Validation of a province-wide commercial food store dataset in a heterogeneous predominantly rural food environment
Bibliographic Data
| ID | 15097015 |
|---|---|
| Authors | Nathan Taylor (0000-0001-6478-8165, Dalhousie University, corresponding author), Nathan GA Taylor, Jillian Stymest (Dalhousie University), Catherine L Mah (0000-0002-7294-2035, Dalhousie University) |
| Year | 2020 |
| Volume | 23 |
| Issue | 11 |
| Pages | 1889-1895 |
| Publication date | 2020-08-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Public Health Nutrition (JOURNAL) |
| Journal identifiers | ISSN: 1368-9800 • E-ISSN: 1475-2727 |
| Publisher | Cambridge University Press (CUP) (PUBLISHER) |
| DOI | 10.1017/s1368980019004506 |
| PMID | 32295655 |
| OpenAlex | W3017143703 |
| Language | EN |
| Citations received | 2 |
| References cited | 37 |
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
Cartography · Concordance · Concordance correlation coefficient · Geocoding · Geography · Government (linguistics · Rural area · Rurality · Scale (ratio · Sensitivity (control systems · Statistics · Consumer Retail Behavior Studies · Data-Driven Disease Surveillance · Engineering · Mathematics · Medicine · Nutritional Studies and Diet
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| Unique citing works | 2 |
|---|---|
| Citations per year | 1 |
| Citation span | 2024 - 2025 (2) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 2 |