Howard et al. BMC Public Health 2011, 11:68 http://www.biomedcentral.com/1471-2458/11/68 [12-15], similar relationships have been reported for the majority of studies involving adults [16-20]. It is hypothesized that the increased availability of low- energy, nutrient-dense foods in supermarkets (e.g. fresh fruits and vegetables) may account for the most typical differences observed among retailer types [18,21]. Other important contexts for children and young adults are the food environments inside and just outside schools, where students may consume up to half of their total food intake [22]. There have been relatively few studies of food environments outside of schools with respect to the outcomes of overweight or obesity, and, as with studies involving adults, more have focused on fast food restaurants than other types of retailers [23]. A statewide study of middle and high school stu- dents in California reported a 6% increase in the odds of overweight when attending schools within 800 m of fast food restaurants, as well as increased soda consumption [24]. An ecological study, also conducted in California, reported higher school rates of overweight when fast food restaurants were located within a smaller, .1 mile buffer, after controlling for school-level variables [25]. One of the few studies of multiple types of retailers near schools in the United States found no associations between proximity to fast food restaurants or conveni- ence stores and adolescent overweight in Minnesota, but these variables were associated with increased consump- tion of sugar-sweetened beverages [26]. The plausibility of convenience stores near schools influencing dietary patterns in children and young adults is strengthened by a recent observational study in Phila- delphia: the researchers reported that fourth, fifth and sixth grade students frequently shopped at corner stores before and after school, and were most likely to buy inexpensive sugar-sweetened drinks, chips and candy (averaging approximately 350 kcal per purchase) [27]. We therefore examined associations between the proxi- mity of fast food restaurants, convenience stores and supermarkets to schools in California, and school over- weight rates. We hypothesized that 1) proximity to fast food restaurants would be associated with higher school overweight rates, 2) proximity to convenience stores would be associated with higher school overweight rates, and 3) proximity to supermarkets would be associated with lower school overweight rates. Methods Variables and Data Sources The dependent variable for this study was the rate of overweight ninth grade students for public schools in California in 2007. The data were obtained from Califor- nia Department of Education, which administers a phy- sical fitness test (FITNESSGRAM®) between February and May of each year. The test is required by state law Page 2 of 8 for public school students in 5th, 7th and ninth grade, and in 2007 approximately 90% of schools participated [28]. The test reports students’ body composition, as measured by skinfold (preferred method), body mass index (weight in kilograms divided by height in meters squared), or bioelectric impedance analyzers. These three different measurement options are provided to ensure broad participation, and while all are subject to error (typically 3 to 6%), comparisons of different meth- ods report high test-retest reliability [29,30]. The defini- tion of overweight differs slightly from others, such as the Centers for Disease Control. Instead, classification in this category is determined by criterion-referenced gen- der-, age- and test-specific cut-offs (e.g. skinfold <32 for a 15 year old female; body mass index <24.5 for a 14 year old male). These standards were established by a national advisory panel, convened by the Cooper Insti- tute of Dallas, Texas [29]. Our analysis is at the school-level because the physical fitness test results are publicly available only at this level of aggregation–individual results are confidential. The original dataset included all public schools in California that reported physical fitness test results. To obtain more stable rates of overweight students, we excluded schools with less than 100 students from the analysis. We focused on ninth graders because they are expected to have greater mobility, and greater financial ability to purchase food from nearby retailers, when compared to 7th and 5th graders. The physical fitness dataset also provided information on the gender and ethnic composition of students tested in each school. We used this information to construct a variable for gender composition, with percentage of male students as the reference category. We also con- structed variables for student composition by major eth- nic groups, with percentage non-Hispanic white as the reference category, and additional variables for the per- centage of students that were Hispanic/Latino, African- American, Asian, Native American (including Alaskan native), Pacific Islander, and those who declined to state their ethnicity. The California Department of Education was the source for several additional datasets, all of which are also publicly available. One contained the street addresses of schools in the study, which we used in con- structing the retailer proximity variables described below. We obtained two other datasets to construct independent variables for 1) percentage of all students (not just ninth graders) in each school receiving free & reduced price meals in 2007, and 2) urban or non-urban school location. The subsidized meal variable was used as a proxy for school-level socioeconomic status, which at the individual-level is known to be strongly associated with overweight. We defined urban schools as those