The number and type of food retailers surrounding schools and their association with lunchtime eating behaviours in students
1 Department of Community Health & Epidemiology, Queen’s University, Kingston, ON, K7L 3N6, Canada
2 Department of Emergency Medicine, Kingston General Hospital, Kingston, ON, K7L 2V7, Canada
3 School of Kinesiology and Health Studies, Queen’s University, 28 Division St, Kingston, ON, K7L 3N6, Canada
International Journal of Behavioral Nutrition and Physical Activity 2013, 10:19 doi:10.1186/1479-5868-10-19Published: 7 February 2013
The primary study objective was to examine whether the presence of food retailers surrounding schools was associated with students’ lunchtime eating behaviours. The secondary objective was to determine whether measures of the food retail environment around schools captured using road network or circular buffers were more strongly related to eating behaviours while at school.
Grade 9 and 10 students (N=6,971) who participated in the 2009/10 Canadian Health Behaviour in School Aged Children Survey were included in this study. The outcome was determined by students’ self-reports of where they typically ate their lunch during school days. Circular and road network-based buffers were created for a 1 km distance surrounding 158 schools participating in the HBSC. The addresses of fast food restaurants, convenience stores and coffee/donut shops were mapped within the buffers. Multilevel logistic regression was used to determine whether there was a relationship between the presence of food retailers near schools and students regularly eating their lunch at a fast food restaurant, snack-bar or café. The Akaike Information Criteria (AIC) value, a measure of goodness-of-fit, was used to determine the optimal buffer type.
For the 1 km circular buffers, students with 1–2 (OR= 1.10, 95% CI: 0.57-2.11), 3–4 (OR=1.45, 95% CI: 0.75-2.82) and ≥5 nearby food retailers (OR=2.94, 95% CI: 1.71-5.09) were more likely to eat lunch at a food retailer compared to students with no nearby food retailers. The relationships were slightly stronger when assessed via 1 km road network buffers, with a greater likelihood of eating at a food retailer for 1–2 (OR=1.20, 95% CI:0.74-1.95), 3–4 (OR=3.19, 95% CI: 1.66-6.13) and ≥5 nearby food retailers (OR=3.54, 95% CI: 2.08-6.02). Road network buffers appeared to provide a better measure of the food retail environment, as indicated by a lower AIC value (3332 vs. 3346).
There was a strong relationship between the presence of food retailers near schools and students’ lunchtime eating behaviours. Results from the goodness of fit analysis suggests that road network buffers provide a more optimal measure of school neighbourhood food environments relative to circular buffers.