The impact of ambient particulate matter on hospital outpatient visits for respiratory and circulatory system disease in an urban Chinese population

Cold waves and fine particulate matter in high-altitude Chinese cities: assessing their interactive impact on outpatient visits for respiratory disease

BACKGROUND

Extreme weather events like heatwaves and fine particulate matter (PM2.5) have a synergistic effect on mortality, but research on the synergistic effect of cold waves and PM2.5 on outpatient visits for respiratory disease, especially at high altitudes in climate change-sensitive areas, is lacking.

METHODS

we collected time-series data on meteorological, air pollution, and outpatient visits for respiratory disease in Xining. We examined the associations between cold waves, PM2.5, and outpatient visits for respiratory disease using a time-stratified case-crossover approach and distributional lag nonlinear modeling. Our analysis also calculated the relative excess odds due to interaction (REOI), proportion attributable to interaction (AP), and synergy index (S). We additionally analyzed cold waves over time to verify climate change.

RESULTS

Under different definitions of cold waves, the odds ratio for the correlation between cold waves and outpatient visits for respiratory disease ranged from 0.95 (95% CI: 0.86, 1.05) to 1.58 (1.47, 1.70). Exposure to PM2.5 was significantly associated with an increase in outpatient visits for respiratory disease. We found that cold waves can synergize with PM2.5 to increase outpatient visits for respiratory disease (REOI > 0, AP > 0, S > 1), decreasing with stricter definitions of cold waves and longer durations. Cold waves' independent effect decreased over time, but their interaction effect persisted. From 8.1 to 21.8% of outpatient visits were due to cold waves and high-level PM2.5. People aged 0-14 and ≥ 65 were more susceptible to cold waves and PM2.5, with a significant interaction for those aged 15-64 and ≥ 65.

CONCLUSION

Our study fills the gap on how extreme weather and PM2.5 synergistically affect respiratory disease outpatient visits in high-altitude regions. The synergy of cold waves and PM2.5 increases outpatient visits for respiratory disease, especially in the elderly. Cold wave warnings and PM2.5 reduction have major public health benefits.

Effects of the interaction between cold spells and fine particulate matter on mortality risk in Xining: a case-crossover study at high altitude

Background

With global climate change, the health impacts of cold spells and air pollution caused by PM2.5 are increasingly aggravated, especially in high-altitude areas, which are particularly sensitive. Exploring their interactions is crucial for public health.

Methods

We collected time-series data on meteorology, air pollution, and various causes of death in Xining. This study employed a time-stratified case-crossover design and conditional logistic regression models to explore the association between cold spells, PM2.5 exposure, and various causes of death, and to assess their interaction. We quantitatively analyzed the interaction using the relative excess odds due to interaction (REOI), attributable proportion due to interaction (AP), and synergy index (S). Moreover, we conducted stratified analyses by average altitude, sex, age, and educational level to identify potential vulnerable groups.

Results

We found significant associations between cold spells, PM2.5, and various causes of death, with noticeable effects on respiratory disease mortality and COPD mortality. We identified significant synergistic effects (REOI>0, AP > 0, S > 1) between cold spells and PM2.5 on various causes of death, which generally weakened with a stricter definition of cold spells and longer duration. It was estimated that up to 9.56% of non-accidental deaths could be attributed to concurrent exposure to cold spells and high-level PM2.5. High-altitude areas, males, the older adults, and individuals with lower educational levels were more sensitive. The interaction mainly varied among age groups, indicating significant impacts and a synergistic action that increased mortality risk.

Conclusion

Our study found that in high-altitude areas, exposure to cold spells and PM2.5 significantly increased the mortality risk from specific diseases among the older adults, males, and those with lower educational levels, and there was an interaction between cold spells and PM2.5. The results underscore the importance of reducing these exposures to protect public health.

The changing health effects of air pollution exposure for respiratory diseases: a multicity study during 2017-2022

BACKGROUND

Multifaceted SARS-CoV-2 interventions have modified exposure to air pollution and dynamics of respiratory diseases. Identifying the most vulnerable individuals requires effort to build a complete picture of the dynamic health effects of air pollution exposure, accounting for disparities across population subgroups.

METHODS

We use generalized additive model to assess the likely changes in the hospitalisation and mortality rate as a result of exposure to PM2.5 and O3 over the course of COVID-19 pandemic. We further disaggregate the population into detailed age categories and illustrate a shifting age profile of high-risk population groups. Additionally, we apply multivariable logistic regression to integrate demographic, socioeconomic and climatic characteristics with the pollution-related excess risk.

RESULTS

Overall, a total of 1,051,893 hospital admissions and 34,954 mortality for respiratory disease are recorded. The findings demonstrate a transition in the association between air pollutants and hospitalisation rates over time. For every 10 µg/m3 increase of PM2.5, the rate of hospital admission increased by 0.2% (95% CI: 0.1-0.7%) and 1.4% (1.0-1.7%) in the pre-pandemic and dynamic zero-COVID stage, respectively. Conversely, O3-related hospitalization rate would be increased by 0.7% (0.5-0.9%) in the pre-pandemic stage but lowered to 1.7% (1.5-1.9%) in the dynamic zero-COVID stage. Further assessment indicates a shift of high-risk people from children and young adolescents to the old, primarily the elevated hospitalization rates among the old people in Lianyungang (RR: 1.53, 95%CI: 1.46, 1.60) and Nantong (RR: 1.65, 95%CI: 1.57, 1.72) relative to those for children and young adolescents. Over the course of our study period, people with underlying diseases would have 26.5% (22.8-30.3%) and 12.7% (10.8-14.6%) higher odds of having longer hospitalisation and over 6 times higher odds of deaths after hospitalisation.

CONCLUSIONS

Our estimates provide the first comprehensive evidence on the dynamic pollution-health associations throughout the pandemic. The results suggest that age and underlying diseases collectively determines the disparities of pollution-related health effect across population subgroups, underscoring the urgency to identifying the most vulnerable individuals to air pollution.

Differential effects of size-specific particulate matter on frailty transitions among middle-aged and older adults in China: findings from the China Health and Retirement Longitudinal Study (CHARLS), 2015-2018

BACKGROUND

This study aimed to assess the long-term effects of size-specific particulate matter (PM) on frailty transitions in middle-aged and older Chinese adults.

METHODS

We included 13 910 participants ≥45 y of age from the China Health and Retirement Longitudinal Study (CHARLS) for 2015 and 2018 who were classified into three categories in 2015 according to their frailty states: robust, prefrail and frail. Air quality data were obtained from the National Urban Air Quality Real-time Publishing Platform. A two-level logistic regression model was used to examine the association between concentrations of PM and frailty transitions.

RESULTS

At baseline, the total number of robust, prefrail and frail participants were 7516 (54.0%), 4324 (31.1%) and 2070 (14.9%), respectively. Significant associations were found between PM concentrations and frailty transitions. For each 10 μg/m3 increase in the 3-y averaged 2.5-μm PM (PM2.5) concentrations, the risk of worsening in frailty increased in robust (odds ratio [OR] 1.06 [95% confidence interval {CI} 1.01 to 1.12]) and prefrail (OR 1.07 [95% CI 1.01 to 1.13]) participants, while the probability of improvement in frailty in prefrail (OR 0.91 [95% CI 0.84 to 0.98]) participants decreased. In addition, the associations of PM10 and coarse fraction of PM with frailty transitions showed similar patterns.

CONCLUSIONS

Long-term exposure to PM was associated with higher risks of worsening and lower risks of improvement in frailty among middle-aged and older adults in China.

Involvement and repair of epithelial barrier dysfunction in allergic diseases

The epithelial barrier serves as a critical defense mechanism separating the human body from the external environment, fulfilling both physical and immune functions. This barrier plays a pivotal role in shielding the body from environmental risk factors such as allergens, pathogens, and pollutants. However, since the 19th century, the escalating threats posed by environmental pollution, global warming, heightened usage of industrial chemical products, and alterations in biodiversity have contributed to a noteworthy surge in allergic disease incidences. Notably, allergic diseases frequently exhibit dysfunction in the epithelial barrier. The proposed epithelial barrier hypothesis introduces a novel avenue for the prevention and treatment of allergic diseases. Despite increased attention to the role of barrier dysfunction in allergic disease development, numerous questions persist regarding the mechanisms underlying the disruption of normal barrier function. Consequently, this review aims to provide a comprehensive overview of the epithelial barrier's role in allergic diseases, encompassing influencing factors, assessment techniques, and repair methodologies. By doing so, it seeks to present innovative strategies for the prevention and treatment of allergic diseases.

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.

Effect of Air Pollutants and Meteorological Factors on Daily Outpatient Visits of Allergic Rhinitis in Hohhot, China

Objective

There is limited evidence that atmospheric pollutants are associated with the number of allergic rhinitis (AR) visits. This study aimed to investigate the relationship between atmospheric pollutants and meteorological factors and the number of daily visits for AR in Hohhot City, providing a theoretical basis for further research on the effects of atmospheric pollutants on AR.

Methods

Microsoft Excel 2016 was used to collect and organize the AR outpatient consultation data, air pollution and meteorological data in Hohhot City during 2018-2020, and the data were descriptively analyzed and Spearman correlation test was performed using SPSS22.0; A generalized additive model was built in R4.2.3 to analyze the effect of air pollution on the number of AR visits and its lagged and cumulative effects, while the robustness of the model was tested using a two-pollutant analysis. Finally, we analyzed the effects of the interaction of temperature, relative humidity and pollutants on the number of AR visits.

Results

The daily average concentrations of PM2.5, PM10, SO2, NO2, CO, and O3 in Hohhot during 2018-2020 were 38.1 μg/m3, 83.3 μg/m3, 36.1 μg/m3, 15.1 μg/m3, 14.2 mg/m3, and 99.95 μg/m3, respectively, with the concentrations of PM2.5 and PM10 exceeding the secondary limit of the national standard. The results of the generalized additive model analysis showed that the RR and 95% CI of the effect of each 10 μg/m3 increase in pollutant concentration (1 mg/m3 increase in CO) on the number of AR outpatient clinics were 1.008 (1.001-1.016), 1.002 (1-1.005), 1.072 (1.033-1.113), 1.020 (1007-1.034), 1.033 (1.014-1.052), 0.987 (0.9804-0.9936).

Conclusion

Short-term exposure to PM2.5, PM10, SO2, NO2, and CO was significantly associated with an increase in AR clinic visits, and short-term exposure to O3 was significantly associated with a decrease in allergic rhinitis clinic visits.

Particulate matter exposure and neurodegenerative diseases: A comprehensive update on toxicity and mechanisms

Exposure to particulate matter (PM) has been associated with a range of health impacts, including neurological abnormalities that affect neurodevelopment, neuroplasticity, and behavior. Recently, there has been growing interest in investigating the possible relationship between PM exposure and the onset and progression of neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, Huntington's disease, and multiple sclerosis. However, the precise mechanism by which PM affects neurodegeneration is still unclear, even though several epidemiological and animal model studies have provided mechanistic insights. This article presents a review of the current research on the neurotoxicity of PM and its impact on neurodegenerative diseases. This review summarizes findings from epidemiological and animal model studies collected through searches in Google Scholar, PubMed, Web of Science, and Scopus. This review paper also discusses the reported effects of PM exposure on the central nervous system and highlights research gaps and future directions. The information presented in this review may inform public health policies aimed at reducing PM exposure and may contribute to the development of new treatments for neurodegenerative diseases. Further mechanistic and therapeutic research will be needed to fully understand the relationship between PM exposure and neurodegenerative diseases.

Impacts and mechanisms of PM2.5 on bone

Osteoporosis is a metabolic bone disease, which is characterized by a decreased bone mass and deterioration of bone microstructure, resulting in increased bone fragility and a higher risk of fracture. The main pathological process of osteoporosis is the dynamic imbalance between bone absorption and bone formation, which can be caused by various factors such as air pollution. Particulate matter (PM)_2.5 refers to the fine particles in the atmosphere, which are small in volume and large in specific surface area. These particles are prone to carrying toxic substances and have negative effects on several extrapulmonary organs, including bones. In this review, we present relevant data from studies, which show that PM_2.5 is associated with abnormal bone turnover and osteoporosis. PM_2.5 may cause or aggravate bone loss by stimulating an inflammatory response, inducing oxidative damage, reducing estrogen efficiency by competitive binding to estrogen receptors, or endocrine disorder mediated by binding with aromatic hydrocarbon receptors, and affecting the synthesis of vitamin D to reduce calcium absorption. The cellular and molecular mechanisms involved in these processes are also summarized in this review.

Long-term exposure to PM2.5 and O3 with cardiometabolic multimorbidity: Evidence among Chinese elderly population from 462 cities

Cardiometabolic multimorbidity (CMM) refers to the presence of multiple cardiovascular and metabolic diseases (CMDs), such as hypertension, diabetes, and cardio-cerebrovascular diseases (CCVD), in the same individual, and has emerge as a significant global health concern due to population aging. Although previous research has demonstrated the association between cardiovascular and metabolic diseases and air pollutants, evidence on the link between CMM and air pollution exposure among Chinese older adults is limited. To address this research gap, we conducted a national representative survey of 222,179 adults aged 60 and older to investigate the epidemiology of CMM and its association with long-term exposure to PM_2.5 and O₃ in China's elderly population. We found that the prevalence of CMM among Chinese older adults was 16.9%, and hypertension and CCVD were the most common CMM cluster (10.8%). After adjusting for confounding variables, we observed a significant positive association between PM_2.5 exposure and the prevalence of hypertension, diabetes, and CCVD, with a respective excess risk increase of 3.2%, 3.6%, and 5.5% for every 10-unit increase. Moreover, every 10-unit increase in PM_2.5 was linked to a higher risk of hypertension and diabetes (2.2%), hypertension and CCVD (5.4%), diabetes and CCVD (5.6%), and hypertension, diabetes, and CCVD combined (7.6%). We also found a U-shaped curve relationship between O₃ exposure and the occurrence of hypertension, diabetes, and CCVD, as well as different subtypes of CMM, with the lowest risk of O₃ exposure was observed near 75-80 μg/m³. Furthermore, we identified that female and rural residents are more vulnerable to the health risks of air pollution than male and urban residents. Given the increasing aging of the population and rising prevalence of multimorbidity, policymakers should focus more attention on the female and rural elderly population to prevent and control CMM. This study provides compelling evidence that reducing air pollution levels can be an effective strategy to prevent and manage CMM among older adults.

Application of machine learning approaches to predict the impact of ambient air pollution on outpatient visits for acute respiratory infections

With a remarkable increase in industrialization among fast-developing countries, air pollution is rising at an alarming rate and has become a public health concern. The study aims to examine the effect of air pollution on patient's hospital visits for respiratory diseases, particularly Acute Respiratory Infections (ARI). Outpatient hospital visits, air pollution and meteorological parameters were collected from March 2018 to October 2021. Eight machine learning algorithms (Random Forest model, K-Nearest Neighbors regression model, Linear regression model, LASSO regression model, Decision Tree Regressor, Support Vector Regression, X.G. Boost and Deep Neural Network with 5-layers) were applied for the analysis of daily air pollutants and outpatient visits for ARI. The evaluation was done by using 5-cross-fold confirmations. The data was randomly divided into test and training data sets at a scale of 1:2, respectively. Results show that among the studied eight machine learning models, the Random Forest model has given the best performance with R² = 0.606, 0.608 without lag and 1-day lag respectively on ARI patients and R² = 0.872, 0.871 without lag and 1-day lag respectively on total patients. All eight models did not perform well with the lag effect on the ARI patient dataset but performed better on the total patient dataset. Thus, the study did not find any significant association between ARI patients and ambient air pollution due to the intermittent availability of data during the COVID-19 period. This study gives insight into developing machine learning programs for risk prediction that can be used to predict analytics for several other diseases apart from ARI, such as heart disease and other respiratory diseases.

Circulatory health risks from additive multi-pollutant models: short-term exposure to three common air pollutants in Canada

Numerous studies have reported adverse health effects of ambient air pollution on circulatory health outcomes mainly based on single-pollutant models. However, limited studies have focused on adjusted effect of multi-pollutant exposures on public health. This study aimed to examine short-term effects of three common air pollutants-ground-level ozone (ozone), nitrogen dioxide (NO2), and fine particulate matter (PM2.5)-through multi-pollutant models for mixed effect of adjustment. Daily data (circulatory hospitalization and mortality) and hourly data (air pollutants and temperature) were collected for 24 Canadian cities for 2001-2012. We applied generalized additive over-dispersion Poisson regression models with 1, 2, or 3 pollutants for city-specific risks, and Bayesian hierarchical models for national risks. This study found little mixed effect of adjustment through multi-pollutant models (ozone and/or NO2 and/or PM2.5) for circulatory hospitalization or mortality in Canada for 2001-2012, indicating that the 1-pollutant model did not result in considerable under- or over-estimates. It seemed weak-to-moderate correlations among air pollutants did not change the significant effect of one air pollutant after accounting for others. Inconsistent findings between other previous studies and this study indicate the need of comparable study design for multi-pollutant effect analysis.

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.

Associations between short-term exposure of ambient particulate matter and hemodialysis patients death: A nationwide, longitudinal case-control study in China

BACKGROUND

Long-term exposure to particulate air pollutants can lead to an increase in mortality of hemodialysis patients, but evidence of mortality risk with short-term exposure to ambient particulate matter is lacking. This study aimed to estimate the association of short-term exposure to ambient particulate matter across a wide range of concentrations with hemodialysis patients mortality.

METHODS

We performed a time-stratified case-crossover study to estimate the association between short-term exposures to PM_2.5 and PM₁₀ and mortality of hemodialysis patients. The study included 18,114 hemodialysis death case from 279 hospitals in 41 cities since 2013. Daily particulate matter exposures were calculated by the inverse distance-weighted model based on each case's dialysis center address. Conditional logistic regression were implemented to quantify exposure-response associations. The sensitivity analysis mainly explored the lag effect of particulate matter.

RESULTS

During the study period, there were 18,114 case days and 61,726 control days. Of all case and control days, average PM_2.5 and PM₁₀ levels were 43.98 μg/m³ and 70.86 μg/m³, respectively. Each short-term increase of 10 μg/m³ in PM_2.5 and PM₁₀ were statistically significantly associated with a relative increase of 1.07 % (95 % confidence interval [CI]: 0.99 % - 1.15 %) and 0.89 % (95 % CI: 0.84 % - 0.94 %) in daily mortality rate of hemodialysis patients, respectively. There was no evidence of a threshold in the exposure-response relationship. The mean of daily exposure on the same day of death and one-day prior (Lag 01 Day) was the most plausible exposure time window.

CONCLUSIONS

This study confirms that short-term exposure to particulate matter leads to increased mortality in hemodialysis patients. Policy makers and public health practices have a clear and urgent opportunity to pass air quality control policies that care for hemodialysis populations and incorporate air quality into the daily medical management of hemodialysis patients.

Has the Risk of Outpatient Visits for Allergic Rhinitis, Related to Short-Term Exposure to Air Pollution, Changed over the Past Years in Beijing, China?

A number of studies have found associations between the short-term exposure to ambient air pollution and hospital admissions. However, little is known about the temporal variations in ambient air pollution associated with health exposure, especially in China. We evaluated whether the risks of allergic rhinitis (AR) outpatient visits from short-term exposure to air pollution varied over time (2014-2020) in Beijing, China. A quasi-Poisson generalized additive model was used to evaluate the relative risks (RRs) and 95% confidence intervals (CIs) associated with the pollutant concentrations during the entire study period and three specific periods. We also analyzed the temporal variations of the period-specific associations and tested the trend of change using the Mann-Kendall test. The concentration-response relationships for the specific periods were further investigated. The RRs (95%CI) for an interquartile range (IQR) increased in PM₁₀ (70 μg/m³) and CO (0.5 mg/m³) decreased from period 1 to period 3. However, The RRs (95%CI) of PM_2.5 (55 μg/m³), SO₂ (7 μg/m³) and NO₂ (27 μg/m³) increased from 1.015 (0.978, 1.054), 1.027 (1.009, 1.044) and 1.086 (1.037, 1.137) in period 1 to 1.069 (1.005, 1.135), 1.074 (1.003, 1.149) and 1.214 (1.149, 1.282) in period 3, respectively. A statistically significant temporal change and the stable effects were observed between the NO₂ exposure and AR visits over time. Despite a substantial reduction in ambient air pollution, the short-term effects on AR outpatient visits remained significant. Our findings provide a rationale for continued air pollution control efforts in the future to minimize air pollution and to protect the public.

Ameliorative Effect of Citrus junos Tanaka Waste (By-Product) Water Extract on Particulate Matter 10-Induced Lung Damage

Citrus junos Tanaka (CJ)-related products are well-accepted by consumers worldwide; thus, they generate huge amounts of waste (peel, pulp, and seed) through CJ processing. Although some CJ by-products (CJBs) are recycled, their use is limited owing to the limited understanding of their nutritional and economic value. The exposure to particulate matter (PM) increases the risk of respiratory diseases. In this study, we investigated the ameliorative effects of CJB extracts (100, 200 mg/kg/day, 7 days) on PM10-induced (10 mg/kg, intranasal, 6 h) lung damage in BALB/c mice. Cell type-specific signaling pathways are examined using the A549 (PM10, 200 μg/mL, 6 h) and RAW264.7 (LPS, 100 ng/mL, 6 h) cell lines. The CJB extracts significantly attenuated PM10-induced pulmonary damage and inflammatory cell infiltration in a mouse model. The essential protein markers in inflammatory signaling pathways, such as AKT, ERK, JNK, and NF-κB for PM10-induced phosphorylation, were dramatically reduced by CJB extract treatment in both the mouse and cell models. Furthermore, the CJB extracts reduced the production of reactive oxygen species and nitric oxide in a dose-dependent manner in the cells. Comprehensively, the CJB extracts were effective in reducing PM10-induced lung injuries by suppressing pulmonary inflammation, potentially due to their anti-inflammatory and antioxidant properties.

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.

New Homogeneous Spatial Areas Identified Using Case-Crossover Spatial Lag Grid Differences between Aerosol Optical Depth-PM2.5 and Respiratory-Cardiovascular Emergency Department Visits and Hospitalizations

Optimal use of Hierarchical Bayesian Model (HBM)-assembled aerosol optical depth (AOD)-PM2.5 fused surfaces in epidemiologic studies requires homogeneous temporal and spatial fused surfaces. No analytical method is available to evaluate spatial heterogeneity. The temporal case-crossover design was modified to assess the spatial association between four experimental AOD-PM2.5 fused surfaces and four respiratory–cardiovascular hospital events in 12 km2 grids. The maximum number of adjacent lag grids with significant odds ratios (ORs) identified homogeneous spatial areas (HOSAs). The largest HOSA included five grids (lag grids 04; 720 km2) and the smallest HOSA contained two grids (lag grids 01; 288 km2). Emergency department asthma and inpatient asthma, myocardial infarction, and heart failure ORs were significantly higher in rural grids without air monitors than in urban grids with air monitors at lag grids 0, 1, and 01. Rural grids had higher AOD-PM2.5 concentration levels, population density, and poverty percentages than urban grids. Warm season ORs were significantly higher than cold season ORs for all health outcomes at lag grids 0, 1, 01, and 04. The possibility of elevated fine and ultrafine PM and other demographic and environmental risk factors synergistically contributing to elevated respiratory–cardiovascular chronic diseases in persons residing in rural areas was discussed.

Health Benefits of Air Quality Improvement: Empirical Research Based on Medical Insurance Reimbursement Data

Measuring the health benefits of air quality improvement is a new perspective for evaluating government investment in pollution control. Improving air quality can reduce the burden on medical insurance funds and patients themselves; however, patients with higher reimbursement rates are more affected by air quality changes. This study calculated health benefits using medical insurance reimbursement data from a sample city in China. The results show that for every 10 μg/m3 decrease in PM2.5, patients' average medical cost will decrease by CNY 1,699 (USD 263.6), and the loss of ordinary working and living time will decrease by 1.24 days. PM2.5 has a more significant impact on patients with chronic respiratory diseases and inpatients with circulatory diseases. Suppose the city's annual PM2.5 concentration drops to the national standard of 35 μg/m3. In that case, it will bring more than CNY 1.28 billion (USD 198 million) in health benefits, accounting for 18% of the city's annual investment in environmental protection.

Time series analysis of short-term effects of particulate matter pollution on the circulatory system disease mortality risk in Lishui District, China

Epidemiological evidence has shown a significant association between short-term exposure to air pollution and mortality risk for circulatory system diseases (CSD). However, informative insights on the significance and magnitude of its relationship in the process of government interventions on abating air pollution are still lacking, particularly in a burgeoning Chinese city. In this study, we conducted a time series study in Lishui District, Nanjing, to examine the effect of ambient particulate matter (PM), e.g., PM_2.5 and PM₁₀, on daily death counts of CSD which included cardiovascular disease (CVD), cerebrovascular disease (CEVD), and arteriosclerotic heart disease (ASHD) mortality from January 1, 2015, to December 31, 2019. The results revealed that each 10 μg/m³ increase in PM_2.5 and PM₁₀ concentration at lag0 day was associated with an increase of 1.33% (95% confidence interval, 0.08%, 2.60%) and 1.12% (0.43%, 1.82%) in CSD mortality; 2.42% (0.44%, 4.43%) and 1.43% (0.32%, 2.55%) in CVD mortality; 1.20% (- 0.31%, 2.73%) and 1.21% (0.38%, 2.05%) in CEVD mortality; and 2.78% (0.00%, 5.62%) and 1.66% (0.14%, 3.21%) in ASHD mortality, respectively. For cumulative risk, the corresponding increase in daily mortality for the same change in PM_2.5 concentration at lag03 day was significantly associated with 1.94% (0.23%, 3.68%), 3.17% (0.58%, 5.84%), 2.38% (0.17%, 4.63%), and 4.92% (1.18%, 8.81%) for CSD, CVD, CEVD, and ASHD, respectively. The exposure-response curves were approximately nonlinear over the entire exposure range of the PM concentrations. We also analyzed the effect modifications by season (warm or cold), age group (0-64 years, 65-74 years, or ≥ 75 years), and sex (male or female). Although not statistically significant, stratified analysis showed greater vulnerability to PM exposure for cold season, population over 65 years of age, and female group.

Effects of particulate matter on hospital admissions for respiratory diseases: an ecological study based on 12.5 years of time series data in Shanghai

BACKGROUND

Previous epidemiological studies on the association between short-term exposure to particulate matter (PM) with hospital admission in major cities in China were limited to shorter study periods or a single hospital. The aim of this ecological study based on a 12.5-year time series was to investigate the association of short-term exposure to PM with aerodynamic diameter ≤ 2.5 μm (PM_2.5) and aerodynamic diameter ≤ 10 μm (PM₁₀) with hospital admissions for respiratory diseases.

METHODS

Daily hospital admissions data were from the Shanghai Medical Insurance System for the period January 1, 2008 to July 31, 2020. We estimated the percentage change with its 95% confidence interval (CI) for each 10 μg/m³ increase in the level of PM_2.5 and PM₁₀ after adjustment for calendar time, day of the week, public holidays, and meteorological factors applying a generalized additive model with a quasi-Poisson distribution.

RESULTS

There were 1,960,361 hospital admissions for respiratory diseases in Shanghai during the study period. A 10 μg/m³ increase in the level of each class of PM was associated with increased total respiratory diseases when the lag time was 0 day (PM_2.5: 0.755%; 95% CI: 0.422, 1.089%; PM₁₀: 0.250%; 95% CI: 0.042, 0.459%). The PM_2.5 and PM₁₀ levels also had positive associations with admissions for COPD, asthma, and pneumonia. Stratified analyses demonstrated stronger effects in patients more than 45 years old and during the cold season. Total respiratory diseases increased linearly with PM concentration from 0 to 100 μg/m³, and increased more slowly at higher PM concentrations.

CONCLUSIONS

This time-series study suggests that short-term exposure to PM increased the risk for hospital admission for respiratory diseases, even at low concentrations. These findings suggest that reducing atmospheric PM concentrations may reduce hospital admissions for respiratory diseases.

Pricing air pollution: evidence from short-term exposure to air pollution on hospitalization of acute bronchitis and chronic obstructive pulmonary disease in southwestern China

Existing evidence suggests that ambient air pollution has serious adverse effects on respiratory diseases, yet there is little direct evidence from China regarding corresponding economic losses. Here we quantified air pollution-related acute health effects and related economic losses of the most common two respiratory diseases in southwestern China, acute bronchitis and chronic obstructive pulmonary disease (COPD). We applied a distributed lag non-linear model to analyse the relationship between ambient air pollutants and hospital admissions of acute bronchitis and COPD, then applied the cost of illness method to explore the attributing economic burden. During the study period, 528 334 and 99 419 hospital admissions of acute bronchitis and COPD, respectively, were recorded. As a result, during the study period the total hospitalization economic losses attributable to air pollution were 486.40 and 254.74 million yuan for acute bronchitis and COPD, respectively, accounting for 0.015% of local gross domestic product. Our research provides intuitive evidence on the health and economic impacts of short-term exposure to air pollution, which is a key basis for the formulation of environmental policies.

Explainable deep learning predictions for illness risk of mental disorders in Nanjing, China

Epidemiological studies have revealed the associations of air pollutants and meteorological factors with a range of mental health conditions. However, little is known about local explanations and global understanding on the importance and effect of input features in the complex system of environmental stressors - mental disorders (MDs), especially for exposure to air pollution mixture. In this study, we combined deep learning neural networks (DLNNs) with SHapley Additive exPlanation (SHAP) to predict the illness risk of MDs on the population level, and then provided explanations for risk factors. The modeling system, which was trained on day-by-day hospital outpatient visits of two major hospitals in Nanjing, China from 2013/07/01 through 2019/02/28, visualized the time-varying prediction, contributing factors, and interaction effects of informative features. Our results suggested that NO₂, SO₂, and CO made outstanding contributions in magnitude of feature attributions under circumstances of mixed air pollutants. In particular, NO₂ at high concentration level was associated with an increase in illness risk of MDs, and the maximum and mean absolute SHAP value were approximated to 10 and 2 as a local and global measure of feature importance, respectively. It presented a marginally antagonistic effect for two pairs of gaseous pollutants, i.e., NO₂ vs. SO₂ and CO vs. NO₂. In contrast, CO and SO₂ displayed the opposite direction of feature effects to the rise of observed concentrations, but an apparent synergistic effect was obviously captured. The primary risk factors driving a sharp increase in acute attack or exacerbation of MDs were also identified by depicting prediction paths of time-series samples. We believe that the significance of coupling accurate predictions from DLNNs with interpretable explanations of why a prediction is completed has broad applicability throughout the field of environmental health.

Impact of ambient fine particulate matter on emergency department admissions for circulatory system disease in a city in Northeast China

The cardiovascular impact of fine particles has caused great concern worldwide. However, evidences on the impact of fine particulate matter (PM_2.5) on emergency department (ED) admissions for circulatory system disease in Northeast China is limited. We assessed the acute, lag, cumulative, and harvesting effects of PM_2.5 on ED admissions for circulatory system diseases and their exposure-response relationship. A total of 26,168 ED admissions, including those for hypertension, ischemic heart disease (IHD), arrhythmia, heart failure (HF), and cerebrovascular events (CVE), were collected from the Shenyang Emergency Center from 1 January 2017 to 31 December 2018. The relationship between PM_2.5 and ED admissions for circulatory system disease was estimated using a distributed lag non-linear model and a generalized additive quasi-Poisson model. We stratified the analyses by temperature. Air pollution was positively correlated with daily ED admissions for circulatory system disease or other cause-specific diseases under different lag structures. For every 10-μg/m³ increase in the PM_2.5 concentration, the relative risk of daily ED admissions for circulatory system disease was 1.007 [95% confidence interval (CI), 1.001-1.013] in lag0, 1.007 (95%CI, 1.000-1.013) in lag1, and 1.011 (95%CI, 1.002-1.021) in lag03. A lag effect was found in IHD, a cumulative effect was found in CVE, and both lag and cumulative effects were found in hypertension and arrhythmia. A harvesting effect was observed in daily ED admissions for circulatory system disease and HF. We found no interaction between pollutants and temperature. We observed a monotonic and almost linear exposure-response relationship between PM_2.5 and circulatory system disease with no threshold effect.PM_2.5 contributes to obvious acute, lag, cumulative, and harvesting effects on circulatory system disease. PM_2.5 was associated with the risk of daily ED admissions for circulatory system disease, hypertension, IHD, arrhythmia, HF, and CVE. Therefore, air quality management must be strengthened.

The effects of traffic-related air pollutants on chronic obstructive pulmonary disease in the community-based general population

Background

Previous studies have shown inconsistent results regarding the impact of traffic pollution on the prevalence of chronic obstructive pulmonary disease (COPD). Therefore, using frequency matching and propensity scores, we explored the association between traffic pollution and COPD in a cohort of 8284 residents in a major agricultural county in Taiwan.

Methods

All subjects completed a structured questionnaire interview and health checkups. Subjects with COPD were identified using Taiwan National Health Insurance Research Databases. A hybrid kriging/LUR model was used to identify levels of traffic-related air pollutants (PM_2.5 and O₃). Multiple logistic regression models were used to calculate the prevalence ratios (PRs) of COPD and evaluate the role played by traffic-related indices between air pollutants and COPD. The distributed lag nonlinear model was applied in the analysis; we excluded current or ever smokers to perform the sensitivity analysis.

Results

Increased PRs of COPD per SD increment of PM_2.5 were 1.10 (95% CI 1.05–1.15) and 1.25 (95% CI 1.13–1.40) in the population with age and sex matching as well as propensity-score matching, respectively. The results of the sensitivity analysis were similar between the single and two pollutant models. PM_2.5 concentrations were significantly associated with traffic flow including sedans, buses, and trucks (p < 0.01). The higher road area and the higher PM_2.5 concentrations near the subject’s residence correlated with a greater risk of developing COPD (p for interaction < 0.01).

Conclusions

Our results suggest that long-term exposure to traffic-related air pollution may be positively associated with the prevalence of COPD.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-021-01812-x.

Combined Effect of Hot Weather and Outdoor Air Pollution on Respiratory Health: Literature Review

Association between short-term exposure to ambient air pollution and respiratory health is well documented. At the same time, it is widely known that extreme weather events intrinsically exacerbate air pollution impact. Particularly, hot weather and extreme temperatures during heat waves (HW) significantly affect human health, increasing risks of respiratory mortality and morbidity. Concurrently, a synergistic effect of air pollution and high temperatures can be combined with weather–air pollution interaction during wildfires. The purpose of the current review is to summarize literature on interplay of hot weather, air pollution, and respiratory health consequences worldwide, with the ultimate goal of identifying the most dangerous pollution agents and vulnerable population groups. A literature search was conducted using electronic databases Web of Science, Pubmed, Science Direct, and Scopus, focusing only on peer-reviewed journal articles published in English from 2000 to 2021. The main findings demonstrate that the increased level of PM10 and O3 results in significantly higher rates of respiratory and cardiopulmonary mortality. Increments in PM2.5 and PM10, O3, CO, and NO2 concentrations during high temperature episodes are dramatically associated with higher admissions to hospital in patients with chronic obstructive pulmonary disease, daily hospital emergency transports for asthma, acute and chronic bronchitis, and premature mortality caused by respiratory disease. Excessive respiratory health risk is more pronounced in elderly cohorts and small children. Both heat waves and outdoor air pollution are synergistically linked and are expected to be more serious in the future due to greater climate instability, being a crucial threat to global public health that requires the responsible involvement of researchers at all levels. Sustainable urban planning and smart city design could significantly reduce both urban heat islands effect and air pollution.

Determining the effects of socioeconomic and environmental determinants on chronic obstructive pulmonary disease (COPD) mortality using geographically and temporally weighted regression model across Xi'an during 2014-2016

Numerous methods have been implemented to evaluate the relationship between environmental factors and respiratory mortality. However, the previous epidemiological studies seldom considered the spatial and temporal variation of the independent variables. The present study aims to detect the relations between respiratory mortality and related affecting factors across Xi'an during 2014-2016 based on a novel geographically and temporally weighted regression model (GTWR). Meanwhile, the ordinary least square (OLS) and the geographically weighted regression (GWR) models were developed for cross-comparison. Additionally, the spatial autocorrelation and Hot Spot analysis methods were conducted to detect the spatiotemporal dynamic of respiratory mortality. Some important outcomes were obtained. Socioeconomic and environmental determinants represented significant effects on respiratory diseases. The respiratory mortality exhibited an obvious spatial correlation feature, and the respiratory diseases tend to occur in winter and rural areas of the study area. The GTWR model outperformed OLS and GWR for determining the relations between respiratory mortality and socioeconomic as well as environmental determinants. The influence degree of anthropic factors on COPD mortality was higher than natural factors, and the effects of independent variables on COPD varied timely and locally. The results can supply a scientific basis for respiratory disease controlling and health facilities planning.

Preconception ambient temperature and preterm birth: a time-series study in rural Henan, China

Changes in the preconception ambient temperature (PAT) can affect the gametogenesis, disturbing the development of the embryo, but the health risks of PAT on the developing fetus are still unclear. Here, based on the National Free Preconception Health Examination Project in the rural areas of Henan Province, we evaluate the effects of PAT on preterm birth (PTB). Data of 1,231,715 records from self-reported interviews, preconception physical examination, early gestation follow-up, and postpartum follow-up were collected from 1 January 2013 to 31 December 2016. Generalized additive models were used to assess the cumulative and lag effects of PAT upon PTB. The significant cumulative effects of mean temperature within 2 weeks and 3 weeks on the risk of PTB, especially upon late PTB (34-36 weeks) (P < 0.05), were observed. Exposure to extreme heat (> 90th percentile) within 2 weeks (RR = 1.470) and 3 weeks (RR = 1.375) before conception could increase the risk of PTB. After stratifying PTB, exposure to extreme heat within 2 weeks before conception can increase the risks of early (< 34 weeks) and late PTB (P < 0.05). Besides, exposure to extreme cold (< 10th percentile) within 3 weeks or longer before conception can elevate the risk of PTB, especially late PTB. The significant lag effects of temperature changes on the risk of early PTB (lag-8 days or earlier) were observed. In conclusion, the risk of PTB was susceptible to PAT changes within 2 weeks or longer before conception. Our findings provide (i) guidance for rural couples to make pregnancy plans and (ii) scientific evidence for the government to formulate policies to prevent PTB.

Deep learning for predicting the occurrence of cardiopulmonary diseases in Nanjing, China

The efficiency of disease prevention and medical care service necessitated the prediction of incidence. However, predictive accuracy and power were largely impeded in a complex system including multiple environmental stressors and health outcome of which the occurrence might be episodic and irregular in time. In this study, we established four different deep learning (DL) models to capture inherent long-term dependencies in sequences and potential complex relationships among constituents by initiating with the original input into a representation at a higher abstract level. We collected 504,555 and 786,324 hospital outpatient visits of grouped categories of respiratory (RESD) and circulatory system disease (CCD), respectively, in Nanjing from 2013 through 2018. The matched observations in time-series that might pose risk to cardiopulmonary health involved conventional air pollutants concentrations and metrological conditions. The results showed that a well-trained network architecture built upon long short-term memory block and a working day enhancer achieved optimal performance by three quantitative statistics, i.e., 0.879 and 0.902 of Nash-Sutcliffe efficiency, 0.921% and 0.667% of percent bias, and 0.347 and 0.312 of root mean square error-standard deviation ratio for RESD and CCD hospital visits, respectively. We observed the non-linear association of nitrogen dioxide and ambient air temperature with CCD hospital visits. Furthermore, these two environmental stressors were identified as the most sensitive predictive variables, and exerted synergetic effect for two health outcomes, particular in winter season. Our study indicated that high-quality surveillance data of atmospheric environments could provide novel opportunity for anticipating temporal trend of cardiopulmonary health outcomes based on DL model.

Temporal cross-correlations between air pollutants and outpatient visits for respiratory and circulatory system diseases in Fuzhou, China

BACKGROUND

Previous studies have suggested that there is an association between air pollutants and circulatory and respiratory diseases; however, relatively few have analyzed the association between air pollutants and outpatient visits based on the mortality, hospitalization rates, etc., especially in areas with relatively good air quality. Therefore, we conducted this study to research the association between air pollutants and outpatient visits in Fuzhou, China.

METHODS

We used a generalized linear Poisson model to study the association between air pollution and outpatient visits for respiratory and circulatory diseases from 2016 to 2018 in Fuzhou, China.

RESULTS

In the single pollutant model, nitrogen dioxide (NO2) had a significant effect. For lag day 0 to lag day 5, the effect decreased with every 10 μg/L increase in NO2. The daily maximum 8-h mean ozone (O3-8h) and upper respiratory outpatient visits were positively associated during the cold period [lag2, excess risk (ER) (95% confidence interval (CI)): 1.68% (0.44-2.94%)], while O3-8h and respiratory disease were positively associated during the warm period [lag5, ER (95% CI): 1.10% (0.11-2.10%) and lag4, ER (95% CI): 1.02% (0.032-2.02%)]. Similarly, particulate matter (PM) with an average aerodynamic diameter of less than 10 μm (PM10) and lower respiratory diseases were positively associated during the warm period [lag0, ER (95% CI): 1.68% (0.44-2.94%)]. When the concentration of O3-8h was higher than 100 μg/L, there was a positive effect on circulatory [lag5, ER (95% CI): 2.83% (0.65-5.06%)], respiratory [lag5, ER (95% CI): 2.47% (0.85-4.11%)] and upper respiratory [lag5, ER (95% CI): 3.06% (1.38-4.77%)] outpatient visits. The variation in O3-8h changed slightly when we adjusted for other air pollutants, and after adjusting for O3-8h, the ERs of the other air pollutants changed slightly. After adjusting for PM with an average aerodynamic diameter of less than 2.5 μm (PM2.5), the ERs of the other air pollutants increased, and after adjusting for NO2, the ER of PM decreased.

CONCLUSION

Exposure to ambient NO2, O3, PM2.5 and PM10 was associated with an increase in respiratory and circulatory system-related outpatient visits in Fuzhou, China.

Unexpected association between increased levels of ambient carbon monoxide and reduced daily outpatient visits for vaginitis: A hospital-based study

Carbon monoxide (CO) is a well-known "toxic gas". It represents a toxic inhalation hazard at high concentration and is commonly found in polluted air. However, a series of recent studies have suggested that low concentration of CO can also produce protective functions. This study was performed to investigate the association between ambient CO exposure and vaginitis outpatient visits. Daily baseline outpatient data of vaginitis from January 1, 2013 to December 31, 2015 were obtained from Xi'an, a heavily-polluted metropolis in China. The over-dispersed Poisson generalized additive model was applied to discover the relations between short-term ambient CO exposure and the number of vaginitis outpatient visits by adjusting day of the week and weather conditions. A total of 16,825 outpatient hospital visits for vaginitis were recorded. The mean daily concentration of carbon monoxide (CO) was well below Chinese and WHO guidelines. During the study period, increased levels of ambient CO was associated with reduced outpatient-visits through concurrent to lag 5 days, and the most significant association was evidenced at lag 05. A 0.1 mg/m³ increase in daily average CO at lag 05 corresponded to -1.25% (95%CI: -1.85%, -0.65%) change in outpatient-visits for vaginitis. Moreover, the association was more significant in those women aged 20-29 years. After adjustment for PM₁₀, PM_2.5, SO₂, and NO₂, and O₃, the negative associations of CO with vaginitis kept significant, suggesting relative stability of effect estimates. In summary, this is the first evidence that increased ambient CO exposure can be related to reduced daily outpatient visits for vaginitis. The results of our study may not only help to establish more comprehensive understanding of the health effects of ambient air on vaginitis and other gynecological diseases, but also provide a clue to new potential interventions.

Association of air pollution with outpatient visits for respiratory diseases of children in an ex-heavily polluted Northwestern city, China

BACKGROUND

A great number of studies have confirmed that children are a particularly vulnerable population to air pollution.

METHODS

In the present study, 332,337 outpatient visits of 15 hospitals for respiratory diseases among children (0-13 years), as well as the simultaneous meteorological and air pollution data, were obtained from 2014 to 2016 in Lanzhou, China. The generalized additive model was used to examine the effects of air pollutants on children's respiratory outpatient visits, including the stratified analysis of age, gender and season.

RESULTS

We found that PM_2.5, NO₂ and SO₂ were significantly associated with the increased total respiratory outpatient visits. The increments of total respiratory outpatient visits were the highest in lag 05 for NO₂ and SO₂, a 10 μg/m³ increase in NO₂ and SO₂ was associated with a 2.50% (95% CI: 1.54, 3.48%) and 3.50% (95% CI: 1.51, 5.53%) increase in total respiratory outpatient visits, respectively. Those associations remained stable in two-pollutant models. Through stratification analysis, all air pollutants other than PM₁₀ were significantly positive associated with the outpatients of bronchitis and upper respiratory tract infection. Besides, both NO₂ and SO₂ were positively related to the pneumonia outpatient visits. PM_2.5 and SO₂ were significantly related to the outpatient visits of other respiratory diseases, while only NO₂ was positively associated with the asthma outpatients. We found these associations were stronger in girls than in boys, particularly in younger (0-3 years) children. Interestingly, season stratification analysis indicated that these associations were stronger in the cold season than in the transition or the hot season for PM₁₀, PM_2.5 and SO₂.

CONCLUSIONS

Our results indicate that the air pollution exposure may account for the increased risk of outpatient visits for respiratory diseases among children in Lanzhou, particularly for younger children and in the cold season.

Short-term associations between ambient fine particulate matter pollution and hospital visits for chronic obstructive pulmonary disease in Yinzhou District, China

Ambient particulate matter is one of the main risk factors of chronic obstructive pulmonary disease (COPD) in developing countries. However, the studies were scant in China concerning the health effects of the fine particulate matter (PM_2.5; particulate matter ≤ 2.5 μm in diameter) on hospital visits for COPD. We applied a generalized additive model (GAM) to calculate relative risks (RRs) with 95% confidence intervals (CIs) for the associations between hospital visits for COPD and an interquartile range (24.50 μg/m³) increment of ambient PM_2.5 concentrations in Yinzhou District between 2016 and 2018. The ambient PM_2.5 concentration was positively associated with hospital visits for COPD at a distributed lag of 0-7 days (RR = 1.073, 95% CI, 1.016, 1.133). In the stratified analysis, we found that the association between ambient PM_2.5 and COPD was stronger during the warm season (April to September) than that during the cold season (October to March), but we did not observe statistically significant differences in age groups (< 60 years and ≥ 60 years) or gender groups (male and female) related to the effects of PM_2.5. The associations between ambient PM_2.5 and COPD became partially attenuated after the adjustment for gaseous pollutants in subgroups. Our findings could provide evidence that regulations for controlling both PM_2.5 and gaseous pollutants should be implemented to protect the overall population.

Particulate matter pollution and hospital outpatient visits for endocrine, digestive, urological, and dermatological diseases in Nanjing, China

Clinical or pathological evidence demonstrated that air pollution could undermine other organ systems of human body besides respiratory and circulation systems. Investigations that directly relate hospital outpatient visits for endocrine (ENDO), digestive (DIGE), urological (UROL), and dermatological (DERM) diseases categories with ambient particulate matter (PM) are still lacking, particularly in heavily polluted cities. Here, we conducted a time-series analysis using 812,624, 1,111,342, 539,803, and 741,662 hospital visits for ENDO, DIGE, UROL, and DERM, respectively, in Nanjing, China from 2013 to 2019. A generalized additive model was applied to estimate the exposure-response associations. Results showed that a 10 μg/m³ increase in PM_2.5 concentration on lag 0 day was significantly associated with 0.59% (95% CI: 0.30%, 0.88%), 0.43% (0.15%, 0.70%), 0.36% (0.06%, 0.66%), and 0.65% (0.42%, 0.87%) increase for ENDO, DIGE, UROL, and DERM hospital visits, respectively. The estimated effects of PM₁₀ were slightly smaller but still statistically significant. The magnitude and significance of the associations between PM and four health outcomes were sensitive to additional adjustment for co-pollutants. Exposure-response relationships were linear for PM concentrations lower than 100 μg/m³ but the curves became nonlinear across the full range of exposures due to a flatten slope at higher concentrations. We also explored the effect modifications by season (cold or warm), age (5-18, 18-64, 65-74, or 75+ years), and sex (male or female). Results showed that the DERM-related population aged 65 years or older was more vulnerable to PM exposure, compared with the 5 to 17-year age group; the DERM-related population aged 75 years or older and 65 years or older was more vulnerable to PM_2.5 and PM₁₀ exposure, respectively, compared with the 18 to 64-year age group. Our study provided suggestive evidence that ambient PM pollution was associated with ENDO, DIGE, UROL, and DERM outpatient hospital visits in Nanjing, China.

Effect modification of the short-term effects of air pollution on morbidity by season: A systematic review and meta-analysis

Studies of the health effects of air pollution have traditionally controlled for ambient temperature as a confounder, and vice versa. However, season might be an important factor contributing to adverse health effects of air pollution. Given the current inconsistencies in results of previous studies on the effect modification of air pollution on morbidity by season, a systematic review and meta-analysis was conducted to synthesize the current evidence on effects of season on air pollution and morbidity. The electronic databases including PubMed, Web of Science, Embase, CNKI, and Wanfang were used to identify papers published up to the 30st of November in 2019. We identified 4284 articles, after screening, eighty papers met the inclusion criteria. Significant effect modification of CO, O₃, SO₂ and NO₂ on morbidity by season was observed, with corresponding ratio of relative risk of 1.0009 (95% CI: 1.0001-1.0018), 1.0080 (95% CI: 1.0021-1.0138), 0.9828 (95% CI: 0.9697-0.9962) and 0.9896 (95% CI: 0.9824-0.9968), respectively. Season significantly modified the effect of CO on pneumonia, the effect of SO₂ on cardiovascular disease, the effect of PM₁₀ on stroke, and the effect of O₃ on stroke, asthma and pneumonia. The effect modifications of air pollution by season were similar among males and females, while the effect estimates seem to be higher among children under 18 years old and the elderly aged 75 or over. Further research is needed to better understand the mechanisms underlying the seasonal variance of the effect of air pollutants on morbidity.

Ambient PM2.5 caused cardiac dysfunction through FoxO1-targeted cardiac hypertrophy and macrophage-activated fibrosis in mice

Plenty of epidemiological evidences have shown that ambient particulate matter (PM2.5) exposure increased the prevalence of cardiovascular disease, but the potential mechanism has not been known clearly. We established mice models by ambient PM2.5 exposure system to explore the adverse effects of PM2.5 on cardiac function in mice. Forty-eight C57BL/6 mice were randomly divided into 3 groups and exposed to filtered air (FA), unfiltered air (UA) and concentrated PM2.5 air (CA) for 8 or 16 weeks, 6 hours per day, 7 days per week, respectively. The changes of cardiac structure and function, histological analysis and related mechanism were investigated. The main manifestations of cardiac structure were cardiac hypertrophy and fibrosis in a dose- and time-dependent manner after PM2.5 exposure, which led to the decrease of cardiac systolic function. Cardiac hypertrophy in mice might be regulated by PI3K/Akt/FoxO1 signal. Cardiac fibrosis might be attributed to inflammatory infiltration caused by macrophage activation. Consequently, our data indicated that cardiac hypertrophy and fibrosis might be important factors of PM2.5-induced cardiac dysfunction in mice.

Estimating health burden and economic loss attributable to short-term exposure to multiple air pollutants in China

Existing studies focused on the evaluation of health burden of long-term exposure to air pollutants, whereas limited information is available on short-term exposure, particularly in China. Air pollutant concentrations in 338 Chinese cities in 2017 were used to estimate the air pollutants related health burden which was defined as premature mortalities from all-cause, cardiovascular and respiratory disease as well as hospital admissions for cardiovascular and respiratory disease. Log-linear model was used as the exposure-response function to estimate the health burden attributable to each air pollutant. The value of statistical life and cost of illness methods were used to estimate economic loss of the premature mortalities and hospital admissions, respectively. The national all-cause premature mortalities attributable to all air pollutants was 1.35 million, accounting for 17.2% of reported deaths in China in 2017. Among all-cause premature mortality, contributions of PM_2.5, PM_2.5-10, NO₂, SO₂, O₃ and CO were11.1%, 5.2%, 28.9%, 9.6%, 23.0%, and 22.2%, respectively. The national cardiovascular and respiratory premature mortalities were 0.77 and 0.21 million, respectively. About 7.8 million cardiovascular and respiratory disease hospital admissions were attributed to short-term exposure to all air pollutants. The economic loss of the overall health burden (premature mortality and hospital admissions) was 2065.54 billion Yuan, which was equivalent to 2.5% of the national GDP in 2017. The health burden and economic loss attributable to short-term exposure to ambient air pollutant are substantial in China. It suggested that the adverse health effects attributable to short-term exposure to air pollutant should not be neglected in China. In order to reduce the health impact of air pollution, each city should develop air pollution prevention and control measures based on existing scientific evidence.

The Impact of PM2.5 on the Host Defense of Respiratory System

The harm of fine particulate matter (PM_2.5) to public health is the focus of attention around the world. The Global Burden of Disease (GBD) Study 2015 (GBD 2015 Risk Factors Collaborators, 2016) ranked PM_2.5 as the fifth leading risk factor for death, which caused 4.2 million deaths and 103.1 million disability-adjusted life-years (DALYs) loss, representing 7.6% of total global deaths and 4.2% of global DALYs. Epidemiological studies have confirmed that exposure to PM_2.5 increases the incidence and mortality of respiratory infections. The host defense dysfunction caused by PM_2.5 exposure may be the key to the susceptibility of respiratory system infection. Thus, this review aims to assess the impact of PM_2.5 on the host defense of respiratory system. Firstly, we elaborated the epidemiological evidence that exposure to PM_2.5 increases the risk of respiratory infections. Secondly, we summarized the experimental evidence that PM_2.5 exposure increases the susceptibility of different pathogens (including bacteria and viruses) in respiratory system. Furthermore, here we discussed the underlying host defense mechanisms by which PM_2.5 exposure increases the risk of respiratory infections as well as future perspectives.