Linking Geospatial Information with Public Health Outcomes: Modeling Asthma Morbidity Across an Urban International Border: Early Findings

2.50
Hdl Handle:
http://hdl.handle.net/10755/158436
Type:
Presentation
Title:
Linking Geospatial Information with Public Health Outcomes: Modeling Asthma Morbidity Across an Urban International Border: Early Findings
Abstract:
Linking Geospatial Information with Public Health Outcomes: Modeling Asthma Morbidity Across an Urban International Border: Early Findings
Conference Sponsor:Midwest Nursing Research Society
Conference Year:2009
Author:Weglicki, Linda, PhD, RN, MSN
P.I. Institution Name:Wayne State University
Title:College of Nursing
Contact Address:5557 Cass Avenue, 368 Cohn, Detroit, MI, 48202, USA
Contact Telephone:313-577-5502
Co-Authors:L.S. Weglicki, H. Krouse, D. Raymond, College of Nursing, Wayne State University, Detroit, MI; L. Larry, Geology, Wayne State University, Detroit, MI; J. Booza, Family Medicine, Wayne State University, Detroit, MI; J. Reiners, Institute of Environmental H
Background: Asthma affects nearly 300 million people worldwide. Epidemiological studies show a significant association between asthma with pollutants (e.g., ozone, nitrogen oxides). The purpose of this research is to develop spatial-temporal models using geographic information systems (GIS) to identify and predict environmentally-induced health conditions (asthma) in adults and children in and across an international border?Detroit, Michigan and Windsor, Ontario. Land use regression (LUR) and air dispersion modeling are being used to predict exposure to air pollutants and to link environmental conditions to asthma morbidity. Methods: There are three phases in this international, multi-institutional, and multi-disciplinary study. Phase I consisted of modeling and collection of air quality data (completed). Phase II included the collection and evaluation of administrative data asthma outcome information (completed). Phase III (in progress) involves the integration of environmental and health outcome data into a GIS framework and then analyzed to determine the spatial relationships between environmental and health information. Results: LUR (using postal codes) and air dispersion modeling resulted in the allocation and placement of 34 active/passive and 34 passive-only air samplers in Detroit and 16 active/passive and 16 passive-only air samplers in Windsor. Samplers were deployed at secured sites throughout both cities for two-weeks in September, 2008. Analyses will be reported for a number of containments including nitrogen dioxide (NO2), sulfur dioxide (SO2), particulate matter (PM), volatile organic compounds (VOCs), and polycyclic aromatic hydrocarbons (PAHs). Implications: The ability to compare and contrast environmental indicators with specific health outcomes (i.e., asthma) will aid in the development of community, family, and school-based interventions that impact the control and management of asthma in children and adults. This study will establish a geospatial and epidemiologic data framework and meta-data resources, which will be the foundation for translational research applied to other diseases and health outcomes (e.g., cardiovascular disease, cancer).
Repository Posting Date:
26-Oct-2011
Date of Publication:
17-Oct-2011
Sponsors:
Midwest Nursing Research Society

Full metadata record

DC FieldValue Language
dc.typePresentationen_GB
dc.titleLinking Geospatial Information with Public Health Outcomes: Modeling Asthma Morbidity Across an Urban International Border: Early Findingsen_GB
dc.identifier.urihttp://hdl.handle.net/10755/158436-
dc.description.abstract<table><tr><td colspan="2" class="item-title">Linking Geospatial Information with Public Health Outcomes: Modeling Asthma Morbidity Across an Urban International Border: Early Findings</td></tr><tr class="item-sponsor"><td class="label">Conference Sponsor:</td><td class="value">Midwest Nursing Research Society</td></tr><tr class="item-year"><td class="label">Conference Year:</td><td class="value">2009</td></tr><tr class="item-author"><td class="label">Author:</td><td class="value">Weglicki, Linda, PhD, RN, MSN</td></tr><tr class="item-institute"><td class="label">P.I. Institution Name:</td><td class="value">Wayne State University</td></tr><tr class="item-author-title"><td class="label">Title:</td><td class="value">College of Nursing</td></tr><tr class="item-address"><td class="label">Contact Address:</td><td class="value">5557 Cass Avenue, 368 Cohn, Detroit, MI, 48202, USA</td></tr><tr class="item-phone"><td class="label">Contact Telephone:</td><td class="value">313-577-5502</td></tr><tr class="item-email"><td class="label">Email:</td><td class="value">lweglicki@hotmail.com</td></tr><tr class="item-co-authors"><td class="label">Co-Authors:</td><td class="value">L.S. Weglicki, H. Krouse, D. Raymond, College of Nursing, Wayne State University, Detroit, MI; L. Larry, Geology, Wayne State University, Detroit, MI; J. Booza, Family Medicine, Wayne State University, Detroit, MI; J. Reiners, Institute of Environmental H</td></tr><tr><td colspan="2" class="item-abstract">Background: Asthma affects nearly 300 million people worldwide. Epidemiological studies show a significant association between asthma with pollutants (e.g., ozone, nitrogen oxides). The purpose of this research is to develop spatial-temporal models using geographic information systems (GIS) to identify and predict environmentally-induced health conditions (asthma) in adults and children in and across an international border?Detroit, Michigan and Windsor, Ontario. Land use regression (LUR) and air dispersion modeling are being used to predict exposure to air pollutants and to link environmental conditions to asthma morbidity. Methods: There are three phases in this international, multi-institutional, and multi-disciplinary study. Phase I consisted of modeling and collection of air quality data (completed). Phase II included the collection and evaluation of administrative data asthma outcome information (completed). Phase III (in progress) involves the integration of environmental and health outcome data into a GIS framework and then analyzed to determine the spatial relationships between environmental and health information. Results: LUR (using postal codes) and air dispersion modeling resulted in the allocation and placement of 34 active/passive and 34 passive-only air samplers in Detroit and 16 active/passive and 16 passive-only air samplers in Windsor. Samplers were deployed at secured sites throughout both cities for two-weeks in September, 2008. Analyses will be reported for a number of containments including nitrogen dioxide (NO2), sulfur dioxide (SO2), particulate matter (PM), volatile organic compounds (VOCs), and polycyclic aromatic hydrocarbons (PAHs). Implications: The ability to compare and contrast environmental indicators with specific health outcomes (i.e., asthma) will aid in the development of community, family, and school-based interventions that impact the control and management of asthma in children and adults. This study will establish a geospatial and epidemiologic data framework and meta-data resources, which will be the foundation for translational research applied to other diseases and health outcomes (e.g., cardiovascular disease, cancer).</td></tr></table>en_GB
dc.date.available2011-10-26T21:03:05Z-
dc.date.issued2011-10-17en_GB
dc.date.accessioned2011-10-26T21:03:05Z-
dc.description.sponsorshipMidwest Nursing Research Societyen_GB
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