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. 2012 Jun 27:11:22.
doi: 10.1186/1476-072X-11-22.

Using GPS technology to (re)-examine operational definitions of 'neighbourhood' in place-based health research

Affiliations

Using GPS technology to (re)-examine operational definitions of 'neighbourhood' in place-based health research

Bryan J Boruff et al. Int J Health Geogr. .

Abstract

Background: Inconsistencies in research findings on the impact of the built environment on walking across the life course may be methodologically driven. Commonly used methods to define 'neighbourhood', from which built environment variables are measured, may not accurately represent the spatial extent to which the behaviour in question occurs. This paper aims to provide new methods for spatially defining 'neighbourhood' based on how people use their surrounding environment.

Results: Informed by Global Positioning Systems (GPS) tracking data, several alternative neighbourhood delineation techniques were examined (i.e., variable width, convex hull and standard deviation buffers). Compared with traditionally used buffers (i.e., circular and polygon network), differences were found in built environment characteristics within the newly created 'neighbourhoods'. Model fit statistics indicated that exposure measures derived from alternative buffering techniques provided a better fit when examining the relationship between land-use and walking for transport or leisure.

Conclusions: This research identifies how changes in the spatial extent from which built environment measures are derived may influence walking behaviour. Buffer size and orientation influences the relationship between built environment measures and walking for leisure in older adults. The use of GPS data proved suitable for re-examining operational definitions of neighbourhood.

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Figures

Figure 1
Figure 1
Example of a GPS track for one walking trip and land-use exposure.
Figure 2
Figure 2
Example of the Spatial Extent of a RIC Line Buffer, RIC Ellipse Buffer, RIC Polygon Buffer and Variable Width Buffer.
Figure 3
Figure 3
Example of the Spatial Extent of Line-based Network Buffers, Polygon Network Buffers and Circular Buffers Used in the Study.

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