Geographic Information Systems in Community-Based Gerontological Research and Practice

Abstract

Geographic information systems (GIS) can assist researchers and practitioners engaged in community-specific analyses that focus on older populations and their resource environments. Although some gerontologists may be using GIS for data visualization (i.e., to present data in map form), GIS spatial analytical functions appear to be underused in studies of older populations. This article examines the capacity and potential of GIS in gerontological research and practice by (a) briefly defining GIS; (b) describing the utility of some basic GIS visualization and spatial analytical methods using an illustrative, community-based gerontological study; and (c) discussing challenges and opportunities in the application of this information technology.

Colocation of older adults with successful aging based on objective and subjective measures

“…Such patterns are important for applied research in community-specific studies of older populations and their resource environments (Hirshorn & Stewart, 2003;Liu & Engels, 2012), as they provide important information about the needs of older people. Yet, despite the unprecedented demographic shift in the age structure of the population, "the connection between geographical inquiry and gerontology remains tenuous" (Cutchin, 2009, p. 440).…”

Ageing in place and ageing with migration in the transitional context of urban China: A case study of ageing communities in Guangzhou

“…Michael, Green, & Farquhar, 2006;Phillips, Siu, Yeh, & Cheng, 2005;Townshend, 2002). Spatial analysis with GIS can help us better understand community-based gerontological issues (Hirshorn & Stewart, 2003).…”

Piloting the Geographic Information System (GIS) Methodology as an Analytic Tool for Subjective Wellbeing Research

“…GIS has been incorporated into a number of area based public health research projects including investigations of substance abuse (Chaix et al 2005;Mason et al 2004), gerontology (Hirshorn and Stewart 2003), obesity (Tilt et al 2007) and gambling (Rush et al 2007). However, there are very few studies that have explored how GIS can be used to understand SWB.…”