Pediatric Emergency Visits and Short-Term Changes in PM2.5 Concentrations in the U.S. State of Georgia

The Influence of Fine Particulate Matter and Cold Weather on Emergency Room Interventions for Childhood Asthma

(1) Background: Children are the most vulnerable to pollution due to their decreased stature, heightened respiratory rate, and frequent outdoor engagement. PM2.5, nitrogen dioxide (NO2), ozone, and cold weather are associated with pediatric asthma. In this study, we investigated the nexus between air pollution, climate factors, and pediatric asthma emergency room visits (ERVs). (2) Method: Pediatric asthma ERV data for healthcare quality from the Taiwanese National Insurance in the Taipei area were obtained from 2015 to 2019. Air pollution and climate factor data were also collected. Poisson regression was employed to determine the relationships with relative risks (RRs). (3) Results: The incidence of pediatric asthma ERVs decreased, with a crude RR of 0.983 (95% CI: 0.98-0.986, p < 0.001). Fine particulate matter (PM2.5) had an adjusted RR of 1.102 (95% CI: 1.037-1.172, p = 0.002) and a 7.7 µg/m3 increase, and air temperature had an adjusted RR of 0.813 (95% CI: 0.745-0.887, p < 0.001) comparing between the highest and lowest quarter air temperature associated with pediatric asthma ERVs. (4) Conclusions: This inquiry underscores the positive associations of PM2.5 and cold weather with pediatric asthma ERVs. The findings could guide the government to establish policies to reduce air pollution and promote children's health.

Bronchiolitis recovery and the use of High Efficiency Particulate Air (HEPA) Filters (The BREATHE Study): study protocol for a multi-center, parallel, double-blind, randomized controlled clinical trial

BACKGROUND

Acute viral bronchiolitis is the most common reason for hospitalization of infants in the USA. Infants hospitalized for bronchiolitis are at high risk for recurrent respiratory symptoms and wheeze in the subsequent year, and longer-term adverse respiratory outcomes such as persistent childhood asthma. There are no effective secondary prevention strategies. Multiple factors, including air pollutant exposure, contribute to risk of adverse respiratory outcomes in these infants. Improvement in indoor air quality following hospitalization for bronchiolitis may be a prevention opportunity to reduce symptom burden. Use of stand-alone high efficiency particulate air (HEPA) filtration units is a simple method to reduce particulate matter ≤ 2.5 µm in diameter (PM2.5), a common component of household air pollution that is strongly linked to health effects.

METHODS

BREATHE is a multi-center, parallel, double-blind, randomized controlled clinical trial. Two hundred twenty-eight children < 12 months of age hospitalized for the first time with bronchiolitis will participate. Children will be randomized 1:1 to receive a 24-week home intervention with filtration units containing HEPA and carbon filters (in the child's sleep space and a common room) or to a control group with units that do not contain HEPA and carbon filters. The primary objective is to determine if use of HEPA filtration units reduces respiratory symptom burden for 24 weeks compared to use of control units. Secondary objectives are to assess the efficacy of the HEPA intervention relative to control on (1) number of unscheduled healthcare visits for respiratory complaints, (2) child quality of life, and (3) average PM2.5 levels in the home.

DISCUSSION

We propose to test the use of HEPA filtration to improve indoor air quality as a strategy to reduce post-bronchiolitis respiratory symptom burden in at-risk infants with severe bronchiolitis. If the intervention proves successful, this trial will support use of HEPA filtration for children with bronchiolitis to reduce respiratory symptom burden following hospitalization.

TRIAL REGISTRATION

NCT05615870. Registered on November 14, 2022.

Exposure to outdoor particulate matter and risk of respiratory diseases: a systematic review and meta-analysis

According to epidemiological studies, particulate matter (PM) is an important air pollutant that poses a significant threat to human health. The relationship between particulate matter and respiratory diseases has been the subject of numerous studies, but these studies have produced inconsistent findings. The purpose of this systematic review was to examine the connection between outdoor particulate matter (PM2.5 and PM10) exposure and respiratory disorders (COPD, lung cancer, LRIs, and COVID-19). For this purpose, we conducted a literature search between 2012 and 2022 in PubMed, Web of Science, and Scopus. Out of the 58 studies that were part of the systematic review, meta-analyses were conducted on 53 of them. A random effect model was applied separately for each category of study design to assess the pooled association between exposure to PM2.5 and PM10 and respiratory diseases. Based on time-series and cohort studies, which are the priorities of the strength of evidence, a significant relationship between the risk of respiratory diseases (COPD, lung cancer, and COVID-19) was observed (COPD: pooled HR = 1.032, 95% CI: 1.004-1.061; lung cancer: pooled HR = 1.017, 95% CI: 1.015-1.020; and COVID-19: pooled RR = 1.004, 95% CI: 1.002-1.006 per 1 μg/m3 increase in PM2.5). Also, a significant relationship was observed between PM10 and respiratory diseases (COPD, LRIs, and COVID-19) based on time-series and cohort studies. Although the number of studies in this field is limited, which requires more investigations, it can be concluded that outdoor particulate matter can increase the risk of respiratory diseases.

Effects of air pollution on emergency visits for acute otitis media among children: a case-crossover study in Chongqing, China

Background

Many epidemiological studies have demonstrated the short-term effects of air pollution on acute otitis media (AOM) in children, but few studies have explored the association between AOM and air pollution in Chinese children. This study aimed to analyze the effects of air pollution on emergency visits for AOM among children through a time-stratified case-crossover design in Chongqing, China.

Methods

The outpatient medical records of children from nine main urban districts who presented with AOM between December 22, 2018 and December 21, 2021 were collected from the Children's Hospital of Chongqing Medical University. Data for air pollution variables, including the air quality index (AQI), particulate matter ≤ 10 μm (PM10), PM2.5, SO2, CO, NO2 and O3 from 17 monitoring sites were collected. Data for meteorological factors as confounding variables also were collected. Conditional logistic regression was used to analyze the data with single-pollutant models, multi-pollutant models, and stratified analyses.

Results

Increases in AQI, PM10, PM2.5, SO2, CO and NO2 were positively associated with emergency visits for AOM among children in single-pollutant models and stratified analyses. Increases in PM10, SO2, CO and NO2 were positively associated with emergency visits for AOM among children in multi-pollutant models. NO2 had the most statistically significant OR values in all models, whereas significant effects of O3 were observed only in seasonal stratification. In single-pollutant models, we found that the best lag periods were lag 0-7 for air pollution variables except for O3 and the largest OR values were 1.185 (95%CI: 1.129-1.245) for SO2 in single-pollutant models. In stratified analyses, there were no difference between groups in these statistically significant OR values through gender and age stratification, while the differences between seasons in these OR values of PM10, SO2, CO, NO2 and O3 were statistically significant. Children aged 0 years and 3-5 years represented the most susceptible population, and among the seasons, susceptibility was greater during Winter and Spring.

Conclusion

Short-term exposure to air pollution can increase emergency visits for AOM among children in Chongqing, China.

Associations between air pollutants and risk of respiratory infection: patient-based bacterial culture in sputum

Air pollution is a crucial risk factor for respiratory infection. However, the relationships between air pollution and respiratory infection based on pathogen detection are scarcely explored in the available literature. We detected respiratory infections through patient-based bacterial culture in sputum, obtained hourly data of all six pollutants (PM_2.5, PM₁₀, SO₂, NO, CO, and O₃) from four air quality monitoring stations, and assessed the relationships of air pollutants and respiratory bacterial infection and multi-drug-resistant bacteria. Air pollution remains a challenge for Mianyang, China, especially PM_2.5 and PM₁₀, and there are seasonal differences; pollution is the heaviest in winter and the lowest in summer. A total of 4237 pathogenic bacteria were detected, and the positive rate of multi-drug-resistant bacteria was 0.38%. Similar seasonal differences were found with respect to respiratory infection. In a single-pollutant model, all pollutants were significantly associated with respiratory bacterial infection, but only O₃ was significantly associated with multi-drug-resistant bacteria. In multi-pollutant models (adjusted for one pollutant), the relationships of air pollutants with respiratory bacterial infection remained significant, while PM_2.5, PM₁₀, and O₃ were significantly associated with the risk of infection with multi-drug-resistant bacteria. When adjusted for other five pollutants, only O₃ was significantly associated with respiratory bacterial infection and the risk of infection with multi-drug-resistant bacteria, showing that O₃ is an independent risk factor for respiratory bacterial infection and infection with multi-drug-resistant bacteria. In summary, this study highlights the adverse effects of air pollution on respiratory infection and the risk of infection with multi-drug-resistant bacteria, which may provide a basis for the formulation of environmental policy to prevent respiratory infections.

Associations between ambient fine particulate matter and child respiratory infection: The role of particulate matter source composition in Dhaka, Bangladesh

Air pollution in the form of fine particulate matter (PM_2.5) has been linked to adverse respiratory outcomes in children. However, the magnitude of this association in South Asia and sources of PM_2.5 that drive adverse health effects are largely unknown. This study evaluates associations between short-term variation in ambient PM_2.5 and incidence of pneumonia and upper respiratory infections among children in Dhaka, Bangladesh. We also perform an exploratory analysis of the PM_2.5 source composition that is most strongly associated with health endpoints. We leveraged data from health surveillance of children less than five years of age between 2005 and 2014 in Kamalapur, Bangladesh, including daily physician-confirmed diagnoses of pneumonia and upper respiratory infection. Twice-weekly source-apportioned ambient PM_2.5 measurements were obtained for the same period, and Poisson regression adjusted for time-varying covariates was used to estimate lagged associations between ambient PM_2.5 and respiratory infection. We use complementary matching and stratification approaches to evaluate whether these associations vary across PM_2.5 source composition. Total PM_2.5 mass was associated with a modest increase in incidence of pneumonia, with a peak effect size two days after exposure (rate ratio = 1.032; 95% confidence interval = 1.008-1.056). We did not identify a significant association between PM_2.5 and upper respiratory infection. Stratified and matching analyses suggested this association was stronger among days when ambient PM_2.5 had a higher mass percent associated with brick kiln and fugitive lead emissions.: This study suggests that elevated ambient PM_2.5 contributes to increased incidence of child pneumonia in urban Dhaka, and that this relationship varies among days with different source composition of PM_2.5.

Effects of Fine Particulate Matter and Its Components on Emergency Room Visits for Pediatric Pneumonia: A Time-Stratified Case-Crossover Study

Pneumonia, one of the important causes of death in children, may be induced or aggravated by particulate matter (PM). Limited research has examined the association between PM and its constituents and pediatric pneumonia-related emergency department (ED) visits. Measurements of PM_2.5, PM₁₀, and four PM_2.5 constituents, including elemental carbon (EC), organic carbon (OC), nitrate, and sulfate, were extracted from 2007 to 2010 from one core station and two satellite stations in Kaohsiung City, Taiwan. Furthermore, the medical records of patients under 17 years old who had visited the ED in a medical center and had a diagnosis of pneumonia were collected. We used a time-stratified, case-crossover study design to estimate the effect of PM. The single-pollutant model demonstrated interquartile range increase in PM_2.5, PM₁₀, nitrate, OC, and EC on lag 3, which increased the risk of pediatric pneumonia by 18.2% (95% confidence interval (Cl), 8.8-28.4%), 13.1% (95% CI, 5.1-21.7%), 29.7% (95% CI, 16.4-44.5%), 16.8% (95% CI, 4.6-30.4%), and 14.4% (95% Cl, 6.5-22.9%), respectively. After PM_2.5, PM₁₀, and OC were adjusted for, nitrate and EC remained significant in two-pollutant models. Subgroup analyses revealed that nitrate had a greater effect on children during the warm season (April to September, interaction p = 0.035). In conclusion, pediatric pneumonia ED visit was related to PM_2.5 and its constituents. Moreover, PM_2.5 constituents, nitrate and EC, were more closely associated with ED visits for pediatric pneumonia, and children seemed to be more susceptible to nitrate during the warm season.

Tracking Air Pollution in China: Near Real-Time PM2.5 Retrievals from Multisource Data Fusion

Air pollution has altered the Earth's radiation balance, disturbed the ecosystem, and increased human morbidity and mortality. Accordingly, a full-coverage high-resolution air pollutant data set with timely updates and historical long-term records is essential to support both research and environmental management. Here, for the first time, we develop a near real-time air pollutant database known as Tracking Air Pollution in China (TAP, http://tapdata.org.cn/) that combines information from multiple data sources, including ground observations, satellite aerosol optical depth (AOD), operational chemical transport model simulations, and other ancillary data such as meteorological fields, land use data, population, and elevation. Daily full-coverage PM_2.5 data at a spatial resolution of 10 km is our first near real-time product. The TAP PM_2.5 is estimated based on a two-stage machine learning model coupled with the synthetic minority oversampling technique and a tree-based gap-filling method. Our model has an averaged out-of-bag cross-validation R² of 0.83 for different years, which is comparable to those of other studies, but improves its performance at high pollution levels and fills the gaps in missing AOD on daily scale. The full coverage and near real-time updates of the daily PM_2.5 data allow us to track the day-to-day variations in PM_2.5 concentrations over China in a timely manner. The long-term records of PM_2.5 data since 2000 will also support policy assessments and health impact studies. The TAP PM_2.5 data are publicly available through our website for sharing with the research and policy communities.

The Impact of an Urban Scrapyard Fire on Respiratory-Related Pediatric Emergency Department Visits

OBJECTIVE

In Philadelphia, a scrapyard fire generated PM2.5 concentrations >1000 μg/m. We assessed whether this was associated with pediatric emergency department visits for respiratory diagnoses.

DESIGN/METHODS

Retrospective observational study using electronic health record data from a local, academic pediatric hospital.

RESULTS

Compared to the two-week period before the fire, patients living directly north of the fire (downwind) had a significant difference in all asthma diagnoses (OR = 3.02, P = 0.03); asthma and upper respiratory infection (OR = 17.3, P = 0.01); overall admissions (OR = 3.04, P = 01); asthma admissions (OR = 4.45, P = .01); and asthma and upper respiratory infection admissions (OR = 15.0, P = 0.01). We did not observe any significant differences among visits or admissions from patients residing in other adjacent zip codes.

CONCLUSION

A localized, transient increase in PM2.5 was associated with increased pediatric emergency department visits for asthma among patients living downwind of the fire.

Satellite Monitoring for Air Quality and Health

Data from satellite instruments provide estimates of gas and particle levels relevant to human health, even pollutants invisible to the human eye. However, the successful interpretation of satellite data requires an understanding of how satellites relate to other data sources, as well as factors affecting their application to health challenges. Drawing from the expertise and experience of the 2016-2020 NASA HAQAST (Health and Air Quality Applied Sciences Team), we present a review of satellite data for air quality and health applications. We include a discussion of satellite data for epidemiological studies and health impact assessments, as well as the use of satellite data to evaluate air quality trends, support air quality regulation, characterize smoke from wildfires, and quantify emission sources. The primary advantage of satellite data compared to in situ measurements, e.g., from air quality monitoring stations, is their spatial coverage. Satellite data can reveal where pollution levels are highest around the world, how levels have changed over daily to decadal periods, and where pollutants are transported from urban to global scales. To date, air quality and health applications have primarily utilized satellite observations and satellite-derived products relevant to near-surface particulate matter <2.5 μm in diameter (PM_2.5) and nitrogen dioxide (NO₂). Health and air quality communities have grown increasingly engaged in the use of satellite data, and this trend is expected to continue. From health researchers to air quality managers, and from global applications to community impacts, satellite data are transforming the way air pollution exposure is evaluated.

Particulate matter exposure predicts residence in high-risk areas for community acquired pneumonia among hospitalized children

Particulate matter exposure is a risk factor for lower respiratory tract infection in children. Here, we investigated the geospatial patterns of community-acquired pneumonia and the impact of PM_2.5 (particulate matter with an aerodynamic diameter ≤2.5 µm) on geospatial variability of pneumonia in children. We performed a retrospective analysis of prospectively collected population-based surveillance study data of community-acquired pneumonia hospitalizations among children <18 years residing in the Memphis metropolitan area, who were enrolled in the Centers for Disease Control and Prevention sponsored Etiology of Pneumonia in the Community (EPIC) study from January 2010 to June 2012. The outcome measure, residence in high- and low-risk areas for community-acquired pneumonia, was determined by calculating pneumonia incidence rates and performing cluster analysis to identify areas with higher/lower than expected rates of community-acquired pneumonia for the population at risk. High PM_2.5 was defined as exposure to PM_2.5 concentrations greater than the mean value (>10.75 μg/m³), and low PM_2.5 is defined as exposure to PM_2.5 concentrations less than or equal to the mean value (≤10.75 μg/m³). We also assessed the effects of age, sex, race/ethnicity, history of wheezing, insurance type, tobacco smoke exposure, bacterial etiology, and viral etiology of infection. Of 810 (96.1%) subjects with radiographic community-acquired pneumonia, who resided in the Memphis metropolitan area and had addresses which were successfully geocoded (Supplementary Figure F2), 220 (27.2%) patients were identified to be from high- (n = 126) or low-risk (n = 94) community-acquired pneumonia areas. Community-acquired pneumonia in Memphis metropolitan area had a non-homogenous geospatial pattern. PM_2.5 was associated with residence in high-risk areas for community-acquired pneumonia. In addition, children with private insurance and bacterial, as opposed to viral, etiology of infection had a decreased risk of residence in a high-risk area for community-acquired pneumonia. The results from this paper suggest that environmental exposures as well as social risk factors are associated with childhood pneumonia.

Retrospective assessment of pregnancy exposure to particulate matter from desert dust on a Caribbean island: could satellite-based aerosol optical thickness be used as an alternative to ground PM10 concentration?

Desert dust transported from the Saharan-Sahel region to the Caribbean Sea is responsible for peak exposures of particulate matter (PM). This study explored the potential added value of satellite aerosol optical thickness (AOT) measurements, compared to the PM concentration at ground level, to retrospectively assess exposure during pregnancy. MAIAC MODIS AOT retrievals in blue band (AOT₄₇₀) were extracted for the French Guadeloupe archipelago. AOT₄₇₀ values and PM₁₀ concentrations were averaged over pregnancy for 906 women (2005-2008). Regression modeling was used to examine the AOT₄₇₀-PM₁₀ relationship during pregnancy and test the association between dust exposure estimates and preterm birth. Moderate agreement was shown between mean AOT₄₇₀ retrievals and PM₁₀ ground-based measurements during pregnancy (R² = 0.289). The magnitude of the association between desert dust exposure and preterm birth tended to be lower using the satellite method compared to the monitor method. The latter remains an acceptable trade-off between epidemiological relevance and exposure misclassification, in areas with few monitoring stations and complex topographical/meteorological conditions, such as tropical islands.

The Impact of Air Pollution on Outpatient Visits of Children with Asthma in Xi'an, China

INTRODUCTION

The number of children with asthma has increased significantly in China. In recent years, there has been a steady increase in outpatient visits of children with asthma, attributed to poor air quality and environmental pollution reported regionally and at our institution. This study aimed to assess the association between air pollution and the number of outpatient visits of children with asthma in Xi'an, the largest city in northwest China.

METHODS

We searched the database of the largest children's hospital in Xi'an for related information from 2014 to 2018 and then acquired data on air pollution, including the daily average concentrations of fine particles (PM_2.5), inhalable particles (PM₁₀), nitrogen dioxide (NO₂), and sulfur dioxide (SO₂) of that same time period. Time-series generalized additive models were used to analyze the relationships.

RESULTS

Our results revealed that air pollution was very serious in Xi'an, with elevated average concentrations of PM_2.5, PM₁₀, and NO₂ from 2015 to 2018. The relative risk of outpatient visits due to asthma associated with PM_2.5, PM₁₀, and SO₂ pollution rose significantly and reached 1.11 (1.02-1.21), 1.25 (1.01-1.55), and 1.71 (1.31-2.25), respectively, when there was a 10 ug·m^-3 increase in concentration, during a lag of 21 d.

CONCLUSIONS

A high concentration of particulate matter (PM_2.5 and PM₁₀) was the prominent feature of air pollution in Xi'an. Exposure to air pollutant (PM_2.5, PM₁₀, SO₂) was positively associated with an increased risk of children's outpatient visits for asthma in Xi'an.

Assessment of the effects of atmospheric pollutants using the animal model Caenorhabditis elegans

Air pollution is recognized as the world's largest environmental health risk. In this work we evaluated in vivo the effects of three relevant components of atmospheric dusts (brake dust, wood pellet ash and Saharan dust) employing the animal model Caenorhabditis elegans. Main endpoints of C. elegans such as life span, brood size and oxidative stress were addressed by exposing the nematodes to different dust concentrations. Brake dust and pellet ash affected the life span and increased significantly the oxidative stress of exposed nematodes, while Saharan dust showed no effects. Water soluble and insoluble fractions of these dusts were used to investigate the impact of the single fraction on C. elegans. The two fractions of brake dust and pellet ash exerted different effects on C. elegans endpoints in terms of life span and oxidative stress response. These fractions acted in different ways on the worm susceptibility to infection of two human pathogens (Staphylococcus aureus and Pseudomonas aeruginosa) affecting the sek-1 gene expression. In conclusion, our study showed that C. elegans is a valuable tool to investigate in vivo possible effects of atmospheric dusts.

Earth Observation Data Supporting Non-Communicable Disease Research: A Review

A disease is non-communicable when it is not transferred from one person to another. Typical examples include all types of cancer, diabetes, stroke, or allergies, as well as mental diseases. Non-communicable diseases have at least two things in common—environmental impact and chronicity. These diseases are often associated with reduced quality of life, a higher rate of premature deaths, and negative impacts on a countries’ economy due to healthcare costs and missing work force. Additionally, they affect the individual’s immune system, which increases susceptibility toward communicable diseases, such as the flu or other viral and bacterial infections. Thus, mitigating the effects of non-communicable diseases is one of the most pressing issues of modern medicine, healthcare, and governments in general. Apart from the predisposition toward such diseases (the genome), their occurrence is associated with environmental parameters that people are exposed to (the exposome). Exposure to stressors such as bad air or water quality, noise, extreme heat, or an overall unnatural surrounding all impact the susceptibility to non-communicable diseases. In the identification of such environmental parameters, geoinformation products derived from Earth Observation data acquired by satellites play an increasingly important role. In this paper, we present a review on the joint use of Earth Observation data and public health data for research on non-communicable diseases. We analyzed 146 articles from peer-reviewed journals (Impact Factor ≥ 2) from all over the world that included Earth Observation data and public health data for their assessments. Our results show that this field of synergistic geohealth analyses is still relatively young, with most studies published within the last five years and within national boundaries. While the contribution of Earth Observation, and especially remote sensing-derived geoinformation products on land surface dynamics is on the rise, there is still a huge potential for transdisciplinary integration into studies. We see the necessity for future research and advocate for the increased incorporation of thematically profound remote sensing products with high spatial and temporal resolution into the mapping of exposomes and thus the vulnerability and resilience assessment of a population regarding non-communicable diseases.

Associations between Particulate Matter and Otitis Media in Children: A Meta-Analysis

Particulate matter (PM), a primary component of air pollution, is a suspected risk factor for the development of otitis media (OM). However, the results of studies on the potential correlation between an increase in the concentration of PM and risk of developing OM are inconsistent. To better characterize this potential association, a meta-analysis of studies indexed in three global databases (PubMed, EMBASE, and The Cochrane Library) was conducted. These databases were systematically screened for observational studies of PM concentration and the development of OM from the time of their inception to 31 March 2020. Following these searches, 12 articles were analyzed using pooled odds ratios generated from random-effects models to test for an association between an increased concentration of PM and the risk of developing OM. The data were analyzed separately according to the size of particulate matter as PM_2.5 and PM₁₀. The pooled odds ratios for each 10 μg/m³ increase in PM_2.5 and PM₁₀ concentration were 1.032 (95% confidence interval (CI), 1.005–1.060) and 1.010 (95% CI, 1.008–1.012), respectively. Specifically, the pooled odds ratios were significant within the short-term studies (PM measured within 1 week of the development of OM), as 1.024 (95% CI, 1.008–1.040) for PM_2.5 concentration and 1.010 (95% CI, 1.008–1.012) for PM₁₀ concentration. They were significant for children under 2 years of age with pooled odds ratios of 1.426 (95% CI, 1.278–1.519) for an increase in the concentration of PM_2.5. The incidence of OM was not correlated with the concentration of PM, but was correlated with an increase in the concentration of PM. In conclusion, an increase in the concentration of PM_2.5 is more closely associated with the development of OM compared with an increase in the concentration of PM₁₀; this influence is more substantial in shorter-term studies and for younger children.

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.

Influence of air pollutants on pneumonia hospitalizations among children in a town in the Brazilian Legal Amazon region: a time series study

BACKGROUND

Exposure to particulate material produced as a result of increased agricultural activity may increase the number of pneumonia hospitalizations among children. We hope to contribute to the knowledge base through highlighting the environmental mechanisms involved in this outcome and optimizing pollutant control policies.

OBJECTIVES

To investigate the association between pneumonia hospitalizations among children and presence of environmental pollutants in a town in the Brazilian Legal Amazon region.

DESIGN AND SETTING

Time series study conducted in the town of Tangará da Serra, Mato Grosso (MT), Brazil.

METHODS

A total of 158 children aged 0 to 10 years participated in the study. Data on environmental variables and pollutants were extracted daily through the Coupled Chemistry-Aerosol-Tracer Transport model coupled to Brazilian Regional Atmospheric Modeling System (CCATT-BRAMS). Meteorological data were provided by the Weather Forecasting and Climate Studies Center (CPTEC).

RESULTS

There was greater frequency of pneumonia hospitalizations in the months of transition between the rainy and dry seasons, with a prevalence ratio 2.4 times higher than in other periods. For environmental pollutants, there was a significant positive correlation between particulate matter (PM2.5) and pneumonia hospitalizations (correlation 0.11), with more admissions on the days when PM2.5 levels were highest (averages of 6.6 µg/m3 when there were no admissions and 13.11 µg/m3 on days with two or more admissions).

CONCLUSIONS

The higher the PM2.5 level was, the greater the frequency of hospitalizations also was. Children living in peripheral areas had higher prevalence of pneumonia hospitalizations in the dry period than those who were living in the town center.

Cohort study of respiratory hospital admissions, air quality and sociodemographic factors in preterm infants born in California

BACKGROUND

Preterm infants suffer from respiratory morbidity especially during the first year of life.

OBJECTIVE

To investigate the association of air quality and sociodemographic indicators on hospital admission rates for respiratory causes.

METHODS

This is a retrospective cohort study. We identified all live-born preterm infants in California from 2007 to 2012 in a population-based administrative data set and linked them to a data set measuring several air quality and sociodemographic indicators at the census tract level. All sociodemographic and air quality predictors were divided into quartiles (first quartile most favourable to the fourth quartile least favourable). Mixed effect logistic models to account for clustering at the census tract level were used to investigate associations between chronic air quality and sociodemographic indicators respiratory hospital admission during the first year of life.

RESULTS

Of 205 178 preterm infants, 5.9% (n = 12 033) were admitted to the hospital for respiratory causes during the first year. In the univariate analysis, comparing the first to the fourth quartile of chronic ozone (risk ratio [RR] 1.29, 95% confidence interval [CI] 1.21, 1.37), diesel (RR 1.10, 95% CI 1.02, 1.17) and particulate matter 2.5 (RR 1.07, 95% CI 1.01, 1.14) exposure were associated with hospital admission during the first year. Following adjustment for confounders, the risk ratios for hospital admission during the first year were 1.53 (95% CI 1.37, 1.72) in relation to educational attainment (per cent of the population over age 25 with less than a high school education) and 1.23 (95% CI 1.09, 1.38) for poverty (per cent of the population living below two times the federal poverty level).

CONCLUSIONS

Among preterm infants, respiratory hospital admissions in the first year in California are associated with socioeconomic characteristics of the neighbourhood an individual is living in.

Contribution of Satellite-Derived Aerosol Optical Depth PM2.5 Bayesian Concentration Surfaces to Respiratory-Cardiovascular Chronic Disease Hospitalizations in Baltimore, Maryland

The fine particulate matter baseline (PMB), which includes PM_2.5 monitor readings fused with Community Multiscale Air Quality (CMAQ) model predictions, using the Hierarchical Bayesian Model (HBM), is less accurate in rural areas without monitors. To address this issue, an upgraded HBM was used to form four experimental aerosol optical depth (AOD)-PM_2.5 concentration surfaces. A case-crossover design and conditional logistic regression evaluated the contribution of the AOD-PM_2.5 surfaces and PMB to four respiratory-cardiovascular hospital events in all 99 12 km² CMAQ grids, and in grids with and without ambient air monitors. For all four health outcomes, only two AOD-PM_2.5 surfaces, one not kriged (PMC) and the other kriged (PMCK), had significantly higher Odds Ratios (ORs) on lag days 0, 1, and 01 than PMB in all grids, and in grids without monitors. In grids with monitors, emergency department (ED) asthma PMCK on lag days 0, 1 and 01 and inpatient (IP) heart failure (HF) PMCK ORs on lag days 01 were significantly higher than PMB ORs. Warm season ORs were significantly higher than cold season ORs. Independent confirmation of these results should include AOD-PM_2.5 concentration surfaces with greater temporal-spatial resolution, now easily available from geostationary satellites, such as GOES-16 and GOES-17.

A comparison of statistical and machine learning methods for creating national daily maps of ambient PM2.5 concentration

A typical challenge in air pollution epidemiology is to perform detailed exposure assessment for individuals for which health data are available. To address this problem, in the last few years, substantial research efforts have been placed in developing statistical methods or machine learning techniques to generate estimates of air pollution at fine spatial and temporal scales (daily, usually) with complete coverage. However, it is not clear how much the predicted exposures yielded by the various methods differ, and which method generates more reliable estimates. In this paper, we aim to address this gap by evaluating a variety of exposure modeling approaches, comparing their predictive performance. Using PM2.5 in year 2011 over the continental U.S. as a case study, we generate national maps of ambient PM2.5 concentration using: (i) ordinary least squares and inverse distance weighting; (ii) kriging; (iii) statistical downscaling models, that is, spatial statistical models that use the information contained in air quality model outputs; (iv) land use regression, that is, linear regression modeling approaches that leverage the information in Geographical Information System (GIS) covariates; and (v) machine learning methods, such as neural networks, random forests and support vector regression. We examine the various methods' predictive performance via cross-validation using Root Mean Squared Error, Mean Absolute Deviation, Pearson correlation, and Mean Spatial Pearson Correlation. Additionally, we evaluated whether factors such as, season, urbanicty, and levels of PM2.5 concentration (low, medium or high) affected the performance of the different methods. Overall, statistical methods that explicitly modeled the spatial correlation, e.g. universal kriging and the downscaler model, outperform all the other exposure assessment approaches regardless of season, urbanicity and PM2.5 concentration level. We posit that the better predictive performance of spatial statistical models over machine learning methods is due to the fact that they explicitly account for spatial dependence, thus borrowing information from neighboring observations. In light of our findings, we suggest that future exposure assessment methods for regional PM2.5 incorporate information from neighboring sites when deriving predictions at unsampled locations or attempt to account for spatial dependence.

Source apportionment of primary and secondary PM2.5: Associations with pediatric respiratory disease emergency department visits in the U.S. State of Georgia

We developed a hybrid chemical transport model and receptor model (CTM-RM) to conduct source apportionment of both primary and secondary PM_2.5 (particulate matter ≤2.5 μm in diameter) at 36 km resolution throughout the U.S. State of Georgia for the years 2005 and 2007. This novel source apportionment model enabled us to estimate and compare associations of short-term changes in 12 PM_2.5 source concentrations (agriculture, biogenic, coal, dust, fuel oil, metals, natural gas, non-road mobile diesel, non-road mobile gasoline, on-road mobile diesel, on-road mobile gasoline, and all other sources) with emergency department (ED) visits for pediatric respiratory diseases. ED visits for asthma (N = 49,651), pneumonia (N = 25,558), and acute upper respiratory infections (acute URI, N = 235,343) among patients aged ≤18 years were obtained from patient claims records. Using a case-crossover study, we estimated odds ratios per interquartile range (IQR) increase for 3-day moving average PM_2.5 source concentrations using conditional logistic regression, matching on day-of-week, month, and year, and adjusting for average temperature, humidity, and holidays. We fit both single-source and multi-source models. We observed positive associations between several PM_2.5 sources and ED visits for asthma, pneumonia, and acute URI. For example, for asthma, per IQR increase in the source contribution in the single-source model, odds ratios were 1.022 (95% CI: 1.013, 1.031) for dust; 1.050 (95% CI: 1.036, 1.063) for metals, and 1.091 (95% CI: 1.064, 1.119) for natural gas. These sources comprised 5.7%, 2.2%, and 6.3% of total PM_2.5 mass, respectively. PM_2.5 from metals and natural gas were positively associated with all three respiratory outcomes. In addition, non-road mobile diesel was positively associated with pneumonia and acute URI.

Spatial and temporal variations of air quality and six air pollutants in China during 2015-2017

Air pollution has aroused significant public concern in China, therefore, long-term air-quality data with high temporal and spatial resolution are needed to understand the variations of air pollution in China. However, the yearly variations with high spatial resolution of air quality and six air pollutants are still unknown for China until now. Therefore, in this paper, we analyze the spatial and temporal variations of air quality and six air pollutants in 366 cities across mainland China during 2015–2017 for the first time to the best of our knowledge. The results indicate that the annual mean mass concentrations of PM2.5, PM10, SO₂, and CO all decreased year by year during 2015–2017. However, the annual mean NO₂ concentrations were almost unchanged, while the annual mean O₃ concentrations increased year by year. Anthropogenic factors were mainly responsible for the variations of air quality. Further analysis suggested that PM2.5 and PM10 were the main factors influencing air quality, while NO₂ played an important role in the formation of PM2.5 and O₃. These findings can provide a theoretical basis for the formulation of future air-pollution control policy in China.

Ambient air pollution is associated with pediatric pneumonia: a time-stratified case-crossover study in an urban area

BACKGROUND

Pneumonia, the leading reason underlying childhood deaths, may be triggered or exacerbated by air pollution. To date, only a few studies have examined the association of air pollution with emergency department (ED) visits for pediatric pneumonia, with inconsistent results. Therefore, we aimed to elucidate the impact of short-term exposure to particulate matter (PM) and other air pollutants on the incidence of ED visits for pediatric pneumonia.

METHODS

PM_2.5, PM₁₀, and other air pollutant levels were measured at 11 air quality-monitoring stations in Kaohsiung City, Taiwan, between 2008 and 2014. Further, we extracted the medical records of non-trauma patients aged ≤17 years and who had visited an ED with the principal diagnosis of pneumonia. A time-stratified case-crossover study design was employed to determine the hazard effect of air pollution in a total of 4024 patients.

RESULTS

The single-pollutant model suggested that per interquartile range increment in PM_2.5, PM₁₀, nitrogen dioxide (NO₂), and sulfur dioxide (SO₂) on 3 days before the event increased the odds of pediatric pneumonia by 14.0% [95% confidence interval (CI), 5.1-23.8%], 10.9% (95% CI, 2.4-20.0%), 14.1% (95% CI, 5.0-24.1%), and 4.5% (95% CI, 0.8-8.4%), respectively. In two-pollutant models, PM_2.5 and NO₂ were significant after adjusting for PM₁₀ and SO₂. Subgroup analyses showed that older children (aged ≥4 years) were more susceptible to PM_2.5 (interaction p = 0.024) and children were more susceptible to NO₂ during warm days (≥26.5 °C, interaction p = 0.011).

CONCLUSIONS

Short-term exposure to PM_2.5 and NO₂ possibly plays an important role in pediatric pneumonia in Kaohsiung, Taiwan. Older children are more susceptible to PM_2.5, and all children are more susceptible to NO₂ during warm days.

Time-series analysis of satellite-derived fine particulate matter pollution and asthma morbidity in Jackson, MS

In order to examine associations between asthma morbidity and local ambient air pollution in an area with relatively low levels of pollution, we conducted a time-series analysis of asthma hospital admissions and fine particulate matter pollution (PM_2.5) in and around Jackson, MS, for the period 2003 to 2011. Daily patient-level records were obtained from the Mississippi State Department of Health (MSDH) Asthma Surveillance System. Patient geolocations were aggregated into a grid with 0.1° × 0.1° resolution within the Jackson Metropolitan Statistical Area. Daily PM_2.5 concentrations were estimated via machine-learning algorithms with remotely sensed aerosol optical depth and other associated parameters as inputs. Controlling for long-term temporal trends and meteorology, we estimated a 7.2% (95% confidence interval 1.7-13.1%) increase in daily all-age asthma emergency room admissions per 10 μg/m³ increase in the 3-day average of PM_2.5 levels (current day and two prior days). Stratified analyses reveal significant associations between asthma and 3-day average PM_2.5 for males and blacks. Our results contribute to the current epidemiologic evidence on the association between acute ambient air pollution exposure and asthma morbidity, even in an area characterized by relatively good air quality.

Impact of air pollution control policies on cardiorespiratory emergency department visits, Atlanta, GA, 1999-2013

BACKGROUND

Air pollution control policies resulting from the 1990 Clean Air Act Amendments were aimed at reducing pollutant emissions, ambient concentrations, and ultimately adverse health outcomes.

OBJECTIVES

As part of a comprehensive air pollution accountability study, we used a counterfactual study design to estimate the impact of mobile source and electricity generation control policies on health outcomes in the Atlanta, GA, metropolitan area from 1999 to 2013.

METHODS

We identified nine sets of pollution control policies, estimated changes in emissions in the absence of these policies, and employed those changes to estimate counterfactual daily ambient pollutant concentrations at a central monitoring location. Using a multipollutant Poisson time-series model, we estimated associations between observed pollutant levels and daily counts of cardiorespiratory emergency department (ED) visits at Atlanta hospitals. These associations were then used to estimate the number of ED visits prevented due to control policies, comparing observed to counterfactual daily concentrations.

RESULTS

Pollution control policies were estimated to substantially reduce ambient concentrations of the nine pollutants examined for the period 1999-2013. We estimated that pollutant concentration reductions resulting from the control policies led to the avoidance of over 55,000 cardiorespiratory disease ED visits in the five-county metropolitan Atlanta area, with greater proportions of visits prevented in later years as effects of policies became more fully realized. During the final two years of the study period, 2012-2013, the policies were estimated to prevent 16.5% of ED visits due to asthma (95% interval estimate: 7.5%, 25.1%), 5.9% (95% interval estimate: -0.4%, 12.3%) of respiratory ED visits, and 2.3% (95% interval estimate: -1.8%, 6.2%) of cardiovascular disease ED visits.

DISCUSSION

Pollution control policies resulting from the 1990 Clean Air Act Amendments led to substantial estimated reductions in ambient pollutant concentrations and cardiorespiratory ED visits in the Atlanta area.

Ambient fine particulate matter inhibits innate airway antimicrobial activity in preschool children in e-waste areas

Ambient fine particulate matter (PM_2.5) is a risk factor for respiratory diseases. Previous studies suggest that PM_2.5 exposure may down-regulate airway antimicrobial proteins and peptides (AMPs), thereby accelerating airway pathogen infection. However, epidemiological research is scarce. Hence, we estimated the associations between individual PM_2.5 chronic daily intake (CDI) and the levels of the airway AMP salivary agglutinin (SAG), as well as peripheral leukocyte counts and pro-inflammatory cytokines, of preschool children in Guiyu (an e-waste area) and Haojiang (a reference area located 31.6 km to the east of Guiyu). We recruited 581 preschool children from Guiyu and Haojiang, of which 222 were included in this study for a matching design (Guiyu: n = 110 vs. Haojiang: n = 112). Air PM_2.5 pollution data was collected to calculate individual PM_2.5 CDI. The mean concentration of PM_2.5 in Guiyu was higher than in Haojiang, resulting in a higher individual PM_2.5 CDI. Concomitantly, saliva SAG levels were lower in Guiyu children (5.05 ng/mL) than in Haojiang children (8.68 ng/mL), and were negatively correlated with CDI. Additionally, peripheral counts of white blood cells, and the concentrations of interleukin-8 and tumor necrosis factor-alpha, in Guiyu children were greater than in Haojiang children, and were positively associated with CDI. Similar results were found for neutrophils and monocytes. To our knowledge, this is the first study on the relationship between PM_2.5 exposure and innate airway antimicrobial activity in children, in an e-waste area, showing that PM_2.5 pollution may weaken airway antimicrobial activity by down-regulation of saliva SAG levels, which might accelerate airway pathogen infection in children.

Satellite-based short- and long-term exposure to PM2.5 and adult mortality in urban Beijing, China

Severe and persistent haze accompanied by high concentrations of fine particulate matter (PM_2.5) has become a great public health concern in urban China. However, research on the health effects of PM_2.5 in China has been hindered by the lack of high-quality exposure estimates. In this study, we assessed the excess mortality associated with both short- and long-term exposure to ambient PM_2.5 simultaneously using satellite-derived exposure data at a high spatiotemporal resolution. Adult registries of non-accidental, respiratory and cardiovascular deaths in urban Beijing in 2013 were collected. Exposure levels were estimated from daily satellite-based PM_2.5 concentrations at 1 km spatial resolution from 2004 to 2013. Mixed Poisson regression models were fitted to estimate the cause-specific mortality in association with PM_2.5 exposures. With the mutual adjustment of short- and long-term exposure of PM_2.5, the percent increases associated with every 10 μg/m³ increase in short-term PM_2.5 exposure were 0.09% (95% CI: -0.14%, 0.33%; lag 01), 1.02% (95% CI: 0.08%, 1.97%; lag 04) and 0.09% (95% CI: -0.23%, 0.42%; lag 01) for non-accidental, respiratory and cardiovascular mortality, respectively; those attributable to every 10 μg/m³ increase in long-term PM_2.5 exposure (9-year moving average) were 16.78% (95% CI: 10.58%, 23.33%), 44.14% (95% CI: 20.73%, 72.10%) and 3.72% (95% CI: -3.75%, 11.77%), respectively. Both associations of short- and long-term exposure with the cause-specific mortality decreased after they were mutually adjusted. Associations between short-term exposure to satellite-based PM_2.5 and cause-specific mortality were larger than those estimated using fixed measurements. Satellite-based PM_2.5 predictions help to improve the spatiotemporal resolution of exposure assessments and the mutual adjustment model provide better estimation of PM_2.5 associated health effects. Effects attributable to long-term exposure of PM_2.5 were larger than those of short-term exposure, which should be more concerned for public health.

Associations between birth outcomes and maternal PM2.5 exposure in Shanghai: A comparison of three exposure assessment approaches

BACKGROUND

Few studies have estimated effects of maternal PM_2.5 exposure on birth outcomes in China due to the lack of historical air pollution data.

OBJECTIVES

We estimated the associations between maternal PM_2.5 exposure and birth outcomes using gap-filled satellite estimates in Shanghai, China.

METHODS

We obtained birth registration records of 132,783 singleton live births during 2011-2014 in Shanghai. PM_2.5 exposures were assessed from satellite-derived estimates or central-site measurements. Linear and logistic regressions were used to estimate associations with term birth weight and term low birth weight (LBW), respectively. Logistic and discrete-time survival models were used to estimate associations with preterm birth. Effect modification by maternal age and parental education levels was investigated.

RESULTS

A 10 μg/m³ increase in gap-filled satellite-based whole-pregnancy PM_2.5 exposure was associated with a -12.85 g (95% CI: -18.44, -7.27) change in term birth weight, increased risk of preterm birth (OR 1.27, 95% CI: 1.20, 1.36), and increased risk of term LBW (OR 1.22, 95% CI: 1.06, 1.41). Sensitivity analyses during 2013-2014, when ground PM_2.5 measurements were available, showed that the health associations using gap-filled satellite PM_2.5 concentrations were higher than those obtained using satellite PM_2.5 concentrations without accounting for missingness. The health associations using gap-filled satellite PM_2.5 had similar magnitudes to those using central-site measurements, but with narrower confidence intervals.

CONCLUSIONS

The magnitude of associations between maternal PM_2.5 exposure and adverse birth outcomes in Shanghai was higher than previous findings. One reason could be reduced exposure error of the gap-filled high-resolution satellite PM_2.5 estimates.

Associations of mobile source air pollution during the first year of life with childhood pneumonia, bronchiolitis, and otitis media

Supplemental Digital Content is available in the text.

Background:

Exposure to air pollution from motor vehicles in early life may increase susceptibility to common pediatric infections.

Methods:

We estimated associations between residential exposure to primary fine particulate matter, nitrogen oxides, and carbon monoxide from traffic during the first year of life and incident pneumonia, bronchiolitis, and otitis media events by age 2 years in 22,441 children from the Kaiser Air Pollution and Pediatric Asthma Study, a retrospective birth cohort of children born during 2000–2010 and insured by Kaiser Permanente Georgia. Time to first clinical diagnosis of each outcome was defined using medical records. Exposure to traffic pollutants was based on observation-calibrated estimates from A Research LINE-source dispersion model for near surface releases and child residential histories. Associations were modeled using Cox proportional hazards models, with exposure as a continuous linear variable, a natural-log transformed continuous variable, and categorized by quintiles.

Results:

During follow-up, 2,181 children were diagnosed with pneumonia, 5,533 with bronchiolitis, and 14,374 with otitis media. We observed positive associations between early-life traffic exposures and all three outcomes; confidence intervals were widest for pneumonia as it was the least common outcome. For example, adjusted hazard ratios for a 1-unit increase in nitrogen oxides on the natural log scale (a 2.7-fold increase) were 1.19 (95% CI = 1.12, 1.27) for bronchiolitis, 1.17 (1.12, 1.22) for otitis media, and 1.08 (0.97, 1.20) for pneumonia.

Conclusions:

Our results provide evidence for modest, positive associations between exposure to traffic emissions and common pediatric infections during early childhood.

Air Pollution and Otitis Media in Children: A Systematic Review of Literature

Young children are particularly vulnerable to otitis media (OM) which globally affects over 80% of children below the age of 3 years. Although there is convincing evidence for an association between environmental tobacco smoke exposure and OM in children, the relationship with ambient air pollution is not clear. We aimed to systematically review the literature on the relationship between ambient air pollution exposure and OM in children. A systematic search was performed in PubMed and EMBASE databases. Of 934 references identified, 24 articles were included. There is an increasing body of evidence supporting an association between higher ambient air pollution exposure and a higher risk of OM in children. While NO₂ showed the most consistent association with OM, other specific pollutants showed inconsistent associations. Studies were mainly conducted in high/middle income countries with limited evidence from low-income countries. Although there was a general consensus that higher air pollution exposure is associated with a greater prevalence of OM, the evidence for associations with specific pollutants is inconsistent. More well-designed studies on associations between specific air pollutants as risk factors for OM are warranted, especially in low income countries with high air pollution levels.

Assessment of PM2.5 concentrations and exposure throughout China using ground observations

Exposure to PM2.5 results in negative effects on human health. However, PM2.5 exposure at the national scale is poorly known for China owing to limited spatial and temporal PM2.5 concentration data. In this study, we present analyses of PM2.5 exposure throughout China using high-resolution temporal and spatial ground-level PM2.5 data from 2015. Our results indicated that the annual mean PM2.5 concentration was 52.81μg/m³, and that the highest annual mean PM2.5 concentrations primarily appeared in the North China Plain. We also found the lowest and highest monthly mean PM2.5 concentrations appeared in August and January, respectively, while the lowest and highest diurnal mean PM2.5 concentrations occurred at 16:00 and 10:00, respectively. Moreover, comparisons to data from 2013 indicated that the annual mean PM2.5 concentrations decreased by 12.31% from 2013 to 2015, which was likely due to the implementation of environmental protection laws in early 2015. Our findings provide new insights, for not only studies of PM2.5 exposure and human health, but also to inform the implementation of national and regional air pollution reduction policies.

Short-term association between ambient air pollution and pneumonia in children: A systematic review and meta-analysis of time-series and case-crossover studies

Ambient air pollution has been associated with respiratory diseases in children. However, its effects on pediatric pneumonia have not been meta-analyzed. We conducted a systematic review and meta-analysis of the short-term association between ambient air pollution and hospitalization of children due to pneumonia. We searched the Web of Science and PubMed for indexed publications up to January 2017. Pollutant-specific excess risk percentage (ER%) and confidence intervals (CI) were estimated using random effect models for particulate matter (PM) with diameter ≤ 10 (PM₁₀) and ≤2.5 μm (PM_2.5), sulfur dioxide (SO₂), ozone (O₃), nitrogen dioxide (NO₂), and carbon monoxide (CO). Results were further stratified by subgroups (children under five, emergency visits versus hospital admissions, income level of study location, and exposure period). Seventeen studies were included in the meta-analysis. The ER% per 10 μg/m³ increase of pollutants was 1.5% (95% CI: 0.6%-2.4%) for PM₁₀ and 1.8% (95% CI: 0.5%-3.1%) for PM_2.5. The corresponding values per 10 ppb increment of gaseous pollutants were 2.9% (95% CI: 0.4%-5.3%) for SO₂, 1.7% (95% CI: 0.5%-2.8%) for O₃, and 1.4% (95% CI: 0.4%-2.4%) for NO₂. ER% per 1000 ppb increment of CO was 0.9% (95% CI: 0.0%-1.9%). Associations were not substantially different between subgroups. This meta-analysis shows a positive association between daily levels of ambient air pollution markers and hospitalization of children due to pneumonia. However, lack of studies from low-and middle-income countries limits the quantitative generalizability given that susceptibilities to the adverse effects of air pollution may be different in those populations. The meta-regression in our analysis further demonstrated a strong effect of country income level on heterogeneity.

Associations between Ambient Fine Particulate Oxidative Potential and Cardiorespiratory Emergency Department Visits

BACKGROUND

Oxidative potential (OP) has been proposed as a measure of toxicity of ambient particulate matter (PM).

OBJECTIVES

Our goal was to address an important research gap by using daily OP measurements to conduct population-level analysis of the health effects of measured ambient OP.

METHODS

A semi-automated dithiothreitol (DTT) analytical system was used to measure daily average OP (OP^DTT) in water-soluble fine PM at a central monitor site in Atlanta, Georgia, over eight sampling periods (a total of 196 d) during June 2012-April 2013. Data on emergency department (ED) visits for selected cardiorespiratory outcomes were obtained for the five-county Atlanta metropolitan area. Poisson log-linear regression models controlling for temporal confounders were used to conduct time-series analyses of the relationship between daily counts of ED visits and either the 3-d moving average (lag 0-2) of OP^DTT or same-day OP^DTT. Bipollutant regression models were run to estimate the health associations of OP^DTT while controlling for other pollutants.

RESULTS

OP^DTT was measured for 196 d (mean=0.32 nmol/min/m³, interquartile range=0.21). Lag 0-2 OP^DTT was associated with ED visits for respiratory disease (RR=1.03, 95% confidence interval (CI): 1.00, 1.05 per interquartile range increase in OP^DTT), asthma (RR=1.12, 95% CI: 1.03, 1.22), and ischemic heart disease (RR=1.19, 95% CI: 1.03, 1.38). Same-day OP^DTT was not associated with ED visits for any outcome. Lag 0-2 OP^DTT remained a significant predictor of asthma and ischemic heart disease in most bipollutant models.

CONCLUSIONS

Lag 0-2 OP^DTT was associated with ED visits for multiple cardiorespiratory outcomes, providing support for the utility of OP^DTT as a measure of fine particle toxicity. https://doi.org/10.1289/EHP1545.

The Potential Impact of Satellite-Retrieved Cloud Parameters on Ground-Level PM2.5 Mass and Composition

Satellite-retrieved aerosol optical properties have been extensively used to estimate ground-level fine particulate matter (PM2.5) concentrations in support of air pollution health effects research and air quality assessment at the urban to global scales. However, a large proportion, ~70%, of satellite observations of aerosols are missing as a result of cloud-cover, surface brightness, and snow-cover. The resulting PM2.5 estimates could therefore be biased due to this non-random data missingness. Cloud-cover in particular has the potential to impact ground-level PM2.5 concentrations through complex chemical and physical processes. We developed a series of statistical models using the Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product at 1 km resolution with information from the MODIS cloud product and meteorological information to investigate the extent to which cloud parameters and associated meteorological conditions impact ground-level aerosols at two urban sites in the US: Atlanta and San Francisco. We find that changes in temperature, wind speed, relative humidity, planetary boundary layer height, convective available potential energy, precipitation, cloud effective radius, cloud optical depth, and cloud emissivity are associated with changes in PM2.5 concentration and composition, and the changes differ by overpass time and cloud phase as well as between the San Francisco and Atlanta sites. A case-study at the San Francisco site confirmed that accounting for cloud-cover and associated meteorological conditions could substantially alter the spatial distribution of monthly ground-level PM2.5 concentrations.

Ambient air pollution and emergency department visits for asthma in Erie County, New York 2007-2012

PURPOSE

8% of the US population has asthma. Air pollution is linked to exacerbation in susceptible individuals. The objective was to identify air pollutants that increased the risk of asthma emergency department visits during a time wherein a polluting factory was criminally convicted, changing local air pollutant levels.

METHODS

An ecological time-series design used a daily count of asthma emergency visits from 2007 to 2012 as the dependent variable. Independent variables air pollutants (NO₂, PM_2.5 CO, and O₃), controlling for meteorological conditions, were analyzed using time-series and Poisson GLM models.

RESULTS

76,651 emergency asthma visits were included with an average of 35 visits per day (SD = 9.2, range 11-80) in a stationary time series. Increased visit volume in fall and spring had no associations to the air pollutants. Associations between individual air pollutants occurred in otherwise low-volume months for asthma emergency visits. The strongest relationship was an 11.6% increase in the asthma emergency visit rate during the month of June. In monthly groupings that removed most of the autumn and spring months, O₃, PM_2.5, CO, and NO₂ were associated with 5, 4, 2, and 2% increases in asthma emergency visits, respectively. CO was the only pollutant with a negative association with asthma emergency visits, occurring in the month of April.

CONCLUSIONS

Pollutants NO₂, PM_2.5 CO, and O₃ were associated with increased emergency asthma visits in some, but not all months of the year. Air pollution's impact on asthma emergencies may be masked by other, more influential seasonal triggers, such as infections or allergies.

The relationship between airborne fine particle matter and emergency ambulance dispatches in a southwestern city in Chengdu, China

High levels of fine particulate matter (PM_2.5) are known to cause adverse effects to human health. The goal of this study was to estimate the acute health effects of short-term exposure to ambient PM_2.5 by analyzing cause-specific emergency ambulance dispatches as the endpoint in Chengdu, a city in Sichuan Province in southwest China. The ambient PM_2.5 concentration of Chengdu reached 63 μg/m³ in 2015. Data related to the causes of specific emergency ambulance dispatches, air pollution, and meteorological conditions were collected from 2013 to 2015 (1095 days). A generalized additive model (GAM) was constructed to control the confounding conditions and to estimate the effects of PM_2.5 on human health conditions. Emergency ambulance dispatches for all causes with (RR for lag0 = 1.0010, 95%CI: 1.0002, 1.0019) or without injuries (RR for lag0 = 1.0012, 95%CI: 1.0002, 1.0022), respiratory diseases (RR for lag0 = 1.0051, 95%CI: 1.0012, 1.0089), and cardiovascular diseases (RR for lag0 = 1.0041, 95%CI: 1.0009, 1.0074) were associated with ambient PM_2.5 concentrations in Chengdu. In addition, the effects of PM_2.5 were not confounded by ozone.

Association of ambient Particulate matter 2.5 with intensive care unit admission due to pneumonia: a distributed lag non-linear model

Air pollution in China has become a major environmental problem. There is a lack of evidence on the impact of haze (especially PM2.5) on intensive care unit admission due to pneumonia (ICUp). We hypothesized that PM2.5 was independently associated with ICUp and there was a non-linear time lag effect. All ICU admissions occurred from January 1, 2014 to December 31, 2016 in Sir Run-Run Shaw hospital were included in the study. The primary reasons for admission were categorized into pneumonia and non-pneumonia. Distributed lag non-linear model (DLNM) was built to account for the effect of air quality parameters in both value and temporal lag dimensions. There was a total of 7487 ICU admissions during the study period, including 391 admissions due to pneumonia. The DLNM showed that the relative risk (RR) of ICUp increased with PM2.5 concentrations. At a PM2.5 concentration of 200 mcg/m3, the RR increased from 1.06 (95% CI: 0.57-1.95) at day 0 to 1.40 (95% CI: 1.05-1.86) at day 3, and returned normal at day 6 (RR: 1.13; 95% CI: 0.83-1.55). The study showed that PM2.5 was independently associated with the risk of ICUp, and the maximum effect occurred at 3 to 4 days after exposure.

The impact of airborne particulate matter on pediatric hospital admissions for pneumonia among children in Jinan, China: A case-crossover study

This study aims to examine the effect of short-term changes in the concentration of particulate matter of diameter ≤2.5 µm (PM_2.5) and ≤10 µm (PM₁₀) on pediatric hospital admissions for pneumonia in Jinan, China. It explores confoundings factors of weather, season, and chemical pollutants. Information on pediatric hospital admissions for pneumonia in 2014 was extracted from the database of Jinan Qilu Hospital. The relative risk of pediatric hospital admissions for pneumonia was assessed using a case-crossover approach, controlling weather variables, day of the week, and seasonality. The single-pollutant model demonstrated that increased risk of pediatric hospital admissions for pneumonia was significantly associated with elevated PM_2.5 concentrations the day before hospital admission and elevated PM₁₀ concentrations 2 days before hospital admission. An increment of 10 μg/m³ in PM_2.5 and PM₁₀ was correlated with a 6% (95% CI 1.02--1.10) and 4% (95% CI 1.00-1.08) rise in number of admissions for pneumonia, respectively. In two pollutant models, PM_2.5 and PM₁₀ remained significant after inclusion of sulfur dioxide or nitrogen dioxide but not carbon monoxide. This study demonstrated that short-term exposure to atmospheric particulate matter (PM_2.5/PM₁₀) may be an important determinant of pediatric hospital admissions for pneumonia in Jinan, China.

IMPLICATIONS

This study demonstrated that short-term exposure to atmospheric particulate matter (PM_2.5/PM₁₀) may be an important determinant of pediatric hospital admissions for pneumonia in Jinan, China, and suggested the relevance of pollutant exposure levels and their effects. As a specific group, children are sensitive to airborne particulate matter. This study estimated the short-term effects attribute to other air pollutants to provide references for relevant studies.

Socioeconomic and air pollution correlates of adult asthma, heart attack, and stroke risks in the United States, 2010-2013

Asthma in the United States has become an important public health issue, with many physicians, regulators, and scientists elsewhere expressing concern that criterion air pollutants have contributed to a rising tide of asthma cases and symptoms. This paper studies recent associations (from 2008 to 2012) between self-reported asthma experiences and potential predictors, including age, sex, income, education, smoking, and county-level average annual ambient concentrations of ozone (O3) and fine particulate matter (PM2.5) levels recorded by the U.S. Environmental Protection Agency, for adults 50 years old or older for whom survey data are available from the Centers for Disease Control and Prevention (CDC) Behavioral Risk Factor Surveillance System (BRFSS). We also examine associations between these variables and self-reported heart attack and stroke experience; all three health outcomes are positively associated with each other. Young divorced women with low incomes are at greatest risk of asthma, especially if they are ever-smokers. Income is an important confounder of other relations. For example, in logistic regression modeling, PM2.5 is positively associated (p<0.06) with both stroke risk and heart attack risk when these are regressed only against PM2.5, sex, age, and ever-smoking status, but not when they are regressed against these variables and income. In this data set, PM2.5 is significantly negatively associated with asthma risk in regression models, with a 10μg/m³ decrease in PM2.5 corresponding to about a 6% increase in the probability of asthma, possibly because of confounding by smoking, which is negatively associated with PM2.5 and positively associated with asthma risk. A variety of non-parametric methods are used to quantify these associations and to explore potential causal interpretations.

Short-term Effect of Fine Particulate Matter on Children's Hospital Admissions and Emergency Department Visits for Asthma: A Systematic Review and Meta-analysis

OBJECTIVES

No children-specified review and meta-analysis paper about the short-term effect of fine particulate matter (PM2.5) on hospital admissions and emergency department visits for asthma has been published. We calculated more precise pooled effect estimates on this topic and evaluated the variation in effect size according to the differences in study characteristics not considered in previous studies.

METHODS

Two authors each independently searched PubMed and EMBASE for relevant studies in March, 2016. We conducted random effect meta-analyses and mixed-effect meta-regression analyses using retrieved summary effect estimates and 95% confidence intervals (CIs) and some characteristics of selected studies. The Egger's test and funnel plot were used to check publication bias. All analyses were done using R version 3.1.3.

RESULTS

We ultimately retrieved 26 time-series and case-crossover design studies about the short-term effect of PM2.5 on children's hospital admissions and emergency department visits for asthma. In the primary meta-analysis, children's hospital admissions and emergency department visits for asthma were positively associated with a short-term 10 μg/m3 increase in PM2.5 (relative risk, 1.048; 95% CI, 1.028 to 1.067; I2=95.7%). We also found different effect coefficients by region; the value in Asia was estimated to be lower than in North America or Europe.

CONCLUSIONS

We strengthened the evidence on the short-term effect of PM2.5 on children's hospital admissions and emergency department visits for asthma. Further studies from other regions outside North America and Europe regions are needed for more generalizable evidence.

Urbanization Level and Vulnerability to Heat-Related Mortality in Jiangsu Province, China

BACKGROUND

Although adverse effects of high temperature on mortality have been studied extensively in urban areas, little is known of the heat-mortality associations outside of cities.

OBJECTIVE

We investigated whether heat-mortality associations differed between urban and nonurban areas and how urbanicity affected the vulnerability to heat-related mortality.

METHODS

We first analyzed heat-related mortality risk in each of 102 counties in Jiangsu Province, China, during 2009-2013 using a distributed-lag nonlinear model. The county-specific estimates were then pooled for more urban (percentage of urban population ≥ 57.11%) and less urban (percentage of urban population < 57.11%) counties using a Bayesian hierarchical model. To explain the spatial variation in associations by county, county-level characteristics affecting heat vulnerability were also examined.

RESULTS

We found that the overall mortality risk comparing the 99th vs. 75th percentiles of temperature was 1.43 [95% posterior intervals (PI): 1.36, 1.50] in less urban counties and 1.26 (95% PI: 1.23, 1.30) in more urban counties. The heat effects on cardiorespiratory mortality followed a similar pattern. Higher education level and prevalence of air conditioning were significantly associated with counties having lower risks, whereas percentage of elderly people was significantly associated with increased risks.

CONCLUSION

Our findings reveal that nonurban areas have significant heat-related mortality risks in Jiangsu, China. These results suggest the need for enhanced adaptation planning in Chinese nonurban areas under a changing climate. Citation: Chen K, Zhou L, Chen X, Ma Z, Liu Y, Huang L, Bi J, Kinney PL. 2016. Urbanization level and vulnerability to heat-related mortality in Jiangsu Province, China. Environ Health Perspect 124:1863-1869; http://dx.doi.org/10.1289/EHP204.