Measurement of the local food environment: a comparison of existing data sources

Am J Epidemiol. 2010 Mar 1;171(5):609-17. doi: 10.1093/aje/kwp419. Epub 2010 Jan 31.

Abstract

Studying the relation between the residential environment and health requires valid, reliable, and cost-effective methods to collect data on residential environments. This 2002 study compared the level of agreement between measures of the presence of neighborhood businesses drawn from 2 common sources of data used for research on the built environment and health: listings of businesses from commercial databases and direct observations of city blocks by raters. Kappa statistics were calculated for 6 types of businesses-drugstores, liquor stores, bars, convenience stores, restaurants, and grocers-located on 1,663 city blocks in Chicago, Illinois. Logistic regressions estimated whether disagreement between measurement methods was systematically correlated with the socioeconomic and demographic characteristics of neighborhoods. Levels of agreement between the 2 sources were relatively high, with significant (P < 0.001) kappa statistics for each business type ranging from 0.32 to 0.70. Most business types were more likely to be reported by direct observations than in the commercial database listings. Disagreement between the 2 sources was not significantly correlated with the socioeconomic and demographic characteristics of neighborhoods. Results suggest that researchers should have reasonable confidence using whichever method (or combination of methods) is most cost-effective and theoretically appropriate for their research design.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Chicago
  • Commerce / statistics & numerical data
  • Data Collection / methods*
  • Environment*
  • Epidemiologic Methods
  • Fast Foods
  • Food Services / statistics & numerical data*
  • Geography
  • Humans
  • Odds Ratio
  • Residence Characteristics / classification
  • Residence Characteristics / statistics & numerical data*
  • Restaurants
  • Socioeconomic Factors