Authors: Xuan Zhang*, University of Georgia, Lan Mu, University of Georgia, Jerry Shannon, University of Georgia
Topics: Migration, Population Geography, Geographic Information Science and Systems
Keywords: Older population, migration, regression, GIS
Session Type: Paper
Presentation File: No File Uploaded
The United States is facing a significantly growing number of older adults (aged 65 and more). Compared with other age groups, older adults move for a distinct set of reasons. Even within older migrants, interstate and intrastate migration, or relatively young (65-74) and old (75 and more) older adults, may have different drivers and constraints. Past research revealed that moving decision is not only related to individual characteristics, such as race and education level, but also associated with destination’s characteristics, including the cost of living, climate, accessibility, among others. However, variables related to long-term care (LTC) facilities are rarely considered, even though the rocketing population indicates a growing demand for LTC services. There is a need to update the metrics for older population migration analysis. Focusing on Georgia, this study examined the older adults’ migration by migration types and age groups. We used linear regression and decision tree regression to analyze the relationship between the number of migrants and destination variables, and further visualized migration patterns in GIS. We considered six perspectives of the destination living environment, including the physical and built, climatic, healthcare, demographic and socioeconomic, recreational and cultural, and lastly, residential environment of the destination county. Results show interstate and intrastate migrations are associated with distinct variables in different directions and various magnitudes. Moreover, we found the number of young older migrants is negatively related to the cost of living index while the old older adults are positively associated with the cost of living index.
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