Assessing the Retail Food Environment in Madrid: An Evaluation of Administrative Data against Ground Truthing

Abstract

Previous studies have suggested that European settings face unique food environment issues; however, retail food environments (RFE) outside Anglo-Saxon contexts remain understudied. We assessed the completeness and accuracy of an administrative dataset against ground truthing, using the example of Madrid (Spain). Further, we tested whether its completeness differed by its area-level socioeconomic status (SES) and population density. First, we collected data on the RFE through the ground truthing of 42 census tracts. Second, we retrieved data on the RFE from an administrative dataset covering the entire city (n = 2412 census tracts), and matched outlets using location matching and location/name matching. Third, we validated the administrative dataset against the gold standard of ground truthing. Using location matching, the administrative dataset had a high sensitivity (0.95; [95% CI = 0.89, 0.98]) and positive predictive values (PPV) (0.79; [95% CI = 0.70, 0.85]), while these values were substantially lower using location/name matching (0.55 and 0.45, respectively). Accuracy was slightly higher using location/name matching (k = 0.71 vs 0.62). We found some evidence for systematic differences in PPV by area-level SES using location matching, and in both sensitivity and PPV by population density using location/name matching. Administrative datasets may offer a reliable and cost-effective source to measure retail food access; however, their accuracy needs to be evaluated before using them for research purposes.

Adaptation and Evaluation of the Nutrition Environment Measures Survey in Stores to Assess Mediterranean Food Environments (NEMS-S-MED)

“…Our study sample included 21 census tracts scattered around the city and encompassed a socioeconomically diverse sample. While details on this sampling strategy have been published elsewhere [ 25 ], Table S1 shows the descriptive statistics for these audit areas.…”

Allostatic Load Measurement: A Systematic Review of Reviews, Database Inventory, and Considerations for Neighborhood Research

“…Perceived neighborhood quality [ 4 , 5 ] with increased neighborhood green spaces [ 6 , 7 ], decreased neighborhood disorder [ 8 ], and neighborhood socioeconomic advantage [ 9 , 10 ] have all been associated with normal allostatic load. Researchers often study allostatic load in the neighborhood context by utilizing administrative boundaries within publicly accessible databases as proxies for neighborhoods, which may not reflect the actual realities of the people who live in those neighborhoods [ 11 , 12 ].…”

Validation of retail food outlet data from a Danish government inspection database

“…Other studies have applied more than one matching approach in the comparison of different sources of secondary food outlet data and ground-truthed data. As in this study, Díez et al [ 24 ] applied location/name matching but also location matching alone to examine administrative food retailer data from Madrid, Spain. The first matching procedure resulted in substantially lower agreement statistics then the latter, with a sensitivity of 0.55 (CI:0.44–0.64) and a PPV of 0.45 (CI:0.37–0.54) compared to a sensitivity of 0.95 (CI:0.89–0.98) and a PPV of 0.79 (CI:0.70–0.85).…”