کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
83351 | 158718 | 2014 | 9 صفحه PDF | دانلود رایگان |
• Food environments are assessed at an individual level.
• An extension of time geographic density estimation in GIS is utilized.
• Data from synthesized households are analyzed to explore spatial patterns.
• Spatially summarized individual experiences potentially reveal place-based differences in accessibility to food.
Within the geography, transportation, and public health communities there has been intense interest in better understanding the linkages between health outcomes such as obesity rates and people's access to healthy foods. In this nexus, personal access to healthy food is shaped by a number of individual and geographical factors including people's time available for shopping, the quality of proximal food vendors (e.g. supermarkets vs. convenience stores), and the nature of the transportation systems available to facilitate mobility. Building on recent research in disaggregate accessibility modeling, including that of time geography, this paper describes an individual-level modeling approach for quantifying peoples' food environments. The approach works by measuring the accessibility people have to local food shopping opportunities given their activity patterns and available time budgets. Individuals' food accessibility may be compared to one another and the underlying mobility afforded by the transportation system is accounted for. Moreover, the individual-level measure is such that it may be resolved to places, whereby the aggregation and mapping of multiple individuals' food accessibility experiences is possible. Hence, possible ‘deserts’ or areas of inaccessibility may be identified through a bottom-up analysis of the travel and mobility experience of a representative sample of individuals. These ideas are demonstrated with spatial data from a smaller urban area in Florida. Results show that individual and place-based differences in food accessibility may be delineated with the metrics.
Journal: Applied Geography - Volume 51, July 2014, Pages 99–107