Clustering of fast-food restaurants around schools: a novel application of spatial statistics to the study of food environments

Am J Public Health. 2005 Sep;95(9):1575-81. doi: 10.2105/AJPH.2004.056341.


Objectives: We examined the concentration of fast food restaurants in areas proximal to schools to characterize school neighborhood food environments.

Methods: We used geocoded databases of restaurant and school addresses to examine locational patterns of fast-food restaurants and kindergartens and primary and secondary schools in Chicago. We used the bivariate K function statistical method to quantify the degree of clustering (spatial dependence) of fast-food restaurants around school locations.

Results: The median distance from any school in Chicago to the nearest fast-food restaurant was 0.52 km, a distance that an adult can walk in little more than 5 minutes, and 78% of schools had at least 1 fast-food restaurant within 800 m. Fast-food restaurants were statistically significantly clustered in areas within a short walking distance from schools, with an estimated 3 to 4 times as many fast-food restaurants within 1.5 km from schools than would be expected if the restaurants were distributed throughout the city in a way unrelated to school locations.

Conclusions: Fast-food restaurants are concentrated within a short walking distance from schools, exposing children to poor-quality food environments in their school neighborhoods.

Publication types

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

MeSH terms

  • Adolescent
  • Adolescent Nutritional Physiological Phenomena
  • Chicago
  • Child
  • Child Nutritional Physiological Phenomena*
  • Data Interpretation, Statistical
  • Databases as Topic
  • Diet Surveys
  • Environment*
  • Feeding Behavior*
  • Food / classification*
  • Geography
  • Humans
  • Public Health
  • Residence Characteristics / statistics & numerical data*
  • Restaurants / classification
  • Restaurants / statistics & numerical data*
  • Schools / statistics & numerical data*