Dataset Information

Validity of secondary retail food outlet data: a systematic review.

ABSTRACT:

Context

Improving access to healthy foods is a promising strategy to prevent nutrition-related chronic diseases. To characterize retail food environments and identify areas with limited retail access, researchers, government programs, and community advocates have primarily used secondary retail food outlet data sources (e.g., InfoUSA or government food registries). To advance the state of the science on measuring retail food environments, this systematic review examined the evidence for validity reported for secondary retail food outlet data sources for characterizing retail food environments.

Evidence acquisition

A literature search was conducted through December 31, 2012, to identify peer-reviewed published literature that compared secondary retail food outlet data sources to primary data sources (i.e., field observations) for accuracy of identifying the type and location of retail food outlets. Data were analyzed in 2013.

Evidence synthesis

Nineteen studies met the inclusion criteria. The evidence for validity reported varied by secondary data sources examined, primary data-gathering approaches, retail food outlets examined, and geographic and sociodemographic characteristics. More than half of the studies (53%) did not report evidence for validity by type of food outlet examined and by a particular secondary data source.

Conclusions

Researchers should strive to gather primary data but if relying on secondary data sources, InfoUSA and government food registries had higher levels of agreement than reported by other secondary data sources and may provide sufficient accuracy for exploring these associations in large study areas.

SUBMITTER: Fleischhacker SE

PROVIDER: S-EPMC3779346 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Validity of secondary retail food outlet data: a systematic review.

Fleischhacker Sheila E SE Evenson Kelly R KR Sharkey Joseph J Pitts Stephanie B Jilcott SB Rodriguez Daniel A DA

American journal of preventive medicine 20131001 4

<h4>Context</h4>Improving access to healthy foods is a promising strategy to prevent nutrition-related chronic diseases. To characterize retail food environments and identify areas with limited retail access, researchers, government programs, and community advocates have primarily used secondary retail food outlet data sources (e.g., InfoUSA or government food registries). To advance the state of the science on measuring retail food environments, this systematic review examined the evidence for ...[more]

PMID: 24050423

Similar Datasets

Project description:BackgroundMost studies on the local food environment have used secondary sources to describe the food environment, such as government food registries or commercial listings (e.g., Reference USA). Most of the studies exploring evidence for validity of secondary retail food data have used on-site verification and have not conducted analysis by data source (e.g., sensitivity of Reference USA) or by food outlet type (e.g., sensitivity of Reference USA for convenience stores). Few studies have explored the food environment in American Indian communities. To advance the science on measuring the food environment, we conducted direct, on-site observations of a wide range of food outlets in multiple American Indian communities, without a list guiding the field observations, and then compared our findings to several types of secondary data.MethodsFood outlets located within seven State Designated Tribal Statistical Areas in North Carolina (NC) were gathered from online Yellow Pages, Reference USA, Dun & Bradstreet, local health departments, and the NC Department of Agriculture and Consumer Services. All TIGER/Line 2009 roads (>1,500 miles) were driven in six of the more rural tribal areas and, for the largest tribe, all roads in two of its cities were driven. Sensitivity, positive predictive value, concordance, and kappa statistics were calculated to compare secondary data sources to primary data.Results699 food outlets were identified during primary data collection. Match rate for primary data and secondary data differed by type of food outlet observed, with the highest match rates found for grocery stores (97%), general merchandise stores (96%), and restaurants (91%). Reference USA exhibited almost perfect sensitivity (0.89). Local health department data had substantial sensitivity (0.66) and was almost perfect when focusing only on restaurants (0.91). Positive predictive value was substantial for Reference USA (0.67) and moderate for local health department data (0.49). Evidence for validity was comparatively lower for Dun & Bradstreet, online Yellow Pages, and the NC Department of Agriculture.ConclusionsSecondary data sources both over- and under-represented the food environment; they were particularly problematic for identifying convenience stores and specialty markets. More attention is needed to improve the validity of existing data sources, especially for rural local food environments.

Project description:BackgroundValidation studies of secondary datasets used to characterize neighborhood food businesses generally evaluate how accurately the database represents the true situation on the ground. Depending on the research objectives, the characterization of the business environment may tolerate some inaccuracies (e.g. minor imprecisions in location or errors in business names). Furthermore, if the number of false negatives (FNs) and false positives (FPs) is balanced within a given area, one could argue that the database still provides a "fair" representation of existing resources in this area. Yet, traditional validation measures do not relax matching criteria, and treat FNs and FPs independently. Through the field validation of food businesses found in a Canadian database, this paper proposes alternative criteria for validity.MethodsField validation of the 2010 Enhanced Points of Interest (EPOI) database (DMTI Spatial®) was performed in 2011 in 12 census tracts (CTs) in Montreal, Canada. Some 410 food outlets were extracted from the database and 484 were observed in the field. First, traditional measures of sensitivity and positive predictive value (PPV) accounting for every single mismatch between the field and the database were computed. Second, relaxed measures of sensitivity and PPV that tolerate mismatches in business names or slight imprecisions in location were assessed. A novel measure of representativity that further allows for compensation between FNs and FPs within the same business category and area was proposed. Representativity was computed at CT level as ((TPs +|FPs-FNs|)/(TPs+FNs)), with TPs meaning true positives, and |FPs-FNs| being the absolute value of the difference between the number of FNs and the number of FPs within each outlet category.ResultsThe EPOI database had a "moderate" capacity to detect an outlet present in the field (sensitivity: 54.5%) or to list only the outlets that actually existed in the field (PPV: 64.4%). Relaxed measures of sensitivity and PPV were respectively 65.5% and 77.3%. The representativity of the EPOI database was 77.7%.ConclusionsThe novel measure of representativity might serve as an alternative to traditional validity measures, and could be more appropriate in certain situations, depending on the nature and scale of the research question.

Dataset Information

Validity of secondary retail food outlet data: a systematic review.

Context

Evidence acquisition

Evidence synthesis

Conclusions

Publications

Validity of secondary retail food outlet data: a systematic review.

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