2026-04-13T13:54:34Zhttps://recercat.cat/oai/request

oai:recercat.cat:2445/1592182025-12-05T14:52:49Zcom_2072_1057col_2072_478917col_2072_478924

00925njm 22002777a 4500 dc Arcila Agudelo, Ana María author Muñoz-Mora, Juan Carlos author Farran, Andreu author 2020-05-07T14:05:43Z 2020-05-07T14:05:43Z 2019-09-25 2020-05-07T14:05:43Z 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. Aliments naturals Sistemes d'informació geogràfica Python (Llenguatge de programació) Natural foods Geographic information systems Python (Computer program language) Validity and reliability of the facility list coder, a new tool to evaluate community food environments