Background
Previous studies report associations between aeroallergen exposure and asthma exacerbations. Aeroallergen burdens and asthma prevalence are increasing worldwide and are projected to increase further with climate change, highlighting the importance of understanding population-level relationships between ambient pollen concentrations and asthma.
Objective
To examine short-term associations between ambient concentrations of various pollen taxa and emergency department (ED) visits for asthma and wheeze in the Atlanta metropolitan area between 1993 and 2004.
Methods
We assessed associations between the three-day moving average (lag 0-1-2) of Betulaceae (except Alnus), Cupressaceae, Quercus, Pinaceae (except Tsuga), Poaceae, and Ambrosia pollen concentrations and daily asthma and wheeze ED visit counts, controlling for covarying pollen taxa and ambient pollutant concentrations.
Results
We observed a 2–3% increase in asthma and wheeze ED visits per standard deviation increase in Quercus and Poaceae pollen and a 10–15% increased risk on days with the highest concentrations (comparing the top 5% of days to the lowest 50% of days). A standard deviation increase in Cupressaceae concentrations was associated with a 1% decrease in ED visits. The association for Quercus pollen was strongest for children age 5 to 17 years. Effects of Ambrosia pollen on asthma exacerbations were difficult to assess in this large-scale temporal analysis due to possible confounding by the steep increase in circulating rhinoviruses every September.
Conclusion
Poaceae and Quercus pollen contribute to asthma morbidity in Atlanta. Altered Quercus and Poaceae pollen production due to climate change could affect allergen-induced asthma morbidity in the southeastern United States.
Introduction
Various temporal metrics of daily pollution levels have been used to examine relationships between air pollutants and acute health outcomes. However, daily metrics of the same pollutant have rarely been systematically compared within a study. In this analysis, we describe the variability of effect estimates attributable to the use of different temporal metrics of daily pollution levels.
Methods
We obtained hourly measurements of ambient particulate matter (PM2.5), carbon monoxide (CO), nitrogen dioxide (NO2), and ozone (O3) from air monitoring networks in 20-county Atlanta for the time period 1993–2004. For each pollutant we created: 1) a daily 1-hour maximum; 2) a 24-hour average; 3) a commute average; 4) a day-time average; 5) a night-time average; and a daily 8-hour maximum (only for O3). Using Poisson generalized linear models, we examined associations between daily counts of respiratory emergency department visits and the previous day’s pollutant metrics.
Results
Variability was greatest across O3 metrics, with the 8-hour maximum, 1-hour maximum, and day-time metrics yielding strong positive associations and the night-time O3 metric yielding a negative association (likely reflecting confounding by air pollutants oxidized by O3). With the exception of the day-time metric, all of the CO and NO2 metrics were positively associated with respiratory emergency department visits.
Discussion
Differences in observed associations with respiratory emergency room visits among temporal metrics of the same pollutant were influenced by the diurnal patterns of the pollutant, spatial representativeness of the metrics, and correlation between each metric and copollutant concentrations. Overall, the use of metrics based on the US National Ambient Air Quality Standards (e.g., the use of a daily 8-hour maximum O3 as opposed to a 24-hour average metric) was supported by this analysis. Comparative analysis of temporal metrics also provided insight into underlying relationships between specific air pollutants and respiratory health.
Introduction
Relatively few studies have evaluated the impacts of heterogeneous spatiotemporal pollutant distributions on health risk estimates in time-series analyses that use data from a central monitor to assign exposures. We present a method for examining the impacts of exposure measurement error relating to spatiotemporal variability in ambient air pollutant concentrations on air pollution health risk estimates in a daily time-series analysis of emergency department visits in Atlanta, Georgia.
Methods
We used Poisson generalized linear models to estimate associations between current day pollutant concentrations and circulatory emergency department visits for the 1998–2004 period. Data from monitoring sites located in different geographical regions of the study area and at different distances from several urban geographic subpopulations served as alternative measures of exposure.
Results
We observed associations for spatially heterogeneous pollutants (CO and NO2) using data from several different urban monitoring sites. These associations were not observed when using data from the most rural site, located 38 miles from the city center. In contrast, associations for spatially homogeneous pollutants (O3 and PM2.5) were similar regardless of monitoring site location.
Conclusions
We found that monitoring site location and the distance of a monitoring site to a population of interest did not meaningfully impact estimated associations for any pollutant when using data from urban sites located within 20 miles from the population center under study. However, for CO and NO2, these factors were important when using data from rural sites, located greater than 30 miles from the population center, likely due to exposure measurement error. Overall, our findings lend support to the use of pollutant data from urban central sites to assess population exposures within geographically dispersed study populations in Atlanta and similar cities.
Rationale: Certain outdoor air pollutants cause asthma exacerbations in children. To advance understanding of these relationships, further characterization of the dose–response and pollutant lag effects are needed, as are investigations of pollutant species beyond the commonly measured criteria pollutants.
Objectives: Investigate short-term associations between ambient air pollutant concentrations and emergency department visits for pediatric asthma.
Methods: Daily counts of emergency department visits for asthma or wheeze among children aged 5 to 17 years were collected from 41 Metropolitan Atlanta hospitals during 1993–2004 (n = 91,386 visits). Ambient concentrations of gaseous pollutants and speciated particulate matter were available from stationary monitors during this time period. Rate ratios for the warm season (May to October) and cold season (November to April) were estimated using Poisson generalized linear models in the framework of a case-crossover analysis.
Measurements and Main Results: Both ozone and primary pollutants from traffic sources were associated with emergency department visits for asthma or wheeze; evidence for independent effects of ozone and primary pollutants from traffic sources were observed in multipollutant models. These associations tended to be of the highest magnitude for concentrations on the day of the emergency department visit and were present at relatively low ambient concentrations.
Conclusions: Even at relatively low ambient concentrations, ozone and primary pollutants from traffic sources independently contributed to the burden of emergency department visits for pediatric asthma.
Oxidative potential (OP) has been proposed as a measure of toxicity of ambient particulate matter (PM). OBJECTIVES: Our goal was to address an important research gap by using daily OP measurements to conduct population-level analysis of the health effects of measured ambient OP. METHODS: A semi-automated dithiothreitol (DTT) analytical system was used to measure daily average OP (OP DTT ) in water-soluble fine PM at a central monitor site in Atlanta, Georgia, over eight sampling periods (a total of 196 d) during June 2012–April 2013. Data on emergency department (ED) visits for selected cardiorespiratory outcomes were obtained for the five-county Atlanta metropolitan area. Poisson log-linear regression models controlling for temporal confounders were used to conduct time-series analyses of the relationship between daily counts of ED visits and either the 3-d moving average (lag 0–2) of OP DTT or same-day OP DTT . Bipollutant regression models were run to estimate the health associations of OP DTT while controlling for other pollutants. RESULTS: OP DTT was measured for 196 d (mean = 0:32 nmol/min/m 3 , interquartile range = 0:21). Lag 0–2 OP DTT was associated with ED visits for respiratory disease (RR = 1:03, 95% confidence interval (CI): 1.00, 1.05 per interquartile range increase in OP DTT ), asthma (RR = 1:12, 95% CI: 1.03, 1.22), and ischemic heart disease (RR = 1:19, 95% CI: 1.03, 1.38). Same-day OP DTT was not associated with ED visits for any outcome. Lag 0–2 OP DTT remained a significant predictor of asthma and ischemic heart disease in most bipollutant models. CONCLUSIONS: Lag 0–2 OP DTT was associated with ED visits for multiple cardiorespiratory outcomes, providing support for the utility of OP DTT as a measure of fine particle toxicity.
OBJECTIVE: We examine whether ambient air pollution is associated with oxygen saturation in 32 elderly subjects in Steubenville, Ohio.
METHODS: We used linear mixed models to examine the effects of fine particulate matter less than 2.5 μm (PM2.5), sulfate (SO4), elemental carbon, and gases on median oxygen saturation.
RESULTS: An interquartile range increase of 13.4 μg/m in PM2.5 on the previous day was associated with a decrease of -0.18% (95% confidence interval: -0.31 to -0.06) and a 5.1 μg/m interquartile range increase in SO4 on the previous day was associated with a decrease of -0.16% (95% confidence interval: -0.27 to -0.04) in oxygen saturation during the initial 5-minute rest period of the protocol.
CONCLUSIONS: Increased exposure to air pollution, including the nontraffic pollutant SO4 from industrial sources, led to changes in oxygen saturation that may reflect particle-induced pulmonary inflammatory or vascular responses.
Background: Recent interest in the health effects of air pollution focuses on identifying combinations of multiple pollutants that may be associated with adverse health risks. Objective: Present a methodology allowing health investigators to explore associations between categories of ambient air quality days (i.e., multipollutant day types) and adverse health. Methods: First, we applied a self-organizing map (SOM) to daily air quality data for 10 pollutants collected between January 1999 and December 2008 at a central monitoring location in Atlanta, Georgia to define a collection of multipollutant day types. Next, we conducted an epidemiologic analysis using our categories as a multipollutant metric of ambient air quality and daily counts of emergency department (ED) visits for asthma or wheeze among children aged 5 to 17 as the health endpoint. We estimated rate ratios (RR) for the association of multipollutant day types and pediatric asthma ED visits using a Poisson generalized linear model controlling for long-term, seasonal, and weekday trends and weather. Results: Using a low pollution day type as the reference level, we found significant associations of increased asthma morbidity in three of nine categories suggesting adverse effects when combinations of primary (CO, NO<inf>2</inf>, NO<inf>X</inf>, EC, and OC) and/or secondary (O<inf>3</inf>, NH<inf>4</inf>, SO<inf>4</inf>) pollutants exhibited elevated concentrations (typically, occurring on dry days with low wind speed). On days with only NO<inf>3</inf> elevated (which tended to be relatively cool) and on days when only SO<inf>2</inf> was elevated (which likely reflected plume touchdowns from coal combustion point sources), estimated associations were modestly positive but confidence intervals included the null. Conclusions: We found that ED visits for pediatric asthma in Atlanta were more strongly associated with certain day types defined by multipollutant characteristics than days with low pollution levels; however, findings did not suggest that any specific combinations were more harmful than others. Relative to other health endpoints, asthma exacerbation may be driven more by total ambient pollutant exposure than by composition.
Background: Characterizing multipollutant health effects is challenging. We use classification and regression trees to identify multipollutant joint effects associated with pediatric asthma exacerbations and compare these results with those from a multipollutant regression model with continuous joint effects. Methods: We investigate the joint effects of ozone, NO<inf>2</inf> and PM<inf>2.5</inf> on emergency department visits for pediatric asthma in Atlanta (1999-2009), Dallas (2006-2009) and St. Louis (2001-2007). Daily concentrations of each pollutant were categorized into four levels, resulting in 64 different combinations or "Day-Types" that can occur. Days when all pollutants were in the lowest level were withheld as the reference group. Separate regression trees were grown for each city, with partitioning based on Day-Type in a model with control for confounding. Day-Types that appeared together in the same terminal node in all three trees were considered to be mixtures of potential interest and were included as indicator variables in a three-city Poisson generalized linear model with confounding control and rate ratios calculated relative to the reference group. For comparison, we estimated analogous joint effects from a multipollutant Poisson model that included terms for each pollutant, with concentrations modeled continuously. Results and discussion: No single mixture emerged as the most harmful. Instead, the rate ratios for the mixtures suggest that all three pollutants drive the health association, and that the rate plateaus in the mixtures with the highest concentrations. In contrast, the results from the comparison model are dominated by an association with ozone and suggest that the rate increases with concentration. Conclusion: The use of classification and regression trees to identify joint effects may lead to different conclusions than multipollutant models with continuous joint effects and may serve as a complementary approach for understanding health effects of multipollutant mixtures.
Results from air pollution exposure assessment studies suggest that ambient fine particles [particulate matter with aerodynamic diameter ≤ 2.5 μg (PM2.5)], but not ambient gases, are strong proxies of corresponding personal exposures. For particles, the strength of the personal–ambient association can differ by particle component and level of home ventilation. For gases, however, such as ozone (O3), nitrogen dioxide (NO2), and sulfur dioxide (SO2), the impact of home ventilation on personal–ambient associations is untested. We measured 24-hr personal exposures and corresponding ambient concentrations to PM2.5, sulfate (SO42−), elemental carbon, O3, NO2, and SO2 for 10 nonsmoking older adults in Steubenville, Ohio. We found strong associations between ambient particle concentrations and corresponding personal exposures. In contrast, although significant, most associations between ambient gases and their corresponding exposures had low slopes and R2 values; the personal–ambient NO2 association in the fall season was moderate. For both particles and gases, personal–ambient associations were highest for individuals spending most of their time in high- compared with low-ventilated environments. Cross-pollutant models indicated that ambient particle concentrations were much better surrogates for exposure to particles than to gases. With the exception of ambient NO2 in the fall, which showed moderate associations with personal exposures, ambient gases were poor proxies for both gas and particle exposures. In combination, our results suggest that a) ventilation may be an important modifier of the magnitude of effect in time-series health studies, and b) results from time-series health studies based on 24-hr ambient concentrations are more readily interpretable for particles than for gases.
Background:
Emergency department (ED) visit and hospital admissions (HA) data have been an indispensible resource for assessing acute morbidity impacts of air pollution. ED visits and HAs are types of health care visits with similarities, but also potentially important differences. Little previous information is available regarding the impact of health care visit type on observed acute air pollution-health associations from studies conducted for the same location, time period, outcome definitions and model specifications.
Methods:
As part of a broader study of air pollution and health in St. Louis, individual-level ED and HA data were obtained for a 6.5 year period for acute care hospitals in the eight Missouri counties of the St. Louis metropolitan area. Patient demographic characteristics and diagnostic code distributions were compared for four visit types including ED visits, HAs, HAs that came through the ED, and non-elective HAs. Time-series analyses of the relationship between daily ambient ozone and PM2.5 and selected cardiorespiratory outcomes were conducted for each visit type.
Results:
Our results indicate that, compared with ED patients, HA patients tended to be older, had evidence of greater severity for some outcomes, and had a different mix of specific outcomes. Consideration of ‘HA through ED’ appeared to more effectively select acute visits than consideration of ‘non-elective HA’. While outcomes with the strongest observed temporal associations with air pollutants tended to show strong associations for all visit types, we found some differences in observed associations for ED visits and HAs. For example, risk ratios for the respiratory disease-ozone association were 1.020 for ED visits and 1.004 for ‘HA through ED’; risk ratios for the asthma/wheeze-ozone association were 1.069 for ED visits and 1.106 for ‘HA through ED’. Several factors (e.g. age) were identified that may be responsible, in part, for the differences in observed associations.
Conclusions:
Demographic and diagnostic differences between visit types may lead to preference for one visit type over another for some questions and populations. The strengths of observed associations with air pollutants sometimes varied between different health care visit types, but the relative strengths of association generally were specific to the pollutant-outcome combination.