Validation of 3 Food Outlet Databases: Completeness and Geospatial Accuracy in Rural and Urban Food Environments

Abstract

Despite interest in the built food environment, little is known about the validity of commonly used secondary data. The authors conducted a comprehensive field census identifying the locations of all food outlets using a handheld global positioning system in 8 counties in South Carolina (2008–2009). Secondary data were obtained from 2 commercial companies, Dun & Bradstreet, Inc. (D&B) (Short Hills, New Jersey) and InfoUSA, Inc. (Omaha, Nebraska), and the South Carolina Department of Health and Environmental Control (DHEC). Sensitivity, positive predictive value, and geospatial accuracy were compared. The field census identified 2,208 food outlets, significantly more than the DHEC (n = 1,694), InfoUSA (n = 1,657), or D&B (n = 1,573). Sensitivities were moderate for DHEC (68%) and InfoUSA (65%) and fair for D&B (55%). Combining InfoUSA and D&B data would have increased sensitivity to 78%. Positive predictive values were very good for DHEC (89%) and InfoUSA (86%) and good for D&B (78%). Geospatial accuracy varied, depending on the scale: More than 80% of outlets were geocoded to the correct US Census tract, but only 29%–39% were correctly allocated within 100 m. This study suggests that the validity of common data sources used to characterize the food environment is limited. The marked undercount of food outlets and the geospatial inaccuracies observed have the potential to introduce bias into studies evaluating the impact of the built food environment.

Geographic and socioeconomic distribution of food vendors: a case study of a municipality in the Southern Brazil

“…Additionally, during data collection we sometimes found more than one food vendor listed in business association or government records with the same address, and occasionally a food vendor no longer existed. This type of outdated information was also found by Liese et al 46 , who also used secondary data.…”

Spatial and Semantic Validation of Secondary Food Source Data

“…The CVR is slightly better than Smiley with an accuracy of 18.74 ± 19.83 m. With 87.70% of the retailers in Smiley and 92.31% in CVR registered within 50 m of the true GPS position, the directories are accurate compared to other studies yielding results of 53%-56% within 100 m in the United States of America [13]. Whether the errors are larger in urban or rural areas is uncertain based on the analysis, though with a small tendency towards smaller errors being in the most populated areas.…”

“…The completeness and thematic accuracy of the data demonstrates that if the raw data were used in research, there would exist a huge overrepresentation of food retailers similar to other studies [13]. The misclassification of retailers poses a major problem if analyzing small retailer groups, such as specialty stores, whereas the errors have less of an impact on large groups, such as restaurants or supermarkets.…”

“…Contemporaneity informs about the retention of outdated information. Unknown errors in the data lead to misinterpretations of the results or under-or over-estimation [12,13] of, for example, the density of food retailers or an analysis of the association of foodscapes with health or socioeconomic factors.…”

“…Previous examinations of the validity of food retailer lists have demonstrated limitations compared to direct observations, due to the lack of completeness, thematic and geographical accuracy and contemporaneity of such lists in the United States of America [13,14] and the United Kingdom [12]. However, studies have demonstrated contradicting results between the use of commercial and government lists.…”