Energy intakes of US children and adults by food purchase location and by specific food source

Foods away from home (FAFH) represent an increasing proportion of energy in the American diet [1‐3]. According to reports from the US Department of Agriculture (USDA) [4, 5], FAFH consumption has been associated with poor diet quality and may contribute to weight gain. The potential links between dietary energy obtained away from home and obesity have become a public health concern [2, 5, 6].

Typically, FAFH have been equated with foods obtained from or consumed in restaurants, including both fast food and full-service restaurants [7]. The United States Department of Agriculture’s (USDA) Economic Research Service (ERS) has classified meals as FAFH if the majority of energy in that meal, excluding beverages, came from fast food or full-service restaurants, cafeterias, or taverns [5]. Strictly speaking, the definition of away from home foods should encompass all foods that are prepared, purchased, and consumed away from home, including those obtained from schools, workplace cafeterias, and vending machines.

Using nationally representative US samples, food purchase location can now be determined more precisely. Since 2003, the National Health and Nutrition Examination Survey (NHANES) has coded all foods consumed by NHANES participants by their location of purchase or origin: store (including grocery, convenience or specialty), quick-service restaurant/pizza (QSR), full-service restaurant (FSR), school cafeteria, workplace cafeteria, vending machine, from someone else/gift, grown, or other. This differentiation of FAFH into subcategories by food purchase location can help inform public policy on ways to improve the quality of the American diet.

Specific food sources of dietary energy can also be identified with greater precision. Dietary intake data from the 2005–6 NHANES were recently aggregated into 96 mutually exclusive food groups (referred to as specific food source throughout the paper) by the National Cancer Institute [8]. Food codes representing similar foods - for example, various types of pasta dishes were combined to provide an indication of how specific food sources contribute to energy and to nutrient intakes. An analogous method was used in the present study.

The present analyses represent the first-ever study of dietary energy intakes by age group, food purchase location and by specific food source. Such analyses provide insight into energy intakes at home and away from home and can be used to shape and target public health policies for different age groups and refine dietary surveillance.

The present research provides an analysis of energy intakes of different age groups in the US, both by food purchase location and by specific food source. Evaluating who consumes what foods and from where provides new insight into the nature of eating patterns in American. Such analyses provide important data to support public health efforts to improve diets in the US.

Various policy approaches have been used to address the obesity epidemic. Among policies proposed to address obesity are measures directed at reducing energy intakes from school meals [12, 13], vending machines [12, 14], and fast food restaurants [15, 16]. A recent measure in New York City proposed quantity limits on sugary soft drinks sold in QSR and other venues, while exempting supermarkets and grocery stores [17].

The present analyses of purchase location show that stores supplied 63% to 76% of dietary energy, depending on age group. Restaurants including QSR and FSR, contributed between 16.9% and 26.3% of dietary energy. School meals provided between 5.5% and 9.8% of energy, whereas the contribution from vending machines was <1%.

Our previous research showed that the prevalence of obesity among adults varied sharply by supermarket type [18]. Shoppers at upscale supermarkets had a lower prevalence of obestiy, whereas shoppers at downscale and discount supermarkets had a higher prevalence of obesity, after adjusting for individual-level education and incomes [18].

The present analyses offer a unique look at the specific food sources by purchase location. Contrary to popular belief, restaurant-sourced pizza, burgers, chicken and French fries accounted for less energy than store-sourced breads, grain-based desserts, pasta and soft drinks. For example, for adolescents in the 12-19y age group, QSR pizza accounted for 3.9% of total energy, whereas QSR French fried potatoes accounted for 1.7%. Interestingly, QSR sugar sweetened beverages provided 1.0-1.4% of dietary energy depending on age, whereas store-sourced beverages provided four times that.

How then to account for reports that eating one meal away from home each week translates into 2 extra pounds of weight gain each year for an average adult [5]? One answer is that cross-sectional studies such as NHANES cannot be used to infer causality or the direction of weight change. NHANES data can be used to uncover associations but can say nothing about weight gain.

There are two legitimate concerns about diet quality and eating away from home. In some previous studies of children aged 13-18y, food obtained from fast food outlets, restaurants, and other commercial sources was associated with lower diet quality and higher energy intakes [2]. The first concern is that FAFH may be higher in problematic nutrients than are meals sourced from grocery stores and prepared and consumed at home [7]. Even though restaurants provide up to 26% energy on the average, they may provide sharply higher amounts of saturated fat, sugar, or salt [19‐21]. That issue is currently under investigation, with comparable analyses by food source and purchase location being conducted for added sugar, sodium, and saturated fat.

The second concern is that Americans may not compensate for the FAFH by making substantially healthier food choices at home [5]. Recent analyses of the USDA Thrifty Food Plan (TFP) [22] showed that FAFH can be a part of a healthy and affordable diet. In general, the TFP stipulates that all foods should be purchased at stores and prepared at home. A nonlinear programming model evaluated the consequences on diet quality of including moderate amounts of FAFH in the food patterns of low income consumers, showing that the overall diet quality, as measured by the Healthy Eating Index 2005, did not change. The USDA researchers suggest that such findings may be used by nutrition educators to develop healthful FAFH.

The present study had limitations. First, all analyses were based on cross-sectional data. Although NHANES data are representative of the US population, they cannot be used to infer causal relationships between diet quality, body weight, or other health outcomes. Second, the present analyses were based on a single 24-hour recall, which may result in under-reporting of some foods. On average, individuals tend to under-report the consumption of foods perceived to be less healthful by either omitting them from their recall or under-estimating the amount consumed [23, 24]. In both cases, the data here may under-represent the contribution of some foods to the energy intakes of the population. This systematic under-reporting may result in a falsely minimized estimation of energy from restaurants or from food sources such as desserts, pizza or soda. For younger children, reporting may be assisted by a proxy respondent. This may result in under-reporting of foods consumed while the parent is not present, which may result in systematic under-estimation of foods consumed, though such reporting error is unlikely to be differential between food sources. The coding scheme for purchase location used by NHANES may also be problematic. Specifically, the use of “store” as a location does not allow for the disaggregation of grocery stores/supermarkets from convenience stores, gas stations or pharmacies, which may be important locations for some food sources (e.g., soda, candy, alcoholic beverages or chips). Data on stores should be carefully interpreted to come from both grocery and other stores. If similar data are collected in other studies, efforts should be made to disaggregate different types of food stores. The evaluation of schools as an important source of energy is hindered by the lack of information on season or month of data collection, which does not allow us to determine when children or adolescents are in school. When restricting analyses to Monday-Friday, schools accounted for 13.8% of energy for children age 6-11y and 7.6% of energy for adolescents age 12-19y (as compared to 9.8% and 5.5% respectively for the entire week), though these still represent an under-estimate of the impact of schools given the inclusion of some respondents from summer months/school holidays. Finally, the present analyses were based on the food purchase location as opposed to eating location. However, from the standpoint of dietary surveillance, understanding the source of energy is more important than identifying where a given food item was consumed. Despite these limitations, these data remain the best data available to evaluate food source and purchase location.

The present analyses offer a detailed description of the food purchase locations for the top calorie sources in the diets of US children, adolescents, and adults. This invaluable population-based data can be used to identify the most important food sources and purchase locations of energy, thereby allowing for more effective targeting of policy interventions aimed at calorie reduction. Specifically, the data presented here suggest that restaurants, schools, and stores each have a role to play in stemming the obesity epidemic.