Although many diet- and weight-related variables examined here were not consistently associated with neighbourhood food environments, SSB intake notably yielded a positive and robust association with the presence of food and non-food retail facilities in the 800 and 1600 m residential buffers. Proximity and access may influence adolescents' SSB consumption, given the convenience of these beverages, minimal cost and ubiquitous presence in a wide range of retail facilities. Findings from Wang et al
show that an average excess intake of 468–690 kJ/d (110–165 kcal/d) may account for the excess weight gain observed among US children over the past two decades. Thus, environmental factors contributing to the daily consumption of one additional SSB may be sufficient to promote long-term weight gain in a significant proportion of youth.
In contrast, we did not detect similar significant and robust associations between other dietary characteristics and features of the neighbourhood environment around the home. It is possible that much of our suburban residing sample may drive more than 3000 m to purchase food for home consumption, thus resulting in overall nutrient intake (e.g. energy or fat intake) having little association with local food availability.
-score and percentage body fat yielded a moderate, positive association with the presence of convenience stores within 1600 m of the home. Although these findings were not particularly robust (i.e. yielding associations with a wide array of neighbourhood characteristics), they align well with two previous studies yielding similar results among youth(6,19)
. Previous studies illustrate that convenience stores offer large proportions of highly processed, energy-dense foods, compared to other types of retail food outlets, and supermarkets offer a greater variety of more healthy foods(20,21)
. Not all previous studies, however, have detected a relationship between these food outlet densities and childhood weight gain(22)
, perhaps underscoring the complexities of the aetiology of obesity.
Although numerous characteristics of the school neighbourhood environment yielded significant associations with diet-related behaviours in unadjusted analyses, most of these relationships were no longer apparent after controlling for covariates. However, few schools in our sample had zero food outlets within the specified buffer areas, meaning that nearly all schools had some food outlet `exposure'. Thus, it is possible that these school-level findings may be explained by the fact that the mere presence (v. absence) of at least one food outlet within close proximity had a greater impact on dietary consumption than the sheer number or density of nearby food outlets. In addition, students in our largely suburban sample may be less influenced by these food outlets if they are bused or driven directly to school (rather than walking or taking public transit).
Paradoxically, the few findings that were significant in our analyses of school neighbourhood environments were in the opposite directions to those that had been hypothesized (i.e. BMI Z-score or percentage body fat was lower among those who were exposed to fast food and/or any restaurants within 800 m of their school). These findings are difficult to explain and may reflect a variety of exposures (in the neighbourhood, as well as schools, families and other realms of influence) in the lives of these young people. The present study required a large number of statistical tests, and although we accounted for this by using relatively conservative procedures and a levels, these findings may reflect a statistical anomaly.
Overall, the specific impact of food outlet access on diet and weight remains somewhat unclear. Policy makers and key stakeholders are searching for guidance about how to positively affect dietary patterns, and additional research is needed to guide practice-based recommendations. Over the years, the implementation of nutrition education programmes has been logistically challenging, and impact has been limited. Thus, attention has turned towards changing the physical infrastructure as a means of addressing obesity. Numerous local governments have proposed changes to zoning, food licensing and other factors in hopes of improving healthy food availability and limiting access to less healthy foods(23)
However, in addition to access, food choices also reflect an array of personal and social values. Although previous studies have reported associations between food access and diet-related factors, overall associations have been rather small in magnitude, with inconsistencies in findings between the USA and other international settings(3)
. In fact, much of the US association between food access and obesity may be attributed to SES-based disparities in access, which have been widely documented(1)
. It is possible that in food-rich environments where access is unrestricted, social influences and personal preferences affect consumption more than physical environments(24)
The present study had numerous strengths (e.g. using state-of-the-art dietary intake assessment and measured heights and weights) as well as limitations. The study was conducted only in one region of the USA and included a small, non-representative youth sample. The inherent limitations of GIS data, particularly with regard to describing food environments, are also well known(10,24)
. Bader et al
found that disagreements between data sources were not significantly correlated with influential covariates, such as SES, but still found substantial disagreements between sources (e.g. a 17.6% disagreement between data sources as to whether a supermarket or grocery was present on a city block). Although commercial food business databases have limitations in data quality, we took extra effort to manually check and ensure the accuracy of addresses in our purchased data(12,26)
Furthermore, the selection of an appropriate buffer size is a difficult issue that deserves additional attention in future studies(1)
. Although most of the study on neigh-bourhood food environments has examined ecological associations between environmental factors and dietary intake, with relatively crude classifications of `neigh-bourhoods' (e.g. exploring food store availability within Census tracts, zip codes or states), the studies that have used GIS buffers to more narrowly define the neighbourhood food environment have not employed a consistently defined buffer size. Buffer sizes have included 100m(27)
and 2 miles(29)
. The use of a larger buffer size to examine neighbourhood food environments may better reflect the fact that a substantial proportion of people (particularly within the USA) do not live within walking distance of their primary food store. For example, Moore et al
found that only 47% of US adults reported doing most of their food shopping within 1 mile of their home. In addition, Rose and Richards(31)
found that only 38% of low-income adults shopped for food ≤1 mile from their home, with an additional 35% shopping within 1–5 miles and 27% shopping >5 miles from home. Therefore, the buffer sizes used in the present study may generally capture the areas in which some of our adolescent participants (and/or their families) do their food purchasing, but others may purchase food outside this area of exposure. In the present study, we were not able to measure specific food purchasing or eating behaviours in terms of the most relevant exposures in the food environment. This is an important limitation.
Overall, adolescence is an important developmental age accompanied by notable declines in a range of health behaviours. Numerous studies indicate that increased fast-food intake and eating away from home is associated with substantially lower diet quality among youth(32–34)
. Our results suggest that neighbourhood environments surrounding the home are particularly associated with adolescents' consumption of SSB. Intervention strategies to promote healthy dietary patterns among adolescents are needed, some of which should include macro-level policy approaches. However, the decision-making processes that occur around dietary choices are highly complex, and nutrition promotion efforts will likely need to employ multiple approaches, including environmental availability and accessibility as well as other strategies, to be successful.