Howard et al. BMC Public Health 2011, 11:68 http://www.biomedcentral.com/1471-2458/11/68 Page 5 of 8 Table 2 Correlations (Kendall’s tau-b) for key school variables in the analysis (n = 879) Overweight (school %) Fast Fooda Conveniencea Supermarketa Fast Fooda Conveniencea Supermarketa Number of Students % Female % Hispanic/Latino % African-American (log) % Asian (log) % Native American (log) % Pacific Islander (log) % Declined to state (log) % Free/reduced meals Non-urban location .091** .138** -.001 -.013 .020 .494** .161** -.233** -.112** -.055* -.162** .494** -.083** *p < .05, **p < .01. a At least one such retailer within an 800 m network buffer. decrease the number of overweight students by 1.9% (95% confidence interval -3.6, -0.1). The model itself explains 3% of the variation in rates of overweight students. The second regression model is shown in Table 4. This model includes additional school-level variables that are known to be associated with overweight status. The variation explained was 51%, a substantial increase when compared to the first model. After controlling for these additional variables, the associations between retai- lers and school overweight rates were weaker, and only the association with convenience stores remained. The presence of a convenience store near a school is pre- dicted to increase its overweight rate by 1.2%. This is approximately 1/3 of that reported in model 1, but the 95% confidence interval (0.03, 2.4) continues to indicate a positive relationship. For a school with the mean num- ber of ninth graders (474), the model predicts that an additional 6 students would be overweight in compari- son to a school without a nearby convenience store. The associations with fast food restaurants and supermarkets when controlling for additional variables are much smal- ler, and their 95% confidence intervals include zero. Table 3 Regression of school percentage of overweight ninth grade students on nearby retailers (Constant) Fast Fooda Conveniencea Supermarketa F Adjusted R-squared B 29.19 1.80 3.54 -1.86 10.60 0.03 95% CI (27.20, 30.17) (0.24, 3.35) (1.94, 5.14) (-3.62, -0.09) b 0.09 0.15 -0.08 SE 0.50 0.79 0.81 0.90 .337** .426** .038 -.019 .101** .072** .016 -.100** .039 -.043 .108** -.137** .231 -.028 .007 .137** .008 -.082** -.060* -.065 -.059* .131** -.057 -.016 -.019 .020 -.032 .002 -.051 -.043 .030 .003 -.058 Variables that had stronger positive associations with school overweight rates than nearby convenience stores included the percentage of students receiving free or reduced price meals, and percentage of Latino, Afri- can-American and Native American students. The per- centage of Asian-American students demonstrated a stronger negative association with obesity rates. Vari- ables in the model that were more weakly associated with school overweight rates than nearby convenience stores included gender composition, percent Pacific Islan- der or “declined to state” ethnicity, and urban/non-urban location. Table 4 Regression of school percentage of overweight ninth grade students on nearby retailers, including additional school-level variables (Constant) Fast Fooda Conveniencea Supermarketa % Female % Hispanic/Latino % African-American (log) % Asian (log) % Native American (log) % Pacific Islander (log) % Declined to state ethnicity (log) % Free/reduced meals Non-urban location F Adjusted R-squared B (95% CI) b SE 15.70 (8.88, 22.32) 3.42 -0.04 (-1.18, 1.10) -0.01 0.58 1.20 (0.03, 2.36) 0.05 0.59 -0.33 (-1.61, 0.95) -0.01 0.65 -0.03 (-0.14, 0.08) -0.01 0.05 16.17 (12.83, 19.51) 0.43 1.70 5.81 (4.45, 7.16) 0.23 0.69 -1.84 (-3.22, -0.46) -0.08 0.70 4.61 (1.81, 7.41) 0.09 1.43 0.96 (-2.18, 4.09) 0.02 1.60 1.53 (-0.63, 3.69) 0.04 1.10 11.08 (7.48, 14.68) 0.28 1.83 0.34 (-0.79, 1.46) 0.02 0.57 75.89 0.51 a At least one such retailer within an 800 m network buffer. a At least one such retailer within an 800 m network buffer.