The relationship between older adult migration and destination characteristics in Georgia. (July 2021)

• Record Type: Journal Article
• Authors: Zhang, Xuan; Mu, Lan; Shannon, Jerry
• Is Part Of: Applied geography. Volume 132(2021)
• Publication Date: 2021-07
• Subjects: Older adults -- Migration -- Long-term care (LTC) -- Linear regression model -- Decision tree; Geography -- Periodicals; Human geography -- Periodicals; Human ecology -- Periodicals; 910
• DOI: 10.1016/j.apgeog.2021.102464
• Languages: English
• ISSNs: 0143-6228

Abstract

Abstract: Older adult migration patterns are shaped by distinct sets of factors for intrastate versus interstate and younger (65–74) versus aged (75+) older migrants. Moving decisions relate to individual factors and the destination's characteristics, including the climate, amenity, and cost of living. Previous studies have rarely integrated destination characteristics such as long-term care (LTC) facilities, affordable housing, or geriatricians. This study addresses this gap by examining older adult migration by age group and migration type. We proposed a variable structure describing six living environment categories of destination counties and further investigated the relationship between migrants and destination characteristics. We identified geographical patterns of migration and used linear regression and decision tree models to analyze migrants' destination variables. Results indicated four subgroups of older migrants have different high-high clusters in or near the Atlanta region and low-low clusters in South Georgia. Linear regression models quantified the relationship and indicated variables such as LTC facility bed and affordable housing availability should be considered in older adult migration analysis. Decision tree models revealed that different variables are associated with certain county groups, such as core Atlanta and rural counties. Our findings highlighted the variety of variables shaping the migration of older adult subgroups. Highlights: Older migration studies should add long-term care and affordable housing variables. Migration of older adults' subgroups are related to different sets of variables. Recreational amenities and hospital availability are not significant with migration. Decision trees categorized counties into groups with various migration relations. Linear models and decision tree analysis reveal various aspects of older migration.