Air pollution and pediatric respiratory hospital admissions in Bursa, Turkey: A time series study

Air Pollution and Childhood Asthma Hospitalizations in Chengdu, China: A Time-Series Study

Purpose

Research on the relationship between air pollutants and hospitalization for asthma in children in developing countries remains inadequate. This study aimed to assess the short-term effects of air pollutants, including sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3), particulate matter ≤ 2.5 µm (PM2.5), and particulate matter ≤ 10 µm (PM10), on children hospitalized for asthma in Chengdu, China, from 2017-2022.

Patients and Methods

During the study period, 5592 children were hospitalized for asthma. A generalized additive model was used to control for seasonality, long-term trends, weather, day of the week, and holidays. The analysis was further stratified by age, sex, and season to estimate the associations.

Results

PM2.5, PM10, SO2, NO2, and CO were significantly associated with an increased risk of hospitalization due to asthma. A 10 μg/m3 increase in PM2.5, PM10, and CO at lag04 corresponded to an increase of 2.07%, 1.56%, and 0.33% in daily hospital admissions for asthma, respectively. A 10 μg/m3 increase in SO2 and NO2 at lag05 corresponded to an increase of 45.69% and 8.16% in daily hospital admissions for asthma, respectively. Further analysis by age found that PM10 and PM2.5 had a greater impact on children aged 5-6 years old while NO2 and CO mainly affected children under 7 years old. Analysis by by sex found that pollutants had a greater impact on hospital admissions in girls. Seasonal analysis revealed that pollutants had a more significant effect on admission during the winter.

Conclusion

Our results suggest that increased concentrations of PM2.5, PM10, SO2, NO2, and CO in Chengdu lead to hospitalization for asthma in children and that a lag effect was observed, especially with SO2. These findings highlight the need for stricter air quality controls to reduce childhood asthma hospitalizations.

Enhancing indoor air quality and cardiopulmonary health in patients with asthma by photocatalytic oxidation and filters air cleaner

BACKGROUND

Air purifiers can enhance indoor air quality and health outcomes, and studies have primarily focused on filters and particulate matter (PM) in households. Photocatalytic oxidation (PCO) is a promising technique for eliminating gaseous pollutants and bioaerosols. However, no field study was conducted in household. Therefore, this study evaluated the effects of the PCO and PCO + filters intervention on indoor air pollutants and cardiopulmonary endpoints in households.

METHODS

A randomized, double-blind crossover clinical trial was conducted. Indoor air pollutants, including PM, bioaerosols, and gaseous pollutants and cardiopulmonary endpoints including lung function, fractional exhaled nitric oxide (FeNO), respiratory symptoms, and blood pressure were assessed before and after intervention.

FINDINGS

This was the first study to evaluate the effects of PCO and PCO + filters interventions on indoor air pollutants and cardiopulmonary health in households. Indoor total volatile organic compounds (TVOC) and sulfur dioxides (SO2) significantly reduced after PCO intervention, however, we also observed the significant reduction in percentage of predicted values of forced vital capacity (FVC%) and forced expiratory volume in 3 s (FEV3%) and increased in FeNO after 13 days of PCO intervention. The PCO + filters intervention significantly reduced the levels of indoor PM1, PM2.5, PM4, PM10, total suspended particulate matter, ultrafine particles, airborne bacteria, fungi, endotoxin, mites, TVOC, nitrogen dioxide, and SO2, and marginal reduction in carbon monoxide. However, indoor carbon dioxide significantly increased after PCO/PCO + filters intervention. As for cardiopulmonary health, FVC%, and FEV1 % marginally increased 7 days after the PCO + filters intervention.

Predicting hospital admissions for upper respiratory tract complaints: An artificial neural network approach integrating air pollution and meteorological factors

This study uses artificial neural networks (ANNs) to examine the intricate relationship between air pollutants, meteorological factors, and respiratory disorders. The study investigates the correlation between hospital admissions for respiratory diseases and the levels of PM10 and SO2 pollutants, as well as local meteorological conditions, using data from 2017 to 2019. The objective of this study is to clarify the impact of air pollution on the well-being of the general population, specifically focusing on respiratory ailments. An ANN called a multilayer perceptron (MLP) was used. The network was trained using the Levenberg-Marquardt (LM) backpropagation algorithm. The data revealed a substantial increase in hospital admissions for upper respiratory tract diseases, amounting to a total of 11,746 cases. There were clear seasonal fluctuations, with fall having the highest number of cases of bronchitis (N = 181), sinusitis (N = 83), and upper respiratory infections (N = 194). The study also found demographic differences, with females and people aged 18 to 65 years having greater admission rates. The performance of the ANN model, measured using R2 values, demonstrated a high level of predictive accuracy. Specifically, the R2 value was 0.91675 during training, 0.99182 during testing, and 0.95287 for validating the prediction of asthma. The comparative analysis revealed that the ANN-MLP model provided the most optimal result. The results emphasize the effectiveness of ANNs in representing the complex relationships between air quality, climatic conditions, and respiratory health. The results offer crucial insights for formulating focused healthcare policies and treatments to alleviate the detrimental impact of air pollution and meteorological factors.

Air pollution and upper respiratory diseases: an examination among medically insured populations in Wuhan, China

Multiple evidence has supported that air pollution exposure has detrimental effects on the cardiovascular and respiratory systems. However, most investigations focus on the general population, with limited research conducted on medically insured populations. To address this gap, the current research was designed to examine the acute effects of inhalable particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), ground-level ozone (O3), and sulfur dioxide (SO2) on the incidence of upper respiratory tract infections (URTI), utilizing medical insurance data in Wuhan, China. Data on URTI were collected from the China Medical Insurance Basic Database for Wuhan covering the period from 2014 to 2018, while air pollutant data was gathered from ten national monitoring stations situated in Wuhan city. Statistical analysis was performed using generalized additive models for quasi-Poisson distribution with a log link function. The analysis indicated that except for ozone, higher exposure to four other pollutants (NO2, SO2, PM2.5, and PM10) were significantly linked to an elevated risk of URTI, particularly during the previous 0-3 days and previous 0-4 days. Additionally, NO2 and SO2 were found to be positively linked with laryngitis. Furthermore, the effects of air pollutants on the risk of URTI were more pronounced during cold seasons than hot seasons. Notably, females and the employed population were more susceptible to infection than males and non-employed individuals. Our findings gave solid proof of the link between ambient air pollution exposure and the risk of URTI in medically insured populations.

Assessment of ground-level ozone pollution in Türkiye according to new WHO limits

Ground-level ozone is a secondary pollutant and is attributable to respiratory diseases and mortality. For this reason, the World Health Organization (WHO) implemented a new long-term (peak season) limit value for ozone. The previous studies related to ozone in Türkiye were spatially limited to certain locations. In this study, annual mean and peak season ozone concentrations, and limit exceedances were investigated for Türkiye for the year 2021. Moreover, ozone peak seasons were determined for the first time for 126 air quality monitoring stations. The annual mean ozone concentration was determined as 44.3 ± 19.3 µg/m3 whereas the peak season average ozone level was 68.4 ± 27.2 µg/m3. April-September period was the most frequently observed ozone peak season. Among all stations, Erzurum Palandöken was by far the most polluted station in terms of annual mean and limit exceedances of ozone. Ankara Siteler stations have the highest rank in peak season mean. 87 and 83 stations exceeded the short-term and long-term recommendations of WHO, respectively. Four hotspot regions were revealed in terms of peak season exceedance: Adana and surrounding provinces, the surroundings of Burdur and Isparta provinces, and the northeastern and northwestern parts of Türkiye. To protect public health, WHO recommendations for 8-h and peak season limits should be immediately implemented in Turkish regulations.