Three exposure metrics of size-specific particulate matter associated with acute lower respiratory infection hospitalization in children: A multi-city time-series analysis in China

Effect of pregnancy and infancy exposure to outdoor particulate matter (PM1, PM2.5, PM10) and SO2 on childhood pneumonia in preschool children in Taiyuan City, China

There is currently a paucity of research on the effects of early life exposure to particulate matter (PM) of various size fractions on pneumonia in preschool-aged children. We explored the connections between antenatal and postnatal exposure to atmospheric pollutants and diagnosed pneumonia among 4814 offspring children in Taiyuan City, northern China. Outdoor air pollutant concentrations and ambient temperature were collected. A machine learning-based model was utilized to compute daily mean concentrations of PM10, PM2.5, and PM1 at the home address. Associations were calculated using generalized linear mixed models, and stratified analysis was used to detect sensitive subpopulations. We observed significant associations between prenatal exposure to atmospheric pollutants and the incidence of pneumonia in children. For every 10 μg/m3 increase, the odds ratios (ORs) were 1.06 for PM10, 1.15 for PM2.5, 1.24 for PM1, and 1.05 for SO2 for the whole pregnancy period. In mid-pregnancy, the most vital connections were found for PM10, PM2.5, and PM1 exposure. Girls showed higher sensitivity to exposure to PM2.5 and PM10. The most significant connections between PM and pneumonia were observed at high SO2 exposure. Connections between PM1, PM2.5 and pneumonia were stronger in children without environmental tobacco smoke (ETS) at home. Associations between PM10 and pneumonia were stronger in children with ETS at home. The synthesis of the data suggests that exposure to PM10, PM2.5, PM1, and SO2 during pregnancy contributes to an elevated susceptibility to childhood pneumonia. The second trimester period is significant and represents a critical window of vulnerability. PM1 may have the strongest impact. Exposure to SO2 can further enhance the PM related risks of pneumonia. Gender and ETS exposure at home can modify associations between outdoor PM and pneumonia. Further reductions in outdoor PM, especially PM1, are needed to reduce childhood pneumonia in China.

A comparative analysis of three PM2.5 exposure metrics and their impact on respiratory disease hospitalizations in Lanzhou, China

Research on the associations between PM2.5 and total respiratory diseases (RD) in Lanzhou is limited. We investigated the short-term impact of PM2.5 on total RD hospitalizations in Lanzhou (2015-2019) using various exposure metrics. We collected data on hospitalizations, daily air pollutant concentrations, and meteorological factors during the study period. Daily excessive concentration hours (DECH) were calculated according to the World Health Organization's air quality guidelines. A distributional lag nonlinear model (DLNM) based on a generalized additive model (GAM) was used to comparatively analyze the association between three PM2.5 exposure metrics (DECH (DECH PM2.5), daily mean concentration (Mean PM2.5), and hourly peak concentration (Peak PM2.5)) and RD hospitalizations. Subgroup analyses and sensitivity analyses were also performed. We found similar effects on RD hospitalizations using DECH PM2.5 and Mean PM2.5, but relatively weak associations observed using Peak PM2.5. The cumulative lag effect increased daily. Subgroup analyses showed that females and children aged 0-17 years were more susceptible to PM2.5 pollution and that the association was enhanced during the cold season. Our research strengthened the evidence that exposure to ambient PM2.5 increases the risk of RD. This study revalidated the reliability of the new metrics and confirmed that DECH PM2.5 effect estimates for exposure-disease were more accurate than the Mean PM2.5.

The Combined Effects of Hourly Multi-Pollutant on the Risk of Ambulance Emergency Calls: A Seven-Year Time Series Study

BACKGROUND

Ambulance emergency calls (AECs) are seen as a more suitable metric for syndromic surveillance due to their heightened sensitivity in reflecting the health impacts of air pollutants. Limited evidence has emphasized the combined effect of hourly air pollutants on AECs. This study aims to investigate the combined effects of multipollutants (i.e., PM2.5, PM10, Ozone, NO2, and SO2) on all-cause and cause-specific AECs by using the quantile g-computation method.

METHODS

We used ambulance emergency dispatch data, air pollutant data, and meteorological data from between 1 January 2013 and 31 December 2019 in Shenzhen, China, to estimate the associations of hourly multipollutants with AECs. We followed a two-stage analytic protocol, including the distributed lag nonlinear model, to examine the predominant lag for each air pollutant, as well as the quantile g-computation model to determine the associations of air pollutant mixtures with all-cause and cause-specific AECs.

RESULTS

A total of 3,022,164 patients were identified during the study period in Shenzhen. We found that each interquartile range increment in the concentrations of PM2.5, PM10, Ozone, NO2, and SO2 in 0-8 h, 0-8 h, 0-48 h, 0-28 h, and 0-24 h was associated with the highest risk of AECs. Each interquartile range increase in the mixture of air pollutants was significantly associated with a 1.67% (95% CI, 0.12-3.12%) increase in the risk of all-cause AECs, a 1.81% (95% CI, 0.25-3.39%) increase in the risk of vascular AECs, a 1.77% (95% CI, 0.44-3.11%) increase in reproductive AECs, and a 2.12% (95% CI, 0.56-3.71%) increase in AECs due to injuries.

CONCLUSIONS

We found combined effects of pollutant mixtures associated with an increased risk of AECs across various causes. These findings highlight the importance of targeted policies and interventions to reduce air pollution, particularly for PM, Ozone, and NO2 emissions.

Impact of short-term exposure to ambient air pollution on osteoarthritis: a multi-city time-series analysis in Central-Eastern China

Osteoarthritis (OA) is a threat to public health issue with high morbidity and disability worldwide. However, unequivocal evidence on the link between air pollution and OA remains little, especially in multi-study sites. This study aimed to explore the relationship between short-term exposure to main air pollutants and the risk of OA outpatient visits in multi-study sites. A multi-city time-series analysis was performed in Anhui Province, Central-Eastern China from January 1, 2015, to December 31, 2020. We used a two-stage analysis to assess the association between air pollution and daily OA outpatient visits. City-specific associations were estimated with a distributed lag nonlinear model and then pooled by random-effects or fixed-effects meta-analysis. Stratified analysis was conducted by gender, age, and season. Additionally, the disease burden of OA attributable to air pollutant exposure was calculated. A total of 35,700 OA outpatients were included during the study period. The pooled exposure-response curves showed that PM2.5 and PM10 concentrations below the reference values could increase the risk of OA outpatient visits. Concretely, per 10 ug/m3 increase in PM2.5 concentration was linked to an elevated risk of OA outpatient visits at lag 2 and lag 3 days, where the effect reached its highest value on lag 2 day (RR: 1.023, 95%CI: 1.005-1.041). We observed that a 10 μg/m3 increase in PM10 was positively correlated with OA outpatient visits (lag2 day, RR: 1.011, 95%CI: 1.001-1.025). Nevertheless, no statistical significance was discovered in gaseous pollutants (including SO2, O3, and CO). Additionally, a significant difference was found between cold and warm seasons, but not between different genders or age groups. This study reveals that particulate matter is an important factor for the onset of OA in Anhui Province, China. However, there is no evidence of a relationship of gaseous pollutants with OA in this area.

Association of Air Pollution with the Number of Common Respiratory Visits in Children in a Heavily Polluted Central City, China

Children's respiratory health is vulnerable to air pollution. Based on data collected from June 2019 to June 2022 at a children's hospital in Zhengzhou, China, this study utilized Spearman correlation analysis and a generalized additive model (GAM) to examine the relationship between daily visits for common respiratory issues in children and air pollutant concentrations. Results show that the number of upper respiratory tract infection (URTI), pneumonia (PNMN), bronchitis (BCT), and bronchiolitis (BCLT) visits in children showed a positive correlation with PM2.5, PM10, NO2, SO2, and CO while exhibiting a negative correlation with temperature and relative humidity. The highest increases in PNMN visits in children were observed at lag 07 for NO2, SO2, and CO. A rise of 10 μg/m3 in NO2, 1 μg/m3 in SO2, and 0.1 mg/m3 in CO corresponded to an increase of 9.7%, 2.91%, and 5.16% in PNMN visits, respectively. The effects of air pollutants on the number of BCT and BCLT visits were more pronounced in boys compared to girls, whereas no significant differences were observed in the number of URTI and PNMN visits based on sex. Overall, air pollutants significantly affect the prevalence of respiratory diseases in children, and it is crucial to improve air quality to protect the children's respiratory health.

Short-term effects of air pollution on hospitalization for acute lower respiratory infections in children: a time-series analysis study from Lanzhou, China

BACKGROUND

Short-term exposure to air pollution is associated with acute lower respiratory infections (ALRI) in children. We investigated the relationship between hospitalization for ALRI in children and air pollutant concentrations from January 1, 2014 to December 31, 2020 in Lanzhou City.

METHODS

We collected data on air pollutant concentrations and children's hospitalization data during the study period. A time series regression analysis was used to assess the short-term effects of air pollutants on ALRI in children, and subgroup analyses and sensitivity analyses were performed.

RESULTS

A total of 51,206 children with ALRI were studied, including 40,126 cases of pneumonia and 11,080 cases of bronchiolitis. The results of the study revealed that PM2.5, PM10, SO2 and NO2 were significantly associated with hospitalization for ALRI in children aged 0-14 years. For each 10 µg/m3 increase in air pollutant concentration in lag0-7, the relative risk of ALRI hospitalization in children due to PM2.5, PM10, SO2 and NO2 increased by 1.089 (95%CI:1.075, 1.103), 1.018 (95%CI:1.014, 1.021), 1.186 (95%CI:1.154. 1.219) and 1.149 (95%CI:1.130, 1.168), respectively.

CONCLUSIONS

PM2.5, PM10, SO2 and NO2 short-term exposures were positively associated with ALRI, pneumonia and bronchiolitis hospitalizations in Lanzhou, China. Local governments should make efforts to improve urban ambient air quality conditions to reduce hospitalization rates for childhood respiratory diseases.

Associations between hourly ambient particulate matter air pollution and ambulance emergency calls among 3,022,164 patients: time stratified case-crossover study

BACKGROUND

Associations between short-term exposure to ambient particulate matter (PM) air pollutants and mortality or hospital admissions have been well documented in previous studies. Less is known about the associations of hourly exposure to PM air pollutants with ambulance emergency calls (AECs) for all causes and specific causes by conducting a case-crossover study. In addition, different patterns of AECs may be attributed to different seasons and daytime/nighttime periods.

OBJECTIVE

In this study, we quantified the risk of all-cause and cause-specific AECs associated with hourly PM air pollutants between 1 January 2013 and 31 December 2019 in Shenzhen, China. We also examined whether the observed associations of particulate matter air pollutants with AECs for all causes differed across strata defined by sex, age, season, and time of day.

METHODS

We used ambulance emergency dispatch data and environmental data between 1 January 2013 and 31 December 2019 from the Shenzhen Ambulance Emergency Centre and the National Environmental Monitor Station to conduct a time-stratified case-crossover study design to estimate the associations of air pollutants (i.e., PM2.5, PM10) with all-cause AECs and cause-specific AECs. We generated a well-established distributed lag nonlinear model for nonlinear concentration response and nonlinear lag response functions. We used conditional logistic regression to estimate odds ratios (ORs) with 95% confidence intervals (CIs), adjusted for public holidays, season, time of day, day of the week, hourly temperature, and hourly humidity to examine the association of all-cause and cause-specific AECs with hourly air pollutant concentrations.

RESULTS

A total of 3,022,164 patients were identified during the study period in Shenzhen. Each IQR increase in PM2.5 (24.0 µg/m3) and PM10 (34.0 µg/m3) concentrations in 24 hours was associated with an increased risk of AECs (PM2.5: all-cause, 1.8%, 95% CI, 0.8%-2.4%; PM10: all-cause, 2.0%, 95% CI, 1.1%-2.9%). We observed a stronger association of all-cause AECs with PM2.5 and PM10 in the daytime than in the nighttime and in the elderly group than in the younger group (PM2.5 daytime, 1.7%, 95% CI, 0.5%-3.0%; nighttime, 1.4%, 95% CI, 0.3%-2.6%; PM10 daytime, 2.1%, 95% CI, 0.9%-3.4%; nighttime, 1.7%, 95% CI, 0.6%-2.8%; PM2.5 18-64 years, 1.4%, 95% CI, 0.6%-2.1%; ≥65 years, 1.6%, 95% CI, 0.6%-2.6%; PM10 18-64 years, 1.8%, 95% CI, 0.9%-2.6%; ≥65 years, 2.0%, 95% CI, 1.1%-3.0%).

CONCLUSIONS

The risk of all-cause AECs increased consistently with increasing concentrations of PM air pollutants, showing a nearly linear relationship with no apparent thresholds. Particulate matter air pollution increase was associated with a higher risk of AECs for all causes, cardiovascular, respiratory, and reproductive AECs. The results of this study may be valuable to air pollution attributable to the distribution of emergency resources, and consistent air pollution control.

CLINICALTRIAL

Cohort profile: Bangladesh Cook Stove Pregnancy Cohort Study (CSPCS)

PURPOSE

The Cook Stove Pregnancy Cohort Study (CSPCS) was designed to assess the effects of biomass fuel use on household air pollution (HAP) as well as the effects of HAP (fine particulate matter, PM_2.5) on birth outcomes and acute lower respiratory infection (ALRI) among infants in Bangladesh.

PARTICIPANTS

We recruited 903 women within 18 weeks of pregnancy from rural and semiurban areas of Bangladesh between November 2016 and March 2017. All women and their infants (N=831 pairs) were followed until 12 months after delivery and a subset have undergone respiratory and gut microbiota analysis.

METHODS

Questionnaires were administered to collect detailed sociodemographic, medical, nutritional and behavioural information on the mother-child dyads. Anthropometric measurements and biological samples were also collected, as well as household PM_2.5 concentrations.

FINDINGS TO DATE

Published work in this cohort showed detrimental effects of biomass fuel and health inequity on birth outcomes. Current analysis indicates high levels of household PM_2.5 being associated with cooking fuel type and infant ALRI. Lastly, we identified distinct gut and respiratory microbial communities at 6 months of age.

FUTURE PLANS

This study provides an economical yet effective framework to conduct pregnancy cohort studies determining the health effects of adverse environmental exposures in low-resource countries. Future analyses in this cohort include assessing the effect of indoor PM_2.5 levels on (1) physical growth, (2) neurodevelopment, (3) age of first incidence and frequency of ALRI in infants and (4) the development of the respiratory and gut microbiome. Additional support has allowed us to investigate the effect of in utero exposure to metals on infant neurodevelopment in the first year of life.

Daily diurnal temperature range associated with outpatient visits of acute lower respiratory infection in children: A time-series study in Guangzhou, China

Background

Diurnal temperature range (DTR) has been increasingly recognized as a risk factor for mortality and morbidity, but the association between DTR and acute lower respiratory infection (ALRI) outpatient visits has not been examined among children in China.

Methods

A total of 79,416 ALRI outpatient visits among children were obtained from the Guangdong Second Provincial General Hospital between 2013 and 2019. DTR was calculated by taking the difference between the maximum and the minimum temperatures. Generalized additive models using a quasi-Poisson distribution were used to model the relationship between DTR and ALRI outpatient visits.

Results

Diurnal temperature range was significantly associated with elevated risks of ALRI outpatient visits: the excess risks (ERs) and 95% confidence intervals (CIs) were 2.31% (1.26, 3.36%) for ALRI, 3.19% (1.86, 4.54%) for pneumonia, and 1.79% (0.59, 3.01%) for bronchiolitis, respectively. Subgroup analyses suggested that the associations were significantly stronger during rainy seasons (ER for ALRI: 3.02%, 95% CI: 1.43, 4.64%) than those in dry seasons (ER for ALRI: 2.21%, 95% CI: 0.65, 3.81%), while no significant effect modifications were found in sex and age groups.

Conclusion

Diurnal temperature range may elevate the risk of ALRI outpatient visits among children in China, especially during rainy seasons. Public health policies are needed to mitigate the adverse health impacts of DTR on children.

Three Exposure Metrics for Fine Particulate Matter Associated With Outpatient Visits for Acute Lower Respiratory Infection Among Children in Guangzhou, China

Ambient fine particulate matter (PM_2.5) is associated with an elevated risk of acute lower respiratory infections (ALRI). However, this association has not been examined using alternative exposure metrics. We collected outpatient data of patients with ALRI aged <14 years from the administrative database of a large tertiary hospital in Guangzhou, China, from 2013 to 2019. Ambient PM_2.5 was measured using three metrics: (a) daily mean, (b) daily excessive concentration hours (DECH), and (c) hourly peak. Generalized additive models were fitted to estimate the excess risk (ER) associated with PM_2.5. A total of 105,639 ALRI (35,310 pneumonia and 68,218 bronchiolitis) outpatient visits were identified during the study period. An interquartile range increment in PM_2.5 DECH was consistently associated with the highest ER of ALRI-related outpatient visits: 12.30% (95% confidence interval [CI]: 9.49–15.18%), compared with 11.20% (95% CI: 8.34–14.13%) for daily mean and 9.73% (95% CI: 6.97–12.55%) for hourly peak. The associations between the three metrics of PM_2.5 and ALRI-related outpatient visits were stronger in the cold season than in the warm season. Future studies should consider PM_2.5 DECH as an alternative method of exposure measurement, in addition to daily mean and hourly peak concentrations of PM_2.5.