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      Generating GPS activity spaces that shed light upon the mobility habits of older adults: a descriptive analysis

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          Abstract

          Background

          Measuring mobility is critical for understanding neighborhood influences on older adults’ health and functioning. Global Positioning Systems (GPS) may represent an important opportunity to measure, describe, and compare mobility patterns in older adults.

          Methods

          We generated three types of activity spaces (Standard Deviation Ellipse, Minimum Convex Polygon, Daily Path Area) using GPS data from 95 older adults in Vancouver, Canada. Calculated activity space areas and compactness were compared across sociodemographic and resource characteristics.

          Results

          Area measures derived from the three different approaches to developing activity spaces were highly correlated. Participants who were younger, lived in less walkable neighborhoods, had a valid driver’s license, had access to a vehicle, or had physical support to go outside of their homes had larger activity spaces. Mobility space compactness measures also differed by sociodemographic and resource characteristics.

          Conclusions

          This research extends the literature by demonstrating that GPS tracking can be used as a valuable tool to better understand the geographic mobility patterns of older adults. This study informs potential ways to maintain older adult independence by identifying factors that influence geographic mobility.

          Electronic supplementary material

          The online version of this article (doi:10.1186/1476-072X-13-51) contains supplementary material, which is available to authorized users.

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          Most cited references76

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          Neighborhood environment in studies of health of older adults: a systematic review.

          Epidemiologists and public health researchers are studying neighborhood's effect on individual health. The health of older adults may be more influenced by their neighborhoods as a result of decreased mobility. However, research on neighborhood's influence on older adults' health, specifically, is limited. Recent studies on neighborhood and health for older adults were identified. Studies were identified through searches of databases including PsycINFO, CINAHL, PubMed, Academic Search Premier, Ageline, Social Science Citation Index, and Health Source. Criteria for inclusion were as follows: human studies; English language; study sample included adults aged > or =55 years; health outcomes, including mental health, health behaviors, morbidity, and mortality; neighborhood as the primary exposure variable of interest; empirical research; and studies that included > or =10 neighborhoods. Air pollution studies were excluded. Five hundred thirty-eight relevant articles were published during 1997-2007; a total of 33 of these articles met inclusion criteria. The measures of objective and perceived aspects of neighborhood were summarized. Neighborhood was primarily operationalized using census-defined boundaries. Measures of neighborhood were principally derived from objective sources of data; eight studies assessed perceived neighborhood alone or in combination with objective measures. Six categories of neighborhood characteristics were socioeconomic composition, racial composition, demographics, perceived resources and/or problems, physical environment, and social environment. The studies are primarily cross-sectional and use administrative data to characterize neighborhood. These studies suggest that neighborhood environment is important for older adults' health and functioning.
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            A review of models of home range for animal movement

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              Activity space environment and dietary and physical activity behaviors: a pilot study.

              This study examined relationships among individual demographics, environmental features (e.g., fast food outlet density, park land use) of residential neighborhoods and activity spaces, and weight-related behaviors (diet, physical activity). Participants' movement was tracked for 7 days using global positioning systems (GPS). Two activity space measures (one standard deviation ellipse, daily path area) were derived from the GPS data. Activity spaces were generally larger than residential neighborhoods; environmental features of residential neighborhoods and activity spaces were weakly associated; and some activity space environmental features were related to dietary behaviors. Activity spaces may provide new insights into environmental influences on obesity-related behaviors. Copyright © 2011 Elsevier Ltd. All rights reserved.
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                Author and article information

                Contributors
                hirsch.jana@gmail.com
                mwinters@sfu.ca
                pjclarke@umich.edu
                heather.mckay@ubc.ca
                Journal
                Int J Health Geogr
                Int J Health Geogr
                International Journal of Health Geographics
                BioMed Central (London )
                1476-072X
                12 December 2014
                2014
                : 13
                : 51
                Affiliations
                [ ]Centre for Hip Health and Mobility and Department of Medicine, University of British Columbia, 2635 Laurel Street, Vancouver, British Columbia V5Z 1 M9 Canada
                [ ]Carolina Population Center, University of North Carolina at Chapel Hill, 206 West Franklin St, Chapel Hill, NC 27516 USA
                [ ]Faculty of Health Sciences, Simon Fraser University, 8888 University Drive, Burnaby, British Columbia V5A 1S6 Canada
                [ ]Institute for Social Research, University of Michigan, 426 Thompson Street, Ann Arbor, MI 48104 USA
                [ ]Centre for Hip Health and Mobility and Department of Family Practice, University of British Columbia, 2635 Laurel Street, Vancouver, British Columbia V5Z 1 M9 Canada
                Article
                624
                10.1186/1476-072X-13-51
                4326206
                25495710
                047aae03-1ac7-4a58-8a8a-ab42bb961c74
                © Hirsch et al.; licensee BioMed Central. 2014

                This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 10 October 2014
                : 30 November 2014
                Categories
                Research
                Custom metadata
                © The Author(s) 2014

                Public health
                global positioning systems (gps),geographic information systems (gis),activity space,mobility,neighborhood attributes,older adults

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