Grantee Research Project Results
2009 Progress Report: The Detroit Asthma Morbidity, Air Quality and Traffic (DAMAT) Study
EPA Grant Number: R833628Title: The Detroit Asthma Morbidity, Air Quality and Traffic (DAMAT) Study
Investigators: Wahl, Robert L , Batterman, Stuart A. , Hultin, Mary Lee , Michalak, Anna , Mukherjee, Bhramar , Wasilevich, Elizabeth , Dombkowski, Kevin
Current Investigators: Wahl, Robert L , Batterman, Stuart A. , Wasilevich, Elizabeth , Hultin, Mary Lee , Dombkowski, Kevin , Mukherjee, Bhramar , Michalak, Anna
Institution: Michigan Department of Community Health , University of Michigan
EPA Project Officer: Hahn, Intaek
Project Period: September 30, 2007 through September 29, 2010 (Extended to September 29, 2011)
Project Period Covered by this Report: August 1, 2008 through July 31,2009
Project Amount: $499,777
RFA: Development of Environmental Health Outcome Indicators (2006) RFA Text | Recipients Lists
Research Category:
Objective:
Develop and evaluate a direct health indicator of pediatric asthma morbidity resulting from exposure to ambient air pollutants using an epidemiological approach that merges existing datasets and incorporates population susceptibility, exposure patterns, and other local conditions.Progress Summary:
We obtained roadway and traffic data for the study region from the Michigan Department of Transportation (MDOT) and the Southeast Michigan Council of Governments (SEMCOG). These data will be used to stratify the residence locations of the Medicaid claimants with respect to their proximity to major roads, an important source of air pollutant exposure. These data include traffic counts (annual average daily traffic [AADT] and commercial average daily traffic [CADT]) from permanent traffic recorders for the major roads; geographical information system (GIS) files describing a detailed road network; and results of a comprehensive traffic demand model (CDM) which provides flows on the network on over 20,000 roadway segments for four periods of the day and separates private and commercial vehicles.
Roadway modeling. A dispersion model capable of predicting short (hourly) to long-term (annual average) pollutant concentrations near roadways was implemented and analyzed. The predictions are comparable to the CALINE4 dispersion model, but can be easily implemented within a GIS platform for the purposes of exposure assessment, risk assessment, land use planning, or other aims. A sensitivity analysis of the CALINE4 model was performed to identify the most influential variables and a multiplicative model was created which incorporated the four most significant variables: distance of receptor to roadway, wind speed, wind direction, and traffic flow. The largest errors in this model (> 15%) were typically observed at very short distances from the freeway (< 30m), low wind speed (< 2 m s-1), and low traffic flow rates (1000 vehicles hr-1). This model can generate reliable estimates (generally < 20% error) of air pollutant concentrations at pre-determined distances from a roadway, when compared to CALINE4 estimates.
Time-series and time-stratified case-crossover analyses with threshold effects. Asthma morbidity has been associated with ambient air pollutants in time-series studies using generalized additive models (GAMs) and case-crossover studies using conditional logistic regression models (CLRMs). We were interested in using threshold effects to explore exposure-response relationships using these study designs. We estimated threshold parameters in both time-series and case-crossover analyses using a simple, testable, and readily implementable profile likelihood-based approach. These methods were applied to daily data on the asthma morbidity experienced by the Medicaid population of Detroit, Michigan and concentrations of pollutants PM2.5, CO, NO2 and SO2 over the 2004 to 2006 period. Evidence of significant increases in daily emergency asthma events was found for SO2 and PM2.5, and a significant threshold effect was estimated for PM2.5 at 13 and 11 μg m-3 using GAMs and CLRMs, respectively. The PM2.5 threshold models were fairly consistent across model types, often exhibiting stronger effect sizes above the threshold compared to linear models, e.g., one interquartile range increase (9.2 μg m-3 ) in PM2.5 (at 3-day-lag) had a risk ratio of 1.032 (95% CI: 1.012, 1.054) in the linear 3-year CLRM, and 1.045 (95% CI: 1.019, 1.071) in the threshold CLRM. From these results, the existence of thresholds can be supported for physiological and statistical reasons, and has significant implications for policy and risk management.
Future Activities:
- Complete linkage of Medicaid and air quality (AQ) data. The linkage has been completed. The analysis of the relationship between daily fluctuations in pollutant concentrations and daily asthma-related urgent care use is ongoing using case-crossover Poisson regression models.
- Acquire local and regional pollutant data. We have estimated background levels from measurements at outlying and upwind monitoring sites. These values have been subtracted from the measurements obtained for Detroit. We have determined associations between the regional and urban increments of the air pollutants and asthma-urgent care use.
- GIS analysis of proximity to roadways and industry. We constructed spatial maps of industrial and other pollutants using GIS, and will classify their potential impact on each child, and incorporate the data into models relating air pollutant exposure and daily asthma-related urgent care use. We will use GIS techniques for this analysis. This analysis will be completed by summer 2010.
- Case-control analysis. For the case-control analysis, we have completed the selection of controls (non-respiratory related events in the Medicaid data). The residence of each child making an asthma- related Medicaid claim (case) and a non-respiratory related Medicaid claim (control) will be classified according to exposure to local emission sources. We will determine the effects of local pollution sources on urgent care use for cases and for controls. We will then determine the probability of asthma-related morbidity in areas affected and not affected by local pollution sources. Multinomial logistic regression models will be used. This analysis is ongoing and will be completed by summer 2010.
- Scenario and uncertainty analysis. Using the collected data, we will first construct three scenarios of contrasting future emissions. We will then estimate the air pollution impact of each scenario using the longitudinal models previously developed. We will evaluate the uncertainty in the indicators using both estimated error as cross-validation comparing results across each year. Finally, we will analyze and compare indicators for spatial and temporal modes, including the effects of prediction uncertainty on both population and individual means. This analysis will be started at the end of in summer of Year 3 and completed by October 2010.
Journal Articles on this Report : 1 Displayed | Download in RIS Format
Other project views: | All 5 publications | 5 publications in selected types | All 5 journal articles |
---|
Type | Citation | ||
---|---|---|---|
|
Li S, Batterman S, Wasilevich E, Wahl R, Wirth J, Su F-C, Mukherjee B. Association of daily asthma emergency department visits and hospital admissions with ambient air pollutants among the pediatric Medicaid population in Detroit: time-series and time-stratified case-crossover analyses with threshold effects. Environmental Research 2011;111(8):1137-1147. |
R833628 (2009) R833628 (2010) R833628 (Final) |
Exit Exit |
Supplemental Keywords:
air, ambient air, ozone, exposure, risk, health effects, human health, sensitive populations, children, age, race, susceptibility, public policy, decision making, epidemiology, modeling, monitoring, analytical, Great Lakes, Midwest, Michigan, MI, EPA Region 5, transportation, industry, RFA, Scientific Discipline, Health, Air, HUMAN HEALTH, particulate matter, Health Risk Assessment, air toxics, Exposure, Epidemiology, Susceptibility/Sensitive Population/Genetic Susceptibility, Risk Assessments, Health Effects, genetic susceptability, Biology, copollutant exposures, sensitive populations, atmospheric particulate matter, asthma, airway epithelial cells, cardiopulmonary responses, fine particles, PM 2.5, inhaled pollutants, acute cardiovascular effects, acute lung injury, stratospheric ozone, morbidity, air pollutants, motor vehicle emissions, automotive emissions, motor vehicle exhaust, air pollution, susceptible subpopulations, cardiac arrest, diesel exhaust, chronic health effects, lung inflammation, oxidant gas, particulate exposure, cardiopulmonary response, heart rate, human exposure, atmospheric aerosols, Acute health effects, inhaled, chronic obstructive pulmonary disease, human susceptibility, cardiotoxicity, cardiopulmonary, mortality, concentrated particulate matter, air contaminant exposure, air quality, environmental hazard exposures, toxics, airborne urban contaminants, cardiovascular disease, acute exposureProgress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.