The results reported here demonstrate that the restaurant environment is associated with weight status net of individual- and county-level factors. The relationship is complex, suggesting that the restaurant environment’s influence goes well beyond a simple positive association between restaurant density and weight status. Rather, different components of the restaurant environment exhibit differential associations with weight status. Individuals residing in areas with a high density of total and full-service restaurants exhibit lower weight status, possibly indicating that these areas possess a more advantageous eating environment. Prior studies have not modeled the possible interdependence among different components of the eating environment and a contribution of this study is that area-level restaurant mix is an important determinant of weight status. Those who reside in areas possessing a higher relative number of fast-food to full-service restaurants have a higher weight status. Hence, the relative availability of alternative types of away-from-home eating establishments may most accurately capture the set of food choices available to individuals and may be salient in determining eating behaviors and ultimately weight status.
Results from this study support the notion that fast-food restaurants are a contributor to obesogenic environments. This study goes beyond prior work in this area by showing that a high relative number of fast-food restaurants are also positively associated with weight status. This suggests that in a culture where eating out is common, the type of restaurant food chosen is important to determining weight status. More patronage of full-service restaurants may be suggestive of less consumption of fast food, which may be serving meals that promote the highest weight gain. A higher density of full-service restaurants is independently associated with lower weight status, further suggesting that full-service restaurants are reflective of a more advantageous eating environment. These results highlight the need for further research into the comparative healthfulness of foods served at fast-food and full-service restaurants. One study found that individuals seeking healthier foods are more likely to eat at full-service restaurants over fast-food restaurants.32
It is unclear whether individuals actually consume fewer calories (and more nutritious food) when eating at full-service restaurants. A study that has compared the nutritional content of food from fast-food and full-service restaurants found that both types of restaurant meals contained similar amounts of total fat, but full-service foods had lower amounts of saturated fats and higher amounts of cholesterol and sodium.15
It did not compare carbohydrate and trans-fat composition or the average calories consumed per meal. Frequent fast-food consumption is associated with higher weight status.12,14,16,34
Less work has been conducted on actual full-service restaurant food consumption and weight status. One study25
reported no significant association between full-service patronage and weight status and another reported a positive association only in men.12
In contrast to this study, Chou et al.6
reported that both fast-food and full-service restaurant availability were positively associated with weight status. This discrepancy in results may have arisen from the different levels of aggregation and, as discussed above, a smaller unit may be more suitable for assessing the restaurant environment. Additionally, Chou et al. used data between 1984 and 1999, while restaurants in this study are measured in 2002. Eating behaviors and the restaurant landscape have been changing rapidly over this period and the relationship between restaurant availability and weight status may have shifted. Maddock et al.23
also reported a positive and significant association between fast-food density and weight status, but their analysis was ecologic while this study accounted for individual-level confounders in a multilevel framework.
This study has limitations. Data on supermarkets and grocery stores were not measured. The Economic Census does not differentiate between large supermarkets and smaller grocery stores, which may be more prevalent in impoverished communities.27,35
The quality of foods and prices offered across these types of stores differs,36–38
and it is not possible to capture these elements with per-capita number or per-capita sales measures. The total restaurant density has a negative relationship to weight status, controlling for the relative number of fast-food to full-service restaurants, which cannot be completely explained, and requires further study. Perhaps the prevalence of restaurants correlates with unobserved social attributes of communities (e.g., social capital and crime) that are themselves associated with weight status.11
Nonetheless, the results are robust to confounding by a wide set of structural factors associated with the socioeconomic and racial makeup of counties and these factors will partly account for unobserved social characteristics and the distribution of supermarkets/grocery stores. Height and weight are self-reported. There is continued debate as to the validity of self-reported weight status,39,40
but many have shown self-reports to be an excellent measure pointing to the high correlation between self-reported and clinically measured values.41–43
A challenge in measuring the relationship between restaurant availability and weight status is accounting for the possibility that latent eating and weight-status preferences of individuals determine the distribution of restaurant availability (a reverse causal process). Ideally, such preferences could be addressed with longitudinal data. For example, combining individual and contextual longitudinal data would make it possible to model the change in weight status and the change in restaurant density over time and to treat underlying eating and weight status preferences as unmeasured fixed-effect characteristics that cancel out of the regression equation. Future research delineating the causal processes associated with restaurant availability and weight status would benefit from these type of data.
In conclusion, this study found that the restaurant environment was independently associated with weight status, including individual-level demographic and behavioral characteristics and county-level structural factors. In particular, the types of restaurants that are available may function as a highly salient determinant for weight outcomes. While a higher mix of fast-food to full-service restaurants may contribute to an obesogenic environment, the availability of full-service restaurants may contribute to a more healthful eating environment. Future studies should consider the restaurant mix as a pathway through which more general area–level factors can affect weight status differences. Future studies should also consider how actual eating behaviors are shaped by the availability of different types of restaurants.