation of composite filter materials in the future.

Experimental Study of the Factors Influencing the Regeneration Performance of Reduced Graphite Oxide Filter Materials under Water Cleaning

With the normalization of epidemic prevention and control, air filters are being used and replaced more frequently. How to efficiently utilize air filter materials and determining whether they have regenerative properties have become current research hotspots. This paper discusses the regeneration performance of reduced graphite oxide filter materials, which were studied in depth using water cleaning and the relevant parameters, including the cleaning times. The results showed that water cleaning was most effective using a 20 L/(s·m²) water flow velocity with a 17 s cleaning time. The filtration efficiency decreased as the number of cleanings increased. Compared to the blank group, the filter material's PM₁₀ filtration efficiency decreased by 0.8%, 19.4%, 26.5%, and 32.4% after the first to fourth cleanings, respectively. The filter material's PM_2.5 filtration efficiency increased by 12.5% after the first cleaning, and decreased by 12.9%, 17.6%, and 30.2% after the second to fourth cleanings, respectively. The filter material's PM_1.0 filtration efficiency increased by 22.7% after the first cleaning, and decreased by 8.1%, 13.8%, and 24.5% after the second to fourth cleanings, respectively. Water cleaning mainly affected the filtration efficiency of particulates sized 0.3-2.5 μm. Reduced graphite oxide air filter materials could be water washed twice and maintain cleanliness equal to 90% of the original filter material. Water washing more than twice could not achieve the standard cleanliness equal to 85% of the original filter material. These data provide useful reference values for the evaluation of the filter materials' regeneration performance.

Access to sustainable healthcare infrastructure: a review of industrial emissions, coal fires, and particulate matter

Environmental health is critical for the economy's social welfare and environmental sustainability. Using time series data from 1975 to 2020, the research examines the short- and long-run relationship between environmental pollutants and healthcare costs in the context of Pakistan. The study's results reveal that short-term and long-term efforts towards cleaner development in terms of carbon emissions, coal combustion, nitrous oxide (N₂O) emissions, and industrial value-added have resulted in significant reductions in healthcare expenses due to improved management of industrial emissions. However, in the long run, particulate matter (PM_2.5) has a detrimental effect on a country's sustainable healthcare agenda, leading to increased healthcare costs. Furthermore, the increased use of coal-fired power plants that release polycyclic aromatic hydrocarbons (PAH) and revenue generated by contaminated production lead to higher out-of-pocket healthcare costs, increasing a country's risk of morbidity and mortality. The study's Granger causality estimations demonstrate that carbon emissions are responsible for emissions-driven healthcare expenses in a nation. Additionally, economic growth leads to increased carbon emissions and industrial toxins, which are also emission-led. Through variance decomposition analysis (VDA), the study finds that carbon emissions have the highest variance shock of 32.702% on healthcare expenditures in the next ten years. This is followed by polluted income and continued economic growth, which have a variance shock of 13.243% and 8.858%, respectively, over the same period. The findings indicate that the maximum healthcare benefits may be acquired by mitigating environmental pollutants via stringent environmental regulations, reducing industrial toxins through solid waste management techniques, and minimizing coal combustion reliance through renewable fuels. Environmental research is still required to provide more sustainable solutions to the sustainability of the global healthcare agenda.

Modifying the Fiber Structure and Filtration Performance of Polyester Materials Based on Two Different Preparation Methods

How to build a satisfactory indoor environment has become increasingly important. In this paper, the synthesis and improvement of the most widely used polyester materials in China were carried out based on two different preparation methods, and the structures and filtration performances were tested and analyzed. The results showed that a carbon black coating was wrapped on the surfaces of the new synthetic polyester filter fibers. Compared with the original materials, the filtration efficiencies of PM₁₀, PM_2.5, and PM₁ were increased by 0.88-6.26, 1.68-8.78, and 0.42-4.84%, respectively. The best filtration velocity was 1.1 m/s, and the new synthetic polyester materials with direct impregnation demonstrated superior filtration performance. The filtration efficiency of the new synthetic polyester materials was improved on the particulates with sizes of 1.0-5.0 μm. The filtration performance of G4 was better than that of G3. The filtration efficiencies of PM₁₀, PM_2.5, and PM₁ were improved by 4.89, 4.20, and 11.69%, respectively. The quality factor value can be used to assess the comprehensive filtration performance of air filters in practical applications. It could provide reference values for the selection of synthetic methods of new filter materials.

Attributable risk and economic burden of pneumonia among older adults admitted to hospital due to short-term exposure to airborne particulate matter: a time-stratified case-crossover study from China

Many studies have proven the relationship between air pollutants and respiratory diseases, but few studies have assessed the impacts of air particulate matter exposure on older patients with pneumonia. This study aimed to reveal the impacts of short-term exposure to air particulate matter on the daily number of older adult patients hospitalized due to pneumonia and calculate the economic costs attributable to this exposure. We collected inpatient data from 9 city hospitals in Sichuan Province, China, from January 1, 2018, to December 31, 2019, and calculated odds ratios and 95% confidence intervals using a time-stratified case-crossover study design and an attributable risk model to calculate the economic burden due to particulate matter pollution. It was found that for every 10 μg/m³ increase in PM_2.5 and PM₁₀ concentrations, the daily number of older adult pneumonia inpatients increased by 1.5% (95% CI: 1.010-1.021) and 1.0% (95% CI: 1.006-1.014), respectively. Those 65 ~ 79 years old were more susceptible to air particulate pollutants (P < 0.05). During the study period, the total hospitalization costs and out-of-pocket expenses attributable to PM_2.5 and PM₁₀ exposure were 44.60 million CNY (6.22%) and 16.03 million CNY (6.21%), respectively, with PM_2.5 being the primary influencing factor. This study revealed the relationship between particulate matter pollution and pneumonia among older adults. The role of policies to limit particulate matter concentrations in reducing disease burden among older adults can be further explored.

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.

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.

Short-Term Exposure to Wildfire Smoke and PM2.5 and Cognitive Performance in a Brain-Training Game: A Longitudinal Study of U.S. Adults

BACKGROUND

There is increasing evidence that long-term exposure to fine particulate matter [PM ≤2.5μm in aerodynamic diameter (PM2.5)] may adversely impact cognitive performance. Wildfire smoke is one of the biggest sources of PM2.5 and concentrations are likely to increase under climate change. However, little is known about how short-term exposure impacts cognitive function.

OBJECTIVES

We aimed to evaluate the associations between daily and subdaily (hourly) PM2.5 and wildfire smoke exposure and cognitive performance in adults.

METHODS

Scores from 20 plays of an attention-oriented brain-training game were obtained for 10,228 adults in the United States (U.S.). We estimated daily and hourly PM2.5 exposure through a data fusion of observations from multiple monitoring networks. Daily smoke exposure in the western U.S. was obtained from satellite-derived estimates of smoke plume density. We used a longitudinal repeated measures design with linear mixed effects models to test for associations between short-term exposure and attention score. Results were also stratified by age, gender, user behavior, and region.

RESULTS

Daily and subdaily PM2.5 were negatively associated with attention score. A 10 μg/m3 increase in PM2.5 in the 3 h prior to gameplay was associated with a 21.0 [95% confidence interval (CI): 3.3, 38.7]-point decrease in score. PM2.5 exposure over 20 plays accounted for an estimated average 3.7% (95% CI: 0.7%, 6.7%) reduction in final score. Associations were more pronounced in the wildfire-impacted western U.S. Medium and heavy smoke density were also negatively associated with score. Heavy smoke density the day prior to gameplay was associated with a 117.0 (95% CI: 1.7, 232.3)-point decrease in score relative to no smoke. Although differences between subgroups were not statistically significant, associations were most pronounced for younger (18-29 y), older (≥70y), habitual, and male users.

DISCUSSION

Our results indicate that PM2.5 and wildfire smoke were associated with reduced attention in adults within hours and days of exposure, but further research is needed to elucidate these relationships. https://doi.org/10.1289/EHP10498.

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.

Short-term effects of air pollutants on hospital admissions for acute bronchitis in children: a multi-city time-series study in Southwest China

BACKGROUND

Few studies have investigated the effects of air pollutants on children with acute bronchitis. This study aimed to explore the acute effects of four air pollutants [fine particulate matter (PM_2.5), inhalable particulate matter (PM₁₀), sulfur dioxide (SO₂), and nitrogen dioxide (NO₂)] on the daily number of children admitted to the hospital for acute bronchitis in Sichuan Province, China.

METHODS

The 49,975 records of hospitalized children with acute bronchitis from medical institutions in nine cities/prefectures, Sichuan Province, China, as well as the simultaneous meteorological data and air pollution data from 183 monitoring sites, were collected from 1 January 2017 to 31 December 2018. A generalized additive model was adopted to analyze the exposure-response and lag effects of hospitalizations of children with acute bronchitis to air pollutants. Stratified analyses were conducted based on sex, age, and season.

RESULTS

The single-pollutant model showed that a 10 µg/m³ increase at lag07 of PM_2.5, PM₁₀, SO₂, and NO₂ corresponded to an increase of 1.23% [95% confidence interval (CI) 0.21-2.26%], 1.33% (95% CI 0.62-2.05%), 23.52% (95% CI 11.52-36.81%), and 12.47% (95% CI 8.46-16.64%) in daily hospitalizations for children with acute bronchitis, respectively. Children aged 0-2 were more prone to PM_2.5 (P < 0.05). Interestingly, the effects were stronger in the warm season than in transition seasons and the cool season for PM_2.5 and PM₁₀ (P < 0.05).

CONCLUSION

The higher daily average concentrations of four pollutants in Sichuan Province can result in an increased number of children hospitalized for acute bronchitis.

Impact of Particulate Matter on Hospitalizations for Respiratory Diseases and Related Economic Losses in Wuhan, China

Background

Prior studies have reported the effects of particulate matter (PM) on respiratory disease (RD) hospitalizations, but few have quantified PM-related economic loss in the central region of China. This investigation aimed to assess the impacts of PM pollution on the risk burden and economic loss of patients admitted with RD.

Methods

Daily cases of RD admitted to the hospital from 1 January 2015 to 31 December 2020 were collected from two class-A tertiary hospitals in Wuhan, China. Time series analysis incorporated with a generalized additive model (GAM) was adopted to assess the impacts of fine particulate matter (PM_2.5) and inhalable particulate matter (PM₁₀) exposures on patients hospitalized with RD. Stratified analyses were performed to investigate underlying effect modification of RD risk by sex, age, and season. The cost of illness (COI) approach was applied to evaluate the related economic losses caused by PM.

Results

A total of 51,676 inpatients with a primary diagnosis of RD were included for the analysis. PM_2.5 and PM₁₀ exposures were associated with increased risks of hospitalizations for RD. Subgroup analysis demonstrated that men and children in the 0–14 years age group were more vulnerable to PM, and the adverse effects were promoted by low temperature in the cold season. A 152.4 million China Yuan (CNY) economic loss could be avoided if concentrations of PM_2.5 and PM₁₀ declined to 10 and 20 μg/m³, respectively.

Conclusions

PM_2.5 and PM₁₀ concentrations were positively associated with RD hospitalization. Men and children were more vulnerable to PM. Effective air pollution control measures can reduce hospitalizations significantly and save economic loss substantially.

Associations of PM2.5 and road traffic noise with mental health: Evidence from UK Biobank

BACKGROUND

The associations of atmospheric particulate matter with diameters of 2.5 μm or less (PM2.5) and road traffic noise with mental disorders in men and women are not well studied.

OBJECTIVES

We aim to examine the cross-sectional associations of PM2.5 and road traffic noise with mental disorders in men and women.

METHODS

The baseline data of the UK Biobank study (2006-2010) were used. Mental disorders including symptoms of nerves, anxiety, tension or depression (NATD), major depression, and bipolar disorder were assessed by validated questions. Verified models were used to estimate PM2.5 and road traffic noise.

RESULTS

A total of 334,986 participants with measurements of NATD and 90,706 participants with measurements of major depression and bipolar disorder were included in the analysis. After adjusting for covariates, the odds for the risk of NATD symptoms increased by 2.31 (95% CI: 2.15-2.50) times per 10 μg/m³ increase in PM2.5. The odds for the risk of major depression and bipolar disorder increased by 2.26 and 4.99 times per 10 μg/m³ increase in PM2.5. On the other hand, higher road traffic noise exposure was significantly associated with a higher risk of NATD symptoms (Decile 6-8 (54.9-57.8 dB), OR: 1.03, 95% CI: 1.01-1.06; Decile 9-10 (≥57.8 dB), OR: 1.04, 95% CI: 1.01-1.07) and bipolar disorder (Decile 2-5 (52.1-54.9 dB), OR: 1.26, 95% CI: 1.00-1.59; Decile 6-8 (54.9-57.8 dB), OR: 1.30, 95% CI: 1.02-1.65; Decile 9-10 (≥57.8 dB), OR: 1.54, 95% CI: 1.21-1.97). Interestingly, a negative association was observed between moderate road traffic noise and major depression (Decile 2-5 (52.1-54.9 dB), OR: 0.95, 95% CI: 0.90-1.00). Interactions between PM2.5 exposure with age, gender, and sleeplessness for NATD symptoms were observed (P < 0.05), while interactions between road traffic noise exposure with age and gender were observed (P < 0.05).

CONCLUSIONS

We found a positive association between PM2.5 and mental disorders. Meanwhile, we found a positive association of road traffic noise with NATD symptoms and bipolar disorder and a negative association of moderate road traffic noise with major depression. Also, the effect modifications of these associations by age, gender, or sleeplessness may exist.

Association between temperature and COVID-19 transmission in 153 countries

The WHO characterized coronavirus disease 2019 (COVID-19) as a global pandemic. The influence of temperature on COVID-19 remains unclear. The objective of this study was to investigate the correlation between temperature and daily newly confirmed COVID-19 cases by different climate regions and temperature levels worldwide. Daily data on average temperature (AT), maximum temperature (MAXT), minimum temperature (MINT), and new COVID-19 cases were collected from 153 countries and 31 provinces of mainland China. We used the spline function method to preliminarily explore the relationship between R₀ and temperature. The generalized additive model (GAM) was used to analyze the association between temperature and daily new cases of COVID-19, and a random effects meta-analysis was conducted to calculate the pooled results in different regions in the second stage. Our findings revealed that temperature was positively related to daily new cases at low temperature but negatively related to daily new cases at high temperature. When the temperature was below the smoothing plot peak, in the temperate zone or at a low temperature level (e.g., <25th percentiles), the RRs were 1.09 (95% CI: 1.04, 1.15), 1.10 (95% CI: 1.05, 1.15), and 1.14 (95% CI: 1.06, 1.23) associated with a 1°C increase in AT, respectively. Whereas temperature was above the smoothing plot peak, in a tropical zone or at a high temperature level (e.g., >75th percentiles), the RRs were 0.79 (95% CI: 0.68, 0.93), 0.60 (95% CI: 0.43, 0.83), and 0.48 (95% CI: 0.28, 0.81) associated with a 1°C increase in AT, respectively. The results were confirmed to be similar regarding MINT, MAXT, and sensitivity analysis. These findings provide preliminary evidence for the prevention and control of COVID-19 in different regions and temperature levels.

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.

The short-term effects and burden of particle air pollution on hospitalization for coronary heart disease: a time-stratified case-crossover study in Sichuan, China

BACKGROUND

Coronary heart disease (CHD), the leading cause of death globally, might be developed or exacerbated by air pollution, resulting high burden to patients. To date, limited studies have estimated the relations between short-term exposure to air pollution and CHD disease burden in China, with inconsistent results. Hence, we aimed to estimate the short-term impact and burden of ambient PM pollutants on hospitalizations of CHD and specific CHD.

METHODS

PM10 and PM2.5 were measured at 82 monitoring stations in 9 cities in Sichuan Province, China during 2017-2018. Based on the time-stratified case-crossover design, the effects of short-term exposure to particle matter (PM) pollution on coronary heart disease (CHD) hospital admissions were estimated. Meanwhile, the linked burden of CHD owing to ambient PM pollution were estimated.

RESULTS

A total of 104,779 CHD records were derived from 153 hospitals from these 9 cities. There were significant effects of PM pollution on hospital admissions (HAs) for CHD and specific CHD in Sichuan Province. A 10 μg/m3 increase of PM10 and PM2.5 was linked with a 0.46% (95% CI: 0.08, 0.84%), and 0.57% (95% CI: 0.05, 1.09%) increments in HAs for CHD at lag7, respectively. The health effects of air pollutants were comparable modified by age, season and gender, showing old (≥ 65 years) and in cold season being more vulnerable to the effects of ambient air pollution, while gender-specific effects is positive but not conclusive. Involving the WHO's air quality guidelines as the reference, 1784 and 2847 total cases of HAs for CHD could be attributable to PM10 and PM2.5, separately. The total medical cost that could be attributable to exceeding PM10 and PM2.5 were 42.04 and 67.25 million CNY from 2017 to 2018, respectively.

CONCLUSIONS

This study suggested that the short-term exposure to air pollutants were associated with increased HAs for CHD in Sichuan Province, which could be implications for local environment improvement and policy reference.

Consumption in the G20 nations causes particulate air pollution resulting in two million premature deaths annually

Worldwide exposure to ambient PM_2.5 causes over 4 million premature deaths annually. As most of these deaths are in developing countries, without internationally coordinated efforts this polarized situation will continue. As yet, however, no studies have quantified nation-to-nation consumer responsibility for global mortality due to both primary and secondary PM_2.5 particles. Here we quantify the global footprint of PM_2.5-driven premature deaths for the 19 G20 nations in a position to lead such efforts. G20 consumption in 2010 was responsible for 1.983 [95% Confidence Interval: 1.685–2.285] million premature deaths, at an average age of 67, including 78.6 [71.5–84.8] thousand infant deaths, implying that the G20 lifetime consumption of about 28 [24–33] people claims one life. Our results indicate that G20 nations should take responsibility for their footprint rather than focusing solely on transboundary air pollution, as this would expand opportunities for reducing PM_2.5-driven premature mortality. Given the infant mortality footprint identified, it would moreover contribute to ensuring infant lives are not unfairly left behind in countries like South Africa, which have a weak relationship with G20 nations.

Worldwide exposure to ambient PM_2.5 causes millions of premature deaths annually. Here the authors quantify the global footprint of PM_2.5-driven premature deaths for the G20 countries, which are in a position to lead internationally coordinated mitigation efforts.

Different sized particles associated with all-cause and cause-specific emergency ambulance calls: A multicity time-series analysis in China

BACKGROUND

Compared with mortality and hospital admission, emergency ambulance calls (EACs) could be a more accurate outcome indicator to reflect the health effects of short-term air pollution exposure. However, such studies have been scarce, especially on a multicity scale in China.

METHODS

We estimated the associations of different diameter particles [i.e., inhalable particulate matter (PM₁₀), coarse particulate matter (PM_c), and fine particulate matter (PM_2.5)] with EACs for all-cause, cardiovascular, and respiratory diseases in seven Chinese cities. We collected data on EACs and air pollution from 2014 to 2019. We used generalized additive models and random-effects meta-analysis to examine the city-specific and overall associations. Stratified analyses were conducted to examine the effect modifications of gender, age, and season.

RESULTS

Significant associations of PM₁₀ and PM_2.5 with EACs were observed, while the PM_c associations were positive but not statistically significant in most analyses. Specifically, each 10 μg/m³ increase in 2-day moving average concentration of PM₁₀ was associated with a 0.25% [95% confidence interval (CI): 0.04%, 0.47%] increase in all-cause EACs, 0.13% (95% CI: -0.01%, 0.26%) in cardiovascular EACs, and 0.35% (95% CI: 0.04%, 0.66%) in respiratory EACs. The corresponding increases in daily EACs for PM_2.5 were 0.30% (95% CI, 0.03%, 0.57%), 0.13% (95% CI, -0.07%, 0.33%), and 0.46% (95% CI, 0.01%, 0.92%). Season of the year also modifies the association between particulate matter pollution and EACs.

CONCLUSIONS

Short-term exposure to PM₁₀ and PM_2.5 were positively associated with daily all-cause and respiratory-related EACs. The associations were stronger during warm season than cold season. Our findings suggest that the most harmful fraction of particulate matter pollution is PM_2.5, which has important implications for current air quality guidelines and regulations in China.

Effect of extreme temperatures on daily emergency room visits for mental disorders

Relatively few studies investigated the effects of extreme temperatures (both heat and cold) on mental health (ICD-9: 290-319; ICD-10: F00-F99) and the potential effect modifications by individuals' age, sex, and race. We aimed to explore the effect of extreme temperatures of both heat and cold on the emergency room (ER) visits for mental health disorders, and conducted a stratified analysis to identify possible susceptible population in Erie and Niagara counties, NY, USA. To assess the short-term impacts of daily maximum temperature on ER visits related to mental disorders (2009-2015), we applied a quasi-Poisson generalized linear model combined with a distributed lag non-linear model (DLNM). The model was adjusted for day of the week, precipitation, long-term time trend, and seasonality. We found that there were positive associations between short-term exposure to extreme ambient temperatures and increased ER visits for mental disorders, and the effects can vary by individual factors. We found heat effect (relative risk (RR) = 1.16; 95% confidence intervals (CI), 1.06-1.27) on exacerbated mental disorders became intense in the study region and subgroup of population (the elderly) being more susceptible to extreme heat than any other age group. For extreme cold, we found that there is a substantial delay effect of 14 days (RR = 1.25; 95% CI = 1.08-1.45), which is particularly burdensome to the age group of 50-64 years old and African-Americans. Our findings suggest that there is a positive association between short-term exposure to extreme ambient temperature (heat and cold) and increased ER visits for mental disorders, and the effects vary as a function of individual factors, such as age and race.

Modeling and Analysis of Data-Driven Systems through Computational Neuroscience Wavelet-Deep Optimized Model for Nonlinear Multicomponent Data Forecasting

Complex time series data exists widely in actual systems, and its forecasting has great practical significance. Simultaneously, the classical linear model cannot obtain satisfactory performance due to nonlinearity and multicomponent characteristics. Based on the data-driven mechanism, this paper proposes a deep learning method coupled with Bayesian optimization based on wavelet decomposition to model the time series data and forecasting its trend. Firstly, the data is decomposed by wavelet transform to reduce the complexity of the time series data. The Gated Recurrent Unit (GRU) network is trained as a submodel for each decomposition component. The hyperparameters of wavelet decomposition and each submodel are optimized with Bayesian sequence model-based optimization (SMBO) to develop the modeling accuracy. Finally, the results of all submodels are added to obtain forecasting results. The PM2.5 data collected by the US Air Quality Monitoring Station is used for experiments. By comparing with other networks, it can be found that the proposed method outperforms well in the multisteps forecasting task for the complex time series.

Particulate matter pollution and risk of outpatient visits for psychological diseases in Nanjing, China

Exposure to air pollution has been associated with increased risk for a range of adverse mental health conditions. Less is known about whether air pollution is also associated with increases in the utilization of mental health services, especially outpatient mental health service utilization. This study aimed to examine the association between the number of daily outpatient visits at the psychological disease departments of two major hospitals (PSYC) and daily average concentrations of PM_2.5 and PM₁₀ in a heavily polluted city in China, Nanjing, from 2013/7/1 to 2019/2/28, using generalized additive models with a quasi-Poisson regression. Results showed that each 10 μg/m³ increase in PM_2.5 concentration on lag0 day was associated with a 0.40% increase (95% CI: 0.07-0.72) in PSYC visits, and each 10 μg/m³ increase in PM₁₀ concentration on the same day a 0.31% increase (95% CI: 0.09-0.54) in PSYC visits. Exposure-response curves suggested linear relationships between PM concentration and daily PSYC outpatient visits, without evidence of a threshold. Associations remained positive, but were non-significant, with adjustment for co-pollutants, SO₂, NO₂ and CO. Significantly larger effects were found for older and male participants, vs. their counterparts. These findings add to the growing literature linking air pollution to mental health service utilization, demonstrating the critical need for both air pollution mitigation measures and increased capacity of the mental health system in China.

Associations between acute exposure to ambient air pollution and length of stay for inpatients with ischemic heart disease: a multi-city analysis in central China

Ambient air pollution (AAP) has been widely associated with increased morbidity of ischemic heart disease (IHD). However, no prior studies have investigated the effects of AAP exposure on the length of stay (LOS) due to IHD. Hospital data during 2015-2017 were obtained from hospital information system in five cities of Hubei province, China. We collected daily mean concentrations of air pollutants, including PM_2.5, PM₁₀, SO₂, NO₂, O₃, and CO, and meteorological data during the same time period. Poisson regression was applied to estimate the acute impacts of AAP on the LOS of IHD inpatients. A total of 42,114 inpatients with primary diagnosis of IHD were included, 50.63% of which were chronic IHD inpatients. Annual average concentrations of PM_2.5, PM₁₀, SO₂, NO₂, O₃, and CO were 61.93 μg/m³, 95.47 μg/m³, 18.59 μg/m³, 35.87 μg/m³, 100.30 μg/m³, and 1.117 mg/m³, respectively. After adjusting for temperature, relative humidity, gender, age group, payment method, number of hospital beds, location of hospital, and surgery or not, exposures to PM_2.5, PM₁₀, SO₂, O₃, and CO were associated with increased LOS for all IHD patients in both single- and multi-pollutant models, and stronger associations were observed among chronic IHD patients. In addition, subgroup analyses demonstrated that males and the group aged 65+ years were more vulnerable to air pollution, and the adverse effects were also promoted by low temperature in cold season. This study provides the first investigation of the adverse effects of AAP on the LOS for IHD patients. In order to shorten the LOS of IHD, measures should be taken to strengthen the AAP management and protect the high-risk population.

Coarse particles (PM2.5-10) and cause-specific hospitalizations in southwestern China: Association, attributable risk and economic costs

The short-term morbidity effects of the coarse particle (diameter in 2.5-10 μm, PM_2.5-10), as well as the corresponding morbidity burden and economic costs, remain understudied, especially in developing countries. This study aimed to examine the associations of PM_2.5-10 with cause-specific hospitalizations in a multi-city setting in southwestern China and assess the attributable risk and economic costs. City-specific associations were firstly estimated using generalized additive models with quasi-poisson distribution to handle over-dispersion, and then combined to obtain the regional average association. City-specific and pooled concentration-response (C-R) associations of PM_2.5-10 with cause-specific hospitalizations were also modeled. Subgroup analyses were performed by age, sex, season and region. The health and economic burden of hospitalizations for multiple outcomes due to PM_2.5-10 were further evaluated. A total of 4,407,601 non-accidental hospitalizations were collected from 678 hospitals. The estimates of percentage change in hospitalizations per 10 μg/m³ increase in PM_2.5-10 at lag01 was 0.68% (95%CI: 0.33%-1.03%) for non-accidental causes, 0.86% (95% CI: 0.36%-1.37%) for circulatory diseases, 1.52% (95% CI: 1.00%-2.05%) for respiratory diseases, 1.08% (95% CI: 0.47%-1.69%) for endocrine diseases, 0.66% (95% CI: 0.12%-1.21%) for nervous system diseases, and 0.84% (95% CI: 0.42%-1.25%) for genitourinary diseases, respectively. The C-R associations of PM_2.5-10 with cause-specific hospitalizations suggested some evidence of nonlinearity, except for endocrine diseases. Meanwhile, the adverse effects were modified by age and season. Overall, about 0.70% (95% CI: 0.35%-1.06%) of non-accidental hospitalizations and 0.78% (95% CI: 0.38%-1.17%) of total hospitalization expenses could be attributed to PM_2.5-10. The largest morbidity burden and economic costs were observed in respiratory diseases. Our findings indicate that PM_2.5-10 exposure may increase the risk of hospitalizations for multiple outcomes, and account for considerable morbidity and economic burden.

Association Pathways Between Neighborhood Greenspaces and the Physical and Mental Health of Older Adults-A Cross-Sectional Study in Guangzhou, China

According to the United Nations, the proportion of the older population is increasing at a faster rate than all other age groups. Hence, the well-being of older adults is a mounting concern worldwide in the current century. Using a single greenery metric, previous studies linked greenness to residents' well-being. This study aims to extend this field by focusing on the mental and physical well-being of older adults by using remote sensing and streetscape metrics in evaluating neighborhood greenness. We selected 20 residential neighborhoods in Guangzhou City, China as the cross-sectional case study areas. We investigated neighborhood normalized difference vegetation index (NDVI) collected using remote sensing images, streetscape greenery, and PM2.5 via field surveys. We assessed the health condition of 972 senior residents selected by multi-stage stratified probability proportionate to population size sampling technique (PPS) using a questionnaire survey. We adopted the structural equation model (SEM) in analyzing the pathways that link neighborhood greenness and the mental and physical health of older adults. We found that neighborhood greenness has a positive association with the physical activity by older adults that is positively linked to their physical health. Moreover, neighborhood greenness is positively related to regular social interactions among older adults that is positively linked to their mental health. These findings are consistent with those of previous studies. However, we obtained new results that were unique to China. We found that neighborhood greenness has no significant direct relationship with the physical and mental health of older adults and that social interactions of low-income senior groups are more substantially related to neighborhood greenness than the other groups. Therefore, community planning should emphasize the development of neighborhood greenness, such as parks and street trees, to provide natural spaces for social interactions and places for physical activities among older residents.

Attributable Risk and Economic Cost of Cardiovascular Hospital Admissions Due to Ambient Particulate Matter in Wuhan, China

Although the adverse effects of ambient particulate matter (PM) on cardiovascular disease (CVD) have been previously documented, information about their economic consequence was insufficient. This study aimed to evaluate the attributable risk and economic cost of cardiovascular hospitalizations due to ambient PM. Data of CVD hospitalizations and PM concentrations from 1 January 2015 to 31 December 2017 were collected in Wuhan, China. A generalized additive model was applied to quantify the PM-attributable CVD hospitalizations, and total attributable hospitalization costs were calculated via multiplying the total attributable cases by the case-average hospitalization costs. A total of 45,714 CVD hospitalizations were included in this study. The results showed that a 10 µg/m3 increase in PM2.5 and PM10 concentrations at lag7 day, respectively, contributed to a 1.01% (95% confidence interval: 0.67-1.34) and 0.48% (0.26-0.70) increase in CVD hospitalizations. During the study period, 1487 and 983 CVD hospitalizations were attributable to PM2.5 and PM10, equaling an economic cost of 29.27 and 19.34 million RMB (1 RMB = 0.1424 USD), respectively, and significant differences in PM-attributable hospitalizations and economic burden were found between gender and age groups. Our study added evidence in heavily polluted megacities regarding the increased health risk and economic cost of CVD hospitalizations associated with ambient particulate pollution.