Measuring the Food Environment Using Geographic Information Systems: A Methodological Review

UMR INSERM U 557/INRA U 1125/CNAM, University Paris 13, CRNH IdF, Bobigny, France.
Public Health Nutrition (Impact Factor: 2.68). 11/2010; 13(11):1773-85. DOI: 10.1017/S1368980010000753
Source: PubMed


Through a literature review, we investigated the geographic information systems (GIS) methods used to define the food environment and the types of spatial measurements they generate.
Review study.
Searches were conducted in health science databases, including Medline/Pubmed, PsycINFO, Francis and GeoBase. We included studies using GIS-based measures of the food environment published up to 1 June 2008.
Twenty-nine papers were included. Two different spatial approaches were identified. The density approach quantifies the availability of food outlets using the buffer method, kernel density estimation or spatial clustering. The proximity approach assesses the distance to food outlets by measuring distances or travel times. GIS network analysis tools enable the modelling of travel time between referent addresses (home) and food outlets for a given transportation network and mode, and the assumption of travel routing behaviours. Numerous studies combined both approaches to compare food outlet spatial accessibility between different types of neighbourhoods or to investigate relationships between characteristics of the food environment and individual food behaviour.
GIS methods provide new approaches for assessing the food environment by modelling spatial accessibility to food outlets. On the basis of the available literature, it appears that only some GIS methods have been used, while other GIS methods combining availability and proximity, such as spatial interaction models, have not yet been applied to this field. Future research would also benefit from a combination of GIS methods with survey approaches to describe both spatial and social food outlet accessibility as important determinants of individual food behaviours.

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Available from: Christiane Weber, Aug 11, 2015
    • "Due to the abundance of food-mapping literature captured in the USDA ERS review and Charreire et al.'s (2010) methodological review, this review is limited to articles and projects published after 2008. However, the review includes research that utilizes mapping in food justice, food sovereignty, consumption , land use, food choice, food trade, consumer behavior , food safety, urban agriculture, and agricultural systems analysis, topics that were not addressed in the 2009 USDA ERS or Charreire et al. (2010) review. If researchers used GIS software to calculate impact of proximity or density without actually mapping the results (e.g., Dunn et al. 2012), they were not included. "
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    ABSTRACT: Various mapping methodologies have been used to explore complex social, economic, and environmental components of the food system. Planning scholars, geographers, public health officials, and community organizations have created maps to better understand disparities in the food environment. This review provides an analysis of the nature of geographic information systems mapping in scholarly research and web-based food mapping since 2008. Our review of thirty-four journal articles and seventy web-mapping projects covers the purpose, study area, topics, methods, and application of food mapping research and initiatives. Scholars and community stakeholders will benefit from this review of methodologies to inform their research and policy initiatives.
    Journal of Planning Literature 02/2016; DOI:10.1177/0885412215599425 · 1.19 Impact Factor
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    • "The bulk of research has described the geographic distribution of various types of food stores as well as the selection, quality, and price of different kinds of food found within them in a single large urban area. 3 There is also research that analyzes customers' and food business proprietors' perceptions of the food environment (Charreire et al. 2010; Reisig and Hobbiss 2000; Zenk et al. 2011). However, most research on healthy food availability focuses on large cities with populations of more than several hundred thousand. "
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    ABSTRACT: This article examines the relationships between neighborhood racial and income composition and healthy food availability. We explore the extent to which physical and social isolation affects healthy food availability for groups marginalized by race and class in a context largely missing from the literature. We use census tract data and five-year estimates from the American Community Survey to produce maps illustrating the patterns of race and income composition in Topeka, Kansas. Included in these maps are data points illustrating the distribution of stores offering healthy foods. We find that, as in the large metro areas analyzed thus far, the distribution of healthy food stores in Topeka is similarly patterned. Blacker (and poorer) neighborhoods tend to have the lowest levels of healthy food availability. We conclude with a discussion of the relevance of this work to the knowledge base regarding food environments and health in the United States.
    Rural Sociology 10/2015; DOI:10.1111/ruso.12063 · 1.89 Impact Factor
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    • "2) Recently, Burgoine et al. [57] found food environment measures of density and proximity to be highly correlated, and concluded that the heterogeneity found in GIS-based exposure metrics within the published literature may not be as problematic as previously argued [58]. Therefore, it might be particularly important to focus future research on combining GIS-based objective measurement of the community food environment with self-report measures of the community food environment, as well as measures of the consumer food environment. "
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    ABSTRACT: Background While there is a growing body of research on food environments for children, there has not been a published comprehensive review to date evaluating food environments outside the home and school and their relationship with diet in children. The purpose of this paper is to review evidence on the influence of the community and consumer nutrition environments on the diet of children under the age of 18 years. Methods Our search strategy included a combination of both subject heading searching as well as natural language, free-text searching. We searched nine databases (MEDLINE, Web of Science, CINAHL, Embase, Scopus, ProQuest Public Health, PsycINFO, Sociological Abstracts, and GEOBASE) for papers published between 1995 and July 2013. Study designs were included if they were empirically-based, published scholarly research articles, were focused on children as the population of interest, fit within the previously mentioned date range, included at least one diet outcome, and exposures within the community nutrition environment (e.g., location and accessibility of food outlets), and consumer nutrition environment (e.g., price, promotion, and placement of food choices). Results After applying exclusion and inclusion criteria, a total of 26 articles were included in our review. The vast majority of the studies were cross-sectional in design, except for two articles reporting on longitudinal studies. The food environment exposure(s) included aspects of the community nutrition environments, except for three that focused on the consumer nutrition environment. The community nutrition environment characterization most often used Geographic Information Systems to geolocate participants’ homes (and/or schools) and then one or more types of food outlets in relation to these. The children included were all of school age. Twenty-two out of 26 studies showed at least one positive association between the food environment exposure and diet outcome. Four studies reported only null associations. Conclusions This review found moderate evidence of the relationship between the community and consumer nutrition environments and dietary intake in children up to 18 years of age. There is wide variation in measures used to characterize both the community and consumer nutrition environments and diet, and future research should work to decrease this heterogeneity.
    BMC Public Health 05/2014; 14(1):522. DOI:10.1186/1471-2458-14-522 · 2.26 Impact Factor
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