OBJECTIVE: To examine associations between various measures of the food environment and BMI percentile among youth. DESIGN: Cross-sectional, observational. SETTING: Pitt County, eastern North Carolina. SUBJECTS: We extracted the electronic medical records for youth receiving well child check-ups from January 2007 to June 2008. We obtained addresses for food venues from two secondary sources and ground-truthing. A geographic information systems database was constructed by geocoding home addresses of 744 youth and food venues. We quantified participants' accessibility to food venues by calculating 'coverage', number of food venues in buffers of 0·25, 0·5, 1 and 5 miles (0·4, 0·8, 1·6 and 8·0 km) and by calculating 'proximity' or distance to the closest food venue. We examined associations between BMI percentile and food venue accessibility using correlation and regression analyses. RESULTS: There were negative associations between BMI percentile and coverage of farmers' markets/produce markets in 0·25 and 0·5 mile Euclidean and 0·25, 0·5 and 1 mile road network buffers. There were positive associations between BMI percentile and coverage of fast-food and pizza places in the 0·25 mile Euclidean and network buffers. In multivariate analyses adjusted for race, insurance status and rural/urban residence, proximity (network distance) to convenience stores was negatively associated with BMI percentile and proximity to farmers' markets was positively associated with BMI percentile. CONCLUSIONS: Accessibility to various types of food venues is associated with BMI percentile in eastern North Carolina youth. Future longitudinal work should examine correlations between accessibility to and use of traditional and non-traditional food venues.
OBJECTIVE: To examine associations between various measures of the food environment and BMI percentile among youth. DESIGN: Cross-sectional, observational. SETTING: Pitt County, eastern North Carolina. SUBJECTS: We extracted the electronic medical records for youth receiving well child check-ups from January 2007 to June 2008. We obtained addresses for food venues from two secondary sources and ground-truthing. A geographic information systems database was constructed by geocoding home addresses of 744 youth and food venues. We quantified participants' accessibility to food venues by calculating 'coverage', number of food venues in buffers of 0·25, 0·5, 1 and 5 miles (0·4, 0·8, 1·6 and 8·0 km) and by calculating 'proximity' or distance to the closest food venue. We examined associations between BMI percentile and food venue accessibility using correlation and regression analyses. RESULTS: There were negative associations between BMI percentile and coverage of farmers' markets/produce markets in 0·25 and 0·5 mile Euclidean and 0·25, 0·5 and 1 mile road network buffers. There were positive associations between BMI percentile and coverage of fast-food and pizza places in the 0·25 mile Euclidean and network buffers. In multivariate analyses adjusted for race, insurance status and rural/urban residence, proximity (network distance) to convenience stores was negatively associated with BMI percentile and proximity to farmers' markets was positively associated with BMI percentile. CONCLUSIONS: Accessibility to various types of food venues is associated with BMI percentile in eastern North Carolina youth. Future longitudinal work should examine correlations between accessibility to and use of traditional and non-traditional food venues.
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