Family Economics and Nutrition Review [Volume 14, Number 1]

              Research Articles
3 Using the Interactive Healthy Eating Index to Assess the Quality of
College Students' Diets
Hazel Hiza and Shirley A. Gerrior
13 Consumers of Reduced-Fat, Skim, and Whole Milks: Intake Status of
Micronutrients and Dietary Fiber
Helen H-C. Lee and Shirley A. Gerrior
25 Expenditures on Children by Families, 2000
PROPE TV
LIBR
Mark Uno 1
43 Selected Food and Nutrient Highlights of the 20th Century:
U.S. Food Supply Series
Lisa Bente and Shirley A. Gerrior
52 The Quality of Young Children's Diets
Mark Uno, P. Peter Basiotis, Shirley A. Gerrior, and Andrea Carlson
Research Briefs
61 Dietary Guidance, 1970 to 1999: Does the U.S. Food Supply Support It?
Shirley A. Gerrior and Lisa Bente
67 Insight 20: Consumption of Food Group Servings: People's Perceptions vs. Reality
P. Peter Basiotis, Mark Uno, and Julia M. Dinkins
71 Insight 22: Serving Sizes in the Food Guide Pyramid and on the Nutrition Facts
Label: What's Different and Why?
David Herring, Patricia Britten, Carole Davis, and Kim Tuepker
Regular Items
USDA Activities • Federal Studies • Journal Abstracts • Food Plans
• Consumer Prices • Poverty Thresholds
Ann M. Veneman, 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 Basiotis, Director
Nutrition Policy and Analysis Staff
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Julia M. Dinkins
Assistant Editor
David M. Herring
Features Editor
Mark Uno
Managing Editor
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Hazel Hiza
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Research Articles
3 Using the Interactive Healthy Eating Index to Assess the Quality of College
Students' Diets
Hazel Hiza and Shirley A. Gerrior
13 Consumers of Reduced-Fat, Skim, and Whole Milks: Intake Status of
25
Micronutrients and Dietary Fiber
Helen H-C. Lee and Shirley A. Gerrior
Expenditures on Children by Families, 2000
Mark Uno
PROPERTY OF THE
LIBRARY
AUG 1 3 2002
43 Selected Food and Nutrient Highlights of the 20th 8W1W~~ ty of N th C I'
u.s. Food Supply Series or aroma
LisaBenteandShirleyA. Gerrior at Greensboro
52 The Quality of Young Children's Diets
Mark Uno, P. Peter Basiotis, Shirley A. Gerrior, and Andrea Carlson
Research Briefs
61 Dietary Guidance, 1970 to 1999: Does the U.S. Food Supply Support It?
Shirley A. Gerrior and Lisa Bente
67 Insight 20: Consumption of Food Group Servings: People's Perceptions vs. Reality
P. Peter Basiotis, Mark Uno, and Julia M. Dinkins
71 Insight 22: Serving Sizes in the Food Guide Pyramid and on the Nutrition Facts Label:
What's Different and Why?
David Herring, Patricia Britten, Carole Davis, and Kim Tuepker
Regular Items
74 Research and Evaluation Activities in USDA
78 Federal Studies
88 Journal Abstracts
90 Official USDA Food Plans: Cost of Food at Home at Four Levels, U.S. Average, May 2002
91 Consumer Prices
92 U.S. Poverty Thresholds and Related Statistics
Volume 14, Number 1
2002
Hazel Hiza, PhD, RD
Shirley A. Gerrior, PhD, RD
U.S. Department of Agriculture
Center for Nutrition Policy and Promotion
2002 Vol. 14 No. 1
Research Articles
Using the Interactive Healthy
Eating Index to Assess the
Quality of College Students' Diets
The Interactive Healthy Eating Index (IHEI) is an Internet application of the Healthy
Eating Index (HE I)-a single summary measure of overall diet quality that was
developed by the U.S. Department of Agriculture. We used this application to
assess the quality of the diets of 100 students at a State university. Paired sample
t tests were used to analyze students' 1-day dietary records to compare students'
mean HEI and component scores with dietary recommendations. The mean
overall HEI score (67.2 of a possible 100) for the total sample exceeded the
national average for a similar age group by 6.3 points. Students who were female,
less than 20 years old, or nonscience majors had the highest HEI scores. While
the students' overall HEI score was higher than the national average, students'
diets still need improvement. Our findings show that the IHEI can be applied in a
university setting to analyze the quality of students' diets. The IHEI can also be
used as a valuable component of collegiate introductory nutrition and health
courses.
E xtensive research has been
conducted on the links between
diet and chronic disease, but
little has been conducted on methods to
assess overall diet quality. To measure
how well American diets conform to
recommendations, the U.S. Department
of Agriculture's (USDA) Center for
Nutrition Policy and Promotion
(CNPP) developed the Healthy Eating
Index (HEI), a single summary measure
(or "report card") of overall diet quality
in 1995 (Kennedy, Bowman, Lino,
Gerrior & Basiotis, 1999; Frazao,
1999). The HEI provides a "snapshot"
of the types of foods people eat, the
variety in their diets, and the degree to
which their diets comply with Federal
dietary guidance (i.e., specific recom­mendations
of the Dietary Guidelines
for Americans) (Bowman, Lino, Gerrior
& Basiotis, 1998; U.S. Department of
Agriculture [USDA] and U.S. Depart­ment
of Health and Human Services
[DHHS], 1995) and the Food Guide
Pyramid (USDA, 1996). The HEI
provides insight into the types of
dietary changes needed to improve
the eating patterns of Americans.
Many Americans are confused about
what to eat (and what not to eat); others
fail to follow healthful eating practices
even when they understand basic
nutrition (Frazao, 1999). Thus, the
USDA developed the Interactive
Healthy Eating Index (IHEI) to in­crease
awareness of diet quality and to
promote healthful eating habits. Based
on the HEI, the IHEI is a consumer­oriented,
online dietary intake assess­ment
tool that allows Americans (2
years and older) to evaluate the quality
of their diets in terms of current dietary
guidance. The IHEI also provides
immediate feedback via scoring options
and targeted nutrition education
messages. Along with increasing
awareness of the quality of a person's
diet, the IHEI helps those who may
3
have access to nutrition information but
who may not have the background to
apply or interpret it conect1y.
College students are expected to
respond favorably to the IHEI and may
benefit positively from its use. They are
both interested in nutrition information
(Hertzler & Frary, 1992) and are
computer literate. Today's college
students take basic nutrition courses
in record numbers. Many of ti)ese
nutrition courses are now computer­assisted
instruction or computer­assisted
learning (Shah, George &
Himburg, 1999). Also, today's young
adults are the first generation to have
grown up with the benefit of dietary
recommendations to reduce intake of
fat and cholesterol and increase intake
of complex carbohydrate and fiber.
Hence, college-age Americans intro­duced
as children to dietary guidance,
such as the Dietary Guidelines for
Americans1 and the USDA Food Guide
Pyramid (USDA & DHHS, 1995;
USDA, 1996), could be expected to
have diets reflective of this guidance.
Overall, however, college students
often develop poor eating habits. These
practices may result from skipping
meals, choosing inappropriate foods,
dieting excessively, consuming inap­propriate
snacks, and avoiding certain
food s (Harless, Koch & Slapar, 1996).
Often, these practices result in low
intake or imbalance of calories and
important nutrients. Some college
students eat foods low in fat (e.g.,
reduced-fat milks) and high in complex
carbohydrates (e.g. , pasta). Many
others, however, frequently eat fast­food
and restaurant foods, both of
which are associated with higher
1 Since the completion of this study and the
development of the IHEI, a new version of the
Dietary Guidelines for Americans was released
(USDA & DHHS, 2000). Also, an updated
version of the IHEI is now available on the
USDA Web site at www.cnpp.usda.gov.
4
intakes of fat and sodium and lower
intakes of dietary fiber and calcium
(Georgiou et al., 1997). These behav­iors
may contribute to inadequacies in
the diets of college students, affect their
health status during a formative period
of growth and development, and
eventually influence the quality of life
they may experience in their middle­aged
and senior years. Consequently,
this population needs more information
about making dietary choices that
include more nutrient-dense foods
(especially for calcium and iron) and
reduced-fat foods (Hertzler et al.,
1992).
This study assessed the quality of
college students' diets. The IHEI was
used to assess that quality. To our
knowledge, this study is the first to
use and evaluate the IHEI as a measure
of the quality of people's diets.
Indices
An important definition in this study is
diet quality, a definition that varies­depending
on the attributes selected.
As applied in this study, diet quality
consists of a comprehensive set of
indicators that incorporated nutrient
needs and recommendations of food
servings into one measure, the Healthy
Eating Index (Kennedy et al., 1995).
Healthy Eating Index
The total HEI score is the sum of 10
equally weighted dietary components,
each having a maximum score of 10
and a minimum score of zero. A
maximum score of 10 was assigned to
each of the five food group components
of the HEI if a person's diet met or
exceeded the recommended number of
servings for a food group of the Food
Guide Pyramid. High component
scores indicate intakes close to the
recommended ranges or amounts; low
component scores, less compliance
with the recommended ranges or
amounts. The 10 components each
represent various aspects of a healthful
diet.
• Components 1 through 5 measure
the degree to which a person's diet
conforms to the recommended
servings of the Food Guide Pyramid
for the five major food groups:
grains, vegetables, fruits, milk, and
meat.
• Component 6 measures total fat
consumption as a percentage of total
food energy intake.
• Component 7 measures saturated fat
consumption as a percentage of t" t" '
food energy intake.
• Component 8 measures total
cholesterol intake.
• Component 9 measures total sodium
intake.
Component 10 measures the variety
in a person's diet. In this study,
variety in the diet was based on the
total number of different foods eaten
in a day in amounts sufficient to
contribute at least one-half of a food
group.2
The maximum overall HEI score a
person can receive is 100. A score
greater than 80 classifies a diet as
"good"; scores between 51 and 80
classify a diet as "needs improvement";
a score less than 51 classifies a diet as
"poor."
Because no single dietary component
defmes the Index, doing well on only
one component does not ensure a
high overall score. A more detailed
description of the development of the
HEI is described elsewhere (Bowman
etal., 1998).
20thers have reported diet variety as the total
number of unique foods consumed in a day
(Kant, 1996).
Family Economics and Nutrition Review
Interactive Healthy Eating Index
An online dietary assessment tool, the
IHEI uses the same data sources as
those used for the HEI. The food
descriptor files, which contain more
than 8,000 foods, were modified to
best reflect users' food choices and
include fast-foods and brand names
for numerous food items reported as
being consumed by survey respondents.
These data reflected the food choices
of a sample population of about 15,000
individuals.
Modified food descriptions were
matched to appropriate data from
several files of the USDA's Continuing
Survey of Food Intakes by Individuals
(CSFll): nutrients, serving measures,
and Pyramid servings. When a food
could not be linked directly to a
Pyramid serving, it was assigned a
Pyramid serving of a similar food.
Methods
Subjects
In the spring of 1999, we conducted
a pilot study at a State university to
test the application of the IHEI. The
subjects, 250 college students enrolled
in an introductory nutrition course,
represented a variety of academic
majors. Many students enrolled in the
course to meet a science requirement.
Many students did not provide
demographic information or did not
complete all necessary components of
the IHEI; thus, the final sample size
was 100.
Data Collection
As an assignment, students evaluated
the IHEI and completed a 1-day dietary
food record. All students were given
guidelines for using the IHEI and an
evaluation form to complete. After
accessing the IHEI from the
university's computer laboratory,
students entered information about
2002 Vol. 14 No. 1
their age, gender, and diet for self­evaluation.
Each student's information
was processed by a Web server and
linked to the databases that include
information on nutrients, serving
measures, and Pyramid servings. This
process calculated each student's 10
component scores and an overall HEI
score, as well as nutrient intakes of up
to 24 nutrients and dietary components.
The evaluation forms and students'
IHEI information were provided to
course instructors for purposes related
to the assignment and then given to
researchers for further analysis.
Analysis
An IHEI student database was created
by using the Statistical Package for the
Social Sciences (SPSS, 1997); a coding
manual was developed to account for
all collected data. The 106 variables
consisted of the students' demographic
information, HEI and component score
variables, Pyramid servings of the five
major food groups, national average
comparisons of HEI and component
scores, nutrient intakes, and recom­mended
dietary intake for each nutrient.
Subjects were divided into the follow­ing
subgroups: gender, age categories
(less than 20 years and 20 years or
older), and majors (science: dentistry,
engineering science, agricultural
science and forestry, medicine, nursing,
and pharmacy; and nonscience: arts
and sciences, business and economics,
creative arts, human resources and
education, journalism, law, and social
work).
SPSS for windows was used to conduct
Student t tests (SPSS, 1997), and paired
sample t tests were used to compare
mean scores between subgroups (the
students' intake and the recommend­ation)
for HEI scores, HEI component
scores, nutrient intakes, and Pyramid
servings. The independent t test was
applied to compare these variables
based on selected demographic
characteristics of the subjects.
Students, regardless of age
category, did not meet the
minimum daily recommendations
for fruits, milk, and meat.
5
Results and Discussion
Demographics of Sample
Over twice as many female students
as male students (70 vs. 30 percent)
provided a 24-hour dietary record
(fig. 1). Most (three-fifths) of the
students were 20 years old or older,
and over half were science majors
(55 percent); that is, they majored
in dentistry, engineering science,
agricultural science and forestry,
medicine, nursing, and pharmacy.
Food Guide Pyramid Servings
For this college group, the recom­mended
daily minimum number of
servings of the Food Guide Pyramid
ranges from 2 to 6 (table 1). To meet
the daily minimum servings, this age
group needs to consume a minimum
of 2 servings each of fruits, milk, and
meat; 3 servings of vegetables; and
6 servings of grains. This student
group (overall and by gender, age, and
major) tended to meet the minimum
recommendations for grains: 6.2 to 6.5
(table 2). Males consumed significantly
fewer daily servings of fruits (1.3) and
milk (1.6) than are recommended;
females consumed significantly fewer
servings of vegetables (2.5), fruits
(1.4), milk (1.3), and meat (1.2).
Students, regardless of age category,
did not meet the minimum daily
recommendations for fruits, milk,
and meat. Whereas the older group
consumed 1.2 to 1.4 servings of these
food groups, the younger age group
consumed 1.4 to 1.6 servings. Both
age groups met or exceeded-but not
significantly-the minimum recom­mendations
for grains.
Whereas nonscience majors failed to
meet the recommended daily minimum
servings of fruits and milk, science
majors failed to meet the recom­mendations
for vegetables, fruits,
milk, and meat. Each group's intake
6
Figure 1. Selected demographic characteristics of college students
45%
.••.•·.•·.•·.•·.•.••· •.•··•··•··•··•··•··•··•··•··•··•··•··• ··.•.:•.:•.:·.:.:•· :.:•·:·:·:·:•·:·:•·:·:·:·:··::··:•:··:•:··::··::··:•:··:•:··:•·:·:•·: ··•··••·•··••·•·•··•··• •••••.•• •·•·•··•·•·• ::::::::::::. ........... ·: ·:·:·:•:·:•::·
:•·..•..•..·•..••..•·..•·..•....•·..•·..•·..•·..•..•..·.•...•·..•·..•·..•.·.•...•.·..•·..•·..•·..•..•..·
·:·:·:·:·:·:·:·:·:·:·:·:·:·:·:•·:•·•:!·•:
~Females
• Males
2lJ ~20 years
• <20 years
[88 Science•
• Nonscience••
• Science majors: dentistry, engineering science, agricultural science and forestry, medicine, nursing, and
pharmacy.
•• Nonscience majors: arts and sciences, business and economics, creative arts, human resources and
education, journalism, law, physical education, and social work.
n=100.
Mean age = 20.5 years.
Table 1. Recommended minimum and maximum number of USDA Food Guide
Pyramid servings per day, by age-gender categories of college students
Category Energy Grains Vegetables Fruits Milk Meat1
(kilocalories)
Females 11-24 2200 6-9 3-4 2-3 2-3 2-2.4
Females 25-50 2200 6-9 3-4 2-3 2·2 2-2.4
Males 19-24 2900 6-11 3-5 2-4 2·3 2-2.8
Males25-50 2900 6-11 3-5 2-4 2-2 2-2.8
Males 15-18 3000 6-11 3-5 2-4 2-3 2-2.8
10ne serving of meat equals 2.5 ounces of lean meat.
Source: Bowman, S.A., Uno, M., Gerrior, S.A., and Basiotis, P.P. 1998. The Healthy Eating Index: 1994·96.
U.S. Department of Agriculture, Center for Nutrition Policy and Promotion. CNPP·5.
represented shortfalls of 0.6 to 0. 7 daily
servings of each of these food groups.
Nonscience majors met or exceeded the
recommended minimum number of
daily servings of grain~ (6.5 vs. 6.0).
On average, students in this study did
not meet the maximum recommended
serving of any of the five major food
groups of the Food Guide Pyramid.
Our findings disagree with those of
Schuette and colleagues (1996) who
reported that college students in an
introductory nutrition course had daily
mean intakes from each of the five
groups at or above the recommended
minimum number of servings. Previous
research, however, shows that even
Family Economics and Nutrition Review
Table 2. Mean Pyramid servings consumed by college students, 1-day intake1
Total
Pyramid sample Gender Age Major2
food groups (n=100) Male Female <20 years ~20 years Science Nonscience
Grains 6.3 6.3 6.2 6.3 6.2 5.0 6.5
Vegetables 2.8 3.4 2.5* 2.9 2.7 2.4* 3.2
Fruits 1.4* 1.3* 1.4* 1.5* 1.2* 1.3* 1.4*
Milk 1.4* 1.6* 1.3* 1.4* 1.3* 1.4* 1.3*
Meat 1.5* 2.2 1.2* 1.6* 1.5* 1.3* 1.7
1 Paired ttests were used to compare mean (± standard error of the mean) intake with the recommended minimum number of servings.
2Science majors: dentistry, engineering science, agricultural science and forestry, medicine, nursing, and pharmacy. Nonscience majors: arts and sciences, business and
economics, creative arts, human resources and education, journalism, law, physical education, and social work.
• Values are significantly lower than the recommended minimum number of Pyramid servings (p< .05).
students consuming foods at an upper
level distribution (the 75'h percentile
of the median) did not meet the
recommended daily minimum servings
of grains and vegetables but did meet
the recommended servings for fruit,
milk, and meat (Georgiou et al., 1997).
This finding illustrates how few
college students actually meet the
recommended maximum serving of the
Food Guide Pyramid and is supportive
of our results. However, in each of
these studies, underreporting the types
of food consumed and underestimating
their portion sizes may be a factor.
Thus, actual intake of these food groups
may be higher than indicated. Students
have been found to underestimate food
portion sizes when using the Food
Guide Pyramid. This is a source of
error that influences assessment of
nutritional adequacy (Tavelli, Beerman,
Shultz & Heiss, 1998).
Selected Nutrient Intakes
Female and male students' intakes met
or exceeded the 1989 Recommended
Dietary Allowances (RDA) for most
of the selected nutrients-vitamins A,
C, and B6; folate; and iron (table 3).
Female students' intake of calcium,
however, was significantly lower than
the RDA. Although students' reported
intakes of vitamins A and C exceeded
2002 Vol. 14 No. 1
100 percent of the RDA, the total
sample still failed to meet the minimum
Pyramid servings of fruits and
vegetables (table 2).
Fruits and vegetables are the key
sources of vitamins A and C as well
as important contributors to folate and
vitamin B6. Underreporting of foods,
such as orange juice (a beverage vs. a
food), and the vegetables in grain
mixtures and other mixed dishes-such
as pizza and Mexican entrees, which
are popular with college students-is
assumed by the authors and helps to
explain this discrepancy. Also, the fact
that male students and nonscience
majors met the minimum number of
vegetable servings may be explained
in part by compliance with recom­mendations
because of an awareness of
the benefits of healthful nutrition.
Many non-nutrition majors enrolled in
basic nutrition courses make positive
dietary changes (Mitchell, 1990).
We expected a more apparent link
between the mean intakes of nutrients
and food sources-such as a link
between vitamin A and vegetables and
fruits, vitamin C and fruits, folate and
fruits and grains, and iron and fortified
grains and meat. The mean intakes of
these nutrients appear to be adequate
for both male and female students,
but these same students generally
consumed less than the recommended
minimum number of servings (with the
exception of grains) from these food
groups. This finding is supported by
Georgiou and colleagues (1997) who
determined that college students and
graduates ate more grains high in
dietary fiber, more fruits, more dark­green
vegetables, and more lowfat
milks and meats than did nonstudents.
Females, however, still failed to meet
the minimum recommendations for
grains, vegetables, and fruits.
Our findings are also similar to those
of Tavelli and colleagues (1998) who
found that although the mean intakes
of nutrients appear adequate, college
students often consumed less than the
recommended minimum number of
servings from the Food Guide Pyramid.
Thus, using the minimum recommend­ations
of the Food Guide Pyramid as
criteria of dietary adequacy may be
misleading in terms of actual nutrient
intake for some nutrients. While the
Pyramid may be a good indicator for
screening nutritionally inadequate diets,
further analysis of the nutritional
adequacy of the total diet is needed to
account for nutrient contributions from
food mixtures and reported incorrect
estimations of serving sizes (Schuette,
Song & Hoerr, 1996).
7
Female and male students'
intakes met or exceeded the
1989 Recommended Dietary
Allowances (RDA) for most
of the selected nutrients­vitamins
A, C, and 86; folate;
and iron.
8
Table 3. College students' mean dietary intakes 1 and percent Recommended Dietary
Allowances (ADA) of selected nutrients, compared w1th the 1989 ADA
Dietary intake
Nutrient Males Females
Mean ± SEM (% RDA)
Vitamin A (RE)
Vitamin C (mg)
Vitamin 86 (mg)
Folate (meg)
Iron (mg)
Calcium (mg)
1642.0 ± 468 (1 69) 1363.0 ± 352 (170)
184.0 ± 49 (307) 138.0 ± 16 (231 )
2.8 ± .22 (140) 2.5 ± .27 (167)
371 .0 ± 56 (1 86) 376.0 ± 59 (220)
19.6 ± 1.9 (1 94) 20.9 ± 3.0 (140)
1137.0 ± 150 (96) 827.0* ± 71 (70)
1 Paried ttests were used to compare means ( :t standard error of the mean).
'The value is significantly lower than the recommendation.
Mean HEI and HEI Component
Scores
National average3 values were based on
data obtained from the CSFII, 1994-
1996. The data for the students were
collected in 1999. Compared with the
national average, student scores for
fruits, total fats, saturated fats,
cholesterol, and variety were signifi­cantly
higher, averaging about 1 to 2
points more (table 4). Compared with
the national average HEI score (60.9
of a possible 100), the overall score
for the female, rather than male, college
students was significantly higher-69.3
versus 62.2 (table 5). The females also
had significantly higher component
scores for fruits, total fats, saturated
fats, cholesterol, and variety. Males,
however, had a significantly lower
score for grains: 5.7 versus 6.6
(national average).
HEI scores based on students' age were
significantly higher than the national
average (69.9 vs. 61.1 for younger
students and 65.5 vs. 60.8 for older
students) as were scores for total fats
and saturated fats. Whereas the national
3This average is deri ved from a population with
similar distributions of age and gender as those
of the college students.
average HEI scores for total fats
and saturated fats were 7.0 and 6.3,
respectively, the students' scores, based
on their age, for total fats ranged from
8.7 to 9.0; their scores for saturated
fats ranged from 8.2 to 8.4. Younger
students had higher mean scores for
each of the five food groups, compared
with older students, but older students
had higher cholesterol scores.
With total HEI scores of 66.5 to 68.0,
science and nonscience majors' scores,
respectively, surpassed the national by
5.4 to 7.9 points. Nonscience majors
had a higher mean HEI score than
did science majors because of higher
scores (0.2 to 1.5 points) for grains,
vegetables, meat, and variety.
Sodium scores were generally lower
(but not significantly) for all groups
studied, compared with the national
average, except for those of science
majors and females. Sodium scores
ranged from 4.0 to 6.6; the national
average was 6.1. Sodium intake may
be related to the type of snack, as well
as the mix of foods, consumed by these
students. For example, lowfat grain
snacks are often salty but promoted as
a healthful food choice. Meals at fast­food
restaurants may also make
appreciable contributions to sodi um
intake.
Family Economics and Nutrition Review
Table 4. Mean HEI and component scores of college students, compared with a
national average 1
HEI National College students
component average (n=100)
Total HEI 60.9±.10 67.2 ± 1.25
Grains 6.6 ± .03 6.6 ± .29
Vegetables 5.9 ± .02 6.5 ± .38
Fruits 3.2 ± .02 4.2 ± .40*
Milk 4.7 ± .03 4.4 ± .35
Meats 6.2 ± .08 6.0 ± .36
Total fats 7.0 ± .01 8.8 ± .26*
Saturated fats 6.3 ± .01 8.3 ± .32*
Cholesterol 7.9 ± .09 8.9 ± .28*
Sodium 6.1 ± .14 5.8 ± .42
Variety 7.1 ± .02 7.9 ± .31**
1Scores are for a population with age and gender distributions that are similar to those of the sample.
*Scores are significantly different from the national average, P< 0.01.
**Scores are significantly different from the national average, p< 0.05.
While we did not analyze fat and
saturated fat as a percentage of total
food energy, scores indicated that the
fat and saturated fat intakes of these
students were lower than the national
average. A translation of a score to
actual percentage of fat is 31 .5 percent
(score of 9.1) for females and 33
percent (score of 8.1) for males.
Hertzler and Frary (1996) reported
student fat intake ranges from 25 to
29 percent for females and males,
respectively. Troyer et al. (1990)
reported fat intake ranges from 34 to
36 percent. The lower intake of fat as
a percentage of total kilocalories is
consistent among students who select
lower fat foods and have concerns
about food and weight (Hertzler &
Frary, 1996).
The Dietary Guidelines for Americans,
the Food Guide Pyramid, and the
National Council's Diet and Health
Report all stress the importance of
variety in a healthful diet (USDA,
1995; National Research Council,
1989). As with the nutrients of
moderation (total fats, saturated fats,
and cholesterol), variety scores for
2002 Vol. 14 No. 1
students who were female, less than 20
years old, and nonscience majors were
significantly higher than the national
average (8.0, 8.3, and 8.4, respectively,
vs. 7.1).
Concerns about health and weight
management commonly expressed by
female students, possible younger
students still living at home and eating
with family members, and an increased
awareness of nutrition and health issues
by non-nutrition students may be
factors contributing to their dietary
choices and the subsequent overall
HEI and component scores seen here.
Limitations of Study
The limitations of this study relate to
the samples, dietary assessment, and the
IHEI food database. We compared
1999 college students' HEI scores with
those based on a 1994-1996 national
average; hence, the differences in
scores may not represent a true change
in dietary intakes. Because we used a
convenience sample, the subjects in this
study may not have been representative
of other college students. Thus,
selection bias may have affected our
results, and our findings may not be
geographically representative of college
students living in the general university
community. In particular, because
ethnic minorities were underrepresented
in this sample, care should be used in
extrapolating the findings of this study
to other college populations or to young
adults in general.
One-day dietary records were used to
assess dietary intakes: such data may be
poor indicators of a person's usual diet,
but a 1-day dietary record is a generally
acceptable means of characterizing a
group's intake when the sample size is
sufficient (Basiotis, Welsh, Cronin,
Kelsay & Mertz, 1987; Levine &
Guthrie, 1997). The use of a 1-day
dietary record, however, may not reflect
a person's normal eating pattern. When
providing dietary information, survey
respondents tend to both underreport
consumption of certain foods­especially
those high in fat and
calories-and overreport consumption
of other foods-such as those high in
nutrients. Pertinent to this study is the
possible omission of some foods
consumed by college students,
including high-protein and sports-type
drinks. These foods are not in the foods
database of the IHEI.
The IHEI used in this pilot study was
a prototype, and its application was
evaluated by the students. Some aspects
of the IHEI program were identified as
needing improvement. In particular, the
types and number of food choices were
somewhat limited. Future work on the
IHEI design will include an updated
food database that includes many more
frequently consumed foods, as well as
the addition of a physical activity
component.
9
Table 5. Mean HEI and component scores of college students, by selected characteristics
HEI Gender Age Major1
component Male Female <20 years ;::20 years Science Nonscience
HEI 62.2 ± 2.1 69.3 ± 1.5* 69.9 ± 1.9* 65.5 ± 1.6* 66.5 ± 1.7* 68.0 ± 1.8*
Grains 5.7 ± .61* 6.9 ± .31 6.8 ± .45 6.4 ± .37 6.5 ± .34 6.7 ± .49
Vegetables 6.8 ± .71 6.3 ± .46 6.8 ± .58 6.2 ±.51 5.8 ±.55 7.3 ±.51
Fruits 3.4 ± .71 4.6 ± .48** 4.9 ± .68** 3.8 ± .49 4.2 ±.55 4.2 ±.59
Milk 4.9 ± .72 4.2 ± .39 4.5 ± .55 4.4 ± .46 4.4 ± .46 4.4 ±.54
Meats 7.8 ±.57 5.2 ± .42 6.4 ± .60 5.7 ± .45 5.4 ± .51 6.8 ± .48
Total fats 8.1 ±.58 9.1±.28* 9.0 ± .35* 8.7 ± .37* 9.0 ± .30* 8.5 ± .47*
Saturated fats 7.5 ± .70 8.6 ± .33* 8.4± .51* 8.2 ± .40* 8.4 ± .39* 8.1 ±.51*
Cholesterol 6.7 ± .79 9.9± .10* 8.8 ± .47 9.0 ± .36* 9.0 ± .36* 8.8 ± .45*
Sodium 4.0 ± .78 6.6 ± .47 6.1 ± .61 5.6 ±.57 6.6 ±.54 4.8 ± .63
Variety 7.3 ±.53 8.0 ± .38* 8.3 ± .48** 7.5 ± .40 7.2 ± .47 8.4 ± .36*
1Science majors: dentistry, engineering science, agricultural science and forestry, medicine, nursing, and pharmacy. Nonscience majors: arts and sciences, business and
economics, creative arts, human resources and education, journalism, law, physical education, and social work.
'Scores are significantly different from a national sample with comparable characteristics, p< .01.
"Scores are significantly different from a national sample with comparable characteristics, p< .05.
n=100.
Conclusions
Current research on diet and chronic
disease has been lacking in appropriate
methods to evaluate overall diet quality.
In this study, we used the IHEI to
assess the quality of college students'
diets. The IHEI proved to be an
effective dietary assessment tool for
this sample. As such, it should be a
component of basic introductory
nutrition courses because the infor­mation
it provides will help educators
tailor their courses. For example,
analyses from the IHEI can help
instructors address specific topics in
their course curriculum. This tailoring
of nutrition education to food habits
and eating practices of subgroups of
the college population should result
in nutrition courses and education
programs that are more meaningful.
Ultimately, this type of nutrition
education at the college level can result
in many positive lifestyle changes that
10
can help achieve the goals of nutrition
and health specified in the Dietary
Guidelines for Americans (USDA,
2000) and in Healthy People, 2010
(DHHS, 2000). In addition, our
findings and the methods used may
serve as a basis for future research on
diet quality and risks of related chronic
diseases among college students as well
as in other subgroups of the American
population.
Family Economics and Nutrition Review
References
Basiotis, P.P., Welsh, S.O., Cronin, F.J., Kelsay, J.L., & Mertz, W. (1987).
Number of days of food intake records required to estimate individual and group
nutrient intakes with defined confidence. The Journal of Nutrition 117(9):1638-
1641.
Bowman, S.A., Lino, M., Gerrior, S.A, & Basiotis, P.P. (1998). The Healthy
Eating Index 1994-96. CNPP-5. U.S. Department of Agriculture, Center for
Nutrition Policy and Promotion.
Douglass, J.S. (1998). Development of Healthy Eating Index Scores for the 1994-
96 USDA Continuing Survey uf Food Intakes by Individuals. f'.:-liqgton, VA: TAS­Environ.
Frazao, E. (1999). High costs of poor eating patterns in the United States. In E.
Frazao (Ed.), America's Eating Habits: Changes & Consequences. Agriculture
Information Bulletin No. 750. U.S. Department of Agriculture, Economic
Research Service.
Georgiou, C.C., Betts, N.M, Hoerr, S.L., Keirn, K., Peters, P.A., Stewart, B., et al.
(1997). Among young adults, college students and graduates practiced more
healthful habits and made more healthful food choices than did nonstudents.
Journal of the American Dietetic Association 97(7):754-759.
Harless, T., Koch, J., & Slapar, H. (1996). Diet and health among college students.
HPER C511 Course for Epidemiology, pp. 1-17.
Hertzler, A.A., & Frary, R.B. (1996). Family factors and fat consumption of
college students. Journal of the American Dietetic Association 96(7):711-714.
Hertzler, A.A. & Frary, R. (1992). Dietary status and eating out practices of
college students. Journal of the American Dietetic Association 92(7):867-869.
Kant, A.K. (1996). Indexes of overall diet quality: A review. Journal of the
American Dietetic Association 96(8):785-791.
Kennedy, E., Bowman, S., Lino, M., Gerrior, S., & Basiotis, P. (1999). Diet
quality of Americans. In E. Frazao (Ed.), America's Eating Habits: Changes &
Consequences. Agriculture Information Bulletin No. 750. U.S. Department of
Agriculture, Economic Research Service.
Kennedy, E.T., Ohls, J., Carlson, S., & Fleming, K. (1995). The Healthy Eating
Index: Design and application. Journal of the American Dietetic Association
95( 10): 1103-1108.
Levine, E., & Guthrie, J. ( 1997). Nutrient intake and eating patterns of teenagers.
Family Economics and Nutrition Review 10(3):20-35.
Mitchell, S.J. (1990). Changes after taking a college basic nutrition course.
Journal of the American Dietetic Association 90(7):955-961.
2002 Vol. 14 No. 1 11
National Research Council, Committee on Diet and Health, Food and Nutrition
Board. (1989). Diet and Health: Implications for Reducing Chronic Disease Risk.
Washington, DC: National Academy Press.
Schuette, L.K., Song, W.O., & Hoerr, S.L. (1996). Quantitative use of the Food
Guide Pyramid to evaluate dietary intake of college students. Journal of the
American Dietetic Association 96(5):453-457.
Shah, Z., George, V.A., & Himburg, S.P. (1999). Computer-assisted education for
dietetic students: A review of literature and selected software. Journal of Nutrition
Education 31(5):255-261.
Statistical Package for the Social Sciences. (1997). Version 9.0. Chicago, Ulinois:
SPSS, Inc.
Tavelli, S., Beerman, K., Shultz, J.E., & Heiss, C. (1998). Sources of error and
nutritional adequacy of the Food Guide Pyramid. Journal of American College
Health 47(2):77-82.
Troyer, D., Ullrich, I.H., Yeater, R.A., & Hopewell, R. (1990). Physical activity
and condition, dietary habits and serum lipids in second-year medical students.
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(1996). The Food Guide Pyramid (slightly revised). Home and Garden Bulletin
No.232. U.S. Department of Agriculture.
U.S. Department of Agriculture and U.S. Department of Health and Human
Services. (1995). Nutrition and Your Health: Dietary Guidelines for Americans
(4th ed.). Home and Garden Bulletin No.232. U.S. Department of Agriculture.
U.S. Department of Agriculture and U.S. Department of Health and Human
Services. (2000). Nutrition and Your Health: Dietary Guidelines for Americans
(5th ed.). Home and Garden Bulletin No.232. U.S. Department of Agriculture.
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(Conference edition, in two volumes). Washington, DC.
12 Family Economics and Nutrition Review
Helen H-C. Lee, PhD, CNS
Food and Drug Administration
Shirley A. Gerrior, PhD, RD
U.S. Department of Agriculture
Center for Nutrition Policy and Promotion
2002 Vol. 14 No. 1
Consumers of Reduced-Fat, Skim,
and Whole Milks: Intake Status of
Micronutrients and Dietary Fiber
Data from the U.S. Department of Agriculture's Continuing Survey of Food Intakes
by Individuals (CSFI I) 1989-91 were used to evaluate the intakes of vitamins,
minerals, and dietary fiber by Americans (ages 2 years and older) who drank milk
containing different levels of fat. Results show that people who drank reduced-fat
or skim milk had sign1i:.:antly greater mean intakes of fat-soluble vitamins and
carotene, water-soluble vitamins, minerals (except sodium), and dietary fiber,
compared with people who drank whole milk. However, intakes of zinc and
vitamin E (by males and females) and calcium (by females) did not meet 100
percent of the Recommended Dietary Allowances (RDAs), regardless of the type
of milk consumed. Overall, those who drank skim milk had the most favorable
micronutrient intakes. These results suggest that those individuals who chose
to drink reduced-fat or skim milk also chose more micronutrient-dense foods,
resulting in more healthful diets. Despite this improved dietary quality, intakes
of foods rich in zinc, vitamin E, and calcium need to be encouraged, regardless
of the type of milk consumed.
S cientific evidence suggests that
diet plays an important role in
development of chronic diseases.
In particular, excessive consumption
of dietary fat has been implicated with
increased risk of coronary heart disease
and some types of cancer (National
Research Council, 1989). To promote
health and reduce risk of chronic
diseases, dietary recommendations
have been developed for Americans
by the National Cancer Institute
(Butrum, Clifford&Lanza, 1988), the
U.S. Surgeon General (U.S. Department
of Health and Human Services [DHHS],
1988), and others (Krauss et al., 1993).
These recommendations are consistent
with the Dietary Guidelines for
Americans and the Food Guide
Pyramid to reduce dietary intakes of
total fat, saturated fat, and cholesterol;
to moderate intakes of sugar, sodium,
and alcohol; and to increase intake
of dietary fiber (U.S. Department of
Agriculture [USDA], 1992; USDA &
DHHS, 1995).
The Dietary Guidelines for Americans
recommend that Americans choose a
diet that provides no more than 30
percent of total calories from fat, less
than 10 percent of total calories from
saturated fat, and no more than 300
milligrams of cholesterol per day.
Dietary fat intake as a percentage of
total calories has declined over the
past 20 years. In 1977-78, intake of
dietary fat was about 40 percent of
energy (USDA, 1984). Intake of dietary
fat as a percentage of energy decreased
to 36 and 37 percent in 1985-86, 34
percent in 1989-91, and 33 percent in
1994-96(Tippettetal., 1995; USDA,
1986,1987, 1997). Along with this
decrease, saturated fat also decreased
as a percentage of energy-from 13
percent in 1985-86 to 11 percent in 1994-
96(USDA, 1986,1987, 1997).During
13
this time, daily grams of fat intake also
decreased untill991 when its intake
increased but remained below earlier
levels. Since 1991, daily grams offat
intake have remained steady or in­creased
depending on the population
subgroup studied (Anand & Basiotis,
1998; Morton & Guthrie, 1998). None­theless,
the overall decrease in dietary
fat over the past 20 years has been
achieved, in part, by consumption of
a variety of lower fat foods and fat­modified
products (Buzzard et al., 1990;
Gorbach, 1990; Lee, Gerrior & Smith,
1998; Peterson, Sigman-Grant,
Eissenstat & Kris-Etherton, 1999;
Wirfalt&Jeffery, 1997).
From analyzing the nationwide food
intake database of the Continuing
Survey of Food Intakes by Individuals
(CSFII) 1989-9l,Leeetal. (1998)
reported that total fat intake of people
who drank skim milk and reduced-fat
milk' was significantly (p~0.05 ) lower
than those who drank whole milk. Thus,
the dietary goal of not more than 30
percent of caloric intake from total fat
was achieved by several age groups
that drank skim milk. This dietary goal
was not achieved by any age groups of
whole milk or reduced-fat milk drinkers.
The authors found that people who
drank reduced-fat and skim milks
consumed more fruits and vegetables
and less meat, compared with people
who drank whole milk.
A number of other studies also
showed that inclusion of lower fat
food choices-such as lower fat dairy
products, leaner meats, and fat-modified
bakery products-lowered intakes of
total fat, saturated fat, and cholesterol
and affected the micronutrient profile
of the diet (Buzzard et al., 1990; Gorbach
etal., 1990; Peterson et al., 1999; Wirfalt
1The term "reduced fat" as used in thjs paper
includes reduced-fat milk (2%) and lowfat
rllilk (1%).
14
& Jeffery, 1997). Two studies that
examined food intakes and dietary
patterns reported that as dietary fat
intake decreased, intakes of reduced-fat
milk, vegetables, fruit, cereals, fish, and
chicken increased and intakes of whole
milk and cheese, salty snacks, peanuts,
red meats, eggs, desserts, and fried
potatoes decreased (Gorbach et al.,
1990; Subar, Ziegler, Patterson, Ursin
& Graubard, 1994). The use of a fat­reduction
strategy appears to be
associated with distinctively different
food choices, and it has been sug­gested
that people who choose food
consistent with fat reduction make more
conscious food choices that result in a
morehealthfu1diet(Leeetal., 1998;
Peterson eta!., 1999).
Fluid milk has provided the consumer
lower fat milk options for many years
and is an integral part of the American
diet. One popular strategy to lower the
intake of dietary fat is the use of
reduced-fat or skim milk in place of
whole milk in the diet. In 1994, con­sumption
of milk and milk products
contributed about 12 percent of total
fat and 6 percent of saturated fat to
the U.S. food supply (Gerrior & Bente,
1997). Of this, wholemilk(with a38-
percent share of the market) contributed
2.0 percent of the total fat and 3.8
percent of the saturated fat; reduced-fat
and skim milks combined (62-percent
share) contributed 1.5 percent of the
total fat and 2.8 percent of the saturated
fat (Gerrior & Bente, 1997).
Milk and milk products also make
important nutrient contributions to the
diet. Along with providing high-quality
protein, they are good sources of
vitamins (A, D, B 12, and riboflavin)
and minerals (calcium, phosphorus,
magnesium, potassium, and zinc).
Studies examining the effect of lower fat
food choices on the nutritional profiles
of the diet reported that adults who
drank skim milk had significant! y higher
intakes of vitamin A, vitamin B6 and
magnesium, compared with users of
higher fat milk (Peterson et al., 1999;
Wirfalt&Jeffery, 1997).
Understanding the effect of the use of
milks on intakes of micronutrients and
dietary fiber is important-considering
the valuable nutrient contributions of
fluid milk, its possible role in lowering
the risk of osteoporosis, and the
decreasing trend in consumption of
fluid milk by Americans (Gerrior,
Putnam & Bente, 1998). The purpose
of this study was to evaluate the
intakes of vitamins, minerals, and
dietary fiber by Americans, 2 years and
older, who drink different types of milk. 2
Survey and Methods
This study used data from the CSFII,
conducted by the U.S. Department of
Agriculture (USDA) between 1989 and
1991 with a national stratified sample
ofl5,128 individuals residing in the48
conterminous States and Washington,
DC. Persons who were living away from
home or in institutions were ineligible.
The stratification took into account
geographic location, degree of urban­ization,
and socioeconomic consider­ations.
The survey used 1-day 24-hour
recalls from an in-person interview
and a 2-day dietary record. Detailed
methods of the survey were published
previously (Tippett et al., 1995). The
present study used basic- or all-income
data from respondents, aged 2 years
and older, with a complete 3-day dietary
intake. Excluded from the analysis were
respondents who reported no food
intake. The nutrient database used to
2For a report on energy compensation,
energy-yeilding nutrient intakes, and food­group
intakes by consumers of different types
of milk in the present study population, see
Peterson et al. ( 1999).
Family Economics and Nutrition Review
Table 1. Mean intakes of vitamins by males, by age and milk type1
Age and Vitamin A Carotene Vitamin E Thiamin Riboflavin Niacin Vitamin B6 Folate Vitamin B12 Vitamin C
milk type (RE) (RE) (alpha·TE) (mg) (mg) (mg) (mg) (1-1-9) (1-1-9) (mg)
~2 years
Whole 1004a 3goa o.a7a 1.72a 2.13a 23.1a 1.82a 272a 6.ooa g1a
(41) (27) (0.24) (0.03) (0.04) (0.4) (0 .03) (6) (0.27) (2)
Reduced-fat 1246b 476b g,77b ugb 2.31b 24.6b 2.02b 307b 6.1oa 104b
(35) (24) (0.36) (0.03) (0.04) (0.4) (0.04) (7) (0.22) (3)
Skim 1375b 57gc 10.05b 1.82b 2.2oab 24 .gb 2.10b 330C 6.2ga 125c
(113) (54) (0.7) (0.07) (0.08) (O,g) (0.08) (14) (O.g5) (6)
20- 50 years
Whole 1036a 460a 8.7aa 1.83a 2.2oa 26.1a 2.g6a 2aoa 6.14a goa
(61) (4g) (0.40) (0.05) (0.07) (0.7) (0.06) (11) (0.27) (4)
Reduced-fat 11g3 436a 10.60b 1.g2a 2.44b 27.5a 2.18b 31aab 6.7oa ggb
(50) (33) (0.64) (0.05) (0 .07) (0.7) (0.06) (11) (0.37) (4)
Skim 1231b 4aoa 11.75b 2.06a 2.43ab 27.7a 2.23b 356b 5.g5a 128C
(7g) (66) (1 .16) (0.12) (0.12) (1.4) (0.12) (22) (0.37) (11)
51 - 64 years
Whole 1186a 5gaa 8.66a 1.66a 2.ooa 23.oa 1.83a 266a o.o3a 81a
(148) (134) (o.ga) (o.og) (0.12) (1.2) (o.og) (11) (0.54) (6)
Reduced-fat 1437b 70gb 11.20b 1.76a 2.14a 25.ga 2.17b 324b 6.o5a 118b
(105) (85) (1 .og) (0.07) (0.08) (0.8) (o.og) (18) (0 .41) (8)
Skim 132gb 57aab g,15ab 1.65a 2.ooa 24.5a 2.14b 326b 5.7aa 12gb
(146) (110) (1.52) (0.10) (0.12) (1 .3) (0 .14) (27) (0.63) (13)
~65 years
Whole 1386a 423a 7.3ga 1.63a 2.04a 21.6a 1.83a 2goa a.a5a ega
(227) (41) (0.52) (0.07) (0.12) (0.8) (o.og) (15) (2 .21) (6)
Reduced-fat 1663a 708b 11 .31b 1.87b 2.2aa 24.6b 2.1ga 344b 7.01a 126b
(132) (61) (1.1g) (0.08) (0.12) (1.0) (0.11) (21) (O,g3) (13)
Skim 2120a gg6b g,7aab 1.64ab 2.15a 22.6ab 2.15a 333b g.7oa 134b
(528) (165) (1.11) (0.10) (0.23) (1 .6) (0.16) (27) (4,g6) (10)
1Standard erro~ of me~n in parentheses. For each vitamin, values with different superscript letters in the same age group are significantly different at p<0.05.
Source: USDAs Contmumg Survey of Food Intakes by Individuals (CSF/1), 1989-91, 3-day intake data. -
estimate intakes of various nutrients
was developed by the USDA for use
in tills survey by using the USDA
National Nutrient Data Base for
Standard Reference and the USDA
Nutrient DataBank (1992). Data
were weighted to reflect the general
population.
Each gender was placed in one of five
groups based on its milk consumption:
no milk, whole milk, reduced-fat milk,
skim milk, and mixed milk. Each group
was also placed in a category based on
age: 2 to 5 years (representing toddlers
and preschoolers), 6 to 11 years
(schoolchildren), 12 to 19 years
(teenagers), 20 to 50 years (adults),
2002 Vol.14No.l
51 to 64 years (middle aged), and 65
years and older (elderly).lntak:es of
food groups by people who drank
whole, reduced-fat, and skim milk were
previously reported (Lee et al., 1998).
Statistical Analysis
We calculated estimates of the mean
and standard error of the means (SEMs)
by using Survey Data Analysis
(SUDAAN), a statistical program
designed for complex, stratified
sampling that is used to collect survey
data (Shah, Barnwell, Hunt & La V ange,
1991). SUDAAN is recommended by
USDA for statistical tests of signifi-cance
on weighted data from its
surveys (USDA, 1989). We also used
Statistical Analysis Software (SAS) to
analyze the data (SAS Institute, Inc.,
1990). If the F test, by analysis of
variance (ANOV A), showed a signifi­cant
difference, Scheffe's t test
(Scheffe, 1953) was used for pair-wise
comparisons between groups at the
5-percent, two-tailed probability level.
The resulting comparisons between the
no-milk group or the mixed-milk group
and the other milk groups showed
inconsistent and insignificant differ­ences.
Therefore, this paper reports
only the comparisons among three
groups of milk drinkers: whole milk,
reduced-fat milk, and skim milk.
15
Table 2. Mean intakes of vitamins by females, by age and milk type1
Age and Vitamin A Carotene Vitamin E Thiamin Riboflavin Niacin Vitamin B6 Folate Vitami n B12 Vitamin C
milk type (RE) (RE) (alpha-TE) (mg) (mg) (mg) (mg) (t-<9) (t-<9) (mg)
?.2 years
Whole 8188 3368 6.178 1.348 1.678 17.88 1.458 2228 4.268 838
(26) (16) (0.12) (0.02) (0.03) (0.2) (0.02) (4) (0.17) (2)
Reduced-fat 983b 411b 6.77b 1.31• 1.69b 18.1b 1.5Qb 231b 4.288 86b
(22) (15) (0.16) (0.02) (0.02) (0.2) (0.02) (4) (0.14) (2)
Skim 1241C 67QC 8.11c 1.40b 1.6aab 19.6C 1.69c 27QC 4.108 1Q5C
(71) (66) (0.49) (0.04) (0.04) (0.5) (0.05) (9) (0.17) (4)
20- 50 years
Whole 8168 3438 6.sa• 1.328 1.598 18.58 1.438 2138 4.ss• so•
(52) (26) (0.23) (0.03) (0.05) (0.4) (0.04) (7) (0.40) (3)
Reduced-fat 946b 391b 7.11 8 1.31 8 1.68b 19.08 1.498 2288 4.41 8 82ab
(32) (23) (0.26) (0.03) (0.03) (0.4) (0.03) (6) (0.26) (3)
Skim 1152" 591c 8.30b 1.43b 1.70b 19.7b 1.93b 261b 4.168 gsb
(20) (117) (0.57) (0.05) (0.06) (0.6) (0.13) (12) (0 .22) (6)
51 - 64 years
Whole 8878 4258 5.468 1.268 1.468 17.28 1.388 2178 4.158 878
(71) (59) (0.27) (0.05) (0.05) (0.7) (0.06) (12) (0.42) (93)
Reduced-fat 1092b 5348 6.96ab 1.31• 1.57ab 19.1b 1.59b 2458 4.298 938
(64) (41) (0.40) (0.04) (0.06) (0.6) (0.07) (10) (0.26) (5)
Skim 1450C 780b 9.00b 1.478 1.80b 21.sc 1.93c 307b 4.91 8 128b
(151) (127) (1.65) (0.12) (0.12) (1.2) (0.14) (28) (0.53) (12)
?.65 years
Whole gsa• 5138 5.91 8 1.208 1.478 15.68 1.368 2178 3.628 848
(67) (60) (0.30) (0.04) (0.04) (0.4) (0.04) (8) (0.24) (5)
Reduced-fat 1134b 531 8 7.ogab 1.2aab 1.6Qb 17.4b 1.56b 241b 4.708 1QQb
(56) (30) (0.37) (0.03) (0.04) (0.5) (0.05) (7) (0.42) (4)
Skim 1349b a sob 7.58b 1.30b 1.54ab 18.1b 1.63b 266b 3.3o• 111b
(102) (93) (0.60) (0.05) (0.17) (0.7) (0.07) (14) (0.20) (7)
1Standard error of mean in parentheses. For each vitamin, values with diHerent superscript letters in the same age group are significantly different at p5_0.0S.
Source: USDA's Continuing Survey of Food Intakes by Individuals (CSF/1), 1989-91, 3-day intake data.
fat milks in the older age groups. A or skim milk, as well as between those
Results detailed description and analysis of who drank reduced-fat milk versus
the study population were reported skim milk. Analysis of possible gender
Study Population previously (Lee et aL, 1998). differences showed that for both
Fifty-six percent of the study popula- genders the significant difference in
tion (n=l0,759) were females. Over the Intakes of Fat-Soluble Vitamins fat-soluble vitamins among the various
3-day period, about one-third of the For both the males and females (age 2 groups of milk drinkers occurred mostly
population consumed whole milk (34 and older), intakes of vitamins A and E in the adult groups (ages 20 and older).
percent) or reduced-fat milk (31 per- and carotene were highest among those
cent); 7 percent, skim milk; 9 percent, who drank skim milk, followed by those Intakes of Water-Soluble Vitamins
mixed types of milk; and 19 percent, no who drank reduced-fat milk, and then For both males and females, ages 2
milk. Generally, fewer people drank milk whole milk (tables 1 and 2). For males, and older, intakes of niacin, vitamin B6,
as their age increased. Compared with the difference in intakes of these fat- folate, and vitamin C were significantly
other age groups, the 20- to 50-year-old soluble vitamins and carotene was lower for those who drank whole milk
group was more likely not to drink milk; significantly different between those than for those consuming reduced-fat
toddlers and preschoolers were more who drank whole milk and those who and skim milk (tables 1 and 2). Intakes
likely to drink whole milk. The con- drank reduced-fat milk or skim milk. For of these four nutrients by females as
sumption of skim milk increased for females, the difference was statistically well as intakes of fo late and vitamin C
older children, indicating a shift in significant between those who drank by males were significant! y lower for
preference from whole milk to lower whole milk, compared with reduced-fat those drinking reduced-fat milk than for
16 Family Economics and Nutrition Review
Table 3. Mean intakes of minerals by males and females age 2 and over, by milk type1
Gender and
type of milk Calcium Phosphorus Magnesium Iron Zinc Copper Potassium Sodium
consumed (mg) (mg) (mg) (mg) (mg) (mg) (mg) (mg)
Males
Whole 905a 1362'1 266a 15.38 12.58 1.1ga 26948 365(11
(21) (25) (5) (0.3) (0.3) (0.04) (46) (65)
Reduced-fat 98~ 1415b 292> 16.? 13.2b 1.2? 2871' 361ga
(16) (18) (4) (0.3) (0.4) (0.02) (42) (53)
Skim 96rJl 1~ 310C 16.9b 12.gab 1.3?C 307ff 3646a
(36) (44) (9) (0.7) (0.5) (0.05) (84) (176)
Females
Whole 71?8 1052'1 2118 1.88 9.18 0.92'1 216()3 26838
(13) (15) (3) (0.2) (0.1) (0.01) (27) (41)
Reduced-fat 745ab 105ga 22rJl 12.6b 9.1 8 0.99b 223Jb 245Jb
(11) (12) (3) (0.2) (0.1) (0.01) (26) (29)
Skim 75fP 1105b 2~ 13.6c 9.8b 1.ogc 248~ 237fP
(20) (21) (6) (0.5) (0.3) (0.03) (46) (59)
1Standard error of mean in parentheses. For each mineral, values with different superscript letters in the same gender group are significantly different at p~0 . 05 .
Source: USDA's Continuing Survey of Food Intakes by Individuals (CSF/1), 1989-91, 3-day intake data.
those drinking skim milk. Intakes of
thiamin were also significantly lower
for the males who drank whole milk,
compared with males who drank
reduced-fat or skim milk; the same was
the case for females who drank whole
milk or reduced-fat milk, compared with
females who drank skim milk (tables 1
and 2).
The analysis of the age groups revealed
that the significant difference in intakes
of water-soluble vitamins according to
milk type occurred among adult age
groups for both males and females
(tables 1 and 2). Intakes of water­soluble
vitamins (including thiamin,
riboflavin, niacin, vitamin B6, folate,
vitamin B 12, and vitamin C) were
significantly lower for those who drank
whole milk, compared with those who
drank reduced-fat or skim milk. This
finding was consistent for most adult
male and female age groups (20 years
and older), but not for younger age
groups (data not shown). For male age
groups, intakes of water-soluble
vitamins between consumers of
2002 Vol.l4No.1
reduced-fat and skim milk were not
significantly different. However, for
certain female age groups, intakes of
several vitamins, including niacin,
folate, vitamin B6, and vitamin C, were
significantly greater for consumers of
skim milk, compared with reduced-fat
milk.
Intakes of Minerals
For both genders, ages 2 and older,
consumers of whole milk, compared
with consumers of reduced-fat milk or
skim milk, had significantly lower
intakes of all the minerals analyzed,
except for sodium for males and zinc for
females (table 3). Sodium intake was not
significantly different based on the
types of milk consumed by males but
was significantly reduced for females
who drank lower fat milk.
In the same age category (ages 2 and
older), intakes of the minerals magne­sium,
copper, and potassium were
significantly lower for males who drank
reduced-fat milk, compared with males
who drank skim milk (table 3). However,
among females, intakes of all the dietary
essential minerals studied, except for
sodium, were significantly lower among
those consuming whole milk, compared
with those drinking skim milk. These
significant increases in intakes of
minerals by those drinking skim milk,
compared with those drinking higher fat
milk, occurred mostly in the adult age
groups (ages 20 and older) of females
(table 3).
Intakes of Dietary Fiber
Those ages 2 and older who drank
whole milk had significantly lower
intakes of dietary fiber than their
counterparts who drank reduced-fat
or skim milk (table4). This significantly
lower intake in dietary fiber by indi­viduals
of both sexes who drank whole
milk occurred in two adult age groups
(adult and elderly) but not in younger
age groups. For several age groups,
including elderly males as well as adult
and elderly females, those who drank
reduced-fat milk had significantly lower
intakes of dietary fiber, compared with
those who drank skim milk.
17
... people who drank reduced-fat
or skim milk had significantly
greater mean intakes of fat-soluble
vitamins and carotene,
water-soluble vitamins, minerals
(except sodium), and dietary
fiber, compared with people
who drank whole milk.
18
Table 4. Mean intake of dietary fiber
(in grams) by males and females, by
age and type of milk consumed1
Age and milk type Male Female
?.2 yrs
Whole 14.2'1 11 .3a
(0.3) (0.2)
Reduced-fat 15.7b 12.1b
(0.3) (0.2)
Skim 18.0C 14.5c
(0.7) (0.4)
2-S yrs
Whole 8.0 8.3
(0.3) (0.3)
Reduced-fat 10.0 9.2
(0.5) (0.4)
Skim 9.8 9.9
(1.1) (0.7)
20-SOyrs
Whole 15.4 11.3a
(0.5) (0.3)
Reduced-fat 17.1 12.ob
(0.5) (0.3)
Skim 19.2 14.1C
(1.2) (0.6)
?.65 yrs
Whole 14.9a 11 .3a
(0.7) (0.4)
Reduced-fat 17.9b 13.2b
(0.6) (0.4)
Skim 20.3C 14.9C
(1.5) (0.6)
1Standard error of mean in parentheses. Values
with different superscript letters in the same
gender-age groups are significantly different at
p~0.05.
Source: USDA's Continuing Survey of Food
Intakes by Individuals (CSF/1), 1989-91, 3-day
intake data.
Percentage of the 1989
Recommended Dietary
Allowances Met
For males and females, intakes of
vitamins by those ages 2 and older met
or exceeded the 1989 RD As (National
Academy of Sciences, 1989). The
exceptions were vitamin E for both men
and women, and vitamin B6 for women
only (table 5). For vitamins in general,
people who drank reduced-fat and skim
milk met a greater percentage of the
RDAs than did people who drank
whole milk, exceeding 100 percent of
the RDAs. Compared with others, those
drinking skim milk alsometatleast 100
percent of the RDAs for vitantins E and
B6, reflecting higher intakes of these
nutrients. Interestingly, those who
drank whole milk met a greater percent­age
ofRDA for vitamin B 12 , compared
with those who drank lower fat milk.
Males 2 years and older met or ex­ceeded
the RDAs for some of the
minerals studied: calcium, phosphorus,
and iron. They generally met the RDA
for magnesium but failed to meet 100
percent of the RDA for zinc (table 6).
Females 2 years and older exceeded
the RDA for phosphorus only-thus
failing to meet 100 percent of the RDAs
for zinc, calcium, or magnesium for all
three milk categories. Iron intake was
below 100 percent of the RDA for
women drinking whole milk but ex­ceeded
the RDA for those drinking
reduced-fat and skim milk. In general,
when people drank reduced-fat and
skim milk, they met a significantly
higher percentage of the RDAs for
calcium, phosphorous, and iron than
did people who drank whole milk.
Discussion
Our results indicate that the choice
of milk people consumed significantly
affects their intakes of essential
micronutrients. In general, compared
with people who drank whole milk,
those who drank reduced-fat and skim
milk had significantly higher intakes
offat-soluble vitamins (A, E, and
carotene3), water-soluble vitamins
(thiamin, riboflavin, niacin, vitantin B6,
folate, vitamin B 12, and vitamin C),
minerals (calcium, phosphorus,
3Carotene is the precursor to vitamjn A.
Although not technically a vitamin, it is
often measured as a predictor of vitamin A
availability or activity.
Family Economics and Nutrition Review
Table 5. Vitamin intake as a percentage of Recommended Dietary Allowances by males and females age 2 and over, by type of
milk consumed1
Gender and
milk type Vitamin A Vitamin E Thiamin Riboflavin Niacin Vitamin B6 Folate Vitamin B12 Vitamin C
Male
Whole 113'3 84a 135a 145a 14oa 103a 17ga 345a 165a
(3) (2) (2) (2) (2) (1) (3} (11) (3}
Reduced-fat 13gb 1Q3b 103a 155b 148b 111b 1W 33~ 18?
(3) (3} (2) (2) (2) (1} (3} (8) (4)
Skim 143b 1Q2b 13~ 144ab 148b 1oot> 178a 323'3 21SC
(8} (5) (3} (4) (3} (3) (5) (34) (7)
Female
Whole 11~ soa 1soa 13~ 1~ gga 164a 255a 15~
(3) (1} (1} (2} (1) (1) (3) (7) (3)
Reduced-fat 1~ 86b 125b 136a 12ga gsa 15oa 236b 15oa
(2) (1) (1} (1) (1) (1) (2) (5) (2}
Skim 155c 100C 133'! 134a 13gb 1Q6b 154a 2ogb 176b
(6) (4) (3} (2) (2} (2} (4) (6} (5)
1 Standard error of mean in parentheses. For each micronutrient, values with different superscript letters in the same gender are significantly different at ps0.05.
Source: USDA's Continuing Survey of Food Intakes by Individuals (CSF/1), 1989-91, 3-day intake data.
magnesium, iron, zinc, copper, and
potassium), and dietary fiber. People
consuming skim milk had the most
favorable profiles regarding the intakes
of micronutrients. These findings are
consistent with previous reports.
Peterson eta!. (1999) evaluated fat­reduction
strategies and subsequent
micronutrient intakes and reported that,
compared with users of higher fat milk,
men and women who used skim milk
exclusively had improved intakes of
vitamin A, vitamin B6, and magnesium.
Only females who used skim milk
exclusively had improved intakes of
vitamin E, iron, calcium, and zinc.
Another study (Wirfalt & Jeffery, 1997)
showed that users of skim milk, rather
than nonusers, had higher intakes of
dietary fiber, calcium, vitamin C, iron,
and vitamin A. In our study, the
differences in micronutrient intakes
among those consuming different types
of milk were more obvious among
females than among males. The analysis
based on people's age revealed that the
statistical significance in intakes of
micronutrients among those drinking
2002 Vol. 14 No.1
different types of milk occurred among
adults ages 20 and older.
Studying the same population as used
here, Lee eta!. (1998) reported that
those who drank reduced-fat milk
consumed more fruits, vegetables, and
seasoning fats and oils. The observed
favorable intake of micronutrients and
dietary fiber by people who drank
reduced-fat milk is likely linked to the
larger amounts of total vegetables and
fruits consumed by those who drank
reduced-fat and skim milk, compared
with their counterparts who drank
whole milk (table 1). This increased
consumption of vegetables and fruits
by people who drank lower fat milk may
have contributed to the significantly
higher intakes of vitamins C, folate,
magnesium, iron, potassium, copper,
and dietary fiber in the diets of those
who drank reduced-fat and skim milk.
Also, the higher intakes of vitamin E­rich
seasoning fats and the use of
margarine and reduced-fat and skim
milk (fortified with vitamin A) may
have contributed to the improved
intakes of vitamins E and A.
The results of the present study and
previously reported studies (Peterson
etal., 1999; Wirfalt& Jeffery, 1997)
suggest that the use of skim milk could
be a simple indicator of a healthful diet.
Basically, Americans who drink skim
milk appear to be making additional
conscious food choices that reflect a
concern for fat intake and an interest
in a varied and balanced diet. The
improved micronutrient profile, signifi­cantly
lower intakes of red meat, and
significantly higher intakes of veg­etables
and fruit by those who drank
skim milk indicate two things: ( 1) a
tendency to select more healthful food
items and (2) a likelihood of having
food intake patterns closer to dietary
guidance (Gorbach et al., 1990; Peterson
eta!., 1999;Subaretal., 1994).
Dietary intake status for zinc has been
considered a potential health issue in
the United States (Federation of
American Societies for Experimental
Biology, 1995). For each type of milk
drinker, 2 years old and older, intake
of dietary zinc was at 77 to 93 percent
of the RDA (table 6). Data from the
19
People consuming skim milk
had the most favorable profiles
regarding the intakes of
micronutrients.
20
Table 6. Mineral intake as a percentage of Recommended Dietary Allowances by
males and females age 2 and over, by type of milk consumed1
Gender and
milk type Calcium Phosphorus Magnesium Iron Zinc
Male
Whole 1()3'1 155a gga 14ga goa
(2) (2) (1) (2) (2)
Reduced-fat 11~ 1EJSb 104b 163b 9~
(1) (2) (1) (2) (2)
Skim 115b 171b 96a 168b aaab
(3) (3) (2) (5) (2)
Female
Whole aoa 118'1 96a 94a 78a
(1) {1) (2) (1) {1)
Reduced-fat 86b 123b 94a 101b na
(1) (1) (1) (1} (1)
Skim agb 130C gsa 111c 81
(2) (2) (2) (3) (2)
1Standard error of mean in parentheses. For each micronutrient, values with different superscript letters in
the same gender are significantly different at ps_0.05.
Source: USDA's Continuing Survey of Food Intakes by Individuals (CSF/1), 1989-91, 3-day intake data.
USDA's CSFII 1989-91 indicate that
women and men consumed only 75 and
89 percent, respectively, of the RDA
for zinc. The population needs to be
encouraged to choose foods high in
bioavailability and content of zinc.
These foods include red meats (beef,
pork, and veal), poultry, oysters, and
dairy products. Fish, cereal, whole grain
products, legumes, and beans have less
zinc content. Also, the presence of
phytates in whole grains negatively
affects its bioavailability (Bosscher et
al.,2001).
Vitamin E intake was lower for people
who consumed whole milk, compared
with those who consumed reduced-fat
or skim milk. As previously reported,
those who drank reduced-fat and skim
milk consumed significantly higher
amounts of seasoning fats and oils,
which we believe are linked to the
higher intakes of vitamin E, as found
in this study (Lee et al., 1998). Never­theless,
males and females who drank
whole milk as well as females who drank
reduced-fat milk met only 80 to 86
percent of the RDA for vitamin E-a
finding that indicates that vitamin E
needs to be targeted in U.S. nutrition
education efforts. Foods rich in vitamin
E are vegetable oils, dark-green leafy
vegetables, nuts, whole grain cereals,
fortified cereals, and eggs.
Calcium intake is considered a current
public health concern. Recent findings
indicate that food selection practices
in the United States make it difficult
to meet calcium needs without having
milk and milk products in the daily diet
(Gerrior et al., 1998). The present study
shows that calcium intake needs to
improve among all people, regardless of
the type of milk consumed. Consuming
adequate amounts of lower fat milk and
dairy products-such as skim milk or
nonfat yogurt-that are as high or
higher in calcium as whole milk (Gerrior
et al., 1998) could be a good means for
improving the intake of dietary calcium.
These findings indicate that a lower
fat diet does not necessarily ensure
a nutritionally optimal diet. These
findings also emphasize the importance
Family Economics and Nutrition Review
of a balanced diet-one that follows
the guidance of the Dietary Guidelines
for Americans and the Food Guide
Pyramid.
Additional studies, with more recent
data, that include a focus on greater
variety of fat-modified food products
are needed to better understand how
Americans incorporate reduced-fat
foods into their diets and how these
food choices affect nutritional status.
This understanding is necessary to
target more effective nutrition educa­tion
efforts that improve diet quality
and the overall health of Americans.
Limitations
Survey Data
The data used in this study, as with any
survey data, should be interpreted with
appropriate care. Dietary surveys are
subject to nonresponse errors, respon­dent
errors (such as underreporting),
coding and processing errors, and
limitation of nutrient data. For example,
the individuals included in the 1989-91
CSFll sample may not be representative
ofthe general U.S. population. Also,
compared with other days, fewer CSFll
interviews were conducted on Sunday.
Thus, percentages of acceptable dietary
forms collected were lower for Saturday
(day-1 recall), Sunday (day-2 record),
and Monday (day-3 record). Weighting
survey results can reduce the potential
for nonresponse bias. We weighted the
results of this study, and we included
the interview data as a control variable.
The nutrient database developed for
the CSFII and used for our study
reflected up-to-date nutrient informa­tion
at the time the CSFll was con­ducted.
Also, most of its nutrient
values included in the database are
supported by laboratory analyses, but
analytical data are not always available.
Hence, values are sometimes imputed.
2002 Vol. 14 No. 1
RDA versus DRI
Adopted by the Food and Nutrition
Board of the Institute of Medicine,
Dietary Reference In takes (D Rls)
represent the new approach to provid­ing
quantitative estimates of nutrient
intakes for use in a variety of settings.
Hence, the DRis replace and expand on
the past 50 years of periodic updates
and revisions of the RDAs. The DRis
differ in amounts and age categories
from the 1989 RDAs. Along with the
RDA category, the DRis include three
new categories of reference values:
Adequate Intake (AI), the Estimated
Average Requirement (EAR), and the
Tolerable Upper Level (UL) (Yates,
Schlicker&Suitor, 1998).
This study does not use the DRis in
the calculation of nutrient intakes and
nutrient analysis. Until expert guidance
is published by the Food and Nutrition
Board regarding the use of the appro­priate
DRI category for assessing the
diets of individuals in large-scale
dietary surveys, USDA continues to
use the 1989 RDAs to analyze nutrients.
While the DRis are published for the
bone-related nutrients (calcium,
phosphorus, magnesium, vitamin D,
and fluoride) and are available for the
B vitamins (folate, pantothenic acid,
biotin, and choline), DRis for other
nutrients have not been released. Thus
for consistency in reporting of micro­nutrient
intakes and evaluating nutrient
status, we used the 1989 RDAs.
Acknowledgment
We appreciate Drs. Jacqueline Dupont
(Florida State University) and P. Peter
Basi otis (Center for Nutrition Policy
and Promotion, USDA) for their help
in installment of this research. We also
thank Ms. Julie Smith (Agricultural
Marketing Service, USDA) for her
substantial assistance in analyzing
the data.
21
22
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and 1994-96 Diet and Health Knowledge Survey. [On-line]. Available: http://
www.barc.iusda.gov/bhnrc/foodsurvey!home.htm. Accessed April6, 1999.
U.S. Department of Agriculture, Human Nutrition Information Service. (1984 ).
Nutrient Intake of Individuals in 48 States, Year I977-78. Nationwide Food
Consumption Survey, 1977-78, ReportNo.1-2.
U.S. Department of Agriculture, Human Nutrition Information Service. (1986).
Continuing Survey of Food Intakes by Individuals. Nationwide Food Consump­tion
Survey Report No. 85-3.
U.S. Department of Agriculture, HumanN utrition Information Service. (1987).
Continuing Survey of Food Intakes by Individuals. Nationwide Food Consump­tion
Survey Report No. 86-1 .
U.S. Department of Agriculture, Human Nutrition Information Service. (1989).
Guidelines for the Use of Weights When Analyzing and Reporting HNIS Survey
Data. Hyattsville, MD.
2002 Vol. 14No. 1 23
U.S. Department of Agriculture, Human Nutrition Information Service. (1992).
The Food Guide Pyramid. Home and Garden Bulletin No. 252.
U.S. Department of Agriculture, Human Nutrition Information Service. (1992). U.S.
Department of Agriculture Nutrient Data Base for Individual Surveys. Release 7.
Computer tape, Accession No. PB94-504552GEL. Springfield, VA: U.S. Department
of Commerce.
U.S. Department of Agriculture, & U.S. Department of Health and Human Services.
(1995). Nutrition and Your Health: Dietary Guidelines for Americans (4th ed.).
Home and Garden Bulletin No. 232. U.S. Department of Agriculture.
U.S. Department of Health and Human Services. ( 1988). The Surgeon General's
Report on Nutrition and Health. DHHS (PHS) Pub]jcation 88-50210. Washington,
DC.
Wirfalt, A.K.E., & Jeffery, R.W. (1997). Using cluster analysis to examine dietary
patterns: Nutrient intakes, gender, and weight status differ across food pattern
clusters. Journal of the American Dietetic Association 97:272-279.
Yates, A.L., Schlicker, S.A., & Suitor, C.W. (1998). Dietary Reference Intakes: The
new basis for recommendations for calcium and related nutrients, B vitamins, and
cho]jne. Journal of the American Dietetic Association 98(6):699-706.
24 Family Economics and Nutrition Review
Mark Lino, PhD
U.S. Department of Agriculture
Center for Nutrition Policy and Promotion
2002 Vol.l4No. 1
Expenditures on Children
by Families, 2000
Since 1960 the U.S. Department of Agriculture has provided estimates of
expenditures on children from birth through age 17. This article presented the
most recent estimates for husband-wife and single-parent families. Data were
from the 1990-92 Consumer Expenditure Survey. The Consumer Price Index
was used to update income and expenditures to 2000 dollars. Data and methods
used in calculating child-rearing expenses were described and estimates were
provided for major components of the budget by age of the child, family income,
and region of residence. Expenses on the younger child in a two-child, husband­wife
household for the overall United States averaged $6,280 to $14,260 in 2000,
depending on the child's age and family income group. Adjustment factors for
number of children in the household were also provided. Results of this study can
be used in developing State child support guidelines and foster care payments
and in developing family educational programs.
Since 1960the U.S. Department of
Agriculture (USDA) has provided
estimates of expenditures on
children from birth through age 17.
These estimates are used in setting
child support guidelines and foster
care payments and in developing
educational programs on parenthood.
This study presents the latest child­rearing
expense estimates, which are
based on 1990-92 expenditure data that
have been updated to 2000 dollars. The
study presents these new estimates
for husband-wife and single-parent
families. It briefly describes the data
and methods used in calculating child­rearing
expenses 1 and then discusses
the estimated expenses.
IThe Expenditures on Children by Families:
2000 Annual Report provides a more detailed
description of the data and methods. To
obtain a copy, contact USDA, Center for
Nutrition Policy and Promotion, 3101 Park
Center Drive, Room I 034, Alexandria, VA
22302 (telephone: 703-305-7600).
The estimates are provided for the
overall United States. The child-rearing
expense estimates for husband-wife
families are also provided for urban
areas in four regions (Northeast, South,
Midwest, and West) and rural areas
throughout the United States2 to
adjust partially for price differentials
and varying patterns of expenditures.
For single-parent families, estimates are
provided for the overall United States
only because of limitations in the
sample size. Expenditures on children
are estimated for the major budgetary
components: housing, food, transporta­tion,
clothing, health care, child care
and education, and miscellaneous
goods and services. The box on p. 26
describes each expenditure component.
2Urban areas are defined as Metropolitan
Statistical Areas (MSA's) and other places of
2,500 or more people outside an MSA; rural
areas are places of less than 2,500 people
outside an MSA.
25
Categories of Household Expenditures
Housing expenses consists of shelter (mortgage interest, property taxes, or rent; maintenance and repairs; and insurance),
utilities (gas, electticity, fuel, telephone, and water), and house furnishings and equipment (furniture, floor coverings,
major appliances, and small appliances). For homeowners, housing expenses do not include mortgage principal payments;
in the Consumer Expenditw·e Survey, such payments are considered to be part of savings. So, total dollars allocated to
housing by homeowners are underestimated in this report.
Food expenses consists of food and nonalcoholic beverages purchased at grocery, convenience, and specialty stores,
including purchases with food stamps; dining at restaurants; and household expenditures on school meals.
Transportation expenses consists of the net outlay on the purchase of new and used vehicles, vehicle finance charges,
gasoline and motor oil, maintenance and repairs, insurance, and public transportation.
Clothing expenses consists of children's apparel such as diapers, shirts, pants, dresses, and suits; footwear; and clothing
services such as dry cleaning, alterations and repair, and storage.
Health care expenses consists of medical and dental services not covered by insurance, prescription drugs and medical
supplies not covered by insurance, and health insurance premiums not paid by the employer or other organization.
Child care and education expenses consists of day care tuition and supplies; baby-sitting; and elementary and high
school tuition, books, and supplies.
Miscellaneous expenses consists of personal care items, entertainment, and reading materials.
Data
The 1990-92 Consumer Expenditure
Survey (CE) is used to estimate
expenditures on children. Administered
by the Bureau of Labor Statistics (BLS),
the CE collects information on socio­demographic
characteristics, income,
and expenditures of households. The
CE, conducted annually since 1980,
interviews about 5,000 households
each quarter over a 1-year period. Each
quarter is deemed an independent
sample by BLS; thus, the total number
of households in the 1990-92 survey is
about 60,000.
Husband-wife and single-parent
families were selected from these
households for this study if (1) they
had at least one child of their own-age
17 or under-in the household, (2) they
had six or fewer children, (3) they had
no other related or unrelated people
26
present in the household except
their own children, and ( 4) they were
complete income reporters.3 Quarterly
expenditures were annualized.
The sample consisted of 12,850
husband-wife households and 3,395
single-parent households. BLS weight­ing
methods were used to weight the
sample to reflect the U.S. population
of interest. Although based on 1990-92
data, the expense estimates were
updated to 2000 dollars by using
the Consumer Price Index (CPI-U).
(Expenditure and income data for 1990
and 1991 were first converted to 1992
dollars; then, all 3 years of data were
updated to 2000 dollars.)
3Complete income reporters are households
that provide values for major sources of
income, such as wages and salaries, self­employment
income, and Social Security
income.
Methods
The CE collects overall household
expenditure data for some budgetary
components (housing, food, transporta­tion,
health care, and miscellaneous
goods and services) and child-specific
expenditure data for other components
(clothing, child care, and education).
Multivariate analysis was used to
estimate household and child-specific
expenditures. Income level, family size,
and age of the younger child were
controlled so that estimates could be
made for families with these varying
characteristics. Regional estimates were
derived by controlling for region. The
three income groups of husband-wife
households were determined by
dividing the sample for the overall
United States into equal thirds: before­tax
income under $31,000, between
$31,000and $52,160, andover$52,160
in 1992dollars.
Family Economics and Nutrition Review
For each income level, the estimates
were for husband-wife families with two
children. The younger child was in one
of six age categories: 0-2, 3-5, 6-8, 9-11,
12-14, and 15-17. Households with four
members (two children) were selected
as the standard because in 1990-92 this
was the average household size of two­parent
families. The focus was on the
younger child in a household because
the older child was sometimes over
age 17.
The estimates are based on CE Inter­views
of households with and without
specific expenses; so for some families,
expenditures may be higher or lower
than the mean estimates, depending on
whether they incur the expense. This
applies particularly to child care and
education for which about 50 percent
of families in the study had no expendi­ture.
Also, the estimates cover out-of­pocket
expenditures on children made
by the parents only and not by others,
such as grandparents or friends. For
example, the value of clothing gifts to
children from grandparents would not
be included in clothing expenses.
Regional income categories were based
on the national income categories in
1992 dollars that were updated to 2000
dollars by using regional CPI' s. The
regional income categories were not
divided into equal thirds for each
region as was done for the overall
United States.
After the various overall household
and child-specific expenditures were
estimated, these total amounts were
allocated among the four family
members (husband, wife, older child,
and younger child). The estimated
expenditures for clothing and child
care and education were for children
only. It was assumed that these
expenses were allocated equally to
each child; therefore, the estimated
2002 Vol.l4No.l
expenditures were divided by two (the
number of children in the household).
Because the CE did not collect expendi­tures
on food and health care by family
member, data from other Federal studies
were used to apportion these budgetary
components to chiklr~!1 by age. Shares
of the food budget as a percentage
of total food expenditures-for the
younger child in a husband-wife
household with two children-were
determined by using the 1994 USDA
food plans (U.S. IieJ:.-~:-'111ent of Agricul­ture,
1994 ). These shares were esti­mated
by age of the child and house­hold
income level. The food budget
shares were then applied to estimated
household food expenditures to
determine food expenses on children.
Shares of the health care budget as
a percentage of total health care
expenses for the younger child in a
husband-wife household with two
children were calculated from the 1987
National Medical Expenditure Survey
(Lefkowitz & Monheit, 1991). These
shares were estimated by age of the
child and applied to estimated house­hold
health care expenditures to
determine expenses on children.
No research base exists for allocating
estimated household expenditures on
housing, transportation, and miscella­neous
goods and services among
household members. The marginal cost
method and the per capita method are
two of the most common approaches
for allocating these expenses.
The marginal cost method measures
expenditures on children as the
difference in expenses between couples
with children and equivalent childless
couples. This method depends on
development of an equivalency
measure; however, there is no univer­sally
accepted measure. Proposed
methods have produced different
estimates of expenditures on children.4
Some of the marginal cost approaches
assume that parents or couples do not
alter expenditures on themselves after
a child is added to a household. Also,
couples without children often buy
larger-than-needed homes at the time
of purchase in anticipation of children.
Comparing the expenditures of childless
couples with expenditures of similar
couples that have children could lead
to underestimated expenditures on
children. Lastly, the marginal cost
method does not provide a direct
estimate of how much is spent on a
child. It estimates how much money
families with children must be compen­sated
to bring the parents to the same
utility level (as gauged by an equiva­lence
scale) of couples without chil­dren.
This is a different question from
"how much do parents spend on
children?"
For these reasons, the USDA uses the
per capita method to allocate housing,
transportation, and miscellaneous
goods and services among household
members. The per capita method
allocates expenses among household
members in equal proportions. Al­though
the per capita method has
limitations, these limitations were
considered less severe than those
of the marginal cost approach.
A major limitation of the per capita
method is that expenditures for an
additional child may be less than
average expenditures. Consequently,
for households of different sizes,
4For a review of equivalency measures and
estimates of expenditures on children
resulting from them, see U.S. Department
of Health and Human Services, Office of
the Assistant Secretary for Planning and
Evaluation, 1990, Estimates of Expenditures
on. Children and Child Support Guidelines
(U.S. Department of Health and Human
Service , 1990).
27
adjustment formulas were devised to
estimate expenditures on one child or
three or more children. These formulas
are discussed later in the paper.
Transportation expenses resulting
from employment activities are not
related to expenses on children, so
these costs were excluded from the
estimated household transportation
expenses. Data used to estimate work­related
transportation expenses were
from a 1990 study by the U.S. Depart­ment
of Transportation ( 1994 ).
Although the USDA uses the per
capita approach rather than a marginal
cost approach in allocating housing,
transportation, and miscellaneous
expenditures to chi ldren in a household,
a USDA study examined how these
expenses would be allocated using
different marginal cost approaches
(Lino & Johnson, 1995). These marginal
cost approaches produced estimates
of expenditures on children for housing
and miscellaneous goods and services
below those produced by the per capita
method. In addition, these approaches
produced estimates of transportation
expenditures on children above those
produced by the per capita method.
Estimated Expenditures on
Children by Husband-Wife
Households
Estimates of family expenditures on the
younger child in husband-wife house­holds
with two children are presented
in tables 2 through 7 on pp. 36-41. The
estimates are for the overall United
States, urban regions, and overall rural
areas. Household income levels were
updated to 2000 dollars by using the
all-items category of the CPI-U, and
expenditures were updated by using
the CPI for the corresponding item
(i.e., the CPI's for housing, food, etc.).
Regional estimates were updated to
28
Figure 1. Estimated 2000 annual family expenditures on a child, by before-tax income
level and age of child1
16,000
14,000
12,000
10,000
~
!Jl 0 8,000
0
6,000
4,000
2,000
0
0-2 3-5 6-8 9-11 12-14 15-17
Age of child
Less than $38,000 • $38,000 - $64,000 • More than $64,000
1U.S. average for the younger child in husband-wife families with children.
2000 dollars by using the regional
CPI's. The following subsections
highlight the child-rearing expense
estimates for the younger child in a
two-child household for the overall
United States by income level, budget­ary
component, and age of the child.
Child-rearing expenses by region are
also discussed.
Income Level
Estimated expenses on children vary
considerably by household income
level (fig. 1). Depending on age of the
child, the annual expenses range from
$6,280 to $7,380 for families in the
lowest income group (2000 before-tax
income less than $38,000), from $8,740
to $9,860 for families in the middle­income
group (2000 before-tax income
between $38,000 and $64,000), and from
$13,000to $14,260 for families in the
highest income group (2000 before-tax
income more than $64,000). On average,
households in the lowest group spend
28 percent of their before-tax income
per year on a chi ld; those in the middle­income
group, 18 percent; and those in
the highest income group, 14 percent.
The range in these percentages would
be narrower if after -tax income were
considered, because a greater percent­age
of income in higher income house­holds
goes toward taxes.
Although families in the highest income
group spend, on average, slightly less
than twice the amount on a child than
that spent by families in the lowest
income group, the amount varies by
budgetary component. In general,
expenses on a child for goods and
services considered to be necessities
(e.g., food and clothing) do not vary
as much as those considered to be
discretionary (e.g., miscellaneous
expenses) among households in the
three income groups. For example,
clothing expenses on a child age 15-17
average $670 in the lowest income
group and $1,020 in the highest income
group, a 52-percent difference. Miscel­laneous
expenses on a child of the same
age average $640 in the lowest income
group and $1,630 in the highest income
group, a !55-percent difference.
Family Economics and Nutrition Review
Budgetary Component
Housing accounts for the largest share
of total child-rearing expenses. The box
on p. 30 shows this for families in the
middle-income group. Based on an
average for the six age groups, housing
accounts for 33 to 36 percent of child­rearing
expenses for a child; the
percentage rises with income. Food is
the second largest average expense on
a child for families regardless of income
level. It accounts for 20 percent of
child-rearing expenses for a child in the
lowest income group, 18 perce11t in the
middle-income group, and 15 percent in
the highest income group. Transporta­tion,
the third largest child-rearing
expense, makes up 14 to 15 percent of
child-rearing expenses across income
levels.
Across the three income groups,
miscellaneous goods and services
(personal care items, entertainment,
and reading materials) is the fourth
largest expense on a child for families
(10 to 12 percent). For families, clothing
(excluding that received as gifts or
hand-me-downs) accounts for 6 to 8
percent of expenses on a child, child
care and education accounts for 8 to
11 percent, and health care accounts
for 6 to 7 percent of child-rearing
expenses across income groups.
Estimated expenditures for health care
include only out-of-pocket expenses
(including insmance premiums not paid
by an employer or other organization)
and not that portion covered by health
insmance.
Age of Child
Expenditures on a child are lower in
the younger age categories and higher
in the older age categories. Figure 2
depicts this for families in the middle­income
group. This held across income
groups and held even though housing
expenses, the highest child-rearing
expenditure, generally decline as the
2002 Vol. 14 No. 1
child ages. The decline in housing
expenses reflects diminishing interest
paid by homeowners over the life of a
mortgage. Payments on principal are
not considered part of housing costs in
the CE; they are deemed to be part of
savings.
For all three income groups, food,
transportation, clothing, and health
care expenses related to child-rearing
generally increase as the child ages.
Transportation expenses are highest for
a child age 15-1 7. when he or she would
start driving. Child care and education
expenses are highest for a child under
age 6. Most of this expense may be
attributable to child care at this age.
The estimated expense for child care
and education may seem low for those
with the expense. The estimates reflect
the average of households with and
without the expense.
Region
Child-rearing expenses in the regions
reflect patterns observed in the overall
United States: in each region, expenses
on a child increase with household
income level and, generally, with age of
the child (fig. 3). Overall child-rearing
expenses are highest in the urban West,
followed by the urban Northeast, and
urban South. Child-rearing expenses
are lowest in the urban Midwest and
rural areas. Much of the difference in
expenses on a child among regions is
related to housing costs. Total housing
expenses on a child are highest in the
urban West and urban Northeast and
lowest in rmal areas. However, child­rearing
transportation expenses are
highest for families in rural areas. This
likely reflects the longer traveling
distances and the lack of public
transportation in these areas.
Food is the second largest
average expense on a child for
families regardless of income
level.
29
Expenditures on Children Over Time
Since 1960 the U.S. Department of Agriculture has provided estimates of expenditures on children from birth through age
17. The original estimates were based on the 1960 Consumer Expenditure Survey. The figure that follows shows how these
expenditure estimates have changed from 1960 to 2000. Depicted are the average total expenditures on a child from birth
through age 17 in a middle-income, husband-wife family. Total expenses are in 2000 dollars (1960 expenses are adjusted
for inflation).
Expenses to raise a child through age 17 have increased in real terms, from$146,780 in 1960 to $165,630 in 2000. New
components of child-rearing costs, particularly child care, are among factors causing this increase. In 1960 child care
expenses were negligible, because many mothers were not in the labor force. In 2000 child care expenses were among
the largest expenditures made on preschool children by middle-income fanlilies.
Expenditures on a child through age 17 by middle-income, husband-wife families
1960
Health care
Clothing
Child care and education
1%
2000
Transportation
Child care and education
Total expenses= $146,780 (in 2000 dollars) Total expenses= $165,630
Adjustments for Older
Children and Household
Size
The expense estimates on a child
represent expenditures on the younger
child at various ages in a husband-wife
household with two children. It cannot
be assumed that expenses on the older
child are the same at these various
ages. Expenses may vary by birth order.
The method described on pp. 26-28
was repeated to determine whether
30
a difference exists, the extent of this
difference, and bow the expenditures
may be adjusted to estimate expenses
on an older child. The focus was on
the older child in each of the same
age categories as those used with the
younger child. A two-child fami ly was
again used as the standard. Household
income and U.S. region of residence
were not held constant, so findings
are applicable to all families.
On average, for husband-wife bouse­holds
with two children, expenditures
do not vary by birth order. So, the
expenditures in tables 2 through 7
reflect those on either child in a two­child
family. Thus, annual expenditures
on children in a husband-wife, two­child
fami ly may be estimated by
summing the expenses for the two
appropriate age categories. For example,
annual expenditures on children ages
9-11 and 15-17 in a husband-wifefamily
in the middle-income group for the
overall United States would be $18,810
($8,950 + $9,860). For specific budgetary
components, annual expenses on an
older child vary, compared with those
on a younger child: families spend more
Family Economics and Nutrition Review
Figure 2. Estimated 2000 annual family expenditures on a child,1 by age and
budgetary share
100
80
c Q)
2
Q)
[l_ 40
20
0
0-2 3-5 6-8 9-11 12-14 15-17
Age of child
Miscellaneous
Child care and education
Clothing
Health care
Transportation
Food
Housing
1U.S. average for the younger child in middle-income, husband-wife families with two children.
Figure 3. Estimated 2000 annual family expenditures on a child, 1 by region and age
11,000
10,500
10,000
~
.!!! 0 9,500
0
9,000
8,500
8,000
0-2 3-5 6-8 9-11
Age of child
• Urban Midwest • Urban South
· - • Rural Urban Northeast
.,...-·-· -·-·
12-14 15-17
Urban West
1 Regional average for the younger child in middle-income, husband-wife families wilh two children.
2002 Vol. 14No.l
on clothing and education for an older
child but less on transportation.
The estimates should also be adjusted
if a household has only one child or
more than two children. Families will
spend more or less on a child depend­ing
on the number of other children in
the household and economies of scale.
Multivariate analysis was used to
estimate expenditures for each budget­ary
component to derive these figures.
Household size and age of the younger
child were controlled; household
income level and region of the country
were not. The results, therefore, are
applicable to all families. These expendi­tures
were then assigned to a child by
using the method described earlier.
Compared with expenditures for each
child in a husband-wife, two-child
family, expenditures for the child in a
one-child family average 24 percent
more and for those with three or more
children, 23 percent less on each child.
To adjust the figures in tables 2
through 7 to estimate annual overall
expenditures on an only child, users
of this report should, therefore, add
24 percent to the total expense for the
child's age category. To estimate
expenditures on three or more children,
users should subtract 23 percent from
the total expense for each child's age
category and then sum the totals. An
example of adjustments needed for
different number of children follows.
The total expenses for a middle-income
family in the overall United States on a
child age 15-17 with no siblings would
be $12,230 ($9,860 x 1.24) and the total
expenses on three children ages 3-5, 12-
14, and 15-17 would be $21,970 ([$8,980
+ $9,690 + $9 ,860] x. 77). For a particular
budgetary component, the percentages
may be more or less. As family size
increases, food costs per child decrease
less than housing and transportation
costs per child decrease.
31
Single-parent families in this
lower income group, therefore,
spend a larger proportion of
their income on children than
do two-parent families.
32
Expenditures by
Single-Parent Families
The estimates of expenditures on
children by husband-wife families do
not apply to single-parent families, a
group that accounts for an increasing
percentage of families with children.
Therefore, separate estimates of child­rearing
expenses in single-parent
households were made by using the
CE data. Most single-parent families
in the survey (90 percent) were headed
by a woman.
The method used in determining
child-rearing expenses for two-parent
households was followed. Multivariate
analysis was used to estimate expendi­tures
for each budgetary component.
Control variables were income level,
household size, and age of the younger
child (the same age categories as those
used with children in two-parent
families). A single parent with two
children was used as the standard
for household size.
Income groups of single-parent
households (before-tax income under
$31,000 and $31,000 and over in 1992
dollars, inflated to 2000 dollars) were
selected to correspond with the income
groups used in estimating child-rearing
expenditures in husband-wife house­holds.
This income includes child
support payments. The two higher
income groups of two-parent families
(income between $31,000 and $52,160
and over $52,160 in 1992 dollars) were
combined because only 17 percent of
single-parent households had a before­tax
income of $31 ,000 and over. The
sample was weighted to reflect the U.S.
population of interest.
Children's clothing and child care and
education expenditures were divided
between the two children in the one­parent
household. For food and health
care, household member shares were
calculated for a three-member house­hold
(single parent and two children,
with the younger child in one of the six
age categories). The USDA food plans
and the 1987 National Medical Expendi­ture
Survey were used to do this. These
shares for the younger child in a single­parent
family were then applied to
estimated food and health care expendi­tures
to determine expenses on the
younger child in each age category.
Housing, transportation, and miscella­neous
expenditures were allocated
among household members on a per
capita basis. Transportation expenses
were adjusted to account for nonem­ployment-
related activities in single­parent
families. Income and expenses
were updated to 2000 dollars.
Child-rearing expense estimates for
single-parent families are in table 8,
p. 42. For the lower income group (2000
before-tax income less than $38,000), a
comparison is presented in table 1 of
estimated expenditures on the younger
child in a single-parent family with two
children versus expenditures on the
younger child in a husband-wife family
with two children. As discussed earlier,
83 percent of single-parent families and
33 percent of husband-wife families
were in this lower income group. More
single-parent than husband-wife
families were in the bottom range of
this lower income group. Average
income for single-parent families in
the lower income group is $15,900;
for husband-wife families it is $23,800.
However, total expenditures on a child
through age 17 are, on average, only 5
percent lower in single-parent house­holds
than in two-parent households.
Single-parent families in this lower
income group, therefore, spend a larger
proportion of their income on children
than do two-parent families. On
average, housing expenses are higher;
Family Economics and Nutrition Review
Table 1. Comparison of estimated 2000 expenditures on a child1 by lower income
single-parent and husband-wife families
Single-parent Husband-wife
Age of child households households
0-2 $5,270 $6,280
3-5 5,950 6,420
6-8 6,710 6,520
9 - 11 6,260 6,530
12 -14 6,730 7,380
15-17 7,460 7,280
Totai(0-17) $115,140 $121 ,230
1 Estimates are for the younger child in two-child families in the overall Un~ed States with 2000 before-tax
income less than $38,000.
whereas, transportation, health care,
child care and education, and miscella­neous
expenditures on a child are lower
in single-parent than in husband-wife
households. Child-related food and
clothing expenditures are similar, on
average, in single- and two-parent
families.
For the higher income group of single­parent
families (2000 before-tax income
of$38,000 and over), child-rearing
expense estimates are about the same
as those for two-parent households
in the before-tax income group of
$64,000 and over. Total expenses, in
2000 dollars, for the younger child
through age 17 are$242,910for single­parent
families versus $241,770 for
husband-wife families. Child-rearing
expenses for the higher income group
of single-parent families, therefore, also
are a larger proportion of income than
they are in husband-wife families. Thus,
expenditures on children do not differ
much between single-parent and
husband-wife households. What differs
is household income levels. Because
single-parent families have one less
potential earner than do husband-wife
families, on average, their total house­hold
income is lower, and child-rearing
expenses are a greater percentage of
this income.
2002 Yol.l4No. I
Estimates cover only out-of-pocket
child-rearing expenditures made by
the parent with primary care of the
child and do not include child-related
expenditures made by the parent
without primary care or made by others,
such as grandparents. Such expendi­tures
could not be estimated from the
data. Overall expenses by both parents
on a child in a single-parent household
are likely greater than estimates of this
study.
The procedure detailed earlier was
repeated to determine the extent of the
difference in expenditures on an older
child in single-parent households. The
focus was on the older child, and a
family with two children was used as
the standard. On average, single-parent
households with two children spend
7 percent less on the older child than
on the younger child (in addition to
age-related differences). This contrasts
with husband-wife households whose
expenditures are unaffected by birth
order.
As with husband-wife households,
single-parent households spend more
or less if there is only one child or three
or more children. Multivariate analysis
was used to estimate expenditures for
each budgetary component to deter­mine
these differences. Household size
and age of the younger child were
control variables. Expenditures were
then assigned to a child by using the
method described earlier. Compared
with expenditures for the younger child
in a single-parent, two-child family,
expenditures for an only child in a
single-parent household average 35
percent more, and expenditures for
three or more children in a single-parent
household average 28 percent less on
each child.
Other Expenditures on
Children
Expenditures on a child that were
estimated in this study consist of
direct parental expenses made on a
child through age 17 for seven major
budgetary components. These direct
expenditures exclude costs related to
childbirth and prenatal health care. In
1996 these particular health care costs
averaged $7,090 for a normal deli very
and $11,450 for a Cesarean delivery
(Mushinski, 1998). These costs may
be reduced by health insurance.
One of the largest expenses made on
children after age 17 is the cost of a
college education. The College Board
(2000) estimates that in 2000-2001,
average annual tuition and fees are
$3,420 at 4-year public colleges and
$13,688 at4-yearprivate colleges.
Annual room and board is $4,705 at
4-year public colleges and $5,447 at
4-year private colleges. For 2-year
colleges in 2000-2001, average annual
tuition and fees are $1,655 at public
colleges and $8,210 at private colleges.
Annual room and board is $4,685 at
2-year private colleges. No estimates
of room and board are given for 2-year
public colleges. Other parental ex­penses
on children after age 17 include
those associated with children living at
home, or if children do not live at home,
gifts and other contributions to them.
33
Estimating Future Costs
The estimates presented in this study represent household expenditures on a child of a certain age in 2000. To estimate
these expenses for the first 17 years, we need to incorporate future price changes in the figures. To do this, we use a future
cost formula, such that:
where:
Cf = projected future annual dollar expenditure on a child of a particular age
CP = present (2000) annual dollar expenditure on a child of a particular age
i = projected annual inflation (or deflation)
n =number of years from present until child will reach a particular age
An example is presented of estimated Estimated annual expenditures on children 1 born in 2000, by income group,
future expenditures on the younger overall United States
child in a husband-wife family with
two children for each of the three Income grouQ
income groups for the overall United Year Age Lowest Middle Highest
States. The example assumes a child
is born in 2000 and reaches age 17 2CXXl <1 $6,280 $8,740 $13,000
in the year 2017. The example also 2001 6,520 9,070 13,490
assumes that the average annual 2002 2 6,770 9,420 14,010
inflation rate over this time is 3.8 2003 3 7,180 10,040 14,850
percent, the average annual inflation
2004 4 7,450 10,420 15,420
rate over the past 20 years (U.S.
Department of Commerce, 2000). 20li 5 7,740 10,820 16,000
Thus total family expenses on a child 20)3 6 8,160 11,240 16,460
through age 17 would be $171,460, 2007 7 8,470 11,670 17,090
$233,530, and $340,130 for households 2COO 8 8,790 12,120 17,740
in the lowest, middle, and highest
2rol 9 9,130 12,520 18,210
income groups, respectively. In 2000
dollars, these figures would be 2010 10 9,480 13,000 18,910
$121,230,$165,630, and $241,770. 2011 11 9,840 13,490 19,620
2012 12 11,550 15,160 21,700
Inflation rates other than 3.8 percent 2013 13 11 ,980 15,740 22,520
could be used in the formula if projec-
2014 14 12,440 16,330 23,380
tions of these rates vary in the future.
Also, it is somewhat unrealistic to 2015 15 12,740 17,250 24,950
assume that households remain in 2016 16 13,220 17,910 25,900
one income category as a child ages. 2017 17 13,720 18,590 26,880
For most families, income rises over Total
time. In addition, such projections
$171,460 $233,530 $340,130
assume child-rearing expenditures
1 change only with inflation, but Estimates are for the younger child in husband·wife families with two children.
parental expenditure patterns also
change over time.
34 Family Economics and Nutrition Review
The estimates do not include all
government expenditures on children.
Examples of excluded expenses are
public education, Medicaid, and school
meals. The actual expenditures on
children (by parents and the govern­ment)
would be higher than reported
in this study, especially for the lowest
income group.
Indirect child-rearing costs are also not
included in the estimates. Although
these costs are typically more difficult
to measure than are direct expenditures,
they can be substantial. The time
involved in rearing children is consider­able.
In addition, one or both parents
may need to reduce hours spent in the
labor force to care for children, thus
reducing current earnings and future
career opportunities. The indirect costs
of child rearing may exceed the direct
costs. For more on these indirect costs,
see Bryant, Zick, and Kim (1992);
Ireland and Ward (1995); Longman
(1998); and Spalter-Roth and Hartmann
(1990).
2002 Voi.14No.1
References
Bryant, W.K., Zick, C.D., & Kim, H. (1992). The Dollar Value of Household Work.
College of Human Ecology, Ithaca, NY: Cornell University.
The College Board. (2000). Trends in College Pricing 2000. Retrieved March 2001
from www .collegeboard.org.
Ireland, T.R., & Ward, J.O. (1995). Valuing Children in Litigation: Family
and Individual Loss Assessment. Tucson, AZ: Lawyers and Judges Publishing
Company, Inc.
Lefkowitz, D., & Monheit, A. ( 1991 ). Health Insurance, Use of Health Services, and
Health Care Expenditures. National Medical Expenditure Survey Research
Findings 12. Publication No. 92-0017. U.S. Department of Health and Human
Services, Public Health Service, Agency for Health Care Policy and Research.
Lino, M., & Johnson, D.S. ( 1995). Housing, transportation, and miscellaneous
expenditures on children: A comparison of methodologies. Family Economics
Review 8( 1 ):2-12.
Longman, P.J. (1998, March 30). The Cost of Children. U.S. News & World Report
124( 12):50-58.
Mushinski, M. (1998). Average charges for uncomplicated vaginal, Cesarean and
VBAC deliveries: Regional variations, United States, 1996. Statistical Bulletin
79(3):17-28.
Spalter-Roth, R.M. , & Hartmann, H.l. (1990). Unnecessary Losses: Costs to Ameri­cans
of the Lack of Family and Medical Leave. Washington, DC: Institute for
Women's Policy Research.
U.S. Department of Agriculture, Agricultural Research Service. (1994 ). Cost of food
at home. Family Economics Review 7(4):45 .
U.S. Department of Commerce, Bureau of the Census. (2000). Statistical Abstract of
the United States, 2000. [120th ed.].
U.S. Department of Health and Human Services, Office of the Assistant Secretary
for Planning and Evaluation. (1990). Estimates of Expenditures on Children and
Child Support Guidelines.
U.S . Department of Transportation, Federal Highway Administration. ( 1994 ). I 990
Nationwide Personal Transportation Study.
35
Table 2. Estimated annual expenditures* on a child by husband-wife families, overall United States, 2000
Child care
Transpor- Health and Miscel-
Age of Child Total Housing Food tation Clothing care education laneoust
Before-tax income: Less than $38,000 (Average=$23,800)
0-2 $6,280 $2,400 $880 $770 $380 $440 $800 $610
3-5 6,420 2,370 980 750 370 420 900 630
6-8 6,520 2,290 1,260 870 410 490 530 670
9- 11 6,530 2,070 1,510 950 450 530 320 700
12- 14 7,380 2,310 1,590 1,070 760 540 230 880
15 - 17 7,280 1,860 1,720 1,440 670 570 380 640
Total $121,230 $39,900 $23,820 $17,550 $9,120 $8,970 $9,480 $12,390
Before-tax income: $38,000 to $64,000 (Average=$50,600)
0-2 $8,740 $3,250 $1,060 $1 '150 $440 $580 $1,310 $950
3-5 8,980 3,220 1,220 1 '130 430 560 1,450 970
6-8 8,990 3,140 1,550 1,250 480 630 930 1,010
9 - 11 8,950 2,920 1,830 1,330 530 690 610 1,040
12 - 14 9,690 3,150 1,840 1,450 890 690 450 1,220
15 - 17 9,860 2,710 2,050 1,830 790 730 770 980
Total $165,630 $55,170 $28,650 $24,420 $10,680 $11 ,640 $16,560 $18,510
Before-tax income: More than $64,000 (Average=$95,800)
0-2 $13,000 $5,160 $1,400 $1 ,610 $580 $670 $1,980 $1,600
3-5 13,280 5,1 30 1,580 1,590 570 640 2,160 1,610
6-8 13,160 5,050 1,910 1,710 620 730 1,490 1,650
9- 11 13,020 4,830 2,220 1,790 680 790 1,030 1,680
12 - 14 13,870 5,070 2,330 1,910 1 '120 790 790 1,860
15 - 17 14,260 4,620 2,450 2,310 1,020 840 1,390 1,630
Total $241,770 $89,580 $35,670 $32,760 $13,770 $13,380 $26,520 $30,090
*Estimates are based on 1990-92 Consumer Expenditure Survey data updated to 2000 dollars using the Consumer Price Index. For each
age category, the expense estimates represent average child-rearing expenditures for each age (e.g., the expense for the 3-5 age
category, on average, applies to the 3-year-old, the 4-year-old, or the 5-year-old). The figures represent estimated expenses on the
younger child in a two-child family. Estimates are about the same for the older child, so to calculate expenses for two children, figures
should be summed for the appropriate age categories. To estimate expenses for an only child, multiply the total expense for the
appropriate age category by 1.24. To estimate expenses for each child in a family with three or more children, multiply the total expense
for each appropriate age category by 0.77. For expenses on all children in a family, these totals should be summed.
tMiscellaneous expenses include personal care items, entertainment, and reading materials.
36 Family Economics and Nutrition Review
Table 3. Estimated annual expenditures* on a child by husband-wife families, urban West,t 2000
Child care
Transpor- Health and Miscel-
Age of Child Total Housing Food tation Clothing care education laneousl=
Before-tax income: Less than $38,200 (Average=$23,800)
0-2 $7,000 $2,930 $970 $850 $360 $380 $790 $720
3-5 7,160 2,910 1,080 830 350 360 890 740
6-8 7,300 2,870 1,380 940 390 410 530 780
9 - 11 7,400 2,71 0 1,660 1,010 440 440 320 820
12 - 14 8,200 2,910 1,730 1 '140 740 460 230 990
15 - 17 8,150 2,500 1,870 1,510 650 480 380 760
Total $135,630 $50,490 $26,070 $18,840 $8,790 $7,590 $9,420 $14,430
Before-tax income: $38,200 to $64,200 (Average=$50,800)
0-2 $9,470 $3,770 $1 '140 $1 ,240 $430 $510 $1,320 $1,060
3-5 9,730 3,750 1,310 1,220 420 490 1,460 1,080
6-8 9,770 3,71 0 1,670 1,330 460 550 930 1,120
9- 11 9,810 3,550 1,970 1,410 510 600 610 1 '160
12 - 14 10,520 3,750 1,980 1,540 860 610 450 1,330
15 - 17 10,730 3,340 2,200 1,920 770 630 770 1 '100
Total $180,090 $65,610 $30,810 $25,980 $10,350 $10,170 $16,620 $20,550
Before-tax income: More than $64,200 (Average=$96,100)
0-2 $13,600 $5,580 $1,470 $1,710 $560 $600 $1,990 $1,690
3-5 13,910 5,560 1,660 1,690 550 570 2,170 1,710
6-8 13,810 5,520 2,000 1,800 600 650 1,490 1,750
9 - 11 13,760 5,360 2,340 1,870 660 700 1,040 1,790
12 - 14 14,550 5,550 2,440 2,000 1,080 710 810 1,960
15 - 17 14,980 5,140 2,580 2,400 980 740 1,410 1,730
Total $253,830 $98,130 $37,470 $34,410 $13,290 $11,910 $26,730 $31,890
*Estimates are based on 1990-92 Consumer Expenditure Survey data updated to 2000 dollars using the regional Consumer Price Index.
For each age category, the expense estimates represent average child-rearing expenditures for each age (e.g., the expense for the
3-5 age category, on average, applies to the 3-year-old, the 4-year-old, or the 5-year-old). The figures represent estimated expenses
on the younger child in a two-child family. Estimates are about the same for the older child, so to calculate expenses for two children,
figures should be summed for the appropriate age categories. To estimate expenses for an only child, multiply the total expense for the
appropriate age category by 1.24. To estimate expenses for each child in a family with three or more children, multiply the total expense
for each appropriate age category by 0.77. For expenses on all children in a family, these totals should be summed.
tThe Western region consists of Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah,
Washington, and Wyoming.
l=Miscellaneous expenses include personal care items, entertainment, and reading materials.
2002 Voi.14No.1 37
Table 4. Estimated annual expenditures* on a child by husband-wife families, urban Northeast,t 2000
Child care
Transpor- Health and Miscel-
Age of Child Total Housing Food tation Clothing care education laneous:l:
Before-tax income: Less than $37,800 (Average=$23,600)
0-2 $6,570 $2,860 $980 $640 $400 $430 $660 $600
3-5 6,700 2,840 1,080 610 390 410 750 620
6-8 6,910 2,800 1,390 720 440 470 430 660
9- 11 7,050 2,640 1,660 800 490 510 250 700
12 - 14 7,920 2,840 1,740 930 830 520 180 880
15 - 17 7,800 2,440 1,870 1,280 730 550 290 640
Total $128,850 $49,260 $26,160 $14,940 $9,840 $8,670 $7,680 $12,300
Before-tax income: $37,800 to $63,500 (Average=$50,200)
0-2 $8,990 $3,680 $1 '1 50 $1 ,030 $480 $580 $1 '120 $950
3-5 9,200 3,660 1,310 1,000 460 550 1,250 970
6-8 9,330 3,620 1,670 1 '120 510 630 780 1,000
9- 11 9,400 3,460 1,970 1 '190 570 670 500 1,040
12 - 14 10,190 3,660 1,970 1,320 970 690 360 1,220
15 - 17 10,330 3,260 2,190 1,690 860 720 620 990
Total $172,320 $64,020 $30,780 $22,050 $11 ,550 $11 ,520 $13,890 $18,510
Before-tax income: More than $63,500 (Average=$95,100)
0-2 $13,010 $5,440 $1 ,470 $1,490 $610 $670 $1,750 $1,580
3-5 13,310 5,430 1,650 1,470 600 650 1,910 1,600
6-8 13,290 5,390 1,990 1,580 660 740 1,290 1,640
9- 11 13,250 5,230 2,320 1,650 720 780 870 1,680
12 - 14 14,160 5,420 2,430 1,780 1,200 800 670 1,860
15 - 17 14,450 5,020 2,550 2,170 1,090 830 1 '160 1,630
Total $244,410 $95,790 $37,230 $30,420 $14,640 $13,410 $22,950 $29,970
*Estimates are based on 1990-92 Consumer Expenditure Survey data updated to 2000 dollars using the regional Consumer Price Index.
For each age category, the expense estimates represent average child-rearing expenditures for each age (e.g., the expense for the
3-5 age category, on average, applies to