@article{cc4bf3109bef464fb5658f13492abfe9,
title = "The quality of OpenStreetMap food-related point-of-interest data for use in epidemiological research",
abstract = "We assessed the quality of food-related OpenStreetMap (OSM) data in urban areas of five European countries. We calculated agreement statistics between point-of-interests (POIs) from OSM and from Google Street View (GSV) in five European regions. We furthermore assessed correlations between exposure measures (distance and counts) from OSM data and administrative data from local data sources on food environment data in three European countries. Agreement between POI data in OSM compared to GSV was poor, but correlations were moderate to high between exposures from OSM and local data sources. OSM data downloaded in 2020 seems to be an acceptable source of data for generating count-based food exposure measures for research in selected European regions.",
keywords = "Exposome, Food environment, Google street view, OpenStreetMap, Quality assessment",
author = "Pinho, {Maria Gabriela M.} and Benjamin Flueckiger and Antonia Valentin and Maria-Iosifina Kasdagli and Kalliopi Kyriakou and Jeroen Lakerveld and Mackenbach, {Joreintje D.} and Beulens, {Joline W. J.} and {de Hoogh}, Kees",
note = "Funding Information: This work is part of the EXPANSE project, funded from the European Union's Horizon 2020 research and innovation programme under grant agreement No 874627 . Food retail data in the Netherlands were obtained via the Geoscience and Health Cohort Consortium (GECCO) , which was financially supported by the Netherlands Organisation for Scientific Research (NWO) , the Netherlands Organisation for Health Research and Development (ZonMw) , and Amsterdam UMC . Publisher Copyright: {\textcopyright} 2023",
year = "2023",
month = sep,
day = "1",
doi = "https://doi.org/10.1016/j.healthplace.2023.103075",
language = "English",
volume = "83",
journal = "Health and Place",
issn = "1353-8292",
publisher = "Elsevier Limited",
}