Family Economics and Nutrition Review [Volume 13, Number 1]

              CENTER FOR NUTRITION POLICY AND PROMOTION
Ann M. V eneman, Secretary
U.S. Department of Agriculture
Eric M. Bost, Under Secretary
Food, Nutrition, and Consumer Services
Steven N. Christensen, Acting Deputy Director
Center for Nutrition Policy and Promotion
P. Peter Basi otis, Director
Nutrition Policy and Analysis Staff
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Editor
Julia M. Dinkins
Assistant Editor
David M. Herring
Features Editor
Mark Lino
Managing Editor
Jane W. Fleming
Contributor
Joan C. Courtless
Family Economics and Nutrition Review is
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(See p. 126.)
Research Articles
3 Profiles of Selected Target Audiences: Promoting the Dietary Guidelines for Americans
Kay Loughrey, P. Peter Basiotis, Claire Zizza, and Julia M Dinkins
15 U.S. Teens and the Nutrient Contribution and Differences of Their Selected
Meal Patterns
Anna Maria Siega-Riz, Claude Cavadini, and Barry M. Popkin
27 Associations Between the Milk Mothers Drink and the Milk Consumed by Their
School-Aged Children
Rachel K. Johnson, Celeste V. Panely, and Min Qi Wang
37 The Effects of Food Advertising Policy on Televised Nutrient Content Claims and
Health Claims
Carol Byrd-Bredbenner and Darlene Grasso
50 The Thrifty Food Plan, 1999: Revisions of the Market Baskets
Staff at the Center for Nutrition Policy and Promotion-Compiled by Mark Lino
65 Sample Menus and Recipes Based on the 1999 Thrifty Food Plan
Staff at the Center for Nutrition Policy and Promotion-
Compiled by Myrtle Hogbin and Mark Lino
Research Briefs
77 USDA's Food Guide: Updating the Research Base to Reflect Changes in Food
Consumption Patterns
Kristin L. Marcoe
81 USDA's Expenditures on Children by Families Project: Uses and Changes Over Time
Mark Lino
87 Current Knowledge of the Health Effects of Sugar Intake
Anne L. Mardis
92 Insight 11 : Food Portions and Servings: How Do They Differ?
Myrtle Hogbin, Anne Shaw, and Rajen S. Anand
95 Insight 14: A Focus on Nutrition for the Elderly: It's Time to Take a Closer Look
Nancy W. Gaston, Anne Mardis, Shirley Gerrior, Nadine Sahyoun, and Rajen S. Anand
98 Insight 19: Beliefs and Attitudes of Americans Toward Their Diet
Julia M. Dinkins
Volume 13, Number 1
2001
Research Summaries
101 Consumer Price Index Research Series Using Current Methods
1 05 Changes in the Health Services Industry
108 Extended Measures of Well-Being: Meeting Basic Needs
112 Measuring Time at Work
Regular Items
1 15 Research and Evaluation Activities in USDA
118 Federal Studies: Review of the Nutritional Status of WIC Participants
120 Journal Abstracts
122 Official USDA Food Plans: Cost of Food at Home at Four Levels, U.S. Average, May 2001
123 Official USDA Alaska and Hawaii Thrifty Food Plans: Cost of Food at Home (2nd Half 2000)
124 Consumer Prices
125 U.S. Poverty Thresholds and Related Statistics
Kay Loughrey, MPH, RD
MRP
P. Peter Basiotis, PhD
Center for Nutrition Policy
and Promotion
Claire Zizzo, MS
University of North Carolina
at Chapel Hill
Julia M. Dinkins, PhD
Center for Nutrition Policy
and Promotion
2001 Vol. 13 No. I
Research Articles
Profiles of Selected Target
Audiences: Promoting the
Dietary Guidelines for Americans
To decrease the risk of nutrition-related diseases, Americans need to
narrow the gap between scientifically based nutrition guidance and
their nutrition-related behaviors. This study examines the usefulness
of segmentation and audience-profiling techniques in promoting the
Dietary Guidelines, designed to help narrow this gap. Using the 1991-
94 survey of the Market Research Corporation of America Information
Services (MRCA), we segmented 491 women gatekeepers into tertiles
(Better Eaters, Fair Eaters, and Poor Eaters) based on their scores on a
modified version of the Healthy Eating Index. We then compared the
segments' demographic characteristics; health and diet orientation;
values about, and perceived benefits and barriers to, healthful eating;
nutrition, food preparation, and shopping habits; and media habits.
Results showed that women gatekeepers were interested in improving
their diets, and they differed significantly regarding values, benefits,
and barriers of eating a healthful diet and nutrition; food preparation
practices; and shopping habits. We discussed the implications of these
differences in terms of improving the quality of the diet.
T he Dietary Guidelines for
Americans (23), issued by the
U.S. Departments of Agriculture
(USDA) and Health and Human
Services (DHHS), answer this basic
question: "What should people eat to
stay healthy?" Forming the basis of
Federal nutrition policy affecting food,
nutrition education, and information
programs, the Guidelines stress the
significance of dietary balance, variety,
and moderation (7). Still, in the United
States, four of the leading causes of
death-heart disease, cancer, stroke,
and diabetes-are linked to nutrition
(1 0). Americans still need to increase
total intake of fruits, vegetables, and
grain products and to decrease intake
of fat and saturated fat. Although some
progress has been made based on
progress in meeting Year 2000
Objectives, the startling increase in
the portion of Americans who are
overweight or obese poses one of the
biggest challenges in meeting Healthy
People 2000 (24). A summary measure
of dietary status- the Healthy Eating
Index-has shown that 7 of I 0 Ameri­cans
need to improve their diet (4) .
Other results have also indicated that
although Americans choose a wide
variety of foods, they consume less
than the recommended servings from
the fruit, dairy, meat, grains, and
vegetable groups of the Food Guide
Pyramid. Americans' consumption of
calories from fats and sugars, however,
exceeds Pyramid recommendations
(11).
3
Thus evidence has shown that Ameri­cans
still need to improve their diet;
Americans need to narrow the gap
between scientifically based nutrition
guidance and consumer behavior that
may increase the risk of illness from
nutrition-related diseases. To better
meet the needs of the public, some
authors believe the Guidelines need to
do two things: (1) continue to advance
national dietary guidance that is based
upon scientific evidence and (2) pro­mote
dietary guidance in ways that
will lead to behavior change, improved
health, and nutritional well-being (22) .
The purpose of this study is to examine
the extent to which major differences
exist between audience segments on
key variables, to profile these audience
segments, and to suggest whether these
differences warrant distinct nutrition
education approaches in attempting to
change dietary behaviors. We describe
three segments of female gatekeepers
and how their characteristics differ on
several dimensions: demographic and
health status; values about, and benefits
and barriers to, healthful eating; nutri­tion,
food preparation, and shopping
habits; and media habits. We discuss
the implications of these differences
in terms of improving the dietary
behavior of these segments. We
believe that nutrition educators can
directly apply this information when
they design program interventions.
The underlying assumption of social
marketing and marketing approaches
is that different audience segments
require alternate approaches for
achieving a desired behavior change.
This study examines whether this
assumption applies to nutrition educa­tion
to create dietary behavior change.
4
Lastly, we examined results in relation­ship
to behavioral models and theories.
We examined how the segments might
differ with respect to their stage of
behavior change and the extent to
which audience segments could be
described, based on Prochaska and Di
Clemente's trans theoretical model of
change (18). The stages of this model
are precontemplation (not considering
whether to make a change), contempla­tion
(thinking about making a change),
decision (making definite plans to
change), action (initiating change), and
maintenance. This model has been used
to describe dietary behavior in relation­ship
to weight control and the reduction
of dietary fat (6, 19).
We looked to social learning theory,
which is based on social cognitive
theory, to inform recommendations
for designing strategies for behavior
change (3,17). Social learning theory
emphasizes the interaction of cogni­tion,
other personal factors (e.g., self­efficacy),
and environmental factors
on behavior. Several critical personal
factors suggested by social learning
theory have been assessed in this
analysis:
• Perception of the situation
• Anticipated outcomes of behavior
• Knowledge and skills to perform a
behavior
• Confidence in performing a
behavior
We considered the theory of planned
behavior in forming program implica­tions
(1). This theory suggests that
people will be more likely to take
action if it leads to consequences they
desire. It also suggests that behavior
and behavioral intent are influenced by
the degree of control people think they
have over circumstances and their
ability to perform a behavior.
Background
Research indicates that nutrition
promotion of the Guidelines should
focus on behavior change; have a
strong consumer orientation; segment
and target consumers; use multiple,
reinforcing, interactive channels; and
refine consumer messages continually
(22,23). Segmentation, a frequently
used approach in commercial-sector
marketing, has been used in programs
designed to change health behaviors
(2) and has been used to create a profile
or snapshot that represents the target
audience. It, as well, has encouraged
creative communication that is tailored
to the target audience (6,12,15).
To segment audiences, social marketers
analyze potential markets and create
subgroups of target populations with
similar characteristics regarding the
desired behavior. Then they allocate
resources among one or more sub­groups
and vary the methods used to
reach each subset (2). Health communi­cators
also use segmentation methods
to identify people who are similar in
key respects and to tailor the content
and delivery of the communication
based on people's profiles (16,21).
Target-audience profiles have been
used in large-scale nutrition education
programs, including the 5 A Day media
campaign of the National Cancer
Institute (1 3,15) and the Nutrition and
Physical Activity program of the
Centers for Disease Control (9).
Family Economics and Nutrition Review
Methods
Database
We analyzed data from the 1991-94
survey of the Market Research Corpo­ration
of America Information Services
(MRCA). Nationally representative, the
MRCA survey consists of information
on people's food and beverage con­sumption
and their opinions and
attitudes about general interests, health,
diet and food preparation, shopping,
and media usage. The MRCA data set
consists of five surveys and two data­base
systems: Household Information
Form, Menu Census Diaries, Pyscho­graphic
Questionnaire, Diet Informa­tion
Quiz, and Food and Nutrition
Attitude Inventory.
To select participating households,
MRCA uses a multistage, stratified­random
procedure. In stage !-the
Household Recruiting Pool-a sam­pling
pool of households is generated
from generic consumer listings of U.S.
households of various demographic
types. Households that agree to par­ticipate
then qualify for the second
stage of sampling-the National
Consumer Panel. The Panel consists of
5,000 households whose demographic
characteristics (household size, home­maker
age, household income, census
regions, and metro-area size) are
matched to the U.S. Census. The third
stage-the Menu Census Panel­consists
of a subsample of households
(n=2,000) from the National Consumer
Panel. For the Menu Census Panel,
MRCA uses a stratified-random
procedure to select 500 households
each quarter. Detailed food diaries of
food and beverage consumption are
collected for 14 consecutive days.
Actual serving sizes are not collected.
They are imputed based on eating
occasions for individual foods by
applying standard serving sizes. For
this reason, they should be considered
2001 Vol. 13 No. 1
estimates rather than precise measures
of food and beverage consumption.
The Nutrient Intake database measures
macro- and micro-nutrient intake;
the Food Guide Pyramid database
measures "servings"' of the Pyramid
Food Groups.
Healthful Eating Measure
The USDA Healthy Eating Index (HEI)
measures the overall quality of Ameri­cans'
diet (4) and uses data from the
USDA Continuing Survey ofFood
Intakes by Individuals (CSFII). The
HEI uses 1 0 components to measure
different aspects of a healthful diet:
• Components 1-5 measure the
degree to which a person's diet
conforms to serving recommenda­tions
of the food groups of the
USDA Food Guide Pyramid:
Grains (bread, cereal, rice, and
pasta), vegetables, fruits, milk
(milk, yogurt, and cheese), and
meat (meat, poultry, fish, dry
beans, eggs, and nuts).
• Components 6 and 7 measure
consumption of total fat and
saturated fat, respectively, as a
percentage of total food energy
intake.
• Component 8 measures total
cholesterol intake.
• Component 9 measures sodium
intake.
• Component 10 measures the variety
of a person's diet on any given day.
1
MRCA used total frequency of"eatings" as the
main measure of the individual food consumed.
MRCA estimated serving sizes for each eating
occasion for over 330 collapsed food categories
based on 1987-88 USDA data on number of
grams for each eating occasion for individual
food items. MRCA then assigned different
serving sizes to 18 age-gender groups: four age
groups for children under 12 and seven age
groups each for males and females over age 13.
Americans still need
to improve their diet;
Americans need to
narrow the gap between
scientifically based nutrition
guidance and consumer
behavior that may increase
the risk of illness from
nutrition-related diseases.
5
Each component of the HEI has a
maximum score of 10 and a minimum
score of zero; intermediate scores are
computed proportionately. The maxi­mum
overall score for the 10 compo­nents
combined is 100. Higher compo­nent
scores indicate intakes close to
recommended ranges or amounts.
The MRCA does not provide informa­tion
on variety; hence, we used a mod­ified
version of the HEI to examine
characteristics that distinguish women
from the MRCA sample with higher
quality diets from those with lower
quality diets. All scores on the modified
version were adjusted to a 1 00-point
score. Thus the total maximum score
was 100. To compute individual HEI
scores, we matched the female gate­keeper
to the appropriate serving
recommendations of the Pyramid Food
Groups. We calculated gatekeepers'
average percentage of calories from
total fat and saturated fat and compared
their intakes of cholesterol and sodium
with Pyramid recommendations.
Sample
We selected healthy adult women in
the United States as the unit of analysis
(target audience) because they often are
gatekeepers who shape their family's
nutrition and health habits.
Our sample consisted of women
gatekeepers aged 25 through 55,
reporting household income of
$20,000 to $125,000 and no major
health problems. Those excluded
reported having high blood pressure,
diabetes, heart disease, high levels of
serum cholesterol, or followed a diet
for diabetes or allergies. We could
not use marital status as a screening
variable because MRCA does not
include information on respondents'
marital status. The database also does
not include information on vegetarian
diets, employment status or profession,
6
and the relationship of household
members. The final sample of 491
gatekeepers was weighted to reflect
the U.S. population of interest.
After ranking and dividing the
gatekeepers into tertiles (segments)
based on their scores on the modified
HEI, we developed profiles of the
women gatekeepers and used multiple
t tests to examine differences among
the three segments. SUDAAN (Soft­ware
for the Statistical Analysis of
Correlational Data), which accounts
for sampling designs that are complex
and stratified, was used in the analysis
to ensure appropriate estimates of
standard errors for hypotheses testing.2
Results
Demographic Characteristics
The women gatekeepers who were
Better Eaters (having the highest HEI
score) are the basis of comparison with
other groups of women gatekeepers:
Fair Eaters and Poor Eaters. The
women gatekeepers differed in some
ways (table 1). Compared with the
other groups, the Better Eaters more
closely met the recommendations of
the USDA Food Guide Pyramid. Based
on percentages, overall, the women
gatekeepers' average Healthy Eating
Index score was 57 percent. With
an average score of74 percent, the
Better Eater had the higher HEI score,
followed by the Fair Eater, with
62 percent; and Poor Eater, with 52
percent. Healthy Eating Index scores
were calculated based on the degree
to which a person in the sample's diet
2
"SUDAAN is specifically designed for analysis
of cluster-correlated data from studies involving
recurrent events, longitudinal data, repeated
measures, multivariate outcomes, multistage
sample designs, stratified designs, unequally
weighted data, and without replacement
samples" (20).
conformed to serving recommendations
of the food groups of the USDA Food
Guide Pyramid as previously
described.
There are small differences in the
gatekeepers' average years of educa­tion,
height, Body Mass Index (BMI),
likelihood of having children present
in the household, and race. The Better
Eater was more likely than the other
Eaters to have more years of education.
Compared with the Poor Eater, the
Better Eater had a lower BMI score,
was slightly taller, and more likely to
be White or of a race other than Black.
Compared with the Fair Eater, the
Better Eater was less likely to have
children.
The women gatekeepers had some
characteristics in common (tables 1
and 2). Their characteristics were
considered similar if more than 60
percent of the women in each group
exhibited them and if the differences
in the characteristics were statistically
insignificant (p>.Ol). These three
groups were similar demographically
based on age, household size, house­hold
income, and self-reported weight.
Values, Benefits, and Barriers
to Healthful Eating
Similar to the Better Eater, the Fair
Eater (F) reported that eating a health­ful
diet was important to her (table 3).
Both said they could avoid future
health problems-a perceived long­term
benefit-by eating more
healthfully. Similarly, the Fair Eater
and the Better Eater reported that
eating "healthy foods" gave them the
energy they needed- a perceived short­term
benefit- and agreed that eating
"healthy foods" improved their
physical appearance.
Family Economics and Nutrition Review
Table 1 . Education distinguishes all three segments of women gatekeepers:
Demographic and health status variables, MRCA 1991-94
Diet status
Variable Better Eaters Fair Eaters Poor Eaters
Mean
Age (years) 39 38 38
Household size 3.3 3.3 3.3
Household income (thousands) 42.97 41.40 41.93
Education (years) 14.2* 13.7* 13.2*
Weight (kg) 67.39 67.96 71 .65
Height (em) 164.7* 163.9 162.7*
BMI 25.07* 25.54 27.31*
Percent
HEI score' 74 62 52
Children present 56* 72* 65
White 94.9* 87.5 83.6*
Block 4.1 7.3 9.3
Other 1.0* 5.2 7.1*
'The Healthy Eating Index scores differ because this foetor was used to segment the women
gatekeepers.
*Means or percentages within the some row ore significantly different (p < 0.05).
The Fair Eater differed, however, from
the Better Eater in two important ways.
( 1) She was Jess likely than the Better
Eater to believe she could avoid future
health problems by exercising. (2) Both
convenience and taste were barriers for
the Fair Eater, who was more likely
than the Better Eater to say that
"healthy foods" had to be convenient
for her to use them and to report that a
reason for not choosing healthful foods
was because they didn't taste good.
The Poor Eater (P) was less likely than
the Better Eater to believe it was
important to eat a healthful diet, look
and feel physically fit, maintain a
proper weight, and to identify with
potential benefits of healthful eating.
She was less likely to agree that she
could avoid future health problems by
eating a healthful diet and by exercis­ing;
she was less likely to report the
perceived short-term benefit that eating
"healthy foods" gave her the energy
she needed and improved her physical
appearance. The Poor Eater also
2001 Vol. 13 No. 1
indicated that she was less likely than
her counterpart to say she knew how to
eat healthfully. She was, however, more
likely than the Better Eater to report
that eating healthfully was too compli­cated
and confusing.
Health and Diet Orientation
All of the women gatekeepers believed
they were knowledgeable about health
and nutrition (table 2). They reported
an interest in improving their diets,
agreed they had some weight to lose,
and tried to do so, at least occasionally.
Similarly, they agreed that it was
important for them to live long and
healthy lives.
Nutrition, Food Preparation,
and ·Shopping Habits
Similar practices among the women
gatekeepers extended to how they
shopped for food and planned and
prepared it (table 2). Among the many
similarities, all three groups redeemed
the coupons they clipped from maga­zines
and newspapers.
The Poor Eater was less
likely than the Better Eater
to believe it was important
to eat a healthful diet,
look and feel physically fit,
maintain a proper weight,
and to identify with
potential benefits of
healthful eating.
7
Table 2. Better Eaters, Fair Eaters, and Poor Eaters have many characteristics' in common, MRCA 1991-94
Variable
Health and diet orientation
Physical activity
Pyschographics
Shopping
Food planning and preparation
Family eating habits
Media
Commonalities
Believe they ore knowledgeable about health and nutrition
Interested in improving their diets
Think they hove some weight to lose
Try, at least occasionally, to lose weight
Believe it is important for them to live a long, healthy life
Frequency
Like to meet new people
Join actively in community groups
Desire to be well respected
Like the outdoors
Enjoy taking the family to a different vocation spot each year
Make a complete list before going shopping
Enjoy browsing through supermarket aisles
Do not like the excitement of a busy supermarket
Save a lot of money by shopping around for food bargains
Stock up on named brand foods that they like during soles
Cut coupons out of newspapers and magazines
Redeem coupons (almost always)
Send away for items offered through advertising
Willing to pay for certain food items for special occasions
En joy cooking and think of themselves OS creative cooks
Don't like to bother cooking just for themselves (when alone)
Enjoy preparing a fancy meal for their families once in awhile
Collect recipes from the food sections of the newspapers
Exchange recipes with friends and relatives
Add something extra (almost always) to prepared foods
Serve the some evening meals from one week to the next
Try to make use of leftovers but usually throw them out
Hove some family members who ore concerned about being overweight
View television-network evening news, cable news/ television
Read magazines and newspaper
'Characteristics were common if more than 60 percent of each group exhibited them and if the differences in the characteristics were statistically
insignificant (p > .01 ).
8 Family Economics and Nutrition Review
Table 3. Most measured beliefs and practices of Poor and Fair Eaters differ from those of Better Eaters, MRCA 1991-94
Degree to which Poor (P) and Fair (F) Eaters soy the following,
compared with Better Eaters
Variable As likely More likely Less likely
Values, Benefits, and Batriers
Eating a healthy diet is important to me. F
I can ovoid future health problems by eating healthfully. F
I choose healthy foods because they give me the energy I need. F
I choose healthy foods because they improve my
physical appearance. F
Healthy foods hove to be convenient for me to use them .
A reason for not choosing healthy foods is they don't taste good.
Trying to eat healthy is too complicated and confusing .
I con ovoid future health problems by exercising.
It is important for me to look and feel physically fit.
It is important for me to maintain my proper weight.
I know how to eat healthy.
Nutrition, Food Preparation, and Shopping Habits
I worry about the nutritional content of the foods I eat. F
I always see to it that my family takes vitamins. P
I'm much more willing to try a new recipe when someone
I know tried it and liked it.
I always or usually pay attention to on-shelf, aisle display.
Most snack foods I like ore unhealthy.
I do not discuss various foods and their food values with
my family so they understand nutrition better.
I always pay attention to instant coupons.
I make every possible effort to see that my family eats really
nourishing foods.
I get upset if the family doesn't eat together.
I go out of my way to buy non-fat foods.
Frozen foods ore more nutritious than conned foods.
I serve fish because it has less fat.
I disagree that red meat is better for your health than fish .
I do not look for prepared dishes when I shop.
I collect recipes from magazines.
I disagree that my family is easy to please.
Media
I watch television in general, including entertainment programs,
and daytime television .
I watch television programs like police/ private eye and daytime
serials because I really like them .
I watch television serials/soap operas because I like them .
I watch prime-time television programs.
I read women's general interest magazines.
F
F
F, p
F
F
p
p
P, F
F, p
F, p
F
P, F
p
p
p
F, p
p
p
p
p
F
F, p
F, p
F, p
F, p
F, p
F
p
p
p
p
Note: The "F" and "P" for the Fair Eaters and Poor Eaters, respectively, indicate that these women gatekeepers differ significantly from the comparison
group: the Better Eaters, at the 0.01 level.
2001 Vol. 13 No. 1 9
Compared with the Better
Eater, the Poor Eater was
less likely to worry ~bout
the nutritional content of
the foods she ate.
10
The groups differed, however, in a
number of important ways related to
nutrition, food preparation, and
shopping habits (table 3). Similar to
the Better Eater, the Fair Eater worried
about the nutritional content of the
foods she ate. Still, she was less likely
than the Better Eater to make an effort
to serve her family nourishing foods,
get upset if the family didn't eat
together, and go out of her way to
buy nonfat foods. She was more likely
than the Better Eater to pay attention to
on-shelf, aisle display ads and instant
coupons and to look for prepared foods
when shopping.
Compared with the Better Eater, the
Poor Eater was less likely to worry
about the nutritional content of the
foods she ate. Like the Fair Eater, she
was also less likely than the Better
Eater to make every possible effort
to see that her family ate nourishing
foods, to get upset if the family didn't
eat together, and to go out of her way
to buy nonfat foods. The Poor Eater
was more likely than the Better Eater
to pay attention to instant coupons, to
agree that most of the snack foods she
liked were unhealthful, and to disagree
that she discussed foods with her
family so they understood nutrition
better.
Media
The three groups watched similar
television programs or stations­evening
network news, cable news,
and cable TV-and they read similar
magazines and newspapers (table 2).
However, the Fair Eater and Poqr Eater
were more likely than the Better Eater
~o watch television in general, includ­mg
entertainment (non-news) shows
and daytime programs (table 3). The
Poor Eater also watched less prime­time
television than did the Better Eater
and was less likely to read women's
general interest magazines.
Discussion
Profiles
Demographic differences in audience
segments do not explain the overall
differences in the three segments'
approaches to food consumption.
Results of this analysis indicate a small
number of demographic differences.
Then what might explain these
differences?
The Better Eaters are more likely than
the Poor Eaters to report that eating a
healthful diet is important to them and
are concerned about the nutritional
content of their diets. They are likely to
perceive short- and long-term benefits
of eating healthfully, and are taking
action to eat healthfully.
Better Eaters are categorized in this
analysis as being either in the action
or maintenance stages of the trans­theoretical
model of change, though
direct assessment of the stages of
change was not measured in this
analysis. Better Eaters are considered
in one of these two stages of change
based on their HEI score, their con­cerns
about nutrition, and their greater
tendency to act on their concerns. It
is therefore not possible to determine
precisely whether they are in the
action or maintenance stage, using the
algorithm applied by Curry et al. for
staging dietary fat reduction (6).
In terms of social learning theory,
Better Eaters appear to be able to
anticipate the outcomes of their
behavior and self-determine their
behavior, successfully although not
perfectly. They appear to be confident
of their ability to carry out healthful
eating behaviors based on their being
less likely to report that trying to eat
more healthfully is complicated and
confusing than did women in the other
two segments. Better Eaters experience
Family Economics and Nutrition Review
a rather high degree of control over
their circumstances in terms of eating
healthfully, based on their responses to
all questions, collectively. This charac­teristic
is a key factor in the theory of
planned behavior. Still, Better Eaters
have room for improving their diets
based on their HEI scores.
Fair Eaters, compared with Better
Eaters, report a mixture of benefits,
barriers, and actions that may account
for their lower HEI score. Like the
Better Eaters, Fair Eaters are more
likely than the Poor Eaters to report
that eating a healthful diet is important
to them, and are concerned about the
nutritional content of their diets. They
are as likely as Better Eaters to per­ceive
short- and long-tenn benefits of
eating healthfully, and are taking some
action to eat healthfully. However, they
are less likely to go out of their way
to eat healthfully, such as making an
effort to serve their families nourishing
foods and buying nonfat foods. They
are more likely to respond to in-store
promotions such as on-shelf, aisle
display ads, and instant coupons.
Taste and convenience are especially
important to Fair Eaters, and they are
more likely than Better Eaters to select
prepared foods. In terms of media use,
they are more likely to watch televi­sion,
particularly for entertainment.
Lastly, the Fair Eaters are more likely
to report that eating healthfully is
complicated and confusing, compared
with Better Eaters.
In sum: Fair-Eaters are convinced yet
not committed to eating healthfully.
While they are interested in the positive
results associated with eating health­fully
and are convinced of its benefits,
Fair Eaters are less proactive in making
healthful eating choices, and appear to
respond passively to stimuli in their
environment, be it family, in-store cues,
desire for sensory satisfaction, or ease
in meal preparation. As a group, they
2001 Vol. 13 No. I
appear to eat healthfully when it's
convenient and could be characterized
as "convinced, but not committed" to
eating healthfully. Many factors can
intervene in their environment to
prevent them from eating healthfully.
Fair Eaters could be considered to be in
a late stage of contemplation in terms
of stages of change, although screening
questions for staging were not included
in the original MRCA questionnaire.
No questions were asked that could
help determine whether Fair Eaters had
developed a plan of action that would
place them in the preparation stage of
the transtheoretical model of change.
Still, their passivity in relationship to
environmental cues indicates that they
have not developed a concerted plan of
action that they intend to implement in
the near future.
In terms of social learning theory, Fair
Eaters are aware of the outcomes of
behaviors, including expected results
and benefits but lack the knowledge
and confidence to eat more healthfully
based on the fact that, compared with
Better Eaters, they are more likely to
report that trying to eat healthfully is
too complicated and confusing. They
also seem to experience a rather low
degree of control over their circum­stances,
an important factor influencing
their behavior that is emphasized by the
theory of planned behavior.
A number of factors may prevent Poor
Eaters from taking actions that could
improve their dietary habits, factors
that may account for their HEI scores
being the lowest among these three
groups. They are less likely to report an
interest in achieving results related to
healthful eating. For example, they are
less likely to report that eating more
healthfully is important to them,
compared with Better Eaters. Poor
Eaters are also less likely to be con­vinced
of long-term benefits: they are
less likely than Better Eaters to agree
that they can avoid future health
problems by eating a healthful diet.
Nor are they convinced of short-term
benefits such as being less likely to
agree that "healthy foods" give them
the energy they need. They are also less
likely to know how to eat healthfully
and are more likely to perceive that
eating healthfully is complicated and
confusing.
Poor Eaters are less concerned about
nutrition for themselves and their
families: they are less likely to report
that they worry about the nutrient
content of the food they eat. They
are also less likely to talk with their
families about foods in terms of their
nutritional value or to report making
every possible effort to see that their
families eat nourishing food.
Thus Poor Eaters are somewhat
interested in improving their diets, but
are not convinced of the benefits of
doing so. They are also less concerned
with achieving the potential results of
eating healthfully than are Better
Eaters. While they, like other
gatekeepers, claim to be knowledge­able
about health and nutrition, they
admit to not knowing how to eat
healthfully. They could be character­ized
as "interested but unconvinced"
that healthful eating is particularly
relevant to them.
Poor Eaters could be categorized as
being in an early phase of contempla­tion
(transtheoretical model of change)
based on their interest in improving
their diet. Although Poor Eaters appear
to be aware of where they stand when
it comes to eating healthfully, they
lack three key critical personal factors
described by social learning theory: (1)
the ability to anticipate outcomes of
their behavior, (2) knowledge and skills
to act, and (3) confidence to perform
this behavior.
11
Program Implications
Given the large number of characteris­tics
these three segments of women
have in common, should the same
approach to nutrition education be
used for these three groups? Speaking
in favor of a common approach are
the characteristics the three segments
share. However, many of the character­istics
the three audience segments have
in common may be attributed to the
fact that the segments are all primary
food preparers. A number of important
differences among these three segments
of women discussed in this paper
suggest that different approaches to
nutrition education are needed for
each segment.
For the Better Eaters especially,
providing tips that are simple, positive,
and easy to apply may build on their
current interest and actions to improve
their diets. A different approach should
be used with Fair Eaters. Nutrition
education for this group should
appeal to their interest in taste and
convenience. Communication and
education strategies should be used
to deliver actionable messages and
illustrate easy methods for improving
their diet that do not sacrifice taste.
Suggestions should be offered that are
easy to apply such as adding a grated
carrot to prepared tomato sauce as a
way to add sweetness, improve its
taste, and add important nutrients.
It may also be helpful to highlight
convenient ways to more healthful
eating such as offering ideas that they
can do quickly such as a "10-minute­a-
day" way to improving their eating
habits. Fair Eaters should be targeted
with a few carefully selected nutrition
messages that are easy to understand
and apply, and that are likely to cut
through confusion generated by media
coverage of nutrition news. Nutrition
education for Fair Eaters should use
mass media to remind them frequently
about eating healthfully. It should also
be presented in an entertaining way,
12
because this audience is used to regular
television entertainment.
It will require a highly targeted
approach to reach Poor Eaters with
nutrition education. An approach is
needed that immediately captures their
attention and establishes cultural and
lifestyle relevance. To help establish
relevance of consequences of healthful
eating, messages to this audience
should come from people they perceive
as peers or from someone they admire,
such as a celebrity, who can model the
desired behavior. For example, the
Milk Mustache Campaign has shown
celebrities and opinion leaders with
their milk mustaches as a way to
establish that drinking milk is a highly
acceptable and desirable behavior with
their target market.
Nutrition education programs and
materials that are highly targeted to a
specific lifestyle or cultural experience
are likely to be welcomed. For ex­ample,
the National Cancer Institute
developed and tested Down Home
Healthy, a recipe booklet designed for
an African-American audience, and
found that respondents were highly
interested in this book because of its
cultural relevance (8). Introducing this
recipe booklet was used to explore
interest in an approach of encouraging
African Americans to use modified
versions of traditional recipes to lower
fat and increase fiber intake. Responses
to the recipe booklet and accompany­ing
brochure were the most active and
engaging aspects of focus group
sessions. Participants welcome9 this
approach, if the taste of the food
presented in the recipes met their
expectations.
Successful nutrition education strate­gies
are recommended that will break
abstract nutrition concepts into practi­cal
action steps that can easily be
mastered and applied to help build
knowledge, skills, and self-efficacy for
eating more healthfully. For example,
guidance about adding more fiber to
the diet should include a brief discus­sion
of the Nutrition Facts panel of the
food label. It should include making a
specific request to ask people to go to
the grocery store and compare the fiber
content on the food label of several
breakfast cereals they like, and then
purchase a cereal that contains 20
percent or more of the Daily Value for
fiber per serving. This approach was
highly effective in transforming apathy
into keen interest in nutrition among
working and middle-class women
attending focus groups sponsored by
the National Cancer Institute (1 4).
This segment of women gatekeepers, in
particular, may be encouraged to begin
taking action as they experience more
short-term benefits that are meaningful
and motivating. To accomplish this,
nutrition education and promotion
efforts for Poor Eaters should move
them from being interested to being
convinced that healthful eating is
meaningful and relevant to them.
Summary
The most effective ways to reach these
women gatekeepers by segment is as
follows:
1. Better Eaters: Offer new tips that
can be added to their current
actions for eating healthfully.
2. Fair Eaters: Insert frequent
environmental cues to eating
healthfully that will appeal to their
interest in taste and convenience.
3. Poor Eaters: Establish relevance
by identifying ways to appeal
immediately to this audience that
are consistent with their lifestyle
and cultural context.
Family Economics and Nutrition Review
These fmdings are consistent with those
of authors reviewing nutrition education
for adults (5). In their review of
successful nutrition education interven­tions
for adults, the authors suggested
nutrition education communication and
strategies in programs that
• Are ongoing and multifaceted;
• Use mass media to increase
awareness and enhance motivation;
• Tailor strategies based on formative
audience research;
• Use motivational messages and
educational strategies; and
• Employ a behaviorally focused
approach that is based on personal
factors, behavioral capabilities, and
environmental factors.
The results of this study suggest that
nutrition educators can apply the same
segmentation methods used by social
marketers and health communicators.
It can be expected that doing so would
allow them to make the most effective
use of resources and to increase
program efficiency. We suggest that
with a greater understanding of
applicable target segments, nutrition
educators, policymakers, and other
information multipliers will be better­positioned
to improve the diets of
Americans.
2001 Vol. 13 No. 1
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14 Family Economics and Nutrition Review
Anna Maria Siega-Riz, PhD
Department of Nutrition
School of Public Health
University of North Carolina
at Chapel Hill, NC, USA
Claude Cavadini
Nestle Research Center
Lausanne, Switzerland
Barry M. Popkin, PhD
Department of Nutrition
School of Public Health
University of North Carolina
at Chapel Hill, NC, USA
2001 Vol. 13 No. 1
U.S. Teens and the Nutrient
Contribution and Differences of
Their Selected Meal Patterns
We examined the nutrient contribution of foods consumed at breakfast,
brunch, lunch, dinner, and snacks, as well as the types of foods con­sumed
on those occasions, by adolescents (n= 1,31 0) participating in
the 1989-91 Continuing Survey of Food Intakes by Individuals. Descrip­tive
statistics were generated, using weights and taking into account
sample design effects, to examine the consistency of their meal patterns:
Consistent, moderately consistent, and inconsistent. Results showed that
for individuals with an inconsistent meal pattern, dinner provided half of
the day's energy and total snacks provided over one-fifth, an equivalent
of one meal for others. Most nutrients studied (fat, protein, calcium, and
iron) followed the same pattern as energy. Age differences were noted :
15- to 18-year-olds were more likely to have inconsistent patterns. The
types of foods consumed also differed by meal pattern. Both increasing
the consistency in the number of meals consumed, as well as improving
food-selection behaviors, may serve as possible interventions to improve
the diets of adolescents.
A dolescence is a period of great
transitions. Nutrient require
ments are increased from
childhood because of physical growth,
and behaviors acquired during this
period persist into adulthood (1,11,
17,22). While many subsets of adoles­cents
engage in behaviors that have
wide public health attention, some
adolescents may also follow pathways
of poor food choices and reduced
physical activity-both of which can
also have deleterious effects on health
(10,25). Among the health conse­quences
of following these pathways
have been rapid increases in obesity
and adult-onset diabetes (1 3,23,26).
Members of this age group are influ­enced
strongly by their peers, the
media, and family situation and less
by their knowledge of risky behaviors
(6,21,22).
Skipping meals is a common practice
among adolescents: about 20 percent
do not eat breakfast, and about half as
many do not eat lunch (3,5,10,18,19).
Skipping meals may lead to more
snacking; for those who do not view
skipping meals as a method of weight
loss, snacks often compensate for
missed calories and other key nutrients.
The literature indicates that, on
average, most children and adolescents
average four eating occasions a day,
with an upper range of 13 occasions
among Mexican children who con­sumed
as much as 45 percent of their
energy from snacks (4,7,8). Research
on the meal patterns of U.S. adoles­cents
showed that most consume at
least two meals (plus or minus snacks)
on a consistent basis while some follow
a highly inconsistent meal pattern: one
meal and/or snacks all day (18).
15
Compared with adolescents with
inconsistent meal patterns, those with
consistent meal patterns consumed a
diet that was adequate in calories and
more nutrient dense (with respect to
calcium, iron, vitamin E, and fiber)
(1 1). Our study examines in more
detail the types of food consumed by
adolescents at each eating occasion
and the nutrient contributions provided
by each eating occasion to adolescents'
total daily intakes. This study is unique:
we examine snacking behaviors by
using a nationally representative
sample, and we determine the nutrient
contributions of snacks. Previous
studies have examined only the nutrient
density of meals versus snacks without
considering their contribution to the
total diet, or previous studies have
used very small samples to examine
this research question (2,16).
Methods
Survey Design
Food consumption data were provided
by the 1989-91 Continuing Survey of
Food Intakes by Individuals (CSFII), a
survey conducted by the U.S. Depart­ment
of Agriculture's Agriculture
Research Service. A nationally repre­sentative
sample was collected by using
a multistage, stratified sample design
of the 48 coterminous States and
Washington, DC. Data were collected
in four waves during each year: one in
each season, between April 1989 and
May 1991. In each wave, a different
sample of participants was selected.
The total number of participants in
all age groups sampled was 15,192.
Dietary data were collected for each
individual in selected households.
Using a 24-hour recall and two 1-day
food records, individuals reported 3
consecutive days of intake. The female
head of the household reported dietary
intake for individuals less than 12 years
16
old. We were interested in the eating
patterns of adolescents, thus our
analysis was restricted to 11- to 18-
year-olds who reported 3 days of
dietary intake (n= 1,31 0). The classifi­cation
of individuals into meal-pattern
categories did not differ between 11-
and 12-year-olds, and the differences
in nutrient composition of reported
intakes of 11- and 12-year-olds were
similar in magnitude to the differences
between 12- and 13-year-olds. There­fore,
11-year-olds were included in the
analysis despite differences in methods
of data collection for dietary intake.
Variables
Meal Paffems
Survey data include descriptors of
eating occasion (breakfast, lunch,
dinner, supper, snack, brunch, and
extended consumption) as well as the
time of day each food was consumed.
To identify meal patterns, we first
developed clear and invariable termi­nology
for eating occasions: Breakfast,
lunch, brunch, dinner, or snack.
Respondents provided the name for
each meal. When respondents reported
consuming either supper or dinner, the
eating occasion was designated as
dinner; when the respondent reported
consuming both supper and dinner,
dinner was designated as lunch and
supper designated as dinner. This
categorization was based on analysis
of the data, which indicated that dinner
was consumed primarily as an evening
meal (85 to 87 percent between 4 and
8 p.m.). When both supper and dinner
were consumed, dinner was the midday
meal (56 to 69 percent betwee!l 11 a.m.
and 3 p.m.) and supper was the evening
meal (70 to 81 percent between 4 and 8
p.m.). Eating occasions for 1.3 percent
of foods were unknown or identified as
extended consumption and therefore
not included in our analysis.
Three meal-pattern categories were
created based on their ability to provide
meaningful comparison of eating
behaviors: Consistent, moderately
consistent, and inconsistent. These
categories are mutually exclusive and
include all possible combinations of
eating occasions. Respondents with
a consistent meal pattern (n=538)
consumed two or three meals (plus or
minus snacks) on all 3 days of reported
intake. Those with a moderately
consistent meal pattern (n=726)
consumed two or three meals (plus or
minus snacks) on 2 of the 3 days of
reported intake. And respondents with
an inconsistent meal pattern (n=46)
consumed only one meal (plus or
minus snacks) or snacks only on all
3 days of reported intake.
Personal, Household, and
Demographic Charaderistics
Population characteristics available
directly from the CSFII were age,
gender, race, region of residence,
supplement use, school attendance,
educational and employment status
of the female head of the household,
income status, and household size. Our
derived variables were consumption of
school-based meals and single- versus
dual-parent households. Respondents
who reported consuming at least one
school-based lunch per week were
classified as consumers of school
lunch. This method was repeated for
school breakfast. Classification as a
single- or dual-parent household was
based on the presence of a male or
female head of household or female
and male heads of household,
respectively.
Nutrient and Food-Grouping System
The nutrient database was provided
by USDA Survey Nutrient Data Base,
Release #7 and was developed for the
1991 CSFII. For this analysis, we used
nutrient information provided as the
total average intake or as the average
percentage of the Recommended
Dietary Allowances (RDA) for all
nutrients (1 2) consumed over 3 days.
Family Economics and Nutrition Review
The age- and gender-appropriate
RDA values were used to calculate
the average percentage of the RDA
consumed. Grams of food consumed
at each eating occasion were calculated
by using the University of North
Carolina at Chapel Hill food-grouping
system. This system disaggregates
major USDA food groups into 56 more
distinct nutrient-based groups based on
the composition of fat and dietary fiber.
The University of North Carolina at
Chapel Hill 's food-grouping system
covered all foods that respondents
reported eating (14,1 5). I
Statistical Methods
We used Student's t test and a chi­square
test to compare the socio­demographic
characteristics among
the groups based on their meal patterns.
Statistical testing, however, was not
performed on the proportion of the
nutrients or the grams of food contrib­uted
by each meal. To do so would
have required many comparisons,
resulting in our having to use a very
stringent p value. Hence our analysis
is descriptive. The results provide
estimates representative of the U.S.
population in the coterminous 48
States. We weighted the statistics for
nonresponse and corrected the standard
errors for the complex multistage
design. We used the STATA survey
option that allows for the effects of the
complex sample design (20).
Results
Sociodemogra phic
Characteristics
Forty-one percent of the adolescents
had consistent meal patterns; only 4
percent had inconsistent meal patterns
(table 1). The 15- to 18-year-olds were
more likely to have inconsistent meal
1This information is available upon request.
2001 Vol. 13 No. I
Table 1 . Descriptive characteristics of 15- to 18-year-olds and their households,
by meal-pattern category, 1989-91 CSFII
Meal pattern
Sociodemographic Moderately
characteristic Consistent consistent Inconsistent
Sample 538 726 46
Percent
Female 47.0 52.61 60.91,2
Black 14.1 19.01 23.91,2
Attends school 93.1 87.21 75.61
Single-parent household 27.3 31.41 34.81
Female head of household
attended college 34.9 31.1 1 27.31,2
Female head of household
has < 12 years of education 26.9 31.11 31.81
Region
Northeast 18.0 17.2 10.91.2
Midwest 30.9 26.51 28.3
South 31.2 35.41 34.8
West 19.9 20.9 26.1 1,2
Mean (± S.D.)
Percentage of poverty 329 (264) 326 (249) 330 (209)
Household size 4.7 (1 .9) 4.2 (1.4)3 4.2 (1 .5)3'4
1 Significantly different from the consistent meal pattern, chi -square analysis, p < 0 .05.
2Significontly different from moderately consistent meal pattern, chi-square analysis, p < 0.05.
3Significantly different from consistent meal pattern, weighted t test, p < 0.05.
4Significantly different from moderately consistent meal pattern, weighted ttest, p < 0.05.
patterns. The consistent meal-pattern
category had a higher percentage of
respondents who were male, white,
and who attended school. Adolescents
with a consistent meal pattern were
less likely to be from a single-parent
household and more likely to be from
a household in which the female head
attended college. Neither the mean
percentage of poverty nor years of
education of the female bead of
household differed significantly by
meal-pattern category.
Nutrient Profiles Based on
Adolescents' Meal Pattern
Adolescents with a consistent or
moderately consistent meal pattern
consumed 37 to 38 percent of their
total energy from dinner. For adoles-cents
in the inconsistent group, 43
percent of their total energy was
consumed at dinner. Even more
important is the difference in the role
of snacks in their diet. Snacks com­prised
about 23 percent of the total
day's energy for those following an
inconsistent meal pattern but only 11
to 16 percent for those following the
other two meal patterns. In total, the
dinner meal and total snacks together
provided more than two-thirds of the
day's total energy for adolescents with
an inconsistent meal pattern.
Differences by age group were noted
(figs. 1 and 3). For instance, 11- to
14-year-olds in the inconsistent group
obtained 24 percent of energy from
lunch while older adolescents in the
same group obtained 9 percent of
17
Figure 1. Distribution of energy obtained, by meal-pattern groups of 11-to 18-year-olds, 1989-91 CSFII
Meal-pattern groups
Consistent
Cinner Total
38%-snacks 11%
Brlllch
1%
C3in8%ne r
Moderately consistent
25%
Total
sna~s
16%
Mlalng
1%
Inconsistent
Total
lniOkl
1%'11
Figure 2. Distribution of energy obtained, by meal-pattern groups of 11-to 14-year-olds, 1989-91 CSFII
Meal-pattern groups
Consistent Moderately consistent
Total
Inconsistent
Total
.... ks
11%
Lunoh
24'4
Figure 3. Distribution of energy obtained, by meal-pattern groups of 15-to 18-year-o/ds, 1989-91 CSFII
Meal-pattern groups
18
Consistent
Total
~~lllllllllfll~sn~a~s 12'1.
0.01%
Breakfast
20'1.
Moderately consistent Inconsistent
Total
Total
25%
Family Economics and Nutrition Review
energy from lunch. For II- to 14-year­olds
with inconsistent meal patterns,
breakfast provided 5 percent of energy,
compared with almost twice that
amount for the older adolescents.
Brunch was more common for older
adolescents with inconsistent meal
patterns. Among older adolescents
(15- to 18-year-olds) following an
inconsistent meal pattern, dinner and
snacks were far more important than
they were for younger adolescents
(II- to 14-year-olds).
Most nutrients follow the same pattern
as that for energy (table 2). Breakfast
provided the same proportion of
nutrients for adolescents with consis­tent
and moderately consistent meal
patterns; whereas, lunch appeared to
have lower proportions of fat, protein,
carbohydrates, calcium, fiber, and
sodium for adolescents with moder­ately
consistent meal patterns. The
proportions of nutrients from brunch
were very low (no more than 3.5
percent) for adolescents with the
consistent and moderately consistent
meal patterns but closer to I 0 percent
for their counterparts with inconsistent
meal patterns. Dinner provided similar
proportions of nutrients for all three
groups.
For adolescents with inconsistent meal
patterns, the proportion of nutrients
provided by total snacks was nearly
double the nutrients provided to
adolescents with consistent meal
patterns. The proportion of nutrients
corning from snacks for the moderately
consistent group falls between those of
the other two groups.
Food Consumed Based on
Adolescents' Meal Patterns
Interesting differences were noted in
the types of foods consumed at each
eating occasion across meal-pattern
groups. At breakfast, adolescents with a
consistent meal pattern, compared with
adolescents in the other groups, had
200 I Vol. 13 No. I
higher per capita consumption of both
low- and medium-fat milk, egg items,
low-fiber breads, cooked and ready-to­eat
cereals, high-fat desserts, and juices
(fig. 4). In contrast, adolescents with
moderate and inconsistent meal
patterns consumed more soft drinks.
At lunch, adolescents with consistent
meal patterns consumed more milk
and higher amounts of total poultry,
high-fat desserts, vegetables, fruits,
and high-fat grain-based mixed dishes
(pizza and macaroni and cheese, etc.),
compared with other adolescents (fig.
5). There was no difference in beef!
pork consumption between adolescents
with consistent and moderately con­sistent
meal patterns, which were,
however, higher than that for adoles­cents
with inconsistent meal patterns.
The inconsistent and consistent groups
had the same quantity of high-fat
potato consumption.
For dinner, teens with an inconsistent
meal pattern had higher intakes of
poultry, green/orange vegetables, high­fat
grain-based mixed dishes, high-fat
breads, and soft drinks and a lower
intake of low- and medium-fat milk,
soy and legumes, and fruits, compared
with their other adolescent counterparts
(fig. 6). In contrast, snacks for the
inconsistent group contained more
grams per capita of milk items, in
particular medium-fat milk items
(whole milk and milk shakes) and
soft drinks than was the case for the
consistent group (fig. 7). All three
groups of adolescents had similar
intakes of fruits, high-fat desserts,
high-fat salty snack items (chips, salty
crackers, etc.) and high-fat grain-based
mixed dishes.
Patterns within each group revealed
that the amount of soft drink consumed
per capita at lunch, dinner, and total
snacks was higher than the amount of
milk consumed (figs. 4-7). High-fat,
low-fiber bread is more commonly
eaten at breakfast, compared with other
bread options available. Low-fiber
In total, the dinner meal
and total snacks together
provided more than two­thirds
of the day's total
energy for adolescents
with an inconsistent
meal pattern.
19
Table 2. Proportion of nutrients provided by each meal among 11- to 18-year-olds, by meal-pattem consumption 1
Consistent meal pattern Moderately consistent meal pattern Inconsistent meal pattern
Nutrient Mean Standard deviation Mean Standard deviation Mean Standard deviation
Breakfast
Energy 19.23 9.69 18.24 10.62 7.94 8.51
Fat 16.07 11.76 15.66 11 .56 6.31 7.94
Saturated fat 17.92 12.87 17.03 12.20 7.67 8.79
Protein 17.27 9.95 16.15 10.60 9.63 11.86
Carbohydrate 21.95 10.28 20.81 11.93 8.70 9.38
Calcium 28.94 16.53 26.31 16.81 15.81 18.04
Cholesterol 23.35 20.16 21 .35 20.82 10.46 17.45
Iron 29.24 17.26 27.47 19.01 19.72 25.64
Folate 39.11 19.16 35.90 22.16 22.66 25.07
Zinc 20.70 13.16 18.63 15.20 10.51 14.33
Fiber 14.68 10.40 16.51 13.05 7.92 12.93
Sodium 16.23 9.54 16.17 10.40 8.86 10.52
Brunch
Energy 0.47 3.48 2.11 5.80 8.58 13.69
Fat 0.51 3.92 2.44 7.85 9.82 16.16
Saturated fat 0.58 3.93 2.47 7.88 9.07 15.41
Protein 0.45 3.16 2.05 6.84 7.02 11.39
Carbohydrate 0.46 3.60 2.04 5.39 7.97 12.99
Calcium 0.60 3.76 2.26 7.36 8.05 16.38
Cholesterol 0.39 2.88 3.50 12.84 7.97 12.93
Iron 0.36 2.52 2.12 6.87 8.00 12.84
Folate 0.40 2.69 2.41 7.76 9.30 16.49
Zinc 0.43 3.04 1.87 5.76 8.65 15.52
Fiber 0.57 5.12 2.13 6.84 8.14 15.44
Sodium 0.39 2.88 2.11 6.30 9.89 17.09
Lunch
Energy 31.22 11 .64 24 .52 12.58 11.94 18.98
Fat 33.29 14.11 26.10 14.56 12.52 20.91
Saturated fat 32.43 14.53 26.33 15.62 11 .94 19.99
Protein 30.46 12.04 24.69 14.14 10.32 18.14
Carbohydrate 30.03 12.02 23.48 12.39 12.39 19.05
Calcium 30.46 15.74 24 .82 16.11 10.32 19.26
Cholesterol 26.65 14.67 22.49 17.68 10.41 18.49
Iron 26.36 12.03 21 .56 13.00 9.54 16.59
Folate 22.88 12.70 19.90 14.38 8.88 18.33
Zinc 27.74 12.99 23.75 14.88 10.42 18.25
Fiber 33.16 15.87 25.26 14.25 12.65 22.14
Sodium 32.26 12.70 25.06 14.12 11.52 20.20
1 The percentage may not total to 1 00 for each nutrient because of rounding and the sm~ll percentage of foods with a missing eating-occasion
classification.
(Continued)
20 Family Economics and Nutrition Review
Table 2. Proportion of nutrienfs provided by each meal among 11- to 18-year-olds, by meal-pattem consumption 1
(continued)
Consistent meal ~attern Moderately consistent meal ~attern Inconsistent meal pattern
Nutrient Mean Standard deviation Mean Standard deviation Mean Standard deviation
Dinner
Energy 37.72 10.53 38.01 14.60 43.21 26.07
Fat 40.17 13.68 39.79 16.77 46.58 26.58
Saturated fat 38.54 14.52 37.87 17.10 44.04 28.06
Protein 45.23 12.33 45.90 16.52 55.07 25.52
Carbohydrate 33.61 10.92 33.92 14.65 37.49 26.89
Calcium 29.86 14.20 30.84 17.28 42.09 29.05
Cholesterol 43.29 18.86 40.97 20.76 49.50 28.39
Iran 36.81 12.84 37.00 17.46 44 .53 30.34
Folate 29.93 13.59 30.53 16.87 38.64 26.11
Zinc 43.80 14.72 43.86 18.95 49.59 28.25
Fiber 41.84 15.89 41 .61 18.22 46.14 27.62
Sodium 44.83 12.15 44.52 16.40 52.51 26.52
Total snacks
Energy 10.92 9.69 15.50 13.74 23.16 19.02
Fat 9.65 10.06 14.40 15.01 21.41 20.34
Saturated fat 10.16 10.94 14.78 15.44 23.38 21 .52
Protein 6.38 7.17 9.85 11 .30 15.36 15.93
Carbohydrate 13.35 11 .53 18.06 15.16 26.91 20.41
Calcium 9.71 11 .97 14.24 15.90 19.52 17.71
Cholesterol 6.05 8.59 10.09 13.08 17.83 21.74
Iron 7.06 8.62 10.45 11.87 15.82 17.82
Folate 7.48 9.93 9.79 12.26 18.75 19.36
Zinc 7.09 8.33 10.53 11 .81 17.37 17.92
Fiber 9.39 10.96 13.11 13.41 22.09 19.26
Sodium 6.12 6.92 10.74 13.18 14.26 14.47
1 The percentage may not total to 100 for each nutrient because of rounding and the small percentage of foods with a missing eating-occasion
classification.
cereal is consumed more than high
fiber, and citrus juices are consumed
more than noncitrus juices or fruit
drinks at breakfast. At lunch, medium
fat beef/pork and poultry were eaten
more than the low- or high-fat option.
The grams per capita for luncheon
meats was equally distributed among
each fat option. In contrast to breakfast,
the low-fat, low-fiber bread option and
fruit drinks were eaten in greater
amounts at lunch for the consistent
and moderately consistent
2001 Vol. 13 No. I
groups. And for all three groups, there
was a higher per capita consumption
of the high-fat versus the low-fat of
grain-based mixed dishes. The type of
bread consumed at the dinner meal was
similar to that seen at breakfast. And
the higher fat version of grain-based
meals was once again consumed more
than the low-fat version at dinner for
all three groups. Patterns within groups
for the different types of foods con­sumed
as snacks were similar.
Discussion
Dietary intake patterns of U.S. adoles­cents
are poor. Skipping meals, ex­cessive
snacking, and consumption of
excessive high-fat, poor nutritionally
dense foods are many of the issues
raised in the literature. However, few
studies have used nationally representa­tive
samples to examine the meal and
food patterns of U.S. adolescents. This
study highlights the large variation in
eating patterns among U.S. adolescents.
21
Figure 4. Grams consumed at breakfast by adolescents
following a consistent, moderately consistent, or
inconsistent meal pattern, by selected food groups1
Figure 5. Grams consumed at lunch by adolescents
following a consistent, moderately consistent, or
inconsistent meal pattern, by selected food groups1
Breakfast food items (grams)
Low-lot milk
Medium-lot milk
Eggs and egg dishes
Low-lot/low-fiber bread
Low-lot/high-fiber bread
High-fat/low-fiber bread
High-fat desserts
Posta, rice, and
cooked cereals
Ready-to-eat cereals
Citrus fruits and juices
Other fruits and juices
Sugars and jellies
Coffee and teo
Soft drinks
Fruit drinks
0 20 40 60
• Consistent
70
68
80
85
8
100 120
Lunch food items (grams)
Low-fat beef and pork
Medium-fat beef
and pork
Low-fat poultry
Medium-fat poultry
Low-/medium-fat
luncheon meats/hot dogs
High-fat
luncheon meats/ hot dogs
High-fat desserts
High-fat grain-based
mixed dishes
Citrus fruits and juices
Other fruits/juices
High-fat potatoes
Vegetables
Soft drinks 88
4
0 20 40 60 80 100
0 Moderately consistent
• Inconsistent
• Consistent
D Moderately consistent
• Inconsistent
1 University of North Carolina at Chapel Hill food-grouping system. 1 University of North Carolina at Chapel Hill food-grouping system.
In particular, we show that teens differ
markedly by the proportion of food
intake from each meal and the types
of foods eaten, based on consistent,
moderately consistent, or inconsistent
meal patterns.
Regarding snacks, our results differ
from the few published studies on this
topic. Our study fmds that snacks
contribute much less to the total diet
than reported previously. For most
adolescents (97 percent), meals con­tribute,
on average, 20 to 40 percent
22
of the total day's energy, compared with
10 to 15 percent contributed by snacks.
One study has found that about 25 to 33
percent of the total day's energy comes
from snacks (16). Other publi~hed
studies have focused more
on the frequency of snacking and the
snack foods adolescents like to eat
(4,5,8).
Our study shows that for all the
adolescents, a higher proportion of the
total day's intake of fat is consumed at
dinner. Otherwise, meals and snacks
provide similar proportions of the other
macronutrients. Our results regarding
macronutrients offer a different view
of examining macronutrient intake;
others who have examined the nutrient
density of meals and snacks have
found that meals are higher in fat and
lower in carbohydrates than are snacks
(8).
The nutrient contribution of snacks is
more significant for those adolescents
following an inconsistent meal pattern,
compared with adolescents following
Family Economics and Nutrition Review
Figure 6. Grams consumed at dinner by adolescents
following a consistent, moderately consistent, or
inconsistent meal pattern, by selected food groups'
Figure 7. Grams consumed at snack by adolescents
following a consistent, moderately consistent, or
inconsistent meal pattern, by selected food groups'
Dinner food items (grams)
Soy and legumes
High-fat/ low-fiber bread
Green and orange
vegetables
Citrus fruits/ juices
Other fruits
Diet soft drinks
0 20
5
40 60 80 100 120
• Consistent
Snack food items {grams)
Low-fat milk
Medium-lot milk
Low-fat desserts
High-fat desserts
High-fat, salty snacks
High-fat groin-based mix
Citrus fruits/ juices
Other fruits
Candy
Fruit drinks
Diet soft drinks
0 20 40 60 80 100 120 140 160 180
• Consistent
0 Moderately consistent
• Inconsistent
D Moderately consistent
• Inconsistent
1 University of North Carolina at Chapel Hill food-grouping system. 1 University of North Carolina at Chapel Hill food-grouping system .
other meal patterns. This occurs simply
by how this group was defmed, those
consuming one meal plus or minus
snacks on 3 days of intake. The nutrient
contribution of snacks for this adoles­cent
group is similar to that reported by
Ruxton et al. (1 6) in a study of 7- to 8-
year-olds (n=136), from five schools in
Scotland). In our study, snacks for the
inconsistent group provided more of
most nutrients than did breakfast or
lunch with the exception of iron and
folate, which were higher at breakfast.
By using the 1977 Nationwide Food
Consumption Survey (NFCS),
2001 Vol. 13 No. I
researchers found that for most
adolescents, snacks compared with
meals contributed significantly more
magnesium, calcium, vitamin A, and
vitamin C to the diet (2). For the only
nutrient on which we overlapped,
calcium, this was not found in the
1989-91 USDA survey. Because of the
frequency of snacking and the signifi­cant
proportion of energy and other
nutrients that snacks provide adoles­cents
with an inconsistent meal pattern,
we believe the nutritional quality of
snacks has important implications for
the health status of these adolescents.
Another nutritionally important issue is
adolescents' high intake of soft drinks
and lower intake of milk [also noted
in the 1977 NFCS survey (9)]. These
consumption patterns apply to adoles­cents
regardless of meal-pattern group.
Even though adolescents with a con­sistent
meal pattern consume the most
milk, their calcium intakes are lower
than recommended. Also, adolescents
appear to be consuming more high-fat
and low-fiber foods than the more
healthful alternatives. Consuming more
high-fat and low-fiber foods may have
serious health consequences (i.e.,
23
obesity, osteoporosis, and cardio­vascular
diseases) if they are consumed
in high amounts throughout life. The
reasons for the high consumption of
these types of foods may be directly
related to their source (home vs. away­from-
home food sources) as well as
the taste preferences of adolescents.
A Minnesota survey of 900 adolescents
reported a strong preference for high­fat
foods that related to taste appeal
despite the health consequences
associated with consumption of these
foods (21).
A limitation of this study is the small
sample size for the group with
an inconsistent meal pattern. However,
there were 27 million adolescents in
the United States (24) around the time
of this survey. Thus 950,000 U.S.
adolescents are represented as follow­ing
an inconsistent meal pattern for
3 days. In general, adolescents are
consuming a large quantity of carbon­ated
beverages and few fruits and
vegetables. And for adolescents who
follow an inconsistent meal pattern,
dinner and snacks provide a dispropor­tionate
amount of nutrients. Differ­ences
are also noted in food selection:
adolescents following an inconsistent
meal-pattern group consume more
types of fast foods . Both meal-pattern
and food-selection behaviors should
be used to target future public health
messages to adolescents. More research
is warranted on the determinants of
adolescent eating patterns. Information
on the determinants could help guide
interventions for changing eating­pattern
behaviors noted in this study.
24
Acknowledgments
We thank the Nestle Research Center
for providing financial support for this
study. We thank Dr. Henri Dirren for
initiating the collaboration between
Nestle and the University of North
Carolina at Chapel Hill. We also thank
Dan Blanchette, Terri Carson, Claire
Zizza, Lynn Igoe, and Frances Dancy
for their assistance.
Family Economics and Nutrition Review
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I. Berenson, G.S., McMahan, C.A., Voors, A.W., Webber, L.S., Srinivasan, S.R., Frank,
G.C., Foster, T.A., and Blonde, C.V. 1980. Cardiovascular Risk Factors in Children, the
Early Natural History of Atherosclerosis and Essential Hypertension. Oxford University
Press, New York.
2. Bigler-Doughten, S. and Jenkins, R.M. 1987. Adolescent snacks: Nutrient density and
nutritional contribution to total intake. Journal of the American Dietetic Association
87:1678-1679.
3. Cavadini, C. 1996. Dietary habits in adolescence: Contributions of snacking. In A.
Ballabriga (Ed.), Feeding from Toddlers to Adolescence. Nestle Nutrition Workshop Series
vol. 37. Lippincott-Raven, Philadelphia. Nestle Nutrition Services, Vevey, Switzerland.
4. Cross, A.T., Babicz, D., and Cushman, L.F. 1994. Snacking patterns among 1800 adults
and children. Journal of the American Dietetic Association 94: 1398-1403.
5. Devaney, B.L., Gordon, A.R., and Burghardt, J.A. 1995. Dietary intakes of students.
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6. Friedman, H.L. 1989. The health of adolescents: Beliefs and behavior. Social Science
and Medicine 29:309-315.
7. Garcia, S.E., Kaiser, L.L., and Dewey, K.G. 1990. The relationship of eating frequency
and caloric density to energy intake among rural Mexican preschool children. European
Journal of Clinical Nutrition 44:381-387.
8. Gatenby, S.J. 1997. Eating frequency: Methodological and dietary aspects. British
Journal of Nutrition 77(supp l):S7-S20.
9. Guenther, P.M. 1986. Beverages in the diets of American teenagers. Journal of the
American Dietetic Association 86:493-499.
10. Lund, E.K., Lee-Finglas, W.E., Southon, S., Gee, J.M., Johnson, I.T., Finglas, P.M.,
and Wright, A.J. 1992. Dietary fat intake and plasma lipid levels in adolescents. European
Journal of Clinical Nutrition 46:857-864.
II. Miller, E. C. and Maropis, C. G. 1998. Nutrition and diet-related problems. Primary
Care 25:193-210.
12. National Research Council, Subcommittee on the Tenth Edition of the RDAs, Food
and Nutrition Board. 1989. Recommended Dietary Allowances (I Oth ed.) National
Academy Press, Washington, DC.
13. Pinhas-Hamiel, 0. and Zeitler, P. 1996. Insulin resistance, obesity, and related
disorders among black adolescents. Journal of Pediatrics 129(3):319-320.
14. Popkin, B.M., Haines, P.S., and Reidy, K.C. 1989. Food consumption trends of U.S.
women: Patterns and determinants between 1977 and 1985. American Journal of Clinical
Nutrition 49:1307-1319.
15. Popkin, B.M., Siega-Riz, A.M., and Haines, P.S. 1996. A comparison of dietary trends
between racial and socioeconomic groups in the United States. New England Journal of
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2001 Vol. 13 No.1 25
16. Ruxton, C.H.S., Kirk, T.R., and Belton, N.R. 1996. The contribution of specific dietary
patterns to energy and nutrient intakes in 7-8 year old Scottish schoolchildren. III.
Snacking habits. Journal of Human Nutrition and Dietetics 9:23-31.
17. Serdula, M.K., Ivery, D., Coates, R.J., Freedman, D.S., Williamson, D.F., and Byers, T.
1993. Do obese children become obese adults? A review of the literature. Preventive
Medicine 22:167-177.
18. Siega-Riz, A.M., Popkin, B.M., and Carson, T. 1998. Three squares or mostly snacks­What
do teens really eat?: A sociodemographic study of meal patterns. Journal of
Adolescent Health 22:29-36.
19. Siega-Riz, A.M., Popkin, B.M., and Carson, T. 1998. Trends in breakfast consumption
for children in the U.S. from 1965-1991. American Journal of Clinical Nutrition 67:748s-
756s.
20. STATA Corporation. 1997. Stata statistical software: Release 5.0. STATA Corporation,
College Station, TX.
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Nutrition Education 18: 188-192.
22. Sweeting, H., Anderson, A., and West, P. 1994. Socio-demographic correlates of dietary
habits in mid to late adolescence. European Journal of Clinical Nutrition 48:736-748.
23. Troiano, R.P., Flegal, K.M., Kuzmarski, R.J., eta!. 1995. Overweight prevalence and
trends for children and adolescents. The National Health and Nutrition Examination
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among children, adolescents, and adults-United States 1988-94. Morbidity and
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26 Family Economics and Nutrition Review
Rachel K. Johnson, PhD, MPH, RD
The University of Vermont
Celeste V. Panely, MS, RD
The University of Vermont
Min Qi Wang, PhD
The University of Maryland
2001 Vol. 13 No. 1
Associations Between the Milk
Mothers Drink and the Milk
Consumed by Their School-Aged
Children
The declining milk intakes of U.S. children are of concern because milk
is the primary source of calcium in children's diets. The aim of th is study
was to determine the predictors of milk consumption in U.S. school­aged
children (ages 5- 17) by using dietary intake data from the USDA
1994-95 Continuing Survey of Food Intakes by Individuals (CSFII).
Sociodemographic variables, type of milk consumed (skim, 1 %, 2%,
whole, or none), and mothers' milk intake (type and amount) were
examined as possible predictors. The sample consisted of 1,303 CSFII
participants. Sample weights were applied to allow for generalizations
to the entire U.S. school-aged population. Children's average milk
intake was 300.4 grams per day. For every gram of milk a mother
consumed, her child's intake increased by 0 .64 grams. Two percent
milk was the most commonly consumed milk among the children. For
each type of milk consumed by mothers, children were at least 30 times
more likely to drink that same type. The strong association between the
milk consumed by mothers and the amount and type of milk consumed
by U.S. school-aged children should be considered when designing
intervention programs aimed at increasing children 's milk intake.
E vidence suggests that attain­ment
of peak bone mass by
early adulthood may be the
most effective protection against
osteoporotic fractures later in life (23).
Throughout the developmental years,
adequate calcium intake is essential to
support bone growth (16). Substantial
evidence exists linking higher calcium
intakes with improved skeletal health in
children (2,3,16,21,23,30). Data from
the U.S. Department of Agriculture's
(USDA) nationwide food consumption
surveys reveal that most U.S. school­aged
children have calcium intakes that
are below recommended levels (4).
Calcium intake is especially problem­atic
for girls, with 59 percent ages 6-11
and 86 percent ages 12-18 not meeting
recommendations (4) .
Milk and dairy products are the
primary source of calcium in children 's
diets (8). Johnson and colleagues found
that in a large sample of school-aged
children, on average, only those
children who consumed milk at the
noon meal met their daily requirement
for calcium (1 5). Rising consumption
of soft drinks has been shown to have
a negative effect on calcium intake
among children and adolescents by
27
competing with milk as a preferred
beverage (9). On the other hand, whole
and 2% milk are leading sources of fat
and saturated fat in the diets of U.S.
children (33). USDA food consumption
survey data indicate that for children in
all age groups, mean total and saturated
fat intakes exceed the recommended
levels (4).
Because milk is an important contribu­tor
of both calcium and fat in the diets
of children, it is important to identify
the predictors of children's milk intake
(both type and amount). The aim of this
study was to identify predictors of U.S.
school-aged children's milk intake.
Familial aggregation studies show
similarities in nutrient intake between
parents (especially mothers) and their
children (26). Hence, milk consump­tion
patterns of mothers were included,
along with sociodemographic variables,
in the research model as possible
predictors of children's milk intake.
Findings from this study will assist
nutrition policymakers, school nutrition
personnel, school administrators,
nutrition educators, and parents in
developing appropriate intervention
strategies to address the problem of
children's declining milk consumption.
Methods
Sample
The research sample was obtained from
the 1994-95 USDA Continuing Survey
of Food Intakes by Individuals (CSFII).
The CSFII is a continuing component
of the USDA Nationwide Food Con­sumption
Survey. The surveys provide
data on demographics as well as dietary
intake for a nationally representative
sample of noninstitutionalized persons
residing in the United States. The
1994-95 survey included data on the
food and nutrient intakes of 5,598
individuals. The response rate of the
28
survey was 80 percent for Day I
dietary intake data and 76 percent for
Day 2 (4). These response rates are
acceptable by research standards (7) .
Trained interviewers used the multiple­pass
24-hour recall method to collect
2 days of dietary intake data from each
respondent. The multiple-pass 24-hour
recall method has been validated as an
accurate measure of children's dietary
intake (11). All children ages 5 to 17
years with 2 complete days of dietary
intake data (N= 1 ,303) and their
mothers were included in this study.
Study Variables
The study investigated predictors of
both the amount and type (skim, 1%,
2%, whole, or none) of milk consumed
by U.S. school-aged children. The
following sociodemographic variables
were assessed as possible predictors:
Child gender, age, and race; household
income; geographic region; urbaniza­tion;
and mother's age, education, and
occupation. Participation in the USDA
Food Stamp Program and participation
in the USDA national school lunch and
school breakfast programs were also
included as possible predictors of a
child's consumption of milk. Milk is
required to be served in the national
school lunch and school breakfast
programs (5) .
Mothers' milk consumption patterns
(both type and amount) were included
as potential predictors. A mother's
nutrient intake has been shown to
influence her child's nutrient intake
(26) . In addition, studies by Pelletier
and colleagues indicated that.among
adult milk drinkers, consumption of
lower fat versions of milk (I% and
skim) was associated with increased
average daily milk consumption (2 7).
If the same is true for children,
promotion of I% and skim milk in
this population could have a positive
influence on calcium intake.
The dependent variables in the analysis
were "Child Milk Amount" and "Child
Milk Type." Child Milk Amount was
defined as the 2-day mean intake in
grams of fluid milk consumed by the
sample child. The 7,250 food codes in
the CSFII database were searched, and
all codes whose primary ingredient was
fluid cows' milk were included. Items
such as flavored milk, evaporated milk,
dry reconstituted milk, eggnog, and
milk shakes were included. However,
items such as flavored drinks (e.g.,
Yoo-hoo®l, canned meal replacements
(e.g., Instant Breakfast®l, and infant
formulas were excluded.
Child Milk Type was defined as the
type of milk (skim, 1%, 2%, whole,
or none) most often consumed by the
sample child. The CSFII food codes
were searched and all fluid milks were
grouped into one of the four categories:
Skim, I%, 2%, or whole. For example:
"milk, chocolate, skim milk based"
was categorized as skim; "milk, dry,
reconstituted, whole" was categorized
as whole. The category consumed in
the greatest quantity in grams over
2 days by each sample child was
considered the Child Milk Type.
Statistical Analysis
The Statistical Export and Tabulation
System (SETS) software and the Statis­tical
Analysis System (SAS) were used
to format and recode the data for statis­tical
analysis. Statistical significance
was set at p S 0.05 for all analyses. To
compensate for variable probabilities
of selection, differential nonresponse
rates, and sampling frame consider­ations,
we applied sample weights in
both the descriptive and comparative
analyses. The Survey Data Analysis
System (SUDAAN) was used to weight
the sample, compute variances, and run
the statistical procedures. Applying
sample weights aiiows the findings
to be generalized to the entire U.S.
population of school-aged children.
Analysis of variance and analysis of
Family Economics and Nutrition Review
covariance were used to determine both
the bivariate and multivariate effect
of each independent variable on the
dependent variable, Child Milk
Amount. Only those independent
variables that were significant at the
bivariate level were included in the
final multivariate model. Chi-square
statistics were used to identify indepen­dent
variables associated bivariately
with Child Milk Type. The Multi­nominal
Logistic Model was used for
the multivariate analysis of Child
Milk Type. As with the Child Milk
Amount model, only those independent
variables that were significant at the
bivariate level were included in the
multivariate model. 1
The results of the multinomial model
were presented as odds ratios, which
describe the change in likelihood of
one outcome (e.g., drinking whole
milk) versus another outcome (e.g.,
drinking 2% milk) given a particular
characteristic or level of predictor (e.g.,
being a male compared with being a
female) (31). In multinominallogistic
models, each outcome (skim, 1%,
whole, none) is compared with a
reference category, which we deter­mined
to be 2% milk-the most
common type of milk consumed. Odds
ratios greater than 1.0 indicate an in­creased
likelihood of consumption of
that type of milk (compared with 2%)
for children with that characteristic;
whereas an odds ratio of less than
1.0 indicates a lower likelihood of
consuming that type of milk (com­pared
with 2%) for children with that
characteristic. Both unadjusted and
adjusted odds ratios were calculated.
1The Multinominal Logistic Model is an
extension of the logistic regression model. While
logistic models can only process dichotomous
outcome variables, the multinominal model can
include outcomes with two or more categories
(25).
2001 Vol. 13 No. 1
Table 1. Amount and type of milk consumed1 by children ages 5-17 who
provided 2 days of dietary intake data, 1994-95 CSFII
Type of milk consumed Percent Mean amount (grams)
Skim 11.4 376.62
1% 9.6 407.9
2% 32.0 385.4
Whole 28.4 347.8
None 18.6 0.0
1Two-day mean intake of milk (groms/ day) = 300.4+ 11 .9 .
2There was no association between type (skim, 1%, 2%, whole) and amount of milk consumed.
N= 1,303.
This allows for the examination of the
influence the independent variables
have on the dependent variable (Child
Milk Type) both before and after the
model is adjusted for all the covariates.
Any odds ratio with 95 percent confi­dence
intervals that included 1.0 was
not considered statistically significant.
Results
Demographics
The unweighted sample of CSFII
respondents consisted of 1,303 partici­pants.
The children's average age was
11.6 years; the mothers', 39 years.
Most of the sample was white, and was
divided relatively equally between boys
and girls. The sample was geographi­cally
diverse and representative of the
U.S. population. Most participants
resided in suburban areas, and the
average yearly household income was
about $44,000. The mothers' most
common classes of occupation included
professionaVtechnical and clericaV
sales. Twenty-four percent of the
children were eligible to receive free
or reduced-price lunches, and 14
percent were eligible to receive free
or reduced-price breakfasts.
Milk Consumption
The 2-day mean milk intake for
children was 300.4 grams per day
(table 1). Mothers' mean intake was
109.0 grams per day. Of the types of
milk consumed by children (skim, l %,
2%, whole, and none), 2% milk was
most commonly consumed, followed
by whole milk. Two percent milk was
also the most commonly consumed
type by mothers, followed closely by
whole milk. No significant associations
were found between the type (skim,
I%, 2%, or whole) and amount of milk
consumed by children.
Predictors of the Amount of
Milk Consumed by Children
Based on the bivariate analysis, the
type and amount of milk consumed by
mothers, geographic region, and the
child's gender were associated with
Child Milk Amount. Hence, these
variables were entered into the multi­variate
model. In this model, the type
of milk mothers consumed was not
significant; however, geographic
region, the child's gender, and the
amount of milk mothers consumed
each had a significant effect on the
amount of milk consumed by children.
In the multivariate analysis, children
from the Midwest had significantly
higher milk intakes than children from
29
For every 1 gram of milk
a mother consumed, her
child's intake increased
by 0.64 grar:ns.
30
Table 2. Amount of milk consumed by children ages 15-17: Analysis of
covariance (ANCOVA)1 of significant relationships, 1994-95 CSFII
Variable
Mothers' milk intake (milk type)
Skim
1%
2%
Whole
None
Mothers' milk intake
(milk amount, grams)
Region
Northeast
Midwest
West
South
Child's gender
Mole
Female
Beta coefficient
(±SE Beta)
1.94±35.1
28.3 ± 28.6
4.3 ± 32.0
29.0 ± 31.7
0.00 ± 0.00
0.64 ± 0.1
11.6 ± 26.9
71.8 ± 35.6
49.3 ± 29.7
0.0 ± 0.0
120.0 ± 16.9
0.0 ± 0.0
P-volue
0.96
0.33
0.89
0.37
<0.001
0.66
0.05
0.10
<0.001
1 F value for overall model = 137.07; P-value for model < .001; Intercept = 145.09.
- = No reference category.
N=1 ,303.
the South (table 2). Boys in the sample
consumed 120 grams more milk per
day than girls consumed. Maternal milk
intake was significantly and positively
associated with the amount of milk
children consumed. For every 1 gram
of milk a mother consumed, her child's
intake increased by 0.64 grams.
Predictors of the Type of Milk
Consumed by Children
Of the 12 independent variables, the
children's age, gender, and race;
geographic region; eligibility for free
and reduced-price school lunch and
breakfast; mothers' age and level of
education; and the amount and type of
milk consumed by mothers had a
significant bivariate effect on Child
Milk Type. Urbanization and participa­tion
in the Food Stamp Program were
not significant predictors, and were
therefore dropped from the multivariate
model.
In the multivariate model, older
children were more likely to drink skim
milk or no milk than were younger
children (table 3). Children who paid
full price for lunch were more likely
to drink skim milk, compared with
children who were eligible to receive
(and presumably received) free school
lunch. Children from the Northeast
were more likely than children from
the South to drink 1% milk; whereas,
children from the South were more
likely than children from the Midwest
to drink whole milk or no milk. Black
children were more likely to drink
whole milk or no milk than were White
children. Girls were twice as likely to
drink no milk, compared with boys.
The type of milk mothers drank was a
very strong predictor of the type of
milk children drank. Two percent milk
was used as the reference category for
Child Milk Type, because this was the
type most commonly consumed by the
Family Economics and Nutrition Review
Table 3. Milk consumed by children ages 5-17: Results of unadjusted and adjusted odds ratios/ 1994-95 CSFII
CHILD
Age (years)
13-17
9-12
5-8
Race
Black
White
Other
Gender
Female
Mole
School lunch
None
Free
Reduced
Full
School breakfast
None
Free
Reduced
Full
MOTHER
Age (years)
40-60
30-39
20-29
Education
College graduate
Some college
High school
Type of milk
consumed
Skim
1%
Whole
None
2%
Amount of milk
consumed (grams)
> 360
241-360
121-240
0-120
REGION t.
Northeast
Midwest
West
South
Unadj
OR2
1.8
1.3
1.0
0.1
1.0
0.5
1.4
1.0
1.3
0.1
0.4
1.0
2.7
0.8
0.0
1.0
2.4
1.4
1.0
2.1
2.0
1.0
37.7
4.3
4.6
7.2
1.0
1.0
1.9
0.6
1.0
1.3
0.6
0.7
1.0
Skim
Adj
OR
2.2
1.6
1.0
0.4
l.O
l.O
1.5
1.0
1.0
0.2
1.2
1.0
2.8
8.6
0.4
1.0
0.7
0.8
1.0
2.0
1.5
1.0
30.0
4.7
5.9
7.2
1.0
0.9
1.4
0.6
1.0
1.5
0.8
1.0
1.0
1.2, 3.9
0.9, 2.9
0.1' 1.2
0.3, 3.8
0.9, 2.7
0.4, 2.8
0.1 , 0.4
0.2, 7.4
0.5, 15.5
1.1' 69.8
0.1, 3.4
0. ' 3.9
0.1 , 4.5
0.5, 8.0
0.7, 3.1
9.4, 95.8
0.8, 28 .3
1.5, 23 .4
2.0, 26.1
0.2, 3.2
0.5, 4.3
0.1, 2.4
0
0.7, 3.2
0.3, 2.0
0.4, 2.2
Unadj
OR
0.7
0.7
1.0
0.1
l.O
0.7
0.9
1.0
3.6
1.1
0.7
l.O
1.4
1.0
1.3
1.0
2.1
2.3
1.0
3.6
2.2
1.0
3.2
67.2
2.8
3.1
l.O
1.6
1.8
0.9
l.O
4.5
0.8
2.0
1.0
1%
Adj
OR
1.2
0.9
1.0
0.5
1.0
0.4
1.2
1.0
2.3
1.3
0.9
1.0
0.7
1.9
2.6
1.0
1.7
2.8
1.0
2.5
1.6
1.0
3.7
114
2.2
4.2
1.0
95%
Cl
0.6, 2.6
0.4, 1.7
0.2, 1.6
0.1' 1.5
0.7, 2.2
1.2, 4.4
0.3, 4.9
0.2, 4.6
0.1 , 4.2
0.2, 21
0.3, 27
0.4, 7.1
0.7, 11
0.9, 6.8
0.8, 3.3
1.1' 12
31, 416
0.5, 8.5
1.2, 15
1.3 0.3, 6.0
2.8 0.6, 12
1.0 0.3, 2.8
1.0
5.5 1.3, 23
0.9 0.2, 3.3
4.0 1.0, 16
1.0-
Unadj
OR
0.8
0.8
1.0
6.4
1.0
2.7
0.9
1.0
1.2
2.6
2.0
1.0
3.0
7.3
7.9
1.0
0.4
0.7
1.0
0.1
0.4
1.0
3.7
5.2
50.1
10.8
1.0
1.0
1.3
0.5
1.0
l.l
0.3
0.7
1.0
Whole
Adj
OR
1.2
1.1
1.0
3.3
1.0
l.7
0.7
1.0
0.9
0.8
1.4
1.0
3.9
3.6
3.1
1.0
0.9
1.5
1.0
0 .3
0 .5
1.0
4 .1
8.2
45.8
13.0
1.0
2.0
1.4
0.9
1.0
1.1
0 .4
0.5
1.0
95%
Cl
0.7, 2.1
0.7, 1.7
1.7, 6.4
0.6, 4.6
0.4, 1.1
0.5, 1.7
0.3, 2.6
0.4, 4.2
0.8, 18.5
0.6, 23 .9
0.4, 22.9
0.4, 2.2
0.6, 3.9
0.1' 0.7
0.3, 0.8
1.2, 14.6
2.6, 25.8
17.1 , 122.8
6.0, 28 .1
0.8, 5.1
0.4, 4.3
0.4, 2.3
0.4, 2.8
0.2, 0.7
0.2, 1.3
Unodj
OR
3.8
1.0
1.0
3.2
1.0
0.8
2.1
1.0
1.4
0.6
0.8
1.0
1.9
1.8
2.7
1.0
2.7
1.4
1.0
1.2
0.8
1.0
4.5
8.1
7.4
6.9
1.0
0.4
0.2
0.3
1.0
0.8
0.3
0.5
1.0
None
Adj
OR
3.9
l.O
l.O
3.0
1.0
1.3
2.1
1.0
1.0
0.3
0.8
1.0
1.8
3.4
3.0
1.0
1.2
1.0
1.0
1.3
0.8
1.0
4.3
8.6
5.9
3.8
1.0
0.7
0.3
0.5
1.0
0.9
0.4
0.7
1.0
95%
Cl
2.2, 7.1
0.5, 1.9
1.2, 7.6
0.4, 4.1
1.1' 4.0
0.6, 1.9
0.1' 1.1
0.3, 2.4
0.4, 8.6
0.4, 26.7
0.4, 21
0.4, 3.8
0.3, 3.0
0.4, 3.8
0.4, 1.4
1.4, 13
3.9, 19
1.8, 19
1.6, 9.2
0.3, 2.0
0.1' 1.1
0.2, 1.3
0.4, 2.1
0.2, 0.8
0.3, 1.7
1Consumption of skim, 1%, whole, or no milk is compared to 2% milk, as 2% is the most commonly consumed milk type among both sample children and mothers. Odds ratios
whose confidence limits do not include 1.0 are bolded.
20dds ratios.
3Confidence intervals.
-=No reference category.
N=l ,303.
2001 Vol. 13 No. 1 31
For each type of milk ...
consumed by mothers,
children were at least
30 times more likely to
drink the some milk type
as their mothers.
32
sample. For each type of milk (skim,
I%, whole, or none) consumed by
mothers, children were at least 30 times
more likely to drink the same milk type
as their mothers. In addition, the more
educated a mother was, the less likely
her child was to drink whole milk.
The odds ratios for school breakfast,
mother milk amount, and mothers' age
were not significant; the 95 percent
confidence intervals for these variables
included or were very close to 1.0.
Discussion
The findings of this study demonstrated
that the amount and type of milk con­sumed
by mothers strongly predicted
the amount and type of milk consumed
by their school-aged children. This
study also demonstrated that differ­ences
in children's milk consumption
patterns were associated with a number
of demographic variables. These in­cluded
regional differences; differences
associated with mothers' level of
education; and children's age, gender,
and race.
Limitations
The problem of underreporting of food
intake is a concern when interpreting
dietary intake data (24) . When food
consumption surveys are used to obtain
dietary intake data, both adults and
adolescents tend to underreport their
food intake (22). However, there is
agreement that individuals of all ages
are prone to exaggerate those foods
they perceive to be healthful and to
underreport foods that are commonly
considered "sin" foods (i.e., foods high
in sugar and fat) (22). Milk is generally
perceived as a healthful food and was
not among those foods most likely to
be underreported in the CSFII (18).
Hence underreporting was not likely to
be a significant problem in this study.
Factors Influencing the Amount
of Milk Consumed by U.S.
School-Aged Children
The amount of milk consumed by
mothers was associated strongly and
positively with the amount of milk
consumed by their children. Parents
guide and direct children's food
choices (17). Wardle and colleagues
studied parental influences on chil­dren's
consumption patterns and found
significant mother-child correlations
for consumption of dietary fat as well
as fruit and vegetable consumption
(34). Harper and Sanders observed
that children sample unfamiliar food
consistently more often when they
view their parents partaking of the food
(10). Children whose mothers do not
drink milk may be less likely to sample
milk, perceiving milk as an unfamiliar
food.
Parental monitoring may also influence
children's milk consumption. Research
has shown that parental monitoring
can have a marked effect on children's
food selection (I 7). Researchers inter­viewed
over 50 focus groups with
children nationwide regarding the
factors that influence their consumption
of calcium-rich foods. They discovered
that a large percentage of children were
neither encouraged nor required by
their parents to drink milk at home
(36).
In our study, other predictors of the
amount of milk consumed by U.S.
school-aged children included chil­dren's
gender and region. Compared
with the girls, the boys consumed an
average of I 28 grams per day more
milk. This is an important finding,
because girls' calcium intakes are also
lower than boys' (4) . Girls' energy
needs are typically lower than boys'.
These lower energy needs may be
reflected in lower intakes of all foods
and beverages, including milk. On the
Family Economics and Nutrition Review
other hand, it is possible that some girls
may be restricting their food intake .
and eliminating or reducing thetr milk
intake to cut calories and fat. Girls may
initiate dieting behaviors as early as
age 6. In one Ohio study of school­children
Grades 1 through 5, close to
twice as many girls as boys reported
restricting or altering their food intake
(1). Adequate calcium int~ke is .
especially important for grrls-bemg
female is an independent risk factor
for developing osteoporosis (8).
In our study, differences found in
children's milk intake by region of
residence are also important. Southern
girls have the lowest calcium int~kes,
compared with girls in other regions
(1 2). This study determined that
children in the South also have the
lowest milk intakes. In addition, they
were more likely than children from
other regions to drink no milk at all.
Increased milk consumption among
children in the South could be influen­tial
in improving their calcium intakes.
Race did not predict the amount of
milk consumed. Lactose maldigestion
appears to vary widely among different
ethnic and racial groups and in the
United States is estimated to be about
15 percent in Whites, 80 percent in
African Americans, and 90 percent
in Asian Americans (19). However,
a dairy-rich diet was found to be
well tolerated when fed to African­American
adolescent girls for 21 days
(29) . In this study race did not infl~­ence
total milk intake. This is consis­tent
with findings that most people with
lactose maldigestion are able to tolerate
a glass of milk at a meal without
developing any significant symptoms
(32).
2001 Vol. 13 No. 1
Factors Influencing the Type
of Milk Consumed by
U.S. School-Aged Children
The results of this study also demon­strated
that a variety of factors influ­enced
the type (skim, 2%, 1%, whole,
none) of milk consumed by U.S. .
school-aged children. The type of milk
consumed by the mothers was associ­ated
strongly with the type of milk
consumed by their children. This
finding was consistent with results
of studies conducted by Fischer and
Birch, demonstrating that exposure
to a food over time will result in the
development of a preference for the
food among children (6) . Children
who have continued exposure to 1%
and skim milk in the home and who
observe their mothers consuming these
types of milk are likely also to dri~
these types of milk. The type of milk
consumed by children can have an
effect on total diet quality. Children
who drink skim milk come closer to
meeting dietary recommendations f~r
fat and saturated fat in their total daily
diet (1 5,28) . Individuals in all age
groups who consume I% and skim
milk also consume more fruits and
vegetables and less red meat (20).
On the other hand, the cross-sectional
nature of these data make it difficult
to sort out the directionality of the
association between the type of milk
consumed by mothers and the type
consumed by their children. Thus, it is
possible that mothers m~y simp_ly drink
the type of milk their children hke, and
if the children do not like milk, mothers
may not buy it just for themselves.
Prior studies have shown that mothers'
education level is correlated with their
children's nutrient intake (13). In our
study, mothers with the fewest years
of education were more likely to have
children who drank whole milk or no
milk at all, compared with mothers who
were more highly educated. Nutrition
information may not be reaching less
educated mothers. It is also possible
that 1% and skim milk are not as
accessible to them. Whole milk is
sometimes the only choice available
in lower income communities (35).
Children from the South (compared
with those in other regions) as well as
black children (compared with white
children) were more likely to drink
whole milk or no milk at all. It may be
necessary to target the Southern United
States for outreach, because children
in the South have the highest fat and
saturated fat intakes and the lowest
calcium intakes of children in all
regions in the United States (14).
Several other variables were associated
with the type of milk consumed by
school-aged children. Older children
and girls were more likely to dri~
skim milk than were younger children
and boys, respectively. Findings als~
showed that children eligible to receive
free school lunch were less likely to
drink skim milk than were children
who paid full price. Beginning in the
fall of 1996, schools participating in
USDA school nutrition programs were
required by law to serve meals that on
average meet the dietary guidelines
for fat, saturated fat, cholesterol, and
sodium (5) . Because it is difficult to
meet the dietary guidelines when a
meal includes whole milk (1 5),
participating schools may now be_
serving and marketing I% and skun
milk more vigorously. Further research
using future USDA surveys is needed
to conftrm this possibility.
33
Implications
The findings of our study demonstrate
that mothers' milk consumption
patterns are potentially strongly
associated with the type and amount
of milk consumed by U.S. school-aged
children. Interventions aimed at
increasing children's milk consumption
should consider the strong influence of
maternal modeling on children's milk
intake. Mothers should be encouraged
to serve as positive role models for
their children by drinking skim or 1%
milk regularly. In addition, it becomes
apparent that milk promotion cam­paigns
targeting women for prevention
of osteoporosis may have a spillover
effect of increasing children's milk
consumption.
Acknowledgments
This project was funded by the
Vermont Agricultural Experiment
Station Hatch Project #VT-NS-00577.
34
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36
Family Economics and Nutrition Review
Carol Byrd-Bredbenner, PhD, RD
Rutgers, The State University
of New Jersey
Darlene Grasso, MA, RD
Montclair State University
2001 Vol. 13 No. l
The Effects of Food Advertising
Policy on Televised Nutrient
Content Claims and Health
Claims
This study examined changes in nutrient content and health claims
made in televised food advertisements before and after the Federal
Trade Commission's 1994 food advertising pol icy, which is predicated
on the Nutrition Labeling and Education Act (NLEA). Our sample
included 1 05 and 1 08 advertisements broadcast during prime-time in
1992 and 1998, respectively. The rate that nutrient content and health
claims were used was low in both years. And none of the advertise­ments
contained diet-disease health claims authorized by the Food and
Drug Administration. Although current food advertising policy virtually
eliminates deceptive advertisements, it may also limit diet-disease health
claims in broadcast media . More flexibility in presenting diet-disease
health cla ims in broadcast media advertising could increase the use of
such claims and contribute to the goal of NLEA to educate consumers.
T he decision to purchase a food
is influenced by many factors,
one of which is advertising
(7,8,36,43). Advertisements tradition­ally
promoted foods and beverages by
featuring mainly sensory qualities,
convenience, and economic factors
(10,44). In recent years some of these
advertisements have tried to influence
consumer-purchasing decisions by also
touting nutritional or health qualities or
both (29,32).
Food advertising, like advertising for
nearly all products, is regulated by the
Federal Trade Commission (FTC).
Historically, the FTC permitted nutrient
claims (e.g., "high in fiber") in adver­tising
and never formally prohibited
diet-disease health claims (i.e., claims
that explicitly linked the consumption
[or lack of consumption] of a particular
nutrient or other substance in a food to
a disease or health-related condition
[e.g., "a calcium-rich diet can help
prevent osteoporosis"]) (32) . However,
if diet-disease health claims were
made on the label, the Food and Drug
Administration (FDA) reclassified
the food as a drug and required the
manufacturer to adhere to the drug­approval
procedures of the FDA (29).
For years food advertisers did not
make diet-disease health claims about
their products, but as the connection
between diet and health became
increasingly clear, food manufacturers
and advertisers grew interested in using
this information to sell their products.
Consequently, in 1984, the Kellogg
Company initiated an advertising
campaign that explicitly described the
relationship between a high-fiber diet
and reduced risk of certain types of
cancer. When the FDA failed to
prosecute this direct violation of
37
diet-disease health claims, other
food manufacturers launched similar
campaigns (18,29). Marketing strate­gies
that included diet-disease health
claims did provide consumers with
information about nutrition and health.
However, in their zeal to gain a
competitive edge, advertisers also
pushed the limits of what science
could support and what consumers
would believe (18,25).
To stem questionable marketing
practices and restore consumer confi­dence,
the Nutrition Labeling and
Education Act (NLEA) was passed
in 1990 and became fully effective
in 1994 (27). The NLEA overhauled
nutrition labels on food packages,
expanded the scope of nutrition
labeling, explicitly defined nutrient
content claims, and regulated diet­disease
health claims (25). While the
new food-labeling regulations did
much to improve the quality of
information on food packages, these
regulations did not extend to food
advertising (41). Fortunately, in its
efforts to prevent deceptive or mis­leading
claims, the FTC announced in
1994 that it would apply the standards
set forth in the NLEA to evaluate
nutrient content and diet-disease health
claims made in food advertisements
(14). The FTC reported that its goal
was to create a food advertising policy
that would help ensure that food
advertising messages are congruent
with data presented and are permitted
on food labels (1 5).
While food and beverage advertise­ments
appear in all types of print,
broadcast, and electronic media,
television is the preferred advertising
medium of food manufacturers--over
7 5 percent of their 1997 advertising
budget was spent on televised advertis­ing
(17). The food and alcohol industry
accounted for more than one-sixth of
the $73-billion mass media advertising
market; only the automobile industry
spent more on advertising ( 17).
38
Although some studies have examined
the nutrient content claims and health
claims in food advertising, few have
focused on televised advertising.
Furthermore, no studies could be
located that compared changes in
nutrient content claims and health
claims over time or examined the effect
of the NLEA and FTC food advertising
policy on televised food advertise­ments.
Thus the purpose of this study
was to examine changes in the nutrient
content claims and health claims made
in televised food advertisements before
and after the enactment of the new food
advertising policy of the FTC, a policy
which is based on the NLEA, and to
determine whether the use of claims
varied by type of food product
advertised.
Methods
Sample
In the autumn ofboth 1992 and 1998,
17.5 hours of top-ranked, prime-time 1
were videotaped. This study focused
on prime-time and major networks
because they traditionally have the
largest viewing audience (35). The
sample comprised all commercials
broadcast during the sampling period.
Commercials (i.e., all non-program
time) included advertisements, public
service announcements, and promo­tions
for television programs. Although
all commercials were recorded and
analyzed, only data pertaining to food
advertisements are presented here. A
food advertisement was defined as a
paid-commercial announc;ement that
specifically promoted a food, beverage,
or dietary supplement intended for
human consumption.
1
Prime-time refers to programming broadcast
from 8 p.m. to 11 p.m. Monday through
Saturday, and 7 p.m. to II p.m. on Sunday.
Major networks refer to ABC, CBS, NBC, Fox,
and WB; note WB became a network in 1998.
Instrument
The food advertisements were content
and textually analyzed by using the
study instrument that was adapted from
those reported elsewhere (5,19,28,38,
40,50). Content analysis permits
systematic, objective evaluation of
visual and linguistic elements (6,24) .
Textual analysis allows researchers to
investigate how linguistic elements
are used, their significance, and their
contribution to understanding a topical
area (4,38).
Content analysis began by eliminating
all nonfood commercials. All food
advertisements were then classified
into 11 food categories based largely on
the USDA Food Guide Pyramid (47):
Breads and cereals, vegetables, fruits,
protein-rich foods (i.e., eggs, meat,
poultry, fish, shellfish, nuts, and seeds),
dairy products, high-sugar foods (e.g.,
syrup, candy, and soft drinks), high-fat
foods (e.g., butter, oils, and salad
dressing), alcohol-containing beverages
(i.e., wine), calorie-free beverages,
dietary supplements, and miscellaneous
items (i.e., seasonings).
Restaurant advertisements frequently
highlighted a variety of food items that
together comprised a meal. Thus to
evaluate the nutritional value of the
foods advertised, we assigned all items
in an advertised meal to the appropriate
food categories. In addition, combina­tion
foods (e.g., fast-food sandwiches
and soups) were broken down into their
component parts and appropriately
assigned to two or more of the food
categories. Foods in the first five
categories listed previously were
further classified by nutrient density:
low, moderate, and high. Methods
described in detail elsewhere were used
to classify density {51). In brief, foods
low in nutrient density tended to be
ones that are highest in fat in each of
the first five categories (e.g., pastries,
French fries, coconut, luncheon meats,
and whole milk). Foods moderate in
Family Economics and Nutrition Review
nutrient density were less nutrient dense
than were foods high in nutrient density
(e.g., breads made with enriched flour
instead of whole grains, candied sweet
potatoes instead of plain vegetables,
fruits canned in syrup rather than fresh
or canned in unsweetened juice, fat­trimmed
beef instead of skinless poultry
white meat, or lowfat instead of nonfat
milk). Foods high in nutrient density
provided the greatest level of nutrients
per kilocalorie.
The subsequent step, requiring textual
analysis, involved identifying and
coding nutrient content claims as either
(a) Contains Specific Nutrient or (b)
Minimizes (or eliminates) Specific
Nutrient. Nutrient content claims,
defined in the FDA and USDA's food­labeling
regulations, include 11 core
terms that can be used to describe the
nutrient content of foods: good source,
more, high, free, low, lean, extra lean,
reduced, less, light, and fewer (42).
An advertisement that indicated