Validation of a province-wide commercial food store dataset in a heterogeneous predominantly rural food environment
OBJECTIVE: Commercially available business (CAB) datasets for food environments have been investigated for error in large urban contexts and some rural areas, but there is a relative dearth of literature that reports error across regions of variable rurality. The objective of the current study was t...
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Online Access: | http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10200544/ http://www.ncbi.nlm.nih.gov/pubmed/32295655 https://doi.org/10.1017/S1368980019004506 |
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ftpubmed:oai:pubmedcentral.nih.gov:10200544 2023-06-11T04:14:12+02:00 Validation of a province-wide commercial food store dataset in a heterogeneous predominantly rural food environment Taylor, Nathan GA Stymest, Jillian Mah, Catherine L 2020-08 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10200544/ http://www.ncbi.nlm.nih.gov/pubmed/32295655 https://doi.org/10.1017/S1368980019004506 en eng Cambridge University Press http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10200544/ http://www.ncbi.nlm.nih.gov/pubmed/32295655 http://dx.doi.org/10.1017/S1368980019004506 © The Authors 2020 Public Health Nutr Short Communication Text 2020 ftpubmed https://doi.org/10.1017/S1368980019004506 2023-05-28T00:45:57Z OBJECTIVE: Commercially available business (CAB) datasets for food environments have been investigated for error in large urban contexts and some rural areas, but there is a relative dearth of literature that reports error across regions of variable rurality. The objective of the current study was to assess the validity of a CAB dataset using a government dataset at the provincial scale. DESIGN: A ground-truthed dataset provided by the government of Newfoundland and Labrador (NL) was used to assess a popular commercial dataset. Concordance, sensitivity, positive-predictive value (PPV) and geocoding errors were calculated. Measures were stratified by store types and rurality to investigate any association between these variables and database accuracy. SETTING: NL, Canada. PARTICIPANTS: The current analysis used store-level (ecological) data. RESULTS: Of 1125 stores, there were 380 stores that existed in both datasets and were considered true-positive stores. The mean positional error between a ground-truthed and test point was 17·72 km. When compared with the provincial dataset of businesses, grocery stores had the greatest agreement, sensitivity = 0·64, PPV = 0·60 and concordance = 0·45. Gas stations had the least agreement, sensitivity = 0·26, PPV = 0·32 and concordance = 0·17. Only 4 % of commercial data points in rural areas matched every criterion examined. CONCLUSIONS: The commercial dataset exhibits a low level of agreement with the ground-truthed provincial data. Particularly retailers in rural areas or belonging to the gas station category suffered from misclassification and/or geocoding errors. Taken together, the commercial dataset is differentially representative of the ground-truthed reality based on store-type and rurality/urbanity. Text Newfoundland PubMed Central (PMC) Newfoundland Canada Public Health Nutrition 23 11 1889 1895 |
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Short Communication Taylor, Nathan GA Stymest, Jillian Mah, Catherine L Validation of a province-wide commercial food store dataset in a heterogeneous predominantly rural food environment |
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Short Communication |
description |
OBJECTIVE: Commercially available business (CAB) datasets for food environments have been investigated for error in large urban contexts and some rural areas, but there is a relative dearth of literature that reports error across regions of variable rurality. The objective of the current study was to assess the validity of a CAB dataset using a government dataset at the provincial scale. DESIGN: A ground-truthed dataset provided by the government of Newfoundland and Labrador (NL) was used to assess a popular commercial dataset. Concordance, sensitivity, positive-predictive value (PPV) and geocoding errors were calculated. Measures were stratified by store types and rurality to investigate any association between these variables and database accuracy. SETTING: NL, Canada. PARTICIPANTS: The current analysis used store-level (ecological) data. RESULTS: Of 1125 stores, there were 380 stores that existed in both datasets and were considered true-positive stores. The mean positional error between a ground-truthed and test point was 17·72 km. When compared with the provincial dataset of businesses, grocery stores had the greatest agreement, sensitivity = 0·64, PPV = 0·60 and concordance = 0·45. Gas stations had the least agreement, sensitivity = 0·26, PPV = 0·32 and concordance = 0·17. Only 4 % of commercial data points in rural areas matched every criterion examined. CONCLUSIONS: The commercial dataset exhibits a low level of agreement with the ground-truthed provincial data. Particularly retailers in rural areas or belonging to the gas station category suffered from misclassification and/or geocoding errors. Taken together, the commercial dataset is differentially representative of the ground-truthed reality based on store-type and rurality/urbanity. |
format |
Text |
author |
Taylor, Nathan GA Stymest, Jillian Mah, Catherine L |
author_facet |
Taylor, Nathan GA Stymest, Jillian Mah, Catherine L |
author_sort |
Taylor, Nathan GA |
title |
Validation of a province-wide commercial food store dataset in a heterogeneous predominantly rural food environment |
title_short |
Validation of a province-wide commercial food store dataset in a heterogeneous predominantly rural food environment |
title_full |
Validation of a province-wide commercial food store dataset in a heterogeneous predominantly rural food environment |
title_fullStr |
Validation of a province-wide commercial food store dataset in a heterogeneous predominantly rural food environment |
title_full_unstemmed |
Validation of a province-wide commercial food store dataset in a heterogeneous predominantly rural food environment |
title_sort |
validation of a province-wide commercial food store dataset in a heterogeneous predominantly rural food environment |
publisher |
Cambridge University Press |
publishDate |
2020 |
url |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10200544/ http://www.ncbi.nlm.nih.gov/pubmed/32295655 https://doi.org/10.1017/S1368980019004506 |
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Newfoundland Canada |
geographic_facet |
Newfoundland Canada |
genre |
Newfoundland |
genre_facet |
Newfoundland |
op_source |
Public Health Nutr |
op_relation |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10200544/ http://www.ncbi.nlm.nih.gov/pubmed/32295655 http://dx.doi.org/10.1017/S1368980019004506 |
op_rights |
© The Authors 2020 |
op_doi |
https://doi.org/10.1017/S1368980019004506 |
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Public Health Nutrition |
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23 |
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11 |
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1889 |
op_container_end_page |
1895 |
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1768392029671260160 |