Ambient air pollution and daily hospital admissions for respiratory system-related diseases in a heavy polluted city in Northeast China

Sources-attributed contributions to health risks associated with PM2.5-bound polycyclic aromatic hydrocarbons during the warm and cold seasons in an urban area of Eastern Asia

Despite the well-established recognition of the health hazards posed by PM2.5-bound PAHs, a comprehensive understanding of their source-specific impact has been lacking. In this study, the health risks associated with PM2.5-bound polycyclic aromatic hydrocarbons (PAHs) and source-specific contributions were investigated in the urban region of Taipei during both cold and warm seasons. The levels of PM2.5-bound PAHs and their potential health risks across different age groups of humans were also characterized. Diagnostic ratios and positive matrix factorization analysis were utilized to identify the sources of PM2.5-bound PAHs. Moreover, potential source contribution function (PSCF), concentration-weighted trajectory (CWT) and source regional apportionment (SRA) analyses were employed to determine the potential source regions. Results showed that the total PAHs (TPAHs) concentrations ranged from 0.08 to 2.37 ng m-3, with an average of 0.69 ± 0.53 ng m-3. Vehicular emissions emerged as the primary contributor to PM2.5-bound PAHs, constituting 39.8 % of the TPAHs concentration, followed by industrial emissions (37.6 %), biomass burning (13.8 %), and petroleum/oil volatilization (8.8 %). PSCF and CWT analyses revealed that industrial activities and shipping processes in northeast China, South China Sea, Yellow Sea, and East China Sea, contributed to the occurrence of PM2.5-bound PAHs in Taipei. SRA identified central China as the primary regional contributor of ambient TPAHs in the cold season and Taiwan in the warm season, respectively. Evaluations of incremental lifetime cancer risk demonstrated the highest risk for adults, followed by children, seniors, and adolescents. The assessments of lifetime lung cancer risk showed that vehicular and industrial emissions were the main contributors to cancer risk induced by PM2.5-bound PAHs. This research emphasizes the essential role of precisely identifying the origins of PM2.5-bound PAHs to enhance our comprehension of the related human health hazards, thus providing valuable insights into the mitigation strategies.

Gelato: a new hybrid deep learning-based Informer model for multivariate air pollution prediction

The increase in air pollutants and its adverse effects on human health and the environment has raised significant concerns. This implies the necessity of predicting air pollutant levels. Numerous studies have aimed to provide new models for more accurate prediction of air pollutants such as CO2, O3, and PM2.5. Most of the models used in the literature are deep learning models with Transformers being the best for time series prediction. However, there is still a need to enhance accuracy in air pollution prediction using Transformers. Alongside the need for increased accuracy, there is a significant demand for predicting a broader spectrum of air pollutants. To encounter this challenge, this paper proposes a new hybrid deep learning-based Informer model called "Gelato" for multivariate air pollution prediction. Gelato takes a leap forward by taking several air pollutants into consideration simultaneously. Besides introducing new changes to the Informer structure as the base model, Gelato utilizes Particle Swarm Optimization for hyperparameter optimization. Moreover, XGBoost is used at the final stage to achieve minimal errors. Applying the proposed model on a dataset containing eight important air pollutants, including CO2, O3, NO, NO2, SO2, PM10, NH3, and PM2.5, the Gelato performance is assessed. Comparing the results of Gelato with other models shows Gelato's superiority over them, proving it is a high-confidence model for multivariate air pollution prediction.

Association between short-term exposure to ambient air pollution and upper respiratory tract infection in Kunshan

The health effects of air pollution have become a major public health problem. Studies on the relationship between short-term exposure to air pollutants and upper respiratory tract infection (URTI) related clinic visits and expenditures were scarce. From January 1, 2019, to December 31, 2021, we included all the URTI cases that turned to 11 public hospitals in Kunshan, and summarized individual medical cost. Daily meteorological factors and 24-h mean concentrations of four common air pollutants, including particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5) and 10 μm (PM10), sulfur dioxide (SO2), and nitrogen dioxide (NO2), were consecutively recorded. Generalized additive regression model was adopted to quantify the associations between each air pollutant and the daily clinic visits of URTI cases. We further calculated attributable number (AN) and attributable fraction, and performed sensitivity analysis by gender, age, and season. A total of 934,180 cases were retrieved during the study period. PM2.5, PM10, SO2, and NO2 showed significant associations with hospital visits and expenditures due to URTI. Relative risks for them were 1.065 (95% confidence interval [CI] 1.055, 1.076), 1.045 (95% CI 1.037, 1.052), 1.098 (95% CI 1.038, 1.163), and 1.098 (95% CI 1.085, 1.111) on lag 0-5 days, respectively. Thirty-one thousand four hundred fifty-five (95% CI 27,457, 35,436) cases could be ascribed to increased NO2 and accounted for 3.37% (95% CI 2.94%, 3.79%) of all clinic visits. Sensitivity analyses indicated that the effects of air pollution were generally consistent for male and female. PM2.5, PM10, and NO2 had stronger associations among people aged ≤ 18 years, followed by those aged 19-64 years and ≥ 65 years. The association strengths of air pollution varied seasonally. Short-term exposure to ambient air pollutants had significant associations with clinic visits and expenditures owing to URTI. Children and adolescents appeared to be more susceptible to adverse health effects of air pollution. NO2 may be a priority when formulating pollution control measures.

A novel approach for forecasting PM2.5 pollution in Delhi using CATALYST

Air pollution is one of the main environmental issues in densely populated urban areas like Delhi. Predictions of the PM2.5 concentration must be accurate for pollution reduction strategies and policy actions to succeed. This research article presents a novel approach for forecasting PM2.5 pollution in Delhi by combining a pre-trained CNN model with a transformer-based model called CATALYST (Convolutional and Transformer model for Air Quality Forecasting). This proposed strategy uses a mixture of the two models. To derive attributes of the PM2.5 timeline of data, a pre-existing CNN model is utilized to transform the data into visual representations, which are analyzed subsequently. The CATALYST model is trained to predict future PM2.5 pollution levels using a sliding window training approach on extracted features. The model is utilized for analyzing temporal dependencies in PM2.5 time-series data. This model incorporates the advancements in the transformer-based architecture initially designed for natural language processing applications. CATALYST combines positional encoding with the Transformer architecture to capture intricate patterns and variations resulting from diverse meteorological, geographical, and anthropogenic factors. In addition, an innovative approach is suggested for building input-output couples, intending to address the problem of missing or partial data in environmental time-series datasets while ensuring that all training data blocks are comprehensive. On a PM2.5 dataset, we analyze the proposed CATALYST model and compare its performance with other standard time-series forecasting approaches, such as ARIMA and LSTM. The outcomes of the experiments demonstrate that the suggested model works better than conventional methods and is a potential strategy for accurately forecasting PM2.5 pollution. The applicability of CATALYST to real-world scenarios can be tested by running more experiments on real-world datasets. This can help develop efficient pollution mitigation measures, impacting public health and environmental sustainability.

Temperature modifies the effects of air pollutants on respiratory diseases

Increasing studies have reported temperature modification effects on air pollutants-induced respiratory diseases. In the current study, daily data of respiratory emergency room visits (ERVs), meteorological factors, and concentrations of air pollutants were collected from 2013 to 2016 in Lanzhou, a northwest city in China. Daily average temperature was stratified into low (≤ 25 percentile, P₂₅), medium (25-75 percentile, P₂₅-P₇₅) and high (≥ 75 percentile, P₇₅) to explore how temperature modifies the effects of air pollutants (PM_2.5, PM₁₀, SO₂, and NO₂) on respiratory ERVs by using generalized additive Poisson regression model (GAM). Seasonal modification was also investigated. Results showed that (a) PM₁₀, PM_2.5, and NO₂ had the strongest effects on respiratory ERVs in low temperature; (b) males and 15-and-younger were more vulnerable in low temperature while females and those older than 46 years were highly affected in high temperature; (c) PM₁₀, PM_2.5, and NO₂ were mostly associated with the total and both males and females in winter, while SO₂ resulted in the highest risk for the total and males in autumn and females in spring. In conclusion, this study found significant temperature modification effects and seasonal differences on the risks of respiratory ERVs due to air pollutants in Lanzhou, China.

Associations between air pollutants and hospital admissions for chronic obstructive pulmonary disease in Jinan: potential benefits from air quality improvements

Evidence between air pollution and chronic obstructive pulmonary disease (COPD) is inconsistent and limited in China. In this study, we aim to examine the associations between air pollutants and hospital admissions for COPD, hoping to provide practical advice for prevention and control of COPD. Hospital admissions for COPD were collected from a Grade-A tertiary hospital in Jinan from 2014 to 2020. A generalized additive model (GAM) was used to examine the associations between air pollutants and hospital admissions for COPD. Stratified analysis was also conducted for gender, age (20-74 and ≥75 years), and season (warm and cold). The avoidable number of COPD hospital admissions was calculated when air pollutants were controlled under national and WHO standards. Over the study period, a total of 4,012 hospital admissions for COPD were recorded. The daily hospital admissions of COPD increased by 2.36% (95%CI: 0.13-4.65%) and 2.39% (95%CI: 0.19-4.65%) for per 10 μg/m³ increase of NO₂ and SO₂ concentrations at lag2, respectively. There was no statistically significant difference in health effects caused by increased concentrations of PM_2.5, PM₁₀, CO, and O₃. The health effects of increased SO₂ concentration were stronger in women, the ≥75 years old people and the cold season. About 2 (95%CI: 0-3), 64 (95%CI: 4-132) and 86 (95%CI: 6-177) COPD admissions would be avoided when the SO₂ concentration was controlled below the NAAQS-II (150 μg/m³), NAAQS-I (50 μg/m³), and WHO's AQG2021 standard (40 μg/m³), respectively. These findings suggest that short-term exposure to NO₂ and SO₂ was associated with increased risks of daily COPD admissions, especially for females and the elderly. The control of SO₂ and NO₂ under the national and WHO standards could avoid more COPD admissions and obtain greater health benefits.

Association of air pollutants and hospital admissions for respiratory diseases in Lanzhou, China, 2014-2019

The aim of this study was to assess the effects of air pollutants on hospital admissions for respiratory disease (RD) by using distributed lag nonlinear model (DLNM) in Lanzhou during 2014-2019. In this study, the dataset of air pollutants, meteorological, and daily hospital admissions for RD in Lanzhou, from January 1st, 2014 to December 31st, 2019, were collected from three national environmental monitoring stations, China meteorological data service center, and three large general hospitals, respectively. A time-series analysis with DLNM was used to estimate the associations between air pollutants and hospital admissions for RD including the stratified analysis of age, gender, and season. The key findings were expressed as the relative risk (RR) with a 95% confidence interval (CI) for single-day and cumulative lag effects (0-7). A total of 90, 942 RD hospitalization cases were identified during the study period. The highest association (RR, 95% CI) of hospital admissions for RD and PM_2.5 (1.030, 1.012-1.049), and PM₁₀ (1.009, 1.001-1.015), and NO₂ (1.047, 1.024-1.071) were observed at lag 07 for an increase of 10 μg/m³ in the concentrations, and CO at lag07 (1.140, 1.052-1.236) for an increase of 1 mg/m³ in the concentration. We observed that the RR estimates for gaseous pollutants (e.g., CO and NO₂) were larger than those of particulate matter (e.g., PM_2.5 and PM₁₀). The harmful effects of PM_2.5, PM₁₀, NO₂, and CO were greater in male, people aged 0-14 group and in the cold season. However, no significant association was observed for SO₂, O₃8h, and total hospital admissions for RD. Therefore, some effective intervention strategies should be taken to strengthen the treatment of the ambient air pollutants, especially gaseous pollutants (e.g., CO and NO₂), thereby, reducing the burden of respiratory diseases.

Environmental pollution in North-Eastern Italy and its influence on chronic obstructive pulmonary disease: time series modelling and analysis using visibility graphs

The impact on human health from environmental pollution is receiving increasing attention. In the case of respiratory diseases such as chronic obstructive pulmonary disease (COPD), the relationship is now well documented. However, few studies have been carried out in areas with low population density and low industrial production, such as the province of Belluno (North-Eastern Italy). The aim of the study was to analyze the effect of exposure to certain pollutants on the temporal dynamics of hospital admissions for COPD in the province of Belluno. Daily air pollution concentration, humidity, precipitations, and temperature were collected from the air monitoring stations in Belluno. Generalized additive mixed models (GAMM) and visibility graphs were used to determine the effects of the short-term exposure to environmental agents on hospital admissions associated to COPD. In the case of the city of Belluno, the GAMM showed that hospital admissions were associated with NO₂, PM₁₀, date, and temperature, while for the city of Feltre, GAMM produced no associated variables. Several visibility graph indices (average edge overlap and interlayer mutual information) showed a significant overlap between environmental agents and hospital admission for both cities. Our study has shown that visibility graphs can be useful in establishing associations between environmental agents and COPD hospitalization in sparsely populated areas.

Evaluation of the efficiency of a Venturi scrubber in particulate matter collection smaller than 2.5 µm emitted by biomass burning

Energy demand has increased worldwide, and biomass burning is one of the solutions most used by industries, especially in countries that have a great potential in agriculture, such as Brazil. However, these energy sources generate pollutants, consisting of particulate matter (PM) with a complex chemical composition, such as sugarcane bagasse (SB) burning. Controlling these emissions is necessary; therefore, the aim was to evaluate PM collection using a rectangular Venturi scrubber (RVS), and its effects on the composition of the PM emitted. Considering the appropriate use of biomass as an industrial fuel and the emerging need for a technique capable of efficiently removing pollutants from biomass burning, this study shows the control of emissions as an innovation in a situation such as the industrial one with the use of a Venturi scrubber in fine particle collection, in addition to using portable and representative isokinetic sampling equipment of these particles. The pilot-scale simulation of the biomass burning process, the representative sampling of fine particles and obtaining parameters to control pollutant emissions for a Venturi scrubber, meets the current situation of concern about air quality. The average collection efficiency values were 96.6% for PM_{> 2.5}, 85.5% for PM_1.0-2.5, and 66.9% for PM_{< 1.0}. The ionic analysis for PM_{< 1.0} filters showed potassium, chloride, nitrate, and nitrite at concentrations ranging from 20.12 to 36.5 μg/m³. As the ethanol and sugar plants will continue to generate electricity with sugarcane bagasse burning, emission control technologies and cost-effective and efficient portable samplers are needed to monitor particulate materials and improve current gas cleaning equipment projects.

Natural and human factors influencing urban particulate matter concentrations in central heating areas with long-term wearable monitoring devices

In northern China, central heating, as an important source of urban particulate matter (UPM), causes more than half of the air pollution during the heating season and has significant spatial-temporal heterogeneity. Owing to the limitations of stationary air monitoring networks, few studies distinguish between heating/non-heating seasons and few have been conducted in urban areas. However, fixed monitoring cannot accurately capture the dynamic exposure of residents to UPM, and there is a lack of comprehensive evaluation of the factors affecting UPM. Therefore, this study used wearable Sniffer 4D equipment to monitor the concentrations of UPM (PM₁, PM_2.5, and PM₁₀) in selected typical areas of Shenyang City from March 2019 to February 2020. A random forest model was combined with land use and point-of-interest data to analyze the contributions and marginal effects of multiple influences on UPM, in both heating and non-heating seasons. The results showed that in the eastern part of the study area, UPM showed completely opposite spatial distribution characteristics during the two seasons. The concentrations of UPM were higher during the heating season than during the non-heating season. The results indicated that temperature and humidity were important factors in diffusing UPM. The production and operation of boilers were important for the production of UPM. In two-dimensional landscape pattern indices, the percentage of forest and Shannon diversity index were the first and second most important factors, respectively. The three-dimensional pattern of buildings had important effects on the transport and diffusion of UPM (landscape height range >100, floor area ratio >1.3, and landscape volume density >5). Wearable devices could monitor the real situation of residents' exposure to UPM and quantify the factors influencing the spatial-temporal distribution of UPM in an ecological sense. These results provide a scientific basis for urban planning and for health risk reduction for residents.

Ambient air pollution, temperature and hospital admissions due to respiratory diseases in a cold, industrial city

Background

The influences of air pollution exposure and temperature on respiratory diseases have become major global health concerns. This study investigated the relationship between ambient air pollutant concentrations and temperature in cold industrial cities that have the risk of hospitalization for respiratory diseases.

Methods

A time-series study was conducted in Changchun, China, from 2015 to 2019 to analyse the number of daily admissions for respiratory diseases, air pollutant concentrations, and meteorological factors. Time-series decomposition was applied to analyse the trend and characteristics of the number of admissions. Generalized additive models and distributed lag nonlinear models were constructed to explore the effects of air pollutant concentrations and temperature on the number of admissions.

Results

The number of daily admissions showed an increasing trend, and the seasonal fluctuation was obvious, with more daily admissions in winter and spring than in summer and autumn. There were positive and gradually decreasing lag effects of PM10, PM2.5, NO₂, and CO concentrations on the number of admissions, whereas O₃ showed a J-shaped trend. The results showed that within the 7-day lag period, 0.5°C was the temperature associated with the lowest relative risk of admission due to respiratory disease, and extremely low and high temperatures (<-18°C, >27°C, respectively) increased the risk of hospitalization for respiratory diseases by 8.3% and 12.1%, respectively.

Conclusions

From 2015 to 2019, respiratory diseases in Changchun showed an increasing trend with obvious seasonality. The increased concentrations of SO₂, NO₂, CO, PM2.5, O₃ and PM10 lead to an increased risk of hospitalization for respiratory diseases, with a significant lag effect. Both extreme heat and cold could lead to increases in the risk of admission due to respiratory disease.

Outdoor particulate matter exposure and upper respiratory tract infections in children and adolescents: A systematic review and meta-analysis

BACKGROUND

While the relationship between outdoor particulate matter (PM) and lower respiratory tract infections in children and adolescents is accepted, we know little about the impacts of outdoor PM on the risk of developing or aggravating upper respiratory tract infections (URTIs).

METHODS

We aimed to review the literature examining the relationship between outdoor PM exposure and URTIs in children and adolescents. A systematic search of EMBASE, MEDLINE, PubMed, Scopus, CINAHL and Web of Science databases was undertaken on April 3, 2020 and October 27, 2021. Comparable short-term studies of time-series or case-crossover designs were pooled in meta-analyses using random-effects models, while the remainder of studies were combined in a narrative analysis. Quality, risk of bias and level of evidence for health effects were appraised using a combination of emerging frameworks in environmental health.

RESULTS

Out of 1366 articles identified, 34 were included in the systematic review and 16 of these were included in meta-analyses. Both PM_2.5 and PM₁₀ levels were associated with hospital presentations for URTIs (PM_2.5: RR = 1.010, 95%CI = 1.007-1.014; PM₁₀: RR = 1.016, 95%CI = 1.011-1.021) in the meta-analyses. Narrative analysis found unequivocally that total suspended particulates were associated with URTIs, but mixed results were found for PM_2.5 and PM₁₀ in both younger and older children.

CONCLUSION

This study found some evidence of associations between PM and URTIs in children and adolescents, the relationship strength increased with PM₁₀. However, the number of studies was limited and heterogeneity was considerable, thus there is a need for further studies, especially studies assessing long-term exposure and comparing sources.

Short-term effects of gaseous air pollutants on outpatient visits for respiratory diseases: a case-crossover study in Baotou, China

Air pollution is a major public health problem throughout the world. Although there have been several studies in this field, most of them have focused on particulate matter and only covered a few key cities. This study aimed to assess a potential association between exposure to gaseous air pollutants and outpatient visits for respiratory diseases in Baotou, China. Daily outpatient visits for respiratory diseases and daily averages of air pollutants and meteorological parameters from 2015 to 2020 were obtained. Time-stratified case-crossover design and restricted cubic splines were used to perform the analyses. Stratified analyses were performed in different hospital departments and districts. Significant association between the concentrations of air pollutants and outpatient visits for respiratory diseases was observed. The odds ratios of outpatient visits for respiratory diseases associated with per 10 μg/m³ increases in concentrations of NO₂ and SO₂, and per 10 mg/m³ increases in concentrations of CO were 1.033 (95% CI: 1.018 to 1.049), 0.965 (95% CI: 0.954 to 0.976), and 1.038 (95% CI: 1.006 to 1.071), respectively. Short-term exposure to NO₂, SO₂, and CO was positively associated with outpatient visits for respiratory diseases, with stronger effects among children. The relationship between O₃ and respiratory diseases varied at different concentrations.

Association between air pollution and hospital admissions for chronic respiratory disease in people aged over 65 years: a time series analysis in Ningbo, China, 2015-2017

PURPOSE

To provide essential information of environmental triggers leading to CRD.

METHODS

We investigated the short-term effects of ambient air pollutants on CRD-related hospitalizations in people aged ≥ 65 years in Ningbo. Data on 23,610 cases of CRD requiring hospitalization were collected from January 2015 to August 2017. After adjusting for temporal trends, seasonality, meteorological conditions, day of week (DOW), and public holidays, we used generalized additive Poisson distribution models to calculate the excess risks (ERs) and 95% confidence intervals (95% CIs) of CRD related hospitalizations.

RESULTS

Our results showed that fine particulate matter (PM_2.5), inhalable particulate matter (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and carbon monoxide (CO) were associated with CRD-related hospitalizations in people aged ≥ 65 years. We observed that each 10 μg/m³ increase (except for each 0.1 mg/m³ increase in CO) in the concentration of air pollutants, the percentage of CRD-related hospitalizations due to PM_2.5, PM₁₀, and SO₂ exposure at lag 07, NO₂ exposure at lag 03, and CO exposure at lag 0 increased by 2.13% (95% CI: 0.55%, 3.74%), 1.76% (95% CI: 0.70%, 2.83%), 8.24% (95% CI: 0.92%, 16.09%), 2.16% (95% CI: 0.26%, 4.05%), and 1.19% (95% CI: 0.26%, 2.12%), respectively. In addition, we found stronger effects of particulate matter in 75-84 years age group, on warmer days, and in asthmatics.

CONCLUSION

In conclusion, air pollution may have adverse effects on CRD-related hospitalizations among people aged ≥ 65 years in Ningbo. Therefore, public health measures should be taken to improve air quality.

Asian dust storms result in a higher risk of the silicosis hospital admissions

PURPOSE

Previous studies found that silicosis was majorly associated with occupation-related risks. However, little evidence was available to clarify the relation between Asian dust storm (ADS) and silicosis hospital admissions. This present paper aims to investigate the association between ADS events and hospital admissions for silicosis.

METHODS

We applied a Poisson time-series regression on the 2000-2012 National Health Insurance Research Database in Taiwan, linking air quality data and ambient temperature data to estimate the impact of ADS on silicosis hospital admissions in the age-specific groups.

RESULTS

A total of 2154 hospital admissions were recorded for silicosis in Taiwan, for a daily average number of 0.45. The number rises from 0.43 on a day without ADS to 0.70 on the outbreak day and continues increasing to 0.83 one day after outbreak. Among patients under 45, the effect of ADS appears on the event day as well as several post-event days (lag2-6) at the significant level of p < 0.1. There is also a significant lag effect on post-event day 2 (p < 0.05) for those aged above 74.

CONCLUSION

Asian dust storms do result in a rise of silicosis hospital admissions, particularly for those above 74, those under 45, and for females.

Association Between Sulfur Dioxide and Daily Inpatient Visits With Respiratory Diseases in Ganzhou, China: A Time Series Study Based on Hospital Data

Background

Sulfur dioxide (SO₂) has been reported to be related to the mortality of respiratory diseases, but the relationship between SO₂ and hospital inpatient visits with respiratory diseases and the potential impact of different seasons on this relationship is still unclear.

Methods

The daily average concentrations of air pollutants, including SO₂ and meteorological data in Ganzhou, China, from 2017 to 2019 were collected. The data on daily hospitalization for respiratory diseases from the biggest hospital in the city were extracted. The generalized additive models (GAM) and the distributed lag non-linear model (DLNM) were employed to evaluate the association between ambient SO₂ and daily inpatient visits for respiratory diseases. Stratified analyses by gender, age, and season were performed to find their potential effects on this association.

Results

There is a positive exposure-response relationship between SO₂ concentration and relative risk of respiratory inpatient visits. Every 10 μg/m³ increase in SO₂ was related to a 3.2% (95% CI: 0.6–6.7%) exaltation in daily respiratory inpatient visits at lag3. In addition, SO₂ had a stronger association with respiratory inpatient visits in women, older adults (≥65 years), and warmer season (May-Oct) subgroups. The relationship between SO₂ and inpatient visits for respiratory diseases was robust after adjusting for other air pollutants, including PM₁₀, NO₂, O₃, and CO.

Conclusion

This time-series study showed that there is a positive association between short-term SO₂ exposure and daily respiratory inpatient visits. These results are important for local administrators to formulate environmental public health policies.

Risk factors of chronic cough in China: a systematic review and meta-analysis

OBJECTIVES

Risk factors of chronic cough in China have not been systematically analyzed and we hypothesized that risk factors of chronic cough might have distinct characteristics in China. Hence, we performed this meta-analysis focusing on the potential risk factors of chronic cough in China.

METHODS

We searched 7 databases for studies published before May 8, 2021. This systematic review was performed in accordance with the PRISMA checklist.

RESULTS

A total of 33 eligible articles were identified and included in this systematic review, and 28 studies were included in the meta-analysis. Our results showed that allergy (OR: 3.72; 95% CI: 1.85-7.47), nasal/sinusitis diseases (OR: 3.56; 95% CI: 2.02-6.29), family history of allergy (OR = 1.74; 95% CI: 1.59-1.90), family history of chronic respiratory diseases (OR = 1.67; 95% CI: 1.47-1.91), exposure to pollutants (OR = 1.60; 95% CI: 1.26-2.04), passive smoking (OR = 1.44; 95% CI: 1.32-1.57), and exposure to pets (OR = 1.37; 95% CI: 1.18-1.58) were risk factors for chronic cough in China.

CONCLUSIONS

Our study indicated some potential risk factors of chronic cough in China, which provides useful epidemiological information for managing chronic cough in China and is worthy as a reference for future global investigations.

Air Pollution in Poland: A 2022 Narrative Review with Focus on Respiratory Diseases

According to the World Bank Group, 36 of the 50 most polluted cities in the European Union are in Poland. Thus, ambient air pollution and its detrimental health effects are a matter of immense importance in Poland. This narrative review aims to analyse current findings on air pollution and health in Poland, with a focus on respiratory diseases, including COVID-19, as well as the Poles’ awareness of air pollution. PubMed, Scopus and Google Scholar databases were searched. In total, results from 71 research papers were summarized qualitatively. In Poland, increased air pollution levels are linked to increased general and respiratory disease mortality rates, higher prevalence of respiratory diseases, including asthma, lung cancer and COVID-19 infections, reduced forced expiratory volume in one second (FEV1) and forced vital capacity (FVC). The proximity of high traffic areas exacerbates respiratory health problems. People living in more polluted regions (south of Poland) and in the winter season have a higher level of air pollution awareness. There is an urgent need to reduce air pollution levels and increase public awareness of this threat. A larger number of multi-city studies are needed in Poland to consistently track the burden of diseases attributable to air pollution.

Association between exposure to ambient air pollution and occurrence of inflammatory acne in the adult population

Background

Acne vulgaris is one of the most prevalent skin diseases responsible for dermatological consultations. Several internal and external factors can affect acne occurrence and severity. Outdoor air pollution is an external factor discussed to trigger inflammation of the skin. The objective of this study was to find a link between the exposure to ambient air pollution and inflammatory acne occurrence in the Lebanese adult population.

Methods

A cross-sectional study was conducted, using an online questionnaire to collect the required data from different Lebanese regions. The survey covered pollution exposure questions as well as queries on several factors known to have a role on acne occurrence.

Results

A total of 372 participants were included in the study, aged 18 to 55 years old. The results of a logistic regression taking the presence/absence of acne as the dependent variable, showed that female gender (aOR = 4.39), younger age (aOR = 1.05), using hydrating cream (aOR = 4.30), working near a power plant vs not (aOR = 3.07), having a severe NO2 exposure compared to none (aOR = 8.24), a higher number of family members with acne or history of acne (aOR = 1.48) were significantly associated with higher odds of having acne, whereas having a dry skin compared to normal (aOR = 0.20) was significantly associated with lower odds of having acne.

Conclusion

The occurrence of inflammatory acne in Lebanese adults was found to be associated with ambient exposure to high levels of NO₂ and employment near a power plant known to emit CO₂, CO, SO₂, NO₂ and PM. Therefore, our findings can serve as a first step towards implementing awareness on a skin care routine suitable for highly polluted areas.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11738-0.

Role of atmospheric particulate matter exposure in COVID-19 and other health risks in human: A review

Due to intense industrialization and urbanization, air pollution has become a serious global concern as a hazard to human health. Epidemiological studies found that exposure to atmospheric particulate matter (PM) causes severe health problems in human and significant damage to the physiological systems. In recent days, PM exposure could be related as a carrier for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus transmission and Coronavirus disease 2019 (COVID-19) infection. Hence, it is important to understand the adverse effects of PM in human health. This review aims to provide insights on the detrimental effects of PM in various human health problems including respiratory, circulatory, nervous, and immune system along with their possible toxicity mechanisms. Overall, this review highlights the potential relationship of PM with several life-limiting human diseases and their significance for better management strategies.

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

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

Association of change in air quality with hospital admission for acute exacerbation of chronic obstructive pulmonary disease in Guangdong, China: A province-wide ecological study

AIMS

To assess possible effect of air quality improvements, we investigated the temporal change in hospital admissions for acute exacerbations of chronic obstructive pulmonary disease (AECOPD) associated with pollutant concentrations.

METHODS

We collected daily concentrations of particulate matter (i.e., PM_2.5, PM₁₀ and PM_coarse), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), ozone (O₃), and admissions for AECOPD for 21 cities in Guangdong from 2013 to 2017. We examined the association of air pollution with AECOPD admissions using two-stage time-series analysis, and estimated the annual attributable fractions, numbers, and direct hospitalization costs of AECOPD admissions with principal component analysis.

RESULTS

From 2013-2017, mean daily concentrations of SO₂, PM₁₀ and PM_2.5 declined by nearly 40%, 30%, and 26% respectively. As the average daily 8 h O₃ concentration increased considerably, the number of days exceeding WHO target (i.e.,100 μg/m³) increased from 103 in 2015-152 in 2017. For each interquartile range increase in pollutant concentration, the relative risks of AECOPD admission at lag 0-3 were 1.093 (95% CI 1.06-1.13) for PM_2.5, 1.092 (95% CI 1.08-1.11) for O₃, and 1.092 (95% CI 1.05-1.14) for SO₂. Attributable fractions of AECOPD admission advanced by air pollution declined from 9.5% in 2013 to 4.9% in 2016, then increased to 6.0% in 2017. A similar declining trend was observed for direct AECOPD hospitalization costs.

CONCLUSION

Declined attributable hospital admissions for AECOPD may be associated with the reduction in concentrations of PM_2.5, PM₁₀ and SO₂ in Guangdong, while O₃ has emerged as an important risk factor. Summarizes the main finding of the work： Reduction in PM may result in declined attributable hospitalizations for AECOPD, while O₃ has emerged as an important risk factor following an intervention.

Association of COVID-19 distribution with air quality, sociodemographic factors, and comorbidities: an ecological study of US states

This ecological study investigated the association between COVID-19 distribution and air quality index (AQI), comorbidities and sociodemographic factors in the USA. The AQI factors included in the study are total AQI, ozone, carbon monoxide, sulfur dioxide, and nitrogen dioxide (NO₂). Other demographic, socioeconomic, and geographic variables were included as covariates. The correlations of COVID-19 variables-proportion of cases and deaths in each population, as well as case fatality rate with independent variables were determined by Pearson and Spearman correlation and multiple linear regression analyses. The results revealed that AQI-NO₂, population density, longitude, gross domestic product per capita, median age, total death of disease, and pneumonia per population were significantly associated with the COVID-19 variables (P < 0.05). Air pollutants, especially NO₂ in the US case, could be addressed as an important factor linked with COVID-19 susceptibility and mortality.

Air Pollution and Emergency Hospital Admissions—Evidences from Lisbon Metropolitan Area, Portugal

The relevance of air pollution in the public health agenda has recently been reinforced—it is known that exposure to it has negative effects in the health of individuals, especially in big cities and metropolitan areas. In this article we observed the evolution of air pollutants (CO, NO, NO2, O3, PM10) emissions and we confront them with health vulnerabilities related to respiratory and circulatory diseases (all circulatory diseases, cardiac diseases, cerebrovascular disease, ischemic heart disease, all respiratory diseases, chronic lower respiratory diseases, acute upper respiratory infections). The study is supported in two databases, one of air pollutants and the other of emergency hospital admissions, in the 2005–2015 period, applied to the Lisbon Metropolitan Area. The analysis was conducted through Ordinary Least Squares (OLS) regression, while also using semi-elasticity to quantify associations. Results showed positive associations between air pollutants and admissions, tendentially higher in respiratory diseases, with CO and O3 having the highest number of associations, and the senior age group being the most impacted. We concluded that O3 is a good predictor for the under-15 age group and PM10 for the over-64 age group; also, there seems to exist a distinction between the urban city core and its suburban areas in air pollution and its relation to emergency hospital admissions.

Revalue associations of short-term exposure to air pollution with respiratory hospital admissions in Lanzhou, China after the control and treatment of current pollution

Significant progress has been made in air pollution control Lanzhou, China recently, however, there was only one study so far on the assessment on health gains from air quality improvement after adopting strict air pollution control measures. The present study aimed to estimate the short-term effects of six criteria air pollutants including PM_2.5, PM₁₀, NO₂, SO₂, CO and O₃ on respiratory admissions in Lanzhou, China, then compare the results of our study with those earlier studies conducted in Lanzhou before the implementation of air pollution control measures. Data on daily hospital admissions from the three largest hospitals in Lanzhou and daily air pollution concentration and meteorological variable were collected during a 4-year period (2014-2017). A generalized additive model; adjusted for long-term trend, seasonality, and other potential confounders was done to quantitatively assess the influences of air pollutants on daily respiratory admissions and analyze the influences of different seasons, sexes, and age groups. The most apparent effects for PM_2.5, PM₁₀, SO₂, CO and O₃ on respiratory hospitalizations were observed at lag6, and lag7, respectively, and a 10μg/m₃ increase in PM_2.5, PM₁₀, SO₂, CO and O₃ concentration were associated with 0.885% (95%CI: 0.414%~1.358%), 0.328% (95%CI: 0.145%~0.511%), 3.005% (95%CI: 1.689%~4.339%), 3.199% (95%CI: 0.912%~5.537%) for CO, 0.733% (95%Cl: 0.263%~1.205%) increase in respiratory admission, respectively. No remarkable association was found between NO₂ and respiratory disease hospitalisation. Females and younger groups were more susceptible to air pollutant than males and elderly groups. Together, we demonstrated that the positive associations were more pronounced in the cold season than in the warm season. The findings in present study suggest that even in Lanzhou, where air quality has been improved dramatically, positive associations still exist between air pollution and daily number of total respiratory admission.

Acute effects of ambient air pollution on hospital outpatients with chronic pharyngitis in Xinxiang, China

We present results on a time-series study that analyzed the acute effects of six criteria air pollutants on hospital outpatient with chronic pharyngitis (CP) in Xinxiang, China. Data on the concentration of air pollutants and CP outpatient records were collected daily in Xinxiang, China, from January 1, 2015 to December 31, 2018. This study identified 62,823 outpatients with CP. The annual average concentrations of PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃ are 75.7, 132.1, 33.2, 48.4, 1377, and 59.4 μg/m³, respectively. Further, a 10 μg/m³ increment in the concentration of PM₁₀, SO₂, NO₂, and CO corresponds to an increase of 0.28% (95% confidence interval (CI): 0.03-0.53%), 1.10% (95% CI: 0.09-2.11%), 1.82% (95% CI: 0.84-2.80%), and 0.03% (95% CI: 0.01-0.06%) in daily CP hospital outpatients, respectively. Furthermore, results indicated that outpatients under the age of 15 are more susceptible to the air pollutants, excluding O₃. Meanwhile, males might be more susceptible, and effect estimates appear slightly stronger in the cool season. Therefore, we should implement effective measures to manage air pollutants and reinforce protection of the high-risk population.