Using Geographic Information Systems (GIS) to Optimize and Enhance Community Health Assessment

2.50
Hdl Handle:
http://hdl.handle.net/10755/156873
Type:
Presentation
Title:
Using Geographic Information Systems (GIS) to Optimize and Enhance Community Health Assessment
Abstract:
Using Geographic Information Systems (GIS) to Optimize and Enhance Community Health Assessment
Conference Sponsor:Sigma Theta Tau International
Conference Year:2002
Conference Date:July, 2002
Author:Faruque, Fazlay
P.I. Institution Name:University of Mississippi Medical Center
Title:Assistant Professor
Objective: To describe the use of Geographic Information Systems (GIS) to enhance limited study resources while optimizing the sample representation. Design: Although the application of GIS in health science is relatively new, it is growing fast because of the spatial analytical capabilities of GIS. Location of the subjects, their communities and healthcare infrastructure-all are spatial in nature. GIS in health science research starts with exploratory data analysis, followed by hypothesis generation, and ends with hypothesis testing. In this study, the exploratory data analysis produced two research questions: 1) will the survey sites located within the low-income and densely populated areas generate a high number of uninsured and underinsured samples? and 2)will the logistically distributed survey sites generate spatially representative samples for the county?. Population: Geographic distribution of the population in this county is diverse both in socio-economic conditions and rural and urban settings. The number of households in Hinds County, Mississippi, USA is 91,030 with a total population of 250,800 (2000 Census). Approximately 85% of the people live in the cities and incorporated areas, with 73% within the City of Jackson, the state capitol of Mississippi, USA. According to the 1990 Census, median household income was $24,676 for Hinds County and $23,270 for the city of Jackson. The city of Jackson lost 11,650 people between census years 1990 and 2000, which will most likely be reflected in the next economic census because of further economic distress in the city. Due to the above facts, 10 out of 17 survey sites were located within the city of Jackson , an urban area, yielding 441 interviewees and the remaining 7 sites were located beyond the Jackson city limits, an rural area yielding 319 interviewees. Sample: A cluster sample (N=760) of Hinds county residents was obtained from community settings (shopping malls, grocery stores, a community college and shelters) located within low-income and high-density communities identified via GIS mapping. Setting: Hinds County, Mississippi, USA. Year: 2001. Variables Studied Together: 1) Level of reported income per census block group(area of demarcation during the census) , 2) Population density per census block group, 3) Location of survey centers, 4) Location of sampled households, and 5)Location of healthcare services. Methods: First, through GIS, the county was examined by population density and income. Census block groups with population density more than 2000 persons per square mile and median household income less than $30,000 were identified. Potential survey centers within these areas were studied for their suitability based on location, type, and number of people who access the facility (see Section III). Permission to map the residence-locations of the interviewees was obtained during the survey. Post-survey steps include geocoding the residence-locations, analyzing the spatial distribution of residences, and calculating the number of interviewees within each census geographic unit. Conclusions: Data collection was completed in July 2001. Analysis will be completed in the fall of 2001. Findings: Preliminary findings suggest a strong link between the sample characteristics and the county data in relationship to health status, health services utilization and financial health care recourses. Final data will be presented at the conference. Implications: Use of GIS technology and existing data have been proven to be effective in conducting surveys for community health status. In future studies, the survey locations will be refined to further optimize the representation of assessment. GIS will be used to study the impact of change in survey locations on sample characteristics.

Repository Posting Date:
26-Oct-2011
Date of Publication:
Jul-2002
Sponsors:
Sigma Theta Tau International

Full metadata record

DC FieldValue Language
dc.typePresentationen_GB
dc.titleUsing Geographic Information Systems (GIS) to Optimize and Enhance Community Health Assessmenten_GB
dc.identifier.urihttp://hdl.handle.net/10755/156873-
dc.description.abstract<table><tr><td colspan="2" class="item-title">Using Geographic Information Systems (GIS) to Optimize and Enhance Community Health Assessment</td></tr><tr class="item-sponsor"><td class="label">Conference Sponsor:</td><td class="value">Sigma Theta Tau International</td></tr><tr class="item-year"><td class="label">Conference Year:</td><td class="value">2002</td></tr><tr class="item-conference-date"><td class="label">Conference Date:</td><td class="value">July, 2002</td></tr><tr class="item-author"><td class="label">Author:</td><td class="value">Faruque, Fazlay</td></tr><tr class="item-institute"><td class="label">P.I. Institution Name:</td><td class="value">University of Mississippi Medical Center</td></tr><tr class="item-author-title"><td class="label">Title:</td><td class="value">Assistant Professor</td></tr><tr class="item-email"><td class="label">Email:</td><td class="value">ffaruque@son.umsmed.edu</td></tr><tr><td colspan="2" class="item-abstract">Objective: To describe the use of Geographic Information Systems (GIS) to enhance limited study resources while optimizing the sample representation. Design: Although the application of GIS in health science is relatively new, it is growing fast because of the spatial analytical capabilities of GIS. Location of the subjects, their communities and healthcare infrastructure-all are spatial in nature. GIS in health science research starts with exploratory data analysis, followed by hypothesis generation, and ends with hypothesis testing. In this study, the exploratory data analysis produced two research questions: 1) will the survey sites located within the low-income and densely populated areas generate a high number of uninsured and underinsured samples? and 2)will the logistically distributed survey sites generate spatially representative samples for the county?. Population: Geographic distribution of the population in this county is diverse both in socio-economic conditions and rural and urban settings. The number of households in Hinds County, Mississippi, USA is 91,030 with a total population of 250,800 (2000 Census). Approximately 85% of the people live in the cities and incorporated areas, with 73% within the City of Jackson, the state capitol of Mississippi, USA. According to the 1990 Census, median household income was $24,676 for Hinds County and $23,270 for the city of Jackson. The city of Jackson lost 11,650 people between census years 1990 and 2000, which will most likely be reflected in the next economic census because of further economic distress in the city. Due to the above facts, 10 out of 17 survey sites were located within the city of Jackson , an urban area, yielding 441 interviewees and the remaining 7 sites were located beyond the Jackson city limits, an rural area yielding 319 interviewees. Sample: A cluster sample (N=760) of Hinds county residents was obtained from community settings (shopping malls, grocery stores, a community college and shelters) located within low-income and high-density communities identified via GIS mapping. Setting: Hinds County, Mississippi, USA. Year: 2001. Variables Studied Together: 1) Level of reported income per census block group(area of demarcation during the census) , 2) Population density per census block group, 3) Location of survey centers, 4) Location of sampled households, and 5)Location of healthcare services. Methods: First, through GIS, the county was examined by population density and income. Census block groups with population density more than 2000 persons per square mile and median household income less than $30,000 were identified. Potential survey centers within these areas were studied for their suitability based on location, type, and number of people who access the facility (see Section III). Permission to map the residence-locations of the interviewees was obtained during the survey. Post-survey steps include geocoding the residence-locations, analyzing the spatial distribution of residences, and calculating the number of interviewees within each census geographic unit. Conclusions: Data collection was completed in July 2001. Analysis will be completed in the fall of 2001. Findings: Preliminary findings suggest a strong link between the sample characteristics and the county data in relationship to health status, health services utilization and financial health care recourses. Final data will be presented at the conference. Implications: Use of GIS technology and existing data have been proven to be effective in conducting surveys for community health status. In future studies, the survey locations will be refined to further optimize the representation of assessment. GIS will be used to study the impact of change in survey locations on sample characteristics.<br/><br/></td></tr></table>en_GB
dc.date.available2011-10-26T15:13:27Z-
dc.date.issued2002-07en_GB
dc.date.accessioned2011-10-26T15:13:27Z-
dc.description.sponsorshipSigma Theta Tau Internationalen_GB
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