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Data on location and retail price of a standard food basket in supermarkets across New York City
Previous work has suggested that the price of food sold at supermarkets may vary according to the socioeconomic characteristics of a neighborhood. Given the importance of food prices in securing access to food, understanding how food prices vary across neighborhoods is crucial to assessing affordabi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10293947/ https://www.ncbi.nlm.nih.gov/pubmed/37383762 http://dx.doi.org/10.1016/j.dib.2023.109222 |
Sumario: | Previous work has suggested that the price of food sold at supermarkets may vary according to the socioeconomic characteristics of a neighborhood. Given the importance of food prices in securing access to food, understanding how food prices vary across neighborhoods is crucial to assessing affordability. To study food pricing in New York City (NYC) a defined standard food basket (SFB) was collected in supermarkets across NYC neighborhoods. A dataset was created that includes pricing data collected in-person for ten pre-determined food items from 163 supermarkets across 71 of the 181 NYC neighborhoods during March through August of 2019. Included in these data are raw and processed pricing data files that illustrate the complexity of standardizing pricing across items. An additional dataset includes neighborhood-level variables of selected socioeconomic and demographic characteristics from the 2014–2018 American Community Survey that is publicly available via the Census API. The pricing data and the data on neighborhood-level characteristics were merged. Basic statistical measures suggest some distributional differences in the price of a SFB by socioeconomic differences between neighborhoods. This database can be used to describe spatial patterns in food pricing in a dense urban setting, while exploring pricing inequities across neighborhoods. In addition, by working with these data, researchers, policy analysts and educators will gain an understanding of the methodologies used to generate pricing data for an SFB. |
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