Air pollution and exacerbation of asthma in African-American children in Los Angeles

Seasonal extreme temperatures and short-term fine particulate matter increases pediatric respiratory healthcare encounters in a sparsely populated region of the intermountain western United States

BACKGROUND

Western Montana, USA, experiences complex air pollution patterns with predominant exposure sources from summer wildfire smoke and winter wood smoke. In addition, climate change related temperatures events are becoming more extreme and expected to contribute to increases in hospital admissions for a range of health outcomes. Evaluating while accounting for these exposures (air pollution and temperature) that often occur simultaneously and may act synergistically on health is becoming more important.

METHODS

We explored short-term exposure to air pollution on children's respiratory health outcomes and how extreme temperature or seasonal period modify the risk of air pollution-associated healthcare events. The main outcome measure included individual-based address located respiratory-related healthcare visits for three categories: asthma, lower respiratory tract infections (LRTI), and upper respiratory tract infections (URTI) across western Montana for ages 0-17 from 2017-2020. We used a time-stratified, case-crossover analysis with distributed lag models to identify sensitive exposure windows of fine particulate matter (PM2.5) lagged from 0 (same-day) to 14 prior-days modified by temperature or season.

RESULTS

For asthma, increases of 1 µg/m3 in PM2.5 exposure 7-13 days prior a healthcare visit date was associated with increased odds that were magnified during median to colder temperatures and winter periods. For LRTIs, 1 µg/m3 increases during 12 days of cumulative PM2.5 with peak exposure periods between 6-12 days before healthcare visit date was associated with elevated LRTI events, also heightened in median to colder temperatures but no seasonal effect was observed. For URTIs, 1 unit increases during 13 days of cumulative PM2.5 with peak exposure periods between 4-10 days prior event date was associated with greater risk for URTIs visits that were intensified during median to hotter temperatures and spring to summer periods.

CONCLUSIONS

Delayed, short-term exposure increases of PM2.5 were associated with elevated odds of all three pediatric respiratory healthcare visit categories in a sparsely population area of the inter-Rocky Mountains, USA. PM2.5 in colder temperatures tended to increase instances of asthma and LRTIs, while PM2.5 during hotter periods increased URTIs.

Bioaerosol size as a potential determinant of airborneE. coliviability under ultraviolet germicidal irradiation and ozone disinfection

Ultraviolet germicidal irradiation (UVGI) and ozone disinfection are crucial methods for mitigating the airborne transmission of pathogenic microorganisms in high-risk settings, particularly with the emergence of respiratory viral pathogens such as SARS-CoV-2 and avian influenza viruses. This study quantitatively investigates the influence of UVGI and ozone on the viability ofE. coliin bioaerosols, with a particular focus on howE. coliviability depends on the size of the bioaerosols, a critical factor that determines deposition patterns within the human respiratory system and the evolution of bioaerosols in indoor environments. This study used a controlled small-scale laboratory chamber whereE. colisuspensions were aerosolized and subjected to varying levels of UVGI and ozone levels throughout the exposure time (2-6 s). The normalized viability ofE. coliwas found to be significantly reduced by UVGI (60-240μW s cm-2) as the exposure time increased from 2 to 6 s, and the most substantial reduction ofE. colinormalized viability was observed when UVGI and ozone (65-131 ppb) were used in combination. We also found that UVGI reduced the normalized viability ofE. coliin bioaerosols more significantly with smaller sizes (0.25-0.5μm) than with larger sizes (0.5-2.5μm). However, when combining UVGI and ozone, the normalized viability was higher for smaller particle sizes than for the larger ones. The findings provide insights into the development of effective UVGI disinfection engineering methods to control the spread of pathogenic microorganisms in high-risk environments. By understanding the influence of the viability of microorganisms in various bioaerosol sizes, we can optimize UVGI and ozone techniques to reduce the potential risk of airborne transmission of pathogens.

Prediction of the number of asthma patients using environmental factors based on deep learning algorithms

BACKGROUND

Air pollution, weather, pollen, and influenza are typical aggravating factors for asthma. Previous studies have identified risk factors using regression-based and ensemble models. However, studies that consider complex relationships and interactions among these factors have yet to be conducted. Although deep learning algorithms can address this problem, further research on modeling and interpreting the results is warranted.

METHODS

In this study, from 2015 to 2019, information about air pollutants, weather conditions, pollen, and influenza were utilized to predict the number of emergency room patients and outpatients with asthma using recurrent neural network, long short-term memory (LSTM), and gated recurrent unit models. The relative importance of the environmental factors in asthma exacerbation was quantified through a feature importance analysis.

RESULTS

We found that LSTM was the best algorithm for modeling patients with asthma. Our results demonstrated that influenza, temperature, PM10, NO2, CO, and pollen had a significant impact on asthma exacerbation. In addition, the week of the year and the number of holidays per week were an important factor to model the seasonality of the number of asthma patients and the effect of holiday clinic closures, respectively.

CONCLUSION

LSTM is an excellent algorithm for modeling complex epidemiological relationships, encompassing nonlinearity, lagged responses, and interactions. Our study findings can guide policymakers in their efforts to understand the environmental factors of asthma exacerbation.

Seasonal extreme temperatures and short-term fine particulate matter increases child respiratory hospitalizations in a sparsely populated region of the intermountain western United States

Background

Western Montana, USA, experiences complex air pollution patterns with predominant exposure sources from summer wildfire smoke and winter wood smoke. In addition, climate change related temperatures events are becoming more extreme and expected to contribute to increases in hospital admissions for a range of health outcomes. Few studies have evaluated these exposures (air pollution and temperature) that often occur simultaneously and may act synergistically on health.

Methods

We explored short-term exposure to air pollution on childhood respiratory health outcomes and how extreme temperature or seasonal period modify the risk of air pollution-associated hospitalizations. The main outcome measure included all respiratory-related hospital admissions for three categories: asthma, lower respiratory tract infections (LRTI), and upper respiratory tract infections (URTI) across western Montana for all individuals aged 0-17 from 2017-2020. We used a time-stratified, case-crossover analysis and distributed lag models to identify sensitive exposure windows of fine particulate matter (PM2.5) lagged from 0 (same-day) to 15 prior-days modified by temperature or season.

Results

Short-term exposure increases of 1 μg/m3 in PM2.5 were associated with elevated odds of all three respiratory hospital admission categories. PM2.5 was associated with the largest increased odds of hospitalizations for asthma at lag 7-13 days [1.87(1.17-2.97)], for LRTI at lag 6-12 days [2.18(1.20-3.97)], and for URTI at a cumulative lag of 13 days [1.29(1.07-1.57)]. The impact of PM2.5 varied by temperature and season for each respiratory outcome scenario. For asthma, PM2.5 was associated most strongly during colder temperatures [3.11(1.40-6.89)] and the winter season [3.26(1.07-9.95)]. Also in colder temperatures, PM2.5 was associated with increased odds of LRTI hospitalization [2.61(1.15-5.94)], but no seasonal effect was observed. Finally, 13 days of cumulative PM2.5 prior to admissions date was associated with the greatest increased odds of URTI hospitalization during summer days [3.35(1.85-6.04)] and hotter temperatures [1.71(1.31-2.22)].

Conclusions

Children's respiratory-related hospital admissions were associated with short-term exposure to PM2.5. PM2.5 associations with asthma and LRTI hospitalizations were strongest during cold periods, whereas associations with URTI were largest during hot periods.

Classification

environmental public health, fine particulate matter air pollution, respiratory infections.

Climate Change, Air Quality, and Pulmonary Health Disparities

Climate change will alter environmental risks that influence pulmonary health, including heat, air pollution, and pollen. These exposures disproportionately burden populations already at risk of ill health, including those at vulnerable life stages, with low socioeconomic status, and systematically targeted by oppressive policies. Climate change can exacerbate existing environmental injustices by affecting future exposure, as well as through differentials in the ability to adapt; this is compounded by disparities in rates of underlying disease and access to health care. Climate change is therefore a dire threat not only to individual and population health but also to health equity.

Observational evidence for detrimental impact of inhaled ozone on human respiratory system

The detrimental influence of inhaled ozone on human respiratory system is ambiguous due to the complexity of dose response relationship between ozone and human respiratory system. This study collects inhaled ozone concentration and respiratory disease data from Shenzhen City to reveal the impact of ozone on respiratory diseases using the Generalized Additive Models (GAM) and Convergent Cross Mapping (CCM) method at the 95% confidence level. The result of GAM exhibits a partially significant lag effect on acute respiratory diseases in cumulative mode. Since the traditional correlation analysis is incapable of capturing causality, the CCM method is applied to examine whether the inhaled ozone affects human respiratory system. The results demonstrate that the inhaled ozone has a significant causative impact on hospitalization rates of both upper and lower respiratory diseases. Furthermore, the harmful causative effects of ozone to the human health are varied with gender and age. Females are more susceptible to inhaled ozone than males, probably because of the estrogen levels and the differential regulation of lung immune response. Adults are more sensitive to ozone exposure than children, potentially due to the fact that children need longer time to react to ozone stress than adults, and the elderly are more tolerant than adults and children, which may be related to pulmonary hypofunction of the elderly while has little correlation with ozone exposure.

Environmental influences on childhood asthma: Climate change

Climate change is a key environmental factor for allergic respiratory diseases, especially in childhood. This review describes the influences of climate change on childhood asthma considering the factors acting directly, indirectly and with their amplifying interactions. Recent findings on the direct effects of temperature and weather changes, as well as the influences of climate change on air pollution, allergens, biocontaminants and their interplays, are discussed herein. The review also focusses on the impact of climate change on biodiversity loss and on migration status as a model to study environmental effects on childhood asthma onset and progression. Adaptation and mitigation strategies are urgently needed to prevent further respiratory diseases and human health damage in general, especially in younger and future generations.

Assessment of the health benefits to children of a transportation climate policy in New York City

BACKGROUND

Assessments of health and environmental effects of clean air and climate policies have revealed substantial health benefits due to reductions in air pollution, but have included few pediatric outcomes or assessed benefits at the neighborhood level.

OBJECTIVES

We estimated benefits across a suite of child health outcomes in 42 New York City (NYC) neighborhoods under the proposed regional Transportation and Climate Initiative. We also estimated their distribution across racial/ethnic and socioeconomic groups.

METHODS

We estimated changes in ambient fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) concentrations associated with on-road emissions under nine different predefined cap-and-invest scenarios. Health outcomes, including selected adverse birth, respiratory, and neurodevelopmental outcomes, were estimated using a program similar to the U.S. EPA BenMAP program. We stratified the associated monetized benefits across racial/ethnic and socioeconomic groups.

RESULTS

The benefits varied widely over the different cap-and-investment scenarios. For a 25% reduction in carbon emissions from 2022 to 2032 and a strategy prioritizing public transit investments, NYC would have an estimated 48 fewer medical visits for childhood asthma, 13,000 avoided asthma exacerbations not requiring medical visits, 640 fewer respiratory illnesses unrelated to asthma, and 9 avoided adverse birth outcomes (infant mortality, preterm birth, and term low birth weight) annually, starting in 2032. The total estimated annual avoided costs are $22 million. City-wide, Black and Hispanic children would experience 1.7 times the health benefits per capita than White and Non-Hispanic White children, respectively. Under the same scenario, neighborhoods experiencing the highest poverty rates in NYC would experience about 2.5 times the health benefits per capita than the lowest poverty neighborhoods.

CONCLUSION

A cap-and-invest strategy to reduce carbon emissions from the transportation sector could provide substantial health and monetized benefits to children in NYC through reductions in criteria pollutant concentrations, with greater benefits among Black and Hispanic children.

Reductions in NO2 and emergency room visits associated with California's goods movement policies: A quasi-experimental study

INTRODUCTION

This study examines whether the "Emission Reduction Plan for Ports and Goods Movement" in California reduced air pollution exposures and emergency room visits among California Medicaid enrollees with asthma and/or chronic obstructive pulmonary disease.

METHOD

We created a retrospective cohort of 5608 Medicaid enrollees from ten counties in California with data from 2004 to 2010. We grouped the patients into two groups: those living within 500 m of goods movement corridors (ports and truck-permitted freeways), and control areas (away from the busy truck or car permitted highways). We created annual air pollution surfaces for nitrogen dioxide and assigned them to enrollees' home addresses. We used a quasi-experimental design with a difference-in-differences method to examine changes before and after the policy for cohort beneficiaries in the two groups.

RESULTS

The reductions in nitrogen dioxide exposures and emergency room visits were greater for enrollees in goods movement corridors than those in control areas in post-policy years. We found that the goods movement actions were associated with 14.8% (95% CI, -24.0% to -4.4%; P = 0.006) and 11.8% (95% CI, -21.2% to -1.2%; P = 0.030) greater reduction in emergency room visits for the beneficiaries with asthma and chronic obstructive pulmonary disease, respectively, in the third year after California's emission reduction plan.

CONCLUSION

These findings indicate remarkable health benefits via reduced emergency room visits from the significantly improved air quality due to public policy interventions for disadvantaged and susceptible populations.

Ragweed pollen concentration predicts seasonal rhino-conjunctivitis and asthma severity in patients allergic to ragweed

In this work, we investigate the correlation between ragweed pollen concentration and conjunctival, nasal, and asthma symptom severity in patients allergic to ragweed pollen using ambient pollen exposure in the Milan area during the 2014 ragweed season We calculate the pollen/symptom thresholds and we assess the effectiveness of ragweed allergen immunotherapy (AIT). A total of 66 participants allergic to ragweed (Amb a 1) were enrolled in the study and divided into two groups: AIT treated (24) and no AIT treated (42). Pollen counts and daily symptom/medication patient diaries were kept. Autoregressive distributed lag models were used to develop predictive models of daily symptoms and evaluate the short-term effects of temporal variations in pollen concentration on the onset of symptoms. We found significant correlations between ragweed pollen load and the intensity of symptoms for all three symptom categories, both in no AIT treated (τ = 0.341, 0.352, and 0.721; and ρ = 0.48, 0.432, and 0.881; p-value < 0.001) and in AIT treated patients (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\tau$$\end{document}τ= 0.46, 0.610, and 0.66; and ρ = 0.692, 0.805, and 0.824; p-value < 0.001). In both groups, we observed a positive correlation between the number of symptoms reported and drug use. Mean symptom levels were significantly higher in no AIT treated than in AIT treated patients (p-value < 0.001) for all symptom categories. Pollen concentration thresholds for the four symptom severity levels (low, medium–low, medium–high and high) were calculated. Ragweed pollen concentration is predictive of symptom severity in patients with a ragweed (Amb a 1) allergy. Patients treated with AIT had significantly reduced mean symptom levels compared to those without AIT.

Spatial Estimation of PM2.5 Exposure and its Association with Asthma Exacerbation: A Prospective Study in Thai Children

Background:

The acceptable fine particulate matter (PM_2.5) level in Thailand is double the recommendation of the World Health Organization. It is necessary to have an accurate measure of PM_2.5 exposure and its association with health problems in vulnerable groups such as asthma exacerbation in Thai children to urge the Clean Air Act in Thailand, which is currently in the process of revision.

Objective:

To study the association between PM_2.5 exposure and asthma exacerbation in children living in Bangkok Metropolitan Region and Chiang Mai Province.

Methods:

A pilot prospective observational study was conducted at the Chest and Allergy clinic at Ramathibodi Hospital, Mahidol University, Bangkok and at the Chest Clinic at Nakornping Hospital, Chiang Mai, Thailand, from June 2020 to February 2021. Children with asthma, aged 5–18 years old, were recruited. Respiratory symptoms, including cough, chest tightness, dyspnea or wheezing, peak expiratory flow rate, and asthma exacerbation, were recorded twice daily by caregivers. Estimated average daily PM_2.5 exposure levels were calculated using ArcGIS® at exacerbation day, three days before exacerbation (lag day 3), and 7 days before exacerbation (lag day 7). Regression analysis was applied to examine the association between PM_2.5 exposure and asthma exacerbation.

Findings:

Seventy asthmatic patients were enrolled. The median age was 9.7 (IQR 5–18) years old. There were 53 respiratory symptoms, 5 admissions, and 1 intensive care unit admission. Daily PM_2.5 levels above 12 mcg/m³ (the US cut-off level for the sensitive group) has higher sensitivity to detect asthma exacerbation compared to Thai cut-off level for the sensitive group (37 mcg/m³) (sensitivity 98.2% vs 32.1%). The average daily PM_2.5 level exposure at lag day 3 in the exacerbation vs the non-exacerbation group was 27.5 and 13.6 mcg/m³ (p < 0.01), respectively. The daily PM_2.5 level at lag day 3 was also correlated with an acute asthmatic attack (r = 0.62, p < 0.01) with the 0.2 events increasing of asthmatic exacerbation every 10 mcg/m³ of increment of daily PM_2.5 level.

Conclusions:

Our findings suggest that asthmatic children are sensitive to daily PM_2.5 levels above 12 mcg/m³. Exposure to high daily PM_2.5 levels can lead to asthma exacerbation within three days. Further participant recruitment is needed to emphasize this association and establish the national data.

Reductions in particulate matter concentrations resulting from air filtration: A randomized sham-controlled crossover study

One-hundred seventy-two households were recruited from regions with high outdoor air pollution (Fresno and Riverside, CA) to participate in a randomized, sham-controlled, cross-over study to determine the effectiveness of high-efficiency air filtration to reduce indoor particle exposures. In 129 households, stand-alone HEPA air cleaners were placed in a bedroom and in the main living area. In 43 households, high-efficiency MERV 16 filters were installed in central forced-air heating and cooling systems and the participating households were asked to run the system on a clean-air cycle for 15 min per hour. Participating households that completed the study received true air filtration for a year and sham air filtration for a year. Air pollution samples were collected at approximately 6-month intervals, with two measurements in each of the sham and true filtration periods. One week indoor and outdoor time-integrated samples were collected for measurement of PM2.5 , PM10 , and ultrafine particulate matter (UFP) measured as PM0.2 . Reflectance measurements were also made on the PM2.5 filters to estimate black carbon. True filtration significantly improved indoor air quality, with a 48% reduction in the geometric mean indoor PM0.2 and PM2.5 concentrations, and a 31% reduction in PM10 . Geometric mean concentrations of indoor/outdoor reflectance values, indicating fraction of particles of outdoor origin remaining indoors, decreased by 77%. Improvements in particle concentrations were greater with continuously operating stand-alone air cleaners than with intermittent central system filtration. Keeping windows closed and increased utilization of the filtration systems further improved indoor air quality.

Outdoor air pollution and the risk of asthma exacerbations in single lag0 and lag1 exposure patterns: a systematic review and meta-analysis

Objective: To synthesize evidence regarding the relationship between outdoor air pollution and risk of asthma exacerbations in single lag0 and lag1 exposure patterns.Methods: We performed a systematic literature search using PubMed, Embase, Cochrane Library, Web of Science, ClinicalTrials, China National Knowledge Internet, Chinese BioMedical, and Wanfang databases. Articles published until August 1, 2020 and the reference lists of the relevant articles were reviewed. Two authors independently evaluated the eligible articles and performed structured extraction of the relevant information. Pooled relative risks (RRs) and 95% confidence intervals (CIs) of lag0 and lag1 exposure patterns were estimated using random-effect models.Results: Eighty-four studies met the eligibility criteria and provided sufficient information for meta-analysis. Outdoor air pollutants were associated with increased risk of asthma exacerbations in both single lag0 and lag1 exposure patterns [lag0: RR (95% CI) (pollutants), 1.057(1.011, 1.103) (air quality index, AQI), 1.007 (1.005, 1.010) (particulate matter of diameter ≤ 2.5 μm, PM_2.5), 1.009 (1.005, 1.012) (particulate matter of diameter, PM₁₀), 1.010 (1.006, 1.014) (NO₂), 1.030 (1.011, 1.048) (CO), 1.005 (1.002, 1.009) (O₃); lag1:1.064(1.022, 1.106) (AQI), 1.005 (1.002, 1.008) (PM_2.5), 1.007 (1.004, 1.011) (PM₁₀), 1.008 (1.004, 1.012) (NO₂), 1.025 (1.007, 1.042) (CO), 1.010 (1.006, 1.013) (O₃)], except SO₂ [lag0: RR (95% CI), 1.004 (1.000, 1.007); lag1: RR (95% CI), 1.003 (0.999, 1.006)]. Subgroup analyses revealed stronger effects in children and asthma exacerbations associated with other events (including symptoms, lung function changes, and medication use).Conclusion: Outdoor air pollution increases the asthma exacerbation risk in single lag0 and lag1 exposure patterns.Trial registration: PROSPERO, CRD42020204097. https://www.crd.york.ac.uk/.Supplemental data for this article is available online at https://doi.org/10.1080/02770903.2021.2008429 .

Health Benefits in California of Strengthening the Fine Particulate Matter Standards

The Clean Air Act requires the United States Environmental Protection Agency to review routinely the National Ambient Air Quality Standards, including fine particulate matter (PM_2.5). A non-governmental Independent Particulate Matter Review Panel recently concluded that the current PM_2.5 standards do not protect public health adequately and recommended revising the daily standard from 35 to 25-30 μg/m³ and the annual standard from 12 to 8-10 μg/m³. To assess the public health implications of adopting the PM_2.5 standards proposed by the panel, the health benefits are quantified from their implementation based on both current (observed) and future (simulated) air quality data for California. The findings indicate that strengthening the standards would provide significant public health benefits valued at $42-$149 billion. Additionally, the stronger standards are shown to benefit environmental justice via health savings that are allocated more within environmentally and socioeconomically disadvantaged communities.

Evaluation of adverse effects of particulate matter on human life

Particulate matter (PM_2.5) has a severe impact on human health. The concentration of PM_2.5, related to air-quality changes, may be associated with perceptible effects on people's health. In this study, computer intelligence was used to assess the negative effects of PM_2.5. The input data, used for the evaluation, were grid definitions (shape-file), PM_2.5, air-quality data, incidence/prevalence rates, a population dataset, and the (Krewski) health-impact function. This paper presents a local (Pakistan) health-impact assessment of PM_2.5 in order to estimate the long-term effects on mortality. A rollback-to-a-standard scenario was based on the PM_2.5 concentration of 15 μg m^-3. Health benefits for a population of about 73 million people were calculated. The results showed that the estimated avoidable mortality, linked to ischemic heart disease and lung cancer, was 2,773 for every 100,000 people, which accounts for 2,024,290 preventable deaths of the total population. The total cost, related to the above mortality, was estimated to be US $ 1,000 million. Therefore, a policy for a PM_2.5-standard up to 15 μg m^-3 is suggested.

The Role of Genetic Ancestry as a Risk Factor for Primary Open-angle Glaucoma in African Americans

Purpose

POAG is the leading cause of irreversible blindness in African Americans. In this study, we quantitatively assess the association of autosomal ancestry with POAG risk in a large cohort of self-identified African Americans.

Methods

Subjects recruited to the Primary Open-Angle African American Glaucoma Genetics (POAAGG) study were classified as glaucoma cases or controls by fellowship-trained glaucoma specialists. POAAGG subjects were genotyped using the MEGA Ex array (discovery cohort, n = 3830; replication cohort, n = 2135). Population structure was interrogated using principal component analysis in the context of the 1000 Genomes Project superpopulations.

Results

The majority of POAAGG samples lie on an axis between African and European superpopulations, with great variation in admixture. Cases had a significantly lower mean value of the ancestral component q0 than controls for both cohorts (P = 6.14-4; P = 3-6), consistent with higher degree of African ancestry. Among POAG cases, higher African ancestry was also associated with thinner central corneal thickness (P = 2-4). Admixture mapping showed that local genetic ancestry was not a significant risk factor for POAG. A polygenic risk score, comprised of 23 glaucoma-associated single nucleotide polymorphisms from the NHGRI-EBI genome-wide association study catalog, was significant in both cohorts (P < 0.001), suggesting that both known POAG single nucleotide polymorphisms and an omnigenic ancestry effect influence POAG risk.

Conclusions

In sum, the POAAGG study population is very admixed, with a higher degree of African ancestry associated with an increased POAG risk. Further analyses should consider social and environmental factors as possible confounding factors for disease predisposition.

A Multifactorial Evaluation of the Effects of Air Pollution and Meteorological Factors on Asthma Exacerbation

In the real world, dynamic changes in air pollutants and meteorological factors coexist simultaneously. Studies identifying the effects of individual pollutants on acute exacerbation (AE) of asthma may overlook the health effects of the overall combination. A comprehensive study examining the influence of air pollution and meteorological factors is required. Asthma AE data from emergency room visits were collected from the Taiwan National Health Insurance Research Database. Complete monitoring data for air pollutants (SO₂; NO₂; O₃; CO; PM_2.5; PM₁₀) and meteorological factors were collected from the Environmental Protection Agency monitoring stations. A bi-directional case-crossover analysis was used to investigate the effects of air pollution and meteorological factors on asthma AE. Among age group divisions, a 1 °C temperature increase was a protective factor for asthma ER visits with OR = 0.981 (95% CI, 0.971–0.991) and 0.985 (95% CI, 0.975–0.994) for pediatric and adult patients, respectively. Children, especially younger females, are more susceptible to asthma AE due to the effects of outdoor air pollution than adults. Meteorological factors are important modulators for asthma AE in both asthmatic children and adults. When studying the effects of air pollution on asthma AE, meteorological factors should be considered.

Exposure Measurement Error in Air Pollution Studies: The Impact of Shared, Multiplicative Measurement Error on Epidemiological Health Risk Estimates

Spatiotemporal air pollution models are increasingly being used to estimate health effects in epidemiological studies. Although such exposure prediction models typically result in improved spatial and temporal resolution of air pollution predictions, they remain subject to shared measurement error, a type of measurement error common in spatiotemporal exposure models which occurs when measurement error is not independent of exposures. A fundamental challenge of exposure measurement error in air pollution assessment is the strong correlation and sometimes identical (shared) error of exposure estimates across geographic space and time. When exposure estimates with shared measurement error are used to estimate health risk in epidemiological analyses, complex errors are potentially introduced, resulting in biased epidemiological conclusions. We demonstrate the influence of using a three-stage spatiotemporal exposure prediction model and introduce formal methods of shared, multiplicative measurement error (SMME) correction of epidemiological health risk estimates. Using our three-stage, ensemble learning based nitrogen oxides (NOx) exposure prediction model, we quantified SMME. We conducted an epidemiological analysis of wheeze risk in relation to NOx exposure among school-aged children. To demonstrate the incremental influence of exposure modeling stage, we iteratively estimated the health risk using assigned exposure predictions from each stage of the NOx model. We then determined the impact of SMME on the variance of the health risk estimates under various scenarios. Depending on the stage of the spatiotemporal exposure model used, we found that wheeze odds ratio ranged from 1.16 to 1.28 for an interquartile range increase in NOx. With each additional stage of exposure modeling, the health effect estimate moved further away from the null (OR=1). When corrected for observed SMME, the health effects confidence intervals slightly lengthened, but our epidemiological conclusions were not altered. When the variance estimate was corrected for the potential "worst case scenario" of SMME, the standard error further increased, having a meaningful influence on epidemiological conclusions. Our framework can be expanded and used to understand the implications of using exposure predictions subject to shared measurement error in future health investigations.

Assessment of Risk Hospitalization due to Acute Respiratory Incidents Related to Ozone Exposure in Silesian Voivodeship (Poland)

The main aim of this work is the estimation of health risks arising from exposure to ozone or other air pollutants by different statistical models taking into account delayed health effects. This paper presents the risk of hospitalization due to bronchitis and asthma exacerbation in adult inhabitants of Silesian Voivodeship from 1 January 2016 to 31 August 2017. Data were obtained from the daily register of hospitalizations for acute bronchitis (code J20-J21, International Classification of Diseases, Tenth Revision - ICD-10) and asthma (J45-J46) which is governed by the National Health Fund. Meteorological data and data on tropospheric ozone concentrations were obtained from the regional environmental monitoring database of the Provincial Inspector of Environmental Protection in Katowice. The paper includes descriptive and analytical statistical methods used in the estimation of health risk with a delayed effect: Almon Distributed Lag Model, the Poisson Distributed Lag Model, and Distributed Lag Non-Linear Model (DLNM). A significant relationship has only been confirmed by DLNM for bronchitis and a relatively short period (1-3 days) from exposure above the limit value (120 µg/m³). The relative risk value was RR = 1.15 (95% CI 1.03-1.28) for a 2-day lag. However, conclusive findings require the continuation of the study over longer observation periods.

Outdoor Air Pollution and New-Onset Airway Disease. An Official American Thoracic Society Workshop Report

Although it is well accepted that air pollution exposure exacerbates preexisting airway disease, it has not been firmly established that long-term pollution exposure increases the risk of new-onset asthma or chronic obstruction pulmonary disease (COPD). This Workshop brought together experts on mechanistic, epidemiological, and clinical aspects of airway disease to review current knowledge regarding whether air pollution is a causal factor in the development of asthma and/or COPD. Speakers presented recent evidence in their respective areas of expertise related to air pollution and new airway disease incidence, followed by interactive discussions. A writing committee summarized their collective findings. The Epidemiology Group found that long-term exposure to air pollution, especially metrics of traffic-related air pollution such as nitrogen dioxide and black carbon, is associated with onset of childhood asthma. However, the evidence for a causal role in adult-onset asthma or COPD remains insufficient. The Mechanistic Group concluded that air pollution exposure can cause airway remodeling, which can lead to asthma or COPD, as well as asthma-like phenotypes that worsen with long-term exposure to air pollution, especially fine particulate matter and ozone. The Clinical Group concluded that air pollution is a plausible contributor to the onset of both asthma and COPD. Available evidence indicates that long-term exposure to air pollution is a cause of childhood asthma, but the evidence for a similar determination for adult asthma or COPD remains insufficient. Further research is needed to elucidate the exact biological mechanism underlying incident childhood asthma, and the specific air pollutant that causes it.

The Role and Potential Pathogenic Mechanism of Particulate Matter in Childhood Asthma: A Review and Perspective

Asthma, the most common chronic respiratory disease in children, affects numerous people worldwide. Accumulating evidence suggests that exposure to high levels of particulate matter (PM), either acutely or chronically, is associated with the exacerbation and incidence of pediatric asthma. However, the detailed pathogenic mechanisms by which PM contributes to the incidence of asthma remain largely unknown. In this short review, we summarize studies of relationships between PM and pediatric asthma and recent advances on the fundamental mechanisms of PM-related asthma, with emphases on cell death regulation and immune system responses. We further discuss the inadequacy of current studies and give a perspective on the prevention strategies for pediatric asthma.

Short-term exposure to pollen and the risk of allergic and asthmatic manifestations: a systematic review and meta-analysis

BACKGROUND

Several studies have assessed effects of short-term exposure to pollen on allergic and asthmatic manifestations. The evidence is inconclusive, and no meta-analysis has been published.

OBJECTIVE

To synthesise the evidence on the relations between short-term pollen exposure and the risk of allergic and asthmatic manifestations.

METHODS

We performed a systematic literature search of PubMed and Scopus databases up to the end of August 2018. In addition, we reviewed the reference lists of relevant articles. Two authors independently evaluated the eligible articles and extracted relevant information in a structured form. We calculated summary effect estimates (EE) based on the study-specific ORs and regression coefficients (β) by applying both fixed-effects and random-effects models.

RESULTS

26 studies met the a priori eligibility criteria, and 12 of them provided sufficient information for the meta-analysis. The summary EE related to 10 grains per m³ increase in pollen exposure showed an 1% increase (EE 1.01, 95% CI 1.00 to 1.02) in the risk of lower respiratory symptoms and a 2% increase (EE 1.02, 95% CI 1.01 to 1.03) in the risk of any allergic or asthmatic symptom. Correspondingly, the risk of upper respiratory symptoms and ocular symptoms increased 7% (EE 1.07, 95% CI 1.04 to 1.09) and 11% (EE 1.11, 95% CI 1.05 to 1.17), respectively, in relation to such pollen exposure. Short-term exposure to pollen did not show any significant effect on daily lung function levels.

CONCLUSION

Our results provide new evidence that short-term pollen exposure significantly increases the risks of allergic and asthmatic symptoms.

Numerical modeling of particle deposition in the conducting airways of asthmatic children

Mounting evidence has linked long- and short-term exposure to particulate air pollution with the incidence and exacerbation of asthma in children, but the biological pathogenesis is unclear. We examined the deposition of particles in the airways of asthmatic children. A planar and symmetric model of airways for 4-year-old asthmatic children was considered. Airflow and particle deposition in the upper (G3-G6) and lower (G9-G12) conducting airways were numerically investigated using computation fluid dynamics (CFD) method. We considered the manifestation of moderate (30% reduction in airway diameter) and severe (60% reduction) asthma. Micron particles (1-10 µm) were considered. We found that particle deposition in the asthmatic children was significantly higher than that in healthy children. The deposition efficiency increased slowly with particle size for healthy children, but increased rapidly for asthmatic children, such that smaller particles could be deposited in the conducting airways of asthmatics. For healthy children, particles were deposited by inertial impaction and gravitational sedimentation respectively in the upper and lower airways, but deposited by inertial impaction in asthmatic children. The severity of the asthma increased the particle deposition in the airways. Our study indicated that asthmatic children were more susceptible to the effect of particulate air pollution. The constricted airways increased the particle deposition by inertial impaction, which may be the biological pathogenesis that causes the hospitalization of asthma in children. Avoiding exposure during air pollution events will be an effective measure to reduce the asthma attack.

Health and Environmental Justice Implications of Retiring Two Coal-Fired Power Plants in the Southern Front Range Region of Colorado

Despite improvements in air quality over the past 50 years, ambient air pollution remains an important public health issue in the United States. In particular, emissions from coal-fired power plants still have a substantial impact on both nearby and regional populations. Of particular concern is the potential for this impact to fall disproportionately on low-income communities and communities of color. We conducted a quantitative health impact assessment to estimate the health benefits of the proposed decommissioning of two coal-fired electricity generating stations in the Southern Front Range region of Colorado. We estimated changes in exposures to fine particulate matter and ozone using the Community Multiscale Air Quality model and predicted avoided health impacts and related economic values. We also quantitatively assessed the distribution of these benefits by population-level socioeconomic status. Across the study area, decommissioning the power plants would result in 2 (95% CI: 1-3) avoided premature deaths each year due to reduced PM2.5 exposures and greater reductions in hospitalizations and other morbidities. Health benefits resulting from the modeled shutdowns were greatest in areas with lower educational attainment and other economic indicators. Our results suggest that decommissioning these power plants and replacing them with zero-emissions sources could have broad public health benefits for residents of Colorado, with larger benefits for those that are socially disadvantaged. Our results also suggested that researchers and decision makers need to consider the unique demographics of their study areas to ensure that important opportunities to reduce health disparities associated with point-source pollution.

Air pollution, respiratory illness and behavioral adaptation: Evidence from South Korea

Air pollution is closely associated with the development of respiratory illness. Behavioral adaptations of people to air pollution may influence its impact, yet this has not been investigated in the literature. Our hypothesis is that people experience and learn the underlying air quality to decide their adaptation, and they have a stronger incentive to behaviorally adapt to the air quality as it deteriorates. We tested our hypothesis on a sample of approximately 25,700 individuals from South Korea from 2002 to 2013 that contained information on daily doctor's visits due to respiratory disease. We matched individuals to the mean of the past seven-day concentration of the particulate matter of size between 2.5 and 10 micrometers (PM10) in their county of residence. We examined whether people living in counties with greater air pollution suffer less from respiratory disease when the concentration increases. For the analysis, we separated counties into quintiles based on their mean seven-day PM10, and regressed the binary indicator of a daily doctor's visit with a resulting diagnosis of respiratory disease on the seven-day PM10 concentration of the county of residence interacted with the quintile dummies. The key findings are that a 1-standard-deviation increase in the seven-day PM10 concentration in the two lowest quintiles is associated with an increase of 0.054 percentage points in the likelihood of a doctor's visit with a resulting diagnosis of respiratory disease, which is about 40% larger than the effect in higher quintiles, and the size of 1-standard-deviation gradually increases from 0.037 percentage points in the third quintile to 0.040 percentage points in the fifth quintile. The smaller increase in the likelihood of respiratory disease in more polluted locations can be explained by the behavioral adaptation to the environment, but the effectiveness of the adaptation seems limited among the highly polluted locations.

A new approach for inferring traffic-related air pollution: Use of radar-calibrated crowd-sourced traffic data

BACKGROUND

Crowd-sourced traffic data potentially allow prediction of traffic-related air pollution at high temporal and spatial resolution.

OBJECTIVES

To examine associations (1) of radar-based traffic measurements with congestion colors displayed on crowd-sourced traffic data maps and (2) of black carbon (BC) levels with radar and crowd-sourced traffic data.

METHODS

At an off-ramp of an interstate and a small one-way street in a mixed-use area in New York City, we used radar devices to obtain vehicle speeds and flows (hourly counts) for cars and trucks. At these radar sites and at an additional non-radar equipped site at a 2-way street, we monitored BC levels using aethalometers in the summer and early fall of 2017. At all three sites, free-flow traffic conditions typically did not occur due to the nearby presence of traffic lights and forced turns. We also downloaded real-time traffic maps from a crowd-sourced traffic data provider and assigned an ordinal integer congestion color code CCC to the congestion colors, ranging from 1 (dark red) to 5 (gray).

RESULTS

CCC increased with vehicle speed. Traffic flow was highest for intermediate speeds and intermediate CCC. Regression analyses showed that BC levels increased with either segregated or total vehicle flows. At the off-ramp, time-dependent BC levels can be inferred from time-dependent CCC and radar-derived mean vehicle flow data. A unit decrease in CCC for a mean traffic flow of 100 vehicles/h was associated with a mean (95% CI) increase in BC levels of 0.023 (0.028, 0.018) μg/m³. At the small 1-way and the 2-way street, BC levels were also negatively associated with CCC, though at a >0.05 significance level.

CONCLUSIONS

Use of inexpensive crowd-sourced traffic data holds great promise in air pollution modeling and health studies. Time-dependent traffic-related primary air pollution levels may be inferred from radar-calibrated crowd-sourced traffic data, in our case radar-derived mean traffic flow and widely available CCC data. However, at some locations mean traffic flow data may already be available.

Air Quality-Related Health Benefits of Energy Efficiency in the United States

While it is known that energy efficiency (EE) lowers power sector demand and emissions, study of the air quality and public health impacts of EE has been limited. Here, we quantify the air quality and mortality impacts of a 12% summertime (June, July, and August) reduction in baseload electricity demand. We use the AVoided Emissions and geneRation Tool (AVERT) to simulate plant-level generation and emissions, the Community Multiscale Air Quality (CMAQ) model to simulate air quality, and the Environmental Benefits Mapping and Analysis Program (BenMAP) to quantify mortality impacts. We find EE reduces emissions of NO _x by 13.2%, SO₂ by 12.6%, and CO₂ by 11.6%. On a nationwide, summer average basis, ambient PM_2.5 is reduced 0.55% and O₃ is reduced 0.45%. Reduced exposure to PM_2.5 avoids 300 premature deaths annually (95% CI: 60 to 580) valued at $2.8 billion ($0.13 billion to $9.3 billion), and reduced exposure to O₃ averts 175 deaths (101 to 244) valued at $1.6 billion ($0.15 billion to $4.5 billion). This translates into a health savings rate of $0.049/kWh ($0.031/kWh for PM_2.5 and $0.018/kWh for O₃). These results illustrate the importance of capturing the health benefits of EE and its potential as a strategy to achieve air standards.

Comparing apples to oranges: Interpreting ozone concentrations from observational studies in the context of the United States ozone regulatory standard

In 2015, the United States Environmental Protection Agency (US EPA) set the ozone National Ambient Air Quality Standards (NAAQS) at 0.070 parts per million (ppm), for an annual 4th highest daily 8-hour (h) maximum average concentration, averaged over three years, with compliance based on the monitor with the highest concentrations. Numerous epidemiological studies have evaluated associations between ozone and health effects, but how the ozone concentrations derived from those studies can be compared to the ozone NAAQS is not clear, because of the complexity of the standard. The purpose of the present work was to determine how ozone summary metrics used in key epidemiology studies compare to the metrics that comprise the ozone regulatory value. Evaluation of epidemiology studies used for quantitative risk assessment in the 2015 ozone NAAQS review demonstrated that the most commonly used summary metrics that differed from the NAAQS were: 1-h maximum or 24-h average concentrations; multiple-day averages from 2 to 30 days; and averaging of ozone concentrations across all monitors in an area and over different months of the year. Using different ozone summary metrics to calculate the ozone regulatory value in twelve US cities for 2000-2002 or 2013-2015 generated alternative ozone regulatory values that were often substantively different and that may or may not vary commensurate with the regulatory standard. Comparison of epidemiology study metrics to other countries' ozone standards or guideline levels produces similar challenges as described here for the NAAQS. In conclusion, many of the ozone concentration metrics used in epidemiology studies cannot be directly compared to the ozone NAAQS, and using simple conversion ratios adds substantial uncertainty to concentration estimates. These summary metrics must be reconciled to the regulatory value before any judgements are made as to the protectiveness of current and alternative standards based on epidemiology study results.

Influence of Air Pollution on Hospital Admissions in Adult Asthma in Northeast China

Background:

Asthma is a common chronic respiratory disease and is related to air pollution exposure. However, only a few studies have concentrated on the association between air pollution and adult asthma. Moreover, the results of these studies are controversial. Therefore, the present study aimed to analyze the influence of various pollutants on hospitalization due to asthma in adults.

Methods:

A total of 1019 unrelated hospitalized adult asthma patients from Northeast China were recruited from 2014 to 2016. Daily average concentrations of air pollutants (particulate matter <2.5 μm [PM_2.5], particulate matter <10 μm [PM₁₀], sulfur dioxide [SO₂], nitrogen dioxide [NO₂], and carbon monoxide [CO]) were obtained from the China National Environmental Monitoring Centre website from 2014 to 2016. Cox logistic regression analysis was used to analyze the relationship between air pollutants and hospital admissions in adult asthma.

Results:

The maximum odds ratio (OR) value for most air pollutants occurred on lag day 1. Lag day 1 was chosen as the exposure period, and 8 days before onset was chosen as the control period. Three pollutants (PM_2.5, CO, and SO₂) were entered into the regression equation, and the corresponding OR (95% confidence interval) was 0.995 (0.991–0.999), 3.107 (1.607–6.010), and 0.979 (0.968–0.990), respectively.

Conclusions:

A positive association between hospital admissions and the daily average concentration of CO was observed. CO is likely to be a risk factor for hospital admissions in adults with asthma.

Detection and analysis of fine particulate matter and microbial aerosol in chicken houses in Shandong Province, China

Bacteria and fungi are primary constituents of airborne microbes in fine particulate matter and harmful to health. To evaluate the environmental quality of different poultry houses in Shandong Province, China, the airborne aerobic bacteria, airborne fungi, and airborne Escherichia coli were collected by the Andersen-6 air microorganism sampler. The fine particulate matter was collected by a ZR-3920 ambient air particulate matter sampler, and bacterial and fungal diversities and relative abundances analyzed using high-throughput sequencing. Results showed that the concentrations of airborne aerobic bacteria, airborne fungi, and airborne Escherichia coli in poultry houses were 0.167 to 4.484 × 104 CFU/m3, 0.236 to 4.735 × 103 CFU/m3, and 0 to 33.0 CFU/m3, respectively. 11.4 to 34.3% of aerobic bacteria and 16.8 to 37.5% of fungi were distributed at levels 5 and 6 (0.6 to 2.1 μm, the particle sizes similar to fine particulate matter) in the Andersen sampler. The concentration of fine particulate matter in the poultry houses was 114 to 230 μg/m3, which was higher than the safety value 10 specified by WHO. In fine particulate matter, the main bacteria at phylum level were Firmicutes, Bacteroidetes, and Proteobacteria, whereas the dominant phylum of fungus was Ascomycota and Basidiomycota. Importantly, the relative abundances of Escherichia and Corynebacterium in the broiler houses were greater than those in layer houses. However, the percentages of Aspergillus and Penicillium were 13.5 and 0.56%, with a relatively high level in the layer houses. Altogether, results revealed that the ambient air quality in the poultry houses sampled had a relatively high abundance of conditional pathogenic bacteria and concentration of fine particulate matter, which could threaten the health of animals and workers in those environments.

Lagged Influence of Fine Particulate Matter and Geographic Disparities on Clinic Visits for Children's Asthma in Taiwan

Recent studies have revealed the influence of fine particulate matter (PM_2.5) on increased medication use, hospital admission, and emergency room visits for asthma attack in children, but the lagged influence of PM_2.5 on children’s asthma and geographic disparities of children’s asthma have rarely been discussed simultaneously. This study investigated the documented diagnosis of children’s asthma in clinic visits for children aged less than 15 years old that were associated with PM_2.5 in two counties located in west-central Taiwan during 2005–2010. The result shows that PM_2.5 had a significant lagged effect on children’s asthma for up to 6 days. A significantly higher relative risk for children’s asthma was more likely to happen at 2-day lag compared to the present day when PM_2.5 increased from 36.17 μg/m³ to 81.26 μg/m³. Considering all lagged effects, the highest relative risk for children’s asthma was 1.08 (95% CI = 1.05, 1.11) as PM_2.5 increased as high as 64.66 μg/m³. In addition, geographic disparities of children’s asthma were significant, and 47.83% of areas were identified to have children vulnerable to asthma. To sum up, our findings can serve as a valuable reference for the implementation of an early warning to governmental agencies about a susceptible population of children.

Ozone exposure and pulmonary effects in panel and human clinical studies: Considerations for design and interpretation

A wealth of literature exists regarding the pulmonary effects of ozone, a photochemical pollutant produced by the reaction of nitrogen oxide and volatile organic precursors in the presence of sunlight. This paper focuses on epidemiological panel studies and human clinical studies of ozone exposure, and discusses issues specific to this pollutant that may influence study design and interpretation as well as other, broader considerations relevant to ozone-health research. The issues are discussed using examples drawn from the wider literature. The recent panel and clinical literature is also reviewed. Health outcomes considered include lung function, symptoms, and pulmonary inflammation. Issues discussed include adversity, reversibility, adaptation, variability in ozone exposure metric used and health outcomes evaluated, co-pollutants in panel studies, influence of temperature in panel studies, and multiple comparisons. Improvements in and standardization of panel study approaches are recommended to facilitate comparisons between studies as well as meta-analyses. Additional clinical studies at or near the current National Ambient Air Quality Standard (NAAQS) of 70 ppb are recommended, as are clinical studies in sensitive subpopulations such as asthmatics.

IMPLICATIONS

The pulmonary health impacts of ozone exposure have been well documented using both epidemiological and chamber study designs. However, there are a number of specific methodological and related issues that should be considered when interpreting the results of these studies and planning additional research, including the standardization of exposure and health metrics to facilitate comparisons among studies.

Estimated effects of air pollution and space-time-activity on cardiopulmonary outcomes in healthy adults: A repeated measures study

BACKGROUND

Exposure to air pollution is known to affect both short and long-term outcomes of the cardiopulmonary system; however, findings on short-term outcomes have been inconsistent and often from isolated and long-term rather than coexisting and short-term exposures, and among susceptible/unhealthy rather than healthy populations.

AIMS

We aimed to investigate separately the annual, daily and daily space-time-activity-weighted effect of ambient air pollution, as well as confounding or modification by other environmental (including noise) or space-time-activity (including total daily physical activity) exposures, on cardiopulmonary outcomes in healthy adults.

METHODS

Participants (N=57: 54% female) had indicators of cardiopulmonary outcomes [blood pressure (BP), pulse (HR) and heart rate variability (HRV {SDNN}), and lung function (spirometry {FEV₁, FVC, SUM})] measured on four different mornings (at least five days apart) in a clinical setting between 2011 and 2014. Spatiotemporal ESCAPE-LUR models were used to estimate daily and annual air pollution exposures (including PM₁₀, PM_Coarse, but not Ozone {derived from closest station}) at participant residential and occupational addresses. Participants' time-activity diaries indicated time spent at either address to allow daily space-time-activity-weighted estimates, and capture total daily physical activity (total-PA {as metabolic-equivalents-of-task, METs}), in the three days preceding health measurements. Multivariate-adjusted linear mixed-effects models (using either annual or daily estimates) were adjusted for possible environmental confounders or mediators including levels of ambient noise and greenness. Causal mediation analysis was also performed separately considering these factors as well as total-PA. All presented models are controlled by age, height, sex and season.

RESULTS

An increase in 5μg/m³ of daily space-time-activity-weighted PM_Coarse exposure was statistically significantly associated with a 4.1% reduction in total heart rate variability (SDNN; p=0.01), and remained robust after adjusting for suspected confounders [except for occupational-address noise (β=-2.7, p=0.20)]. An increase in 10ppb of annual mean Ozone concentration at the residential address was statistically significantly associated with an increase in diastolic BP of 6.4mmHg (p<0.01), which lost statistical significance when substituted with daily space-time-activity-weighted estimates. As for pulmonary function, an increase in 10μg/m³ of annual mean PM₁₀ concentration at the residential address was significantly associated with a 0.3% reduction in FVC (p<0.01) and a 0.5% reduction in SUM (p<0.04), for which again significance was lost when substituted for daily space-time-activity-weighted estimates These associations with pulmonary function remained robust after adjusting for suspected confounders, including annual Ozone, as well as total-PA and bioaerosol (pollen and fungal spore) levels (but not residential-neighborhood greenness {β=-0.22, p=0.09; β=-0.34, p=0.15, respectively}). Multilevel mediation analysis indicated that the proportion mediated as a direct effect on cardiopulmonary outcomes by suspected confounders (including total-PA, residential-neighborhood greenness, and occupational-address noise level) from primary exposures (including PM₁₀, PM_Coarse, and O₃) was not statistically significant.

CONCLUSION

Our findings suggest that increased daily space-time-activity-weighted PM_Coarse exposure levels significantly adversely affect cardiac autonomic modulation (as reduced total HRV) among healthy adults. Additionally, increased annual levels at the residential address of Ozone and PM₁₀ significantly increase diastolic blood pressure and reduce lung function, respectively, among healthy adults. These associations typically remained robust when adjusting for suspected confounders. Occupational-address noise and residential-neighborhood greenness levels, however, were seen as mediators of cardiovascular and pulmonary outcomes, respectively. Total daily physical activity was not seen as a mediator of any of the studied outcomes, which supports the promotion of active mobility within cities.

Air pollution as a risk factor in health impact assessments of a travel mode shift towards cycling

BACKGROUND

Promotion of active commuting provides substantial health and environmental benefits by influencing air pollution, physical activity, accidents, and noise. However, studies evaluating intervention and policies on a mode shift from motorized transport to cycling have estimated health impacts with varying validity and precision.

OBJECTIVE

To review and discuss the estimation of air pollution exposure and its impacts in health impact assessment studies of a shift in transport from cars to bicycles in order to guide future assessments.

METHODS

A systematic database search of PubMed was done primarily for articles published from January 2000 to May 2016 according to PRISMA guidelines.

RESULTS

We identified 18 studies of health impact assessment of change in transport mode. Most studies investigated future hypothetical scenarios of increased cycling. The impact on the general population was estimated using a comparative risk assessment approach in the majority of these studies, whereas some used previously published cost estimates. Air pollution exposure during cycling was estimated based on the ventilation rate, the pollutant concentration, and the trip duration. Most studies employed exposure-response functions from studies comparing background levels of fine particles between cities to estimate the health impacts of local traffic emissions. The effect of air pollution associated with increased cycling contributed small health benefits for the general population, and also only slightly increased risks associated with fine particle exposure among those who shifted to cycling. However, studies calculating health impacts based on exposure-response functions for ozone, black carbon or nitrogen oxides found larger effects attributed to changes in air pollution exposure.

CONCLUSION

A large discrepancy between studies was observed due to different health impact assessment approaches, different assumptions for calculation of inhaled dose and different selection of dose-response functions. This kind of assessments would improve from more holistic approaches using more specific exposure-response functions.

24-h Nitrogen dioxide concentration is associated with cooking behaviors and an increase in rescue medication use in children with asthma

Exposure to nitrogen dioxide (NO₂), a byproduct of combustion, is associated with poor asthma control in children. We sought to determine whether gas-fueled kitchen appliance use is associated with 24-h indoor NO₂ concentrations and whether these concentrations are associated with asthma morbidity in children. Children aged 5-12 years old with asthma were eligible. Mean 24-h NO₂ concentration was measured in the kitchen over a four-day sampling period and gas stove use was captured in time activity diaries. The relationship between stove and oven use and daily NO₂ concentration was analyzed. Longitudinal analysis assessed the effect of daily NO₂ exposure on symptoms, inhaler use, and lung function. Multivariate models were adjusted for age, sex, season, and maternal education. Thirty children contributed 126 participant days of sampling. Mean indoor 24-h NO₂ concentration was 58(48)ppb with a median (range) of 45(12-276)ppb. All homes had gas stoves and furnaces. Each hour of kitchen appliance use was associated with an 18ppb increase in 24-h NO₂ concentration. In longitudinal multivariate analysis, each ten-fold increase in previous-day NO₂ was associated with increased nighttime inhaler use (OR = 4.9, p = 0.04). There were no associations between NO₂ and lung function or asthma symptoms. Higher previous-day 24-h concentration of NO₂ is associated with increased nighttime inhaler use in children with asthma.

Weekly Personal Ozone Exposure and Respiratory Health in a Panel of Greek Schoolchildren

BACKGROUND

The association of ozone exposure with respiratory outcomes has been investigated in epidemiologic studies mainly including asthmatic children. The findings reported had methodological gaps and inconsistencies.

OBJECTIVES

We aimed to investigate effects of personal ozone exposure on various respiratory outcomes in school-age children generally representative of the population during their normal activities.

METHODS

We conducted a panel study in a representative sample of school-age children in the two major cities of Greece, Athens and Thessaloniki. We followed 188, 10- to 11-y-old, elementary school students for 5 wk spread throughout the 2013–2014 academic year, during which ozone was measured using personal samplers. At the end of each study week, spirometry was performed by trained physicians, and the fractional concentration of nitric oxide in exhaled air (F_eNO) was measured. Students kept a daily time–activity–symptom diary and measured PEF (peak expiratory flow) using peak flow meters. Mixed models accounting for repeated measurements were applied.

RESULTS

An increase of 10 μg/m³ in weekly ozone concentration was associated with a decrease in FVC (forced vital capacity) and FEV₁ (forced expiratory volume in 1 s) of 0.03 L [95% confidence interval (CI): −0.05, −0.01] and 0.01 L (95% CI: −0.03, 0.003) respectively. The same increase in exposure was associated with a 11.10% (95% CI: 4.23, 18.43) increase in F_eNO and 19% (95% CI: −0.53, 42.75) increase in days with any symptom. The effect estimates were robust to PM₁₀ adjustment. No inverse association was found between ozone exposure and PEF.

CONCLUSIONS

The study provides evidence that airway inflammation and the frequency of respiratory symptoms increase, whereas lung function decreases with increased ozone exposure in schoolchildren. https://doi.org/10.1289/EHP635.

Air pollution, PM2.5 composition, source factors, and respiratory symptoms in asthmatic and nonasthmatic children in Santiago, Chile

The objective of this study was to determine the association of respiratory symptoms and medication use and exposure to various air pollutants, PM_2.5 components, and source factors in a panel of asthmatic and nonasthmatic children in Santiago, Chile. To this end, 174 children (90 asthmatics and 84 nonasthmatics) were followed throughout the winter months of 2010 and 2011. During the study period, children filled out daily diaries to record respiratory symptoms and medication use. Air pollution data were obtained from government central site measurements and a PM_2.5 characterization campaign. PM_2.5 source factors were obtained using positive matrix factorization (PMF). Associations of symptoms and exposure to pollutants and source-factor daily scores were modeled separately for asthmatic and nonasthmatic children using mixed logistic regression models with random intercepts, controlling for weather, day of the week, year, and viral outbreaks. Overall, high concentrations of air pollutants and PM_2.5 components were observed. Six source factors were identified by PMF (motor vehicles, marine aerosol, copper smelter, secondary sulfates, wood burning, and soil dust). Overall, single pollutant models showed significant and strong associations between 7-day exposures for several criteria pollutants (PM_2.5, NO₂, O₃), PM_2.5 components (OC, K, S, Se, V), and source factors (secondary sulfate) and coughing, wheezing and three other respiratory symptoms in both in asthmatic and nonasthmatic children. No associations were found for use of rescue inhalers in asthmatics. Two-pollutant models showed that several associations remained significant after including PM_2.5, and other criteria pollutants, in the models, particularly components and source factors associated with industrial sources. In conclusion, exposure to air pollutants, especially PM_2.5, NO₂, and O₃, were found to exacerbate respiratory symptoms in both asthmatic and nonasthmatic children. Some of the results suggest that PM_2.5 components associated with a secondary sulfate source may have a greater impact on some symptoms than PM_2.5. In general, the results of this study show important associations at concentrations close or below current air quality standards.

The effect of size-segregated ambient particulate matter on Th1/Th2-like immune responses in mice

Background

Particulate matter (PM) has been associated with increased pulmonary and cardiovascular mortality and morbidity. Additionally, PM is known to exacerbate asthma. However, whether ambient PM exposure contributes to the onset of asthma, especially in non-atopic children and adults, is less conclusive. The current study aimed to evaluate the effects of size-fractioned PM on lung immune responses in healthy BALB/c mice.

Methods and principal findings

We collected PM₁₀, PM_2.5, PM₁ and PM_0.1 samples from October 2012 to August 2013 in the Taipei Basin. These PM samples were representative of urban traffic pollution. The samples were extracted and sonicated in phosphate-buffered saline (PBS). Female BALB/c mice were exposed to the samples via intratracheal instillation at three different doses: 1.75 mg/kg (35 μg/per mouse), 5 mg/kg (100 μg/per mouse), and 12.5 mg/kg (250 μg/per mouse). The mice were exposed on days 0 and 7, and PBS alone was used as a control. Following the exposures, the expression profiles of inflammatory cells and cytokines in bronchoalveolar lavage fluid (BALF) were assessed. Exposure to PM₁₀ resulted in inflammatory responses, including the recruitment of neutrophils and the induction of T helper 1 (Th1) cell-related cytokine release, such as TNF-α and IFN-γ. Furthermore, an allergic immune response, including the recruitment of eosinophils and the up-regulation of T helper 2 (Th2) cell-related cytokine release, such as IL-5 and IL-13, was also observed in the BALF of mice exposed to PM₁₀.

Conclusions

Our study showed that exposure to PM alone caused mixed Th1/Th2 inflammatory responses in healthy mice. These findings support the hypothesis that PM may contribute to the onset of asthma.

High risks of lung disease associated with early-life and moderate lifetime arsenic exposure in northern Chile

BACKGROUND

Arsenic in drinking water has been associated with increases in lung disease, but information on the long-term impacts of early-life exposure or moderate exposure levels are limited.

METHODS

We investigated pulmonary disease and lung function in 795 subjects from three socio-demographically similar areas in northern Chile: Antofagasta, which had a well-described period of high arsenic water concentrations (860μg/L) from 1958 to 1970; Iquique, which had long-term arsenic water concentrations near 60μg/L; and Arica, with long-term water concentrations ≤10μg/L.

RESULTS

Compared to adults never exposed >10μg/L, adults born in Antofagasta during the high exposure period had elevated odds ratios (OR) of respiratory symptoms (e.g., OR for shortness of breath=5.56, 90% confidence interval (CI): 2.68-11.5), and decreases in pulmonary function (e.g., 224mL decrease in forced vital capacity in nonsmokers, 90% CI: 97-351mL). Subjects with long-term exposure to arsenic water concentrations near 60μg/L also had increases in some pulmonary symptoms and reduced lung function.

CONCLUSIONS

Overall, these findings provide new evidence that in utero or childhood arsenic exposure is associated with non-malignant pulmonary disease in adults. They also provide preliminary new evidence that long-term exposures to moderate levels of arsenic may be associated with lung toxicity, although the magnitude of these latter findings were greater than expected and should be confirmed.

Air quality co-benefits of subnational carbon policies

To mitigate climate change, governments ranging from city to multi-national have adopted greenhouse gas (GHG) emissions reduction targets. While the location of GHG reductions does not affect their climate benefits, it can impact human health benefits associated with co-emitted pollutants. Here, an advanced modeling framework is used to explore how subnational level GHG targets influence air pollutant co-benefits from ground level ozone and fine particulate matter. Two carbon policy scenarios are analyzed, each reducing the same total amount of GHG emissions in the Northeast US: an economy-wide Cap and Trade (CAT) program reducing emissions from all sectors of the economy, and a Clean Energy Standard (CES) reducing emissions from the electricity sector only. Results suggest that a regional CES policy will cost about 10 times more than a CAT policy. Despite having the same regional targets in the Northeast, carbon leakage to non-capped regions varies between policies. Consequently, a regional CAT policy will result in national carbon reductions that are over six times greater than the carbon reduced by the CES in 2030. Monetized regional human health benefits of the CAT and CES policies are 844% and 185% of the costs of each policy, respectively. Benefits for both policies are thus estimated to exceed their costs in the Northeast US. The estimated value of human health co-benefits associated with air pollution reductions for the CES scenario is two times that of the CAT scenario.

IMPLICATIONS

In this research, an advanced modeling framework is used to determine the potential impacts of regional carbon policies on air pollution co-benefits associated with ground level ozone and fine particulate matter. Study results show that spatially heterogeneous GHG policies have the potential to create areas of air pollution dis-benefit. It is also shown that monetized human health benefits within the area covered by policy may be larger than the model estimated cost of the policy. These findings are of particular interest both as U.S. states work to develop plans to meet state-level carbon emissions reduction targets set by the EPA through the Clean Power Plan, and in the absence of comprehensive national carbon policy.

Association Between Unconventional Natural Gas Development in the Marcellus Shale and Asthma Exacerbations

IMPORTANCE

Asthma is common and can be exacerbated by air pollution and stress. Unconventional natural gas development (UNGD) has community and environmental impacts. In Pennsylvania, UNGD began in 2005, and by 2012, 6253 wells had been drilled. There are no prior studies of UNGD and objective respiratory outcomes.

OBJECTIVE

To evaluate associations between UNGD and asthma exacerbations.

DESIGN

A nested case-control study comparing patients with asthma with and without exacerbations from 2005 through 2012 treated at the Geisinger Clinic, which provides primary care services to over 400 000 patients in Pennsylvania. Patients with asthma aged 5 to 90 years (n = 35 508) were identified in electronic health records; those with exacerbations were frequency matched on age, sex, and year of event to those without.

EXPOSURES

On the day before each patient's index date (cases, date of event or medication order; controls, contact date), we estimated activity metrics for 4 UNGD phases (pad preparation, drilling, stimulation [hydraulic fracturing, or "fracking"], and production) using distance from the patient's home to the well, well characteristics, and the dates and durations of phases.

MAIN OUTCOMES AND MEASURES

We identified and defined asthma exacerbations as mild (new oral corticosteroid medication order), moderate (emergency department encounter), or severe (hospitalization).

RESULTS

We identified 20 749 mild, 1870 moderate, and 4782 severe asthma exacerbations, and frequency matched these to 18 693, 9350, and 14 104 control index dates, respectively. In 3-level adjusted models, there was an association between the highest group of the activity metric for each UNGD phase compared with the lowest group for 11 of 12 UNGD-outcome pairs: odds ratios (ORs) ranged from 1.5 (95% CI, 1.2-1.7) for the association of the pad metric with severe exacerbations to 4.4 (95% CI, 3.8-5.2) for the association of the production metric with mild exacerbations. Six of the 12 UNGD-outcome associations had increasing ORs across quartiles. Our findings were robust to increasing levels of covariate control and in sensitivity analyses that included evaluation of some possible sources of unmeasured confounding.

CONCLUSIONS AND RELEVANCE

Residential UNGD activity metrics were statistically associated with increased risk of mild, moderate, and severe asthma exacerbations. Whether these associations are causal awaits further investigation, including more detailed exposure assessment.

Integrating High-Resolution Datasets to Target Mitigation Efforts for Improving Air Quality and Public Health in Urban Neighborhoods

Reducing exposure to degraded air quality is essential for building healthy cities. Although air quality and population vary at fine spatial scales, current regulatory and public health frameworks assess human exposures using county- or city-scales. We build on a spatial analysis technique, dasymetric mapping, for allocating urban populations that, together with emerging fine-scale measurements of air pollution, addresses three objectives: (1) evaluate the role of spatial scale in estimating exposure; (2) identify urban communities that are disproportionately burdened by poor air quality; and (3) estimate reduction in mobile sources of pollutants due to local tree-planting efforts using nitrogen dioxide. Our results show a maximum value of 197% difference between cadastrally-informed dasymetric system (CIDS) and standard estimations of population exposure to degraded air quality for small spatial extent analyses, and a lack of substantial difference for large spatial extent analyses. These results provide the foundation for improving policies for managing air quality, and targeting mitigation efforts to address challenges of environmental justice.

Spatiotemporal calibration and resolution refinement of output from deterministic models

Spatiotemporal calibration of output from deterministic models is an increasingly popular tool to more accurately and efficiently estimate the true distribution of spatial and temporal processes. Current calibration techniques have focused on a single source of data on observed measurements of the process of interest that are both temporally and spatially dense. Additionally, these methods often calibrate deterministic models available in grid-cell format with pixel sizes small enough that the centroid of the pixel closely approximates the measurement for other points within the pixel. We develop a modeling strategy that allows us to simultaneously incorporate information from two sources of data on observed measurements of the process (that differ in their spatial and temporal resolutions) to calibrate estimates from a deterministic model available on a regular grid. This method not only improves estimates of the pollutant at the grid centroids but also refines the spatial resolution of the grid data. The modeling strategy is illustrated by calibrating and spatially refining daily estimates of ambient nitrogen dioxide concentration over Connecticut for 1994 from the Community Multiscale Air Quality model (temporally dense grid-cell estimates on a large pixel size) using observations from an epidemiologic study (spatially dense and temporally sparse) and Environmental Protection Agency monitoring stations (temporally dense and spatially sparse). Copyright © 2016 John Wiley & Sons, Ltd.

Potential hazards of air pollutant emissions from unconventional oil and natural gas operations on the respiratory health of children and infants

Research on air pollutant emissions associated with unconventional oil and gas (UOG) development has grown significantly in recent years. Empirical investigations have focused on the identification and measurement of oil and gas air pollutants [e.g. volatile organic compounds (VOCs), particulate matter (PM), methane] and the influence of UOG on local and regional ambient air quality (e.g. tropospheric ozone). While more studies to better characterize spatial and temporal trends in exposure among children and newborns near UOG sites are needed, existing research suggests that exposure to air pollutants emitted during lifecycle operations can potentially lead to adverse respiratory outcomes in this population. Children are known to be at a greater risk from exposure to air pollutants, which can impair lung function and neurodevelopment, or exacerbate existing conditions, such as asthma, because the respiratory system is particularly vulnerable during development in-utero, the postnatal period, and early childhood. In this article, we review the literature relevant to respiratory risks of UOG on infants and children. Existing epidemiology studies document the impact of air pollutant exposure on children in other contexts and suggest impacts near UOG. Research is sparse on long-term health risks associated with frequent acute exposures - especially in children - hence our interpretation of these findings may be conservative. Many data gaps remain, but existing data support precautionary measures to protect the health of infants and children.

Inflammatory cell signaling following exposures to particulate matter and ozone

BACKGROUND

Particulate matter (PM) and ozone (O3) are two major ambient air pollutants. Epidemiological and toxicological studies have demonstrated exposure to these pollutants is associated with a variety of adverse health effects, including cardiovascular and respiratory disease, in which inflammation is believed to be a common and essential factor.

SCOPE OF REVIEW

This review mainly focuses on major inflammatory cell signaling pathways triggered by exposure to PM and O3. The receptors covered in this review include the EGF receptor, toll like receptor, and NOD-like receptor. Intracellular signaling protein kinases depicted in this review are phosphatidylinositol 3-kinase and mitogen-activated protein kinases. Activation of antioxidant and inflammatory transcription factors such as NrF2 and NFκB induced by PM and O3 is also discussed.

MAJOR CONCLUSIONS

Exposure to PM or O3 can activate cellular signaling networks including membrane receptors, intracellular kinases and phosphatases, and transcription factors that regulate inflammatory responses. While PM-induced cell signaling is associated with resultant ROS, O3-induced cell signaling implicates phosphates. Notably, the cellular signaling induced by PM and O3 exposure varies with cell type and physiochemical properties of these pollutants.

GENERAL SIGNIFICANCE

Cellular signaling plays a critical role in the regulation of inflammatory pathogenesis. Elucidation of cellular signaling pathways initiated by PM or O3 cannot only help to uncover the mechanisms of air pollutant toxicity but also provide clues for development of interventional measures against air pollution-induced disorders. This article is part of a Special Issue entitled Air Pollution, edited by Wenjun Ding, Andrew J. Ghio and Weidong Wu.

Assessing public health burden associated with exposure to ambient black carbon in the United States

Black carbon (BC) is a significant component of fine particulate matter (PM2.5) air pollution, which has been linked to a series of adverse health effects, in particular premature mortality. Recent scientific research indicates that BC also plays an important role in climate change. Therefore, controlling black carbon emissions provides an opportunity for a double dividend. This study quantifies the national burden of mortality and morbidity attributable to exposure to ambient BC in the United States (US). We use GEOS-Chem, a global 3-D model of atmospheric composition to estimate the 2010 annual average BC levels at 0.5×0.667° resolution, and then re-grid to 12-km grid resolution across the continental US. Using PM2.5 mortality risk coefficient drawn from the American Cancer Society cohort study, the numbers of deaths due to BC exposure were estimated for each 12-km grid, and then aggregated to the county, state and national level. Given evidence that BC particles may pose a greater risk on human health than other components of PM2.5, we also conducted sensitivity analysis using BC-specific risk coefficients drawn from recent literature. We estimated approximately 14,000 deaths to result from the 2010 BC levels, and hundreds of thousands of illness cases, ranging from hospitalizations and emergency department visits to minor respiratory symptoms. Sensitivity analysis indicates that the total BC-related mortality could be even significantly larger than the above mortality estimate. Our findings indicate that controlling BC emissions would have substantial benefits for public health in the US.

Regression calibration with instrumental variables for longitudinal models with interaction terms, and application to air pollution studies

In this paper, we derive forms of estimators and associated variances for regression calibration with instrumental variables in longitudinal models that include interaction terms between two unobservable predictors and interactions between these predictors and covariates not measured with error; the inclusion of the latter interactions generalize results we previously reported. The methods are applied to air pollution and health data collected on children with asthma. The new methods allow for the examination of how the relationship between health outcome leukotriene E4 (LTE₄, a biomarker of inflammation) and two unobservable pollutant exposures and their interaction are modified by the presence or absence of upper respiratory infections. The pollutant variables include secondhand smoke and ambient (outdoor) fine particulate matter. Simulations verify the accuracy of the proposed methods under various conditions.