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Assessing the retail food environment in Madrid: An evaluation of administrative data against ground truthing

Author
Diez, Julia; Cebrecos, Alba; Galán, Iñaki; Pérez-Freixo, Hugo; Franco, Manuel; Bilal, Usama
Entity
UAM. Departamento de Medicina Preventiva y Salud Pública y Microbiología; Instituto de Investigación Sanitaria Hospital Universitario de La Paz (IdiPAZ)
Publisher
MDPI, Basel, Switzerland
Date
2019-09-21
Citation
10.3390/ijerph16193538
International Journal of Environmental Research and Public Health 16 (2019): 3538
 
 
 
ISSN
1661-7827 (print); 1660-4601 (online)
DOI
10.3390/ijerph16193538
Funded by
This research was funded by the European Research Council under the European Union’ Seventh Framework Programme (FP7/2007–2013/ERC Starting Grant HeartHealthyHoods Agreement no.336893).
Project
info:eu-repo/grantAgreement/EC/FP7/336893/EU
Editor's Version
https://doi.org/10.3390/ijerph16193538
Subjects
Retail food environment; Validity; Secondary data; Differential exposure; Ground-truthing; Food outlets; Spain; Medicina
URI
http://hdl.handle.net/10486/691229
Rights
© 2019 by the authors

Licencia Creative Commons
Esta obra está bajo una Licencia Creative Commons Atribución 4.0 Internacional.

Abstract

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 (n = 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 (k = 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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Google™ Scholar:Diez, Julia - Cebrecos, Alba - Galán, Iñaki - Pérez-Freixo, Hugo - Franco, Manuel - Bilal, Usama

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  • Producción científica en acceso abierto de la UAM [14696]

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