The relationship between obesity and the prevalence of fast food restaurants: state-level analysis.
OBJECTIVE
Obesity accounts for approximately 300,000 deaths a year in the United States, and prevalence rates have been increasing over the past decade. The nutrition environment may be contributing to this epidemic. This study examined the relationship between fast food restaurants and obesity on a state-wide basis.


METHODS
A one-time cross-sectional analysis of secondary data was used for this study.


METHODS
The setting for this study was the United States.


METHODS
State-level data were used as the unit of analysis. Alaska was excluded as an outlier, and the District of Columbia was added (N = 50).


METHODS
Measures included aggregate state-level means for square miles per fast food restaurant, population per fast food restaurant, population density, ethnicity, age, gender, physical inactivity, fruit and vegetable intake, and obesity rates. Data were obtained from the 2002 Behavioral Risk Factor and Surveillance Survey, the 2000 U.S. Census, and the 2002 U.S. Yellow Pages.


RESULTS
Multiple hierarchal regressions revealed that square miles per fast food restaurants and residents per restaurant accounted for 6% of the variance in state obesity rates after controlling for population density, ethnicity, age, gender, physical inactivity, and fruit and vegetable intake. The entire model explained 70% of the total variance in state obesity rates.


CONCLUSIONS
These results indicate a correlational relationship between both the number of residents per fast food restaurant and the square miles per fast food restaurants with state-level obesity prevalence. Limitations include the use of correlational aggregate data.
Maddock
Jay
J
University of Hawaii at Manoa, Honolulu, Hawaii 96822, USA. jmaddock@hawaii.edu
D000293:Adolescent; D000328:Adult; D003430:Cross-Sectional Studies; D004034:Diet Surveys; D005260:Female; D005638:Fruit; D006801:Humans; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000453:epidemiology*; D011156:Population Density; D015995:Prevalence; D012044:Regression Analysis; D012147:Restaurants / Q000145:classification*; D014481:United States / Q000453:epidemiology; D014675:Vegetables