The rise of food banks and the challenge of matching food assistance with potential need: towards a spatially specific, rapid assessment approach

Christopher M. Bacon () and Gregory A. Baker
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Christopher M. Bacon: Santa Clara University
Gregory A. Baker: Santa Clara University

Agriculture and Human Values, 2017, vol. 34, issue 4, No 8, 899-919

Abstract: Abstract In the United States, food banks served an estimated 46 million people in 2015. A combination of government policy reforms and political economic trends contributed to the rising numbers of individuals relying on private food assistance in the US, the United Kingdom and other high-income countries. Although researchers frequently map urban food environments, this project is one of the first to map private food assistance and potential need at the census-tract scale. We utilize Geographic Information Systems, demographic data, and food assistance locations to develop a rapid assessment tool that could support food banks, pantries, soup kitchens, and government agencies that seek to answer the question of whether people with the greatest need have food distribution sites in close proximity. We define access based on distance and then calculate potential food insecurity using either poverty rates or a food insecurity index. We apply these methods in a case study analysis of Santa Clara County, California. Our findings suggest that food assistance distribution locations match the areas of potential need in more than 80% of urban census tracts. However, there are several potentially underserved locations and populations that could benefit from new food assistance operations. The poverty and index-based approaches show significant spatial overlap in mapped areas of high food insecurity and low access. The poverty only approach produces a higher estimate of food insecurity rates, is easier to calculate, and draws attention to the need to address poverty as a root cause of hunger.

Keywords: Food security; Food assistance; Food justice; Poverty; Food environments; Geographic information systems (GIS); Decision support (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s10460-017-9783-y

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