Final Report: Air Quality and Reported Asthma Incidence in IllinoisEPA Grant Number: R829402C003
Subproject: this is subproject number 003 , established and managed by the Center Director under grant R829402
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
Center: Center for Integrating Statistical and Environmental Science
Center Director: Stein, Michael
Title: Air Quality and Reported Asthma Incidence in Illinois
Investigators: Frederick, John , Draghicescu, Dana , Dukic, Vanja , Eshel, Gidon , Im, Haekyung , Naureckas, Edward , Rathouz, Paul
Institution: University of Chicago
EPA Project Officer: Packard, Benjamin H
Project Period: March 12, 2002 through March 11, 2007
RFA: Environmental Statistics Center (2001) RFA Text | Recipients Lists
Research Category: Environmental Statistics , Ecological Indicators/Assessment/Restoration , Health , Ecosystems , Air
This project examined various indicators of air quality and meteorology in the Chicago area and carried out statistical analyses to define the relationship between these environmental variables and measures of respiratory health with an emphasis on asthma. The goal of developing improved statistical models for linking acute asthma events to air quality indicators was a driving force behind much of the work, and development of these models was ongoing throughout the duration of the project. Based on this overarching goal, several important investigations were undertaken. These included: (A) an analysis of the validity of alternate asthma severity indicators; (B) an investigation of processes that confound the exposure-outcome relationship in daily time series studies; (C) development of a new statistical method for disease incidence mapping based on kriging; (D) the most detailed analysis to date of daily temperature patterns in the Chicago metropolitan area involving 20 years of data collected at more than 10 sites; and (E) an investigation of variability in urban particulate matter abundances associated with a major highway construction project.
Interactions with EPA
The Air Quality and Asthma Group had ongoing interaction with Thomas Brody and Michael Compher (U.S. EPA Region 5, Air and Radiation Division) concerning studies that EPA is conducting with the Wisconsin and CDC Public Health Tracking offices. In addition, Vanja Dukic and Edward Naureckas served as members of the Chicago Asthma Consortium together with Thomas Brody (U.S. EPA Region 5). This organization, composed of researchers from the health and air quality communities, addresses a variety of problems concerning causes, incidence and treatment of asthma in the Chicago area. Dr. Dukic was a member of the Data Task Force within the consortium. Finally, Paul Rathouz interacted from time to time with Brad Schultz, currently Chief of the Exposure Modeling Research Branch at EPA in Research Triangle Park, to discuss the current state of research in human risk assessment models.
- Validation of alternate measures of asthma outcomes
- The exposure-outcome relationship in daily time series studies in metropolitan Chicago
- Disease incidence mapping
- Space-time modeling of 20 years of daily air temperature in the Chicago metropolitan region
- It quickly became clear that in order to obtain sufficient information on both the space and time structure of the data, we would require many more than the 4 years of data with which we had been working. We therefore based our analysis on 20 years of data from 1981 to 2000 inclusive.
- We learned that, while the so-called lake effect on temperature (that is, the tendency for temperatures to be warmer in the winter and colder in the summer near the lake) is widelyclaimed to exist, there was little in the way of formal empirical analysis or description of this effect in the meteorological literature.
- The analysis was considerably complicated by the seasonal variation not only in the mean model, but also in the space-time variance-covariance structure. Temperature is less variable in the summer, and auto-regressive time parameters and spatial covariance parameters vary strongly by season.
- Variability in urban particulate matter abundances associated with a major highway construction project
The objective of this study was to determine whether prescription fills for short-acting beta agonists by patients with asthma might act as a surrogate marker for other measures of asthma morbidity such as hospitalizations or emergency department (ED) visits. The research was part of the graduate work of the student Xiaoming Bao, and the results have been published (Naureckas, et al., 2005). By comparing outcomes from the Illinois Medicaid Database with regional EPA data on outdoor air quality, it became clear that prescription fills of short acting bronchodilators provided a useful indicator of asthma outcomes with a high event frequency. The literature contains numerous studies utilizing claims data for asthma hospitalizations and emergency department visits. While these traditional outcomes have the advantage of providing an easily definable event, they represent only the most severe instances of asthma exacerbation. The occurrence of these events is also influenced by a number of factors that may be independent of asthma severity, such as availability of a primary care physician to provide an urgent outpatient visit. For these reasons, these outcomes may be neither sensitive nor specific as a marker for asthma exacerbation due to adverse air quality or other factors.
Albuterol prescription refills occur at a rate much higher than the markers described above. An early fill by an individual may be indicative of increased asthma activity in this person, even if the exacerbation does not result in a hospitalization or an emergency department visit for asthma. For this reason, prescription fills for short-acting bronchodilators may provide a much more sensitive marker for low-level respiratory effects of degraded outdoor air quality. The goal of this project was to determine the degree to which short-acting bronchodilator prescription fills are correlated with the more traditional asthma outcomes.
The analysis of Naureckas, et al. (2005) found that the greatest association between betaagonist prescription refills and ED or hospital visits is observed on the day of a short acting prescription fill. There is a smaller but still strong association for each of the next 4 days following the prescription fills. This association is still seen whether or not patients are actively using controller therapy such as inhaled corticosteroids. This relationship also was independent of gender and was also seen in both the adult and pediatric populations.
The results of this work support the use of short acting bronchodilator prescriptions as a surrogate marker for asthma exacerbation. The patterns seen in the analysis suggest that a distributed lag approach may be useful in investigating the relationship between outdoor air quality and asthma outcomes in our current database, as well as additional databases in the future.
A strengthened capability to characterize atmospheric states that promote degraded air quality is important for improving forecasts of conditions that may pose health-related risks. A statistical analysis of ground-level ozone in Illinois in conjunction with radiosonde data for the decade of the 1990s defined the regional meteorology most likely to be associated with poor air quality. Results showed that elevated ozone amounts tend to occur during periods of strengthened subsidence over the state, leading to a shallow boundary layer. The prevailing downward motions inhibit ventilation of the boundary layer by convection, thereby allowing a buildup of ozone. The paper by Eshel and Bernstein (2006) summarizes all aspects of this work.
This project was carried out by Vanja Dukic and Chava Zibman, a Ph.D. candidate in the Department of Statistics, who is expected to defend her thesis during the summer of 2008. Ms. Zibman’s thesis contains two major parts. The first part develops a novel Bayesian hierarchical semi-parametric Poisson model for describing the effects of air pollution on short-term asthma health outcomes. In this model, flexible year-specific functions of time with unknown degrees of smoothness were introduced to capture time-varying confounding processes. A separate Markov Chain Monte Carlo algorithm was implemented to estimate all the parameters, and the model was applied to analyses of two datasets: the Medicaid and Osco daily prescription refills in Chicago. Two papers (one applied and one methodological) based on this work are in preparation and will be submitted for publication to applied statistics and epidemiology journals. The second part of Ms. Zibman’s thesis is focused on theory and novel methods for estimation of effects in the presence of high-frequency time-varying confounders in linear and log-linear models. In particular, the research examines the performance of several procedures for choosing the appropriate set of bases and degrees of smoothness in the estimation of a time-varying confounder function, resulting in adaptive estimators of the effect of ozone and other factors of interest. This part is joint work with Professors Michael Stein and Paul Rathouz.
This project focused on development of a statistical model and computational method for disease incidence mapping. The effort developed a statistical model and new computational technique for mapping smoothed disease incidence rates over space when the data consist of event counts aggregated over geographical areas such as ZIP-codes, census tracts or counties. This work was done jointly with David Clifford, a former Ph.D. student in Statistics at the University of Chicago who was not funded by CISES. The methodology works by (i) tiling the entire region with square cells; (ii) using the tiling to approximate the integrals required to compute the variance-covariance matrix of area-level average disease risk; and (iii) basing spatial interpolation and point-wise incidence estimation on best-linear unbiased prediction of disease risk given the area-aggregated disease counts, much like as is done in kriging. The project included: (i) developing the computational technique, (ii) investigating the computational savings in using this new technique versus traditional methods of computing the variance-covariance matrix, (iii) developing measures of numerical precision of variance-covariance values amongst the areas, and (iv) refining a computational algorithm that can fit the model and generate smooth incidence plots using up to 6000 cells over the Chicago region in approximately 10 minutes on CISES computers. This relatively low level of computational burden suggests that the method is practical to use in applied disease mapping work.
This study arose out of the need in the asthma-ozone project to have spatially-resolved temperature measurements as a key exposure variable, parallel to our measures of ozone, which are also spatially and temporally resolved. Dr. H. K. Im took on this project at the beginning of her appointment as Research Associate, under the direction of Dr. Rathouz. Initially, the goal of this paper was to construct a space-time interpolation model for maximum daily temperature. The project rapidly evolved into a more elaborate investigation owing to several facets of the analysis:
The goal of our analysis was therefore to develop a space-time model of air temperature that will permit spatial interpolation of temperature on any given day and will also yield parsimonious descriptions and quantifications of patterns of variability of air temperature in this area. Our model incorporated a description of the lake effect on temperature by allowing mean temperature to vary as a function of distance from Lake Michigan. We also modeled effects of latitude and of winds to and from the North-East and North-West. Throughout, we allowed for differential predictor effects as a function of season of the year. The resulting parsimonious space-time model permitted spatial interpolation of air temperature on any given day using data from the current day and days nearby in time. Our results showed a strong spatial structure for temperature on a given day and temporal structure from day to day, and our model provided a description of those structures in terms of meaningful model parameters. The resulting manuscript is available as CISES technical report #45 and has been tentatively accepted for publication in Environmetrics.
With the recent revision in EPA’s standard for airborne particulates in response to literature demonstrating an increase in all-cause mortality associated with particulates, there has been great interest in this pollutant as a possible exacerbant of asthma. Unfortunately, in the time period covered by the beta agonist dataset, the Chicago-area’s EPA particulate monitoring network did not provide the density of data necessary to perform the Zip code level analysis that was possible using the ozone data.
The reconstruction of the Dan Ryan Expressway, a major highway running through the South Side of Chicago, provided an opportunity to further investigate this type of pollutant. As a major component of the project, the Illinois Department of Transportation (IDOT) invested in an extensive network of monitors both prior to and during construction to assess the impact of the construction on communities surrounding the construction zone. The activity of the construction only mildly increased atmospheric particulate matter arising from movement of dirt, demolition of old structures, use of construction materials, and burning of diesel fuel. IDOT’s measurements included a baseline measurement as well as measurements through the three years of construction, which was completed summer of 2007. Measurements of PM2.5 and PM10 were made continuously at one site and daily at approximately 10 locations on the south side of Chicago. In addition to PM10 and PM2.5, measurements were made of total dust loading, the abundances of diesel components, lead, and respirable dust.
In the final year of CISES we began analyzing the available PM10 and PM2.5 data collected along the construction zone, with emphasis on statistical comparisons to data from EPA-sponsored sites on the south side of Chicago. The time period considered was January through June 2005, coincident with the early phase of the construction activity. The IDOT-EPA comparisons were complicated by the fact that the IDOT measurements for any given species do not uniformly occur on a daily basis, and the exact location of any measurement may lie at various points along the expressway. Therefore, our analyses were restricted to the limited number of coincidences.
The comparison of PM10 measurements from the IDOT network with those from four EPA monitors in the same part of the city showed significant positive correlations (1% level of confidence), and no persistent effect of the construction activity was evident. In three of the four cases, the regression line relating the IDOT and EPA datasets differed only slightly from a straight line with a slope of unity and an intercept of zero. However, in all cases, the largest individual PM10 values, near 70 μg m-3, appear in the IDOT data. A comparison of IDOT and EPA data for PM2.5 was possible for only one EPA location. In this case, the EPA measurements explained 41% of the variance in the IDOT data, while the means of coincident measurements were virtually identical, being 16.7 μg m-3 and 16.5 μg m-3 for EPA and IDOT respectively.
Based on the work completed, the effect of the construction activity lies in the sporadic appearance of elevated PM10 abundances, confined to a single day per occurrence. These spikes were imposed on a PM10 background typical of that for Chicago’s south side.
Contributions to understanding of environmental problems
The identification of statistical linkages between air quality and measures of human health is an environmental issue of high priority, but such efforts are plagued by difficulties related to the measurement of both health outcomes and environmental exposures, differing spatial-temporal coverage of health datasets, and the existence of confounding variables. This project has contributed to our understanding of these problems in several ways.
The results reported by Naureckas, et al. (2005) showed that the database available for bronchodilator prescriptions is a valid indicator of asthma exacerbation. This is important because the amount of information available here on a daily basis is large compared to that provided by the more traditional asthma indicators such as hospitalizations and emergency room visits. In addition, hospitalization for asthma occurs only in the most severe cases, while the number of prescription refills is a more representative indicator of asthma exacerbation in the broad population.
Spatial variability in disease incidence across an urban area can provide important information concerning the causal factors at work. However, health data often have coarse spatial resolution. For example, the number of daily hospitalizations for asthma might be reported according to the patient’s Zip Code of residence. The work by Paul Rathouz and David Clifford developed a new statistical model and efficient computational technique for using reported medical data to create smooth spatial maps of disease incidence. Although the specific application was to asthma incidence in Chicago, the approach is general. The new methodology is computationally efficient, allowing it to be used in a range of disease mapping applications.
Early analyses showed that air temperature is an important variable for which to control when seeking links between air quality and measures of human health. It is necessary to have spatially and temporally resolved temperature values to accompany the datasets for asthma and air quality. Unfortunately, for a typical metropolitan area air temperature measurements are reported at only a small number of sites. The analysis by Im et al. (2007) showed strong temporal and spatial structure in the air temperature data for metropolitan Chicago. This can be modeled by considering the effects of latitude, winds, and geographic factors peculiar to the region, in this case the effect of proximity to Lake Michigan. Models of the type developed by Im et al. (2007) should be included in future studies of links between air quality and respiratory health.
Journal Articles on this Report : 3 Displayed | Download in RIS Format
|Other subproject views:||All 21 publications||4 publications in selected types||All 3 journal articles|
|Other center views:||All 115 publications||69 publications in selected types||All 47 journal articles|
||Eshel G, Bernstein JJ. Relationship between large-scale atmospheric states, subsidence, static stability and ground-level ozone in Illinois, USA. Water, Air, & Soil Pollution 2006;171(1-4):111-133.||
||Im H-K, Rathouz PJ, Frederick JE. Space-time modeling of 20 years of daily air temperature in the Chicago metropolitan region. Environmetrics 2009;20(5):494-511.||
||Naureckas ET, Dukic V, Bao X, Rathouz P. Short-acting β-agonist prescription fills as a marker for asthma morbidity. Chest 2005;128(2):602-608.||
Supplemental Keywords:RFA, Scientific Discipline, Health, Economic, Social, & Behavioral Science Research Program, PHYSICAL ASPECTS, Air, Geographic Area, Ecosystem Protection/Environmental Exposure & Risk, HUMAN HEALTH, Applied Math & Statistics, particulate matter, Health Risk Assessment, Ecosystem/Assessment/Indicators, Ecosystem Protection, Ecological Effects - Environmental Exposure & Risk, Monitoring/Modeling, Risk Assessments, Environmental Monitoring, Ecological Effects - Human Health, Health Effects, Physical Processes, Ecological Risk Assessment, Environmental Statistics, Environmental Engineering, Engineering, Chemistry, & Physics, Ecological Indicators, EPA Region, asthma, ecological effects, monitoring, particulates, risk assessment, health risk analysis, atmospheric particulate matter, ecological health, human health effects, particulate, watersheds, stratospheric ozone, ozone , emissions monitoring, computer models, exposure, ozone, sediment transport, airborne particulate matter, air pollution, trend monitoring, chemical transport, chemical transport modeling, environmental health effects, human exposure, statistical models, air pollutant-induced pulmonary inflammation, ecological risk, ecosystem health, environmental indicators, PM, water, data models, modeling studies, Region 5, chemical transport models, ecological models, aersol particles, air quality, human health risk, statistical methods, stochastic models
Progress and Final Reports:Original Abstract
Main Center Abstract and Reports:R829402 Center for Integrating Statistical and Environmental Science
Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
R829402C001 Detection of a Recovery in Stratospheric and Total Ozone
R829402C002 Integrating Numerical Models and Monitoring Data
R829402C003 Air Quality and Reported Asthma Incidence in Illinois
R829402C004 Quasi-Experimental Evidence on How Airborne Particulates Affect Human Health
R829402C005 Model Choice Stochasticity, and Ecological Complexity
R829402C006 Statistical Approaches to Detection and Downscaling of Climate Variability and Change