Spatio-temporal ozone variation in a case-crossover analysis of childhood asthma hospital visits in New York City

Warm season ambient ozone and children's health in the USA

BACKGROUND

Over 120 million people in the USA live in areas with unsafe ozone (O3) levels. Studies among adults have linked exposure to worse lung function and higher risk of asthma and chronic obstructive pulmonary disease (COPD). However, few studies have examined the effects of O3 in children, and existing studies are limited in terms of their geographic scope or outcomes considered.

METHODS

We leveraged a dataset of encounters at 42 US children's hospitals from 2004-2015. We used a one-stage case-crossover design to quantify the association between daily maximum 8-hour O3 in the county in which the hospital is located and risk of emergency department (ED) visits for any cause and for respiratory disorders, asthma, respiratory infections, allergies and ear disorders.

RESULTS

Approximately 28 million visits were available during this period. Per 10 ppb increase, warm-season (May through September) O3 levels over the past three days were associated with higher risk of ED visits for all causes (risk ratio [RR]: 0.3% [95% confidence interval (CI): 0.2%, 0.4%]), allergies (4.1% [2.5%, 5.7%]), ear disorders (0.8% [0.3%, 1.3%]) and asthma (1.3% [0.8%, 1.9%]). When restricting to levels below the current regulatory standard (70 ppb), O3 was still associated with risk of ED visits for all-cause, allergies, ear disorders and asthma. Stratified analyses suggest that the risk of O3-related all-cause ED visits may be higher in older children.

CONCLUSIONS

Results from this national study extend prior research on the impacts of daily O3 on children's health and reinforce the presence of important adverse health impacts even at levels below the current regulatory standard in the USA.

Ozone and childhood respiratory health: A primer for US pediatric providers and a call for a more protective standard

Ground level ozone is a potent respiratory toxicant with decades of accumulated data demonstrating respiratory harms to children. Despite the ubiquity of ozone in the United States, impacting both urban and rural communities, the associated harms of exposure to this important air pollutant are often infrequently or inadequately covered during medical training including pulmonary specialization. Thus, many providers caring for children's respiratory health may have limited knowledge of the harms which may result in reduced discussion of ozone pollution during clinical encounters. Further, the current US air quality standard for ozone does not adequately protect children. In this nonsystematic review, we present basic background information for healthcare providers caring for children's respiratory health, review the US process for setting air quality standards, discuss the respiratory harms of ozone for healthy children and those with underlying respiratory disease, highlight the urgent need for a more protective ozone standard to adequately protect children's respiratory health, review impacts of climate change on ozone levels, and provide information for discussion in clinical encounters.

Performance Evaluation of the Meteorology and Air Quality Conditions From Multiscale WRF-CMAQ Simulations for the Long Island Sound Tropospheric Ozone Study (LISTOS)

The Long Island Sound (LIS) Tropospheric Ozone Study was a multi-agency collaborative field campaign conducted during the summer of 2018 to improve the understanding of ozone chemistry and transport from New York City to areas downstream, especially the LIS and adjacent Connecticut coastline. Measurements made during this campaign were leveraged to test and evaluate the coupled WRF-CMAQ model at 12 km, 4 and 1.33 km horizontal grid spacing. Special attention was placed on the model's representation of sea breeze circulations, low level jets, and boundary layer evolution. The evaluation suggests using higher resolutions resulted in improved surface meteorology statistics throughout the whole summer, with temperature biases seeing the biggest statistical improvements when using 1.33-km grid spacing, going from -0.12 to 0.08 K. Additionally, 4-km grid spacing provided the biggest advantage when simulating ozone over the region of interest, with biases being reduced from 2.40 to 0.57 to 0.37 ppbV with increased resolution. Case studies of two high ozone concentration events (July 10 and August 6) revealed that sound breezes and low-level jets had a critical role in transporting pollutant-rich, shallow marine air masses from the LIS inland over the Connecticut coast. Modifications were made to the representation of sea surface temperatures, which subsequently improved the simulation of surface ozone predictions.

Social Susceptibility to Multiple Air Pollutants in Cardiovascular Disease

INTRODUCTION

Cardiovascular disease (CVD) is the leading cause of death in the United States, and substantial research has linked ambient air pollution to elevated rates of CVD etiology and events. Much of this research identified increased effects of air pollution in lower socioeconomic position (SEP) communities, where pollution exposures are also often higher. The complex spatial confounding between air pollution and SEP makes it very challenging, however, to disentangle the impacts of these very different exposure types and to accurately assess their interactions. The specific causal components (i.e., specific social stressors) underlying this SEP-related susceptibility remain unknown, because there are myriad pathways through which poverty and/or lower-SEP conditions may influence pollution susceptibility - including diet, smoking, coexposures in the home and occupational environments, health behaviors, and healthcare access. Growing evidence suggests that a substantial portion of SEP-related susceptibility may be due to chronic psychosocial stress - given the known wide-ranging impacts of chronic stress on immune, endocrine, and metabolic function - and to a higher prevalence of unpredictable chronic stressors in many lower-SEP communities, including violence, job insecurity, and housing instability. As such, elucidating susceptibility to pollution in the etiology of CVD, and in the risk of CVD events, has been identified as a research priority. This interplay among social and environmental conditions may be particularly relevant for CVD, because pollution and chronic stress both impact inflammation, metabolic function, oxidative stress, hypertension, atherosclerosis, and other processes relevant to CVD etiology. Because pollution exposures are often spatially patterned by SEP, disentangling their effects - and quantifying any interplay - is especially challenging. Doing so, however, would help to improve our ability to identify and characterize susceptible populations and to improve our understanding of how community stressors may alter responses to multiple air pollutants. More clearly characterizing susceptible populations will improve our ability to design and target interventions more effectively (and cost-effectively) and may reveal greater benefits of pollution reduction in susceptible communities, strengthening cost-benefit and accountability analyses, ultimately reducing the disproportionate burden of CVD and reducing health disparities.

METHODS

In the current study, we aimed to quantify combined effects of multiple pollutants and stressor exposures on CVD events, using a number of unique datasets we have compiled and verified, including the following. 1. Poverty metrics, violent crime rates, a composite socioeconomic deprivation index (SDI), an index of racial and economic segregation, noise disturbance metrics, and three composite spatial factors produced from a factor analysis of 27 community stressors. All indicators have citywide coverage and were verified against individual reports of stress and stressor exposure, in citywide focus groups and surveys. 2. Spatial surfaces for multiple pollutants from the New York City (NYC) Community Air Survey (NYCCAS), which monitored multiple pollutants year-round at 150 sites and used land use regression (LUR) modeling to estimate fine-scale (100-m) intra-urban spatial variance in fine particles (PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3). 3. Daily data and time-trends derived from all U.S. Environmental Protection Agency (EPA) Air Quality System (AQS) monitors in NYC for 2005-2011, which we combined with NYCCAS surfaces to create residence- and day-specific spatiotemporal exposure estimates. 4. Complete data on in- and out-patient unscheduled CVD events presented in NYC hospitals for 2005-2011 (n = 1,113,185) from the New York State (NYS) Department of Health's Statewide Planning and Research Cooperative System (SPARCS). In the study, we quantified relationships between multiple pollutant exposures and both community CVD event rates and individual risk of CVD events in NYC and tested whether pollution-CVD associations varied by community SEP and social stressor exposures. We hypothesized (1) that greater chronic community-level SEP, stressor, and pollution exposures would be associated with higher community CVD rates; (2) that spatiotemporal variations in multiple pollutants would be associated with excess risk of CVD events; and (3) that pollution-CVD associations would be stronger in communities of lower SEP or higher stressor exposures.

RESULTS

To first understand the separate and combined associations with CVD for both stressors and pollutants measured at the same spatial and temporal scale of resolution, we used ecological cross-sectional models to examine spatial relationships between multiple chronic pollutant and stressor exposures and age-adjusted community CVD rates. Using census-tract-level annual averages (n = 2,167), we compared associations with CVD rates for multiple pollutant concentrations and social stressors. We found that associations with community CVD rates were consistently stronger for social stressors than for pollutants, in terms of both magnitude and significance. We note, however, that this result may be driven by the relatively greater variation (on a proportional basis) for stressors than for pollutants in NYC. We also tested effect modification of pollutant-CVD associations by each social stressor and found evidence of stronger associations for NO2, PM2.5, and wintertime SO2 with CVD rates, particularly across quintiles of increasing community violence or assault rates (P trend < 0.0001). To examine individual-level associations between spatiotemporal exposures to multiple pollutants and the risk of CVD events, across multiple lag days, we examined the combined effects of multiple pollutant exposures, using spatiotemporal (day- and residence-specific) pollution exposure estimates and hospital data on individual CVD events in case-crossover models, which inherently adjust for nontime-varying individual confounders (e.g., sex and race) and comorbidities. We found consistent significant relationships only for same-day pollutant exposures and the risk of CVD events, suggesting very acute impacts of pollution on CVD risk. Associations with CVD were positive for NO2, PM2.5, and SO2, as hypothesized, and we found inverse associations for O3 (a secondary pollutant chemically decreased ["scavenged"] by fresh emissions that, in NYC, displays spatial and temporal patterns opposite those of NO2). Finally, to test effect modification by chronic community social stressors on the relationships between spatiotemporal pollution measures and the risk of CVD events, we used individual-level case-crossover models, adding interaction terms with categorical versions of each social stressor. We found that associations between NO2 and the risk of CVD events were significantly elevated only in communities with the highest exposures to social stressors (i.e., in the highest quintiles of poverty, socioeconomic deprivation, violence, or assault). The largest positive associations for PM2.5 and winter SO2 were generally found in the highest-stressor communities but were not significant in any quintile. We again found inverse associations for O3, which were likewise stronger for individuals living in communities with greater stressor exposures.

CONCLUSIONS

In ecological models, we found stronger relationships with community CVD rates for social stressors than for pollutant exposures. In case-crossover analyses, higher exposures to NO2, PM2.5, and SO2 were associated with greater excess risk of CVD events but only on the case day (there were no consistent significant lagged-day effects). In effect-modification analyses at both the community and individual level, we found evidence of stronger pollution-CVD associations in communities with higher stressor exposures. Given substantial spatial confounding across multiple social stressors, further research is needed to disentangle these effects in order to identify the predominant social stressors driving this observed differential susceptibility.

Temporal variability in the impacts of particulate matter on crop yields on the North China Plain

The North China Plain (NCP) is a major agricultural region, producing 45% of China's maize. It is also vital to the Chinese economy, encompassing the Beijing-Tianjin-Hebei megacity region. Anthropogenic factors increasingly impact crop yields on the NCP, and globally. Particulate matter (PM) pollution is a significant problem in this region, where annual average PM concentrations over three times the Chinese national air quality standard were recorded for the Beijing-Tianjin-Hebei megacity region between 2013 and 18. PM absorbs light, reducing total shortwave radiation (SW), thereby limiting plant productivity. However, PM also scatters incoming SW, increasing the diffuse fraction, which has been shown to increase growth and biomass assimilation. The Joint UK Land Environment Simulator (JULES) crop model was used to assess the net impact of these competing changes in light on NCP maize yields. In contrast to some previous analyses, we find that PM-associated decreases in SW outweigh any positive impact on yield from an increasing proportion of diffuse radiation. Furthermore, carbon allocation to different portions of the growing cropchanges during the development cycle. We find significant differences between the effect on final yield of identical changes to diffuse fraction and total SW occurring during different development stages. The greatest simulated yield gains from increased SW and reduced diffuse fraction, consistent with reductions in PM, are observed during the early reproductive stage of development (July-August), when the simulated gain of yield is as much as 12.9% more than in other periods. To further assess the impact of PM-linked changes in SW and diffuse fraction on NCP crop yields, radiation profiles from different city regions were then applied across the NCP. The changes in SW associated with these city regions could increase maize yields across China by ~8 Mt. This would completely offset China's annual maize imports, increasing both national and global food security.

Effects of ambient air pollution on childhood asthma exacerbation in the Philadelphia metropolitan Region, 2011-2014

Fine particulate matter (PM_2.5) and ozone (O₃) air pollutants are known risk factors for asthma exacerbation. We studied the association of these air pollutants with pediatric asthma exacerbation in the Philadelphia metropolitan region, and evaluated potential effect modification by children's characteristics (e.g., race/ethnicity, atopic conditions) and environmental factors (e.g., neighborhood tree canopy, meteorological factors, aeroallergens). We conducted a time-stratified case-crossover study of 54,632 pediatric (age ≤18 years) asthma exacerbation cases occurring from 2011 to 2014, identified through electronic health records (EHR) of the Children's Hospital of Philadelphia (CHOP) health system. We applied conditional logistic regression to estimate associations between air pollution and asthma exacerbation, using daily census-tract level pollutant concentrations estimated from the EPA Fused Air Quality Surface Using Downscaling (FAQSD) files. The associations were estimated within warm (Apr-Sep) and cold (Oct-Mar) months for unlagged exposure and for cumulative effects up to 5 days after exposure, with adjustment for temperature, relative humidity, and holidays. We found small increases in odds of asthma exacerbation with higher pollutant concentrations, with positive associations (OR, comparing concentrations of 75th to 25th percentile) observed for PM_2.5 during both warm (1.03, 95% CI: 0.98-1.08) and cold months (1.05, 95% CI: 1.02-1.07), and for O₃ during cold months (1.08, 95% CI: 1.02-1.14). The exposure-response relationship with PM_2.5 during the cold months was essentially linear, whereas thresholds of effect were observed for the other associations at low-medium pollutant concentrations. Results were robust to multi-pollutant modeling and adjustment for additional covariates. We found no effect modification by most children's characteristics, while effect sizes were higher on days with detected tree and grass pollens during warm months. Our results suggest that even small decreases in pollutant concentrations could potentially reduce risk of childhood asthma exacerbation - an important finding, given the high burden of childhood asthma and known disparities in asthma control.

Air Pollution and Risk of Placental Abruption: A Study of Births in New York City, 2008-2014

We evaluated the associations of exposure to fine particulate matter (particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) at concentrations of <12 μg/m3, 12-14 μg/m3, and ≥15 μg/m3) and nitrogen dioxide (at concentrations of <26 parts per billion (ppb), 26-29 ppb, and ≥30 ppb) with placental abruption in a prospective cohort study of 685,908 pregnancies in New York, New York (2008-2014). In copollutant analyses, these associations were examined using distributed-lag nonlinear models based on Cox models. The prevalence of abruption was 0.9% (n = 6,025). Compared with a PM2.5 concentration less than 12 μg/m3, women exposed to PM2.5 levels of ≥15 μg/m3 in the third trimester had a higher rate of abruption (hazard ratio (HR) = 1.68, 95% confidence interval (CI): 1.41, 2.00). Compared with a nitrogen dioxide concentration less than 26 ppb, women exposed to nitrogen dioxide levels of 26-29 ppb (HR = 1.11, 95% CI: 1.02, 1.20) and ≥30 ppb (HR = 1.06, 95% CI: 0.96, 1.24) in the first trimester had higher rates of abruption. Compared with both PM2.5 and nitrogen dioxide levels less than the 95th percentile in the third trimester, rates of abruption were increased with both PM2.5 and nitrogen dioxide ≥95th percentile (HR = 1.44, 95% CI: 1.15, 1.80) and PM2.5 ≥95th percentile and nitrogen dioxide <95th percentile (HR = 1.43 95% CI: 1.23, 1.66). Increased levels of PM2.5 exposure in the third trimester and nitrogen dioxide exposure in the first trimester are associated with elevated rates of placental abruption, suggesting that these exposures may be important triggers of premature placental separation through different pathways.

Association between air pollutants and outpatient and emergency hospital visits for childhood asthma in Shenyang city of China

Effects of air pollution on asthma vary in different study areas, and long-term time series research on the effects of air pollution on asthma outpatients and emergency hospital visits has not been conducted in Northeast China. We assessed the impact of air pollutants on the risk of asthma outpatients and emergency hospital visits in Shenyang, China. A distributed lag non-linear model with a Poisson regression was used to assess the short-term effects of air pollutants on asthma outpatient and emergency hospital visits between January 1, 2013 and December 31, 2017. Confounding factors were adjusted using natural cubic splines. Ozone (O₃), carbon monoxide (CO), and suspended particulates < 10 μm in aerodynamic diameter (PM₁₀) were positively associated with the number of asthma hospital visits. The largest cumulative effects of O₃, CO, and PM₁₀ on hospital visits were on lag day 2 (RR = 1.163, 95% CI 1.051-1.287) for 0-5-year-old childhood asthma, on lag day 3 (RR = 1.386, 95% CI 1.136-1.69) for asthma in winter, and on lag day 10 (RR = 1.148, 95% CI 0.942-1.399) for female asthma, respectively. The cumulative effect of air pollution represented by the air quality index (AQI) was largest on lag day 10 for 0-5-year-old childhood asthma with an increase of 28.6% (95% CI 6.5-55.4) hospital visits every IQR increment of the AQI. CO, O₃, and PM₁₀ were the main air pollutants in Shenyang city. Children with bronchitis asthma were more vulnerable to air pollution during the cold season.

Association of Fine Particulate Matter and Risk of Stroke in Patients With Atrial Fibrillation

IMPORTANCE

Air pollution is associated with cardiovascular outcomes. Specifically, fine particulate matter measuring 2.5 μm or less (PM2.5) is associated with thrombosis, stroke, and myocardial infarction. Few studies have examined particulate matter and stroke risk in individuals with atrial fibrillation (AF).

OBJECTIVE

To assess the association of residential-level pollution exposure in 1 year and ischemic stroke in individuals with AF.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study included 31 414 individuals with AF from a large regional health care system in an area with historically high industrial pollution. All participants had valid residential addresses for geocoding and ascertainment of neighborhood-level income and educational level. Participants were studied from January 1, 2007, through September 30, 2015, with prospective follow-up through December 1, 2017. Data analysis was performed from March 14, 2018, to October 9, 2019.

EXPOSURES

Exposure to PM2.5 ascertained using geocoding of addresses and fine-scale air pollution exposure surfaces derived from a spatial saturation monitoring campaign and land-use regression modeling. Exposure to PM2.5 was estimated annually across the study period at the residence level.

MAIN OUTCOMES AND MEASURES

Multivariable-adjusted stroke risk by quartile of residence-level and annual PM2.5 exposure.

RESULTS

The cohort included 31 414 individuals (15 813 [50.3%] female; mean [SD] age, 74.4 [13.5] years), with a median follow-up of 3.5 years (interquartile range, 1.6-5.8 years). The mean (SD) annual PM2.5 exposure was 10.6 (0.7) μg/m3. A 1-SD increase in PM2.5 was associated with a greater risk of stroke after both adjustment for demographic and clinical variables (hazard ratio [HR], 1.08; 95% CI, 1.03-1.14) and multivariable adjustment that included neighborhood-level income and educational level (HR, 1.07; 95% CI, 1.00-1.14). The highest quartile of PM2.5 exposure had an increased risk of stroke relative to the first quartile (HR, 1.36; 95% CI, 1.18-1.58). After adjustment for clinical covariates, income, and educational level, risk of stroke remained greater for the highest quartile of exposure relative to the first quartile (HR, 1.21; 95% CI, 1.01-1.45).

CONCLUSIONS AND RELEVANCE

This large cohort study of individuals with AF identified associations between PM2.5 and risk of ischemic stroke. The results suggest an association between fine particulate air pollution and cardiovascular disease and outcomes.

Geocoding Error, Spatial Uncertainty, and Implications for Exposure Assessment and Environmental Epidemiology

Although environmental epidemiology studies often rely on geocoding procedures in the process of assigning spatial exposure estimates, geocoding methods are not commonly reported, nor are consequent errors in exposure assignment explored. Geocoding methods differ in accuracy, however, and, given the increasing refinement of available exposure models for air pollution and other exposures, geocoding error may account for an increasingly larger proportion of exposure misclassification. We used residential addresses from a reasonably large, dense dataset of asthma emergency department visits from all New York City hospitals (n = 21,183; 26.9 addresses/km²), and geocoded each using three methods (Address Point, Street Segment, Parcel Centroid). We compared missingness and spatial patterning therein, quantified distance and directional errors, and quantified impacts on pollution exposure estimates and assignment to Census areas for sociodemographic characterization. Parcel Centroids had the highest overall missingness rate (38.1%, Address Point = 9.6%, Street Segment = 6.1%), and spatial clustering in missingness was significant for all methods, though its spatial patterns differed. Street Segment geocodes had the largest mean distance error (µ = 29.2 (SD = 26.2) m; vs. µ = 15.9 (SD = 17.7) m for Parcel Centroids), and the strongest spatial patterns therein. We found substantial over- and under-estimation of pollution exposures, with greater error for higher pollutant concentrations, but minimal impact on Census area assignment. Finally, we developed surfaces of spatial patterns in errors in order to identify locations in the study area where exposures may be over-/under-estimated. Our observations provide insights towards refining geocoding methods for epidemiology, and suggest methods for quantifying and interpreting geocoding error with respect to exposure misclassification, towards understanding potential impacts on health effect estimates.

A geographic identifier assignment algorithm with Bayesian variable selection to identify neighborhood factors associated with emergency department visit disparities for asthma

BACKGROUND

Ecologic health studies often rely on outcomes from health service utilization data that are limited by relatively coarse spatial resolutions and missing geographic information, particularly neighborhood level identifiers. When fine-scale geographic data are missing, the ramifications and strategies for addressing them are not well researched or developed. This study illustrates a novel spatio-temporal framework that combines a geographic identifier assignment (i.e., geographic imputation) algorithm with predictive Bayesian variable selection to identify neighborhood factors associated with disparities in emergency department (ED) visits for asthma.

METHODS

ED visit records with missing fine-scale spatial identifiers (~ 20%) were geocoded using information from known, coarser, misaligned spatial units using an innovative geographic identifier assignment algorithm. We then employed systematic variable selection in a spatio-temporal Bayesian hierarchical model (BHM) predictive framework within the NIMBLE package in R. Our novel methodology is illustrated in an ecologic case study aimed at identifying neighborhood-level predictors of asthma ED visits in South Carolina, United States, from 1999 to 2015. The health outcome was annual ED visit counts in small areas (i.e., census tracts) with primary diagnoses of asthma (ICD9 codes 493.XX) among children ages 5 to 19 years.

RESULTS

We maintained 96% of ED visit records for this analysis. When the algorithm used areal proportions as probabilities for assignment, which addressed differential missingness of census tract identifiers in rural areas, variable selection consistently identified significant neighborhood-level predictors of asthma ED visit risk including pharmacy proximity, average household size, and carbon monoxide interactions. Contrasted with common solutions of removing geographically incomplete records or scaling up analyses, our methodology identified critical differences in parameters estimated, predictors selected, and inferences. We posit that the differences were attributable to improved data resolution, resulting in greater power and less bias. Importantly, without this methodology, we would have inaccurately identified predictors of risk for asthma ED visits, particularly in rural areas.

CONCLUSIONS

Our approach innovatively addressed several issues in ecologic health studies, including missing small-area geographic information, multiple correlated neighborhood covariates, and multiscale unmeasured confounding factors. Our methodology could be widely applied to other small-area studies, useful to a range of researchers throughout the world.

Putting Co-Exposures on Equal Footing: An Ecological Analysis of Same-Scale Measures of Air Pollution and Social Factors on Cardiovascular Disease in New York City

Epidemiologic evidence consistently links urban air pollution exposures to health, even after adjustment for potential spatial confounding by socioeconomic position (SEP), given concerns that air pollution sources may be clustered in and around lower-SEP communities. SEP, however, is often measured with less spatial and temporal resolution than are air pollution exposures (i.e., census-tract socio-demographics vs. fine-scale spatio-temporal air pollution models). Although many questions remain regarding the most appropriate, meaningful scales for the measurement and evaluation of each type of exposure, we aimed to compare associations for multiple air pollutants and social factors against cardiovascular disease (CVD) event rates, with each exposure measured at equal spatial and temporal resolution. We found that, in multivariable census-tract-level models including both types of exposures, most pollutant-CVD associations were non-significant, while most social factors retained significance. Similarly, the magnitude of association was higher for an IQR-range difference in the social factors than in pollutant concentrations. We found that when offered equal spatial and temporal resolution, CVD was more strongly associated with social factors than with air pollutant exposures in census-tract-level analyses in New York City.

Violent crime and socioeconomic deprivation in shaping asthma-related pollution susceptibility: a case-crossover design

Background

The objective of this study was to quantify and compare the relative influence of community violent crime and socioeconomic deprivation in modifying associations between ozone and emergency department (ED) visits for asthma among children.

Methods

We used a spatiotemporal case-crossover analysis for all New York City EDs for the months May–September from 2005 to 2011 from a statewide administrative ED dataset. The data included 11 719 asthmatic children aged 5–18 years, and the main outcome measure was percentage of excess risk of asthma ED visit based on Cox regression analysis.

Results

Stronger ozone–asthma associations were observed for both elevated crime and deprivation (eg, on lag day 2, we found 20.0% (95% CI 10.2% to 30.6 %) and 21.0% (10.5% to 32.5%) increased risk per 10 ppb ozone, for communities in the highest vs lowest quartiles of violent crime and deprivation, respectively). However, in varied models accounting for both modifiers, only violence retained significance.

Conclusions

The results suggest stronger spatiotemporal ozone–asthma associations in communities of higher violent crime or deprivation. Notably, violence was the more consistent and significant modifier, potentially mediating a substantial portion of socioeconomic position–related susceptibility.

Air pollution, urgent asthma medical visits and the modifying effect of neighborhood asthma prevalence

BACKGROUND

Social and environmental stressors may modify associations between environmental pollutants and asthma symptoms. We examined if neighborhood asthma prevalence (higher: HAPN vs. lower: LAPN), a surrogate for underlying risk factors for asthma, modified the relationship between pollutants and urgent asthma visits.

METHODS

Through zip code, home addresses were linked to New York City Community Air Survey's land use regression model for street-level, annual average nitrogen dioxide (NO2), particulate matter (PM2.5), elemental carbon (EC), summer average ozone (O3), winter average sulfur dioxide (SO2) concentrations. Poisson regression models were fit to estimate the association (prevalence ratio, PR) between pollutant exposures and seeking urgent asthma care.

RESULTS

All pollutants, except O3 were higher in HAPN than LAPN (P < 0.01). Neighborhood asthma prevalence modified the relationship between pollutants and urgent asthma (P-interaction < 0.01, for NO2 and SO3). Associations between pollutants and urgent asthma were observed only in LAPN (NO2: PR = 1.38, P = 0.01; SO3: PR = 1.85, P = 0.04). No association was observed between pollutants and urgent asthma among children in HAPN (P > 0.05).

CONCLUSIONS

Relationships between modeled street-level pollutants and urgent asthma were stronger in LAPN compared to HAPN. Social stressors that may be more prevalent in HAPN than LAPN, could play a greater role in asthma exacerbations in HAPN vs. pollutant exposure alone.

The Use of Geographic Data to Improve Asthma Care Delivery and Population Health

The authors examine uses of geographic data to improve asthma care delivery and population health and describe potential practice changes and areas for future research.

Air pollutants and asthma patient visits: Indication of source influence

BACKGROUND

Sources of air pollutants are significant factors for adverse health effect. Few current studies explored the linking of sources influence and ambient pollutants to asthma patient visits in Shanghai, China.

OBJECTIVES

This study explored the associations between short-term exposures to ambient pollutants and asthma morbidity with terrestrial and marine source influence in Shanghai.

METHODS

Generalized additive model (GAM) was used to explore the association of daily patient visits and ambient pollutants. These analyses were calculated in R statistical software in mgcv package. PSCF modeling was used to locate potential source areas contributing to the concentrations of pollutants.

RESULTS

We found that per IQR of PM_2.5, PM₁₀, NO₂, SO₂, O₃ and CO in terrestrial source were associated with an increase of 6.63% (95% CI: -0.27% to 14%), 6.48% (95% CI: 0.06% to 13.3%), 1.68% (95% CI: -2.68% to 6.24%), 2.81% (95% CI: -1.42% to 7.22%), -0.60% (95% CI: -5.94% to 5.04%) and 16.6% (95% CI: 8.68% to 25.2%), respectively in asthma patient visits. Per IQR of PM_2.5, PM₁₀, NO₂, SO₂, O₃ and CO in marine source were associated with an increase of 5.34% (95% CI: 0.42% to 10.5%), 3.84% (95% CI: 0.08% to 7.74%), 3.21% (95% CI: -0.92% to 7.52%), 2.58% (95% CI: -1.02% to 6.30%), 1.42% (95% CI: -3.10% to 6.15%) and 8.81% (95% CI: 2.56% to 15.4%). The PSCF show all of the pollutants except O₃ mainly come from terrestrial during observation. We also found that all of the pollutants except NO₂ displayed the highest effect in the spring for relative risk of asthma morbidity.

CONCLUSIONS

Ambient air pollutants that cause an increase in asthma patient visits, such as PM_2.5, PM₁₀, NO₂, SO₂ and CO are mainly produced from terrestrial sources, while O₃ is primarily from marine sources. The association of ambient pollutants and asthma patient visits is closely related with seasons, especially with spring. PM_2.5 and CO are major air pollutants increasing the relative risk of asthma patient visits in Shanghai.

Ozone-Related Respiratory Morbidity in a Low-Pollution Region

OBJECTIVE

We evaluated the effects of ozone on respiratory-related hospital admissions in three counties in Washington State from 1990 to 2006. We further examined vulnerability to ozone by key demographic factors.

METHOD

Using linked hospital admission and ambient monitoring data, we estimated the age-, sex-, and health insurance-stratified associations between ozone (0 to 3 days' lag) and respiratory-related hospital admissions in King, Spokane, and Clark County, Washington.

RESULTS

The adjusted relative risk (RR) for a 10 ppb increase in ozone at 3 days' lag was 1.04 (95% confidence interval [CI]: 1.02, 1.07) for Clark County, 1.03 (95% CI: 1.01, 1.05) for Spokane County, and 1.02 (95% CI: 1.01, 1.03) for King County. There was consistent evidence of effect modification by age.

CONCLUSION

Ozone at levels below federal standards contributes to respiratory morbidity among high-risk groups in Washington.

Application of a Time-Stratified Case-Crossover Design to Explore the Effects of Air Pollution and Season on Childhood Asthma Hospitalization in Cities of Differing Urban Patterns: Big Data Analytics of Government Open Data

Few studies have assessed the lagged effects of levels of different urban city air pollutants and seasons on asthma hospitalization in children. This study used big data analysis to explore the effects of daily changes in air pollution and season on childhood asthma hospitalization from 2001 to 2010 in Taipei and Kaohsiung City, Taiwan. A time-stratified case-crossover study and conditional logistic regression analysis were employed to identify associations between the risk of hospitalization due to asthma in children and the levels of air pollutants (PM_2.5, PM₁₀, O₃, SO₂, and NO₂) in the days preceding hospitalization. During the study period, 2900 children in Taipei and 1337 in Kaohsiung aged ≤15 years were hospitalized due to asthma for the first time. The results indicated that the levels of air pollutants were significantly associated with the risk of asthma hospitalization in children, and seasonal effects were observed. High levels of air pollution in Kaohsiung had greater effects than in Taipei after adjusting for seasonal variation. The most important factor was O₃ in spring in Taipei. In children aged 0-6 years, asthma was associated with O₃ in Taipei and SO₂ in Kaohsiung, after controlling for the daily mean temperature and relative humidity.

City housing atmospheric pollutant impact on emergency visit for asthma: A classification and regression tree approach

INTRODUCTION

Particulate matter, nitrogen dioxide (NO₂) and ozone are recognized as the three pollutants that most significantly affect human health. Asthma is a multifactorial disease. However, the place of residence has rarely been investigated. We compared the impact of air pollution, measured near patients' homes, on emergency department (ED) visits for asthma or trauma (controls) within the Provence-Alpes-Côte-d'Azur region.

METHODS

Variables were selected using classification and regression trees on asthmatic and control population, 3-99 years, visiting ED from January 1 to December 31, 2013. Then in a nested case control study, randomization was based on the day of ED visit and on defined age groups. Pollution, meteorological, pollens and viral data measured that day were linked to the patient's ZIP code.

RESULTS

A total of 794,884 visits were reported including 6250 for asthma and 278,192 for trauma. Factors associated with an excess risk of emergency visit for asthma included short-term exposure to NO₂, female gender, high viral load and a combination of low temperature and high humidity.

CONCLUSION

Short-term exposures to high NO₂ concentrations, as assessed close to the homes of the patients, were significantly associated with asthma-related ED visits in children and adults.

Effect of personal exposure to black carbon on changes in allergic asthma gene methylation measured 5 days later in urban children: importance of allergic sensitization

Background

Asthma gene DNA methylation may underlie the effects of air pollution on airway inflammation. However, the temporality and individual susceptibility to environmental epigenetic regulation of asthma has not been fully elucidated. Our objective was to determine the timeline of black carbon (BC) exposure, measured by personal sampling, on DNA methylation of allergic asthma genes 5 days later to capture usual weather variations and differences related to changes in behavior and activities. We also sought to determine how methylation may vary by seroatopy and cockroach sensitization and by elevated fractional exhaled nitric oxide (FeNO).

Methods

Personal BC levels were measured during two 24-h periods over a 6-day sampling period in 163 New York City children (age 9–14 years), repeated 6 months later. During home visits, buccal cells were collected as noninvasive surrogates for lower airway epithelial cells and FeNO measured as an indicator of airway inflammation. CpG promoter loci of allergic asthma genes (e.g., interleukin 4 (IL4), interferon gamma (IFNγ), inducible nitric oxide synthase (NOS2A)), arginase 2 (ARG2)) were pyrosequenced at the start and end of each sampling period.

Results

Higher levels of BC were associated with lower methylation of IL4 promoter CpG⁻⁴⁸ 5 days later. The magnitude of association between BC exposure and demethylation of IL4 CpG⁻⁴⁸ and NOS2A CpG⁺⁵⁰⁹⁹ measured 5 days later appeared to be greater among seroatopic children, especially those sensitized to cockroach allergens (RR [95% CI] 0.55 [0.37–0.82] and 0.67 [0.45–0.98] for IL4 CpG⁻⁴⁸ and NOS2A CpG⁺⁵⁰⁹⁹, respectively), compared to non-sensitized children (RR [95% CI] 0.87 [0.65–1.17] and 0.95 [0.69–1.33] for IL4 CpG⁻⁴⁸ and NOS2A CpG⁺⁵⁰⁹⁹, respectively); however, the difference was not statistically different. In multivariable linear regression models, lower DNA methylation of IL4 CpG⁻⁴⁸ and NOS2A CpG⁺⁵⁰⁹⁹ were associated with increased FeNO.

Conclusions

Our results suggest that exposure to BC may exert asthma proinflammatory gene demethylation 5 days later that in turn may link to airway inflammation. Our results further suggest that seroatopic children, especially those sensitized to cockroach allergens, may be more susceptible to the effect of acute BC exposure on epigenetic changes.

Electronic supplementary material

The online version of this article (doi:10.1186/s13148-017-0361-3) contains supplementary material, which is available to authorized users.

Urban air pollution and meteorological factors affect emergency department visits of elderly patients with chronic obstructive pulmonary disease in Taiwan

Both air pollution and meteorological factors in metropolitan areas increased emergency department (ED) visits from people with chronic obstructive pulmonary disease (COPD). Few studies investigated the associations between air pollution, meteorological factors, and COPD-related health disorders in Asian countries. This study aimed to investigate the relationship between the environmental factors and COPD-associated ED visits of susceptible elderly population in the largest Taiwanese metropolitan area (Taipei area, including Taipei city and New Taipei city) between 2000 and 2013. Data of air pollutant concentrations (PM₁₀, PM_2.5, O₃, SO₂, NO₂ and CO), meteorological factors (daily temperature, relative humidity and air pressure), and daily COPD-associated ED visits were collected from Taiwan Environmental Protection Administration air monitoring stations, Central Weather Bureau stations, and the Taiwan National Health Insurance database in Taipei area. We used a case-crossover study design and conditional logistic regression models with odds ratios (ORs), and 95% confidence intervals (CIs) for evaluating the associations between the environmental factors and COPD-associated ED visits. Analyses showed that PM_2.5, O₃, and SO₂ had significantly greater lag effects (the lag was 4 days for PM_2.5, and 5 days for O₃ and SO₂) on COPD-associated ED visits of the elderly population (65-79 years old). In warmer days, a significantly greater effect on elderly COPD-associated ED visits was estimated for PM_2.5 with coexistence of O₃. Additionally, either O₃ or SO₂ combined with other air pollutants increased the risk of elderly COPD-associated ED visits in the days of high relative humidity and air pressure difference, respectively. This study showed that joint effect of urban air pollution and meteorological factors contributed to the COPD-associated ED visits of the susceptible elderly population in the largest metropolitan area in Taiwan. Government authorities should review existing air pollution policies, and strengthen health education propaganda to ensure the health of the susceptible elderly population.

Identification and influence of spatio-temporal outliers in urban air quality measurements

Forty eight potential outliers in air pollution measurements taken simultaneously in Detroit, Michigan, USA and Windsor, Ontario, Canada in 2008 and 2009 were identified using four independent methods: box plots, variogram clouds, difference maps, and the Local Moran's I statistic. These methods were subsequently used in combination to reduce and select a final set of 13 outliers for nitrogen dioxide (NO₂), volatile organic compounds (VOCs), total benzene, toluene, ethyl benzene, and xylene (BTEX), and particulate matter in two size fractions (PM_2.5 and PM₁₀). The selected outliers were excluded from the measurement datasets and used to revise air pollution models. In addition, a set of temporally-scaled air pollution models was generated using time series measurements from community air quality monitors, with and without the selected outliers. The influence of outlier exclusion on associations with asthma exacerbation rates aggregated at a postal zone scale in both cities was evaluated. Results demonstrate that the inclusion or exclusion of outliers influences the strength of observed associations between intraurban air quality and asthma exacerbation in both cities. The box plot, variogram cloud, and difference map methods largely determined the final list of outliers, due to the high degree of conformity among their results. The Moran's I approach was not useful for outlier identification in the datasets studied. Removing outliers changed the spatial distribution of modeled concentration values and derivative exposure estimates averaged over postal zones. Overall, associations between air pollution and acute asthma exacerbation rates were weaker with outliers removed, but improved with the addition of temporal information. Decreases in statistically significant associations between air pollution and asthma resulted, in part, from smaller pollutant concentration ranges used for linear regression. Nevertheless, the practice of identifying outliers through congruence among multiple methods strengthens confidence in the analysis of outlier presence and influence in environmental datasets.