US secondary schools and food outlets
Introduction
The three-fold increase in the prevalence of obesity among US adolescents in the last four decades is a major public health concern (Hedley et al., 2004; Ogden et al., 2002). Recent estimates indicate that 21.8% of African-American adolescents aged 12–19 years are overweight when compared with 17.3% and 16.3% of non-Hispanic White and Mexican-American adolescents, respectively (Ogden et al., 2006). Though highest among African-American adolescents, the prevalence of overweight is now rising fastest among non-Hispanic White children (Ogden et al., 2006; Strauss and Pollack, 2001). Not only are overweight youth at increased risk for developing type 2 diabetes mellitus and cardiovascular disease (CVD) risk factors, but they also have a 70% chance of becoming overweight or obese adults (Freedman et al., 1999; Hannon et al., 2005; USDHHS, n.d.). Adolescence is a critical period in shaping eating habits and weight status later in life (Story et al., 2002).
Schools are a pivotal setting for promoting healthy eating among adolescents and curbing the obesity epidemic because of the considerable amount of time adolescents spend there (Katz et al., 2005; Kubik et al., 2003; Neumark-Sztainer et al., 2005; Story, 1999; Wechsler et al., 2000). Attention has appropriately focused on food service, à la carte foods, vending machines, and stores in schools. Yet, efforts to change the food environment within schools may be ineffective in reducing adolescent overweight if the surrounding neighborhood food environment is neglected (Story et al., 2002; Wechsler et al., 2000). Approximately 5% and 15% of US 10th and 12th graders, respectively, go off campus for lunch (Johnston et al., 2007). In addition, 68% of adolescents nationwide walk/bike, take public transportation, or ride in a private vehicle to and from school (versus ride the school bus), which presents them with opportunities to access nearby retail food outlets (Bureau of Transportation Statistics, 1999). Thus, the retail food environment surrounding schools may influence adolescents’ eating patterns and weight status.
Despite suggestions that convenience stores and fast food restaurants are often located near schools which encourages use (Story et al., 2002), we identified few published empirical studies. A Chicago study found 78% of all kindergarten, primary, and secondary schools had at least one fast food restaurant within 800 m and that areas within 1.5 km of schools had 3–4 times as many fast food restaurants than would be expected if the restaurants were evenly distributed throughout the city (Austin et al., 2005). A pilot study of four communities, cross-classified by “walkability” and income, in the Atlanta Region found that fast food restaurants were closer to middle schools than sit-down restaurants and convenience stores were closer than grocery stores in three of the four communities (Frank et al., 2007).
These studies contribute to our understanding of the spatial accessibility of retail food outlets to schools, but are limited to two US urban areas. National data describing the spatial accessibility around schools of food outlets that contribute to adolescents’ diets would provide important information for policymakers who are concerned with open versus closed campus lunch policies and land use planning and zoning (Ashe et al., 2003). Furthermore, if schools located in racial/ethnic minority and economically disadvantaged neighborhoods have more fast food restaurants and/or convenience stores, researchers and policymakers will want to pay particular attention to addressing these inequalities.
This study had two objectives. The first objective was to examine the availability of retail food outlets within walking distance (0.5 miles or 805 m) of US public secondary schools, including whether schools located in racial/ethnic minority and economically disadvantaged neighborhoods have more fast food restaurants and convenience stores than those located in more advantaged neighborhoods, controlling for neighborhood population density and urbanicity. We compared results for retail food outlet availability within walking distance of schools located in the 50 states and in the 20 largest (i.e., most populous) cities in the US. A half-mile was selected to reflect a space in which adolescents may spend time and be exposed during lunch and before and after school hours. Controlling for neighborhood characteristics included under the first objective, the second objective was to examine, in the 20 largest US cities, whether neighborhoods with a secondary school have more fast food restaurants and convenience stores than neighborhoods without a secondary school.
Section snippets
Schools
We obtained data on public secondary (middle, high) schools located in the US for the 2004–2005 school year from the National Center for Education Statistics (NCES) Common Core of Data Elementary/Secondary School Universe Survey: School Year 2004–2005 (Sable et al., 2006). For the 2004–2005 school year, we identified 31,433 regular (excluding special education, vocational education, alternative/other, Department of Defense schools) and operational secondary schools, located in the 50 states and
Descriptives
Table 2 shows descriptive statistics for the study variables. About 37% and 33% of public secondary schools nationwide have at least one fast food restaurant (mean=0.88; std. dev.=1.89) and convenience store (mean=0.48; std. dev.=0.83) within walking distance, respectively. Even higher proportions were found for schools located in the largest cities, with 68% having one or more fast food restaurants and 56% having one or more convenience stores.
Regression results
Table 3, Table 4 show results of analyses for
Limitations
This study has several limitations. A first limitation is use of a GIS spatial join procedure to obtain schools’ census tract identifiers from Census boundary files. Though commonly used, this method can be inaccurate, with one study finding that 14% of addresses were assigned the incorrect census tract identifier (McElroy et al., 2003; Rushton et al., 2006; Yang et al., 2004). Still, because of racial and economic residential segregation, racial/ethnic and socioeconomic characteristics of
Acknowledgments
We thank Brandon Nolin and Juliana Mendes for assistance with the GIS work and Yanjun Bao for assistance with data analysis. We also thank the Robert Wood Johnson Foundation for supporting this research through the ImpacTeen part of Bridging the Gap.
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