Literature DB >> 24958694

Identifying naturally occurring retirement communities: a spatial analysis.

Maricruz Rivera-Hernandez1, Takashi Yamashita2, Jennifer M Kinney3.   

Abstract

OBJECTIVES: Guided by the concept of "aging in place" and potential policy implications, the study analyzed naturally occurring retirement communities (NORCs; 40% or greater house owners and renters aged 65 years and older) and whether there were spatiotemporal patterns in Ohio between 2000 and 2010.
METHOD: Data were derived from the 2000 and 2010 census tracts. Geovisualization was used to visually examine the distribution of NORCs in 2000 and 2010. Global Moran's I was used to quantify the spatial distribution of NORCs in Ohio and Local Moran's I was used to identify clusters of NORCs (i.e., hot spots).
RESULTS: The number of NORCs slightly decreased despite the overall increase of the older population from 2000 to 2010. NORCs were identified in one of the 3 most populous counties (i.e., Cuyahoga) and its neighboring counties. A number of hot spots were identified in Cuyahoga County (among Ohio's most populous and NORC-rich counties), both in 2000 and 2010. There were different patterns including emerging, disappearing, and enduring NORCs and disproportionate distributions of NORCs across the state between 2000 and 2010. DISCUSSION: Locating NORCs could aid governments to create "aging in place" sensitive policies to address issues of independence, social care, health care, volunteerism, and community participation.
© The Author 2014. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Keywords:  Aging in place; Geographic information systems; Housing; Naturally occurring retirement communities; Population aging; Spatial analysis.

Mesh:

Year:  2014        PMID: 24958694      PMCID: PMC4786298          DOI: 10.1093/geronb/gbu077

Source DB:  PubMed          Journal:  J Gerontol B Psychol Sci Soc Sci        ISSN: 1079-5014            Impact factor:   4.077


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Authors:  Jason W Smith; Jennifer Knight Davis; Catherine C Quatman-Yates; Brittany L Waterman; Scott A Strassels; Jen D Wong; Victor K Heh; Holly E Baselice; Guy N Brock; Brian C Clark; John F P Bridges; Heena P Santry
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