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Assessing the Retail Food Environment in Madrid: An Evaluation of Administrative Data against Ground Truthing
Journal article   Open access   Peer reviewed

Assessing the Retail Food Environment in Madrid: An Evaluation of Administrative Data against Ground Truthing

Julia Díez, Alba Cebrecos, Iñaki Galán, Hugo Pérez-Freixo, Manuel Franco and Usama Bilal
International journal of environmental research and public health, v 16(19), p3538
21 Sep 2019
DOI: https://doi.org/10.3390/ijerph16193538
PMID: 31546670
Featured in Collection :   UN Sustainable Development Goals @ Drexel
url
https://doi.org/10.3390/ijerph16193538View
Published, Version of Record (VoR)CC BY V4.0,  Open

Abstract

Cities Commerce Data Collection Food Food Supply Humans Residence Characteristics Social Class Spain
Previous studies have suggested that European settings face unique food environment issues; however, retail food environments (RFE) outside Anglo-Saxon contexts remain understudied. We assessed the completeness and accuracy of an administrative dataset against ground truthing, using the example of Madrid (Spain). Further, we tested whether its completeness differed by its area-level socioeconomic status (SES) and population density. First, we collected data on the RFE through the ground truthing of 42 census tracts. Second, we retrieved data on the RFE from an administrative dataset covering the entire city ( = 2412 census tracts), and matched outlets using location matching and location/name matching. Third, we validated the administrative dataset against the gold standard of ground truthing. Using location matching, the administrative dataset had a high sensitivity (0.95; [95% CI = 0.89, 0.98]) and positive predictive values (PPV) (0.79; [95% CI = 0.70, 0.85]), while these values were substantially lower using location/name matching (0.55 and 0.45, respectively). Accuracy was slightly higher using location/name matching ( = 0.71 vs 0.62). We found some evidence for systematic differences in PPV by area-level SES using location matching, and in both sensitivity and PPV by population density using location/name matching. Administrative datasets may offer a reliable and cost-effective source to measure retail food access; however, their accuracy needs to be evaluated before using them for research purposes.

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9 citations in Web of Science
8 citations in Scopus

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Collaboration types
Domestic collaboration
International collaboration
Web of Science research areas
Environmental Sciences
Public, Environmental & Occupational Health
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