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Spring 2005
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In the City of Toledo, Ohio, Senior Meal Sites Are Planned With GIS

Over time, senior (65+) populations change both demographically and geographically. For example, a study of residents in the city of Toledo, Ohio, indicated that from generation to generation the senior citizen population has tended to move out of the downtown area into the suburbs. Obviously, resources need to be located where the target population group is currently located rather than where it was located decades ago. GIS is a useful tool for understanding changes in the population and for developing service plans for providing health and social services.

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Distribution of persons aged 65 and older, Lucas County, Ohio, for specific years.

Ohio's Bowling Green State University studied patterns of senior population shifts across a 60-year time span. This information is useful for analyzing the patterns of location as the population becomes older and, accordingly, planning the location for a new hot meal site to service seniors. Yu Zhou, associate professor, and Bruce Smith, professor of the university's Department of Geography, studied three senior population patterns found in and around the city of Toledo.

First is the change of elderly populations. In 1940, the 65+ group accounted for only 4 percent of the population; in 2000 it accounted for 13 percent. Even though the county population decreased overall from 1970 to 2000, the elderly population continued to increase.

Second is the change in geographic distribution of this population. Based on census tract information from 1940–2000, spatial depiction reveals a pattern of population change in Toledo over six decades. During 1940–1950, the majority of seniors lived in Toledo's downtown area. Seniors of the 1960–1970 era lived just beyond the downtown area. The majority of the population who were seniors during the decade 1980–1990 were living in the suburban area. This pattern of moving outward is consistent throughout Toledo's population for seniors age 65+, as well as for seniors age 85+.

The third phenomenon considered is the distribution of services for the elderly. In the 1970s, six nutrition sites opened, which were all located in close proximity to Toledo's central business district. These sites were selected partially as a result of the concentration of senior citizens in that area. After the 1970s, 18 additional meal sites were established. Many of the newer facilities were opened in or close to the central business district even though the six original nutrition sites were continuing to operate in that general area. The maps clearly underscore the problem that although the population had changed, service access had not.

GIS is used to evaluate the efficiency of the location of services. A standard feature in ArcView is the ability to create buffers, which are useful for examining spatial relationships among features. Buffers are rings drawn around features at a specified distance from the features. With ArcView Network Analyst, buffers can be drawn around service centers based on road accessibility.

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Effect of the proposed meal site on elderly population.

By placing a two-mile road network buffer around meal sites and combining the map with a 65+ population layer, the GIS shows a problem with site access by the intended client population. Areas that were once residential are now predominated by businesses and, therefore, downtown site access zones overlap. But a significant number of the target clientele live outside the centers' access zones.

Selecting the best location for a new meal center is also supported by GIS because it provides insight for predicting "what if" scenarios, for example, "What if we placed the new site here or there?" GIS can calculate the usage for a proposed site to form a prediction of the use of services by the elderly. The use study indicates that of the 65+ population, 37.4 percent have taken advantage of the meal services provided at the program's 22 sites located in the area. By placing just one site in the suburban area where seniors currently live, the model predicts that total use of services would increase to 45.4 percent. One well-placed site would increase service use by 8 percent of the target population.

Including additional demographics in the model, such as race, gender, and income levels, can be useful in customizing the type of care the program offers a specific area's population. GIS is an effective tool for planning the most successful allocation of resources for targeted clientele.

For more information, contact Yu Zhou, associate professor, Bowling Green State University (tel.: 419-372-7828, e-mail: yzhou@bgnet.bgsu.edu). Information and maps were provided by Yu Zhou and Bruce Smith of the Department of Geography, Bowling Green State University.

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