DEVELOPMENT OF EXPOSURE AND HEALTH OUTCOME INDICATORS FOR THOSE WITH ASTHMA OR OTHER RESPIRATORY PROBLEMS
Impact/Purpose:
The research will investigate the feasibility of combining existing environmental monitoring and health survey data (California Health Interview Survey (CHIS)) to develop health outcome indicators, such as asthma-related emergency department (ED) visits, doctor’s visits, absences from school/work, medication use, and frequency of asthma symptoms for those with asthma, as well as asthma-like symptoms, doctor’s visits and absences from work/school due to breathing problems for those without asthma diagnoses.
Description:
The results are expected to provide a comprehensive set of outcome-based health indicators to signal the impact of changes in environmental conditions, management approaches, and policies on asthma and other respiratory problems. Linkages found between the proposed exposure metrics and health outcomes can inform the public and policy makers about the impact of current air quality regulations or programs and provide valuable feedbacks for improving regulatory or other actions.
Record Details:
Record Type:PROJECT(
ABSTRACT
)
Start Date:09/01/2007
Completion Date:08/31/2010
Record ID:
205716
Keywords:
INDOOR AIR, MOBILE SOURCES, RISK, HEALTH EFFECTS, ECOLOGICAL EFFECTS, VULNERABILITY, PUBLIC POLICY, DECISION MAKING, PUBLIC GOOD, BAYESIAN, SOCIO-ECONOMIC, EPIDEMIOLOGY, MODELING, ANALYTICAL, MEASUREMENT METHODS, NORTHWEST, CALIFORNIA, CA, EPA REGION 9,
Related Organizations:
Role
:OWNER
Organization Name
:UNIVERSITY OF CALIFORNIA - LOS ANGELES
Mailing Address
:405 Hilgard Ave
Citation
:Los Angeles
State
:CA
Zip Code
:90024
Project Information:
Approach
:The research will first use Geographic Information System (GIS) software to link CHIS 2003 and 2005 respondents with various exposure indicators: 1) Long-term exposures to criteria air pollutants (O3, PM10, PM2.5, and NO2) from the nearest air monitors; 2) geostatistical exposure modeling (e.g., kriging for O3, and land use regression (LUR) for PM10, PM2.5, NOx, NO and NO2); and 3) residential traffic density and proximity to roadways. With this combined data, then statistical modeling will be used to quantify spatial and temporal links between the exposure indicators and health outcome indicators after adjusting for other risk factors, such as secondhand smoking.
Cost
:$500,000.00
Research Component
:Health Effects
Project IDs:
ID Code
:R833629
Project type
:EPA Grant