Drewnowski and Rehm Nutrition Journal 2013, 1259httpwww..docx

Drewnowski and Rehm Nutrition Journal 2013, 12:59
http://www.nutritionj.com/content/12/1/59
RESEARCH Open Access
Energy intakes of US children and adults by food
purchase location and by specific food source
Adam Drewnowski1,2* and Colin D Rehm2
Abstract
Background: To our knowledge, no studies have examined
energy intakes by food purchase location and food
source using a representative sample of US children,
adolescents and adults. Evaluations of purchase location and
food sources of energy may inform public health policy.
Methods: Analyses were based on the first day of 24-hour recall
for 22,852 persons in the 2003-4, 2005-6, and
2007-8 National Health and Nutrition Examination Surveys
(NHANES). The most common food purchase locations
were stores (grocery store, supermarket, convenience store, or
specialty store), quick-service restaurants/pizza (QSR),
full-service restaurants (FSR), school cafeterias, or food from
someone else/gifts. Specific food sources of energy
were identified using the National Cancer Institute aggregation
scheme. Separate analyses were conducted for
children ages 6-11y, adolescents ages 12-19y, and adults aged
20-50y and ≥51y.
Results: Stores (grocery, convenience, and specialty) were the
food purchase locations for between 63.3% and
70.3% of dietary energy in the US diet. Restaurants provided
between 16.9% and 26.3% of total energy. Depending
on the respondents’ age, QSR provided between 12.5% and

17.5% of energy, whereas FSR provided between 4.7%
and 10.4% of energy. School meals provided 9.8% of energy for
children and 5.5% for adolescents. Vending
machines provided <1% of energy. Pizza from QSR, the top
food away from home (FAFH) item, provided 2.2% of
energy in the diets of children and 3.4% in the diets of
adolescents. Soda, energy, and sports drinks from QSR
provided approximately 1.2% of dietary energy.
Conclusions: Refining dietary surveillance approaches by
incorporating food purchase location may help inform
public health policy. Characterizing the important sources of
energy, in terms of both purchase location and source
may be useful in anticipating the population-level impacts of
proposed policy or educational interventions. These
data show that stores provide a majority of energy for the
population, followed by quick-service and full-service
restaurants. All food purchase locations, including stores,
restaurants and schools play an important role in
stemming the obesity epidemic.
Keywords: Energy intake, Obesity, Food away from home, Food
source, Food purchase location
Background
Foods away from home (FAFH) represent an increasing
proportion of energy in the American diet [1-3]. Accor-
ding 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
* Correspondence: [email protected]
1Université Pierre et Marie Curie - Paris VI, Groupe Hospitalier
Pitié-Salpêtrière,
91 boulevard de l’hôpital, Paris 75013, France
2Center for Public Health Nutrition, University of Washington,
Box 353410,

Seattle, WA 98195, USA
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distribution, and reproduction in any medium
away from home and obesity have become a public health
concern [2,5,6].
Typically, FAFH have been equated with foods obtai-
ned 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, cafe-
terias, or taverns [5]. Strictly speaking, the definition of
away from home foods should encompass all foods
that are prepared, purchased, and consumed away from
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Drewnowski and Rehm Nutrition Journal 2013, 12:59 Page 2 of
10
home, including those obtained from schools, workplace
cafeterias, and vending machines.
Using nationally representative US samples, food pur-
chase location can now be determined more precisely.

Since 2003, the National Health and Nutrition Exami-
nation Survey (NHANES) has coded all foods consumed
by NHANES participants by their location of purchase
or origin: store (including grocery, convenience or spe-
cialty), 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 lo-
cation and by specific food source. Such analyses pro-
vide 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.
Methods
Dietary intake databases
Data from three cycles of NHANES, 2003-3004, 2005-
2006, and 2007-2008, were used to identify the main
sources of dietary energy by age group, food purchase
location, and by specific food source (e.g., food group)

[9]. The National Center for Health Statistics (NCHS)
has obtained IRB approval for all cycles of NHANES
studies and the data has been made available for public
use [9].
The 2003-8 NHANES database includes 3,033 children
(age 6-11y); 5,432 adolescents (age 12-19y); and 14,387
adults (age≥20y) for a total of 22,852 persons. The pre-
sent analyses were based on one 24-hour dietary recall
conducted in-person. A single 24-hour recall for a large
population yields an unbiased estimate of the dietary
patterns of populations. Respondents reported the types
and amounts of all food and beverages consumed in the
preceding 24-hours, from midnight to midnight. Spe-
cifically, the NHANES 24-hour recall uses the USDA
Automated Multiple Pass Method. This is a compute-
rized method that first identifies a quick list of foods
consumed followed by a probe for any forgotten foods
and the recording of time and occasion for each food
item reported. A detailed cycle is then conducted that
records an estimation of the amounts consumed
followed by a final probe for any potentially forgotten
foods [10].
For children 6-11y, the child was the primary respon-
dent, but the proxy was present and able to assist. For
children 12y and older, the child was the primary source
of dietary recall information, but could be assisted by an
adult who had knowledge of their diet [10].
Food purchase locations
For each food or beverage consumed, NHANES staff
obtained information on the locations where the food
was purchased or obtained (referred to as food purchase
location throughout this paper). The primary locations
were stores, QSR (including pizza take-out/delivery),

FSR, school and from someone else/gift. Additional food
locations were vending machines; other types of cafete-
rias including workplace, grown or caught (e.g., through
gardening or hunting); tavern/bar; or from a sporting/
cultural/entertainment event (e.g., movie theater or
baseball game). The store category did not separate
grocery stores, supermarkets, convenience stores, and
specialty food stores, but the majority of foods in this
category would presumably come from grocery stores
or supermarkets. For the present analyses, the primary
purchase locations were narrowed to stores, QSR inclu-
ding pizza take-out/delivery, FSR and a combined other
category.
Specific food sources
The Food and Nutrient Database for Dietary Studies
(FNDDS) provides a detailed description for each food
and beverage consumed by NHANES participants [11].
All foods consumed by NHANES participants were ag-
gregated into 96 specific food sources belonging to 8
major food groups, based on a food coding scheme de-
veloped by the National Cancer Institute (NCI). This
was done using the version of FNDDS complementing
each cycle of NHANES (e.g., FNDDS 2.0 for NHANES
2003-04) [8]. Examples of specific food sources are soda,
energy and sports drinks, yeast breads, grain-based des-
serts, burgers, fried potatoes, pizza, sandwiches, chicken
dishes, or mixed Mexican dishes. The NCI groupings are
particularly useful for showing the relative contribution
of different food sources to energy or nutrient intakes at
the population level and have previously been used in
the 2010 Dietary Guidelines for Americans.
Analysis approach
Separate analyses were conducted for children (age 6-11y),
adolescents (age 12-19y), and for younger (age 20-50y)

10
and older adults (≥51y). These age strata were selected
to focus on elementary school aged children, secondary
school children and younger and older adults.
First, the NCI coding scheme was used to estimate the
relative contribution of specific food sources to energy
intakes by age group. The food purchase location infor-
mation was then used to estimate the relative contribu-
tion of energy of the US diet by age group and race/
ethnicity for adults. The race/ethnicity analyses were ad-
justed for age group to account for differences in the age
distribution of different race/ethnicity groups. Specific
food sources were identified by food purchase location,
separately for each age group. These analyses allowed us
to distinguish the contribution of beverages or pizza
from stores versus beverages or pizza from QSR, while
also evaluating energy intakes of each age group or race/
ethnicity group.
While the primary aim of this study was descriptive,
limited hypothesis testing was conducted. Specifically,
we evaluated whether there were significant effects of
race/ethnicity on food purchase location of energy using
a survey-weighted Wald test after adjusting for age
by making a pairwise contrast between Non-Hispanic
whites (reference group) and specific non-white race/
ethnicity groups. For analyses of food sources, we used a
global survey-weighted Wald test to determine if energy
from various food sources varied as a function of age.
Lastly, within each age group we evaluated whether

there were significant differences between purchase lo-
cations for each food source using a global survey-
Figure 1 Energy intake (calories) by food purchase location and
age g
weighted Wald test. Because NHANES is a complex
sample survey, all analyses reported here were survey-
weighted to account for the survey design and reflect
the behaviors of the United States population. Analyses
were conducted in Stata 11.2 (College Station, TX).
Results
Energy intakes by food purchase location
Data presented in Figure 1 show that both energy in-
takes and food purchase location varied by age group.
Energy intakes first increased and then decreased with
age, as expected.
For each age group, stores and restaurants (full-service
and quick-service/pizza) accounted for at least 85% of
total energy. However, the food purchase location also
varied sharply depending on age.
For primary school-aged children (6-11y), 63.3% of en-
ergy came from stores, 12.2% from QSR, and 9.8% from
school cafeterias. Among adolescents (12-19y), 63.1% of
energy came from stores, 17.5% from QSR and 7.0%
from FSR. The contribution of school meals to adoles-
cent diets was 5.5% of energy, whereas the contribution
of energy from vending machines (<1%) was negligible.
For adults age 20-50y, 63.1% of energy was obtained
from stores, 15.9% from QSR and 10.4% from FSR. For
older adults age ≥51y, 70.3% of energy was obtained
from stores, 8.6% from QSR and 10.4% from FSR. Adults
>70y obtained >76% of energy from grocery stores, and
proportionately less from restaurants (data not shown).
roup, NHANES 2003-2008.

10
Adults, aged 20-50y, obtained the highest proportion
of dietary energy (26.3%) from restaurants, both QSR
and FSR, followed by the 12-19y age group (24.5%). Al-
though the overall amount of energy obtained from res-
taurants declined after age 50y, energy from QSR tended
to be replaced with FSR.
For adults, the combined contribution of all restau-
rants, QSR and FSR, to total energy did not surpass 25%
for any race/ethnicity group. Non-Hispanic whites ob-
tained the lowest amount of energy from stores (1,442
kcal or 64.9%) and obtained 290 kcal (13.0%) from
QSR. Non-Hispanic blacks obtained 1,405 kcal (67.7%)
from stores and 345 kcal (16.6%) from QSR. Mexican-
Americans/other Hispanics obtained 1,436 kcal (69.3%)
from stores and 258 kcal (12.5%) from QSR. The amount
of energy from FSR was 241 kcal (10.9%) for whites; 142
kcal (6.9%) for non-Hispanic blacks, and 195 kcal (9.4%)
for other Hispanics. Mexican-American/other Hispanics
obtained the greatest percentage of their dietary energy
from stores and the least from QSR and FSR combined.
The data are shown in Figure 2.
Energy intakes by specific food sources
Table 1 shows the contribution of specific food sources
to energy intakes by age group. The age groups are de-
fined as children (6-11y), adolescents (12-19y), younger
adults (20-50y) and older adults (≥51y). Presented are
data for total energy and percent energy intakes for
the top 24 food sources for the total population; the
Figure 2 Sources of energy intake (calories) by food purchase

locatio
remaining specific food sources contributed <2.0% of
daily energy for each age group.
The top sources of dietary energy for children 6-11y
were grain-based desserts (6.9% of energy) and yeast
breads (6.4% of energy). Those two food sources were
among the top energy sources across all age groups.
Among adolescents, aged 12-19y, the top energy sources
were soda, energy and sports drinks (8.2%); pizza (7.2%);
yeast breads (6.3%), and chicken and chicken mixed
dishes (6.2%). Burgers contributed 2.0% of energy and
fried white potatoes contributed 2.7% of energy in the
12-19y age group.
Younger adults (20-50y) derived 6.8% of energy from
soda, energy and sports drinks; 6.0% from chicken and
chicken mixed dishes; and 6.1% from yeast breads. Ano-
ther 5.5% of energy came from grain-based desserts and
5.3% from alcoholic beverages.
The top sources of energy for older adults (≥51y) were
yeast breads (7.9%); grain-based desserts (7.1%); chicken
(4.9%); and beef dishes (4.3%), followed by alcoholic be-
verages (3.6%) and soda, energy and sports drinks (3.2%).
Energy intakes by specific food source and purchase
location
Table 2 shows the contribution of the top 24 food
sources to energy intakes of children ages 6-11y by pur-
chase location. Most of the dietary energy was contrib-
uted by store-bought grain-based desserts (4.8%), breads
(4.4%), pasta (3.6%), reduced fat milk (3.3%), ready to eat
(RTE) cereals (3.1%), soda (2.7%), potato chips (2.7%)
n and race/ethnicity among adults age ≥20y, NHANES 2003-
2008.

Table 1 Contribution to dietary energy by specific food sources
by age group, NHANES 2003-2008
6-11y (n=3,033) 12-19y (n=5,432) 20-50y (n=7,635) ≥51y
(n=6,752)
Category1 calories % total calories % total calories % total
calories % total p-value
Grain-based desserts 139 6.9 131 5.8 129 5.5 134 7.1 <0.001
Yeast breads 129 6.4 143 6.3 145 6.1 150 7.9 <0.001
Pizza 119 5.9 169 7.5 109 4.6 41 2.2 <0.001
Reduced fat milk 112 5.6 81 3.6 48 2.0 43 2.3 <0.001
Chicken and chicken mixed dishes 104 5.2 140 6.2 141 6.0 91
4.8 <0.001
Soda, energy and sports drinks 94 4.7 187 8.2 161 6.8 58 3.0
<0.001
Pasta and pasta mixed dishes 93 4.6 84 3.7 84 3.6 58 3.1 <0.001
Potato/corn/other chips 71 3.5 83 3.7 61 2.6 37 1.9 <0.001
Ready-to-eat cereals 71 3.5 62 2.7 40 1.7 45 2.4 <0.001
Dairy desserts 69 3.4 53 2.3 46 2.0 56 3.0 <0.001
Sausage, franks, bacon and ribs 60 3.0 49 2.2 59 2.5 52 2.7
<0.001

Whole milk 60 3.0 42 1.8 27 1.1 17 0.9 <0.001
Candy 57 2.9 62 2.7 50 2.1 38 2.0 <0.001
Beef and beef mixed dishes2 55 2.8 89 3.9 102 4.3 82 4.4
<0.001
Fruit drinks 55 2.7 57 2.5 37 1.5 18 0.9 <0.001
Mexican mixed dishes 50 2.5 81 3.6 85 3.6 35 1.9 <0.001
Regular cheese 50 2.5 57 2.5 61 2.6 43 2.3 0.039
Fried white potatoes 48 2.4 62 2.7 57 2.4 31 1.7 <0.001
Quickbreads 32 1.6 44 1.9 61 2.6 44 2.3 <0.001
Nuts/seeds and nut/seed mixed dishes 30 1.5 28 1.2 41 1.7 52
2.7 <0.001
Egg and egg mixed dishes 27 1.3 30 1.3 43 1.8 43 2.3 <0.001
Rice and rice mixed dishes 26 1.3 34 1.5 55 2.3 32 1.7 <0.001
Burgers2 25 1.2 45 2.0 36 1.5 16 0.8 <0.001
Alcoholic beverages 0 0.0 18 0.8 125 5.3 66 3.5 <0.0014
Others3 436 21.7 437 19.2 558 23.6 612 32.3 -
1 Sorted by total contribution among 6-11 year-olds (for
comparison purposes), 2 Burgers, as defined in the database,
can only come from quick-service
restaurants. All burgers reported from store or full-service
restaurants are composed of individual ingredients. Therefore,
components of hamburgers/

cheeseburgers will be present in the yeast breads, beef and beef
mixed dishes, regular cheese and other food groupings, 3 Others
include all categories
contributing <1.3% of total energy for the entire population. 4
Hypothesis testing for alcoholic beverages only conducted for
adults.
10
and chicken and chicken mixed dishes (2.1%). The top
QSR item, pizza, contributed 2.4% of energy, somewhat
more than pizza purchased in the grocery store (1.5%).
Detailed listings of the proportion of total energy by
food source and food purchase location for each age
group can be found in the appendix (Additional file 1:
Tables S1-S4).
sources to energy intakes of adolescents ages 12-19y by
purchase location. Most of the dietary energy was
contributed by store-bought soda (5.3%), breads (4.6%),
grain-based desserts (4.4%), potato and corn chips
(3.1%), pasta (3.0%), reduced-fat milk (2.9%), RTE cereals
(2.7%), and beef (2.3%) and chicken dishes (2.2%). The
top QSR item, pizza, contributed 3.9% of energy, more
than pizza purchased in the grocery store (1.9%). The
second highest QSR item, chicken dishes, contributed
2.2% of energy, the same as chicken dishes sourced from
the grocery store.
sources to energy intakes of adults ages 20-50y by pur-
chase location. Most of the dietary energy was contributed
by store-bought soda (4.5%), breads (4.2%), grain-based

desserts (3.9%), pasta (2.7%), and beef (2.5%) and chicken
dishes (2.4%). The top QSR item, pizza, contributed 2.7%
of energy, more than pizza purchased in the grocery store
(1.1%). The second highest QSR item, chicken dishes, con-
tributed 2.1% of energy, somewhat less than chicken
dishes sourced from the grocery store (2.4%).
sources to energy intakes of adults ages ≥51y by pur-
chase location. Most of the dietary energy was contrib-
uted by store-bought breads (6.0%), grain-based desserts
(5.0%), beef (2.6%) and chicken dishes (2.4%), nuts
Table 2 Contribution to total energy intakes from specific food
sources by purchase location for children (6-11y),
NHANES 2003-2008
Store QSR FSR Other1
Category2 Average
calories
% of
total
Average
calories
% of
total
Average
calories

% of
total
Average
calories
% of
total
p-value
Yeast breads 89 4.4 10 0.5 4 0.2 26 1.3 <0.001
Pizza 31 1.5 48 2.4 15 0.7 25 1.3 <0.001
Reduced fat milk 66 3.3 3 0.1 1 0.1 42 2.1 <0.001
Chicken and chicken mixed dishes 42 2.1 33 1.7 9 0.4 19 0.9
<0.001
<0.001
Dairy desserts 42 2.1 12 0.6 4 0.2 11 0.6 <0.001
Sausage, franks, bacon and ribs 41 2.0 3 0.2 1 0.0 15 0.8 <0.001
Whole milk 45 2.2 0 0.0 0 0.0 14 0.7 <0.001

Beef and beef mixed dishes3 34 1.7 5 0.2 4 0.2 13 0.6 <0.001
Candy 39 1.9 0 0.0 0 0.0 17 0.9 <0.001
Fruit drinks 43 2.1 3 0.2 2 0.1 7 0.3 <0.001
Regular cheese 8 0.4 32 1.6 4 0.2 5 0.2 <0.001
Quickbreads 22 1.1 2 0.1 1 0.0 8 0.4 <0.001
Nuts/seeds and nut/seed mixed dishes 25 1.3 0 0 1 0.1 3 0.1
<0.001
Burgers3 0 0.0 24 1.2 0 0.0 0 0.0 <0.001
Other4 317 15.8 20 1.0 17 0.8 82 4.1 <0.001
1 Includes school cafeteria, child care, vending machine, food
provided by someone else, grown/caught, sports recreation
facility and others. 2 Sorted by rank for
total energy for ages 6-11y for comparison purposes, 3 Burgers,
as defined in the database, can only come from quick-service
restaurants. All burgers reported
from store or full-service restaurants are composed of
individual ingredients. Therefore, components of
hamburgers/cheeseburgers will be present in the yeast

breads, beef and beef mixed dishes, regular cheese and other
food groupings, 4 Others include all categories contributing
<1.3% of total energy for the
total population.
10
(2.6%) and alcohol (2.5%). The top QSR item, chicken,
contributed 1.1% of energy, less than chicken dishes
sourced from the grocery store. QSR pizza contributed
1.1% of energy in this age group.
Soda, energy and sports drinks, which receive much at-
tention in the policy arena, was predominantly sourced
from stores for all age groups. The specific contribution of
QSR soda to total energy intakes was in the order of 1%,
reaching a maximum of 1.4% of energy intakes in the 12-
19y age group. The contribution of FSR soda to total en-
ergy intakes was between 0.3% and 0.8% depending on age.
Discussion
The present research provides an analysis of energy in-
takes 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
sources by purchase location for adolescents (12-19y),
NHANES 2003-2008
Category2 Average
calories
% of
total
Average
calories
% of
total
Average
calories
% of
total
Average
calories
% of

total
p-value
Yeast breads 104 4.6 13 0.6 8 0.4 18 0.4 <0.001
Pizza 44 1.9 89 3.9 16 0.7 21 0.7 <0.001
Reduced fat milk 67 2.9 0 0.0 1 0.0 13 0.0 <0.001
<0.001
<0.001
Ready-to-eat cereals 61 2.7 0 0 0 0.0 1 0.0 <0.001
Dairy desserts 38 1.7 9 0.4 1 0.1 5 0.1 <0.001
Whole milk 36 1.6 0 0.0 0 0.0 6 0.0 <0.001
Candy 48 2.1 0 0.0 0 0.0 14 0.0 <0.001
Fruit drinks 43 1.9 5 0.2 2 0.1 7 0.1 <0.001

Regular cheese 35 1.6 8 0.4 5 0.2 9 0.2 <0.001
Quickbreads 27 1.2 7 0.3 4 0.2 6 0.2 <0.001
Nuts/seeds and nut/seed mixed dishes 26 1.1 0 0.0 0 0.0 2 0.0
<0.001
Burgers3 0 0.0 44 1.9 1 0.0 0 0.0 <0.001
Other4 318 14.0 33 1.4 30 1.3 55 1.3 <0.001
total population.
10

on age group. Restaurants including QSR and FSR, contri-
buted 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 ex-
ample, 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 bever-
ages 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.

sources by purchase location for younger adults
(age 20-50y), NHANES 2003-2008
Category2 Average
calories
% of
total
Average
calories
% of
total
Average
calories
% of
total
Average
calories
% of
total
p-value
Yeast breads 99 4.2 15 0.6 16 1.3 15 0.6 <0.001

Pizza 25 1.1 63 2.7 16 2.0 5 0.2 <0.001
Reduced fat milk 45 1.9 0 0.0 1 0.3 2 0.1 <0.001
<0.001
<0.001
Dairy desserts 33 1.4 8 0.3 2 0.4 3 0.1 <0.001
Whole milk 24 1.0 1 0.0 0 0.1 2 0.1 <0.001
Candy 39 1.7 0 0.0 0 0.1 10 0.4 <0.001
Fruit drinks 27 1.2 4 0.2 2 0.7 3 0.1 <0.001
Regular cheese 38 1.6 10 0.4 6 0.6 6 0.3 <0.001
Quickbreads 42 1.8 7 0.3 6 0.7 6 0.3 <0.001

<0.001
Burgers3 0 0.0 35 1.5 1 0.3 0 0.0 <0.001
Other4 396 16.8 42 1.8 60 2.6 59 2.5 <0.001
total population.
10
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 in-
takes [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 cur-
rently 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 com-
pensate 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 in-
cluding 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.
sources by purchase location for older adults (age
≥51), NHANES 2003-2008
Category2 Average
calories
% of
total

Average
calories
% of
total
Average
calories
% of
total
Average
calories
% of
total
p-value
Yeast breads 114 6.0 8 0.4 14 0.7 14 0.7 <0.001
Pizza 13 0.7 19 1.0 7 0.4 2 0.1 <0.001
Reduced fat milk 40 2.1 0 0.0 0 0.0 2 0.1 <0.001
<0.001
Soda, energy and sports drinks 40 2.1 8 0.4 5 0.3 5 0.3 <0.001

Dairy desserts 44 2.3 5 0.3 3 0.2 4 0.2 <0.001
Whole milk 15 0.8 0 0.0 0 0.0 1 0.1 <0.001
Candy 32 1.7 0 0.0 0 0.0 5 0.3 <0.001
Fruit drinks 15 0.8 0 0.0 1 0.1 1 0.1 <0.001
Regular cheese 32 1.7 3 0.2 3 0.2 4 0.2 <0.001
Quickbreads 30 1.6 4 0.2 4 0.2 4 0.2 <0.001
<0.001
Burgers3 0 0.0 16 0.8 0 0.0 0 0.0 <0.001
Other4 457 24.1 26 1.4 64 3.4 64 3.4 <0.001

total population.
10
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 en-
ergy 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 loca-
tions 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
Drewnowski and Rehm Nutrition Journal 2013, 12:59 Page 10
of 10
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 en-
ergy 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 loca-
tion. 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.

Conclusions
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 im-
portant food sources and purchase locations of energy,
thereby allowing for more effective targeting of policy inter-
ventions 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.
Additional file
Additional file 1: Table S1. Proportion of total energy by food
source
and food purchase location, by age group.
Competing interests
The authors declare that they have no competing interest.
Authors’ contributions
AD suggested statistical analyses and provided critical input
into the
manuscript. CR conducted the statistical analyses and helped to
draft the
manuscript. Both authors read and approved the final
manuscript.
Acknowledgment
Supported by the National Restaurant Association.
Received: 14 January 2013 Accepted: 2 May 2013
Published: 8 May 2013
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doi:10.1186/1475-2891-12-59
Cite this article as: Drewnowski and Rehm: Energy intakes of
US
children and adults by food purchase location and by specific
food
source. Nutrition Journal 2013 12:59.
http://www.biomedcentral.com/content/supplementary/1475-
2891-12-59-S1.doc
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center-obesity-forum_may-2006.pdf
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center-obesity-forum_may-2006.pdf
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f
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f
http://www.ars.usda.gov/services/docs.htm?docid=12089
http://www.ars.usda.gov/services/docs.htm?docid=12089
Reproduced with permission of the copyright owner. Further
reproduction prohibited without
permission.

AbstractBackgroundMethodsResultsConclusionsBackgroundMet
hodsDietary intake databasesFood purchase locationsSpecific
food sourcesAnalysis approachResultsEnergy intakes by food
purchase locationEnergy intakes by specific food sourcesEnergy
intakes by specific food source and purchase
locationDiscussionConclusionsAdditional fileCompeting
interestsAuthors’ contributionsAcknowledgmentReferences
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100630072006f006200610074002004420430002000410064006f
00620065002000520065006100640065007200200035002e00300
02004300431043e0020043f04560437043d04560448043e045700
20043204350440044104560457002e>
/ENU (Use these settings to create Adobe PDF documents for
quality printing on desktop printers and proofers. Created PDF
documents can be opened with Acrobat and Adobe Reader 5.0
and later.)
>>
/Namespace [
(Adobe)
(Common)
(1.0)
]
/OtherNamespaces [
<<
/AsReaderSpreads false
/CropImagesToFrames true
/ErrorControl /WarnAndContinue
/FlattenerIgnoreSpreadOverrides false

/IncludeGuidesGrids false
/IncludeNonPrinting false
/IncludeSlug false
/Namespace [
(Adobe)
(InDesign)
(4.0)
]
/OmitPlacedBitmaps false
/OmitPlacedEPS false
/OmitPlacedPDF false
/SimulateOverprint /Legacy
>>
<<
/AddBleedMarks false
/AddColorBars false
/AddCropMarks false
/AddPageInfo false
/AddRegMarks false
/ConvertColors /NoConversion
/DestinationProfileName ()
/DestinationProfileSelector /NA
/Downsample16BitImages true
/FlattenerPreset <<
/PresetSelector /MediumResolution
>>
/FormElements false
/GenerateStructure true
/IncludeBookmarks false
/IncludeHyperlinks false
/IncludeInteractive false
/IncludeLayers false
/IncludeProfiles true
/MultimediaHandling /UseObjectSettings
/Namespace [
(Adobe)

(CreativeSuite)
(2.0)
]
/PDFXOutputIntentProfileSelector /NA
/PreserveEditing true
/UntaggedCMYKHandling /LeaveUntagged
/UntaggedRGBHandling /LeaveUntagged
/UseDocumentBleed false
>>
]
>> setdistillerparams
<<
/HWResolution [2400 2400]
/PageSize [595.440 793.440]
>> setpagedevice

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