Assessing the Validity of Commercial and Municipal Food Environment Datasets in Vancouver, Canada Daepp, Madeleine I. G.; Black, Jennifer
Objective: This study assessed systematic bias and the effects of dataset error on the validity of food environment measures in two municipal and two commercial secondary datasets. Design: Sensitivity, positive predictive value (PPV), and concordance were calculated by comparing two municipal and two commercial secondary datasets with ground-truthed data collected within 800m buffers surrounding 26 schools. Logistic regression examined associations between sensitivity and PPV with commercial density and neighborhood socioeconomic deprivation. Kendall's Tau estimated correlations between density and proximity of food outlets near schools constructed with secondary datasets versus ground-truthed data. Setting: Vancouver, Canada. Subjects: Food retailers located within 800m of 26 schools Results: All datasets scored relatively poorly across validity measures, though overall, municipal datasets had higher levels of validity than did commercial datasets. Food outlets were more likely to be missing from municipal health inspections lists and commercial datasets in neighborhoods with higher commercial density. Still, both proximity and density measures constructed from all secondary datasets were highly correlated (Kendall’s Tau> 0.70) with measures constructed from ground-truthed data. Conclusions: Despite relatively low levels of validity in all secondary datasets examined, food environment measures constructed from secondary datasets remained highly correlated with ground-truthed data. Findings suggest that secondary datasets can be used to measure the food environment, though estimates should be treated with caution in areas with high commercial density.
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