Obesity and the built environment: does the density of neighborhood fast-food outlets matter?
OBJECTIVE
Examine variation in obesity among older adults relative to the joint influences of density of neighborhood fast food outlets and residents' behavioral, psychosocial, and sociodemographic characteristics.


METHODS
Cross-sectional and multilevel design.


METHODS
Census block groups, used as a proxy for neighborhoods, within the metropolitan region's Urban Growth Boundary in Portland, Oregon.


METHODS
A total of 1221 residents (mean age, 65 years) recruited randomly from 120 neighborhoods (48% response rate).


METHODS
A geographic information system-based measure of fast food restaurant density across 120 neighborhoods was created. Residents within the sampled neighborhoods were assessed with respect to their body mass indices (BMI), frequency of visits to local fast food restaurants, fried food consumption, levels of physical activity, self-efficacy of eating fruits and vegetables, household income, and race/ethnicity.


METHODS
Multilevel logistic regression analyses.


RESULTS
Significant associations were found between resident-level individual characteristics and the likelihood of being obese (BMI > or = 30) for neighborhoods with a high-density of fast food restaurants in comparison with those with a low density: odds ratios for obesity, 95% confidence intervals (CI), were 1.878 (CI, 1.006-3.496) for weekly visits to local fast food restaurants; 1.792 (CI, 1.006-3.190) for not meeting physical activity recommendations; 1.212 (CI, 1.057-1.391) for low confidence in eating healthy food; and 8.057 (CI, 1.705-38.086) for non-Hispanic black residents.


CONCLUSIONS
Increased density of neighborhood fast food outlets was associated with unhealthy lifestyles, poorer psychosocial profiles, and increased risk of obesity among older adults.
Li
Fuzhong
F
Oregon Research Institute, Eugene, OR 97403, USA. fuzhongl@ori.org
Harmer
Peter
P
Cardinal
Bradley J
BJ
Bosworth
Mark
M
Johnson-Shelton
Deb
D
D000368:Aged; D000886:Anthropometry; D015992:Body Mass Index; D003296:Cooking; D004041:Dietary Fats / Q000008:administration & dosage / Q000009:adverse effects; D004779:Environment Design; D005247:Feeding Behavior; D005260:Female; D040362:Geographic Information Systems; D006801:Humans; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000453:epidemiology* / Q000517:prevention & control / Q000523:psychology; D009922:Oregon / Q000453:epidemiology; D012111:Residence Characteristics / Q000706:statistics & numerical data*; D012147:Restaurants / Q000145:classification / Q000706:statistics & numerical data*; D020377:Self Efficacy; D012959:Socioeconomic Factors; D014504:Urban Health / Q000706:statistics & numerical data*
D004041:Dietary Fats