Impact/Purpose:

Pediatric asthma is an important and growing public health problem known to be associated with exposure to air pollutants and potentially without a concentration threshold for particulate matter exposure. 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. Hypotheses: (1) Daily changes in asthma morbidity among the pediatric Medicaid population in Detroit are attributable to fluctuations in ambient air pollutant concentrations. (2) Daily changes in asthma morbidity can be separated into effects caused by regional and local emission sources. (3) Associations between air pollutants and asthma morbidity are strengthened by accounting for residential location and exposures due to traffic and industry-related pollutants. (4) The spatial pattern of asthma-related urgent care use relative to other pediatric claims is determined in part by exposure to traffic- and industry-related pollutants. (5) The developed indicators provide meaningful measures of health impacts that can inform decision-making and comparative impact assessments.

Description:

The project was completed successfully. In Project Year 1, the health outcome and exposure data sets were collected, cleaned and processed, including specifically:

• A set of daily exposure measures, based on measurements of the selected pollutants measured at Detroit air quality monitors for the primary study period (2004-2006), was developed.
• Daily Medicaid data on all children (1-17 years of age) residing in Detroit using urgent care facilities for asthma related claims, including hospital visits and urgent care visits, for the study period were obtained (Table 1).

Figure 1.  Trend of daily counts of asthma events for the pediatric Medicaid population (children 2–18 years of age) in Detroit, Michigan, 2004–2006.  Daily observations are shown as points with locally estimated scatter-plot smoothing trend shown as overlaying fitted curve.  The endpoints of asthma events include emergency department visits without hospitalization, direct admission for hospitalization, and hospitalizations admitted through the emergency department.

During Project Year 2, Specific Aims 1 through 4 were all addressed as follows: 

• The Medicaid and air quality data sets were linked (Hypothesis 1);
• Indicators for the urban increment of air pollution were developed by estimating background pollutant levels derived from measurements at outlying and upwind monitoring sites and subtracting these values from measurements monitored in Detroit.  Associations between the regional and urban increments of specific criteria air pollutants (CAPs – PM₁₀, PM_2.5, O₃, and SO₂) and daily urgent care use for asthma were determined (Hypothesis 2);
• Maps showing the spatial patterns of traffic-related pollutants using a geographical information system (GIS) analysis and simplified dispersion models were constructed.  Traffic data included total and commercial vehicle flows; the latter was a surrogate for heavy-diesel vehicles.  We began to classify the likely impact of traffic and other local pollutant sources on each Medicaid claim during the study period using the children’s residence location (each of which has been previously geo-coded (Hypothesis 3); and
• Residence location of each child making an asthma-related Medicaid claim was classified with regard to potential exposure from local emission sources; controls were selected randomly from claims for non-respiratory related events and appropriately matched to the asthma claims; and analysis was initiated to determine the relative probability of asthma-related morbidity in areas affected and not affected by local pollution sources using case/control methods, including multi-nominal multiple logistic regression models to analyze subtypes of asthma claims (Hypothesis 4). 

In Project Year 3, all five Specific Aims were addressed as follows:

• The relationship between daily fluctuations in pollutant concentrations and daily urgent care use was investigated using a longitudinal analysis employing case/cross-over Poisson (time series) regression models (Hypothesis 1);
• The analyses to examine relationships between regional and urban increments of specific CAPs and asthma outcomes were completed (started in year 2; Hypothesis 2);
• The classification of the likely impact of traffic and other local pollutant sources on each Medicaid claim was completed and efforts to determine the effect of traffic and other local pollutant sources on the strength of the association between daily asthma-related morbidity and daily air pollution exposures, using the longitudinal models developed in this project, was started and almost completed (Hypothesis 3);
• The case control study was completed to determine the relative probability of asthma-related morbidity in areas affected and not affected by local pollution sources, including multi-nomial multiple logistic regression models to analyze subtypes of asthma claims (Hypothesis 4); and
• Three scenarios portraying reasonable but contrasting future emission patterns were derived, including (1) current conditions; (2) reduced emissions from local mobile sources; and (3) reduced regional transport (Hypothesis 5).

In Project Year 4 (no-cost extension), Specific Aims 3 and 5 were addressed as follows:

• Assessment of the effects of traffic and other local pollutant sources on the strength of the association between daily asthma-related morbidity and daily air pollution exposures, using the longitudinal models developed in this project, was completed (started in year 3; Hypothesis 3);
• Air pollution impacts were estimated for each of three scenarios portraying future emission patterns (see Project Year 3 above) using the results of the longitudinal models (Hypotheses 1, 2, and 3) and results of the spatial analysis (Hypothesis 4; Hypothesis 5).
• Evaluated the uncertainty in the indicators, using both the estimated error as well as cross-validations that compared results across each study year.
• Analyzed and compared indicators for the spatial and temporal modes, including effects of prediction uncertainty on both population and individual means.
• We developed four manuscripts based on our work (see publications).  We also have developed poster and oral presentations for team members to present at scientific meetings and conferences.  Writing manuscripts and presenting our results will continue beyond the project period.

URLs/Downloads:

Final Progress Report

2009 Progress Report

2010 Progress Report

2008 Progress Report

Record Details:

Record Type:PROJECT( ABSTRACT )

Start Date:09/30/2007

Completion Date:09/29/2010

Record ID: 200531

Show Additional Record Data

Related Organizations:

Role :OWNER

Organization Name :MICHIGAN DEPARTMENT OF COMMUNITY HEALTH

Mailing Address :Capitol View Building
201 Townsend Street

Citation :Lansing

State :MI

Zip Code :48913



Role :OWNER

Organization Name :UNIVERSITY OF MICHIGAN - ANN ARBOR

Organization Name :ATMOSPHERIC, OCEANIC AND SPACE SCIENCE DEPT.

Citation :Ann Arbor

State :MI

Zip Code :48109



Role :OWNER

Organization Name :SCHOOL OF PUBLIC HEALTH AND COLLEGE OF ENGINEERING

Citation :Ann Arbor

State :MI

Zip Code :48109

Project Information:

Approach :

The DAMAT study will integrate: Medicaid data (pediatric asthma-related hospitalizations, emergency department visits and urgent care visits) among Detroit children from January 1, 2004 to December 31, 2006; geocoding data providing residence of children; air quality data from MDEQ; traffic data from the Michigan Department of Transportation; air emission data from the EPA Toxic Inventory Release System; and demographic data from the US Census. Following initial descriptive analyses, crude univariate analyses of urgent care outcomes and exposures 1-5 days prior to the daily counts will be completed. Longitudinal analyses using multivariate case-crossover Poisson models will relate daily asthma events to concentrations of ambient pollutants. Spatial analyses using case/control methods including multinominal multiple logistic regression models will evaluate whether children living in areas affected by traffic and industrial emissions have higher relative risks for severe asthma events. Using the asthma morbidity indicators, health impacts and uncertainties will be demonstrated for three emission/ concentration scenarios.

Cost :$499,777.00

Research Component :Health Effects

Project IDs:

ID Code :R833628

Project type :EPA Grant