Please use this identifier to cite or link to this item:
Title: Validity and reliability of the facility list coder, a new tool to evaluate community food environments
Author: Arcila Agudelo, Ana María
Muñoz-Mora, Juan Carlos
Farran, Andreu
Keywords: Aliments naturals
Sistemes d'informació geogràfica
Python (Llenguatge de programació)
Natural foods
Geographic information systems
Python (Computer program language)
Issue Date: 25-Sep-2019
Publisher: MDPI
Abstract: A community food environment plays an essential role in explaining the healthy lifestyle patterns of its community members. However, there is a lack of compelling quantitative approaches to evaluate these environments. This study introduces and validates a new tool named the facility list coder (FLC), whose purpose is to assess food environments based on data sources and classification algorithms. Using the case of Mataró (Spain), we randomly selected 301 grids areas (100 m2), in which we conducted street audits in order to physically identify all the facilities by name, address, and type. Then, audit-identified facilities were matched with those automatically-identified and were classified using the FLC to determine its quality. Our results suggest that automatically-identified and audit-identified food environments have a high level of agreement. The intra-class correlation coe cient (ICC) estimates and their respective 95% confidence intervals for the overall sample yield the result 'excellent' (ICC 0.9) for the level of reliability of the FLC.
Note: Reproducció del document publicat a:
It is part of: International Journal of Environmental Research and Public Health, 2019, vol. 16, num. 19, p. 3578
Related resource:
ISSN: 1660-4601
Appears in Collections:Articles publicats en revistes (Nutrició, Ciències de l'Alimentació i Gastronomia)

Files in This Item:
File Description SizeFormat 
692048.pdf3.16 MBAdobe PDFView/Open

This item is licensed under a Creative Commons License Creative Commons