Exploring obesogenic food environments in Edmonton, Canada: the association between socioeconomic factors and fast-food outlet access.
OBJECTIVE
To explore the relationship between the placement of fast-food outlets and neighborhood-level socioeconomic variables by determining if indicators of lower socioeconomic status were predictive of exposure to fast food.


METHODS
A descriptive analysis of the fast-food environment in a Canadian urban center, using secondary analysis of census data and Geographic Information Systems technology.


METHODS
Edmonton, Alberta, Canada.


METHODS
Neighborhoods were classified as High, Medium, or Low Access based on the number of fast-food opportunities available to them. Neighborhood-level socioeconomic data (income, education, employment, immigration status, and housing tenure) from the 2001 Statistics Canada federal census were obtained.


METHODS
A discriminant function analysis was used to determine if any association existed between neighborhood demographic characteristics and accessibility of fast-food outlets.


RESULTS
Significant differences were found between the three levels of fast-food accessibility across the socioeconomic variables, with successively greater percentages of unemployment, low income, and renters in neighborhoods with increasingly greater access to fast-food restaurants. A high score on several of these variables was predictive of greater access to fast-food restaurants.


CONCLUSIONS
Although a causal inference is not possible, these results suggest that the distribution of fast-food outlets relative to neighborhood-level socioeconomic status requires further attention in the process of explaining the increased rates of obesity observed in relatively deprived populations.
Hemphill
Eric
E
Centre for Health Promotion Studies, University of Alberta, Edmonton, Alberta, Canada.
Raine
Kim
K
Spence
John C
JC
Smoyer-Tomic
Karen E
KE
D000416:Alberta; D019352:Censuses; D016002:Discriminant Analysis; D004522:Educational Status; D054242:Emigrants and Immigrants; D004779:Environment Design; D005247:Feeding Behavior; D040362:Geographic Information Systems; D006801:Humans; D007182:Income; D009765:Obesity / Q000191:economics; D011204:Poverty Areas; D012111:Residence Characteristics / Q000145:classification*; D012147:Restaurants / Q000145:classification* / Q000706:statistics & numerical data*; D012923:Social Class; D014478:Unemployment; D014504:Urban Health / Q000145:classification* / Q000706:statistics & numerical data