shows descriptive statistics stratified by level of school. There are no significant differences between middle and high schools in the number of convenience stores within 400 m and the number of off-licences within 400 or 800 m; all other comparisons are statistically significant at P <0.001. The most important differences are that middle schools are smaller, more likely to qualify for Title I, and more likely to have a majority of students who are eligible for free school meals. Differences in the business environment are relatively small, which was an unexpected finding given the differences in school size and location.
stratifies schools by the existence or absence of a particular type of business within 400 m. The rows show schools without any businesses within 400 m (n = 17,972), schools with at least one business within 400 m (n = 13,650), schools with at least one convenience store within 400 m (n = 5335), and schools with at least one off-licence within 400 m; arguably the least desirable type of establishment among those considered (n = 2849). Ordering schools in this way reveals a very strong association with student and school characteristics. For example, consider the first column (Title I eligible school): among schools with no businesses within 400 m, 36.9% are Title I eligible. The percentage of Title I eligible schools increases to 40.0% among schools with at least one convenience store, restaurant or off-licence, 42.2% among schools with at least one convenience store, and 43.1% among schools with an off-licence within 400 m.
School characteristics by presence and absence of businesses within 400 m.
The gradient is even stronger for race/ethnicity. In schools with no businesses within 400 m, 13.6% are Hispanic and 12.8% are non-Hispanic Black. In schools with nearby convenience stores, 17.6% are Hispanic and 18.2% are non-Hispanic Black. In schools with at least one off-licence within 400 m, 21.7% are Hispanic and 22.7% are non-Hispanic Black. There were no significant differences for percentage of Asians, percentage of Native Americans, total enrolment and student/teacher ratio, and these variables are not shown. However, there is also an important difference in terms of location, in that schools with nearby off-licences are more likely to be in an urban area and those with no businesses in a rural area; potentially an important confounder.
and show the results from the multivariate analysis, and provides additional sensitivity analyses stratifying by location. In , the dependent variable is whether or not there is at least one business of a certain type within 400 m. In , the dependent variable is the number of outlets (a measure of density). The entries in are odds ratios and standard errors associated with the explanatory variables. In some ways, this provides a mirror image of , which is stratified by business environment and gave the means of the explanatory variables. Odds ratios that are significantly different from 1.00 at P
<0.01 are in bold. Regarding economic characteristics, a higher proportion of students eligible for free school meals increases the likelihood of any nearby businesses (other than snack stores) and is significant for any business, convenience stores and restaurants. A similar association holds for Title I eligibility of schools. However, remarkably, student poverty, after controlling for type of location, is not predictive of nearby off-licences, even though low-income neighbourhoods nationally have a higher density of alcohol outlets.12
Odds ratios: predictors of business types near schools.
Incidence rate ratios for number of establishments within 400 m of schools by location for non-Hispanic Blacks.
Hispanic students are more likely to be in schools surrounded by restaurants, snack stores or off-licences. A higher percentage of Asian or non-Hispanic Black students is associated with a higher likelihood of nearby off-licences. In contrast, there is no significant association between the proportion of non-Hispanic Blacks and any businesses, convenience stores, restaurants or snack stores after controlling for location (direct effect only, see for interaction sensitivity analyses). Thus, the strong association seen in bivariate comparisons disappears for non-Hispanic Blacks when distinguishing urban, suburban, town and rural locations. As expected, locations other than urban are associated with fewer businesses, middle schools are associated with fewer surrounding businesses than high schools, and larger schools are associated with fewer businesses than smaller schools, probably because they also cover more of the area within 400 m of the main entrance. There is no clear or consistent effect of student/teacher ratio.
repeats the analysis using counts of establishments within 400 m, thus analysing the density of food-related businesses. The qualitative results are unchanged, and even the magnitude of the incidence rate ratio is similar to the odds ratio for the less common types of stores (convenience stores and off-licences).
A number of sensitivity analyses were conducted to test whether the findings are robust to model specifications, with the main concern being possible interactions between location and race/ethnicity. Generally, the main findings from and hold when urban, suburban, town and rural areas are analysed separately. The largest difference between a pooled and a stratified analysis is for the percentage of non-Hispanic Blacks, and shows the incidence rate ratios for percentage of non-Hispanic Blacks when stratifying the models by location. The notable result is that in urban areas, Black students tend to be exposed to more food businesses than their non-Hispanic White counterparts, but the opposite is true in rural areas and towns. For restaurants, the stratified analysis shows significantly higher rates in urban areas and significantly lower rates in rural areas, which disappear in the pooled analysis of . The qualitative results also remain largely unchanged when using 800-m buffers, except that results tend to be more statistically significant.