Research articleThe School Food Environment: Associations with Adolescent Soft Drink and Snack Consumption
Introduction
Obesity is a major problem in many countries, and its prevalence is increasing.1, 2 Dietary patterns such as the consumption of fast food, snacks, and soft drinks may contribute to the development of overweight and obesity through the foods' high energy density (i.e., high calorie content) and large portion sizes.3, 4, 5, 6, 7, 8, 9
The theory of planned behavior (TPB) has proven to be useful in understanding correlates or determinants of soft drink and snack consumption.10, 11, 12, 13 According to the TPB, behavior can be predicted from the intention to perform behavior that is determined by attitudes, subjective norm, modeling, and perceived behavioral control.14, 15, 16 However, obesogenic dietary behaviors may also be influenced by the environmental opportunities to eat food.17, 18, 19 In social-ecologic models, (e.g., the Environmental Research framework for weight Gain prevention [the EnRG framework]), it is proposed that environmental factors indirectly influence behavior via the individual's cognitions.20 Environments that offer appealing opportunities for unhealthy foods may result in positive cognitions regarding the consumption of these unhealthy foods, resulting in higher intake of them.
Schools may be an important setting for obesity-prevention interventions, as many schools provide extensive facilities for selling food and drinks.21, 22 During breaks, adolescents may also purchase food items in the immediate area around the school.
Relatively few studies18, 23, 24 are available that examine environmental factors in a school setting. These studies found that the number of snack vending machines was associated with student snack purchases and lower fruit intake, and that in schools where soft drink machines were turned off during lunch time, adolescents purchased fewer soft drinks.23, 24 Many fast-food restaurants are located within walking distance of a school, and an open-campus policy during lunchtime was found to be associated with a higher likelihood of students' eating lunch at a fast-food restaurant.24, 25, 26, 27
The present study expands on the limited literature that explores the role of school food environments in influencing the dietary behaviors of youth. The overall hypothesis for this study was that a greater availability of soft drinks and snacks at school and in the school neighborhood as well as positive cognitions would lead to a higher intake of soft drinks and snacks. A second hypothesis was that environmental factors influence behavior via cognitions, that is, that cognitive factors mediate the association between environmental factors and behavior. This study specifically aimed to (1) examine the associations between school food availability and food stores in the school neighborhood with soft drink and snack consumption, (2) examine the associations between cognitions and soft drink and snack consumption, and (3) examine whether the effect of environmental factors on soft drink and snack consumption is partly mediated by cognitions (mediation effect).
Section snippets
Study Design and Sample Selection
The Environmental Determinants of Obesity in Rotterdam SchoolchildrEn (ENDORSE) study is a prospective 2-year study among adolescents (aged 12–13 years) in the first year and third year (aged 14–15 years) of secondary school.28 In 2005–2006, 24 of 56 schools in Rotterdam participated in the ENDORSE study. After stratification according to city region, 17 schools were selected. From them, a total of 78 classes (1668 adolescents) were randomly selected to participate in the ENDORSE study. Because
School Environment and Participant Characteristics
Four of the 15 schools sold fruit/vegetables, and two schools had low-energy snacks available in their vending machines. A small food store was the closest store for five schools, while only one school had a fruit/vegetable store as the closest store. The mean number of food establishments within 500 meters of schools was 16.7 (range=1–45), and consisted mostly of small food stores (M=6.7, range=0–21), followed by fast food outlets (M=4.7, range=1–12); bakeries (M=2.9, range=0–8);
Discussion
This is one of the first studies to systematically examine the association of self-reported cognitive factors and objectively measured school-environment factors with soft drink and snack consumption among adolescents. As in other studies,10, 11, 12, 13 significant positive associations were found for individual cognitions for both behaviors. This may indicate that cognitions are important factors to target in interventions, that is, by means of health education techniques.
Only small
Conclusion
This study provided little evidence for associations of environmental factors in the school environment with soft drink and snack consumption, while finding clear positive associations between cognitions and soft drink and snack intake. This indicates that such cognitions, rather than environmental factors, should be the primary target for interventions. However, the inverse associations between environmental factors and soft drink intake might indicate that the environment can also exert a
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2022, Journal of Adolescent HealthA systematic review of existing observational tools to measure the food and physical activity environment in schools
2020, Health and PlaceCitation Excerpt :A longitudinal study that used SPEEDY to assess both elementary and middle schools pointed out that the instrument, which was tested for reliability in elementary schools but not tailored for middle schools, may not capture relevant differences between the two (Harrison et al., 2016a,b). Authors commonly described limitations related to using the tool in single point-in-time observation studies, as they may not reflect the dynamic aspects of policy or program implementation (Thomas et al., 2016a,b; Black et al., 2015; Ritchie et al., 2015; Van Der Horst et al., 2008; Dias et al., 2017; Colabianchi et al., 2011). Some studies discussed the limitations of the tools themselves rather than their use in the studies, including rating scales used to assess “condition” of facilities or equipment, which authors noted can be somewhat subjective and thus vulnerable to measurement error (Leatherdale et al., 2014a; Jones et al., 2010; Colabianchi et al., 2011).