Joint effects of ambient air pollutants on pediatric asthma emergency department visits in Atlanta, 1998-2004

Short-Term Interaction Effects of PM2.5 and O3 on Daily Mortality: A Time-Series Study of Multiple Cities in China

In recent years, PM2.5 and O3 have been the two main pollutants affecting public health in China, but the interaction of the two pollutants on human health remains unclear. A two-stage analytical approach was used to investigate the relationships of PM2.5-O3 co-pollution with nonaccidental, cardiovascular, and respiratory mortality levels across 14 cities in China. We first utilized a generalized additive model (GAM) to determine the city-specific associations of PM2.5 and O3 with daily mortality. The associations were then combined at the national and regional levels using meta-analysis. To investigate the potential interactions between the two pollutants and cause-specific mortality, we performed stratified analyses by co-pollutant exposure levels and the synergy index (SI) (SI > 1 indicates a synergistic interaction). The effect of changes in the two pollutants' concentrations (in 10 μg/m3 increases) on mortality was assessed. The stratification analysis results suggested that each 10 μg/m3 increase in PM2.5 at lag0-1 (lag01) in the low, moderate, and high strata of the O3 concentrations increased nonaccidental mortality by 0.07% (95% confidence interval: -0.03%, 0.17%), 0.33% (0.13%, 0.53%), and 0.68% (0.30%, 1.06%), respectively, with significant between-group differences (p < 0.001). Moreover, each 10 μg/m3 increase in O3 (lag01) in the low, moderate, and high strata of the PM2.5 concentrations increased nonaccidental mortality by 0.15% (-0.06%, 0.36%), 0.53% (0.19%, 0.87%), and 0.75% (0.14%, 1.36%), respectively, with significant between-group differences (p < 0.001). We also found substantial synergistic interactions between the two pollutants and nonaccidental, cardiovascular, and respiratory mortality levels, with SI values of 1.48, 1.51, and 1.33, respectively. Additionally, a subgroup analysis revealed that the interaction of these two pollutants on nonaccidental mortality were greater in South China compared to elsewhere, and during the warm season compared to during the cold season. Our findings suggested that the simultaneous control of PM2.5 and O3 within the context of combined air pollution could significantly decrease the disease risk, especially in southern China and during the warm season.

Joint Effect of Short-Term Exposure to Fine Particulate Matter and Ozone on Mortality: A Time Series Study in 272 Chinese Cities

Short-term exposure to PM2.5 or O3 can increase mortality risk; however, limited studies have evaluated their interaction. A multicity time series study was conducted to investigate the synergistic effect of PM2.5 and O3 on mortality in China, using mortality data and high-resolution pollutant predictions from 272 cities in 2013-2015. Generalized additive models were applied to estimate associations of PM2.5 and O3 with mortality. Modification and interaction effects were explored by stratified analyses and synergistic indexes. Deaths attributable to PM2.5 and O3 were evaluated with or without modification of the other pollutant. The risk of total nonaccidental mortality increased by 0.70% for each 10 μg/m3 increase in PM2.5 when O3 levels were high, compared to 0.12% at low O3 levels. The effect of O3 on total nonaccidental mortality at high PM2.5 levels (1.26%) was also significantly higher than that at low PM2.5 levels (0.59%). Similar patterns were observed for cardiovascular or respiratory diseases. The relative excess risk of interaction and synergy index of PM2.5 and O3 on nonaccidental mortality were 0.69% and 1.31 with statistical significance, respectively. Nonaccidental deaths attributable to short-term exposure of PM2.5 or O3 when considering modification of the other pollutant were 28% and 31% higher than those without considering modification, respectively. Our results found synergistic effects of short-term coexposure to PM2.5 and O3 on mortality and suggested underestimations of attributable risks without considering their synergistic effects.

Ambient air pollution and the risk of violence in primary and secondary school settings: a cross-sectional study

BACKGROUND

Individual and social characteristics are attributed to violent behavior in schools, yet environmental hazards may play an understudied role. Ambient air pollution has been linked to neurological dysfunction that inhibits decision-making and may result in violent behavior in adult populations. However, little is known on how air pollution may be associated with violent behaviors in children.

METHODS

A cross-sectional ecologic study was designed to estimate the associations between air pollution (fine particulate matter, carbon monoxide, and nitrogen dioxide) with the occurrence of violent incidents and incidents involving a weapon among a cohort of children in Minnesota schools (2008-2012). Differences by urban and rural status of schools were also explored. Negative binomial regression models were developed to estimate incidence rate ratios (IRR) and incidence rate differences (IRD) to describe associations between air pollution and violent incidents in school settings.

RESULTS

Our results indicate that the highest levels of carbon monoxide, nitrogen dioxide and fine particulate matter concentrations were associated with increased violent disciplinary incidents. Among the total student population, the 4th quartile of carbon monoxide exposure was associated with an IRD of 775.62 (95% CI 543.2, 1008.05) violent incidents per 100,000 students per school year compared to schools in the lowest quartile of exposure. Comparing the 4th to the 1st quartiles of exposure, nitrogen dioxide and fine particulate matter had an IRD of 629.16 (95% CI 384.87, 873.46), and 510.49 (95% CI 274.92, 746.05) violent incidents per 100,000 students per school year respectively. Schools in urban settings shared a larger burden of violent incidents associated with air pollution compared to rural schools.

CONCLUSIONS

Modifying environmental pollutants surrounding school environments, particularly for high exposure communities, may be a novel tool for reducing violence and subsequent injuries in schools.

Combined effect of changes in NO2, O3, PM2.5, SO2 and CO concentrations on small airway dysfunction

BACKGROUND AND OBJECTIVE

When multiple complex air pollutants are combined in real-world settings, the reliability of estimating the effect of a single pollutant is questionable. This study aimed to investigate the combined effects of changes in air pollutants on small airway dysfunction (SAD).

METHODS

We analysed Korea National Health and Nutrition Examination Survey (KNHANES) V-VIII database from 2010 to 2018 to elucidate the associations between annual changes in air pollutants over a previous 5-year period and small airway function. We estimated the annual concentrations of five air pollutants: NO2, O3, PM2.5, SO2 and CO. Forced expiratory flow between 25% and 75% of vital capacity (FEF25%-75%) <65% was defined as SAD. Using the quantile generalized-Computation (g-Computation) model, the combined effect of the annual changes in different air pollutants was estimated.

RESULTS

A total of 29,115 individuals were included. We found significant associations between SAD and the quartiles of annual changes in NO2 (OR = 1.10, 95% CI = 1.08-1.12), O3 (OR = 1.03, 95% CI = 1.00-1.05), PM2.5 (OR = 1.03, 95% CI = 1.00-1.05), SO2 (OR = 1.04, 95% CI = 1.02-1.08) and CO (OR = 1.16, 95% CI = 1.12-1.19). The combined effect of the air pollutant changes was significantly associated with SAD independent of smoking (OR = 1.31, 95% CI = 1.26-1.35, p-value <0.001), and this trend was consistently observed across the entire study population and various subgroup populations. As the estimated risk of SAD, determined by individual-specific combined effect models, increased and the log odds for SAD increased linearly.

CONCLUSION

The combined effect of annual changes in multiple air pollutant concentrations were associated with an increased risk of SAD.

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.

The joint effects of mixture exposure to multiple meteorological factors on step count: A panel study in China

The public health burden of increasing extreme weather events has been well documented. However, the influence of meteorological factors on physical activity remains limited. Existing mixture effect methods cannot handle cumulative lag effects. Therefore, we developed quantile g-computation Distributed lag non-linear model (QG-DLNM) by embedding a DLNM into quantile g-computation to allow for the concurrent consideration of both cumulated lag effects and mixture effects. We gathered repeated measurement data from Henan Province in China to investigate both the individual impact of meteorological factor on step counts using a DLNM, and the joint effect using the QG-DLNM. We projected future step counts linked to changes in temperature and relative humidity driven by climate change under three scenarios from the sixth phase of the Coupled Model Intercomparison Project. Our findings indicate there are inversed U-shaped associations for temperature, wind speed, and mixture exposure with step counts, peaking at 11.6 °C in temperature, 2.7 m/s in wind speed, and 30th percentile in mixture exposure. However, there are negative associations between relative humidity and rainfall with step counts. Additionally, relative humidity possesses the highest weights in the joint effect (49% contribution). Compared to 2022s, future step counts are projected to decrease due to temperature changes, while increase due to relative humidity changes. However, when considering both future temperature and humidity changes driven by climate change, the projections indicate a decrease in step counts. Our findings may suggest Chinese physical activity will be negatively influenced by global warming.

The joint effect of cumulative doses for outdoor air pollutants exposure in early life on asthma and wheezing among young children

BACKGROUND

Constrained by no proper way to assess cumulative exposure, the joint effect of air pollution cumulative exposure doses on childhood asthma and wheezing (AW) was not understood.

OBJECTIVE

To assess the association between cumulative exposure to multiple air pollutants in early life and childhood AW.

METHODS

We designed a nested case-control study based on the birth cohort in Jinan City. Children with AW followed up within 2 years after birth were treated as cases, and non-cases in this cohort were treated as the control source population, and the propensity score matching method was used to match each case to 5 controls. We calculated the individual cumulative outdoor exposure doses for each period using an inverse distance weighted model, alongside the complex Simpson's formula, accounting for outdoor time and respiratory volume. The Least absolute shrinkage and selection operator (Lasso) regression was performed to screen for covariates. To analyze the joint effects of pollutants, we employed the weighted quantile sum (WQS) regression model in conjunction with conditional logistic regression.

RESULTS

84 cases and 420 controls were included in this study. The odds ratio (OR) with 95% confidence interval (CI) of the impact of cumulative exposure (mg/m3) after birth on childhood AW was 1.78 (1.15-2.74) for SO2, 1.69 (1.11-2.57) for NO2, and 1.65 (1.09-2.52) for PM2.5, respectively. Furthermore, with each 25th percentile increase in the WQS index, the overall risk of cumulative doses for six pollutants exposure after birth on AW increased by an adjusted OR of 1.10 (1.03, 1.18), and SO2, PM2.5, and NO2 contributed the most to the WQS index. However, no statistically significant association was found between cumulative exposure to all pollutants before birth and childhood AW.

CONCLUSIONS

There was a joint effect of the cumulative exposure dose of outdoor air pollutants after birth on AW in children aged 0-2 years. And traffic-related pollutants (SO2, PM2.5, and NO2) make a greater contribution to the joint effect.

Quantifying Multipollutant Health Impacts Using the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE): A Case Study in Atlanta, Georgia

BACKGROUND

Air pollution risk assessments do not generally quantify health impacts using multipollutant risk estimates, but instead use results from single-pollutant or copollutant models. Multipollutant epidemiological models account for pollutant interactions and joint effects but can be computationally complex and data intensive. Risk estimates from multipollutant studies are therefore challenging to implement in the quantification of health impacts.

OBJECTIVES

Our objective was to conduct a case study using a developmental multipollutant version of the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) to estimate the health impact associated with changes in multiple air pollutants using both a single and multipollutant approach.

METHODS

BenMAP-CE was used to estimate the change in the number of pediatric asthma emergency department (ED) visits attributable to simulated changes in air pollution between 2011 and 2025 in Atlanta, Georgia, applying risk estimates from an epidemiological study that examined short-term single-pollutant and multipollutant (with and without first-order interactions) exposures. Analyses examined individual pollutants (i.e., ozone, fine particulate matter, carbon monoxide, nitrogen dioxide (NO 2 ), sulfur dioxide, and particulate matter components) and combinations of these pollutants meant to represent shared properties or predefined sources (i.e., oxidant gases, secondary pollutants, traffic, power plant, and criteria pollutants). Comparisons were made between multipollutant health impact functions (HIF) and the sum of single-pollutant HIFs for the individual pollutants that constitute the respective pollutant groups.

RESULTS

Photochemical modeling predicted large decreases in most of the examined pollutant concentrations between 2011 and 2025 based on sector specific (i.e., source-based) estimates of growth and anticipated controls. Estimated number of avoided asthma ED visits attributable to any given multipollutant group were generally higher when using results from models that included interaction terms in comparison with those that did not. We estimated the greatest number of avoided pediatric asthma ED visits for pollutant groups that include NO 2 (i. e., criteria pollutants, oxidants, and traffic pollutants). In models that accounted for interaction, year-round estimates for pollutant groups that included NO 2 ranged from 27.1 [95% confidence interval (CI): 1.6, 52.7; traffic pollutants] to 55.4 (95% CI: 41.8, 69.0; oxidants) avoided pediatric asthma ED visits. Year-round results using multipollutant risk estimates with interaction were comparable to the sum of the single-pollutant results corresponding to most multipollutant groups [e.g., 52.9 (95% CI: 43.6, 62.2) for oxidants] but were notably lower than the sum of the single-pollutant results for some pollutant groups [e.g., 77.5 (95% CI: 66.0, 89.0) for traffic pollutants].

DISCUSSION

Performing a multipollutant health impact assessment is technically feasible but computationally complex. It requires time, resources, and detailed input parameters not commonly reported in air pollution epidemiological studies. Results estimated using the sum of single-pollutant models are comparable to those quantified using a multipollutant model. Although limited to a single study and location, assessing the trade-offs between a multipollutant and single-pollutant approach is warranted. https://doi.org/10.1289/EHP12969.

Per- and polyfluoroalkyl substances, polychlorinated biphenyls, organochlorine pesticides, and polybrominated diphenyl ethers and dysregulation of MicroRNA expression in humans and animals-A systematic review

BACKGROUND

Persistent organic pollutants (POPs) are chemicals characterized by their environmental persistence. Evidence suggests that exposure to POPs, which is ubiquitous, is associated with microRNA (miRNA) dysregulation. miRNA are key regulators in many physiological processes. It is thus of public health concern to understand the relationships between POPs and miRNA as related to health outcomes.

OBJECTIVES

This systematic review evaluated the relationship between widely recognized, intentionally manufactured, POPs, including per- and polyfluoroalkyl substances (PFAS), polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), and organochlorine pesticides (dichlorodiphenyltrichloroethane [DDT], dichlorodiphenyldichloroethylene [DDE], hexachlorobenzene [HCB]), with miRNA expression in both human and animal studies.

METHODS

We used PubMed and Embase to systematically search the literature up to September 29th, 2023. Search results for human and animal studies were included if they incorporated at least one POP of interest in relation to at least one miRNA. Data were synthesized to determine the direction and significance of associations between POPs and miRNA. We utilized ingenuity pathway analysis to review disease pathways for miRNA that were associated with POPs.

RESULTS

Our search identified 38 eligible studies: 9 in humans and 29 in model organisms. PFAS were associated with decreased expression of miR-19, miR-193b, and miR-92b, as well as increased expression of miR-128, miR-199a-3p, and miR-26b across species. PCBs were associated with increased expression of miR-15a, miR-1537, miR-21, miR-22-3p, miR-223, miR-30b, and miR-34a, as well as decreased expression of miR-130a and let-7b in both humans and animals. Pathway analysis for POP-associated miRNA identified pathways related to carcinogenesis.

DISCUSSION

This is the first systematic review of the association of POPs with miRNA in humans and model organisms. Large-scale prospective human studies are warranted to examine the role of miRNA as mediators between POPs and health outcomes.

Integrating Clinical and Air Quality Data to Improve Prediction of COPD Exacerbations

Several studies have found associations between air pollution and respiratory disease outcomes. However, there is minimal prognostic research exploring whether integrating air quality into clinical prediction models can improve accuracy and utility. In this study, we built models using both logistic regression and random forests to determine the benefits of including air quality data with meteorological and clinical data in prediction of COPD exacerbations requiring medical care. Logistic models were not improved by inclusion of air quality. However, the net benefit curves of random forest models showed greater clinical utility with the addition of air quality data. These models demonstrate a practical and relatively low-cost way to include environmental information into clinical prediction tools to improve the clinical utility of COPD prediction. Findings could be used to provide population level health warnings as well as individual-patient risk assessments.

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.

Short-term joint effects of ambient PM2.5 and O3 on mortality in Beijing, China

Introduction

In recent years, air pollution caused by co-occurring PM2.5 and O3, named combined air pollution (CAP), has been observed in Beijing, China, although the health effects of CAP on population mortality are unclear.

Methods

We employed Poisson generalized additive models (GAMs) to evaluate the individual and joint effects of PM2.5 and O3 on mortality (nonaccidental, respiratory, and cardiovascular mortality) in Beijing, China, during the whole period (2014-2016) and the CAP period. Adverse health effects were assessed for percentage increases (%) in the three mortality categories with each 10-μg/m3 increase in PM2.5 and O3. The cumulative risk index (CRI) was adopted as a novel approach to quantify the joint effects.

Results

The results suggested that both PM2.5 and O3 exhibited the greatest individual effects on the three mortality categories with cumulative lag day 01. Increases in the nonaccidental, cardiovascular, and respiratory mortality categories were 0.32%, 0.36%, and 0.43% for PM2.5 (lag day 01) and 0.22%, 0.37%, and 0.25% for O3 (lag day 01), respectively. There were remarkably synergistic interactions between PM2.5 and O3 on the three mortality categories. The study showed that the combined effects of PM2.5 and O3 on nonaccidental, cardiovascular, and respiratory mortality were 0.34%, 0.43%, and 0.46%, respectively, during the whole period and 0.58%, 0.79%, and 0.75%, respectively, during the CAP period. Our findings suggest that combined exposure to PM2.5 and O3, particularly during CAP periods, could further exacerbate their single-pollutant health risks.

Conclusion

These findings provide essential scientific evidence for the possible creation and implementation of environmental protection strategies by policymakers.

Joint Effects of Long-Term Exposure to Ambient Fine Particulate Matter and Ozone on Asthmatic Symptoms: Prospective Cohort Study

BACKGROUND

The associations of long-term exposure to air pollutants in the presence of asthmatic symptoms remain inconclusive and the joint effects of air pollutants as a mixture are unclear.

OBJECTIVE

We aimed to investigate the individual and joint associations of long-term exposure to ambient fine particulate matter (PM2.5) and daily 8-hour maximum ozone concentrations (MDA8 O3) in the presence of asthmatic symptoms in Chinese adults.

METHODS

Data were derived from the World Health Organization Study on Global Ageing and Adult Health (WHO SAGE) cohort study among adults aged 50 years or older, which was implemented in 1 municipality and 7 provinces across China during 2007-2018. Annual average MDA8 O3 and PM2.5 at individual residential addresses were estimated by an iterative random forest model and a satellite-based spatiotemporal model, respectively. Participants who were diagnosed with asthma by a doctor or taking asthma-related therapies or experiencing related conditions within the past 12 months were recorded as having asthmatic symptoms. The individual associations of PM2.5 and MDA8 O3 with asthmatic symptoms were estimated by a Cox proportional hazards regression model, and the joint association was estimated by a quantile g-computation model. A series of subgroup analyses was applied to examine the potential modifications of some characteristics. We also calculated the population-attributable fraction (PAF) of asthmatic symptoms attributed to PM2.5 and MDA8 O3.

RESULTS

A total of 8490 adults older than 50 years were included, and the average follow-up duration was 6.9 years. During the follow-up periods, 586 (6.9%) participants reported asthmatic symptoms. Individual effect analyses showed that the risk of asthmatic symptoms was positively associated with MDA8 O3 (hazard ratio [HR] 1.12, 95% CI 1.01-1.24, for per quantile) and PM2.5 (HR 1.18, 95% CI 1.05-1.31, for per quantile). Joint effect analyses showed that per equal quantile increment of MDA8 O3 and PM2.5 was associated with an 18% (HR 1.18, 95% CI 1.05-1.33) increase in the risk of asthmatic symptoms, and PM2.5 contributed more (68%) in the joint effects. The individual PAFs of asthmatic symptoms attributable to PM2.5 and MDA8 O3 were 2.86% (95% CI 0.17%-5.50%) and 4.83% (95% CI 1.42%-7.25%), respectively, while the joint PAF of asthmatic symptoms attributable to exposure mixture was 4.32% (95% CI 1.10%-7.46%). The joint associations were greater in participants with obesity, in urban areas, with lower family income, and who used unclean household cooking fuel.

CONCLUSIONS

Long-term exposure to PM2.5 and MDA8 O3 may individually and jointly increase the risk of asthmatic symptoms, and the joint effects were smaller than the sum of individual effects. These findings informed the importance of joint associations of long-term exposure to air pollutants with asthma.

Monitoring vs. modeled exposure data in time-series studies of ambient air pollution and acute health outcomes

BACKGROUND

Population-based short-term air pollution health studies often have limited spatiotemporally representative exposure data, leading to concerns of exposure measurement error.

OBJECTIVE

To compare the use of monitoring and modeled exposure metrics in time-series analyses of air pollution and cardiorespiratory emergency department (ED) visits.

METHODS

We obtained daily counts of ED visits for Atlanta, GA during 2009-2013. We leveraged daily ZIP code level concentration estimates for eight pollutants from nine exposure metrics. Metrics included central monitor (CM), monitor-based (inverse distance weighting, kriging), model-based [community multiscale air quality (CMAQ), land use regression (LUR)], and satellite-based measures. We used Poisson models to estimate air pollution health associations using the different exposure metrics. The approach involved: (1) assessing CM-based associations, (2) determining if non-CM metrics can reproduce CM-based associations, and (3) identifying potential value added of incorporating full spatiotemporal information provided by non-CM metrics.

RESULTS

Using CM exposures, we observed associations between cardiovascular ED visits and carbon monoxide, nitrogen dioxide, fine particulate matter, elemental and organic carbon, and between respiratory ED visits and ozone. Non-CM metrics were largely able to reproduce CM-based associations, although some unexpected results using CMAQ- and LUR-based metrics reduced confidence in these data for some spatiotemporally-variable pollutants. Associations with nitrogen dioxide and sulfur dioxide were only detected, or were stronger, when using metrics that incorporate all available monitoring data (i.e., inverse distance weighting and kriging).

SIGNIFICANCE

The use of routinely-collected ambient monitoring data for exposure assignment in time-series studies of large metropolitan areas is a sound approach, particularly when data from multiple monitors are available. More sophisticated approaches derived from CMAQ, LUR, or satellites may add value when monitoring data are inadequate and if paired with thorough data characterization. These results are useful for interpretation of existing literature and for improving exposure assessment in future studies.

IMPACT STATEMENT

This study compared and interpreted the use of monitoring and modeled exposure metrics in a daily time-series analysis of air pollution and cardiorespiratory emergency department visits. The results suggest that the use of routinely-collected ambient monitoring data in population-based short-term air pollution and health studies is a sound approach for exposure assignment in large metropolitan regions. CMAQ-, LUR-, and satellite-based metrics may allow for health effects estimation when monitoring data are sparse, if paired with thorough data characterization. These results are useful for interpretation of existing health effects literature and for improving exposure assessment in future air pollution epidemiology studies.

Health effects of air pollutant mixtures (volatile organic compounds, particulate matter, sulfur and nitrogen oxides) - a review of the literature

The health risks associated with individual air pollutant exposures have been studied and documented, but in real-life, the population is exposed to a multitude of different substances, designated as mixtures. A body of literature on air pollutants indicated that the next step in air pollution research is investigating pollutant mixtures and their potential impacts on health, as a risk assessment of individual air pollutants may actually underestimate the overall risks. This review aims to synthesize the health effects related to air pollutant mixtures containing selected pollutants such as: volatile organic compounds, particulate matter, sulfur and nitrogen oxides. For this review, the PubMed database was used to search for articles published within the last decade, and we included studies assessing the associations between air pollutant mixtures and health effects. The literature search was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A number of 110 studies were included in the review from which data on pollutant mixtures, health effects, methods used, and primary results were extracted. Our review emphasized that there are a relatively small number of studies addressing the health effects of air pollutants as mixtures and there is a gap in knowledge regarding the health effects associated with these mixtures. Studying the health effects of air pollutant mixtures is challenging due to the complexity of components that mixtures may contain, and the possible interactions these different components may have.

The Moderating Role of Housing Quality on Concentrated Poverty and Asthma-Related Emergency Department Visits Among Hispanics/Latinos

Background. Rates of asthma-related emergency department visits have been shown to vary significantly by place (i.e., neighborhood) and race/ethnicity. The moderating factors of asthmatic events among Hispanic/Latino-specific populations are known to a much lesser degree. Objective. To assess the extent to which housing moderates the effect of poverty on Hispanic/Latino-specific asthma-related emergency department (ED) visits at an ecological level. Methods. Using data from the Office of Statewide Health Planning and Development (OSHPD) and the 2016-2017 U.S. Census, a cross-sectional ecological analysis at the census tract-level was conducted. Crosswalk files from the U.S. Department of Housing and Urban Development were used to associate zip codes to census tracts. Negative binomial regression was used to estimate rate ratios. Results. The effect of poverty on asthma-related ED visits was significantly moderated by the median year of housing structures built. The effect of mid-level poverty (RR= 1.57, 95% CI 1.27, 1.95) and high-level poverty (RR= 1.47, 95% CI 1.22, 1.78) in comparison to low-level poverty, was significantly greater among census tracts with housing built prior to 1965 in comparison to census tract with housing built between 1965-2020. Conclusion. Communities with older housing structures tend to be associated with increased Hispanic/Latino ED visits apart from affluent communities.

Joint Associations of Short-Term Exposure to Ambient Air Pollutants with Hospital Admission of Ischemic Stroke

BACKGROUND

Studies have estimated the associations of short-term exposure to ambient air pollution with ischemic stroke. However, the joint associations of ischemic stroke with air pollution as a mixture remain unknown.

METHODS

We employed a time-stratified case-crossover study to investigate 824,808 ischemic stroke patients across China. We calculated daily mean concentrations of particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5), maximum 8-h average for O3 (MDA8 O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO) across all monitoring stations in the city where the IS patients resided. We conducted conditional logistic regression models to estimate the exposure-response associations.

RESULTS

Results from single-pollutant models showed positive associations of hospital admission for ischemic stroke with PM2.5 (excess risk [ER] = 0.38%, 95% confidence interval [CI]: 0.29% to 0.47%, for 10 μg/m3), MDA8 O3 (ER = 0.29%, 95% CI: 0.18% to 0.40%, for 10 μg/m3), NO2 (ER = 1.15%, 95% CI: 0.92% to 1.39%, for 10 μg/m3), SO2 (ER = 0.82%, 95% CI: 0.53% to 1.11%, for 10 μg/m3) and CO (ER = 3.47%, 95% CI: 2.70% to 4.26%, for 1 mg/m3). The joint associations (ER) with all air pollutants (for interquartile range width increases in each pollutant) estimated by the single-pollutant model was 8.73% and was 4.27% by the multipollutant model. The joint attributable fraction of ischemic stroke attributable to air pollutants based on the multipollutant model was 7%.

CONCLUSIONS

Short-term exposures to PM2.5, MDA8 O3, NO2, SO2, and CO were positively associated with increased risks of hospital admission for ischemic stroke. The joint associations of air pollutants with ischemic stroke might be overestimated using single-pollutant models. See video abstract at, http://links.lww.com/EDE/C8.

The establishment of Air Quality Health Index in China: A comparative analysis of methodological approaches

BACKGROUND

The Air Quality Index (AQI) has been criticized because it does not adequately account for the health effect of multi-pollutants. Although the developed Air Quality Health Index (AQHI) is a more effective communication tool, little is known about the best method to construct AQHI on long time and large spatial scales.

OBJECTIVES

To further evaluate the validity of existing approaches to the establishment of AQHI on both long time and larger spatial scales.

METHODS

By introducing 3 approaches addressing multi-pollutant exposures: cumulative risk index (CRI), supervised principal component analysis (SPCA), and Bayesian multi-pollutants weighted model (BMP), we constructed CRI-AQHI, SPCA-AQHI, BMP-AQHI and standard-AQHI on cardiovascular mortality in China from 2015 to 2019 at both the national and geographic regional levels. We further assessed the performance of the four methods in estimating the joint effect of multi-pollutants by simulations under various scenarios of pollution effect.

RESULTS

The results of national China showed that the BMP-AQHI improved the goodness of fit of the standard-AQHI by 108.24%, followed by CRI-AQHI (5.02%), and all AQHIs performed better than AQI, consistent with 6 geographic regional results. In addition, the simulation result showed that the BMP method provided stable and relatively accurate estimations of the short-term combined effect of exposure to multi-pollutants.

CONCLUSIONS

AQHI based on BMP could communicate the air pollution risk to the public more effectively than the current AQHI and AQI.

A Multipollutant Approach to Estimating Causal Effects of Air Pollution Mixtures on Overall Mortality in a Large, Prospective Cohort

BACKGROUND

Several studies have confirmed associations between air pollution and overall mortality, but it is unclear to what extent these associations reflect causal relationships. Moreover, few studies to our knowledge have accounted for complex mixtures of air pollution. In this study, we evaluate the causal effects of a mixture of air pollutants on overall mortality in a large, prospective cohort of Dutch individuals.

METHODS

We evaluated 86,882 individuals from the LIFEWORK study, assessing overall mortality between 2013 and 2017 through national registry linkage. We predicted outdoor concentration of five air pollutants (PM2.5, PM10, NO2, PM2.5 absorbance, and oxidative potential) with land-use regression. We used logistic regression and mixture modeling (weighted quantile sum and boosted regression tree models) to identify potential confounders, assess pollutants' relevance in the mixture-outcome association, and investigate interactions and nonlinearities. Based on these results, we built a multivariate generalized propensity score model to estimate the causal effects of pollutant mixtures.

RESULTS

Regression model results were influenced by multicollinearity. Weighted quantile sum and boosted regression tree models indicated that all components contributed to a positive linear association with the outcome, with PM2.5 being the most relevant contributor. In the multivariate propensity score model, PM2.5 (OR=1.18, 95% CI: 1.08-1.29) and PM10 (OR=1.02, 95% CI: 0.91-1.14) were associated with increased odds of mortality per interquartile range increase.

CONCLUSION

Using novel methods for causal inference and mixture modeling in a large prospective cohort, this study strengthened the causal interpretation of air pollution effects on overall mortality, emphasizing the primary role of PM2.5 within the pollutant mixture.

Improved morbidity-based air quality health index development using Bayesian multi-pollutant weighted model

BACKGROUND

The widely used Air Quality Index (AQI) has been criticized due to its inaccuracy, leading to the development of the air quality health index (AQHI), an improvement on the AQI. However, there is currently no consensus on the most appropriate construction strategy for the AQHI.

OBJECTIVES

In this study, we aimed to evaluate the utility of AQHIs constructed by different models and health outcomes, and determine a better strategy.

METHODS

Based on the daily time-series outpatient visits and hospital admissions from 299 hospitals (January 2016-December 2018), and mortality (January 2017-December 2019) in Guangzhou, China, we utilized cumulative risk index (CRI) method, Bayesian multi-pollutant weighted (BMW) model and standard method to construct AQHIs for different health outcomes. The effectiveness of AQHIs constructed by different strategies was evaluated by a two-stage validation analysis and examined their exposure-response relationships with the cause-specific morbidity and mortality.

RESULTS

Validation by different models showed that AQHI constructed with the BMW model (BMW-AQHI) had the strongest association with the health outcome either in the total population or subpopulation among air quality indexes, followed by AQHI constructed with the CRI method (CRI-AQHI), then common AQHI and AQI. Further validation by different health outcomes showed that AQHI constructed with the risk of outpatient visits generally exhibited the highest utility in presenting mortality and morbidity, followed by AQHI constructed with the risk of hospitalizations, then mortality-based AQHI and AQI. The contributions of NO₂ and O₃ to the final AQHI were prominent, while the contribution of SO₂ and PM_2.5 were relatively small.

CONCLUSIONS

The BMW model is likely to be more effective for AQHI construction than CRI and standard methods. Based on the BMW model, the AQHI constructed with the outpatient data may be more effective in presenting short-term health risks associated with the co-exposure to air pollutants than the mortality-based AQHI and existing AQIs.

Sex-difference in air pollution-related acute circulatory and respiratory mortality and hospitalization

BACKGROUND

Numerous studies have estimated adverse effects of short-term exposure to ambient air pollution on public health. Few have focused on sex-differences, and results have been inconsistent. The purpose of this study was three-fold: to identify sex-differences in air pollution-related health outcomes; to examine sex-differences by cause and season; and to examine time trends in sex-differences.

METHODS

Daily data were collected on circulatory- and respiratory-related mortality (for 29 years) and cause-specific hospitalization (for 17 years) with hourly concentrations of ozone (O3), nitrogen dioxide (NO2), and fine particulate matter (PM2.5). For hospitalization, more specific causes were examined: ischemic heart disease (IHD), other heart disease (OHD), cerebrovascular disease (CEV), chronic lower respiratory diseases (CLRD), and Influenza/Pneumonia (InfPn). Generalized Poisson models were applied to 24 Canadian cities, and the city-specific estimates were combined for nationwide estimates for each sex using Bayesian hierarchical models. Finally, sex-differences were tested statistically based on their interval estimates, considering the correlation between sex-specific national estimates.

RESULTS

Sex-differences were more frequently observed for hospitalization than mortality, respiratory than circulatory health outcomes, and warm than cold season. For hospitalization, males were at higher risk (M > F) for warm season (OHD and InfPn from O3; IHD from NO2; and InfPn from PM2.5), but F > M for cold season (CEV from O3 and OHD from NO2). For mortality, we found F > M only for circulatory diseases from ozone during the warm season. Among the above-mentioned sex-differences, three cases showed consistent time trends over the years: while M > F for OHD from O3 and IHD from NO2, F > M for OHD from NO2.

CONCLUSIONS

We found that sex-differences in effect of ambient air pollution varied over health outcome, cause, season and time. In particular, the consistent trends (either F > M or M > F) across 17 years provide stronger evidence of sex-differences in hospitalizations, and warrant investigation in other populations.

Prenatal PM2.5 Exposure in Relation to Maternal and Newborn Telomere Length at Delivery

Particulate matter with an aerodynamic diameter of 2.5 μm or less (PM_2.5) is a ubiquitous air pollutant that is increasingly threatening the health of adults and children worldwide. One health impact of elevated PM_2.5 exposure is alterations in telomere length (TL)-protective caps on chromosome ends that shorten with each cell division. Few analyses involve prenatal PM_2.5 exposure, and paired maternal and cord TL measurements. Here, we analyzed the association between average and trimester-specific prenatal PM_2.5 exposure, and maternal and newborn relative leukocyte TL measured at birth among 193 mothers and their newborns enrolled in a New-York-City-based birth cohort. Results indicated an overall negative relationship between prenatal PM_2.5 and maternal TL at delivery, with a significant association observed in the second trimester (β = -0.039, 95% CI: -0.074, -0.003). PM_2.5 exposure in trimester two was also inversely related to cord TL; however, this result did not reach statistical significance (β = -0.037, 95% CI: -0.114, 0.039), and no clear pattern emerged between PM_2.5 and cord TL across the different exposure periods. Our analysis contributes to a limited body of research on ambient air pollution and human telomeres, and emphasizes the need for continued investigation into how PM_2.5 exposure during pregnancy influences maternal and newborn health.

Using Bayesian time-stratified case-crossover models to examine associations between air pollution and "asthma seasons" in a low air pollution environment

Many areas of the United States have air pollution levels typically below Environmental Protection Agency (EPA) regulatory limits. Most health effects studies of air pollution use meteorological (e.g., warm/cool) or astronomical (e.g., solstice/equinox) definitions of seasons despite evidence suggesting temporally-misaligned intra-annual periods of relative asthma burden (i.e., “asthma seasons”). We introduce asthma seasons to elucidate whether air pollutants are associated with seasonal differences in asthma emergency department (ED) visits in a low air pollution environment. Within a Bayesian time-stratified case-crossover framework, we quantify seasonal associations between highly resolved estimates of six criteria air pollutants, two weather variables, and asthma ED visits among 66,092 children ages 5–19 living in South Carolina (SC) census tracts from 2005 to 2014. Results show that coarse particulates (particulate matter <10 μm and >2.5 μm: PM_10-2.5) and nitrogen oxides (NO_x) may contribute to asthma ED visits across years, but are particularly implicated in the highest-burden fall asthma season. Fine particulate matter (<2.5 μm: PM_2.5) is only associated in the lowest-burden summer asthma season. Relatively cool and dry conditions in the summer asthma season and increased temperatures in the spring and fall asthma seasons are associated with increased ED visit odds. Few significant associations in the medium-burden winter and medium-high-burden spring asthma seasons suggest other ED visit drivers (e.g., viral infections) for each, respectively. Across rural and urban areas characterized by generally low air pollution levels, there are acute health effects associated with particulate matter, but only in the summer and fall asthma seasons and differing by PM size.

Identifying impacts of air pollution on subacute asthma symptoms using digital medication sensors

BACKGROUND

Objective tracking of asthma medication use and exposure in real-time and space has not been feasible previously. Exposure assessments have typically been tied to residential locations, which ignore exposure within patterns of daily activities.

METHODS

We investigated the associations of exposure to multiple air pollutants, derived from nearest air quality monitors, with space-time asthma rescue inhaler use captured by digital sensors, in Jefferson County, Kentucky. A generalized linear mixed model, capable of accounting for repeated measures, over-dispersion and excessive zeros, was used in our analysis. A secondary analysis was done through the random forest machine learning technique.

RESULTS

The 1039 participants enrolled were 63.4% female, 77.3% adult (>18) and 46.8% White. Digital sensors monitored the time and location of over 286 980 asthma rescue medication uses and associated air pollution exposures over 193 697 patient-days, creating a rich spatiotemporal dataset of over 10 905 240 data elements. In the generalized linear mixed model, an interquartile range (IQR) increase in pollutant exposure was associated with a mean rescue medication use increase per person per day of 0.201 [95% confidence interval (CI): 0.189-0.214], 0.153 (95% CI: 0.136-0.171), 0.131 (95% CI: 0.115-0.147) and 0.113 (95% CI: 0.097-0.129), for sulphur dioxide (SO2), nitrogen dioxide (NO2), fine particulate matter (PM2.5) and ozone (O3), respectively. Similar effect sizes were identified with the random forest model. Time-lagged exposure effects of 0-3 days were observed.

CONCLUSIONS

Daily exposure to multiple pollutants was associated with increases in daily asthma rescue medication use for same day and lagged exposures up to 3 days. Associations were consistent when evaluated with the random forest modelling approach.

Association between Meniere's disease and air pollution in South Korea

Meniere's disease is thought to be a disorder of the inner ear function, affected by genetic and environmental factors. Several recent studies have shown that air pollution could affect middle and inner ear diseases. The purpose of this study was to investigate the relationship between the Meniere's disease occurrence and air pollution status in Korea. This study used a time-stratified case-crossover design. Hospital visit data by Meniere's disease were collected from the Korea National Health Insurance Service-National Sample Cohort (NHIS-NSC) database. Daily air pollution data for sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3), and particulate matter (PM10: ≤ 10 μm in diameter, and PM2.5: ≤ 2.5 μm in diameter) were collected from the National Ambient air quality Monitoring Information System (NAMIS) database. We used two-stage analysis to assess the association between degree of air pollution and the occurrence of Meniere's disease. In the first stage, region-specific analysis was conducted to estimate the odds ratios (ORs) of Meniere's disease risk associated with each air pollutant exposure by using conditional logistic regression for matched case-control sets in 16 regions. In the second stage, region-specific ORs from the first stage were combined and the pooled effect estimates were derived through fixed and random effect meta-analysis. Subgroup analysis was conducted for age, sex, seasonality, and urbanization of residence. In total, 29,646 (32.1% males and 67.9% females) Meniere's disease cases were identified from Korea NHIS-NSC database between 2008 and 2015. Overall, SO2, NO2, CO, and PM10 showed significant correlation with Meniere's disease risk at immediate lags, and weaker correlation at delayed lags, whereas O3 showed slightly negative correlation at the immediate lag (lag0) and PM2.5 did not show strong correlation (SO2: 1.04 [95% confidence interval: 1.01, 1.06]; NO2: 1.08 [1.06, 1.11]; CO: 1.04 [1.02, 1.06]; O3: 0.96 [0.93, 0.99]: statistically significant ORs at lag0 are listed). These positive and negative associations between Meniere's disease and each air pollutant were generally stronger in the age of 40-64, female, summer (June-August) season, and urban subgroups. Our results showed that hospital visits for Meniere's disease were associated with the measured concentrations of ambient air pollutants SO2, NO2, CO, and PM10. Further studies are required to confirm these associations and find their mechanisms.

The construction of the air quality health index (AQHI) and a validity comparison based on three different methods

The most common currently used air quality risk communication tool, the Air Quality Index (AQI), has been criticized. As a result, Canada proposed the Air Quality Health Index (AQHI) to communicate the health risks of multiple pollutants. However, the AQHI is calculated by directly summing the excess risks from single-pollutant models, which may overestimate the effects of the pollutants. To solve this problem, we introduced two methods for estimating the joint effects of multiple pollutants: the cumulative risk index (CRI) and supervised principal component analysis (SPCA). Based on three methods, i.e., the standard, CRI and SPCA methods, we constructed three types of AQHIs and compared their validity to select the best communication tool. Our results showed that compared with the AQI, all three AQHIs had a linear relationship with mortality. In addition, the CRI-AQHI had the best goodness of fit and captured the overall health risk of pollution mixtures most robustly among various cause-specific mortalities when identifying health risks. Our study indicated that the CRI-AQHI may have the potential to be a better alternative to the standard AQHI in communicating air pollution-related health risks to the public.

Model choice for estimating the association between exposure to chemical mixtures and health outcomes: A simulation study

Challenges arise in researching health effects associated with chemical mixtures. Several methods have recently been proposed for estimating the association between health outcomes and exposure to chemical mixtures, but a formal simulation study comparing broad-ranging methods is lacking. We select five recently developed methods and evaluate their performance in estimating the exposure-response function, identifying active mixture components, and identifying interactions in a simulation study. Bayesian kernel machine regression (BKMR) and nonparametric Bayes shrinkage (NPB) were top-performing methods in our simulation study. BKMR and NPB outperformed other contemporary methods and traditional linear models in estimating the exposure-response function and identifying active mixture components. BKMR and NPB produced similar results in a data analysis of the effects of multipollutant exposure on lung function in children with asthma.

Traffic-related organic and inorganic air pollution and risk of development of childhood asthma: A meta-analysis

The effect of early childhood exposure to traffic-related air pollution (TRAP) on the development of asthma remains unclear. The aim of this study was to clarify potential associations between TRAP (fine particulate matter, PM_2.5; nitrogen dioxide, NO₂; Benzene and total volatile organic pollutants, TVOCs) and childhood asthma by integrating the results from previous studies. Elsevier, LISTA (EBSCO) and Web of Science databases were searched for relevant studies. Adjusted odds ratio (OR) with corresponding 95% confidence interval (CI) for the association between traffic-related air pollutants and health effects were recovered from individual studies and summary effect estimates (meta-OR) were generated in Review Manager 5.3. Twenty-seven studies were included in the meta-analysis and the results showed that TRAP increased the risk of asthma among children: PM_2.5 (meta-OR = 1.07, 95% CI:1.00-1.13), NO₂ (meta-OR = 1.11, 95% CI:1.06-1.17), Benzene (meta-OR: 1.21, 95% CI:1.13-1.29) and TVOC (meta-OR:1.06, 95% CI: 1.03-1.10). Sensitivity analyses supported these findings. In addition, regional analysis showed that ORs of inorganic TRAP (PM_2.5 and NO₂) on the risk of childhood asthma were significantly higher in Asia than those in Europe and North America. Subsequent research should focus on the association between organic pollutants in TRAP and childhood asthma. Furthermore, the disentanglement between TRAP and other pollutant sources may be investigated in future studies.

Synergistic health effects of air pollution, temperature, and pollen exposure: a systematic review of epidemiological evidence

BACKGROUND

Exposure to heat, air pollution, and pollen are associated with health outcomes, including cardiovascular and respiratory disease. Studies assessing the health impacts of climate change have considered increased exposure to these risk factors separately, though they may be increasing simultaneously for some populations and may act synergistically on health. Our objective is to systematically review epidemiological evidence for interactive effects of multiple exposures to heat, air pollution, and pollen on human health.

METHODS

We systematically searched electronic literature databases (last search, April 29, 2019) for studies reporting quantitative measurements of associations between at least two of the exposures and mortality from any cause and cardiovascular and respiratory morbidity and mortality specifically. Following the Navigation Guide systematic review methodology, we evaluated the risk of bias of individual studies and the overall quality and strength of evidence.

RESULTS

We found 56 studies that met the inclusion criteria. Of these, six measured air pollution, heat, and pollen; 39 measured air pollution and heat; 10 measured air pollution and pollen; and one measured heat and pollen. Nearly all studies were at risk of bias from exposure assessment error. However, consistent exposure-response across studies led us to conclude that there is overall moderate quality and sufficient evidence for synergistic effects of heat and air pollution. We concluded that there is overall low quality and limited evidence for synergistic effects from simultaneous exposure to (1) air pollution, pollen, and heat; and (2) air pollution and pollen. With only one study, we were unable to assess the evidence for synergistic effects of heat and pollen.

CONCLUSIONS

If synergistic effects between heat and air pollution are confirmed with additional research, the health impacts from climate change-driven increases in air pollution and heat exposure may be larger than previously estimated in studies that consider these risk factors individually.

Acute Air Pollution Exposure and the Risk of Violent Behavior in the United States

BACKGROUND

Violence is a leading cause of death and an important public health threat, particularly among adolescents and young adults. However, the environmental causes of violent behavior are not well understood. Emerging evidence suggests exposure to air pollution may be associated with aggressive or impulsive reactions in people.

METHODS

We applied a two-stage hierarchical time-series model to estimate change in risk of violent and nonviolent criminal behavior associated with short-term air pollution in U.S. counties (2000-2013). We used daily monitoring data for ozone and fine particulate matter (PM2.5) from the Environmental Protection Agency and daily crime counts from the Federal Bureau of Investigation. We evaluated the exposure-response relation and assessed differences in risk by community characteristics of poverty, urbanicity, race, and age.

RESULTS

Our analysis spans 301 counties in 34 states, representing 86.1 million people and 721,674 days. Each 10 µg/m change in daily PM2.5 was associated with a 1.17% (95% confidence interval [CI] = 0.90, 1.43) and a 10 ppb change in ozone with a 0.59% (95% CI = 0.41, 0.78) relative risk increase (RRI) for violent crime. However, we observed no risk increase for nonviolent property crime due to PM2.5 (RRI: 0.11%; 95% CI = -0.09, 0.31) or ozone (RRI: -0.05%; 95% CI = -0.22, 0.12). Our results were robust across all community types, except rural regions. Exposure-response curves indicated increased violent crime risk at concentrations below regulatory standards.

CONCLUSIONS

Our results suggest that short-term changes in ambient air pollution may be associated with a greater risk of violent behavior, regardless of community type.

Improved risk communications with a Bayesian multipollutant Air Quality Health Index

Establishing an optimal indicator to communicate health risks of multiple air pollutants to public is much important. The Air Quality Health Index (AQHI) has been developed in many countries as a communication tool of multiple air pollutants related health risks. However, the current AQHI is based on the sum of the excess health risks which are typically derived from the single-pollutant statistical models. Such a strategy may overestimate the joint effect of multiple pollutants. We proposed an improved strategy to construct the AQHI based on a Bayesian multipollutant weighted model. Using this strategy, two improved indices - Bayesian multipollutant AQHI (BMP-AQHI) and Bayesian multipollutant AQHI with seasonal specificity (SBMP-AQHI) were calculated to present the multiple pollutants related health risks to the cardiovascular system based on data collected in Chengdu, China during 2013 to 2018. The two improved indices were compared to current Air Quality Index (AQI) and AQHI to evaluate the effectiveness of the improved indices in characterizing multipollutant health risks. The AQI risk classification suggested much smaller health risks than AQHIs. Among three AQHI types, the BMP-AQHI and SBMP-AQHI suggested slightly lower health risks to the cardiovascular system than the current AQHI. In the evaluation analysis, the SBMP-AQHI had the strongest association with the mortality of cardiovascular disease (CVD) (2.66%; 95%CI, 1.57%, 3.76%). In the subgroup analysis, an interquartile increase (IQR) of the SBMP-AQHI was associated with 3.21% (95%CI, 2.06%, 4.38%), 1.34% (95%CI, -0.13%, 2.82%), and 4.20% (95%CI, 2.59%, 5.84%) increases for CVD mortality in the elderly, male, and female subgroups, respectively. The study shows that the improved AQHIs can communicate the health information of multiple air pollutants more efficiently. The study also indicates the necessity to consider seasonal specificity in the construction of the AQHI.

Ambient air pollution and sickle cell disease-related emergency department visits in Atlanta, GA

BACKGROUND

Sickle cell disease (SCD) is an inherited, autosomal recessive blood disorder, among the most prevalent genetic diseases, globally. While the genetic and hemolytic dynamics of SCD have been well-characterized, the etiology of SCD-related pathophysiological processes is unclear. Although limited, observational evidence suggests that environmental factors, including urban air pollution, may play a role.

OBJECTIVES

We assessed whether daily ambient air pollution concentrations are associated with corresponding emergency department (ED) visit counts for acute SCD exacerbations in Atlanta, Georgia, during a 9-year (2005-2013) period. We also examined heterogeneity in response by age and sex.

METHODS

ED visit data were from 41 hospitals in the 20-county Atlanta, GA area. Associations between daily air pollution levels for 8 urban air pollutants and counts of SCD related ED visits were estimated using Poisson generalized linear models.

RESULTS

We observed positive associations between pollutants generally indicative of traffic emissions and corresponding SCD ED visits [e.g., rate ratio of 1.022 (95% CI: 1.002, 1.043) per interquartile range increase in carbon monoxide]. Age stratified analyses indicated stronger associations with traffic pollutants among children (0-18 years), as compared to older age strata. Associations involving other pollutants, including ozone and particulate matter and for models of individuals >18 years old, were consistent a null hypothesis of no association.

DISCUSSION

This analysis represents the first North American study to examine acute risk among individuals with SCD to urban air pollution and provide evidence of urban air pollution, especially from traffic sources, as a trigger for acute exacerbations. These findings are consistent with a hypothesis that biological pathways, including several centrally associated with oxidative stress, may contribute towards enhanced susceptibility in individuals with SCD.

Joint effect of multiple air pollutants on daily emergency department visits in Chengdu, China

Existing studies have typically investigated only the association between single pollutants and health outcomes. However, in the real world, people are exposed to multiple air pollutants simultaneously. The effect of air pollutants on emergency department (ED) visits has not been previously studied in the Sichuan Basin, which is one of the most polluted areas. We collected nonaccidental, respiratory and cardiovascular daily ED visits and daily concentrations of PM_2.5, PM_c, CO, SO₂, NO₂ and O₃ in Chengdu, China, from 2014 to 2016. A weighted variable for the combination of multiple air pollutants was constructed to assess the joint adverse health effects. Each air pollutant was assigned a health-related weight, which indicated the pollutant's relative contribution to the joint effect. The effects on specific subpopulations (males and females; 15-65 years old and >65 years old) were also examined. With an increase of 10 μg/m³ of the combined multiple air pollutants, the daily ED visits for nonaccidental, respiratory and cardiovascular causes increased by 0.96% (95% CI: 0.51%-1.39%), 1.19% (95% CI: 0.53%, 1.85%) and 4.36% (95% CI: 1.06%, 7.76%) at lag 1, respectively. Males presented more pronounced effects, except for cardiovascular disease, than females. Elderly individuals were found to be more sensitive than young individuals. For nonaccidental and respiratory diseases, the contributions of particulate matter (PM) were dominant among the air pollutants, whereas cardiovascular disease was mainly affected by gaseous air pollutants. The combination of multiple air pollutants was significantly associated with ED visits in the Sichuan Basin, China. The joint effect of the combination of multiple air pollutants was highest for cardiovascular disease at lag 1. The relative contributions of individual pollutants varied by disease and subpopulation. These findings suggest that under different pollution scenarios, preventive strategies should target those with different diseases and different subpopulations.

The hospitalization attributable burden of acute exacerbations of chronic obstructive pulmonary disease due to ambient air pollution in Shijiazhuang, China

Few studies have investigated the acute exacerbations of chronic obstructive pulmonary disease (AECOPD)-associated attributable burden under exposure to high levels of air pollution among Asians. Data on hospitalization for AECOPD, air pollution and meteorological factors from 1 January 2013 to 31 December 2016 were collected in Shijiazhuang, China. We used a Poisson generalized linear regression model combined with a distributed lag nonlinear model (DLNM) to evaluate the relative cumulative risk for a lag of 0-7 days and examined the potential effect modifications by age and sex via stratification analyses, controlling for long-term trends, seasonal patterns, meteorological factors, and other possible confounders. Then, we computed hospitalization percentages attributable to air pollutants. The AECOPD-associated relative cumulative risks for PM_2.5, PM₁₀, NO₂, SO₂, and CO for a lag of 0-7 days were significantly positively correlated with hospitalization. The associations were stronger in females and retired patients. The NO₂ Cum RR of AECOPD admission was the greatest. A 10μg/m³ increase in daily NO₂ concentration was associated with 6.7% and 5.7% increases in COPD hospitalizations in the retired and female groups, respectively. The results showed that 13%, 9.4%, 1.7%, 9.7%, and 8.8% of AECOPD hospitalizations were attributable to exposure to PM_2.5, PM₁₀, SO₂, NO₂, and CO, respectively. If the air pollutant concentration was reduced to the 24-h average grade II levels of NAAQS of China, the AECOPD attributable percentage for PM_2.5 and PM₁₀ would decrease by 80%. The air pollutants PM_2.5, PM₁₀, SO₂, NO₂, and CO were significantly relevant to AECOPD-associated hospitalization. The associations differed by individual characteristics. The retired and female populations were highly vulnerable.

Short-term effect of PM2.5 on pediatric asthma incidence in Shanghai, China

Recent epidemiological studies pointed out that air pollution has a significant impact on pediatric asthma. Shanghai is one of the biggest cities in China, and the short-term effect of atmospheric particulate matter on the incidence of pediatric asthma has become a hot topic. From January 1, 2009, to December 31, 2010, we used daily measurements of pollutant concentrations, daily weather data, and daily records of pediatric asthma hospital visits from local authorities to evaluate the short-term effect of air pollution on pediatric asthma incidence in Shanghai, China. We used a generalized additive model (GAM) in the analysis, and the controlled confounding factors include long-term trends, day-of-the-week effects, and weather elements. We divided the entire study group into different age-subgroups. In addition, we took a variety of lag models into consideration. The results showed a strong connection between concentrations of fine particulate matter (PM_2.5) and pediatric asthma hospital visits from 2009 to 2010 in Shanghai, China. For the entire study group, the greatest relative risk (RR) of PM_2.5 on pediatric asthma hospital visits was 1.060 on a lag of 4 days. As for the three different age-subgroups, the greatest RR of PM_2.5 on pediatric asthma hospital visits was 1.061 (at a lag of 5 days), 1.071 (at a lag of 4 days), and 1.052 (at a lag of 2 days), for the under-2-year-olds, 3-to-5-year-olds, and the 6-to-18-year-olds, respectively. The overall short-term effect of PM_2.5 on pediatric asthma hospital visits was relatively stronger in younger children. Within the year, we detected the strongest seasonal effect of PM_2.5 on pediatric asthma hospital visits in Summer. When adding other air pollutants in the analysis model, RR of PM_2.5 on pediatric asthma hospital visits would be increased.

The effect and burden modification of heating on adult asthma hospitalizations in Shijiazhuang: a time-series analysis

Background

Previous studies have found associations between asthma morbidity and air pollution especially in young population, (PLoS One 12:e0180522, 2017; Can J Public Health 103:4-8, 2012; Environ Health Perspect 118:449-57, 2010; Am J Respir Crit Care Med 182:307-16, 2010; J Allergy Clin Immunol 104:717-22, 2008; J Allergy Clin Immunol 104:717-22, 1999; Environ Res 111:1137-47, 2011) but most of them were conducted in areas with relatively low air pollutant level. Moreover, very few studies have investigated the effect and burden modification of heating season during which the ambient air pollution level is significantly different from that during non-heating season in north China.

Objectives

This study aimed to evaluate the effect and burden modification of heating on short-term associations between adult asthma hospitalizations and ambient air pollution in the north China city of Shijiazhuang.

Methods

Generalized additive models combined with penalized distributed lag nonlinear models were used to model associations between daily asthma hospitalizations and ambient air pollutants from 1 January 2013 to 16 December 2016 in Shijiazhuang city, adjusting for long-term and seasonality trend, day of week, statutory holiday, daily mean air pressure and temperature. Attributable risks were calculated to evaluate the burden of asthma hospitalizations due to air pollutants exposure. The effect of pollutants on hospitalization and the attributable measures were estimated in heating and non-heating season separately and the comparisons between the two seasons were conducted.

Results

All pollutants demonstrated positive and significant impacts on asthma hospitalizations both in heating season and non-heating season, except for O₃ in heating season where a negative association was observed. However, the differences of the pollutant-specific effects between the two seasons were not significant. SO₂ and NO₂ exposure were associated with the heaviest burden among all pollutants in heating season; meanwhile, PM₁₀ and PM_2.5 were associated with the heaviest burden in heating season.

Conclusions

In conclusion, we found evidence of the effect of ambient air pollutants on asthma hospitalizations in Shijiazhuang. The central heating period could modify the effects in terms of attributable risks. The disease burden modification of heating should be taken into consideration when planning intervention measures to reduce the risk of asthma hospitalization.

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.

Short-term joint effects of ambient air pollutants on emergency department visits for respiratory and circulatory diseases in Colombia, 2011-2014

BACKGROUND

We evaluated the short-term effect of mixtures of ambient air pollutants on respiratory and circulatory morbidity in four Colombian cities.

METHODS

Daily Emergency Department (ED) visit records for respiratory and circulatory selected diagnosis and daily concentrations for six criteria air pollutant were obtained in four of the five major cities in Colombia: Bucaramanga, Bogota, Cali, and Medellin during 2011-2014. Using conditional Poisson time series analysis with fixed effects, we assessed the effect of air pollutants on health outcomes using single-pollutant, two-pollutant and specific mixtures-of-pollutant models controlling for meteorology and time trends. The percentages of change in the rate of ED visits and their 95% confidence interval were estimated for the joint effect of pollutants.

RESULTS

In single-pollutant models increases in gases concentrations were associated with increases in ED visits for respiratory and circulatory diseases. The two-pollutant models for respiratory diseases showed that the effect of NO₂ alone (% change 2.86 95% CI 1.87-3.85) is higher than the joint effect of any of its combinations except for its combination with SO₂ (% change 3.05 95%CI 1.04-5.05). The two-pollutant models for circulatory diseases showed synergistic effects between NO₂ and PM_2.5 (% change 2.13 95%CI 0.001-4.26). Specific mixtures models showed that the mixture of "traffic-related pollutants" has the higher joint effect on circulatory morbidity and respiratory morbidity.

CONCLUSIONS

The results show the dominant effect of NO₂ in air pollution mixtures on respiratory and circulatory morbidity, and the synergistic effect of NO₂ and SO₂ in air pollution mixtures on respiratory morbidity.

A tensor product quasi-Poisson model for estimating health effects of multiple ambient pollutants on mortality

BACKGROUND

People are exposed to mixtures of highly correlated gaseous, liquid and solid pollutants. However, in previous studies, the assessment of air pollution effects was mainly based on single-pollutant models or was simultaneously included as multiple pollutants in a model. It is essential to develop appropriate methods to accurately estimate the health effects of multiple pollutants in the presence of a high correlation between pollutants.

METHODS

The flexible tensor product smooths of multiple pollutants was applied for the first time in a quasi-Poisson model to estimate the health effects of SO₂, NO₂ and PM₁₀ on daily all-cause deaths during 2005-2012 in Guangzhou, China. The results were compared with those from three other conventional models, including the single-pollutant model and the three-pollutant model with and without first-order interactions.

RESULTS

The tensor product model revealed a complex interaction among three pollutants and significant combined effects of PM₁₀, NO₂ and SO₂, which revealed a 2.53% (95%CI: 1.03-4.01%) increase in mortality associated with an interquartile-range (IQR) increase in the concentrations of all three pollutants. The combined effect estimated by the single-pollutant model was 5.63% (95% CI: 3.96-7.34%). Although the conventional three-pollutant models produced combined effect estimates (2.20, 95%CI, 1.18-3.23%; 2.78, 95%CI: 1.35-4.23%) similar to those of the tensor product model, they distorted the estimates and inflated the variances of the estimates when attributing the combined health effects to individual pollutants.

CONCLUSIONS

The single-pollutant model or conventional multi-pollutant model may yield misleading results in the presence of collinearity. The tensor product quasi-Poisson regression provides a novel approach to the assessment of the health impacts of multiple pollutants by flexibly fitting the interaction effects and avoiding the collinearity problem.

Short-term PM10 and emergency department admissions for selective cardiovascular and respiratory diseases in Beijing, China

BACKGROUND

Few studies have explored PM₁₀'s connection with specific respiratory and cardiovascular emergency department admissions (EDAs). This study aimed to examine the overall effects of PM₁₀ on EDAs for cardiovascular and respiratory diseases, including specifically, cerebrovascular events (CVE), ischemic heart disease (IHD), arrhythmia, heart failure (HF), upper respiratory tract infection (URTI), lower respiratory tract infection (LRTI), chronic obstructive pulmonary disease (COPD) and asthma.

METHODS

We collected daily data for EDAs from the 10 largest hospitals in Beijing, between January 2013 and December 2013 as well as daily measurements of PM₁₀ from 17 stations in Beijing. The generalized-additive model was utilized to evaluate the associations between daily PM₁₀ and cardio-pulmonary disease admissions. Differences in gender, age, and season groups were also examined by models. Relative risks (RR) with 95% confidence interval (CI) were calculated based on subtype, age, gender and seasonal groups. In all, there were approximately 56,212 cardiovascular and 92,464 respiratory emergency admissions presented in this study.

RESULTS

The largest estimate effects in EDAs of total cardiovascular disease, CVE, IHD, total respiratory diseases, URTI, LRTI and COPD were found for PM₁₀ at day 4 (accumulative) moving average, were 0.29% (95% CI:0.12%, 0.46%), 0.36% (95% CI:0.11%, 0.61%), 0.68% (95% CI:0.25%, 1.10%), 0.34% (95% CI:0.22%, 0.47%), 0.35% (95% CI:0.18%, 0.51%), 0.34% (95% CI:0.14%, 0.55%), 2.75% (95% CI:1.38%, 4.12%) respectively. In two-pollutant models and full-pollutant model modified confounding factors, the positive correlation remained unchanged. The elderly (age ≥ 65 years) and male subjects were more susceptible to specific respiratory diseases. PM₁₀'s impact on EDAs for HF was found higher during the hot season however, EDAs for COPD peaked during the cold season.

CONCLUSION

The study markedly informed that PM₁₀ pollution was strongly associated with EDAs for cardio-pulmonary diseases. The effects of PM₁₀ pollution on COPD and heart failure EDAs were clearly determined by seasonal-temperatures.

Exposure to bisphenol A, chlorophenols, benzophenones, and parabens in relation to reproductive hormones in healthy women: A chemical mixture approach

BACKGROUND

Little is known about the associations of bisphenol A, chlorophenols, benzophenones, and parabens with reproductive hormone levels in women. Our goal was to evaluate the associations between repeated measures of these chemicals and their mixtures with reproductive hormones in women.

METHODS

Longitudinal urine samples from healthy, premenopausal women (n = 143 with 3-5 urine samples each) were measured for bisphenol A, five chlorophenols (2,4-dichlorophenol (2,4-DCP), 2,5-dichlorophenol, 2,4,5-trichlorophenol, 2,4,6-trichlorophenol, triclosan), two ultraviolet (UV) filters (benzophenone-1, benzophenone-3), and eight parabens and their metabolites (benzyl, butyl, ethyl, heptyl, methyl, propyl, 4-hydroxybenzoic acid (4-HB), 3,4-dihydroxybenzoic acid (3,4-DHB)) over two menstrual cycles. Estradiol, progesterone, luteinizing hormone (LH), and follicle stimulating hormone (FSH) were measured in blood up to 8 times each menstrual cycle. Linear mixed models were used for both single and multi-chemical exposures estimated using principal component analysis. Four factors were identified including: paraben; paraben metabolites and BPA, phenols, and UV filters. Models were adjusted for creatinine, age, race, and body mass index and weighted with inverse probability of exposure weights to account for time varying confounding.

RESULTS

In single-chemical models, 3,4-DHB was associated with estradiol (0.06 (95% confidence interval (CI): 0.001, 0.12)), 2-4-DCP with increased progesterone 0.14 (0.06, 0.21) and decreased FSH -0.08 (-0.11, -0.04), and 4-HB was associated with increased FSH 0.07 (0.01, 0.13). In multi-chemical models, all factors were associated with increased progesterone (beta coefficient range: 0.15 for UV filter factor to 0.32 for paraben factor). The paraben factor and the paraben metabolite and BPA factor were associated with increased estradiol [0.21 (0.15, 0.28); 0.12 (0.07, 0.18)]. The phenol and UV filter factors were associated with decreased estradiol, FSH, and LH. The UV filter factor showed the strongest inverse association with estradiol -0.16 (-0.22, -0.10), FSH -0.12 (-0.17, -0.07), and LH -0.17 (-0.23, -0.10).

CONCLUSION

Mixtures of phenols were associated with changes in reproductive hormones. Such changes could contribute to adverse health in women but additional research is necessary.

Estimates of the Global Burden of Ambient [Formula: see text], Ozone, and [Formula: see text] on Asthma Incidence and Emergency Room Visits

BACKGROUND

Asthma is the most prevalent chronic respiratory disease worldwide, affecting 358 million people in 2015. Ambient air pollution exacerbates asthma among populations around the world and may also contribute to new-onset asthma.

OBJECTIVES

We aimed to estimate the number of asthma emergency room visits and new onset asthma cases globally attributable to fine particulate matter ([Formula: see text]), ozone, and nitrogen dioxide ([Formula: see text]) concentrations.

METHODS

We used epidemiological health impact functions combined with data describing population, baseline asthma incidence and prevalence, and pollutant concentrations. We constructed a new dataset of national and regional emergency room visit rates among people with asthma using published survey data.

RESULTS

We estimated that 9–23 million and 5–10 million annual asthma emergency room visits globally in 2015 could be attributable to ozone and [Formula: see text], respectively, representing 8–20% and 4–9% of the annual number of global visits, respectively. The range reflects the application of central risk estimates from different epidemiological meta-analyses. Anthropogenic emissions were responsible for [Formula: see text] and 73% of ozone and [Formula: see text] impacts, respectively. Remaining impacts were attributable to naturally occurring ozone precursor emissions (e.g., from vegetation, lightning) and [Formula: see text] (e.g., dust, sea salt), though several of these sources are also influenced by humans. The largest impacts were estimated in China and India.

CONCLUSIONS

These findings estimate the magnitude of the global asthma burden that could be avoided by reducing ambient air pollution. We also identified key uncertainties and data limitations to be addressed to enable refined estimation. https://doi.org/10.1289/EHP3766.

Assessing the cumulative health effect following short term exposure to multiple pollutants: An evaluation of methodological approaches using simulations and real data

BACKGROUND

Assessment of the cumulative effect of correlated exposures is an open methodological issue in environmental epidemiology. Most previous studies have applied regression models with interaction terms or dimension reduction methods. The combined effect of pollutants has been also evaluated through the use of exposure scores that incorporate weights based on the strength of the component-specific associations with health outcomes.

METHODS

We compared three approaches addressing multi-pollutant exposures in epidemiological models: main effects models, the adaptive least absolute shrinkage and selection operator (LASSO) and a weighted exposure score. We assessed the performance of the methods by simulations under various scenarios for the pollutants' correlations. We further applied these methods to time series data from Athens, Greece in 2007-12 to investigate the combined effect of short-term exposure to six regulated pollutants on all-cause and respiratory mortality.

RESULTS

The exposure score provided the least biased estimate under all correlation scenarios for both mortality outcomes. The adaptive LASSO performed well in the case of low and medium correlation between exposures while the main effect model resulted in severe bias. In the real data application, the cumulative effect estimate was similar between approaches for all-cause mortality ranging from 0.7% increase per interquartile range (IQR) (score) to 1.1% (main effects), while for respiratory mortality conclusions were contradictive and ranged from - 0.6% (adaptive LASSO) to 2.8% (score).

CONCLUSIONS

Τhe use of a weighted exposure score to address cumulative effects of correlated metrics may perform well under different exposure correlation and variability in the health outcomes.

Impacts of fire smoke plumes on regional air quality, 2006-2013

Increases in the severity and frequency of large fires necessitate improved understanding of the influence of smoke on air quality and public health. The objective of this study is to estimate the effect of smoke from fires across the continental U.S. on regional air quality over an extended period of time. We use 2006-2013 data on ozone (O₃), fine particulate matter (PM_2.5), and PM_2.5 constituents from environmental monitoring sites to characterize regional air quality and satellite imagery data to identify plumes. Unhealthy levels of O₃ and PM_2.5 were, respectively, 3.3 and 2.5 times more likely to occur on plume days than on clear days. With a two-stage approach, we estimated the effect of plumes on pollutants, controlling for season, temperature, and within-site and between-site variability. Plumes were associated with an average increase of 2.6 p.p.b. (2.5, 2.7) in O₃ and 2.9 µg/m³ (2.8, 3.0) in PM_2.5 nationwide, but the magnitude of effects varied by location. The largest impacts were observed across the southeast. High impacts on O₃ were also observed in densely populated urban areas at large distance from the fires throughout the southeast. Fire smoke substantially affects regional air quality and accounts for a disproportionate number of unhealthy days.

Ambient concentrations of particulate matter and hospitalization for depression in 26 Chinese cities: A case-crossover study

OBJECTIVE

Air pollution with high ambient concentrations of particulate matter (PM) has been frequently reported in China. However, no Chinese study has looked into the short-term effect of PM on hospitalization for depression. We used a time-stratified case-crossover design to identify possible links between ambient PM levels and hospital admissions for depression in 26 Chinese cities.

METHODS

Electronic hospitalization summary reports (January 1, 2014-December 31, 2015) were used to identify hospital admissions related to depression. Conditional logistic regression was applied to determine the association between PM levels and hospitalizations for depression, with stratification by sex, age, and comorbidities.

RESULTS

Both PM_2.5 and PM₁₀ levels were positively associated with the number of hospital admissions for depression. The strongest effect was observed on the day of exposure (lag day 0) for PM₁₀, with an interquartile range increase in PM₁₀ associated with a 3.55% (95% confidence interval: 1.69-5.45) increase in admissions for depression. For PM_2.5, the risks of hospitalization peaked on lag day 0 (2.92; 1.37-4.50) and lag day 5 (3.65; 2.09-5.24). The elderly (>65) were more sensitive to PM_2.5 exposure (9.23; 5.09-13.53) and PM₁₀ exposure (6.35; 3.31-9.49) on lag day 0, and patients with cardiovascular disease were likely to be hospitalized for depression following exposure to high levels of PM₁₀ (4.47; 2.13-6.85).

CONCLUSIONS

Short-term elevations in PM may increase the risk of hospitalization for depression, particularly in the elderly and in patients with cardiovascular disease.

Impacts of Regulations on Air Quality and Emergency Department Visits in the Atlanta Metropolitan Area, 1999-2013

INTRODUCTION

The United States and Western Europe have seen great improvements in air quality, presumably in response to various regulations curtailing emissions from the broad range of sources that have contributed to local, regional, and global pollution. Such regulations, and the ensuing controls, however, have not come without costs, which are estimated at tens of billions of dollars per year. These costs motivate accountability-related questions such as, to what extent do regulations lead to emissions changes? More important, to what degree have the regulations provided the expected human health benefits?

Here, the impacts of specific regulations on both electricity generating unit (EGU) and on-road mobile sources are examined through the classical accountability process laid out in the 2003 Health Effects Institute report linking regulations to emissions to air quality to health effects, with a focus on the 1999-2013 period. This analysis centers on regulatory actions in the southeastern United States and their effects on health outcomes in the 5-county Atlanta metropolitan area. The regulations examined are largely driven by the 1990 Clean Air Act Amendments (C). This work investigates regulatory actions and controls promulgated on EGUs: the Acid Rain Program (ARP), the NOx Budget Trading Program (NBP), and the Clean Air Interstate Rule (CAIR) - and mobile sources: Tier 2 Gasoline Vehicle Standards and the 2007 Heavy Duty Diesel Rule.

METHODS

Each step in the classic accountability process was addressed using one or more methods. Linking regulations to emissions was accomplished by identifying major federal regulations and the associated state regulations, along with analysis of individual facility emissions and control technologies and emissions modeling (e.g., using the U.S. Environmental Protection Agency's [U.S. EPA's] MOtor Vehicle Emissions Simulator [MOVES] mobile-source model). Regulators, including those from state environmental and transportation agencies, along with the public service commissions, play an important role in implementing federal rules and were involved along with other regional stakeholders in the study. We used trend analysis, air quality modeling, satellite data, and a ratio-of-ratios technique to investigate a critical current issue, a potential large bias in mobile-source oxides of nitrogen (NOx) emissions estimates.

The second link, emissions-air quality relationships, was addressed using both empirical analyses as well as chemical transport modeling employing the Community Multiscale Air Quality (CMAQ) model. Kolmogorov-Zurbenko filtering accounting for day of the year was used to separate the air quality signal into long-term, seasonal, weekday-holiday, and short-term meteorological signals. Regression modeling was then used to link emissions and meteorology to ambient concentrations for each of the species examined (ozone [O3], particulate matter ≤ 2.5 μm in aerodynamic diameter [PM2.5], nitrogen dioxide [NO2], sulfur dioxide [SO2], carbon monoxide [CO], sulfate [SO4-2], nitrate [NO3-], ammonium [NH4+], organic carbon [OC], and elemental carbon [EC]). CMAQ modeling was likewise used to link emissions changes to air quality changes, as well as to further establish the relative roles of meteorology versus emissions change impacts on air quality trends. CMAQ and empirical modeling were used to investigate aerosol acidity trends, employing the ISORROPIA II thermodynamic equilibrium model to calculate pH based on aerosol composition. The relationships between emissions and meteorology were then used to construct estimated counterfactual air quality time series of daily pollutant concentrations that would have occurred in the absence of the regulations. Uncertainties in counterfactual air quality were captured by the construction of 5,000 pollutant time series using a Monte Carlo sampling technique, accounting for uncertainties in emissions and model parameters.

Health impacts of the regulatory actions were assessed using data on cardiorespiratory emergency department (ED) visits, using patient-level data in the Atlanta area for the 1999-2013 period. Four outcome groups were chosen based on previous studies identifying associations with ambient air pollution: a combined respiratory disease (RD) category; the subgroup of RD presenting with asthma; a combined cardiovascular disease (CVD) category; and the subgroup of CVD presenting with congestive heart failure (CHF).

Models were fit to estimate the joint effects of multiple pollutants on ED visits in a time-series framework, using Poisson generalized linear models accounting for overdispersion, with a priori model formulations for temporal and meteorological covariates and lag structures. Several parameterizations were considered for the joint-effects models, including different sets of pollutants and models with nonlinear pollutant terms and first-order interactions among pollutants. Use of different periods for parameter estimates was assessed, as associations between pollutant levels and ED visits varied over the study period. A 7-pollutant, nonlinear model with pollutant interaction terms was chosen as the baseline model and fitted using pollutant and outcome data from 1999-2005 before regulations might have substantially changed the toxicity of pollutant mixtures. In separate analyses, these models were fitted using pollutant and outcome data from the entire 1999-2013 study period. Daily counterfactual time series of pollutant concentrations were then input into the health models, and the differences between the observed and counterfactual concentrations were used to estimate the impacts of the regulations on daily counts of ED visits. To account for the uncertainty in both the estimation of the counterfactual time series of ambient pollutant levels and the estimation of the health model parameters, we simulated 5,000 sets of parameter estimates using a multivariate normal distribution based on the observed variance-covariance matrix, allowing for uncertainty at each step of the chain of accountability. Sensitivity tests were conducted to assess the robustness of the results.

RESULTS

EGU NOx and SO2 emissions in the Southeast decreased by 82% and 83%, respectively, between 1999 and 2013, while mobile-source emissions controls led to estimated decreases in Atlanta-area pollutant emissions of between 61% and 93%, depending on pollutant. While EGU emissions were measured, mobile-source emissions were modeled. Our results are supportive of a potential high bias in mobile-source NOx and CO emissions estimates. Air quality benefits from regulatory actions have increased as programs have been fully implemented and have had varying impacts over different seasons. In a scenario that accounted for all emissions reductions across the period, observed Atlanta central monitoring site maximum daily 8-hour (MDA8h) O3 was estimated to have been reduced by controls in the summertime and increased in the wintertime, with a change in mean annual MDA8h O3 from 39.7 ppb (counterfactual) to 38.4 ppb (observed). PM2.5 reductions were observed year-round, with average 2013 values at 8.9 μg/m3 (observed) versus 19.1 μg/m3 (counterfactual). Empirical and CMAQ analyses found that long-term meteorological trends across the Southeast over the period examined played little role in the distribution of species concentrations, while emissions changes explained the decreases observed. Aerosol pH, which plays a key role in aerosol formation and dynamics and may have health implications, was typically very low (on the order of 1-2, but sometimes much lower), with little trend over time despite the stringent SO2 controls and SO42- reductions.

Using health models fit from 1999-2005, emissions reductions from all selected pollution-control policies led to an estimated 55,794 cardiorespiratory disease ED visits prevented (i.e., fewer observed ED visits than would have been expected under counterfactual scenarios) - 52,717 RD visits, of which 38,038 were for asthma, and 3,057 CVD visits, of which 2,104 were for CHF - among the residents of the 5-county area over the 1999-2013 period, an area with approximately 3.5 million people in 2013. During the final two years of the study (2012-2013), when pollution-control policies were most fully implemented and the associated benefits realized, these policies were estimated to prevent 5.9% of the RD ED visits that would have occurred in the absence of the policies (95% interval estimate: -0.4% to 12.3%); 16.5% of the asthma ED visits (95% interval estimate: 7.5% to 25.1%); 2.3% of the CVD ED visits (95% interval estimate: -1.8% to 6.2%); and -.6% of the CHF ED visits (95% interval estimate: 26.3% to 10.4%). Estimates of ED visits prevented were generally lower when using health models fit for the entire 1999-2013 study period.

Sensitivity analyses were conducted to show the impact of the choice of parameterization of the health models and to assess alternative definitions of the study area. When impacts were assessed for separate policy interventions, policies affecting emissions from EGUs, especially the ARP and the NBP, appeared to have had the greatest effect on prevention of RD and asthma ED visits.

CONCLUSIONS

This study demonstrates the effectiveness of regulations on improving air quality and health in the southeastern United States. It also demonstrates the complexities of accountability assessments as uncertainties are introduced in each step of the classic accountability process. While accounting for uncertainties in emissions, air quality-emissions relationships, and health models does lead to relatively large uncertainties in the estimated outcomes due to specific regulations, overall the benefits of regulations have been substantial.

Estimating Acute Cardiorespiratory Effects of Ambient Volatile Organic Compounds

BACKGROUND

The health effects of ambient volatile organic compounds (VOCs) have received less attention in epidemiologic studies than other commonly measured ambient pollutants. In this study, we estimated acute cardiorespiratory effects of ambient VOCs in an urban population.

METHODS

Daily concentrations of 89 VOCs were measured at a centrally-located ambient monitoring site in Atlanta and daily counts of emergency department visits for cardiovascular diseases and asthma in the five-county Atlanta area were obtained for the 1998-2008 period. To understand the health effects of the large number of species, we grouped these VOCs a priori by chemical structure and estimated the associations between VOC groups and daily counts of emergency department visits in a time-series framework using Poisson regression. We applied three analytic approaches to estimate the VOC group effects: an indicator pollutant approach, a joint effect analysis, and a random effect meta-analysis, each with different assumptions. We performed sensitivity analyses to evaluate copollutant confounding.

RESULTS

Hydrocarbon groups, particularly alkenes and alkynes, were associated with emergency department visits for cardiovascular diseases, while the ketone group was associated with emergency department visits for asthma.

CONCLUSIONS

The associations observed between emergency department visits for cardiovascular diseases and alkenes and alkynes may reflect the role of traffic exhaust, while the association between asthma visits and ketones may reflect the role of secondary organic compounds. The different patterns of associations we observed for cardiovascular diseases and asthma suggest different modes of action of these pollutants or the mixtures they represent.