Particulate matter pollution and emergency room visits for respiratory diseases in a valley Basin city of Northwest China

Associations between air pollutants and emergency ambulance dispatches for all-cause and nervous system disease in China Qingdao: a time-stratified case-crossover study

The health hazards of air pollution have been recognized worldwide, and emergency ambulance dispatches (EADs) data have excellent research value in the field of environmental health and wellness. This study evaluated EADs data from January 1, 2016 to December 31, 2019, in Qingdao to assess the impact of air pollution on all-cause as well as nervous system emergency ambulance dispatches (NS-EADs). This study adopted a time-stratified case-crossover design to construct a time-series distribution-lagged single-pollutant model to assess the effects of air pollution on all-cause and NS-EADs, stratified by gender, age, and season. Confounding factors that could affect the results were controlled for in the model. Air pollutants were positively associated with all-cause and NS-EADs. The findings of the single-day lag effect demonstrated positive associations between PM2.5 (lag0 and lag1 days), CO (lag0 and lag1 days), PM10 (lag0 and lag1 days), SO2 (lag1 days), and NO2 (lag1 days) with an increased risk of all-cause EADs. Additionally, O3 (lag0 days), CO (lag0 days), PM10 (lag0 days), and NO2 (lag0 days) exhibited positive correlations with an elevated risk of NS-EADs. To be specific, with every 10 μg/m3 increase in the concentrations of O3, CO, PM10, and NO2 at lag 0, there was a corresponding increase in NS-EADs risk of 0.67% (95% confidence interval, 0.05%, 1.30%); 0.05% (0.01%, 0.10%); 0.50% (0.13%, 0.87%); and 1.52% (0.24%, 2.82%), respectively. Stratified analysis revealed a higher risk of NS-EADs associated with air pollution, specifically observed in subgroups including individuals under 65 years old, males, and during the cold season. Air pollution was associated with all-cause EADs and NS-EADs, and males, people under 65 years old were more vulnerable to air pollution. Furthermore, the impact of air pollution is more pronounced during the cold season.

PM2.5 and NOX concentrations decrease as a result of a railway electrification

This work examines the impact of the electrification of the Holon-Bat Yam passenger train line (central Israel) on air pollutant concentrations using data collected from air quality monitoring stations that operated at the train stations across the electrified train line. We present statistically significant reduction in the annual average NO2, NO and NOX concentrations (29-45%, 79-85% and 65-75%, respectively), attributed to the electrification of the passenger train line. The drop in the NO and NOX concentrations was much stronger than in the NO2 concentrations, since NO is the main nitrogen species emitted by diesel locomotives. PM2.5 concentrations also significantly decreased, but only in two (out of the three) train stations situated along the electrified line. Following various analyses, we conclude that electrification of train lines reduces train locomotive emissions and improves the air quality at the stations, as expected, thus protecting the passengers and reducing their exposure to air pollutants. Although this study presents a specific case, the findings are expected to be applicable, at least quantitatively, to other locations, as railway electrification removes emissions associated with fossil-fuel-powered locomotives. This work supports railway electrification policy, which has the potential to substantially lower air pollution levels and diminish the passengers' exposure to harmful air pollutants.

The influence of PM2.5 exposure duration and concentration on outpatient visits of urban hospital in a typical heavy industrial city

To explain the duration and dose effects of pollutant exposure on public health and provide scientific data for air pollution prevention and control and disease prevention by examining the influence of PM2.5 concentration and exposure duration on daily outpatient visits among patients with cardiovascular, cerebrovascular, and respiratory diseases in a typical heavy industrial city in China. Daily outpatient data on cardiovascular, cerebrovascular, and respiratory diseases and regional PM2.5 exposure duration and concentration were collected from a provincial hospital in Taiyuan, China, from 2016 to 2021. The correlations of numeric variables were analyzed using the Pearson correlation method. A generalized additive model (GAMs) was also established to investigate the effects of PM2.5 concentration and exposure duration on outpatient visits. Correlation analysis showed that the outpatient visits in Taiyuan was significantly correlated with the PM2.5 concentration and exposure duration. The longer the exposure time of PM2.5 pollution, the stronger the correlation of PM2.5 with outpatient visits showed. Cardiovascular outpatient visits were extremely significant related with medium to long-term exposure of PM2.5 (exposure with more than 30 days) (p < 0.001). In addition, outpatient visits of cerebrovascular and respiratory disease were extremely significant correlated with PM2.5 (exposures within 0-360 days) (p < 0.001). The results of GAMs showed the linear or the nonlinear relationships between outpatient visits and exposure of PM2.5. Among the linear relationships, when average concentration of PM2.5 (exposure within less than 15 days) increased by 1 mg/m3, the cardiovascular outpatient visits increased most dramatically (by about 440 people). For nonlinear relationships, when the average PM2.5 concentration (exposure with over 30 days or more) increased by 1 mg/m3, the most dramatic increase occurred in cardiovascular outpatient visits (with a maximum increase of 7000), followed by cerebrovascular outpatient visits (with a maximum increase of 1200), and respiratory outpatient visits (with a maximum increase of 250). The GAMs also revealed a dose effect in the relationship between outpatient visits and PM2.5 exposure. In moderately polluted air (based on air quality standards of China, GB3095-2012), when the average concentration of PM2.5 increased by 1 mg/m3, the cardiovascular outpatient visits increased the most (by 1200 people), followed by cerebrovascular outpatient visits (by 200 people) and respiratory outpatient visits (by 20 people). We concluded that outpatient visits in cardiovascular, cerebrovascular, and respiratory disease are closely correlated with the concentration and exposure duration of air pollution. There is a linear relationship between short-term air pollution exposure (exposure within less than 15 days) and outpatient visits. As PM2.5 concentration increases, cardiovascular outpatient visits increase gradually, with its growth trend exceeding that of cerebrovascular and respiratory disease. There is a nonlinear relationship between medium and long-term air pollution exposure (exposure with more than 30 days) and outpatient visits, with cardiovascular and cerebrovascular outpatient visits showed a nonlinear but overall upward trend when the atmosphere is moderately polluted.

Cumulative and lagged effects of varying-sized particulate matter exposure associates with toddlers' gut microbiota

Particulate matter (PM) is an important component of air pollutants and is associated with various health risks. However, the impact of PM on toddlers' gut microbiota is rarely investigated. This study aimed to assess the cumulative and lagged effects of varying-sized PMs on toddlers' gut microbiota. We collected demographic information, stool samples, and exposure to PM from 36 toddlers aged 2-3 years. The toddlers were divided into warm season group and cooler season group according to the collection time of stool samples. The gut microbiota was processed and analyzed using 16S rRNA V3-V4 gene regions. The concentration of PM was calculated using China High Air Pollutants (CHAP) database. To assess the mixed effects of varying-sized PM, multiple-PM models were utilized. There were significant differences between the community composition, α- and β-diversity between two groups. In multiple-PM models, there was a significant effect of weight quantile sum (PM1, PM2.5, and PM10) on α-diversity indices. In weight quantile sum models, after adjusting for a priori confounders, we found a negative effect of weight quantile sum on Enterococcus (β = -0.134, 95% CI -0.263 to -0.006), positive effects of weight quantile sum on unclassified_f__Ruminococcaceae (β = 0.247, 95% CI 0.102 to 0.393), Ruminococcus_1 (β = 0.444, 95% CI 0.238 to 0.650), unclassified_f__Lachnospiraceae (β = 0.278, 95% CI 0.099 to 0.458), and Family_XIII_AD_3011_group (β = 0.254, 95% CI 0.086 to 0.422) in WSG and CSG. In lagged weight quantile sum models, the correlation between lag time PM levels and the gut microbiota showed seasonal trends, and weights of PM changed with lag periods. This is the first study to highlight that cumulative and lagged effects of PMs synergistically affect the diversities (α- and β-diversity) and abundance of the gut microbiota in toddlers. Further research is needed to explore the mediating mechanism of varying-sized PMs exposure on the gut microbiota in toddlers.

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.

Differential effects of size-specific particulate matter on the number of visits to outpatient fever clinics: A time-series analysis in Zhuhai, China

INTRODUCTION

While many studies have investigated the adverse effects of particulate matter (PM), few of them distinguished the different effects of PM2.5, PM10, and coarse PM (PMc) on outpatients with fever. Our study aimed to estimate and compare the acute cumulative effects of exposure to three size-specific particles on the number of visits to outpatient fever clinics.

METHODS

To examine the association between daily PM concentrations and outpatients in fever clinics, a generalized additive Poisson model was applied, stratified by sex, age, and season.

RESULTS

Our study included 56,144 outpatient visits in Zhuhai, from January 2020 to June 2021. On the current day, each 10 mg/m3 increment of PM10 and PMc were estimated to increase fever clinic visits by 1.74% (95% CI: 0.59%, 2.91%) and 4.42 % (2.30%, 6.58%), respectively. Cumulative effects enhanced from lag01 to lag05 for PM10 and PMc, and PMc had the strongest impact [ER = 8.92% (5.91%, 12.01%) at lag05]. Female outpatients and outpatients aged 14 years and above had an increased PM-related risk. During the cold season, significant effects could be observed for the three-size PM, while only PMc showed the impact during the warm season.

DISCUSSION

Overall, the three size-specific PM exerted different effects on the fever clinic visits. Strategies to control the concentrations of PM are still necessary, especially against PM10 and PMc.

Association of short-term exposure to air pollution with emergency visits for respiratory diseases in children

Ambient air pollutants are health hazards to children. This study comprised 773,504 emergency department visits (EDVs) at 0–14 years of age with respiratory diseases in southern China. All air pollutants were positively associated with EDVs of total respiratory diseases, especially pneumonia. NO₂, PM₁₀, and PM_2.5 had intraday effects and cumulative effects on asthma EDVs. The effect of SO₂, PM₁₀, and PM_2.5 on pneumonia EDVs was stronger in girls than in boys. The effect of NO₂ on acute upper respiratory tract infection EDVs was greater in children aged 0–5 years old; however, the effect of PM₁₀ on acute upper respiratory tract infection EDVs was greater in the 6–14 years group. In a two-pollutant model, NO₂ was associated with bronchitis and pneumonia, and PM₁₀ was associated with acute upper respiratory tract infection. In this time-series study, NO₂ and PM₁₀ were risk indicators for respiratory diseases in children.

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Air pollution associates with children emergency visits for respiratory diseases

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NO₂ and PM₁₀ are risk indicators for respiratory diseases in children

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Young children are more sensitive to gaseous pollutants

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School-age children are more sensitive to PM₁₀

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.