Comparing Perception-Based and Geographic Information System (GIS)-based characterizations of the local food environment.
Measuring features of the local food environment has been a major challenge in studying the effect of the environment on diet. This study examined associations between alternate ways of characterizing the local food environment by comparing Geographic Information System (GIS)-derived densities of various types of stores to perception-based measures of the availability of healthy foods. Survey questions rating the availability of produce and low-fat products in neighborhoods were aggregated into a healthy food availability score for 5,774 residents of North Carolina, Maryland, and New York. Densities of supermarkets and smaller stores per square mile were computed for 1 mile around each respondent's residence using kernel estimation. The number of different store types in the area was used to measure variety in the food environment. Linear regression was used to examine associations of store densities and variety with reported availability. Respondents living in areas with lower densities of supermarkets rated the selection and availability of produce and low-fat foods 17% lower than those in areas with the highest densities of supermarkets (95% CL, -18.8, -15.1). In areas without supermarkets, low densities of smaller stores and less store variety were associated with worse perceived availability of healthy foods only in North Carolina (8.8% lower availability, 95% CL, -13.8, -3.4 for lowest vs. highest small-store density; 10.5% lower 95% CL, -16.0, -4.7 for least vs. most store variety). In contrast, higher smaller store densities and more variety were associated with worse perceived healthy food availability in Maryland. Perception- and GIS-based characterizations of the environment are associated but are not identical. Combinations of different types of measures may yield more valid measures of the environment.
Moore
Latetia V
LV
University of Michigan, Department of Epidemiology, 109 Observatory St., 4648 SPH I Ann Arbor, MI, 48109-2029, USA, lvmoore@cdc.gov.
Diez Roux
Ana V
AV
Brines
Shannon
S
D015142:Baltimore; D003132:Commerce; D003430:Cross-Sectional Studies; D019649:Food Industry; D005523:Food Supply; D040362:Geographic Information Systems; D006801:Humans; D007407:Interviews as Topic; D009519:New York City; D009657:North Carolina; D011639:Public Opinion; D012111:Residence Characteristics; D012923:Social Class; D012931:Social Environment; D014505:Urban Population