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DIETARY QUALITY AND DIETARY CHANGES OF EFNEP PARTICIPANTS:
1994-95 MICHIGAN STUDY

BY

LiFan W. Koerner

A THESIS

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

MASTER OF SCIENCE

Department of Food Science and Human Nutrition

1997

ABSTRACT

DIETARY QUALITY AND DIETARY CHANGES OF EFNEP PARTICIPANTS:
1994-95 MICHIGAN STUDY

BY

LiFan W. Koerner

The central focus of this study was to assess the
dietary quality of 1994—95 Michigan EFNEP participants at
the time of entry (cross-section data, n=3866), and their
dietary changes upon the completion of the program
(longitudinal data, n=2454). Majority of subjects’ diets
(59%) were classified at the time of entry as low dietary
quality (i.e., not including at least one serving from each
of the five major food groups, and deriving more than 30%
daily energy intake from fat). The low dietary quality was
associated with high intake of added fats and sugar and low
frequency of meal/snack consumption. Subjects whose diets
were classified as low dietary quality at the entry made two
positive dietary changes: increased consumption of five
major food groups and reduced percent of energy from fat.
Michigan EFNEP can further enhance its effectiveness in
improving dietary intake of its participants by targeting at

subjects with low quality diets.

ACKNOWLEDGMENT S

First of all, I would like to thank Dr. Won Song, my
academic advisor, for her encouragement and guidance
throughout my graduate program. I want to especially thank
her for her valuable comments, suggestions, and detailed
criticism of my thesis. I also want to extend a very special
thank to my guidance committee members: Dr. Wanda Chenoweth,
Dr. Sharon Hoerr, Dr. Bruce Haas, and Barbara Mutch. They
each have contributed so much in a unique way to my present
research. Many thanks are also offered to the Michigan EFNEP
program leaders for their cooperation, assistance, and
interest. They are Dr. Amy Slonim, Gayle Coleman, Lynn
Himebauch, and Karen Martin. Thanks also to my lab mates,
Yali Huang, Prodromou Prodromos, Janet Lawrence, Saori
Obayashi, and Viviane Oyarzun for their friendship and
support. Most important, my deepest gratitude goes to my
dearest husband, Kenneth, and my mother, Luo Ning, for their

support, understanding, and emphasis on hard work.

iii

TABLE OF CONTENTS

LIST OF TABLE ............................................. Vi

CHAPTER ONE

INTRODUCTION
Introduction .......................................... 1
A statement of the problem .............................. 3
Objectives ........................................... 7
Hypotheses ............................................ 8
Significance of the study .............................. 9
Working definitions of the terms ..................... 10

CHAPTER TWO
RELATED LITERATURE

EFNEP evaluation studies ............................. 13
Description of EFNEP participants .................... 16
Dietary adequacy of EFNEP participants ................. 18
Dietary changes of EFNEP participants

and associated factors ............................... 27
Indices of overall dietary quality ................... 30
Dietary assessment methods used by EFNEP ............. 34

CHAPTER THREE

METHODOLOGY
Research design ...................................... 40
Subjects ............................................. 40
Data collection ...................................... 45
Foods database ....................................... 46
Data processing ...................................... 49
Statistical analyses ................................. 54

iv

CHAPTER FOUR

RESULTS
Subjects ............................................. 62
Factors differentiating the EFNEP
dropouts from the graduates .......................... 64
Meal and food intake patterns of EFNEP participants
at the time of entry ................................. 68
Overall dietary quality of EFNEP participants
at the time of entry ................................. 80
Factors associated with low dietary quality ......... 87
Dietary changes by the EFNEP graduates ................ 93

CHAPTER FIVE
DISCUSSION, CONCLUSION AND IMPLICATION

Discussion ........................................... 98
Conclusion ........................................... 110
Assumptions .......................................... 112
limitations .................. , ........................ 112
Strengths ........................................... 113
Implications for future management ................... 114
Recommendations for future study ..................... 116

REFERENCE MATERIALS

Appendices
Appendix A. Summary of adult participant
profiles ............................. 118
Appendix B. Diet summary report .................. 125
Appendix C. Distribution of Michigan EFNEP
counties 1994-95 ..................... 135
Appendix D. List of EFNEP curriculum content ..... 136
Appendix E. UCRIHS approval ...................... 137
Appendix F. Adult family record .................. 138
Appendix G. 24-hour food recall .................. 139
Appendix H. Print outs of three ERS
raw data files (Adult.dbf,
Recall.dbf and meals.dbf) ............ 140
The Bibliography ................. . ....................... 154

LI ST OF TABLES

Table 1. Previous Studies of dietary changes
and associated factors in EFNEP population ...... 14

Table 2. 1994-95 ERS raw data received from
16 Michigan EFNEP counties ...................... 43

Table 3. Procedure for exclusion of cases from
1994-95 EFNEP database .......................... 44

Table 4. Two levels of recommended number of servings
for the five major food groups ................... 53

Table 5. Baseline characteristics of all subjects,
graduates, and dropouts ......................... 63

Table 6. Programmatic factors for 12 Michigan
EFNEP counties, 1994-95 ......................... 66

Table 7. Percent of graduates and percent of dropouts
classified into four dietary quality groups

based on entry 24-hour food recalls ............. 67

Table 8. Top 20 contributors of five major food groups
and “other” food group .......................... 70

Table 9. Top 20 contributors of five micro-nutrients
by food groups and food items ................... 75

Table 10. Top 20 contributors of dietary fiber
by food groups and food items ................... 79

Table 11. Daily intake (in servings) of five major
food groups by the subjects

vi

Table

Table

Table

Table

Table

Table

Table

12.

13.

14.

15.

16.

17.

18.

at the time of entry (n=3866) ................... 81

Daily intake of macro—nutrients by
pregnant/nursing subjects,
young female subjects,

and adult female subjects ........................ 82

Daily intake of micro-nutrients by
pregnant/nursing subjects
young female subjects,

and adult female subjects ........................ 83

Mean MAR-5 score, and Odds Ratios of
having MAR-5 < 75 by

four dietary quality groups ..................... 85

Adjusted Odds Ratios
and 95% confidence intervals

of factors associated with low dietary quality..

Percentage of graduates
classified into four dietary quality groups

at the time of entry and exit (n=2454) ...........

Average food group scores,
food group servings, percent energy from fat,
and energy intake for graduates

by four dietary quality groups (n=2454) ........

Dietary changes (meaniSD) of EFNEP graduates

among four dietary quality groups ..............

vii

.90

.93

.95

.97

Chapter One

INTRODUCTION

Introduction

The Expanded Food and Nutrition Education Program
(EFNEP) was initiated by USDA in 1968. The fundamental
objective of EFNEP is to provide nutrition education for
low-income people to improve the adequacy of their daily
diets and gain maximum nutritional benefits from their food
resources. Low-income homemakers with young children are
particularly targeted. The EFNEP employs indigenous
paraprofessionals to deliver its service. Rather than
providing food or food dollars like other food assistance
programs such as Food Stamps and the Supplemental Food
Program for Women, Infants, and Children (WIC), EFNEP
provides education to its participants about the importance
of good nutrition, knowledge about how to use available food
resources, and how to develop food related skills.

EFNEP is administered by the Cooperative State

2

Research, Education and Extension Service (CSREES), U.S.
Department of Agriculture. Currently, EFNEP is operated
through the Cooperative Extension System at land-grant
universities in all 50 states and 6 US territories (American
Samoa, Guam, Micronesia, Northern Marianas, Puerto Rico and
the Virgin Islands (USDA, 1994).

As an ongoing nutrition education program, EFNEP
requires continuous and careful evaluations to enhance the
efficacy of the program with the targeted audience and to
adjust the program accordingly. The EFNEP
Evaluation/Reporting System (ERS), a computerized dietary
assessment software, organizes information on demographics
and dietary intakes of the participants that are collected
by paraprofessionals during the educational program. ERS was
developed by World Computer Systems, Inc. (14405 Laurel
Place, Laurel Maryland 20707) under the contract with USDA.
It has been used since 1993 for reporting EFNEP's impact to
the USDA (ERS User's Guide). Previous reporting systems
used by EFNEP were software programs called EFNEP I and
EFNEP II (personal communication with Ingham county EFENP
staff). Currently, ERS is in use in all states and all US

territories except New York, South Carolina, the Virgin

Islands and Northern Marianas (personal communication with
Wells Willis, EFNEP national program leader, USDA). To our
best knowledge, no any other states or territories have used
the ERS raw data in an integrated fashion for comprehensive
program evaluation.

This research project was aimed at performing a
Michigan in-depth EFNEP evaluation. The goals of this study
are to provide an in-depth evaluation of the currently
offered program and also to identify sensitive and effective
tools to enhance the outreach and implementation of Michigan
EFNEP in the future, such as defining most needy audiences,
planning focused curriculum revision, and targeting

paraprofessional training.

A statement of the problem

Over and under consumption of foods and nutrients
persists among Americans. Results from USDA's 1994
Continuing Survey of Food Intakes by Individuals (CSFII)
show that average intakes of women (20 years of age and
older) are below Recommended Dietary Allowances (RDAs) for
iron, zinc, vitamin B6, calcium, magnesium, and vitamin E.

Further, CSFII 1994 indicated that U.S. women consume 32% of

4

calories from fat and 11% from saturated fat, and an average
of only 14 g of dietary fiber/day (Cleveland et al., 1997).
The National Cancer Institute recommends that people consume
20 to 30 g of dietary fiber daily. Data from USDA's 1989-90
CSFII show that Americans of basic income group (those
individuals in all households were eligible to be
interviewed) had inadequate intakes of vitamin B6, calcium,
and zinc. Intakes of these nutrients by low income group
(those with income at or below 130 percent of the poverty
thresholds during the previous month) were lower than those
by the basic income group. Both total fat and saturated fat
intake exceeded the amount recommended by the Dietary
Guidelines for Americans, with little difference by sex,
age, income, or race (Frazao, 1996).

One of USDA's main concerns is hard-to—reach or at risk
populations--those least likely to be aware of the diet-
health links or to have adequate nutrition knowledge. Adults
from low income families often experience social isolation
due to underemployment, unemployment, lack of
transportation, limited literacy, and lack of child care. In
turn, socially isolated families also tend to be isolated

from sources of information about nutrition, food selection,

5

preparation techniques, and menu planning (Conone, 1992).
For families with low incomes, the struggle to cope with
life’s everyday problems takes precedence over health
promotion and disease prevention. These families are often
at high risk for health problems arising from the abuse of
alcohol and tobacco, a lack of exercise, and a poor diet
(Singleton, 1994).

EFNEP is a food and nutrition intervention program
designed to help low income families with children improve
the adequacy of their daily diets through increased
knowledge and skills, thus limiting the occurrence of
undernourishment and chronic diseases in this population.
An on-going evaluation on EFNEP is needed to identify areas
for future program refinement and policy recommendations.
Since the inception of EFNEP in 1968, many situations have
changed, including demographic characteristics of EFNEP
participants, dietary standards, nutrition knowledge, health
concerns, EFNEP reporting methods, food composition and
availability in the market. Thus an current evaluation with
accurate knowledge on the current situation is necessary.

In 1968, EFNEP strove to reduce malnutrition and hunger

for families living in poverty in the United States. In

6

1979, a federally mandated evaluation of EFNEP reported that
many problems of actual hunger had abated. Compared to the
EFNEP participants almost three decades ago, many of today's
EFNEP participants are less isolated, more sophisticated and
better educated. Increasing numbers of the EFNEP
participants are also enrolled in other food assistant
programs such as the Food Stamp program, WIC and Headstart
(Chipman and Kendall, 1989).

The dietary standards used frequently for evaluation of
EFNEP in previous studies were the Basic Four Food Groups
and Recommended Dietary Allowances. The Food Guide Pyramid,
released by the USDA in 1992, incorporates three key dietary
concepts: variety, moderation, and proportionality. It is
utilized by EFNEP for teaching, but has not been integrated
into program evaluation. In the present study, we utilized
the basic concepts of the Food Guide Pyramid and the Dietary
Guidelines for Americans to evaluate each participant’s
overall dietary quality, and to assess the extent of their
overall dietary changes.

For each reporting period (a fiscal year, which begins
on September 1 of one year and ends on August 31 of the next

year), summary reports and raw data generated by ERS are

7

exported to diskettes at county level and state level. These
county and state-level summary reports contain only the
aggregate total on participants' information: demographic
characteristics (Appendix A: Summary of adult participant
profiles); and descriptive statistics of the dietary changes
between entry and exit of the program (Appendix B: Diet
summary report). Although the summary reports reveal
positive changes in intake of a few nutrients and food
groups made by the participants as a group, little is known
regarding specific dietary changes, who makes the changes,
and to what extent the changes are made.

In the present study, the ERS raw data files from 1994-
95 reporting period that were collected from 12 Michigan
EFNEP counties and compiled into a EFNEP database during the
summer of 1996. In-depth dietary evaluation were conducted
by using this EFNEP database to address the needs of the

current and dynamic situation.

Objectives

The specific objectives of this study were:
1. To identify factors differentiating the dropouts from

the graduates.

8

To describe meal and food intake patterns of Michigan
EFNEP participants at the time of entry.

To assess the overall quality of Michigan EFNEP
participants' diets at the time of entry.

To identify factors associated with low dietary quality
at the entry.

To determine whether initial dietary quality can

predict the dietary changes in Michigan EFNEP.

Hypotheses

Objectives one, two, and three were descriptive data

analyses with no hypotheses testing. Our hypotheses for

objectives four and five were stated as follows:

1)

2)

3)

Subjects with high intakes of added fats and sugar have
high risk of having diets with low dietary quality
(defined in Working definitions of the terms in Page
10).

Subjects who consume less than three meals/snacks per
day have high chance of having diets with low dietary
quality.

Initial dietary quality can predict the dietary changes

of Michigan EFNEP participants.

Significance of the study

EFNEP is designed to make desirable behavior changes
and skill development through educational activities.
Evaluation of EFNEP should quantify the degree of desirable
behavior changes and identify problematic areas, thus
providing the basis for decision making, program planning
and execution.

The significance of the study includes the following:
1. Explored meal and food intake patterns of Michigan

EFNEP population. Identifying common food sources of

Michigan EFNEP participants provides valuable

information to EFNEP educators for program refinement

and evaluation purposes.

2. Evaluated the EFNEP participants’ dietary quality by
comparing them to the current Dietary Guidelines for
Americans and the Food Guide Pyramid. Assessed the
relationship between dietary quality and participants'
demographic, dietary and lifestyle variables.

3. Quantified the positive dietary changes made by EFNEP
participants. Identified subgroups of the EFNEP
population who benefited the most from the program. The

findings of the study can be used to further enhance

10

the effectiveness of Michigan EFNEP by meeting the

needs and priorities of the people it serves.

working definitions of the terms

Dieeaxy qualiey: A binary outcome variable, which is based
on the rationale that the high dietary quality should
address the basic concepts of the Food Guide Pyramid and the
Dietary Guidelines for Americans. Two criteria were set for
the present study to assess the quality of participants'
diets: (1) including at least one serving from each of the
five major food groups as defined by the Food Guide Pyramid
(i.e., Grain-Vegetable-Fruit-Meat-Dairy = 1-1-1-1-1,
Schuette et a1, 1996); and (2) limiting fat intake to s 30%
daily energy intake (Dietary Guidelines for Americans,
1995).

Diets which failed to meet neither criteria were
considered as low dietary quality. Diets which met both
criteria were considered as high dietary quality.

Dietary ehangee: The reported changes in the EFNEP
participant's food consumption behavior that occurred
between the enrollment to graduation. Two dietary changes

are observed in our study: (1) change in consumption of five

11

major food groups, determined by subtracting the food group
score at entry from that at exit; (2) change in consumption
of fat, determined by subtracting the percent energy from
fat at entry from that at exit.

Feed Gregg Segre: This was developed based on the Food Guide
Pyramid. Score for one food group was calculated by actual
intake of the food group in number of servings divided by
minimum recommended number of servings for the food group
(i.e., Grain-Vegetable-Fruit-Meat-Dairy = 6-3-2-2-2). The
food group score was the sum of scores for five major food
groups. A score larger than 1 was truncated at 1 for each
food group to remove the influence of excessive intake of
one or more food groups on the overall score. The food group
score thus ranged from 0 to 5. For example, a participant’s
daily food group intake pattern is Grain-Vegetable-Fruit-
Meat-Dairy = 8-2-1-2-2, then her food group score was
calculated as (8+6)+(2+3)+(1+2)+(2+2)+(2+2)= 4.17.

fitheri feed green: It includes added fat and sugar. Each
serving of an “other” food group was equivalent to
approximately 35 calories (1 tsp fat or 2 tsp sugar). For
example, 10 french fries contain 1.75 servings of “other”

food group.

12

RENEE pareieipanee: Low-income (at or below 185% Federal
Poverty Income Guideline) homemakers/individuals living
either in rural or urban areas, and responsible for planning
and preparing the family's foods.

EFNEP daeahaee: The database used in the present study to
produce in-depth dietary intake evaluation of Michigan EFNEP
participants. It was built by using 1994-95 raw data from
each Michigan County's ERS. Three data files (Adult.dbf,
Recall.dbf and Meals.dbf) from 12 Michigan EFNEP counties

were integrated into one database.

Chapter Two

RELAT- LITERATURE

EFNEP evaluation studies

EFNEP is an on-going nutrition education program
targeted at low-income people in the United State.
Continuous and careful evaluations are necessary for
ensuring targeted populations are reached, demonstrating
program effectiveness and efficiency. In preciously
published EFNEP evaluation studies, researchers have
examined indicators for effectiveness of program, such as
attitude, nutrition knowledge, dietary intake, and food
practices which include food planning and purchasing, food
storage, and sanitation. Effectiveness of EFNEP has been
traditionally evaluated by analyzing changes of
participants' food consumption practices determined through
24—hour food recalls. Summary of some published EFNEP

evaluation studies are presented in Table 1.

13

Table 1.

14

Previous studies of dietary changes and associated

factors in EFNEP population

 

References

Population

Main findings

 

Cox et al.,
1995

Brink and
Sobal, 1994

Del Tredici
et al., 1988

Virginia
Regular lessons
(n=116)

Tailored lessons
(n=113)
Control(n=110)

New York
n = 50

California
EFNEP group
(n = 335)
Control group
(n = 328)

Subjects receiving the
cancer-prevention
lessons (tailored
lessons) made more
dietary changes than
those receiving the
EFNEP lessons only
(regular lessons), and
both made greater
improvement than those
receiving no nutrition
lessons (control).

Participants retain
their dietary
improvement at 1 year
follow-up.

After 6 months of
instruction in the
EFNEP group, there
was a significant
increase in food
recall score for
EFNEP group and no
change in the control
group. Dietary
changes were
positively associated
with the length of
the EFNEP visit
(minutes), the number
of visits, and
certain instruction
topics.

 

(Continues)

 

 

Table 1. (cont'd)

References Population Main findings

Amstutz and Maryland No association between

Dixon, 1986 n = 129 dietary changes and 12
demographic/programmatic
variables were found.

Brown and Georgia Teaching methods (one to

Pestle, 1981 n = 225 one vs. Group) made no
difference on dietary
improvement.
Number of visits were
positively associated
with increased diet
scores.

Johnson and Wisconsin The length of time people

Nitzke, 1975 n = 169 participated in the
program (month) had a
positive influence on
Vitamin A intake.

Verma and Louisiana Teaching methods (one to

Jones, 1973 n = 433 one vs. Group) had about

the same effect on
dietary changes.

Number of visits were
positively associated
with increasing intake of
two food groups (milk and
bread/cereals).

 

16

Description of EFNEP participants

EFNEP has successfully addressed the nutrition
education needs of low-income families with young children
for nearly three decades. According to EFNEP National
Synthesis Report (USDA, 1994), in Fiscal Year 1992, 51% of
the families served by EFNEP had incomes under $438 (family
size was not specified). 56% of EFNEP participants had 1 or
2 children at home. More than half of the EFNEP participants
participated in food assistance programs such as Food
Stamps, the Supplemental Food Program for Women, Infants,
and Children (WIC). EFNEP participants lived in diverse
communities: 26% EFNEP participants were from rural areas,
and 74% were from suburbs or cities. EFNEP participants came
from diverse ethnic background: 37% were African American,
36% were Caucasian, 23% were Hispanic, 3% were Asian or
Pacific Islander, and 1% were American Indian.

EFNEP's traditional audiences have been hard-to-reach,
difficult-to-teach, low-income urban and rural families. In
the first decade of the program (1968-1983), indigenous
paraprofessionals were instructed to canvas neighborhoods to
assess families' financial need and to emphasize recruitment

of families with children under five years of age (Armstrong

17

et al. 1992). Since 1983, the federal EFNEP guidelines have
authorized state innovations in recruitment and program
delivery to increase program efficiency and effectiveness.
Interagency referrals, especially recruitment from other
food assistance programs, were given greater emphasis.
(EFNEP policies, 1983). Those changes of EFNEP policies had
an effect on characteristics of EFNEP participants.
Increasing numbers of participants were also enrolled in the
Food Stamp program, WIC and Headstart (Armstrong et
al.,1992). Walker et al.(1983) compared the participants in
their study with traditional EFNEP participants in previous
years, they found that participants in their study tended to
be Caucasian, educated, frequently single-parents or dual-
earner households being victims of temperate unemployment
who had applied for public assistance. Researchers concluded
that recruitment and teaching of clienteles from a low-
income assistance network appears to be a cost-effective
method for reaching large numbers of low-income clienteles.
However, Armstrong et a1. (1992) questioned whether
recruitment from other agencies might limit the EFNEP's
outreach to the most needy people, who had the poorest

dietary status and lacked access to other support systems.

18

A special effort has been made by EFNEP to recruit
pregnant teens and pregnant adult women because adequate
nutrition of mothers can not only decrease the incidence of
low birth weight babies but also support the health of the
mothers and growth of the infants (Conone, 1992).

Attrition is considered a failure since participants
leaving the program in half way do not receive the full
benefit of the EFNEP. Reasons for dropping out of the
program include returning to school, finding new employment,
moving and other family concerns. Number of adults in the
home did affect the dropout rate. Walker et al. (1983)
reported that EFNEP participants who dropped out were more
likely to live in a home with only one adult. Child care and
other home responsibilities may have been a factor in

decisions to drop out of the program.

Dietary adequacy of EFNEP participants

In order to ensure that EFNEP services target the most
needy audiences, a number of EFNEP studies have examined
social/demographic factors that could affect participants'
dietary status. Observable characteristics most commonly

used in assessing factors impacting on diet adequacy include

19

race, income, education level, family composition,
residential pattern (urban, suburban, and rural), food
assistance program participation, etc.

Rage Cox et a1. (1995) reported that 54% to 70% EFNEP
participants in their study had low mean intakes of dietary
fiber (8 to 9 g/day), calcium (504 mg/day) and vitamin A
(648 to 764 retinol equivalents). Cox et al. (1995) also
reported that fat was the only nutrient for which the mean
intake by black participants (37% Kcal from fat) was
significantly higher than that of white participants (34%
Kcal from fat), with both groups being above the recommended
30% kcal from fat. In contrast, Amstutz and Dixon (1986)
observed higher consumption of foods from the "other" food
group (fats, sweets, alcohol and other) by white
participants than by nonwhite participants. The contrast
might be due to the differences in the analytical methods.
Cox et al (1995) reported fat intake as a single nutrient,
calculated as % kcal from fat. Whereas, Amstutz and Dixon
(1986) reported fat intake as a component of the "other"
food group as defined in the Food Guide Pyramid (fat, added
sugar, alcohol and other), calculated as number of servings.

Thus fat contents were differ in two studies.

20

Ineeme Based on the empirical literature review, Morgan
(1986) provided the conclusion that income was a major
determinant of household food expenditure. There was also a
positive relationship between income and dietary status,
though it was not strong statistically. In a study
investigating dietary diversity among 1976-80 NHANES II
respondents, Kant et a1. (1991) reported that food group
score1 and serving score2 showed a significantly positive
trend with increasing income and level of education in the
survey sample (n=11,658, age 19 to 74 years old). They
suggested that increasing purchasing power could increase
availability and afford ability of food for limited income
and limited formal education population groups.

However, another dietary assessment study which was
based on the 1987-88 NFCS (Nationwide Food Consumption

Survey) did not reveal a relationship between income and

 

1. Food group score counted the number of food groups
consumed daily from a total of five groups—dairy, meat,
grain, fruit, and vegetable. One point was counted for each
food group consumed. Maximum score = 5.

2. Serving score evaluated every food recall for consumption
of at least two servings each from dairy, meat, fruit, and
vegetable groups and four servings from the grain group.
Four points were counted for each of the five groups.
Maximum score = 20.

21

dietary quality (Murphy et a1, 1992). If a person’s mean of
the 3-day reported intakes were above 67% RDA for 15
nutrients (i.e., protein, vitamin A, vitamin E, vitamin C,
thiamin, riboflavin, niacin, vitamin 36, folate, vitamin
312, calcium, phosphorus, magnesium, iron, and zinc) and
percent energy form fat was below 30%, this person defined
as having a high quality diet. They reported that income was
not the predictor of dietary quality. The discrepancy of the
findings between Kant et al (1991) and Murphy et al (1992)
may be due to the differences between dietary data
collection methods ( one day 24-hour food recall vs. one day
food recall plus two day food record), and the measurement
of dietary quality (food group score and serving score based
on food group consumption vs. two criteria based on
nutrients intake).

Haines et a1 (1992) used data from 1985 CSFII to
investigate whether differences in energy and nutrient
intakes were present for women classified into different
eating patterns. They found that women classified in “Fast
Food eating pattern” (i.e., 40% to 50% of energy came from
away-from-home sources, e.g., fast food locations and

cafeterias) were predominantly young women, and women

22

classified in “Restaurant pattern” (i.e., 46% energy came
from restaurant eating) were predominantly high-income,
well-educated women. Both patterns represent the stereotype
of away-from-home consumption. Each is either high in intake
of total fat, saturated fat, cholesterol, and sodium, or low
in nutrient densities for dietary fiber, calcium, vitamin C
and folacin. In contrast, middle-income, moderately educated
and middle-aged women in “Home Mixed eating pattern” (i.e.,
70% energy consumed at home, 30% energy consumed away from
home) consumed the most healthful diets. Unemployed, low-
income, less educated women in “Home All pattern” (i.e.,
100% energy consumed at home) consumed neither the most nor
least healthful diet.

Two studies examined and found no relationships between
dietary adequacy and income of EFNEP participants at the
time of entry (Johnson and Nitzke, 1975 and Amstutz and
Dixon, 1986). These results might be due to the fact that
the income of this low-income population did not range
sufficiently to reveal a relationship.

Edueaeien_leyel Numerous studies with non EFNEP
participants report that education level has a significantly

positive impact on nutrition knowledge and food consumption

23

habits (Patterson et al., 1994; Murphy et al., 1992; Kant et
al., 1991; Popkin et al., 1989). Rogers et a1. (1995)
assessed factors associated with poor dietary habits in a
clinical population. They reported that patients with less
than a 12th grade education were twice as likely to have low
consumption of vegetables and fruits (less than 2 servings
per day, respectively) as more highly educated patients.

In contrast, Haines et al..(1992) showed that well-
educated, high-income women tended to be classified in
“restaurant eating pattern”, diets of which contained the
highest overall fat density and low nutrient densities for
dietary fiber and many of the micronutrient.

Several EFNEP studies have examined the relationship
between participants’ entry dietary quality and education.
Amustutz and Dixon (1986) reported that participants with a
low educational level (8th grade or less) consumed more
servings from the “other” food group (fats, sweets, alcohol
and other) than participants with a higher educational level
(9th grade or above) based on the entry 24-hour food recall
data. Brown and Pestle (1981) observed that participants
with a low educational level (8th grade or less) had lower

entry diet scores than participants with a higher

24

educational level (9th grade or above), but the difference
were not statistically significant. Johnson and Nitzke
(1975) reported no relationship between education level and
dietary adequacy of their EFNEP participants. They suggested
that the findings might be due to similar educational
backgrounds of their participants.

In order to improve the efficacy of EFNEP education, a
few studies addressed special needs of low-literacy
participants in EFNEP. Hartman et al. (1994‘) cautioned that
years in school did not accurately predict reading ability
for EFNEP participants in their study. They concluded that
printed materials for this sub—population should be designed
at a low—reading level. From focus group studies, Hartman et
al. (1994b) , alone with Boushey and Rauch (1989) have found
that EFNEP participants preferred demonstration and hands-on
activities to receive nutrition information rather than
lectures.

Eamily_eempeeirien No relationship was found between
EFNEP participants' dietary quality and their family size,
and number of children at home (Amustutz and Dixon, 1986;

Brown and Pestle, 1981).

Residential_patterne Several studies reported dietary

25

adequacy level at the entry by Nutrient Adequacy Ratios
(NARs)(Johnson and Nitzke, 1975), and by diet scores (Brown
and Ruth, 1981). They reported that EFNEP participants who
lived on farms had higher dietary adequacy than those of
urban and non-farm participants. These results might be due
to the summer months when the studies were conducted. The
availability and variety of foods from gardens and local
farmers' markets had an impact on EFNEP participants who
lived on farms.
Wen Morgen (1986)
reported that a food stamp bonus and other food help (e.g.,
WIC and Meal Service) did have an positive effect on
participants' food expenditure and reported dietary intake.
Armstrong et al (1992) conducted a multi year case
study to evaluate the effects of changes in recruitment and
instructional methods on dietary quality of EFNEP audiences.
Participants who were recruited by paraprofessionals
canvassing neighborhoods were called "traditional group." Of
the 1989, in the tradition group, 68% received Food Stamps,
and 39% were enrolled in WIC. Participants who were
recruited though WIC and Headstart sites were called

"modified group.” Of the 1989, in the modified group, 35%

26

received Food Stamps, and 72% were enrolled in WIC. The
participants from the modified group tend to have a higher
initial dietary adequacy level than the participants in
traditional group. This suggested that the diets of the
participants from the modified group might have been
positively influenced by nutrition education from WIC
program.

Similarly, Walker et a1 (1983) found that the diets of
EFNEP participants enrolled in other food assistance
programs (e.g., food stamps, WIC etc.) showed less
improvement because they were more adequate from the start.

In 1975, Johnson and Nitzke (1975) found no
relationship between nutrient adequacy and the receipt of
food stamps (30% of EFNEP participants in their study
receiving food stamps), or participation in other welfare
programs.

In summary, (1) EFNEP participants in previous studies
had similar educational backgrounds and family incomes.
Thus, the level of education and income for EFNEP population
were not good predictors for the dietary adequacy level. (2)
The EFNEP participants' dietary quality was not influenced

by their family composition (family size, number of children

27

at home). (3) The entrance dietary adequacy level of EFNEP
participants who lived on farms tend to be higher than those
of urban and non-farm participants. (4) Other food
assistance programs in which EFNEP participants frequently
enrolled in have a positive influence on the dietary quality

of EFNEP participants.

Dietary changes of EFNEP participants and associated factors

A number of EFNEP studies have used multi-variate
statistical methods to evaluate hypotheses related to the
factors influencing participants' dietary changes. Dietary
changes have been predicted most commonly by income, food
assistance program participation, household composition,
education level, place of residency (e.g., urban, suburban,
and rural), race, ethnic origin, and programmatic factors
(e.g., teaching methods, education topics, frequency of
EFNEP visit, length of EFNEP visit).

EFNEP dietary assessment studies have shown positive
dietary changes of participants at the completion of the
program. Participants retained their dietary improvement at
various follow-up periods (6 months to 36 months): Brink and

Sobal (1 year follow-up, 1994), Torisky et a1. (6—36 months

28

follow-up, 1989), Amstutz and Dixon (18 months follow-up,
1986), Brown and Pestle (1 year follow-up, 1981).

In addition to improvement of dietary intake, EFNEP
participants improved program-related knowledge (such as
food storage and sanitation, meal planning), resource—
management and decision making skills, and self-confidence
(Brink and Sobal, 1994; Bowens et al., 1995; Romers et al.,
1988; Anderson, 1988).

Amstutz and Dixon (1986) reported that dietary
improvement measured by changes in diet score could not be
predicted by any of the following participants'
characteristics: education, race, age of homemaker, presence
of adult male in the home, size of household, income, Food
Stamp participation, welfare status, initial diet scores,
months stayed in the program, and number of lessons
received. Significant reduction of intake of the "other"
food group (fats, sweets, alcohol and other) were reported
in the participants with the high initial servings from the
"other" food group.

Family composition is considered an external factor
influencing EFNEP participants' dietary improvement. Torisky

et a1 (1989) reported that EFNEP participants’ dietary

29

improvement was not associated with selected family factors,
such as family composition, family support and family diet
control.

Del Tredici et al.(1988) concluded that dietary changes
were determined by the length of the EFNEP visit(mean
80.5124.3 minutes), the frequency of EFNEP visits (mean
7.8:3.9), and the EFNEP instruction topics (such as
nutrition facts, selection and buying, cooking skills,
economical preparation, food safety, and preservation).Even
though these factors did not always directly influence diet
scores, they directly increased participants’ knowledge and
attitudes, which in turn influenced diet scores. Three other
studies agreed that the number of visits were positively
associated with increased intake of certain food groups
(Brown and Pestle, 1981; Johnson and Nitzke, 1975; Verma and
Jones, 1973).

Programmatic variables such as curriculum and teaching
methods (individual instruction or group teaching) have been
studied in relation to EFNEP Participants' dietary changes.
Cox et a1. (1995) found that participants receiving tailored
cancer-prevention lessons made more dietary changes than

those receiving the EFNEP regular lessons only. Individual

30

instruction and group teaching had about the same effect on
dietary changes, although group teaching methods reached
more people (Walker, 1983; Brown and Pestle, 1981; Verma and
Jones, 1973).

In summary, EFNEP evaluation studies show that the
program has made positive changes in participants' dietary
adequacy. Overall, dietary changes of EFNEP participants was
not related to various demographic characteristics such as
education, race, age, income, family composition, etc. This
might be due to similar economic background and lifestyle of
the EFNEP participants. A few researchers suggested that the
number of visit and tailored curriculum had positive

influence on dietary changes of participants.

Indices of overall dietary quality

Quantitative measurement for diet quality of a
population which can address several important nutrition
concepts of the current dietary recommendations and food
guides is highly desirable for administration and evaluation
of various nutrition education programs.

Kant (1996) compiled the diet quality indexes that have

been reported in the literature into three major categories:

31

indexes derived from nutrients only; indexes based on foods
or food groups; and indexes based on a combination of
nutrients and foods.

A few early measures have focused on the nutritional
adequacy of a single nutrient or combinations of nutrients
for which the Recommended Dietary Allowances (RDA) are
established. Such as the Index of Nutritional Quality (INQ,
Sorenson et al., 1976), the Nutrient Adequacy Ratio (NAR,
Gibson, 1990), the Mean Adequacy Ratio (MAR, Abdel-Ghany,
1978).

Researchers have also taken approaches for measuring
overall dietary quality based on consumption of food groups.
Guthrie and Scheer (1981) validated the use of a dietary
score based on the Basic Four Food Groups3 by comparing it
to a nutrient adequacy score based on the actual 12 nutrient
intakes‘cof 212 college students. The dietary score range

from 0 to 12. Two points were given for each servings in

 

3. The Basic Four Food Groups include: milk and milk
products, meat and meat alternatives, fruit and vegetables,
plus bread and cereals.

4. Twelve nutrients include: protein, calcium, zinc,
magnesium, iron, Vitamin A, Vitamin B6, Vitamin B12, Vitamin
C, thiamin, riboflavin, and folacin.

32

both milk and meat group. One point was given for each
serving in both fruit/vegetable and bread/cereal groups. No
extra points were given for serving numbers excess the
recommendation. As the dietary score increased, the
percentage of subjects obtaining 67% RDAs for 12 nutrients
also increased. The authors concluded that the scoring
method based on food grouping has the power to assessing
dietary adequacy of the target population.

Kant et a1. (1991) concluded that screening diets for
food group consumption can quickly provide meaningful
information about their quality. Authors reported that a
food intake pattern in which respondents consumed foods from
all five food groups (grain, vegetable, fruit, meat, and
dairy) provided mean amounts of all the key nutrients
(protein, vitamin C, vitamin A, vitamin E, vitamin B6,
folate, zinc, iron, calcium, and potassium) at levels
greater than or equal to the RDAs.

Schuette et al.(1996) proposed and validated the use of
a food group score system for assessing nutritional
inadequacy in 2489 college students. Authors evaluated diets
containing at least one serving from the five major food

group as defined in the Food Guide Pyramid by comparing to

33

MAR-6 score (iron, calcium, magnesium, vitamins A, C and
B6). The sensitivity and specificity of this food group
score system for screening nutritionally inadequate diets
based on MAR-6 < 75% were 89% and 45% for college students.
They suggested that the minimal number of servings of the
Food Guide Pyramid food groups can be used as a quantitative
tool for assessing nutritional inadequacy.

Within the last two to three years, a few indexes have
been developed for assessment of dietary quality according
to the Dietary Guidelines for Americans and the Food Guide
Pyramid, namely, a high quality diet should be adequate in
energy and nutrients and moderated of fat and sodium. The
Healthy Eating Index (HEI; Kennedy et a1, 1995) was
developed based on a ten component system: five food groups
(i.e., grains, vegetables, fruits, milk, and meat), four
nutrients (i.e., total fat, saturated fat, cholesterol, and
sodium), and a measure of variety in food intake. The Diet
Quality Index (DQI; Patterson et al., 1994) was developed
based on weighting of selected nutrients and food intake
recommendations of the Food and Nutrition Board. Diets were
assigned points which were summed across eight diet

variables to score the index from zero (excellent diet) to

34

16 (poor diet). Both indexes were designed for use by
researchers as indicators of overall diet quality. The
requirement of quantitative estimation of nutrients and food
groups makes both indices too complex to be useful.

In summary, a goal for nutrition intervention programs
is to increase the nutritional quality of the participants’
diets. All of the indices mentioned above are useful for
evaluating certain aspects of diet quality. Continued
endeavor is needed to ensure that a valid and reliable index
which incorporates the recommendations of both the Food
Guide Pyramid and the Dietary Guidelines for Americans. The
index also needs to be simple for the quantitative
procedures for routine evaluation of the efficacy of

nutrition intervention programs.

Dietary assessment methods used by EFNEP

24-hour food recall which was used in present study has
traditionally been the dietary assessment instrument for
both describing initial dietary status of EFNEP participants
and for measuring change in dietary practice resulting from
EFNEP participation.

There are four main categories of nutritional

35

assessment techniques: anthropometric measurements,
biochemical analyses, clinic examinations and historical
dietary information. 24-hour food recall which provides diet
histories fits into the fourth categories. No one technique
alone is sufficient for assessing the nutritional status of
individuals or groups. Woteki (1992) has suggested that the
choice of dietary assessment method should be determined by
1) practicality in terms of respondent burden, 2) analysis

resources, and 3) reliability and validity.

In The Expanded EQQd and Nutritien Edneatien Eregram;
Histerical_and_Statistical_£refile (USDA, 1979), the

following reasons are delineated for using 24-hour food
recall in EFNEP:

The diet assessment methods used by EFNEP must be
simple and brief. Program homemakers will not
likely tolerate lengthy and involved questioning
about their nutrition habits, nor will they submit
to complicated biochemical and medical tests.
Furthermore, the procedure has to be accurately
applied by paraprofessional aides, who may not
have the background to collect and interpret
detailed information on nutrients in food
consumed. The method has to serve as a measure of
assessing progress during the homemaker's
participation the program. This implies repeated
diet assessments, which could not be feasible with
complex assessment procedures. Hence, the use of
the 24 Hour Dietary Food Recall.

36

Sanjur (1982) summarized the following strengths and
weaknesses of the 24-hour food recall: its strengths include
validity to provide estimates of the mean intakes of
population groups, simple to use, requiring less effort and
time on the part of the respondents, inexpensive, and
useability with illiterate individuals. The weaknesses
result from low reliability and validity to estimate the
individual's typical daily food intake, the "flat-slope
syndrome" (the tendency of large eaters to underestimate and
small eaters to overestimate amounts eaten), reliance on
honesty and memory of the subject, and lack of accurate
quantitative information.

Axelson (1984) cautioned against repeatedly employing
24-hour food recall to measure dietary changes in nutrition
education programs. Axelson observed that mean intake for
most nutrients increased, although not significantly, from
pre- to post—recall even when no nutrition intervention was
conducted between the two recalls. The author suggested that
the experience of the first food recall might accounted for
some of the differences in post—food recall, and thus groups
to be evaluated should not serve as their own controls.

Either random assignments to control and experimental groups

37

or statistical treatment should be used to control for the
unequal initial mean measurements of existing groups.

In EFNEP, 24-hour food recalls were completed by EFNEP
participants prior to and after the nutrition intervention.
Each 24-hour food recall was assigned a score by using a
method of scoring developed by the Synectics Scoring System
for the USDA Extension Service (Jones et al, 1975). The
Synectics Scoring System is based on the concept of the
Basic Four Food Groups. For an adult, the Basic Four Food
Groups recommended the serving numbers were milk-meat-
fruit/vegetable-bread/cereal = 2-2-4-4. Food and beverages
that do not belong to one of the four food groups are
classified as "other" food group (e.g., fats, sweets, and
alcohol). The score derived from this scoring method has
been called Synectics score, USDA score, food recall score,
diet score, dietary score and dietary adequacy score by
different EFNEP studies.

The score ranges from 0 to 100. A minimum of 0 servings
expressed as a score of 0, and a maximum of 12 servings
expressed a score of 100. The 12 servings signified the
recommended number of servings for an adult from each of the

four main food groups (i.e., Milk-Meat—Fruit/Veg-

38

Bread/Cereals with 2-2-4-4 pattern). No additional points
were given for consuming more than the recommended number of
servings in any of the food groups. For example, a diet with
Milk-Meat-Fruit/Veg-Bread/Cereals = 1-2-2-4 pattern. The
Synectics score = 9+12x100 = 75. The higher scores
represents the better nutritional adequacy of a diet. The
weakness of the Synetics Scoring System is that each serving
of the food groups was equally weighed in the final food
group score, i.e. 1 serving of milk is given an equal weight
as 1 serving of bread/cereal. Thus the food group which
required more servings in a daily diet were weighed more in
the final food group score.

The strength of "food group approach" for dietary
assessment is obvious. People eat food not nutrients. The
"food group approach" is consistent with the nutritional
education efforts that encourage clients to improve their
food intake practice. Its concept is easily understood by
the general population. The scoring systems based on food
groups provides a basic indicator of dietary balance.

The Food Guide Pyramid (USDA, 1992) which illustrates
the key concepts of variety, moderation, and proportionality

addresses many of the weaknesses of the Basic Four Food

39

Groups. The Basic Four Food Groups does not provide guidance
for moderate consumption of fat, cholesterol, saturated fat,
calories, salt, sugar, or alcohol which are related to
diseases of overabundance such as obesity and coronary heart
disease.

The USDA's Food Guide Pyramid has been utilized by
EFNEP educators to teach clients how to put the Dietary
Guidelines into action. The relevant instrument which can
assess overall dietary quality should be utilized to
evaluate the effectiveness of the EFNEP participants'
dietary changes.

In summary, the Michigan EFNEP evaluation incorporated
the following conclusions in research design: (1) The 24-
hour food recall was considered suitable and valid for
assessment of dietary intake of EFNEP participants. (2) The
score assigned to a food recall, which based on the Basic
Four Food Groups, was as good as analyzing nutrient content
to assess a diet. (3) Scoring system based on food groups
should be modified to address the concepts of Food Guide

Pyramid.

Chapter Three

METHODOLOGY

Research design

The central focus of this research project was to
evaluate the dietary quality of Michigan EFNEP participants,
and to assess the dietary changes fostered by the program by
using the concepts of the Food Guide Pyramid and the Dietary
Guideline for Americans. A cross-sectional evaluation was
performed to assess overall dietary quality of Michigan
EFNEP participants at the time of enrOllment (n= 3866,
August, 1994 - September, 1995). A longitudinal evaluation
research approach was chosen to study dietary changes of a
subgroup called EFNEP graduates (n = 2454, August, 1994 -

September, 1995).

Subjects
The subjects of the present study were 3866 female
participants in EFNEP from 12 Michigan EFNEP counties

40

41

between 1994 and 1995 (Appendix C: Distribution of Michigan
EFNEP counties 1994-95). Data were collected by EFNEP
Evaluation/Reporting System (ERS) on demographic information
and dietary intakes by 24-hour food recalls at the beginning
and the end of the program.

Michigan EFNEP is administered through Michigan State
University Extension and managed by county-based MSU
Extension home economists. Low-income (at or below 185%
Federal Poverty Income Guideline) homemakers/individuals
living either in rural or urban areas, and responsible for
planning and preparing the family's foods were recruited.
Most of participants enrolled in the program voluntarily,
others enrolled in the program through selected cooperating
agencies, or through court order in cases of child custody.
Participants received instructions from EFNEP
paraprofessionals using Eating Right Is Basic (Third
Edition) curriculum. This curriculum was developed and
produced by Michigan State University Extension Service
(Appendix D: List of EFNEP curriculum content). Participants
who complete at least seven core lessons were eligible to
receive graduation certificates.

Approval for the study was obtained from the University

42

Committee on Research Involving Human Subjects (Appendix E:
UCRIHS approval). All information was kept strictly
confidential. Participants' names, phone numbers and mailing
addresses were deleted from the original files. No
respondent was identified individually in any way in the
final data presentation.

Approximately 5,000 families in Michigan participate in
the EFNEP annually. In 1994-95 fiscal year, sixteen Michigan
counties offered EFNEP to local low-income families.
Fourteen of sixteen used ERS to collect information on
demographics and dietary intake of the participants during
the educational program. Twelve counties provided complete
data. Thus, these 12 counties were included in present
study. These 12 Michigan EFNEP counties were: Berrien,
Dickinson, Genesee, Kalamazoo, kent, Muskegon, Oakland,
Saginaw, Sanilac, St. Clair, Washtenaw, and Wayne (Table 2).

For each fiscal year, there were three subgroups of
EFNEP participants: those who had met the objective of the
education (graduates), those who had withdrawn from the
program due to the reasons such as returning to school,
finding a job etc. (dropouts), and those who are still

participated in the program (continued participants).

43

 

 

 

continued participants, respectively.

Table 2. 1994-95 ERS raw data received from 16 Michigan
EFNEP countries

COUNTY DATA PROBLEM TOTAL GRAD* DROP* CONT*
Berrien OK 414 307 35 72
Dickinson OK 30 21 3 6
Genesee OK 376 270 52 54
Ingham Incomplete data.
Kalamazoo OK 372 265 39 68
Kent OK 448 283 104 61
Lenawee Not using ERS at

1994-95
Macomb Incorrect reporting

period
Muskegon OK 329 189 76 64
Oakland OK 660 404 108 148
Saginaw OK 425 278 38 109
Sanilac OK 99 78 5 16
St. Clair OK 73 61 1 11
Washtenaw OK 172 81 44 47
Wayne OK 766 449 139 178
Bay Not using ERS at

1994-95
Total 12 counties raw

data 4164 2686 644 834

12 counties-female

data 3866 2454 621 791

GRAD, DROP, and CONT indicate graduates, dropouts, and

44

Our raw data included 4164 cases. We performed six

steps procedure to eliminate 298 cases from the 1994—95 data

set.

criteria for cases in the present study were: incomplete

The reminders were 3866 female subjects. The exclusion

dietary record, age, gender, income, caloric intake (Table

 

 

3).
Table 3. Procedure for exclusion of cases from 1994-95
EFNEP database
Step Procedure Number
excluded
(n=298)
1. Eliminate cases without 24-hour food recall at 15
the time of entry
2. Eiéminate cases whose age was less than 13 years 16
o
3. Eliminate cases whose monthly income > 185% 37
Poverty index
4. Eliminate cases that had no caloric.intake or 25
caloric intake above 4 standard.dev1ation from
the mean at the time of entry (i.e., 6048
Kcal/day).
5. Eliminate graduate.cases that had no caloric 15
intake.or caloric intake above 4_standard.
deViation from the mean at the time of eXlt
(i.e., 6049 Kcal/day).
6. Eliminate cases with male participants. 190

 

45

Data collection

The data for EFNEP participants were collected by
paraprofessionals using two standardized forms: Adult Family
Record (Appendix F) and 24-Hour Food Recall (Appendix G).

The Adult Family Record is normally completed by the
participants during the first enrollment visit. Demographic
data were recorded on participants and their families for:
age, sex, pregnancy, nursing, race, place of residence,
total household income last month, number of children
(through age 19) at home and their ages, number of other
adults in household, type of instruction (group or
individual teaching), other assistance programs in which the
family participates.

24-Hour Food Recall is normally completed by the
participants with the help of paraprofessionals during the
first enrollment visit and the last visit. Respondents
report, as accurately as possible, the foods and drinks they
have consumed in the 24-hour time period before the visit.
Paraprofessionals in Michigan have been trained to maximize
accuracy of the recall by establishing rapport at the
beginning of the program; soliciting cooperation and

confidence by explaining the purpose of the food recall;

46

asking follow-up questions about the food consumed;
demonstrating the house measures such as glasses, cups,
spoons, bowls and plates to help participants to estimates
the amount of foods consumed; and verifying the reported
food consumed by repeating the information and asking if
everything has been included.

Each participant's information collected by the above
two standardized forms were entered into ERS at the EFNEP
county office by a trained clerical staff. The forms were
frequently (but not consistently) checked prior to entry by
an Extension Home Economist.

24-hour recalls were entered into ERS with the correct
meal code, food name, and quantity of the food item. ERS
defined meal code as: 1 - Morning meal or snack; 2 -
Midmorning meal or snack; 3 - Noontime meal or snack; 4 -
Afternoon meal or snack; 5 - Evening meal or snack; 6 - Late
evening meal or snack. The Grams/Unit and the description of
the unit size (e.g. ounce, slice, dozen) of the food item
were used as a guide to the appropriate quantity for food

items.

Foods database

47

The EFNEP ERS Foods Database contained the following

nutrient values and servings of food groups for 1373 food

items.

Food ID
Name of food item
Unit of measure of item (ounce, each, slice, etc.)

Gram weight of item

Serving size of item

Number
Number
Number
Number
Number
Number

Number
Grams
Grams
Grams
Grams
Grams

of
of
of
of
of
of

of
of
of
of
of
of

servings
servings
servings
servings
servings
servings

calories
protein
fat

carbohydrates

fiber
alcohol

of
of
of
of
of
of

bread

fruit

vegetables

meat

dairy/calcium products

other foods (added fat and sugar)

Retinol equivalents of vitamin A
Milligrams of vitamin C

Milligrams of calcium
Milligrams of iron

Milligrams of vitamin B6

The Foods Database was designed to be a "generic",

reliable, concise for use in all EFNEP states and

territories

. The Foods Database includes about 1373 core

foods. Nutrient values of most foods were taken from the

USDA Handbook #8 series of the database from the Human

Nutrition Information Service that was used to analyze the

48

Nationwide Food Consumption Survey. Foods were assigned to
the Food Guide Pyramid food groups based on the definition
and specifications of servings as stipulated by the US
Department of Agriculture and Department of Health and Human
Services. The Food Database was flexible permitting
continuous updating of existing values and additions of new
single or composite foods. Additional recipes,
manufacturers' and ethnic food data were entered to make the
database as complete as possible. Additional foods commonly
eaten in the area can be entered into database by each state
office. There were no missing values in the food database.
Nutrients derived from supplements were not quantified and
therefore were not included in the daily totals.

The Foods Database was indexed by food name. The food
names are listed by categories, such as bread, beverages and
juices, chicken, fish, beef, turkey, cereal, candy, soup,
sandwiches and sauces. These foods were all listed with the
category name first, then a comma, and then a more precise
description (such as chicken, thigh, batter/fried). Food ID
numbers were originally organized in alphabetical order by
food name. Standard units included those for items, e.g., 1

apple, 1 sandwich, 1 slice etc., and those for measures

49

e.g., teaspoon, tablespoon, ounce, or cup. Since the weight
of "servings" of food are approximate, and the Food Guide
Pyramid gives broad definitions of serving sizes for classes
of foods, the Foods Database rounds the number of servings
to a unit of 1/4 serving (i.e. 1.02:1.00; 0.23:0.25;
0.78:0.75, etc). Where appropriate, ERS uses 0.33 and 0.67
to represent 1/3 and 2/3 respectively, and occasionally to

the nearest 0.10 serving unit.

Data processing

The ERS system data can be used in various ways. They
are used to provide the recall diagnostic reports as
feedback to participants and to generate summary reports of
the EFNEP unit for each designated reporting period. Used in
the present study are the raw back up data files from the
system database. Three data files (Adult.dbf, Recall.dbf and
Meals.dbf) backed up from each county were integrated into
one statewide database (Appendix H: Print outs of three ERS
raw data files).

Adult.dbf - contains participants' demographic and

programmatic variables (from the Adult

Family Record).

50

Recall.dbf - contains information about the
recalls. For each recall, nutrients
values and the number of servings of the
food groups are listed as variables
(from 24-hour food recall).

Meals.dbf - holds the quantities of each food item

consumed (from 24-Hour Food Recall).

In the EFNEP database, each case contains the complete
information (i.e., demographic and dietary intake) for each
participant. The original Recall.dbf file was split into
entry recall file and exit recall file. Variables for an
entry file were renamed as variables 1. Variables for an
exit recall file were renamed as variables 2. These two
files were then combined with the same cases, but with
different variables. This newly combined recall file was
then merged into Adult.dbf file to form one final integrated
data set. Procedures of file transforming were repeated for
all the backup diskette(s) from each of the Michigan EFNEP
counties to create a EFNEP database.

Dietary quality was a binary outcome variable. The
classification was based on the rationale that the high

dietary quality should encompass the concepts of both the

51

Food Guide Pyramid and the Dietary Guidelines for Americans.
Two criteria set for the present study to assess the quality
of participants' diets are: (1) Including at least one
serving from each of the five major food groups as defined
by the Food Guide Pyramid (i.e., Grain-Vegetable-Fruit-Meat-
Dairy = 1-1-1-1-1); (2) Limiting fat intake to s 30% daily
energy intake. Diets which failed to meet both criteria were
considered low dietary quality, and diets met both criteria
were considered high dietary quality in subsequent data
analysis.

In the present study, a diet with Mean Adequacy Ratio
MAR-5 score < 75 was defined as nutritionally inadequate. It
was less liberal than 67% of RDA, but not as stringent as
100% of RDA (Schuette et al.,1996). Five nutrients (i.e.,
calcium, iron, and Vitamin A, C, and B6) were used to
calculate MAR-5. These five nutrients were most often
lacking in American diets (CSFII 1994). Additionally,
vitamins A, vitamin C, calcium and iron are four micro
nutrients included in new food labels established by the
Food and Drug Administration regulations (Federal Register,
1993). .

MAR-5 was calculated by the following two steps:

52

actual nutrient intake
recommended dietary allowance

sum of NARs for 5 nutrients

NARs scores 2 100 was truncated at 100.

Dietary changes were the changes in the participants’
food consumption behavior that occurred between the entry
and graduation of the program. In our study, dietary changes
were determined by two criteria: 1) change in consumption of
five major food groups, which was determined by subtracting
the entry food group scores from the exit food group scores;
2) change in consumption of fat, which is determined by
subtracting the percent energy from fat at the entry from
that at the exit. Desirable changes were an increase in food
group score and a reduction in percent energy from fat.

Food group score (FGS) was developed based on the Food
Guide Pyramid. Score for one food group was calculated by
actual intake of the food group in serving numbers divided
by minimum recommended servings for this food group. Food
group score was the sum of scores for the five major food

groups. A score larger than 1 was truncated at 1 for each

53

food group. The resulting final food group score were in an
interval scale of numbers with decimals. Food group score
ranged from 0 to 5. The equation for calculating the food

group score was as following:

5 actual intake servings

n=1 minimum recommended servings

Two levels of recommended number of servings for five
food groups were used in our study based on participants'

gender, age and maternal status (Table 4).

Table 4. Two levels of recommended number of servings for
the five major food groups

 

 

Bread-Veg-Fruit-Meat-Dairy Participants Age
level 1 6-3-2-2-2 Female Adult 25-99
level 2 6-3-2-2-3 Female Pregnant 0-99
Female Nursing 0-99

Pregnant & Nursing 0-99

Female Young 0-24

 

Note: Diary products are the best source of calcium. The Food Guide Pyramid
suggests 2 to 3 servings of milk, yogurt, and cheese a day--2 for most
people, and 3 for women who are pregnant or breast-feeding, teenagers, and
young adults to age 24.

For example, of a pregnant EFNEP participant's daily

food group intake pattern was Bread-Veg-Fruit-Meat-Dairy =

54

8-2-1-2-3, her Food group score was calculated as
(8+6)+(2+3)+(1+2)+(2+2)+(3+3) = 1+0.67+0.5+1+1= 4.17.

The strength of the modified food group score used in
our study is that each food group had the same weight in
final food group score. i.e. 6 servings from the bread/grain
group is equal weight as 2 servings from the fruit group,
both earn score one. This was based on the assumptions that
each food group had its own unique nutritional composition
and thus made an equally significant contribution to
nutrient adequacy. The food group score was used to measure
the dietary adequacy level, and to describe the dietary

changes after EFNEP participation.

Statistical analyses

Statistical analyses for objective one, objective two,
objective three, objective four, and objective five were
carried out by using SPSS 6.0 for Windows.
thfiflfii!§_9ne (graduates vs. dropouts):

Frequency distributions were generated to describe the
characteristics of all Michigan EFNEP participants and
subgroups. Pearson chi-square tests were performed to

evaluate whether graduates and dropouts had the same

555

demographic characteristics in ethnic origin, age group,
maternal status, family size, place of residence, and number
of public assistance programs participation in. Pearson chi—
square test was also performed to determine whether the
percentage graduates and dropouts classified into four
dietary quality groups were the same.

thfiQLi!§_LHQ (food intake patterns):

Frequency distributions of skipping breakfast, lunch,
and dinner were generated. The top 20 food items that
contributed most intakes (in servings) of the five food
groups (i.e., grain, vegetable, fruit, meat, and dairy) and
“other” food group (i.e., added fat and sugar) were listed
respectively.

The percent contribution provided by a particular food

item j to a certain food group (e.g., grain) was given by:

Total intake of a food group
from food j summed over all individuals

 

X 100

Total intake of a food group
from all foods summed over all individuals
Estimated by:

3866 x

Z 2 food group”,

1-1 k-O

)( Il()0

 

3688 1373 K

2 Z 2 food group“,

i-l j-l k-O

56

Where i = subjects, 1,2,...,3866;
j = food items, 1,2,..., 1373;
k = intake of food item j to that subject,
0,1,2,...K (in servings);

food grouptw = serving numbers contained in serving k
of food item j to subject 1.

The percent contribution provided by a particular food
item 1 to a nutrient (e.g., iron) was calculated by using
the same formula above. The top 20 food items that
contributed most the intakes (in g, or mg) of calcium, iron,
vitamin A, vitamin C, vitamin B6, and fiber were also listed
respectively.

Qbi£££i¥§.£hr§e (overall dietary quality):

Descriptive statistics of food groups, nutrients and
food components were obtained for all Michigan EFNEP
participants at the time of entry. Frequency distribution of
four dietary quality sub-groups was obtained.

Qbieeriye_fiear (factors associated with dietary quality):

Of a total of 3866 participants at the time of entry,
2287 participants’ diets which met neither criteria were
classified as low dietary quality(coded as 1), 183
participants' diets which met both criteria were classified
as high dietary quality (coded as 0). 1396 participants who

met only one criterion were not retained for the data

57

analysis of this objective.

For objective four, the dietary quality, was the
dependent variable, with low quality diets and high quality
diets as the risk (coded as 1) and referent levels (coded as
0), respectively. Our primary interest was to evaluate
whether low dietary quality can be predicted by two
undesirable food behaviors: (1) high intake of the “other”
food group (i.e., 10 to 20 servings vs. 5 10 servings, and >
20 servings vs. s 10 servings); and (2) low frequency of
meals/snacks consumption (i.e., < 3 meals/day vs 2 3
meals/day) while controlling for energy intake in the model.
We also investigated if the low dietary quality was
associated with factors such as maternal status, race,
participation in other food assistance programs, family
size, place of residency, age, and income.

The association of factors investigated in our study
with the dietary quality (1 = low quality, 0 = high quality)
was determined by logistic regression. Odds ratios (ORs) and
95% confidence intervals (95% CI) were calculated to assess
the strength and statistical significance of the
associations. An odds ratio larger than one indicates a

positive association and an odds ratio less than one

58

indicates a negative association. A 95% confidence interval
that does not include the value of one denotes rejection of
the null hypothesis that the odds ratio is 1.

A full interaction model of logistic regression was
used to examine the relationship between the dietary quality
and each of the undesirable food behaviors while controlling
for the effect of confounding variables in the model. Two-
way interactions between energy intake and two undesirable
food behaviors plus age, race, and maternal status were
included. The backward Likelihood-ratio test was used for
determining variables to be removed from the model. The
entry and removal criteria for stepwise variable selection
were p < 0.05 and p < 0.10, respectively. The p-value < 0.05
was used to assess the significant association. To minimize
the possibility of Type I errors, only interactions with
associated probabilities of less than 0.01 were accepted.

The full interaction model is written in logit form.
Logit P(X) = a + Bl intake of added fat and sugar

+ 82 frequency of meals/snacks

+

yl energy intake + y2 age + v3 race

v4 income + y5 maternal status

4.

+

v6 place of residence

59

+ v7 participation in other food programs

+ 61 energyxintake of added fat and sugar

+ 62 energyxfrequency of meals/snacks

+ 63 energyxage

+ 64 energyxrace

+ 65 energyxmaternal status
d- constant
81— coefficient of primary factors
vi- coefficient of confounding variables
61- coefficient of two-way interaction terms

When the energy intake was found interacting

significantly with undesirable food behaviors, subjects were
stratified into three energy intake groups to minimize these
interactions. Subjects whose energy intake were below one
standard deviation from the mean (< 803 Kcal) were
classified as low energy intake group. Subjects whose energy
intake were over one standard deviation from the mean (>
2596 Kcal) were classified as high energy intake group.
Subjects whose energy intake were between plus and minus one
standard deviation from the mean (803 Kcal - 2596 Kcal) were
classified as moderate energy intake group.

The final main effect model was performed separately in

60

three energy intake sub-groups to estimate the group-
specific association between the variables and dietary
quality. For a comparison purpose, the final main effect
model was also performed for all participants in three
energy intake sub-groups. Backward Likelihood-ratio test was
used for determining variables to be removed from the model.
The p-value < 0.05 was used to assess the significant
association.
The final main model is written in logit form as below:

Logit P(X) = d + 81 intake of added fat and sugar

+ 82 frequency of meals/snacks

+ yl energy intake + y2 age + v3 race

+ Y4 income + y5 maternal status

+ v6 place of residence

+ y7 participating in other food programs
d- constant

Bi- coefficient of primary factors
vi- coefficient of confounding variables
thfigli¥§_fii!§ (dietary changes):

ANOCOVA was conducted to determine whether average

changes in food group score and percent energy from fat

61

differed among four dietary quality groups, when differences
in energy intake and number of lessons completed were
controlled. Paired t-tests were used to test whether the
food group score, percent energy intake from fat, number of
servings for each food group and energy intake of graduates
differed between the time of entry and the time of exit. A
significance level of p < 0.05 was selected to determine

statistical differences.

Chapter Four

RESULTS

Subjects

Subjects included in the present study were 3866 female
participants. As summarized in Table 5, age of the subjects
ranged from 13 years old to 85 years old. Mean(¢SD) and
median age was 28:8.5 and 27 years old, respectively. The
majority of the subjects (87%) in the EFNEP were enrolled in
at least one other public assistance program: Food Stamps
(58.3%), Women, Infants & Children Supplement Food Program
(57.9%), Aid to Families with Dependent Children (AFDC,
39%), Child Nutrition (School Lunch/breakfast, 23%), Head
Start (20%), the Emergency Food Assistance Program (TEFAP,
10%), Food Distribution Program on Indian Reservations
(FDPIR, 1%) and other public assistance programs (not
specified, 14%) that require low income for eligibility.

The subjects in the study had an average household size
of four people. The mean (iSD) and median monthly household

income were $5611484 and $488, respectively. Twenty two

62

63

Table 5. Baseline characteristics of all subjects,
graduates, and dropoutsa

 

 

 

All
subjects Graduates Dropouts
% % %
Ethnic Origin
White 47.3 46.8 47.2
Black 39.9 39.3 40.9
Other” 12.9 13.9 11.9
Age Group°(yr)*
13 - 14 0.7 0.8 0.5
15 - 18 11.8 12.6 11.8
19 - 24 26.9 24.6 33.0
25 - 50 59.1 60.6 53.3
51 - 85 1.4 1.6 1.4
Maternal Status
Pregnant/Nursing 21.2 19.8 20.3
Non-pregnant/non-nursing 78.8 80.2 79.7
Family size
1 - 2 22.5 22.9 22.9
3 - 5 64.6 64.1 65.4
6 + 12.9 13.0 11.8
Place of residence*
Rural area 13.0 15.0 8.5
(population < 10,000)
Towns/cities 27.6 25.7 34.0
(pop. 10,000-50,000)
Central cities 59.4 59.3 57.5
(population > 50,000)
Participation in public
assistance programs
None 13.3 14.5 9.0
At least one 86.7 85.5 91.0
Food stamps 58.3 57.1 65.9
WIC 57.9 54.8 61.8
a. All subjects (n=3866) at the time of entry (baseline)

include graduates (n=2454), dropouts (n=621) and those who
continued the program (n=791).

lb. Other ethnic origin includes Hispanic (10.0%), Asian/Pacific
Islanders (1.7%), and Native American (1.2%).

c. Age group classification corresponds to the age groups of
RDA: 11-14 yr, 15-18 yr, 19-24 yr, 25-50 yr, and 50+ yr.

*. Graduates differed significantly from the dropouts in age

distribution and place of residence (P<0.001, Pearson Chi-
square test).

64
percent of the subjects reported their monthly household

income of less than $10.

Factors differentiating the EFNEP dropouts from the
graduates (Objective one)

The EFNEP participants were classified into three sub-
groups: (1) those who had met the educational objectives
(graduates, n=2454, 64%), (2) those who had withdrawn from
the program (dropouts, n=621, 16%), and (3) those who were
still enrolled in the program (continued, n=791, 20%). The
majority of the graduates (67%) completed the program with
10 or fewer visits, whereas 32% completed with 11 - 20
visits, and less than 1 % completed with more than 20
visits.

Graduates and dropouts sub-groups were compared for
demographic characteristics (e.g., ethnic origin, age group,
maternal status, family size, place of residence, and number
of public assistance programs participated). The graduates
differed significantly from the dropouts in age distribution
and place of residence (Table 5). Subjects aged 19 - 24
years old were more likely to drop out of the program rather
than stay on. Subjects residing in the towns or cities

(population 10,000 — 50,000) were more likely to drop out of

65
the program rather than stay on.

Dropout rates varied widely among the twelve Michigan
EFNEP counties (1.5% - 25.6%, Table 6). Three counties with
the highest dropout rates were Washtenaw County (25.6%),
Muskegon County (23.7%), and Kent County (23.3%). These
three counties had no common characteristics in age
distribution and place of residence. In Muskegon County,
Washtenaw County, and Kent County, percent of subjects
residing in towns or cities (population 10,000 - 50,000)
were 94.8%, 68.5%, and 16.5%, respectively. Comparing with
26.9% of total subjects in age group 19-24, Kent county had
fairly large portion of its subjects in age group 19-24 year
old (36.9%).

Dropouts indicated their reasons for dropping out of
the program as: having lost interest (43%), moving (20%),
taking a job (13%), family concerns (5%), and returning to
school (3%). Sixteen percent of the dropouts indicated no
specific reason. In Kent County, as high as 97.1% of
dropouts gave the reason for dropping out of the program as
lose of interest. Sixty five percent of dropouts in
Washtenaw County and 45% of dropouts in Muskegon County also

reported the same reason for dropping out.

66

 

 

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67

In 1994-95 reporting period, Average number of subjects
served by a paraprofessional varied among the twelve
Michigan EFNEP counties (from n=25 to n=84). Michigan EFNEP
participants received instructions from paraprofessionals
most frequently in a group format (51%), followed by one-to—
one basis (44%) and mixed type of instruction formats (5%).

Based on entry 24-hour food recalls, percent of
graduates and percent of dropouts classified into four
dietary quality sub-groups were summarized in Table 7.
Table 7. Percent of graduates and percent of dropouts

classified into four dietary quality groups based
on entry 24-hour food recalls

 

 

Dietary quality group Graduates Dropouts
(n=2454) (n=621)
Group 1 (met neither) 59% 62%
Group 2 (met only 5 30% fat) 26% 23%
Group 3 (met only 1-1-1-1-1) 10% 11%
Group 4 (met both) 5% 4%

 

Note:Group 1, graduates whose diets met neither criteria;
Group 2, graduates whose diets met only dietary fat
criterion (i.e., s 30% fat);

Group 3, graduates whose diets met only food group
criterion (i.e., G—V—F-M-D = 1-1-1-1-1);
Group 4, graduates whose diets met both criteria.

The percentage graduates and dropouts classified into

four dietary quality groups did not differ statistically

68

(Pearson Chi-square test, P>0.3). This means that the
quality of graduates’ diets did not differ from the quality

of dropouts’ diets at the time of entry.

Meal and food intake patterns of EFNEP participants at the
the of entry (Objective two)

Percent of subjects who skipped breakfast, lunch, and
dinner were 26%, 32%, and 24%, respectively. Twenty eight
percent of subjects ate less than 3 meals/snacks at the time
of entry. The subjects consumed an average of eight
different food items daily with a range from one to 22.

Table 8 presents the top 20 food items that contributed
the most number of servings in each of the five food groups
(i.e., grain, vegetable, fruit, meat, and dairy) and “other”
food group(i.e., added fat and sugar), the percent
contribution of each food to total intake, and the percent
subjects who consumed the food item.

The 20 major grain group contributors listed in Table 8
explained 45.5% of the total number of servings in the grain
group. The single most important contributor was white bread
(11.5% of total bread group), which was consumed second most

frequently among all foods (25.8% subjects consumed it).

69
Combination dishes such as hot dogs, macaroni, spaghetti,
pizza and sandwichs were among the top 20 food items that
contributed the most number of servings in the grain group.

The 20 major vegetable group contributors listed in
Table 8 explained 55.9% of the total number of servings in
the vegetable group. Various white potato products such as
french fries, mashed potato, and baked potato accounted for
25.2% of the total number of servings in the vegetable
group.

The 20 major fruit group contributors listed in Table 8
explained 78.0% of the total number of servings in the fruit
group.

The 20 major meat group contributors listed in Table 8
explained 39.7% of the total number of serving in the meat
group. Chicken products accounted for 11.8% of the total
number of servings in the meat group. Because meat was one
of the main ingredients in some combination dishes
(e.g.,spaghetti, hamburger, taco and sandwich), these food
items were among the top 20 food items that contributed the
most number of servings in the meat group as well as in the
bread group.

The 20 major dairy group contributors listed in Table 8

explained 79.7% of the total number of servings in the dairy

70

Table 8. Top 20 contributors of five major food groups and
“other” food group

 

% of the % of
Food items total number subjects
of servings consumed

 

Grain group

BREAD, WHITE

HOTDOG ON BUN

MACARONI AND CHEESE

SPAGHETTI W/MEATBALLS,MEAT&TOM SAUCE
BREAD, WHOLE WHEAT

HAMBURGER 1/4 LB, W/O MAYO
PIZZA, MEAT & VEGETABLE

TACO OR TOSTADO W/BEEF & CHEESE
TORTILLA,CORN

SANDWICH, PEANUT BUTTER/JELLY
PANCAKES, PLAIN

RICE, WHITE CONVERTED, COOKED
SANDWICH, BOLOGNA

BAGEL

SANDWICH, HAM AND CHEESE
PIZZA, MEAT

SANDWICH, HAM

CEREAL, ANY TYPE, READY-TO-EAT
CEREAL, CORN FLAKES

CRACKER, SALTINE

Subtotal

H

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UWbNNNNUWWWNthhbmeb-m
O‘NwOWW‘OHI-‘WUINHOWWIAQQQ

uh

 

Vegetable group

FRENCH FRIES, MCDONALDS

SALAD, LETTUCE W/.25 C TOMATO
POTATO, MASHED,CKD,W/FAT ONLY

TACO OR TOSTADO W/BEEF & CHEESE
CORN, CKD,ANY COLOR

BEANS, GREEN, FRZN, CKD

POTATO, FRNCH FRD FR FROZ,DEEP FRIED
POTATO, MASHED,W/MILK,NO FAT

SALAD, LETTUCE W/VEG(NO TOM/CAR)W/O DRES
PIZZA, MEAT & VEGETABLE

POTATO, HOME FRIES

BEEF, STEW W/POT,CAR,ONION,PEAS,GRAVY
POTATO, HASH BROWN,FROM FROZEN

CORN, ON COB

SPAGHETTI W/MEATBALLS,MEAT&TOM SAUCE
GREENS,COOKED,NO FAT

SOUP, VEGETARIAN VEGETABLE

POTATO, BAKED W/PEEL, W/O FAT

BEANS, STRING, CKD,

LASAGNA

Subtotal

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71

Table 8.(cont’d).

 

% of the % of
Food items total number subjects
of servings consumed

 

Fruit group

JUICE, ORANGE CANNED UNSWEETENED
JUICE , APPLE

JUICE, ORANGE,FROZEN,UNSWT,W/WATER
APPLE, RAW, PEEL, SLICED

BANANA

JUICE, ORANGE,FRESH

JUICE, JUICY-JUICE

ORANGE, RAW
MELON,WATERMELON,RAW

JUICE, GRAPE, SWEETENED

GRAPE, RAW

DRINK, ORANGE JULIUS

MELON, CANTALOUPE(MUSKMELON),RAW
APPLESAUCE,STEWED APPLES,WO/SUGAR
CEREAL, RAISIN BRAN

PEACHES,CKD OR CAN,HEAVY SYRUP
APPLESAUCE,STEWED APPLES,W/SUGAR
PEACHES,RAW

STRAWBERRIES, RAW, WHOLE

JUICE, CRANBERRY W/SUGAR
Subtotal

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Heat group

SPAGHETTI W/MEATBALLS,MEAT&TOM SAUCE
EGG, FRIED, SCRAMBLED W/O MILK
EGG, SCRAMBLED EGGS

CHICKEN, BBQ SAUCE, LEG AND THIGH
HAMBURGER 1/4 LB, W/O MAYO

TACO OR TOSTADO W/BEEF & CHEESE
CHICKEN, BREAST,W/SK,BDK/FRD W/FL
BEEF, STEAK

SANDWICH, TURKEY, APPROX 4 H OZ MEAT
CHICKEN, BREAST, ROASTED, 7 OUNCES
CHICKEN, LEG,BKD/FRIED W/FLOUR
CHICKEN, BREAST, NO SKIN, ROAST
BEEF, GOULASH W/NOODLES

PORK, CHOP,BREADED,FRIED

CHICKEN, WING,W/SK,BKD/FRD W/FLOUR
CHILI CON CARNE W/BEANS

SANDWICH, TUNA SALAD

BEEF, GROUND REGULAR

SANDWICH, BOLOGNA

HOTDOG ON BUN

Subtotal

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72

Table 8. (cont’d)

 

% of the % of
Food items total number subjects
of servings consumed

 

Dairy group
MILK, WHOLE 23.

MILK, LOW FAT 2% 12.
MILK, CONDENSED,SWEETENED,UNDILUTED
MACARONI AND CHEESE

PIZZA, MEAT & VEGETABLE

CHEESE, CHEDDAR/AMERICAN TYPE-OUNCE
CHEESE, AMERICAN & SWISS PROCESSED
MILK, SKIM OR NONFAT

PIZZA, MEAT

ICE CREAM, REG, FLAVORS OTHER THAN CHOC
TACO OR TOSTADO W/BEEF & CHEESE
SANDWICH, HAM AND CHEESE

MILK, LOW FAT 1%

LASAGNA

CHEESE, MOZZARELLA,PART SKIM
YOGURT,FRUIT VARIETY,LOWFAT MILK
NACHOS WITH CHEESE

SANDWICH, SUBMARINE

CHEESEBURGER, 1/4 LB, W/O MAYO

MILK, CHOC,SKIM,MILK BASE

Subtotal

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01

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“Other" food group (added fats and sugar)
DRINK, SODA, COKE, ROOT BEER

MILK, CONDENSED,SWEETENED,UNDILUTED
CHIP, POTATO

MILK, WHOLE

MACARONI AND CHEESE

DRINK, KOOL AID

DRINK, SODA,FRT-FLAV,W/CAFFEINE

ICE CREAM, REG, FLAVORS OTHER THAN CHOC
FRENCH FRIES, MCDONALDS, SMALL
BACON

POTATO, FRNCH FRD FR FROZ,DEEP FRIED
DRINK, SODA, 7-UP, GINGER ALE
CAKE,CHOCOLATE,DEVIL'S FOOD,W/ICING
MILK, LOW FAT 2%

BUTTER

PIZZA, MEAT & VEGETABLE

CHEESE, AMERICAN & SWISS PROCESSED
SYRUP, PANCAKE

CHIP, TORTILLA

EGG, SCRAMBLED EGGS

Subtotal

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* Less than 1% of subjects consumed this food item.

73

group. Whole milk and 2% low fat milk accounted for 36.2% of
the total number of servings of dairy group. Cheese products
and combination dishes with cheese were among the list of
top 20 contributors.

Table 8 also lists the 20 major “other” group
contributors, which explained 51.4% of the total number of
servings in the “other” food group. Four soft drinks
(coke/root beer, kool aid, fruit favored soda, and 7-
up/ginger ale) on the list together provided 18.4% of the
total number of servings in the “other" food group.
Condensed/sweetened/undiluted milk was ranked as second
major contributor in the “other" food group (7.6%), even
though only small proportion of the subjects consumed it.
This was due to its high sugar and fat content. Potato chips
alone provided 6.0% of the total number of servings in the
“other” food group. It was ranked as the third major
contributor in the “other" food group.

Table 9 presents the top 20 food items that contributed
most the intakes of calcium, iron, vitamin A, vitamin C, or
vitamin B6. The percent contribution of each food to the
total intake (in g, or mg), and the percent of total
subjects consuming the food item were listed.

The 20 major calcium contributors listed in Table 9

explained 54.4% of the total intake of calcium. Whole milk,

74
which was consumed by 25.5% of the subjects, provided most
of the total calcium intake (13.6%). Combination dishes with
cheese provided 13.3% of calcium intake. Despite their low
content of the calcium, white bread, soft drinks, and kool
aid were among the 20 major calcium contributors, ranking
5th, 9th, and 14th, respectively. This was because of the
large proportion of the total subjects who consumed these
food items (25.8%, 28.4%, and 10.3% of total subjects,
respectively). Calcium provided by 1 slice white bread, 1
fluid ounce kool aid, and 1 fluid coke/root beer was 30, 6,
and 2 mg, respectively (ERS User’s Guide, Version 3.0).

The 20 major iron contributors listed in Table 9
explained 29.6% of the total intake of iron. Six ready-to-
eat cereal products combined contributed 9.6% of the total
iron intake due to the fortification of nutrients. White
bread, which was consumed by 25.8% of subjects, was ranked
as the first single contributor (3.8% of total iron). 11.3%
of iron came from various combination dishes. Four food
items classified in the meat group were also among the list.

The 20 major vitamin A contributors listed in Table 9
explained 51.4% of the total intake of vitamin A. The first
three major vitamin contributors (liver, cooked carrots, and
raw carrots) were consumed by less than 3% of the subjects.

Food items classified in the vegetable group contributed

75

Table 9. Top 20 contributors of five micro-nutrient intake
by food groups and food items

 

Food items Rank %total %subjects

 

Calcium
Dairy group

MILK, WHOLE 1 13.6 25.5
MILK, LOW FAT 2% 2 7.6 12.8
MILK, CONDENSED,SWEETENED,UNDILUTED 3 5.6 3.8
CHEESE, CHEDDAR/AMERICAN TYPE-OUNCE 7 1.9 3.1
CHEESE, AMERICAN & SWISS PROCESSED 8 1.8 5.9
MILK, SKIM OR NONFAT 10 1.4 2.6
ICE CREAM, REG, FLAVORS OTHER THAN CHOC 16 1.1 3.3
MILK, LOW FAT 1% 18 0.9 1.4
YOGURT,FRUIT VARIETY,LOWFAT MILK 19 0.9 1.3

Combination dishes

 

MACARONI AND CHEESE 4 5.0 6.7
PIZZA, MEAT & VEGETABLE 6 2.1 4.0
PIZZA, MEAT 11 1.4 2.9
SPAGHETTI W/MEATBALLS,MEAT&TOM SAUCE 12 1.4 4.4
TACO OR TOSTADO W/BEEF & CHEESE 13 1.3 4.1
SANDWICH, HAM AND CHEESE 15 1.1 2.9
LASAGNA 17 1.0 1.9
Grain group
BREAD, WHITE 5 2.5 25.8
Meat group
EGG, SCRAMBLED EGGS 20 0.8 6.9
Other group
DRINK, SODA, COKE, ROOT BEER 9 1.7 28.4
DRINK, KOOL AID 14 1.3 10.3
Iron
Grain group
BREAD, WHITE 1 3.8 25.8
CEREAL, RAISIN BRAN 3 2.4 1.1
CEREAL, TOTAL 4 2.1 *
CEREAL, CAPTAIN CRUNCH 7 1.8 1.2
CEREAL, CHEERIOS 8 1.7 3.3
RICE, WHITE CONVERTED, COOKED 9 1.4 3.1
CEREAL, CORN FLAKES 16 0.8 5.2
CEREAL, FRUIT LOOPS 17 0.8 1.3
Combination dishes '
SPAGHETTI W/MEATBALLS,MEAT&TOM SAUCE 2 2.6 4.4
HAMBURGER 1/4 LB, W/O MAYO 5 1.9 4.9
MACARONI AND CHEESE 6 1.8 6.7
PIZZA, MEAT & VEGETABLE 10 1.3 4.0
TACO OR TOSTADO W/BEEF & CHEESE 11 1.1 4.1
HOTDOG ON BUN 12 1.0 4.7
LASAGNA 18 0.8 1.9
PIZZA, MEAT 19 0.8 2.9
Meat group
CHILI CON CARNE W/BEANS 13 0.9 1.6
BEEF, STEAK 14 0.9 3.7
EGG, FRIED, SCRAMBLED W/O MILK 15 0.9 8.0
EGG, SCRAMBLED EGGS 20 0.8 6.9

 

76

Table 9. (Cont’d)

 

 

 

Food items Rank %total %subjects
Vitamin A
Meat group
LIVER, BEEF, FRD OR BRLD, NO COATING 1 8.4 *
EGG, FRIED, SCRAMBLED W/O MILK 10 2.0 8.0
EGG, SCRAMBLED EGGS 13 1.9 6.9
Vegetable group
CARROTS, COOKED 2 5.8 2.0
CARROTS, RAW, ONE CARROT 3 4.8 1.1
GREENS,COOKED,NO FAT 11 2.0 1.7
SWEETPOTATO, BOIL, MASHED 12 2.0 *
CARROTS, RAW, CUP 15 1.4 1.1
VEGETABLE, MIX, CANNED 19 1.2 1.3
VEGETABLE, MIX 20 1.1 *
Dairy group
MILK, LOW FAT 2% 4 2.8 12.8
MILK, WHOLE 6 2.6 25.5
MILK, CONDENSED,SWEETENED,UNDILUTED 18 1.3 3.8
Combination dishes
MACARONI AND CHEESE 5 2.7 6.7
BEEF, STEW W/POT,CAR,ONION,PEAS,GRAVY 16 1.4 1.6
SPAGHETTI W/MEATBALLS,MEAT&TOM SAUCE 17 1.3 4.4
Grain group
, TOTAL 7 2.4 *
CEREAL, CORN FLAKES 8 2.3 5.2
CEREAL, ANY TYPE, READY-TO-EAT 9 2.1 4.3
CEREAL, CHEERIOS 14 1.9 3.3
Vitamin C
Fruit group
JUICE, ORANGE CANNED UNSWEETENED 1 11.3 8.5
JUICE, ORANGE,FROZEN,UNSWT,W/WATER 2 6.8 5.2
JUICE, ORANGE,FRESH 3 6.5 5.9
ORANGE, RAW 5 2.9 3.2
JUICE-DRINK,FRUITADES,FRUITPUNCHES 6 2.5 1.6
JUICE, GRAPE, SWEETENED 8 2.2 2.5
JUICE, JUICY-JUICE 10 1.9 2.0
JUICE, CRANBERRY W/SUGAR 13 1.6 *
DRINK, ORANGE BRKFST DRK FROM FROZ CONC 14 1.1 *
DRINK, ORANGE JULIUS 15 1.1 *
Other group
CHIP, POTATO 4 3.9 10.8
DRINK, KOOL AID 12 1.7 10.3
Combination dishes
SPAGHETTI W/MEATBALLS,MEAT&TOM SAUCE 7 4 4.4
PIZZA, MEAT & VEGETABLE 11 1 9 4.0
HOTDOG ON BUN 16 1 4.7
Vegetable group
FRENCH FRIES, MCDONALDS 9 2.0 8.7
GREENS,COOKED,NO FAT 17 1.0 1.7
POTATO, FRNCH FRD FR FROZ,DEEP FRIED 19 1.0 5.1
POTATO, MASHED,CKD,W/FAT ONLY 20 0.9 5.0

Grain group
CEREAL, TOTAL 18

p
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77

Table 9. (Cont’d)

 

 

Food items Rank %total %subjects
Vitamin B6
Fruit group
BANANA 1 3.2 5.9
JUICE, ORANGE CANNED UNSWEETENED 3 1-8 3-5
Other group
CHIP, POTATO 2 2-5 10-9
Combination dishes
SPAGHETTI W/MEATBALLS,MEAT&TOM SAUCE 3 2-2 4-4
TACO on TOSTADO W/BEEF & CHEESE :3 i-é 1';
HAMBURGER 1/4 LB, W/O MAYO ‘ '
Vegetable group 4 1 9 5 0
POTATO, MASHED,CKD,W/FAT ONLY 7 1.8 8.7
FRENCH FRIES, MCDONALDS, SMALL 16 1‘4 5'1
POTATO, FRNCH FRD FR FROZ,DEEP FRIED 19 1'1 5’0
POTATO, MASHED,W/MILK,NO FAT ’ '
Grain group
cmmmuu'nnnL 5 l 9 *
CEREAL, CORN FLAKES 6 1'9 5 2
CEREAL, ANY TYPE, READY-TO-EAT 10 1‘7 4'3
CEREAL, CHEERIOS 12 1‘6 3'3
CEREAL, CAPTAIN CRUNCH 13 1.5 1.2
Dairy group
MILK' WHOLE 9 1.8 25.5
Meat group 11 1 7 3 6
CHICKEN, BREAST,W/SK,BDK/FRD W/FL 14 1'5 3'1
CHICKEN, BREAST, NO SKIN, ROAST 15 1'4 '*
CHICKEN, BBQ SAUCE, LEG AND THIGH 17 1'4 1 3
CHICKEN, BREAST, ROASTED, 7 OUNCES ’ '

 

* Less than 1% of subjects consumed this food item.

78

18.3% of total vitamin A intake. The four fortified cereals
combined provided 8.7% of the total vitamin A intake.

The 20 major vitamin C contributors listed in Table 9
explained 54.7% of the total intake of vitamin C. 37.9% of
total vitamin C came from the food items classified in the
fruit group with canned orange juice leading the list.
Potato chip, which was ranked as the number six most
frequently consumed food item (consumed by 10.8% of
subjects), was the fourth major contributor for vitamin C.
One ounce of potato chips provided 12mg vitamin C (ERS
User’s Guide, Version 3.0).

The 20 major vitamin B6 contributors listed in Table 9
explained 34.4% of the total intake of vitamin B6. Banana
was ranked as the number one most important contributor of
vitamin B6 (3.2% of total). Potato chips were ranked as the
number two (2.5% of total). One ounce of potato chips
provided 0.14 mg vitamin B6 (ERS User’s Guide, Version 3.0).
Five specific cereals combined provided 8.6% of the total
vitamin B6 intake of the Michigan EFNEP participants. White
potato products provide 6.2% of vitamin B6. From the meat
group, chicken contributed 6% of vitamin B6.

Table 10 lists 20 major fiber contributors. These 20
food items explained 32% of total intake of fiber. Potato

chips, spaghetti with meatballs, and french fries were the

79

first three fiber contributors (3.2%, 2.6% and 2.6% of total
fiber, respectively). Fiber provided by 1 ounce of potato
chips, 1 cup spaghetti with meatballs, and 10 french fries
was 1.3, 3.4, and 1.7 g, respectively (ERS User’s Guide,

Version 3.0).

Table 10. Top 20 contributors of dietary fiber by food
groups and food items

 

Food items Rank %total %subjects

 

Other group

CHIP, POTATO 1 3.2 10.8
TORTILLA,CORN 9 .4 2
Combination dishes

SPAGHETTI W/MEATBALLS,MEAT&TOM SAUCE 2 2.6 4.4
TACO OR TOSTADO W/BEEF & CHEESE 7 1.7 4.1
MACARONI AND CHEESE 8 1.6 6.7
PIZZA, MEAT & VEGETABLE (1/8 of 12" PIE) 10 1.4 4.0
CHILI CON CARNE W/BEANS 12 1.3 1.6
Vegetable group

POTATO, FRNCH FRD FR FROZ,DEEP FRIED 3 2.6 5.1
POTATO, MASHED,CKD,W/FAT ONLY 5 2.0 5.0
CORN, CKD,ANY COLOR 11 1.4 5.8
POTATO, MASHED,W/MILK,NO FAT 14 1.2 3.1
VEGETABLE, MIX (CRN,LMA,GBNS,CAR,CK) 16 1.1 *
Bread group

BREAD, WHOLE WHEAT 4 . 4.9
CEREAL, CHEERIOS 13 1.3 3.3
CEREAL, RAISIN BRAN 20 1.0 1.1
Fruit group

APPLE, RAW, PEEL, SLICED 6 1.8 6.0
BANANA 15 1.2 5.9
ORANGE, RAW 18 1 0 3.2
Meat group

BEANS, BAKED CND, W/SWEET SAUCE 17 1.1 1.1
BEANS, PINTO, CKD W/FAT 19 1.0 *

 

* Less than 1% of subjects consumed this food item.

80

Overall dietary quality of EFNEP participants at the time of
entry (Objective three)

At the time of enrollment, only 16% of the subjects
consumed at least one serving from each five major food
groups of the Food Guide Pyramid (Table 11). Only 3.2% of
the subjects consumed the minimum number of servings from
each five major food groups recommended for their category
(i.e., Grain-Veg—Fruit-Meat-Dairy = 6-3-2-2-2 for female
aged 25 years or older; and 6-3-2-2-3 for female aged 24
years or younger; and pregnant/nursing female, all ages).
Food groups which skipped most frequently by the subjects
were fruit group(53%), followed by the dairy group (24%) and
vegetable group (20%).

The average daily energy intake of all subjects at the
time of enrollment was 1700 Kcal (Table 12). Carbohydrate,
protein, and fat contributed 49%, 16% and 36% of the daily
energy intake, respectively. Daily protein intake for
pregnant/nursing, young female, and adult female was above
or close to 100% RDA: 60-65, 59, and 63 g/day, respectively.

The average fiber density for all subjects (6 g/1000
Kcal) was only half of the recommended level (12.5 g/1000
Kcal). Intakes of energy, protein, carbohydrate, and fat of
pregnant/nursing subjects were significantly higher than

those of non-pregnant/non-nursing subjects (p<.001).

81

Table 11. Daily intake (in servings) of five major food
groups by the subjects at the time of entry

 

 

 

 

(n=3866)
Food groups MeaniSD Number of Percent of
Median Servingsa subjects
(servings) (%)
Grain 4.813.1 0 4.2
4.3 0-1 5.8
0-6 67.1
2 6 32.9
Vegetable 2 5:2.7 0 20.0
2 0 0-1 25.4
0-3 62.8
2 3 37.2
Fruit 1.011.? 0 53.0
0 0 0-1 60.9
0—2 79.7
2 2 20.3
Meat 2.111.? 0 5.3
1 9 0-1 21.9
0-2 55.2
2 2 44.8
Dairy 1.4:1.5 0 24.2
1.0 0-1 44.7
0-2 71.5
2 2 28.5
2 3 12.3
G-V-F-M-Db 1-1-1-1-1 15.6
6-3-2-2-2(3) 3.2
a. The recommended minimum number of servings from each of

the five major food groups of Food Guide Pyramid are:
Grain-Veg—Fruit-Meat-Dairy = 6-3—2-2-2 for female adult
(25+ yr), and 6-3-2-2-3 for female young (< 24 yr) and
pregnant/nursing female (all age).

b. G-V-F-M-D represents Grain-Veg-Fruit-Meat-Dairy.

82

 

 

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83

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84

The average fiber density of the diets consumed by
pregnant/nursing subjects (6.1 g/1000 Kcal) however was
significantly less than that of the non-pregnant/non-nursing
subjects (6.4:4.6 g/1000 Kcal, p<.05).

In our study, eighteen percent of the total subjects
took nutrient supplements: 47% of pregnant/nursing subjects
took nutrient supplements and only 10% of non-pregant/non-
nursing subjects did. 22% of subjects aged 24 or younger
took nutrient supplements, while 15% of subjects aged 25 or
older took nutrients. However, nutrients derived from
supplements were not included in the daily nutrient intake
totals in the present study because they were not
quantifiable. Based on 24-hour food recalls, for five
nutrients (i.e., calcium, iron, vitamin A, vitamin C, and
vitamin B6), the percentages of subjects who reported intake
less than 75% RDA differed significantly among the three
demographic sub—groups (Table 13). Calcium appeared to be a
problematic nutrient for young females (13-24 yr), because
75% subjects in this category failed to meet 75% of RDA for
calcium. Iron intakes were low for pregnant/nursing women
with 79% of subjects in this category failing to meet 75% of
the RDA. Overall, the percent subjects who had inadequate
intakes (less than 75% RDA) ranged from 46% to 65% for the
five nutrients.

The four sub-groups of dietary quality were further

85
validated by MAR-5 scores <75 for sensitivity and

specificity. Odds ratios of having MAR-5 score less than 75

were calculated (Table 14).

Table 14. Mean MAR-5 score, and Odds Ratios of having MAR-5
< 75 by four dietary quality groups

 

 

Dietary quality n MAR-5a % ORs°
groups % mean:SD (MAR-5<75)b 95% CI
Group 1 2287 61:23 70 7.8
(Met neither) 59% 5.4-11.1
Group 2 976 56:25 74 9.4
(Met s 30% fat only) 25% 6.5-13.7
Group 3 420 84:14 24 1.1
(Met 1-1-1-1-1 only) 11% 0.9-1.6
Group 4 183 85:14 23 1.0
(Met both) 5%

 

Note:Group 1, graduates whose diets met neither criteria;
Group 2, graduates whose diets met only dietary fat
criterion (i.e., s 30% fat);

Group 3, graduates whose diets met only food group
criterion (i.e., G-V-F-M-D = 1-1-1-1-1);
Group 4, graduates whose diets met both criteria.

a. MAR-5 score = Average NAR scores for 5 nutrients:
calcium, iron, vitamin A, vitamin c, and vitamin B6.
NAR = (nutrient intake/RDA)x100. NAR >100 truncated at
100.

b. Percent of subjects whose MAR-5 < 75.

C. Odds Ratio of having MAR-5 < 75, plus 95% confidence
interval.

Sensitivity and specificity for the first criterion,
i.e., consume at least one serving from each of the five
major food groups, were 94% and 32%, respectively.

Sensitivity was defined as the proportion of subjects whose

86

dietary quality was low (by MAR-5) and who were classified
as having low dietary quality by the first criterion. A high
sensitivity was required to accurately classify subjects at
nutritional risk by the criterion one. Specificity was
defined as the proportion of participants whose dietary
quality was high (by MAR-5) and were classified as high
dietary quality by the first criterion.

Essentially, subjects in dietary quality group 1 and 2
were the subjects whose diets were inadequate by the first
criterion (i.e., diets failed to included at least one
serving from each of the five major food groups of the Food
Guide Pyramid), regardless of fat contents of the diets.
Subjects in dietary quality groups 3 and 4 were the subjects
whose diets were above the first criterion (i.e., diets
included at least one serving from each of the five major
food groups of the Food Guide Pyramid), regardless of the
fat content of diets.

In computation of odds ratio, dietary quality group 4
(i.e., met both criteria) was used as reference group. Odds
of having MAR-5 < 75 for subjects in dietary quality group 3
(i.e., met only 1-1-1-1-1) did not differ from those for
subjects in dietary quality group 4 (ORs = 1.1, 95% CI =
0.9, 1.6). Odds of having MAR-5 < 75 for subjects in dietary
quality group 1 (i.e., met neither criterion) and dietary

quality group 2 (i.e., met only 3 30% fat) were

87

significantly higher than those for subjects in dietary
quality group 4 (ORs = 7.8, 95% CI = 5.4, 11.1; and ORs =
9.4, 95% CI = 6.5, 13.7; respectively). More specifically,
subjects who met neither criteria were approximately 8 times
more likely to have MAR-5 score less than 75. Subjects who
met only 5 30% fat were approximately 9 times more likely to
having MAR-5 score less than 75.

In summary, the majority of subjects in our study had
relatively low quality diets at the time of entry. Only 5%
of subjects’ diets contained at least one serving from each
of the major five food groups and s 30% daily energy intake
from fat. Including at least one serving from each of the
five major food groups in the diet was significantly
associated with having MAR-5 score less than 75 with
sensitivity and specificity of 94% and 32%, respectively.
Intakes of calcium and iron were the most problematic
nutrients for young female subjects (13-24 yr), and

pregnant/nursing women, respectively.

Factors associated with low dietary quality (Objective four)
The fourth objective was to identify undesirable food
behaviors that were associated with the low dietary quality
diets classified by the objective three. Specially, we
hypothesized that low dietary quality diets were predicted

by (1) high intake of food from the “other” food group

88

(i.e., added fat and sugar, 10 to 20 servings and > 20
servings vs 5 10 servings, respectively); and (2) low
frequency of consumption of meals/snacks consumption (< 3
meals/day vs 2 3 meals/day), while controlling for energy
intake in the model. We also investigated if the low dietary
quality was associated with demographic factors such as
maternal status, race, participation in other social
assistant program, family size, place of residency, age, and
income.

In full interaction model of logistic analysis to
predict the dietary quality, both undesirable food behaviors
(i.e., high intake of food from the “other" food group and
consumed less than three meals/snacks per day) were found to
interact significantly with energy intake (p<.001).
Subsequently, energy intake was controlled in the final main
effect model by using three energy intake levels: low,
moderate and high. Low energy intake level included subjects
whose energy intake was less than one standard deviation
below the mean (i.e., <803 kcal, 11%). Moderate energy
intake level included subjects whose energy intake was
between one standard deviation below and above the mean
(i.e., 803-2596 Kcal, 75%). High energy intake level
included subjects whose energy intake was more than one
standard deviation above the mean (i.e., >2596 Kcal, 14%).

For the subjects whose diets were in the low energy

89
intake group, all diets (100%) were low in dietary quality
on the basis of not including at least one serving of each
from five major food groups and deriving > 30% of energy
from fat. Low energy intake was thus a single most important
predictor for low dietary quality of subjects in Michigan
EFNEP participants.

For the subjects whose diets were in the high energy
intake group, all variables examined were removed from the
final main effect model. This means that low dietary quality
was not be explained by any of variables examined for the
diets in this high energy intake group.

For subjects whose diets were in the moderate energy
intake group, both undesirable food behaviors (i.e., high
intake of food from the “other” food group and consumption
of less than three meals/snacks per day) increased
significantly the odds for low dietary quality (p<0.05).
Other variables that increased the odds for low dietary
quality were: maternal status (non pregnant/non-nursing vs.
pregnant/nursing) and race (white, black vs. other origin
respectively). Adjusted odds ratios for factors associated
with low dietary quality are summarized in Table 15 for
subjects whose diets were in the moderate energy intake
group and for all subjects included in the objective four
study.

When the final main effect model was performed for

90

Table 15. Adjusted Odds Ratios54and 95% confidence intervals
of factors associated with low dietary quality

 

 

 

Subjects whose .All subjects
diets were in in objective
Factors the moderate four study
energy intake (n=2470)
group
(n=1861)
Intake of
“other" food group 8.4(4.5, 15.8) 3.2(1.9, 5.5)
> 20 servings 3.0(1.9, 4.7) 1.5(1.1, 2.3)
10 to 20 servings 1.0 1.0
s 10 servings
Frequency of
Meals/Snacks 2.6(1.4, 4.7) 3.4(2.0, 5.8)
< 3 meals/snacks 1.0 1.0
2 3 meals/snacks
Maternal status
Non Pregnant/Non nursing 2.3(1.6, 3.3) 2.2(1.6, 3.0)
Pregnant/Nursing 1.0 1.0
Race
White 2.0(1.2, 3.2) 2.0(l.3, 3.0)
Black 2.0(1.2, 3.3) 2.1(1.4, 3.3)
Other 1.0 1.0

 

a. Adjusted for listed factors plus energy intake.

91

subjects whose diets were in the moderate energy intake
group, those subjects who consumed between 10 to 20 servings
of “other” food group (i.e., added fat and sugar) had three
times higher odds for having low quality diets (adjusted
OR=3.0, 95% CI=1.9, 4.7) than those who consumed s 10
servings of other food group. Subjects who consumed more
than 20 servings of “other” food group had approximately
eight times higher odds for having low quality diets
(adjusted OR=8.4, 95% CI=4.5, 15.8) than those who consumed
s 10 servings of other food group. Increased intake of foods
from the “other" food group was clearly associated with
increased risk of having low dietary quality. Subjects who
ate less than three meals/snacks a day were approximately
three times more likely to have low quality diets (adjusted
OR=2.6, 95% CI=1.4, 4.7) than those who ate at least three
meals a day.

Non pregnant/non-nursing subjects had approximately two
times higher odds for having low quality diets (adjusted
OR=2.3, 95% CI=1.6, 3.3) compared to those who were
pregnant/nursing. Compared to other ethnic groups (Hispanic,
Asian/Pacific Islander, American Indian/Alaskan Native),
whites and blacks were approximately two times more likely
to have low dietary quality (adjusted OR = 2.0, 95% CI =
1.2, 3.2; and adjusted OR = 2.0, 95% CI = 1.2, 3.3;

respectively).

92

The final main effect model was performed for all
subjects in the objective four study, and it produced
similar results to those whose diets were in the moderate
energy intake group. Both undesirable food behaviors plus
maternal status and race were significantly associated with
low dietary quality while controlling for energy intake.
However, without classifying subjects into three energy
intake levels, the precise relationship between factors with
low dietary quality would be overlooked. In low energy
intake group, low energy intake itself was a single
important risk factor for low dietary quality. In high
energy intake level, low dietary quality was not explained
by any of the factors we investigated.

In summary, when the subjects whose energy intake was
above or below one standard deviation from the mean were
excluded (14% and 11%, respectively), we confirmed clearly
the association between the two undesirable food behaviors
and low dietary quality. Subjects with increased intake of
food from the “other” food group had increased risk of low
dietary quality due to a large proportion of their energy
intake that came from added fats and sugars. Subjects who
consumed less than three meals/snacks per day had high
chance to have low quality diets due to reduced probability

to eating a variety of foods.

93
Dietary changes by the EFNEP graduates (Objective five)

At the exit of the EFNEP, fewer graduates (40%) were
classified into the low dietary quality group (i.e.,met
neither criterion) than did at the time of entry (59%). More
graduates (15%) moved into the high dietary quality group
(i.e., met both criteria) at the time of exit than did at

the time of entry (5%) (Table 16).

Table 16. Percentage of graduates classified into four
dietary quality groups at the time of entry and
exit (n=2454)

 

 

Dietary quality group Entry Exit
Group 1 (met neither) 59% 40%
Group 2 (met only 5 30% fat) 26% 17%
Group 3 (met only 1-1-1—1-1) 10% 28%
Group 4 (met both) 5% 15%

 

Note:Group 1, graduates whose diets met neither criteria;
Group 2, graduates whose diets met only dietary fat
criterion (i.e., s 30% fat);

Group 3, graduates whose diets met only food group
criterion (i.e., G-V-F-M—D = 1-1-1-1-1);
Group 4, graduates whose diets met both criteria.

Fourty three percent of graduates included at least one
serving from each of the five major food groups in their
diets at exit, compared to 15% graduates did so at entry.
Only slightly more graduates (32%) limited fat intake to

less than 30% daily energy intake at the exit than did at

94

the entry (31%). This means that the first criterion (i.e.,
met 1-1-1-1-1) was achieved more effectively by participants
upon the completion of the program than the second criterion
(i.e., met 330% fat).

As a group, consumption of the five food groups
measured by the food group score increased significantly,
while decreasing the percentage of energy intake from fat
significantly (Table 17). We assessed the extent of dietary
changes made between entry and exit of the EFNEP by the four
dietary quality groups. We hypothesized that the graduates
who failed to meet one or both dietary quality criterion at
the time of entry would make more dietary changes at the
time of exit than graduates who had met both dietary quality
criterion at the time of entry.

The food group scores for graduates in the three
dietary quality groups (group 1, group 2, and group 3)
differed significantly between the entry and exit (p<.0001,
Table 17). The exception was dietary quality group 4 (i.e.,
met both criteria). In both dietary quality group 1 (i.e.,
met neither criterion) and dietary quality group 2 (i.e.,
met only 3 30% fat), graduates failed to include at least
one serving from each of the five major food groups in their
diets at the time of entry. Graduates in both groups
increased their food group scores significantly by

increasing their consumptions of five food groups measured

Table 17. Average food group scores,
percent energy from fat,

95

food group servings,
and energy intake for

graduates by four dietary quality groups (n=2454)

 

 

 

 

 

 

Ent Exit

Dietary quality groups mean:SD mean:SD t-value

Group 1

(Met neither, n=1443)

Food Group Score (points) 2.6:0.8 3.6:0.9 30.23**
Grain (servings) 4.7:3.2 5.8:3.0 10.66**
Veg (servings) 2.4:3.0 3.4:3.1 9.43**
Fruit (servings) 0.5:1.3 1.6:2.0 17.74**
Meat (servings) 2.2:1.8 2.5:1.6 4.76**
Dairy (servings) 1.3:1.5 1.9:1.6 13.24**

Energy from fat (%) 40.7:7. 0 35. 6:8. 6 -18.71**

Energy intake (Kcal) 1667:873 2011:877 11.61**

Group 2

(Met only s 30% fat, n=642)

Food Group Score (points) 2.4:1.0 3.6:1.0 22.85**
Grain (servings) 4.3:3.0 6.2:3.1 11.84**
Veg (servings) 2.1:2.1 3.5:2.7 10.58**
Fruit (servings) 1.1:2.1 1.6:1.8 4.76**
Meat (servings) 1.4:1.3 2.3:1.7 10.50**
Dairy (servings) 1.0:1.4 2.2:1.9 14.42**

Energy from fat (%) 23.5:6. 4 33.0:8. 9 22.75**

Energy intake (Kcal) 1389:782 2056:955 14.93**

Group 3

(Met only 1-1-1-1-1, n=256)

Food Group Score (points) 4.2:0.6 3.8:0.9 -5.67**
Grain (servings) 5.8:2.8 5.9:2.8 0.42
Veg (servings) 3.8:3.2 3.4:2.2 -1.54
Fruit (servings) 2.2:1.2 1.9:2.1 -1.56
Meat (servings) 2.9:1.7 2.6:1.7 -2.11*
Dairy (servings) 2.3:1.3 2.2:1.6 -0.69

Energy from fat (%) 38.8:5. 4 35.2:8. 3 -5.89**

Energy intake (Kcal) 2287:860 2050:824 -3.73**

Group 4

(Met both, n=113)

Food Group Score (points) 4.2:0.5 4.0:0.8 -1.43
Grain (servings) 6.1:2.6 6.6:3.0 1.59
Veg (servings) 3.5:2.3 3.6:2.2 0.48
Fruit (servings) 2.8:2.1 2.5:2.0 -1.29
Meat (servings) 2.2:1.0 2.4:1.4 1.13
Dairy (servings) 2.6:1.8 3.0:2.2 1.41

Energy from fat (%) 25.4:4.0 32.2:8. 1 8.49**

Energy intake (Kcal) 2167:831 2346:932 1.72

A11 graduates (n=2454)

Food Group Score (points) 3.0:1.0 3.6:0.9 31.78**

Energy from fat (%) 35.3:10.1 34.7:8.7 2.23*

Energy intake (Kcal) 1682:887 2042:898 15.62**

 

* p<.05,

** p<.0001 by paired t-test between entry and exit

96
by serving numbers at exit. Graduates in dietary quality
group 3 (i.e., met only 1-1-1-1-1) decreased their food
group scores slightly, because they consumed less meat at
exit than did at entry.

Graduates in both dietary quality group 1 (i.e., met
neither criteria) and dietary quality group 3 (i.e., met
only 1-1-1-1-1 criterion), had > 30% of energy from fat at
the entry, decreased the percent energy intake from fat
significantly at the end of the program (p<0.05). On the
other hand, graduates in both dietary quality group 2 (i.e.,
met only 530% fat) and dietary quality group 4 (i.e., met
both criteria), had s 30% energy from fat at the entry, but
increased the percent energy from fat significantly at the
end of the program (p<0.05).

There was no significant change observed in energy
intake for dietary quality group 4 (i.e., met both
criteria). Energy intake increased significantly from the
entry to exit in dietary quality group 1 (i.e., met neither
criterion) and dietary quality group 2 (i.e., met only 530%
fat). Energy intake decreased significantly in dietary
quality group 3 (i.e., met only 1-1-1—1-1).

Overall, graduates who were initially in the low
dietary quality group (i.e., group 1, met neither criterion)
made more dietary changes in two positive directions than

those in other groups. Graduates who were initially in

97
dietary quality group 1 not only increased their consumption
of five major food groups but also decreased their intake of
fat.

The average changes in food group score differed
significantly among the four dietary quality groups, when
controlling for changes in energy intake and number of EFNEP
visits in the ANOCOVA model (Table 18). This finding
confirmed our hypothesis that graduates with relatively low
dietary quality at the time of entry made more positive
dietary changes at the time of exit than those graduates
whose dietary quality was high at the time of entry. Initial

dietary quality can be used to predict the dietary changes.

Table 18. Dietary changes (mean:SD) of EFNEP graduates among
four dietary quality groups

 

Group 1a Group 2a Group 3‘ Group 48

 

 

(n=1443) (n=642) (n=256) (n=113) F°
Changes
in FGSb 1.0:1.2 1.1:1.3 -.4:1.0 -.1:0.9 100.93**
Changes
in % fat -5.l:10.3 9.5:10.6 -3.6:9.7 6.8:8.5 312.22**
a. Group 1, graduates whose diets met neither criteria;

Group 2, graduates whose diets met only dietary fat

criterion (i.e., s 30% fat);

Group 3, graduates whose diets met only food group

criterion (i.e., G-V-F-M-D = 1-1-1-1-1);

Group 4, graduates whose diets met both criteria.

FGS stands for food group score. It ranges 0 - 5.

c. Controlling for changes of energy intake and number of
EFNEP visits. ** P < .0001

O‘

Chapter Five

DISCUSSION, CONCLUSION, AND IMPLICATION

Discussion

In 1994—95, Michigan EFNEP made a positive impact on
the dietary changes of its participants. As a group,
consumption of the five food groups measured by the food
group score increased significantly, while the percentage of
energy intake from fat decreased significantly. The findings
are consistent with EFNEP's documented success in helping
families improve dietary adequacy (USDA, 1994).

As individuals, graduates improved their diets to
different extent. Compared to participants who had
relatively high quality diets at the time of entry, those
who had low quality diets improved their diets to a greater
degree by the time of exit. Previously, Kateregga (1981)
pointed out that the EFNEP program in Michigan was not
equally effective for all participants. In Kateregga’s

study, 54% graduates improved the food group scores after

98

99

the program, while the rest did not change or declined in
scores. The author reported that the entry food group score
was a crucial indicator of dietary improvement resulting
from participation in EFNEP. Similarly, we also observed
that participants whose initial food group scores were low
tended to have the greatest improvement.

In a Maryland EFNEP study, Amstutz and Dixon (1986)
found that the graduates, as a group, did not decrease their
consumption of “fifth food group" of the Daily Food Guide
(i.e., fats, sweets, and alcohol which are equivalent to the
“other” food group of the Food Guide Pyramid). After
partitioning the group into a high and a low consumption
group of the “fifth food group", the authors found that the
high consumption group decreased significantly the number of
“fifth food group" servings upon the completion of the
program. They did not report what happened to the low
consumption group.

Previous studies failed to identify key demographic
variables that may predict the dietary improvement of EFNEP
participants (Amstutz and Dixon, 1986, Torisky et al.,
1989). Although we know that participants as a group improve

dietary adequacy, little is known as to who makes the

100

changes, and to what extent the changes are made. In our
study, we took another approach. Instead of investigating
directly the relationship between the dietary change and
associated factors, we identified factors associated with
the low dietary quality. This information is necessary to
better understand EFNEP participants and for EFNEP to
efficiently allocate its effort and resources.

We found that low dietary quality at the time of entry
was significantly associated with two undesirable food
behaviors when controlling for confounding variables (i.e.,
race, maternal status, and energy intake). These two
undesirable food behaviors were high intake of added fat and
sugar foods and low frequency of meals/snacks consumption.

The association between high fat intake and chronic
disease condition is well established (The Surgeon General’s
Report, 1988). The direct linkage between high intake of
added sugar and the development of health conditions such as
diabetes, cardiovascular disease or high blood pressure has
not yet been proved (NRC, 1989, Glinsmann et al., 1986;
Bierman, 1979).

Concerns about high intake of added sugars are relative

to increased incidence of dental caries and decreased

101

nutrient density of diets especially for people who have low
energy needs (Dietary Guidelines for Americans, 1995; Food
Guide Pyramid, 1992). Baghurst et al.(1992) and Lewis et
al.(1992) have shown that people with a higher percentage of
energy derived from added sugar in their diets had lower
percentage of dietary energy from fat and lower intakes of
micro-nutrients than did people with a relatively lower
dietary energy from added sugars. Given the need to meet
energy requirements, reduction in added sugars might lead to
increased relative fat consumption unless guidance is
provided. Both studies raised the caution that educational
messages focusing on reduction of added sugar should be
specific enough to provide the healthy food choices to
replace the energy contributed by sugar.

In our study, all participants with low energy intake
at the time of entry (i.e., energy intake below one standard
deviation from the mean, i.e., < 803 Kcal) were classified
into the low dietary quality group based on the two dietary
quality criteria established for the present study:
(1)including at least one serving from each of the five
major food groups as defined by the Food Guide Pyramid

(i.e., Grain-Vegetable-Fruit-Meat-Dairy = 1-1-1—1-1); and

102

(2) limiting fat intake to s 30% daily energy intake. We
concluded that low energy intake itself was a risk factor
for low dietary quality. This finding is consistent with the
finding of Murphy et al.(1992). They reported that energy
intake is the best single predictor of the nutritional
adequacy of the US adult diet.

In our study, the frequency of skipping meals by
subjects was similar for breakfast, lunch, and dinner (26%,
32%, and 24%, respectively). We found that high frequency of
skipping meals/snacks was a risk factor for low dietary
quality. Morgan et al. (1986) demonstrated that omission of
breakfast had a significantly negative impact on the diet
quality, particularly among adult females. Stanton and Keast
(1989) reported that serum cholesterol levels were high
among breakfast skippers. By studying meal skipping pattern
and nutrient intake in a southern rural elderly population,
Lee et al. (1996) found that meal skippers were more likely
to be smokers, younger elders, female, less educated, lower
socioeconomic status, eat alone, and had high BMI. Authors
also reported that though meal skippers snacked more
frequently, their nutrient intakes were significantly lower

than those of three-meal eaters.

103

The majority of subjects in our study had low quality
diets at the time of entry (59%). Sixteen percent of diets
included at least one serving from each of five major food
groups. Thirty percent of diets had less than 30% energy
intake from fat. Only 5% of the subjects consumed foods from
five food groups (at least one serving of each food group)
and limited fat to less than 30% of caloric intake. Murphy
et al.(1992) reported similar findings from 5884 adults (19
years of age and older) who participated in the 1987-88
Nationwide Food Consumption Survey. They reported that only
22% of the adults consumed diets containing more than two
thirds of the RDA for 15 nutrients (i.e., protein, vitamin
A, vitamin E, vitamin C, thiamin, riboflavin, niacin,
vitamin B6, folate, vitamin 312, calcium, phosphorus,
magnesium, iron, and zinc) and only 14% of the adults
consumed diets containing 3 30% fat for energy intake. Only
2% of the adults chose diets that were both high in
nutrients and low in fat.

The Dietary Guidelines for Americans have focused on
reducing the level of fat in the diet while maintaining
nutritional adequacy (USDA, 1995). Kant (1996) reviewed the

published indices of overall diet quality. The majority of

104

the indices which were reviewed addressed nutrient adequacy
only. Few indices have addressed both low fat and meeting
energy and nutrient needs simultaneously.

In our study, we used two criteria to classify the
quality of diets. Our criterion one (i.e., including at
least one serving from each of five major food groups) was
designed to address variety and nutrient adequacy based on
the intake of five food groups. This criterion has been
proved to be a valid quantitative tool for screening for
nutritional inadequate diets (reference: MAR-6 <75) with
high sensitivity (89%) for college population (Schutte et
al., 1996). Criterion one also had a high sensitivity (94%)
in screening for nutritional inadequacy (reference: MAR-5 <
75) of Michigan EFNEP population in our study. Criterion two
(i.e., limiting percent energy intake from fat to less than
30%) was established to address the guideline of moderation
in fat intake. Compared to the subjects who met both
criteria at the time of entry, subjects who met neither
criteria were approximately 8 times more likely to have MAR-
5 score less than 75.

At the time of entry, more than half of our subjects

consumed less than 75% RDA for calcium, iron, vitamin A, and

105

vitamin B6 (63%, 65%, 60% and 54%, respectively). This
finding is consistent with findings from national surveys.
CSFII 1994 data show that average intakes of women 20 years
of age and older are below 100% RDA for six nutrients: iron,
zinc, vitamin B6, calcium, magnesium, and vitamin E (USDA,
1996). In our study, based on 24-hour food recalls, calcium
intake appeared to be particularly low in the young female
subgroup (13-24 yr, n= 1013) with an average intake of 650
mg (54% RDA). Iron appeared to be a problematic nutrient for
pregnant or pregnant/nursing women (all age, n=820) with an
average intake of 13 mg (43% RDA). Keep in mind that
nutrients derived from supplements were not quantified and
therefore were not included in the daily totals. In our
study, eighteen percent of the total subjects took nutrient
supplements. Especially, forty seven percent of
pregnant/nursing subjects took nutrient supplements.

The Food Guide Pyramid is a general guide for eating a
variety of foods to get the nutrients that humans need. The
Food Guide Pyramid recommends that a diet includes 6-11
servings of the grain group, 3-5 servings of the vegetable
group, 2-4 servings of the fruit group, 2—3 servings of the

dairy group, and 2-3 servings of the meat group. On average,

106

Michigan EFNEP participants (female, 13-85 years old,
n=3866) ate 4.8, 2.5, 1.0, 2.1, and 1.4 servings of grains,
vegetables, fruits, meat, and dairy, respectively. Food
groups which were skipped most frequently by the subjects
were the fruit group (53%), followed by the dairy group
(24%) and vegetable group (20%). During the same survey
period as ours, CSFII 1994 data show that female adults (age
20 or older) ate an average of about 5.3, 3.0, 1.5, 4.0, and
1.1 servings of grains, vegetables, fruits, meat, and dairy,
respectively (Cleveland et al., Pyramid servings data,
1997). Average consumption of the five food groups (in
servings) in national representative female adults
population was higher than that in our low income Michigan
EFNEP population. The Food Guide Pyramid encourages
consumers to use fats, oils, and sweets sparingly. The
Dietary Guidelines of Americans state that consumers should
limit their fat intake to 30% daily energy intake. Subjects
in our study had 36% daily energy intake from fat. This
value was higher than the national average of 33% daily
energy from fat for women (Cleveland et al.,Highlights from
CSFII 1994, 1997).

In the Michigan EFNEP population, many of the major

107

food contributors for calcium, iron, vitamin A, vitamin C
and vitamin B6 were not necessarily the rich sources of the
nutrients. For example, potato chips were among the top five
contributors for vitamin C, vitamin B6 and fiber. White
bread was the most significant contributor for iron, and
fifth important contributor for calcium. We do not know if
this is due to the subjects’ lack of knowledge of nutrient
rich food sources, or due to the fact that limited financial
resources constrain food choices. Lutz et al. (1995)
reported that low-income households consumed 21% less fresh
fruits, 13% less fresh vegetables, and 10% less dairy
products than the national average. On the other hand, low
income households used about 9% more fresh potatoes, 11%
more canned fruits and vegetables than did the national
average. The findings reflected the relatively lower price
of potatoes and canned items. In our study, white potato
products such as french fries, mashed potato, and baked
potato accounted for 25.2% of total serving numbers of
vegetable group. White potato products were the major
sources for subjects’ intake of vitamin C, vitamin B6, and
fiber. Because of the common cooking method of potato

products (i.e., fry), a significant amount of fat was

108

absorbed by the french-fried potatoes during preparation.
Inevitably, white potato products became the major
contributors for the “other” food group (i.e., added fat and
sugar). Potatoes were very important economical foods that
accounted for nutrient intake in this population. Creative
cooking methods of preparing potatoes without adding too
much fat (e.g., stir fry, casserole, and soup) should be
incorporated into the menu planning section of the EFNEP
curriculum.

The average fiber density in the diets of all subjects
(6 g/1000 Kcal) was only half of the recommended level (12.5
g/1000 Kcal). Eating five fruits and vegetables per day is
the nutritional advice to increase fiber intake. Reicks et
al. (1994) concluded that cost, storage space and seasonal
availabilities were the barriers to consumption of fresh
fruits and vegetables for low-income families. While fruits
and ready-to-eat cereals were major contributors to fiber
intake among basic income women (>185% Federal Poverty
Income Guideline), white potatoes and soups/dried beans were
among the major contributors for low income women (s 185%
PI; Thompson et al., 1992). EFNEP clienteles can be

encouraged to achieve a substantial fiber intake with foods

109
which are economical to them, such as spaghetti and taco.
Nutrition promotion facilitates the appropriate eating
behaviors by translating science-based dietary guidance into
consumer-oriented messages (Sutton et al., 1996). EFNEP has
taken the food group approach since the program began. The
sound rationale behind this approach is that people eat
foods not nutrients. In our study, graduates who did not
include at least one serving from each of the five food
group at the time of entry increased their consumption of
the five food groups significantly by the end of the
program. Other researchers have provided support for the
importance of nutrition education efforts to take the food
group approach. Guthrie and Fulton (1995) found that
knowledge of the recommended number of servings for the five
food groups was significantly associated with consumption of
four food groups (vegetable, fruit, meat, dairy) after
controlling for the effects of a number of other factors
that may influence food consumption behavior. They concluded
that knowledge of recommended servings by itself was able to
encourage consumers to achieve the recommended consumption

amount of major food groups.

110

Conclusion

1.

The majority of Michigan EFNEP participants had
relatively low dietary quality at the time of
enrollment in the program. Fifty nine percent of the
participants had diets which were classified as low
quality diets by not meeting the two dietary quality
criteria set in our study. Only 5% of subjects met
both criteria by obtaining nutrients from five food
groups (at least one serving of each food group) and
limiting fat intake to less than 30% of daily energy
intake. Fat intake averaged 36% of the daily energy
intake. Fiber density averaged 6 g/1000 Kcal. More than
half of the subjects failed to meet 75% RDA for
calcium, iron, vitamin A, and vitamin B6, respectively.
White bread, whole milk, white potato products, juice,
potato chips and soft drinks were frequently consumed,
economically acceptable foods that accounted for intake
of most of the nutrients and the “other” food group
(i.e., added fat and sugar) by the low-income Michigan
EFNEP participants.

Two undesirable food behaviors that were significantly

associated with low dietary quality of Michigan EFNEP

111

participants were: high intake of add fat and sugar,

and low frequency of meals/snacks consumption. Other

characteristics such as energy intake, race, and
maternal status were also associated with dietary
quality.

4. Initial dietary quality can predict dietary changes of
Michigan EFNEP participants. Participants with
relatively low dietary quality at the time of entry
made more dietary changes at the time of exit than
those whose initial dietary quality was high.

In summary, the overall dietary quality of Michigan
EFNEP participants was relatively low at the time when they
entered the program. Michigan EFNEP was effective in
improving diets and nutritional well-being of participants,
especially those with relatively low dietary quality at the
entry. This research provided a better understanding of
EFNEP participants’ diets, identified new areas of
improvement, and posed managerial challenges for EFNEP
program leaders. It is hoped that this research will
encourage serious discussion and action and stimulate other
researchers to pursue further research in this area. In-

depth EFNEP evaluation such as the present study is a means

112

of improving effectiveness and efficiency of programs.

Assumptions

In conducting the present study, the following

assumptions were made:

1) The 24-hour food recall is a valid and reliable
instrument for estimating dietary intake for a large
group population.

2) The subjects recorded honestly and accurately all food
and beverage items consumed for each 24-hour recall.

3) EFNEP staff have entered the food items into the EFNEP
Evaluation/Reporting System (ERS) correctly with
appropriate substitutions for food items which were not
in the food database of ERS.

4) The individual teaching performance was the same among
paraprofessionals.

5) Improvement in food consumption behavior was assumed
due to the EFNEP intervention.

Limitations

This study has a few limitations which should be addressed.

1)

24-hour food recall does not give data representative

113

of an individual’s usual intake. It relies on memory,
depends on honesty and accuracy of self-reported food
consumption, and can be affected by the learning

effects when it is used more than once.

2) There may be other variables that might have affected
the outcome of this study, such as education level,
physical activity level. Our research questions were
set up based on the available variables.

Strengths

The strengths of this study that should be recognized

are the following:

1)

2)

The validity of the study is increased by the large
sample size of low income women representing Michigan
statewide EFNEP participants (n = 3866) and the wide
range of the subjects’ age distribution (13 years old
to 85 years old). Our cross-sectional simple size
(n=3866) is larger than CSFII 1994 low income
population which was over-sampled nationally (n=732).
Our longitudinal data also contains a large number of
Michigan low income individuals (n=2454).

The dietary data for subjects were collected between

114

August 31, 1994 and September 1, 1995. Thus seasonal
bias is not a concern.

3) ERS addresses intake values of nutrients, foods, and
food groups with a reasonably large and accurate

database.

Implications for future management

1) Michigan EFNEP can further enhance its effectiveness in
improving dietary intake of its participants by targeting
participants who have low dietary quality diets at the time
of entry. The EFNEP Evaluation/Reporting System (ERS) has a
function to generate individual diagnostic reports as a
feedback to participant. Participants' first 24-hour recalls
collected at the time of entry can be quickly screened by
checking whether the diets include at least one serving from
each of the five food groups, and by checking whether the
fat intake is below 30% daily energy intake. These two tools
have been developed and validated in this study.
Participants who had low dietary quality diets could be
given a priority for enrollment in the currently offered
program. Instruction topics for this group may focus on

basic nutrition knowledge.

115

On the other hand, participants classified in the high
initial dietary quality subgroup may receive educational
activities with different emphasis, for example, resource
management. Instead of costly and time-consuming home
visits, newsletters can be a highly efficient and effective
tool for participants in high initial dietary quality
subgroup in refreshing their nutrition knowledge.

2) The effectiveness of Michigan EFNEP can be further
enhanced by incorporating newly identified educational needs
into the current curriculum. The current emphases on eating
a variety of foods from five major food groups while
reducing fat intake, may be incorporated with specific
advice. Examples may include listing the good food sources
for key nutrients and how to prepare these foods in the
meals. During cooking sessions of the EFNEP home visits, low
fat recipes could be taught. Curriculum should also address
the need of changing undesirable food behaviors, such as the
low frequency of meal/snack consumption and the high intake
of added fat and sugar.

3) The effectiveness of Michigan EFNEP can further be

enhanced through communicating the research findings of this

study with paraprofessionals to help them better understand

116
their audiences and educational strategies.
Paraprofessionals, when carefully trained and appropriately
supervised, would
effectively improve the diets of low-income audience.
4) “Lose interest” was the number one reason for
participants dropping out of the EFNEP in Michigan. In Kent
county, 100 out 103 dropouts indicated “lose interest" as
their reason for dropping out. How to retain the
participants in the program needs each county’s attention.
Paraprofessionals performance should be evaluated
periodically.
5) A special staff is needed for building up each year’s
statewide database for in-depth program evaluation. Computer
technical support should be available to county staff.
6) Sources of nutrients consumed by Michigan EFNEP
participants which were generated from this study can be
used as reference to develop food frequency questionnaire
related to certain health concern for Michigan low—income

population for other researchers.

Recommendations for future study

1) In our study, participants with relatively low dietary

117

quality at the time of entry made more dietary changes at
the time of exit than those whose dietary quality was high
at the time of entry. This result poses a challenge for
EFNEP program leaders who may have to decide who should be
offered EFNEP services and how different emphases of
educational activity should be given for participants with
different entry dietary adequacy levels. The economic,
political, and ethical implications of the issue on whether
to screen the diets of participants at the time of entry
should be addressed in future studying.

2) In our study, pregnant/nursing participants were less
likely to have low dietary quality at the time of entry than
those who were non-pregnant/non-nursing. Food stamps and WIC
were the two programs in which most of our subjects
participated (58% and 58%, respectively). Additional
research should be conducted to see how other public
assistant programs such as food stamps and WIC impact EFNEP

participants’ diets.

APPENDICES

APPENDIX A

SUMMARY OF ADULT PARTICIPANT PROFILES

118

AHNEENDUD{.A

SUMMARY OF ADULT PARTICIPANT PROFILES

State: M1109 11/08/1994
Michigan

Reporting Period: 09/01/1993 - 08/31/1994
1) TOtal number of program familes: 5310

2) Number of new families enrolled this reporting period: 4618 (87 %I

3) Number of persons in program families: 18988
4) Distribution of household children:

Number of Number of
Children Families Percent

0 498 9 %
1 1819 34 %
2 1497 28 %
3 890 17 %
4 352 7 %
5 167 3 %
6+ 87- 2 %
Total 5310 100 %

5) Distribution of ages of children:

Age Number of

Range Children Percent

Under 1 1242 12 %
1 - 5 4805 46 %
6 - 8 - 1577 15 %
9 - 12 1421 14 %

13 - 15 750 7 %

16 - 19 551 5 %
Total 10346 100 %

6) Family enrollment in other programs:

Number of
Program Families Percent
WIC/CSFP 2811 53 %
Food Stamps 3222 61 %
FDPIR 31 1 %
TEFAP (Commodities) 755 14 %
Head Start 836 16 %
Child Nutrition 1188 22 %
AFDC 2222 42 %
Other Public Assistance 504 9 %
Enrolled in EFNEP Only 814 15 %

119

1UPPEEHIEX A.

SUMMARY OF ADULT PARTICIPANT PROFILES

State: M1109 11/08/1994
Michigan

Reporting Period: 09/01/1993 - 08/31/1994

7) Gender and racial/ethnic characteristics:

Female Male Total
Number PCT Number PCT Number PCT

White Total 2769 52% 90 2% 2859 54%
Black Total 1744 33% 135 3% 1879 35%
American Indian/Alaskan Total 67 1% 9 0% 76 1%
Hispanic Total 337 6% 9 0% 346 7%
Asian or Pacific Islander Total 144 3% 6 0% 150 3%

Total all race codes 5061 95% 249 5% 5310 100%

8) Place of residence:
Families Percent

Farm 71 1 %
Towns under 10,000 and rural non-farm 737 14‘%
Towns & cities 10,000 to 50,000 8 their suburbs 1397 26 %
Suburbs of cities over 50,000 924 17 %
Central cities over 50,000 ’ 2181 41 %

Total 5310 100 %

9) Gender and age distribution of homemakers:

Female Male Total
Age Number Percent Number Percent Number Percent
10- 6 O % 0 0 % 6 0 %
11 0 0 % 0 0 % 0 0 %
12 0 0 % 0 0 % 0 0 %
13 6 0 % 1 0 % 7 0 %
14 17 0 % 0 0 % 17 0 %
15 57 1 % 1 0 % 58 1 %
16 136 3 % 4 0 % 140 3 %
17 190 4 % 12 0 % 202 4 %
18 184 3 % 22 0 % 206 4 %
19 170 3 % 7 0 % 177 3 %
20 190 4 % 5 0 % 195 4 %
21+ 4105 77 % 197 4 % 4302 81 %
Total 5061 95 % 249 5 % 5310 100 %

120
.APPTDHIEX A.

SUMMARY OF ADULT.PARTICIPANT PROFILES

State: M1109 11/08/1994
Michigan

Reporting Period: 09/01/1993 - 08/31/1994
10) Pregnant and Nursing:

Pregnant 848 16 %
Nursing 241 5 %
Pregnant 5 Nursing 39 1 %
Age < 20 and Pregnant

and/or Nursing 392 7 %

11) Type of instruction:

Group 2813 -53 %
Individual 2327 44 %
Both indiv. & group 168 3 %,
Other 2 0 %~
Total homemakers taught 5310 100 %

12) Status of homemakers:
- Number Percent

Completed program 3685 69 %
Terminated program 589 11 %
Continuing in program 1036 20 %
Total 5310 100 %
13) Months in program:
Months in

Program Number Percent

0 - 3 3705 70 %

4 - 6 1099 21 %

7 - 9 330 6 %

10 - 12 132 2 %

13 - 15 31 1 %

l6 4 up 13 0 %

%

121

.APPTRUIEX A:

SUMMARY OF ADULT PARTICIPANT PROFILES

State: M1109 11/08/1994
Michigan

Reporting Period: 09/01/1993 - 08/31/1994
14) Distribution of family size:

Family Number of

Size Families' Percent
1 242 5 %
2 1151 22 %
3 1444 27 %
4 1231 23 %
5 701 13 %
6 331 6 %
7 118 2 %
‘8+ 92 2.%
Total 5310 100 %

15) Household income:

Percentage of Number of
Poverty Level Families Percent

 

 

<- 50% - .2054 39 %
51 - 75% 1073 20 %
76 - 100% 511 10 %
101 - 125% 280 5 %
126 - 150% 111 2 %
151 - 185% 76 1 %
>- 186% 67 1 %
Not specified 1138 21 %

Total 5310 100 %

16) Reasons why homemaker did not complete program:
Exit Reason Number Percent
Returned to school 29 5 %
Took a job 75 13 %
Family concerns 46 8 %
Staff vacancy 8 1 %
Moved - 137 23 %
No longer interested 242 41 %
Other 52 9 %
Total 589 100 %

122

.APPTDHIEX A.

SUMMARY OF ADULT PARTICIPANT PROFILES

State: MI109 11/08/1994
Michigan

Reporting Period: 09/01/1993 - 08/31/1994

17) Family enrollment in other programs due to
EFNEP assistance!recommendation:

Number of
Program Families Percent
WIC/CSFP 84 2 %
Food Stamps 44 1 %
FDPIR 1 0 4
TEFAP (Commodities) 167 3 %
Head Start 23 0 %
Child Nutrition 15 0 %
AFDC 33 1 %
Other Public Assistance 75 1 %

18) Distribution of lessons taught - Completed Program:

Number of Number
Lessons of Hmkrs Percent

0 - 6 968 26 %
7 - 13 1826 50 %
14 - 20 878 24 %
21¢ 13 0 %
Total 3685 100 %

Mean - 9.7 Standard Deviation - 4.86

19) Distribution of lessons taught - Terminated Program:

Number of Number
Lessons of Hmkrs Percent

o - 6 556 94 s
7 - 13 25 4 4
14 - 20 7 1 4
21+ 1 0 %
Total 589 ' 100 4

Mean - 2.4 Standard Deviation - 2.84

State:

123

.APPTDHIEK.A

SUMMARY OF ADULT PARTICIPANT PROFILES

MI109
Michigan

11/08/1994

Reporting Period: 09/01/1993 - 08/31/1994

20) Length of Enrollment and Number of Lessons - Completed Program:

21)

m<Hv-3:ur*czc:n
072(307mtnr' ~10 namcnszczz

+ ........
I

+ ........
I Entry

I

+ ————————
I 1-6

I

+ --------
| 7-12

I

+ --------
| 13-18

I

+ ........
I 19+

I

4. ........
I Total

I

.4. ........

+—-+—+

+

* Less than 0.5%

Months of enrollment

16+

H
+-—-+-—-+-——-

------- +---~---+-------+-------+-------+-------
0 - 3 I 4 - 6 I 7 - 9 I 10-12 I 13-15 I
------- +-------+--—----+------—+-------+
157| 32I lSI 16| 4|
4% I 1% I * I * l * I
------- +-------+---—---+-----—-+—------+
594| llSI 28I 7| 0|
16% l 3% I 1% I * I 0% I
------- +-------+-------+----1--+-------+
1075i 412I 92I 13I 3|
29% I 11% I 2% I * I * I
------- +-------+-------+-------+-------+
768I 166| 30I . 6| ll
21% I 5% I 1% I * I * I
------- +-------+-------+-------+-------+
125| 12I 12l 0| 0|
3% I * I * I 0% I 0% I
------- +-------+-------+-------+-—-----+
27l9| 737| 177) 42I 8|
74% I 20% | 5% I 1% I * I
------- +-------+-------+-------+-------+

+——+—+

+——+-—

Length of Enrollment and Number of Lessons - Terminated Program:

FI<HH>FCKCO
00200301011" ”10 wmwzcz

+ ........
I

.1. ........
I Entry

I

+ ........
I 1-6

I

+ ........
| 7-12

I

+ ........
I 13-18

I

+ ........
I 19+

I

+ --------
I Total

I

+ ........

-—-+--+--+—-—-+-——-+-——-+-—+

+

* Less than 0.5%

Months of enrollment

0 - 3 | 4 - 6 | 7 - 9 | 10-12 | 13-15
------- +-------+---—---+-------+-------
62I 40| 14| 9| 4

11% | 7% | 2% | 2% | 1%
------- +-------+-------+-------+-------
267I 1171 38I 3| 2

45% | 20% | 6% | 1% | *

------- +-------+-------+-------+-------
3| 11| 3| 2| 0

1% | 2% | 1% | * | 0%
------- +-------+-------+—------+--—----
1| 5| 0| 1| 0

* | 1% | 0% | * | 0%
----- + -----+---—---+-------+-------
0| 0| 0| 0| 1

0% | 0% | 0% | 0% | *

----- + -----+-------+-------+-------
338I 173| 55| 15| 7

57% | 29% | 9% | 3% | 1%
----- + -----+-------+-------+-—-----

+.._—

+-—+—-

+——+——

+-—+——

+——+——+—-+——

State:

M1109
Michigan

SUMMARY OF ADULT_PARTICIPANT PROFILES

124

.APPEHUIIX A;

11/08/1994

Reporting Period: 09/01/1993 - 08/31/1994

22) Length of Enrollment and Number of Lessons - Continuing in Program:

p)<:4~i>1ficzztzr)
002(Duumtnr‘ 'flC) :numm:zc:z

 

 

 

 

 

 

 

 

Months of enrollmen
+ -------- 4 ------- +--- 4 — 4 = 4 —---+ ------- + ------- 4
| | o - 3 | 4 - 6 | 7 - 9 | 10-12 | 13-15 I 16+ | 16:51 |
4——— 4— — 4— 4 4 — 4—— =—-+ ------- + ------- 4
I Entry I 527I 147I 94I 67I llI 10I 856I
| | 51% I 14% | 9% | 6% | 1% | 1% | 83% |
| 1-6 | 102| 14| 4| '3| 1| 0| 124|
| | 10% | 1% | | I * | 0% | 12% |
4 4 4 4 4 4 4 — =4 ------- 4
I 7-12 I 19I 2II 0| 3| 2| 0| 51l
I I 2% I 3% I 0% I I * I 0% I 5% I
I 13-18 I 0|, 1I° 0| II. 2| 0| 4|
I I 0% I * I 0% I I ‘ I 0% I ' I
4—— 4 H 4 4 4 4 4 —-+ ------- +
| 19+ | 0| 0| 0| 1| 0| 0| 1|
| | 0% | 0% | 0% | | 0% | 0% | * |
+= 4 4 4 4 4 4 =4 ------- +
I Total I 540I 189I 98I 75I 15I 10| 1036|
I I 63% I 18% I 9% I 7% I 2% I 1% I 100% I
* Less than 0.5%

( 15 units]

APPENDIX B

DIET SUMMARY REPORT

State: M1109

Michigan

125

.APPTUUIEX B

0m 50mm: 115209.1-

11/08/1994

Reporting Period: 09/01/1993 - 08/31/1994
. SUMMARY OF DIETARY IMPROVEMENT

. Mean and percent of graduates
eating a specific number of servings

of each food group

3688 graduates

Graduates at:

 

Entry Exit
. Breads 8 Cereals: Mean +/- StD 4.8 3.7 5.7
0 servings 6.2% 1.8%
1-3 servings 32.5% 21.2%
4-5 servings 28.3% 27.4%
6-11 servings 29.9% 45.6%
12+ servings 2.3.2% 4.0%
. Fruits: Mean +/- StD 1.1 4.3 1.5
0 servings 58.9% 35.0%
1 serving 18.8% 25.3%
2+ servings 22.3% 39.8%
. Vegetables: Mean +/- StD 2.5 4.7 3.3
0 servings 26.5% 11.6%
1 serving 16.9% 11.7%
2 servings 20.7% 19.8%
3+ servings 35.9% 57.0%
. Calcium/Dairy: Mean +/- StD 1.4 2.2 2.1
0 servings 41.8% 23.1%
1 serving 24.8% 25.2%
2 servings 16.9% 25.3%
3+ servings 16.5% 26.4%
. Meats & Alternates: Mean +/- StD 1.7 2.3 2.1
0 servings 22.4% 12.0%
1 serving 32.8% 30.3%
2+ servings 44.9% 57.7%

126

APPENDIX B

DIET SUMMARY REPORT

State: MI109 11/08/1994

Michigan

Reporting Period: 09/01/1993 - 08/31/1994

I. SUMMARY OF DIETARY IMPROVEMENT

Graduates at:

3688 graduates

 

Entry Exit
6. Percent with positive Change in any

food group at exit (BC,F,V,Ca,Mt): 92.6%

7. Percent with 3-1-1-1-1 food pattern: 16.0% 40.4%

8. Percent with 6-2-3-2-2 food pattern: 1.5% 5.7%
9. Other Servings: Mean +/- StD 17.0 17.1 20.0 19.4

0-4 servings 18.4% 10.6%

5-9 servings 18.0% 17.3%

10-14 servings 17.5% 18.4%

15-19 servings 14.2% 15.1%

20+ Servings 31.9% 38.6%

Notes: .
a. Food pattern order:

BreadsICereals-Fruits-Vegetables-Calcium/Dairy-Meat

b. Each ’other serving’ is approximately equal to 35 calories,

or 1 tsp. fat, or 2 tsp. sugar

State: M1109
Michigan

127

.APPEEHIEX B

DIET SOMMARX REPORT

11/08/1994

Reporting Period: 09/01/1993 - 08/31/1994
I. SUMMAR! OF DIETARX IMPROVEMENT

8. Percentage of graduates reporting
eating a specific number of

3688 graduates

Graduates at:

 

 

 

[15 units]

meals/snacks Entry Exit

% eating one meal/snack 7.7% 1.6%

% eating two meal/snacks 19.8% 10.1%

% eating 3 or more meal/snack“ 72.5% 88.3%

C. Number and percent of graduates Graduates at:

who reported supplemental use: 'Entry Exit
Number 512 394
Percent 13.9% 10.7%

D. Money spent on food per capita per Graduates at:

month: Entry Exit

Number of homemakers reporting: 2501 2262

Mean +l- StD of money spent on food

per capita per month (5) 65.9 34.7 64.7 38.1

Mean family size +/- StD 3.7 1.6 3.6 1.6
$50— 36.9% 40.7%
$51-99 50.3% 47 9%
5100-124 8.3% 7.1%
5125-149 1.6% 1.9%
5150-174 1.1% 0 9%
$175+ 1.8% 1.6%

128

.APPimflIEX B

DIET SUMMARX REPORT

State: M1109 11/08/1994

Michigan

Reporting Period: 09/01/1993 - 08/31/1994

II. SUMMARX OP CALORIE/NUTRIENT IMPROVEMENT

A. Mean caloric intake and percentage
of calories

Graduates at:

3518 graduates

 

Entry Exit
1. Mean +/- StD grams consumed:
Carbohydrates (grams) 219.4 157.3 270.3 144.7
Eats (grams) 72.4 59.4 88.6 68.1
Protein (grams) 70.5 53.0 92.2 50.6
Alcohol (grams) 0.4 8.9 0.3 3.3
Dietary Fiber (grams) 11.7 13.1 15.7 11.0
2. Mean +/- StD caloric intake: (Calories) 1790.9 1179.5 2219.4 1162
3. Ranges of caloric intake:
1199- calories 30.5% 13.9%
1200-2199 calories 45.1% 49.5%
2200+ calories 24.4% 39.2%
4. Percentage of calories:
a. Prom carbohydrates: Mean +/- StD 48.6 12.4 49.6 6.8
<25% 2.2% 1.3%
25-49 52.6% 55.6%
50-60% 29.9% 33.3%
>60% 15.3% 12.6%
b. From fat: Mean +/- StD 35.0 10.1 35.6 7.0
<20% 6.5% 4.6%
20-29% 20.6% 24.3%
30-34% 18.2% 20.2%
35-39% 20.8% 22.3%
>39% 33.9% 31.3%
c. From protein: Mean +/- StD 16.1 5.9 17.3 4.3
(5% 1.0% 0.2%
5-9% 8.1% 3.1%
10-14% 33.2% 31.4%
15-19% 35.0% 42.8%
>19% 22.7% 25.2%

State: M1109

129

.APPEQHIEK B

DIET SUMMARX REPORT
11/08/1994

Michigan

Reporting Period: 09/01/1993 - 08/31/1994

II. SUMMARX OP CALORIE/NUTRIENT IMPROVEMENT

Graduates at:

3518 graduates

 

 

Entry Exit
5. Ranges of dietary fiber intake:
Mean +l- StD 11.7 13.1 15.7 11.0
4- grams 20.6% 7.4%
5-15 grams 57.5% 56.1%
16-24 grams 14.2% 25.8%
25+ grams 7.7% 13.3%
8. Mean nutrient intake and percent'ot Graduates at:
RDAs Entry Exit
1. Protein:' Mean NAR 0.90 0.99
<51% RDA. 7.8% 2.0%
51-69% RDA 7.0% 2.4%
70-99% RDA 14.8% 8.2%
>99% RDA 70.4% 90.1%
2. Iron: Mean NAR 0.66 0.81
<51% RDA. 32.4% 14.8%
51-69% RDA 19.6% 18.6%
70-99% RDA 24.0% 31.5%
>99% RDA. 24.0% 37.8%
3.Ca1cium: Mean NAR 0.54 0.71
<51% RDA 50.7% 29.3%
51-69% RDA 16.3% 18.7%
70-99% RDA 16.5% 25.7%
>99% RDA 16.5% 29.1%
4. Vitamin A: Mean NAR 0.62 0.81
<51% RDA 40.6% 20.2%
51-69% RDA 12.8% 12.8%
70-99% RDA 14.0% 17.4%
>99% RDA 32.5% 52.4%

130

.APPEDHIEX B

DIET SUMMAR! REPORT

State: M1109 11/08/1994
Michigan

Reporting Period: 09/01/1993 - 08/31/1994

II. SUMMARX OE CALORIE/NUTRIENT‘IMPROVEMENT 3518 graduates

Graduates at:

 

Entry Exit
5'. Vitamin c: Mean m 0.72 0.37
<51: 30a 29.9% 14.8%
51-69% 30a 10.0% 7.0%
70-99% RDA 12.1% 11.2%
>99% non ' 40.0% 69.6%
5. Vitamin 96: Mean an 0.70 ' 0.86
<51% m 29.4% 11.4%
51-69% 301: 15.7: 13.3%
70-99: RDA 22.0: 23.9%
>99% non 32 . 9% ' 54 . 1:
7. SMAR: Mean MAR. 0.69 0.84
<0.51 m 21.8% 6.6%
0.51-0.69 m 23.3% 14.9%
0.70-0.99 m 49.1% 67.1%
>0.99 m 5.8% 14.1%
[15 units]
Notes:

NAR - Nutrient Adequacy Ratio - Nutrient intake/RDA (limited at 1.0)
6MAR - Sum.or NAR.values for protein, iron, calcium,
vitamins A, C, and 86 /6 - Average NAR

131

.APPEDHIEX B

DIET SUMMARY REPORT

State: M1109
Michigan

11/08/1994

Reporting Period: 09/01/1993 - 08/31/1994
III. DISTRIBUTION or moan: AND NUTRIENT INTAKE 3518 graduates
' 493 exits

A. Calorie and nutrient intake among

homemakers Graduates at:

 

[Completed EFNEP] Entry Exit

1. Homemakers with 0% - 40% calorie intake
Number and percent or homemakers 554 15.7% 167 4.7%
Calories: mean % RDA +/-StD 27.6 9.5 30.2 8.7
Protein: mean % RDA +/-StD 57.1 31.3 66.9 34.8
Iron: mean % RDA rI-StD 32.5 25.9 39.4 36.0
Calcium: mean % RDA +l-StD 20.1 15.9 26.3 18.5
Vitamin A: mean % RDA +/-StD 43.5 63.7 56.4 66.8
Vitamin C: mean % RDA +/-StD 63.3 73.5 94.0 109.1
Vitamin 36: mean % RDA +/-StD 37.0 31.3 46.1 34.8

2. Homemakers with 41% - 80% calorie intake
Number and percent of homemakers 1519 43.2% 1357 38.6%
Calories: mean % RDA +/-StD 60.5 11.3 63.1 10.7
Protein: mean % RDA +/-StD 120.7 42.2 132.6 41.3
Iron: mean % RDA +/-StD 66.3 41.4 74.6 44.1
Calcium: mean % RDA +/-StD 46.7 27.6 55.5 26.2
Vitamin A: mean % RDA +/-StD 84.3 120.8 125.1 183.0
Vitamin C: mean % RDA +/-StD 120.5 138.4 147.4 116.9
Vitamin 86: mean % RDA +l-StD 72.6 43.5 86.9 44.8

3. Homemakers with 81% - 120% calorie intake
Number and percent of homemakers 943 26.8% 1231 35.0%
Calories: mean % RDA +/-StD 97.1 11.1 97.7 11.5
Protein: mean % RDA +/‘StD 182.2 58.0 201.0 57.5
Iron: mean % RDA +l-StD 96.3 49.4 104.5 55.1
Calcium: mean % RDA +/-StD 77.7 40.1 83.6 36.5
Vitamin A: mean % RDA +l-StD 128.8 167.1 168.2 232.7
Vitamin C: mean % RDA +l-StD 172.3 154.8 206.7 157.6
Vitamin B6: mean % RDA +l-StD 105.7 51.7 52.2

120.1

132

.APPETHIEX B

DIET SUMMAR! REPORT

State: M1109
Michigan

11/08/1994

Reporting Period: 09/01/1993 - 08/31/1994

 

III. DISTRIBUTION OF CALORIE AND NUTRIENT INTAKE 3518 graduates
493 exits
Graduates at:
Entry Exit
4. Homemakers with over 120% calorie intake
Number and percent of homemakers 502 14.3% 858 24.4%
Calories: mean % RDA.+/-StD 174.6 75.9 167.7 67.0
Protein: mean % RDA +/-StD 303:2 206.8 310.6 153.4
Iron: mean % RDA +/-StD 157.0 144.7 150.1 115.9
Calcium: mean % RDA +/-StD 139.3 109.4 155.0 105.3
Vitamin A: mean % RDA +/-StD 213.3 343.2 240.3 417.6
Vitamin C: mean % RDA +/-StD 329.6 450.4 297.2 234.4
Vitamin 36: mean % RDA +/-StD 194.0 202.6 176.5 105.8

3. Calorie and nutrient

intake among
homemakers

 

At
[Exited, objectives not met] Entry
1. Homemakers with 0% - 40% calorie intake
Number and percent of homemakers 86 17.4%
Calories: mean % RDA +/-StD 25.9 9.9
Protein: mean % RDA.+/-StD 55.0 29.9
Iron: mean % RDA +/-StD 30.8 27.6
Calcium: mean % RDA +/-StD 23.9 17.0
vitamin A: mean % RDA +/-StD 42.6 73.0
Vitamin C: mean % RDA +/-StD 52.8 62.2
Vitamin B6: mean % RDA +/-StD 33.1 23.4
2. Homemakers with 41% - 80% calorie intake

Number and percent of homemakers 216 43.8%
Calories: mean % RDA +l-StD 60.9 11.1
Protein: mean % RDA +/-StD 123.2 40.7
Iron: mean % RDA +/-StD 62.6 27.9
Calcium: mean % RDA.+/-StD 47.8 25.6
Vitamin A: mean % RDA +/-StD 85.4 125.5
Vitamin C: mean % RDA +/-StD 122.0 123.3
Vitamin 86: mean % RDA +/-StD 71.8 34.8

133

.APPEDHIEX B

DIET SUMMARI REPORT

State: M1109 11/08/1994
Michigan

Reporting Period: 09/01/1993 - 08/31/1994

III. DISTRIBUTION OF CALORIE AND NUTRIENT INTAKE 3518 graduates

 

493 exits
At:
Entry
3. Homemakers with 81% - 120% calorie intake
Number and percent of homemakers 127 25.8%
Calories: mean % RDA +l-StD 95.8 10.7
Protein: mean % RDA +l-StD 186.7 62.0
Iron: mean % RDA.+/-StD 96.2 52.3
Calcium: mean % RDA.+/-StD 80.6 42.9
Vitamin A: mean % RDA.%/-StD 131.2 141.2
Vitamin C: mean % RDA.+/-StD 189.3 164.6
Vitamin 86: mean % RDA +l-StD 117.1 67.2
4. Homemakers with over 120% calorie intake
Number and percent or homemakers 64 13.0%
Calories: mean % RDA +l-StD 159.3 41.9
Protein: mean % RDA +/-StD 289.3 107.6
Iron: mean % RDA +/-StD 140.5 84.5
Calcium: mean % RDA +/-StD 115.4 81.2
Vitamin A: mean % RDA.+[-StD 212.8 357.5
Vitamin C: mean % RDA +/-StD 206.3 165.6
Vitamin 86: mean % RDA.+/-StD 177.6 104.6

134

JAPPEDHDIXIIB

DIET SUMMARX REPORT

State: M1109 11(08/1994
Michigan

Reporting Period: 09/01/1993 - 08/31/1994

III. DISTRIBUTION OF CALORIE AND'NUTRIENT INTAKE 3518 graduates
' ' 493 exits

C. Number of homemakers with calorie &

 

 

nutrient values over 200% RDA Graduates at:
[Completed EFNEP] Entry- Exit
Number or Homemakers 3518 3518
Homemakers with over 200% RDA of - ,
Calories ' 100 143
Protein 768 1397
Iron 149 240
Calcium h 98 183
Vitamin A. 403 773
Vitamin C 844 1452
Vitamin B6 218 340
D. Number or homemakers with calorie &
nutrient values over 200% RDA. At
[Exited, objectives not met] Entry
Number of Homemakers 493
Homemakers with over 200% RDA of
Calories 9
Protein 102
Iron 11
Calcium 6
Vitamin A. 52
Vitamin C 108
Vitamin 86 31

[15 units]

APPENDIX C

DISTRIBUTION OF MICHIGAN EFNEP COUNTIES 1994-95

135
APPENDIX C

DISTRIBUTION OF MICHIGAN EFNEP COUNTIES 1994-95

 

 

 

  

16 EFNEP counties
Berrien
Dickinson
Genesee
Ingham
Kent
Kalamazoo
Lenawee
Macomb
Muskegon
Oakland
Sanilac
Saginaw
St. Clair
Wayne
Washtenaw

 

 

 

 

APPENDIX D

LIST OF EFNEP CURRICULUM CONTENT

13 6
APPENDIX D

LIST OF EFNEP CURRICULUM CONTENT

EATING RIGHT IS BASIC
third edition

Introduction

Starting with the Basics

Food Guide Pyramid

Understanding Food Labels

Planning Makes a. Difference

Making the Most of Your Food Dollars
Keeping Food Safe

Bread, Cereal, Rice & Pasta

 

Vegetable Group

121 E. 31M
230:“ 319 9 . Fruit Group
Mason. MI 48854
Plioce- 5175764207 10.

Milk, Yogurt & Cheese Group
“517/576-7230

2728mm __ 11. Meat, Poultry, Fish, Dry Beans,
Luring. MI 48912 Eggs 5 Nuts Group
Phone: 517/484-9450

',12. Breakfast, Choosing Healthy Snacks
13. Eating Right for No

W. m“. I! E . 14. Feeding Your New Baby
mmumnmo

{I wimwm b we. we: 15 . Feeding Infants 6 Children
nuw m e: m 9" —"--

arm
”WWW“, - ® Eating Right a Light

mamas

charisma.
“508871th "on

mm denotes part of the core curriculum

APPENDIX E

UCRIHS APPROVAL

 

onuros
RESEARCH
AND
GRADUATE
STUDIES

Unlvtmty tommluu so
Research luvs
Human sums
(UCRIHS)

MDCDIOQD 5U. Um
232 Acmmm 81M
East Lansing W
48824-1045

517355-21”
FAX: 517/4324":

he 44¢th
064 4 "MM.
emu-lam.

VS. ! i' W
9.7.? 'ftmw

137

APPENDIX E UCRIHS APPROVAL

MICHIGAN STATE

UNIV

ERSITY

June 13, 1996

To: Lifan Koerner

 

RE: IREu: 96-371
TITLE: STATEWIDE IN-DEPTE DIETARY EVALUATION OF
MICHIGAN EXPANDED FOOD AND NUTRITION EDUCATION
PROGRAM PARTICIPANTS
REVISION REQUESTED: N A -
CATEGORY: 2-’
APPROVAL DATE: 06 12/96

The Uhiversit Committee on Research Involving human Sub ects'IUCRIHS)

review of thiz project is complete. I am pleased to adv se that the

rights and welfare of the human subjectt appear to be adequately

rotected and methods to obtain informed consent are ap ropriate.
Therefore, the UCRIHS approved this project and any rev sions listed
ve. .

RENEIAL: UCRIHS a roval is valid for one cal ear, be inning with
the apprgeal date shown above. Invest gatgrs planging to
continue a project be on year must use the green renewal
form (enclosed with t orig l a roval letter or when a
project is renewed) to seek u te certification. There is a .
max mum of four such expedite renewals ssible. Investigators
wis to continue a project beyond the time need to submit it
again or complete rev ew.

REVISIONS: UCRIHS must review an changes in rocedures involving human
subjects, rior to in tiation of change. If this is done at
the time o renewal, please use the green renewal form. To
revise an ap roved protocol at an o her time during the year,
send your wr tten request to the HS Chair, requesting reVised
approval and referencing the project's 1R8 R and title. Include
in ur request a description of the change and any revised

ns ruments, consent forms or advertisements that are applicable.
nouns!

CEANGEE:

Should either of the followin arise during the course of the

work, investigators must noti UCRIHS promptly: (1) roblems
(unexpected side effects aints, e c.) involving uman

comp

subjects or (2) changes in the research environment or new
information indicating greater risk to the human suggects than
existed when the protocol was previously reviewed approved.

If we can be of any future help please do not hesitate to contact us
at (517)355-2100 or sax (517M, 5-

Sincerely,

  
 
   

DEW :bed

cc: Non O.

171 .

. W

D vid E. Wright, Ph
188 Chair

Song

 

APPENDIX F

ADULT FAMILY RECORD

138

APPENDIX F

Adult Family Record
Michigan Expanded Food and Nutrition Education Program

   
 
    

3. Homemakers Nana

 

 

 

 

 

a?) (he) .......
Addrm 5. Enrolled In EFNEP beiors?
DY" C] No
C:
W Z, 6. If yes, did you receive a certificate 0! completion?
Phone L ) DY“ D No
7. Age __ ll. Race: Check the category you identity with. 12. Place of Residence: (circle one)
8. Sex F M _ (100) White (non-Hispanic) l Farm
9. Pregnant? (Z-W) Black (non-Hispanic) 2 Teams under 10.“)0 a rural non-farm
Yes No
__ (3.00) An Man/Alaskan Native 3 Towns a Cities 10.000.50.000
10. Breaslieedlng‘!
Yes No (400) Hispanic 4 Suburbs of Cities over 50.000
_ (5-00) Asian or Pacific Islander 5 Central Cities over 50.(X)0

 

13. Total household income last month: 8

 

14. Household members: Lin l'lrfl names of children (through age 19) and their ages.

 

 

 

 

 

 

 

 

 

     
 

 

MB A"
l) 6) .
n D
3) 8)
4) 9)
5) L°L
15. Number of other adults in household 18. We programs that the Family Participates in at ENTRY: (circle)
(not counting homemaker): ____
WICESFP Y N
iarnunmNMM Rdamm y N
l) Group. , mm Goodbisnibuion
' . Ping. on Indian Res.) Y N
2) individual
, Contamditics Y N
3130111
Read Stan Y N
4) Other
, Quid Nutrition Y N
amc Y N
l7. Entry Date: I t
Y N
(Sadly)

 

Comments:

 

 

 

 

APPENDIX G

24-HOUR FOOD RECALL

 

139

APPENDIX c; 24-H0ur Food Recall
. Michigan Expanded Food and Nutrition Education Program

 

l. Nousmhar's Nat-s:

 

 

3. Date of Recall:

 

 

 

 

 

 

 

 

 

 

 

 

 

5. Pregnant 7 6. Ming? 7. Nutritional Supplements 2 I I
DY» D No UV. 0N9 DY: (please list) I
a Moaeyapeetesteodlsst-sath: s | 0'“
9. Which Food Roam D ENTRY D m D Ghee: Number
MEALTYPE SERVING ABBREVIATIONS

l- Morning ‘- Aitstnooa mp . “PM c . an,

2- Manning 5- m up . W n, . M

3- Noon GILIstuhg 013m slaslioe
m. Whatdidhotnonnherad-ddrlahlsthalastuhoun? ‘y'._'_-. Clerical

fiebsflllodoubyl'raplotossiomiorw «inhuman
MEAL FOOD I'm AND DESCRIPTION AMOWT .
m unto-end u- my. amuse... cam ..- 4.. am“... A. fizfiflmcm

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Answer 1244/» we; Mansion.
II. Total number atlases:

MAW __bdm
_M

Panning:—

I.\. Eaitreasoucircleone)

Emotional objectives met
Renamed to actual

Took job

Family coateerns

Sufi vacancy

Moved

boat imam:

Other

endow-bu”-

 

"2N

 

 

 

l4. Did your isndly receive anistana as the result at a reterral or
suggestion from EFNEP pemnnel?

DY“ CINo
U18. ditch all that apply:

__ WICICSH’

__ Food Stumps

_ FDPIR (Food Distribution Frog. on lndian Res.)
__ Commodities

__ Head Start

_, Child Nutrition

_ AFDC

_ Other

 

(Spociiy)

 

 

 

C 2145'

APPENDIX E

PRINT OUTS OF THREE ERS RAW DATA FILES
(ADULT.DBF, RECALL.DBF, AND MEALS.DBF)

140

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

APPENDIX H PRINT OUTS or THREE ERS RAW DATA FILES
arladulteav
I unit_id I staff_id sex pregnant nursing age race_ood .
1IMI043 6 900001 F F F I 33 1-00
2EMI043 19 900001 F F F i 22 1-00
3IMI043 20 900001 F F F I 22 100 X,
4 M1043 21 900001 F F F 19 100 i
5 M1043 ' 22 900001 F F T 19 1.00
5 M1043 23 900001 F F F 23 1-00
7 M1043 24 900001 F F F 23 1.00
a M1043 25 900001 F F F 24 1.00
9 M1043 26 900001 F F F 31 1-00
10 Ml043 27 P00001 F F F 17 4.00
11 M1043 29 900001 F F F 23 1.00
12 M1043 29 900001 F F F 22 1.00
13TM|043 30 900001 F F F 42 1.00
14 ’ M1043 31 900001 F F F 29 .1.00 1
“15 i M1043 34 900001 F T F 23 4.00
16 I M1043 35 900001 F F F 27 1-00 —
17 M1043 ‘ 36 900001 F F F 34 1-00 j
19 M1043 I 37 900001 F F F 31 1.00
19 M1043 I 39 900001 F F F 33 3-00
20 M1043 39 900001 F F F 39 1-00
21 M1043 40 900001 F T F 19 1-00
22 M1043 41 900001 F F F 23 1-00
23 M1043 42 900001 F T F 23 3-00
24 M1043 I 43 900001 F T F 36 5-00
25 M1043 I; 44 900001 F F 1' 31 1-00

 

 

 

 

 

 

 

 

 

141

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

APPENDIX H PRINT OUTS OF THREE ERS RAW DATA FILES
azladultsav

I income town_siz n_ege_00 n_ago_01 n_age_02 n_age_03 n_age_04
1' “4 2 1 0 1 0 0,
2I 20012 0 1 0 0 01
3g 13502 0 0 0 1 E
43 720.2 1 0 0 0 0
5 50012 1 0 0 0 0
6 120012 0 0 1 1 0
7 25002 0 0 0 1 0
8 185 2 1 0 1 0 0
9 1075 2 0 0 2 0 1
10 300 2 1 0 0 0 0
11 444 2 0 1 0 1 0
12 800 1 0 1 0 0 0
13 789 2 0 0 0 0 0
14 50012 0 0 2 0 01
151 012 0 0 0 0 0:
16' 230011 0 o 0 1 0I
17 220072 0 0 '0 0 T
19) 650 2 0 0 0 0 D
19f 407 2 0 0 0 0 0
20I 1730 2 0 0 0 1 0
21fT 0 2 0 1' 0 0 0
223 1674 2 1 0 1 0 0
23E 1400 2 0 1 0 1 0
241 1356 2 0 0 0 0 0
251 1600 2 1 0 0 0 0

 

 

 

 

 

 

 

 

142
PRINT OUTS OF THREE ERS RAW DATA FILES

APPENDIX H

a:\adult.sav

n_age_1 1

 

.OL
Oi

 

° 1

 

 

n_age_1 O

 

n_age_09

 

n_age_08

 

n_age_07

 

n_age_06

 

: n_age_05

 

 

 

 

 

 

 

 

 

 

 

1O

 

11

 

12

 

13

 

14

 

 

151

16!

 

 

17*

 

18

 

19

 

20

 

21

 

 

23

24

 

 

25

 

143

PRINT OUTS OF THREE ERS RAW DATA FILES

APPENDIX H

a:\adult.sav

n_age_1 8

 

o i

 

 

n_age_1 7

 

n_age_16

o I

 

 

n_age_1 5

 

n_age__14

 

n_age_1 3

 

n__age_1 2

 

 

 

 

 

 

 

 

 

 

 

1O

 

11

 

12

 

13

 

14

15

 

 

16

 

17

 

18

 

19

 

20

 

21

 

 

23

 

24

 

25

 

144

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

APPENDIX H PRINT OUTS OF mgzedtfiagv RAW DATA FILES

A n_age_19 A oth6r_fa famly_to entry_da e_wic_cs 1 e_fd_sta e_fdpir

1 - 0 ' 1 5 01-JUN-93 T 1T F

2: 0. 0 2 21-JUL-94 T :1: .F

34 05 1 4 21-JUL-94 T 1F '1:

4 o; 0 2 26-JUL-94 T T F

51 01 1 3 O4-AUG-94 T F F 1
61 01 0 3 24-MAY-94 T T F

71 0' 1 5 20-JUL-94 T F F

81 0 0 3 29-JUL-94 T F F

9 0i 0 4 25-OCT-94 T F F

10 01 0 2 16—DEC-94 T T F 1
11 1 0' 1 4 13-OCT-94 T T F T
121 0 1 3 06-JAN-95 T F F 7
13I 0; 0 2 01-Dec-94 F T F 1
14 0 1 6 30-N0v-94 F T F

15 01 0 1 14-MAR-95 T .T F

16l 01 1 5 26-JUN-95 F F F ~
171 01 0 4 26-JUN-95 F F F
‘31 0 f 0 4 26-JUN-95 F F F *7
191 01 1 4 26-JUN-95 F T F

20 01 0 5 01-MAY-95 T F F 1
21 01 0 2 22-MAY-95 T F F i
22 01 1 4 24-MAY-95 T F F

231 o 1 4 24-MAY-95 T F F

24% 01 1 3 31-MAY-95 T F F

25 01 1 5 19-JUN-95 T F F T;

 

 

 

 

 

 

 

APPENDIX H

145

PRINT OUTS OF THREE ERS RAW DATA FILES

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

a:\adu|t.sav
646pr e_hd_sta 1 e_lunche e_afdc 0_other lesson_t lesson_c

1 ;T T 1T T F 2 1?
2 E F F 1F F F 1 4 1
3 ' F 1 F 1F F F 2 21 1
4 E T V F F T T 2 19 ,
5 F F F F F 1 15
61F F F T F 2 14
71F T F F F 2 14
81F F F F F 2 11
9 F T F F F 2 3
1011' F F T F 2 9
11 1T F F T F 2 12
121F F F F F 2 6
131T F T F T 2 12
14 1 F F F F F 2 7
15 j F F 1 F T F 2 4 .
16 - F T is: F T ,1 9 1
17 ; F F F F F 3 9
18 i F T F F F 3 9
19 ; F F T T F 3 9
20 1 F F T T T 2 7
21 F F F F T 1 4
22 1 F F F F F 3 7
231 F F F F F 3 7
241F F F F T 1 6
251F F F F F 2 5

 

 

 

 

 

 

 

 

 

APPENDIX H

PRINT

146

OUTS OF THREE ERS RAW DATA FILES

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

a:\adult.sav
exit_cod 1 exit_dat efn6p_he x_wic_cs x_fd_sta x_fdpir x_tefap
1 Y 1 15-JUN-95 T T T F T
2 7 12651394 T T F F T I
3 1 26-MAY-95 T T T F F
4 24-APR-95 F F F F F
5 : 02-FEB-95 T T F F F
6 1 30-MAY-95 T T T F F 1
7 I 05AFR-95 F F F F F I
6 29-MAY-95 T T T F F
9 15-MAR-95 F F F F F
10 02-JUN-95 T T T F F
11 03-MAY-95 T T T T F
12 06-MAR-95 F F F F F
13 23—JUN-95 F F F F F
14 13-JUN-95 T T T T F
15 06-JUL-95 T T T F F i
16 1 26-JUN-95 F F F F F __1
17 1 14-JUL-95 T F T 1: F _
16 10-JUL-95 F F F F F j
19 16.JUL-95 F F F F F 1
20 19-JUL-95 F F F F F
21 21-JUN-95 F F F F F
22 F F F F F
23 F F F F F
24 19—JUL-95 F F F F F
25 F F F F F

 

 

 

 

 

 

 

 

 

147

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

APPENDIX H PRINT OUTS or THREE ERS RAW DATA FILES
a:\adult.sav

x__hd_sta x_lunche x_afdc x_oth6r recaan recalLl recall; 1
1 . T T T T 2 15-JUN-95 01.JUN-937
2 F F F F 1 21-JUL-94 21-JUL-94:
3 T AT F F 2 26-MAY-95 21-JUL-94
4 F F F F 2 24-APR-95 2641116947
5 F VF F F 2 02-FEB-95 23-AUG-94'
6 F F T T 2 30-MAY-95 24-MAY-94
7 F F F F 2 05-AFR-95 204111.94
6 F F F F 2 29-MAY-95 29-JUL-94
9 F F F F 1 25-OCT-94 25-OCT-94
10 F F T F 2 02-JUN-95 16—DEC-94
11 T T T F 2 03-MAY-95 13-OCT-94
12 F F F F 2 O6-MAR-95 OMAN-95
13 F F F F 2 23—JUN-95 O1-DEC-94
14 T T T F 2 13-JUN.95 30-NOV-941
15 F F T F 2 06-JUL-95 14-MAR951
16 F' F F F 2 18-JUL-95 2641111119;
17 F F F F 2 14-JUL-95 264m»;
16 F F F F 2 10-JUL-95 26-JUN-95
19 F F F F 2 18-JUL-95 26-JUN-95
20 F F F F 2 19-JUL-95 O1-MAY-95
21 F F F F 1 22-MAY-95 22-MAY-95
22 F F F F 1 24-MAY-95 24-MAY-95
23 F F F F 1 24-MAY-95 24-MAY-95
24 F F F F 2 19-JUL-95 3141MY-95
25 F F F F 1 19-JUN-95 19-JUN-95

 

 

 

 

 

 

 

 

 

148

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

APPENDIX H PRINT OUTS OF THREE ERS RAW DATA FILES
a:\ad0lt.sav
reca||_x 1 cklist_n cklist_l cklist_e cklist_x lastmod
1 = 154011-951 2 151011-95 014011-93 154011-95 O7-SEP-95j
2 1 1 21401-94 21401-94 . ‘ 15—AUG-95 :
3 26-MAY-95 :r 2 26-MAY-95 21401-94 26-MAY-95j 07-55995 V
4 24-APR-95 E 2 24-AFR-95 26401-94 24-APR-95Y 15—AUG—95 1
5 . 02-FE8-95 f 2 02-FEB-95 04-AUG-94 02-FEB-95 154106-951
6 1 30-MAY-95 2 30-MAY-95 24-MAY-94 30-MAY-95 15-AUG-95
7 3 05-APR-95 2 05-APR-95 20401-94 O5-APR-95 15-AUG-95
8 f— 29-MAY-95 2 25-MAY-95 29401-94 25-MAY-95 15-AUG-95
.9 1 25-OCT-94 25-oCT-94 15-AUG-95
10 f 024011-95 2 024011-95 16—DEC-94 024011-95 15—AUG-95
11? 03-MAY-95 2 03-MAY-95 13-00T-94 03-MAY-95 15-AUG-95
121 06-MAR-95 2 06-MAR-95 06-JAN-95 06-MAR-95 15-AUG-95
131r 234011-95 2 234011-95 O1-DEC-94 234011-95 15-AUG-95
14 134011-95 2 134011-95 30Nov-94 134011-95 07-SEF-95
15 ' 06401-95 2 06401-95 14-MAR-95 06401-95 07-55995 J
T6 1 18-JUL-95 2 16401-95 264011-95 16401-95 18-AUG-9;
7; 1 14401-95 2 14401-95 264011-95 14401-95 28—AUG-95 3
16 ' 10401-95 2 10401-95 26-JUN-95 10401-95 28-AUG-95 ’
19f 16401-95 2 16401-95 264011-95 16401-95 28-AUG-95
20 5 19401951 2 1640195 O1-MAY-95 16401-95 28-AUG-95
21 1 . I 2 214011-95 22-MAY-95 214011-95 28-AUG-95
22 T, 1 24-MAY-95 24-MAY-95 07-SEF-95
23 1T 1 24-MAY-95 24-MAY—95 07-SEP-95
24 1940195 2 19401-95 31 MAY-95 19401-95 28-AUG-95
25 1 1 194011-95 194011-95 28-AUG-95

 

 

149

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

APPENDIX H PRINT OUTS OF THREE ERS RAW DATA FILES
a:\recall.sav
id rdate nutmth ispreg isnurse isnutsup foodcost
1 6 O1-JUN-93 1 F F F 200
2 6 15-JUN-95 1 F F F
3 19 21-JUL-94 1 F F F 0
4 20 21-JUL-94 1 F F F 200
5 20 26-MAY-95 1 F F F
6 21 26-JUL-94 1 F F F 150
7 21 24-APR-95 1 F F F 150
6 22 23-AUG-94 1 T F T 50
9 22 OZ-FEB—95 1 F T F 100
10 23 24-MAY-94 1 F F F 150
11 23 30-MAY-95 1 F F F 150
12 24 20-JUL-94 1 F F F 200
13 24 05-APR-95 1 F F F 180
14 25 29-JUL-94 1 F F F 55
15 25 29—MAY-95 1 F F F
16 26 25-OCT-94 1 F F F . 150
17 27 16-DEC-94 1 F F 1: 1107
18 L 27 OZ-JUN-95 1 F F F 100
19 f 26 13-00T-94 1 F F p 160
20 28 03-MAY-95 1 F F F 165
21 29 OB-JAN-95 1 F F F 246
22 29 06-MAR-95 1 F F F 200
23 3O O1-DEC-94 1 F F F 100
24 3O 23-JUN-95 1 F F F
25 31 30—NOV-94 1 F F F 150

 

 

 

 

 

 

 

 

 

150

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

APPENDIX H PRINT OUTS OF THREE ERS RAW DATA FILES
a:\recall.sav

‘ isexit I nmeals smeat sdai1y sveg sbread sfruit sother ,

1 I 3 2.00 2.90 1.00 6.00 1.36 11.03

2 I y 6 3.22 3.21 6.25 7.19 3.02 13.267

3 i F T 3 2.30 3.09 2.25 6.50 .04 I 26.66 I

4 a F f 4 1 .99 1.04 6.00 5.50 .00 I 15.30 g

—5 T 3 1 2.50 3.06 3.00 6.40 1.02 192?;

6 I 3 1.60 6.64 5.00 7.50 3.00 26.6:
I T 4 2.31 1.96 3.50 4.00 .75 16.20
617: 6 1.66 3.64 1.00 11.60 2.00 17.60
QTT 6 4.04 2.66 6.00 5.00 2.52 14.15
To 41 F 6 2.75 3.50 5.00 6.50 2.00 26.26
11 IT 4 6.50 2.06 5.50 5.60 1.36 26.70
12TF 6 I 9.10 1.66 1.50 6.70 3.04 29.71
13 IT 6 I 2.00 4.32 3.12 6.50 4.02 20.40
14 i F 6 2.00 2.75 2.00 6.50 2.00 21.55
757 T 3 1.33 2.60 1.00 7.00 1.00 11.94
76? 5 1.75 4.25 4.00 6.40 1.02 23.25
17 I F 5 .00 .75 5.00 3.00 2.36 14.66

16 I T 3 2.20 5.46 2.00 6.00 2.04 21.13 .3
19I F 3 1.33 1.54 .75 3.60 .00 30.45
20 | T 3 4.56 3.62 5.00 7.00 1.02 20.60
21 I F j 6 1.19 5.70 2.50 7.90 1.00 37.45
227; 4 1.99 3.94 1.00 4.50 .00 25.61
23 5 2.21 1.60 4.00 2.50 2.00 16.33
24 4 4.75 2.36 3.50 6.00 2.04 20.00
25 3 3.50 2.06 2.00 4.90 .00 24.40

 

 

 

 

 

 

 

 

 

151

DATA FILES

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

APPENDIX H PRINT OUTS or THREE ERS RAW
a:\recall.sav
ncal gprotein gfat gcarbo mgiron mgea reva

1 I 1576 66.6 50.7 217.6 14.9 1179 679

2 2044 121.9 70.6 260.4 20.3 1353 5413

3 I 2325 119.5 117.2 196.3 10.6 1330 636

4 : 1746 49.5 69.7 240.9 10.2 616 370

5 2124 63.4 79.1 304.9 24.0 1157 454

6 I 2671 107.1 106.5 327.2 12.4 2192 1129

7 ’ 1744 f 65.1 71.9 191.9 7.7 625 4096

—8 I 2462 92.2 75.4 361.7 34.1 1265 659

_9 I 2419 136.6 105.1 237.0 16.3 1346 2663

10 . 2337 92.9 75.5 339.3 20.7 1412 2397

11 2664 170.4 111.7 304.6 16.1 1012 2714

12 I 2940 161.5 122.1 276.6 16.9 1050 652

13 I 2361 104.6 79.5 323.0 35.1 1606 1542

14 2306 61.1 92.1 300.1 14.7 1052 730

15 1460 61.6 44.7 203.7 16.6 1079 3093

16 z 2156 67.6 84.0 295.6 13.7 1336 2396
—17 I 1140 25.4 29.4 199.1 6.4 324' 434 i
.18 . 2425 93.1 111.3 272.1 10.6 1603 753

—19 1622 51.5 64.4 269.2 10.4 609 699

20 I 2510 116.5 100.9 264.9 16.2 1334 1936

31? 2702 95.9 116.6 314.2 11.6 1766 911

22 I 1943 60.0 104.3 170.6 7.4 1306 765

23? 1957 69.7 76.1 242.1 12.6 941 696

24I 2207 135.9 77.1 236.0 13.6 1076 764

25 I 2127 76.0 95.9 239.5 9.6 637 1223

 

 

 

 

 

 

 

 

PRINT OUTS OF THREE ERS RAW DATA FILES

152

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

APPENDIX H a:\recall.sav
3 mgvc I 111ng I gfiber galcohol frozen lastmod
1; 71 1.67 11.1 .0 F 19940419
2 165 3.17 46.3 .0 F 19950907
3I 16 1.53 7.4 .0 F 19940727
4I 56 1.22I 9.5 .0 F 19940727 1
5I 169 3.25I 27.6 .0 F 19950907 '
6f 66 1.73; 16.4 .0 F 19940912fl
—71 32 2.281 9.4 .0 F 19950426
_8 I 96 3.23 17.5 .0 F 19950406
9I 113 2.04 19.6 .0 F 19950216
10 114 2.96 21.9 .0 F 19940912
11 70 3.40 23.5 .0 F 19950615
12 55 3.01 11.2 .0 F 19940912
13 161 2.04 26.9 .0 F 19950426
14 43 2.16 16.4 .0 F 19940912
15 60 2.76 12.6 .0 F 19950815
16 166 1.51 9.6 .0 F 19950216
17 104 .821 3.6 .0 F 19950216
161 167 1.21! 9.4 .0 F 19950615 3
19I 24 132' 3.6 .0 F 19950216?
20T 30 1.62 9.6 .0 F 19950615 '
21 22 1.30 20.4 12.0 F 19950303
22 6 .95 6.6 .0 F 19950317
23 77 2.97 27.2 .0 F 19950303
24 64 2.74 16.9 .0 F 19950615
25 l 21 1.15 3.0 .0 F 19950303

 

 

 

 

 

 

 

153

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

APPENDIX H PRINT OUTS or THREE ERS RAW DATA FILES
a:Vneals.sav
id rdate 9 mealtype foodid nservos
1I 6 01401193 1 263 1.00
2 si 014011-93 1 674 6.00
3I 6 TAM-101193 1 761 1.00
4. 6 01401193 5 143 2.00
sI 6 0140N93 5 761 1.00
6I BI 01401193 5 1205 2.00
7' 6I 014011-93 6 995 1.00
BI 6 715401195 1 133 2.00
91 6 15401195 1 259 1.00
103 6 154011-95 1 676 6.00
11 6 15401195 1 776 4.00
12 61 154011-95 2 3 1.00
131 arm-101195 3 154 2.00
14i 6 154011-95 3 255 1.00
15I 6 15.101195 3 316 1.50
16I 6 1540N95 3 631 3.00
17I 6 15401195 3 727 25
18I 6! 15401195 4 246 2.00
19; 6615-.1UN-95 5 419 .50
20I SI 15401195 5 461 1.00
21I 6i 154011-95 5 765 12.00
22! 6 f15—JUN-95 5 952 6.00
23I 6 I115401195 5 966 .50
24I 6 154011-95 5 1349 1.00
25I 6 15401195 6 940 3.00

 

 

 

 

 

 

BIBLIOGRAPHY

BIBLIOGRAPHY

Abdel-Ghany M. Evaluation of household diets by the Index of
Nutritional Quality. J'NUtr Ed. 1978; 10:79-81.

Armstrong JE, Butkus S, Movius M, Crowley D. The effect of
changes in recruitment and instruction on characteristics of
EFNEP enrollers and graduates. J'NUtr Ed. 1992; 24(2):87-90.

Amstutz MK, Dixon D1. Dietary changes resulting from the
Expanded Food and Nutrition Education Program. J'NUtr Ed.
1986; 18(2):55-60.

Anderson JEL. EFNEP evaluation in Colorado using a
simplified progression form. J'NUtr Ed. 1988; 20(5):227-231.

Axelson JM. Repeated measurements in evaluation. J'Nntr Ed.
1984; 16(1):12-l4.

Baghurst KI, Baghurst PA, Record SJ. Demographic and
nutritional profiles of people consuming varying levels of
added sugars. NUtrition Research. 1992; 12:1455-1465.

Bierman EL. Carbohydrate and sucrose intake in the causation
of atherosclerotic heart disease, diabetes mellitus, and
dental caries. Am J Clin Nutr. 1979; 32:2644-2647.

Block G, Dresser CM, Hartman AM, Carroll MD. Nutrient
sources in the American diet: Quantitative data from the
NHANEA II survey, II. Macronutrients and Fats. Am J'Epi.
1985; 122(1): 27-40.

Boushey CJ, Rauch M. Demonstration increases recipe use
among Hawaii graduates of the Expanded Food and Nutrition

154

155

Education Program. J'Am Diet Assoc. 1989; 89(11):1656-1658.

Bowens J, Cox RH, Pratt C, Gaylord C. Development of a food
practice checklist for use with low-literacy homemakers in
EFNEP. J Fami Cons Sci. 1995:35-42.

Bremner B, Campbell CC, Sobal J. Comparison of the beliefs
and practices of EFNEP clients with staff perceptions of
clients. J'NUtr Ed. 1994; 26(3):123-130.

Brink MS, Sobal J. Retention of nutrition knowledge and
practices among adult EFNEP Participants. J'NUtr Ed. 1994;
26(2):74-78.

Brown AJ, Pestle RE. Dietary Intake and Food Behavior
Practices: Long-Term Effects of the Georgia Expanded Food
and Nutrition Program. Hame Economics Research J. 1981;
10(1):62-68.

Cleveland LE, Goldman JD, Borrund LG. “What we eat in

America” Survey: Highlights from USDA’s 1994 Continuing
Survey of Food Intake by Individuals and 1994 Diet and
Health Knowledge Survey. Nutrition Today. 1997; 32(1):37-40.

Cleveland LE, Cook AJ, Wilson JW, Friday JE, Ho JW, Chahil
PS. Pyramid servings data: Results from USDA’s 1994
Continuing Survey of Food Intakes by Individuals. Food
surveys research group, Beltsville human nutrition research
center, ARS, USDA. 4700 River road, Unit 83, Riverdale, MD
20737. March 1997.

Cox RH, Parker GG, Watson AC, Robinson SH, Simonson CJ,
Elledge JC, Diggs S, Smith E. Dietary cancer risk of low-
income women and change with intervention. J'Am Diet Assoc.
1995; 95(9):1031-1034.

Conone RM. EFNEP: Reaching out to families in poverty. J
HOme Econo. 1992; Winterz38-41.

Chipman H, Kendall PA. 20 years of EFNEP: Changes and
challenges. J.N0tr Ed. 1989; 21(6):256-269.

156

Derrickson JP, Gans DA. EFNEP-Food Stamp pilot nutrition
education project. J.NUtr Ed. 1993; 25:367A.

Del Tredici AM, Joy AB, Omelich CL, Laughlin SG. Evaluation
study of the California Expanded Food and Nutrition
Education Program: 24-hour food recall data. J'Am Diet
Assoc. 1988; 88(2):185-190.

French AM. A guide to evaluation in the Expanded Food and
Nutrition Education Program. 1983. Prepared for U.S.
Department of Agriculture: Cooperative Extension.
InterAmerica Research Association. Rosslyn, Virginia.

Frazao E. The American Diet: Health and Economic
Consequences. 1996. Food and Consumer Economics Division,
Economic Research Service, US Department of Agriculture.
Agriculture Information Bulletin No. 711.

Gibson RS. Principles of nutritional assessment. New York,
NY: Oxford University Press, 1990.

Glinsmann WH, Irausquin H, Park YK. Evaluation of health
aspects of sugars contained in carbohydrate sweeteners:
Report from Sugars Task Force. J'Nutr. 1986; 116:81-8216.

Guthrie HA, Scheer JC. Validity of a dietary score for

assessing nutrient adequacy. J’Am Diet Assoc. 1981; 78:240-
245.

Guthrie JF, Fulton LH. Relationship of knowledge of food
group servings recommendations to food group consumption.
Family'Econ NUtr Rev. 1995; 8(4): 2-17.

Hartman TJ, McCarthy PR, Park R, Schuster ER, Kushi LH.
Evaluation of the literacy level of participants in and
urban Expanded Food and Nutrition Education Program. J'NUtr
Ed. 1994(a); 26(1):37-41.

Hartman TJ, McCarthy PR, Park R, Schuster ER, Kusti LH.
Focus group responses of potential participants in a
nutrition education program for individuals with limited
literacy skills. J'Am Diet Assoc. 1994(b); 94(7):744-748.

157

Hewitt BA, Willis W. Expanded Food and Nutrition Education
Program: National Synthesis Report, Extension Service
Update. Washington DC: United States Department of
Agriculture, 1989.

Haines PS, Hungerford DW, Popkin BM, Guilkey AK. Eating
patterns and energy and nutrient intakes of US women. J'Am
Diet Assoc. 1992; 92(6):698-704.

Johnson NE, Nitzke S. Nutritional Adequacy of Diets of a
selected Group of Low-income Women: Identification of Some
Related Factors. HOme Economics Research J. 1975; 3(4):241-
248.

Jones EM, Munger SJ, Altman JW. A field guide for evaluation
of nutrition education. 1975, Synectics Corporation. Allison
Park, PA.

Kant AK. Indexes of overall diet quality: A review. J'Am
Diet Assoc. 1996; 96(8):?85-791.

Kant AK, Block G, Schatzkin A, Ziegler RG, Nestle M. Dietary
diversity in the US population, NHANES II, 1976-1980. J'Am
Diet Assoc. 1991; 91(12):1526-1531.

Kant AK, Schatzkin A, Block G, Ziegler RG, Nestle M. Food
group intake patterns and associated nutrient profiles of
the US population. J'Am Diet Assoc. 1991; 91:1532-1537.

Kateregga CN. A follow-up evaluation of the effects of the
Michigan Expanded Food and Nutrition Education Program on
homemakers’ dietary adequacy: implications for future
management. A dissertation, Michigan State University, East
Lansing, Michigan, 1981.

Kennedy ET, Ohls J, Carlson S, Fleming K. The healthy eating

Index: design and applications. J'Am Diet Assoc. 1995;
95:1103-1108.

Konzelmann KL. Decreasing infant mortality through EFNEP
instruction. Report to Kraft, Inc. West Lafayette,
Indiana.,1990.

158

Lee CJ, Templeton S, Wang C. Meal skipping patterns and
nutrient intakes of rural southern elderly. J NUtr for
Elderly. 1996; 15(2):1-14.

Lewis CJ, Park YK, Dexter PB, Yetley EA. Nutrient intakes
and body weights of persons consuming high and moderate
levels of added sugars. J'Am Diet Assoc. 1992; 92(6):708-
713.

Lutz SM, Smallwood DM, Blaylock JR. Limited financial
resources constrain food choices. Food Review. 1995;
18(1):13-17.

Murphy SP, Rose D, Hudes M, Viteri FE. Demographic and
economic factors associated with dietary quality for adults
in the 1987-88 Nationwide Food Consumption Survey. J'Am Diet
Assoc. 1992; 92(11):1352-1357.

Morgan KJ. Socioeconomic factors affecting dietary status:
An appraisal. Amer J Agr Econ. 1986:1240-1246.

Morgan KJ, Zabik ME, Stampley GL. The role of breakfast in

diet adequacy of the U.S. adult population. J'Am Cbll NUtr.
1986; 5(6):551-563.

National Research Council, Food and Nutrition Board. Diet
and Health; Implications for reducing chronic disease risk.
Washington, DC: National Academy of Sciences; 1989.

Patterson RE, Haines PS, Popkin BM. Diet quality index:
capturing a multidimensional behavior. J'Am Diet Assoc.
1994; 94:57-64.

Popkin BM, Haines PS, Reidy KC. Food consumption trends of
US women: Patterns and determinants between 1977 and 1985.
Am J Clin NUtr. 1988; 49:1307-1319.

Randall MJ, Brink MS, Joy AB. EFNEP: An investment in
America's Future. J'Nutr Ed. 1989; 21(6):276-279.

Reicks M, Randall JL, Haynes BJ. Factors affecting
consumption of fruits and vegetabels by low-income families.

159

J’Am Diet ASSOC. 1994; 94(11):1309-1311.

Rogers MAM, Simon DG, Zucker LB, Mackessy JS, Newman-Palmer
NB. Indicators of poor dietary habits in a high fisk
popylation. J'Am Cbll NUtr. 1995; 14(2):159-164.

Romers VA, Medeiros DM, Melcher L. Use and effectiveness of
Wyoming EFNEP's lesson series. J'NUtr Ed. 1988; 20(1):15—19.

Sanjur D. Social and Cultural Perspectives in nutrition.
Prentice-Hall, Inc., Englewood Cliffs, NJ. 07632. pp. 174.

Schuette LK, Song WO, Hoerr SL. Quantitative use of the Food
Guide Pyramid to evaluate dietary intake of college
students. J'Am Diet Assoc. 1996; 96(5):453-457.

Singleton JC. Nutrition and Health Education for Limited
Income, High-Risk Group: Implications for Nutrition
Educators. J'NUtr Ed. 1994; 26(3):153-155.

Sorenson AW, Wyse BW, Wittwer AJ, Hansen RG. An index of

nutritional quality for a balanced diet. J’Am Diet Assoc.
1976; 68:236-242.

Stanton JL Jr, Keast-DR. Serum cholesterol, fat intake, and
breakfast consumption in the United States adult population.
J'Am Cbll NUtr. 1989; 8(6):S67-572.

Strychar IM, Achterberg CL, Sullivan LA. EFNEP for pregnant
teens. J'NUtr Ed. 1991; 23(1):40c-40d.

Thompson FE, Sowers MF, Frongillo EA, Parpia BJ. Sources of
Fiber and Fat in Diets of US Women Aged 19 to 50:
Implications for Nutrition Education and Policy. Am J Public
health. 1992; 82(5):695-702.

Tippett KS and Goldman JD. Diets more healthful, but still

fall short of dietary guidelines. Fd Rev. Jan-Apr 1994;
l7(1):8-14.

Torisky DM, Hertzler AA, Johnson JM, Keller JF, Hodges PAM,
Mifflin BS. Virginia EFNEP homemaker's dietary improvement

160

and relation to selected family factors. J'NUtr Ed. 1989;
21(6):249-256.

U.S. Department of Agriculture, Human Nutrition Information
Service. The Food Guide Pyramid. 1992. Home and Garden
Bulletin No. 252.

U.S. Department of Agriculture. Science and Education
Administration. Food. USDA's Daily Food Guide to the Rescue.
Home and Garden Bulletin No. 228, Washington, DC: Government
Printing Office, 1979, pp. 4-10.

U.S. Department of Agriculture. EFNEP Evaluation/Reporting
System User's Guide, Version 3.0. 1993. Developed by World
Computer System, Inc. Under Contract #53-3159-9-1.

U.S. Department of Agriculture. The Expanded Food and
Nutrition Education Program: Historical and Statistical
Profile. SEA—Extension Program Aide 1230, January 1979, PP.
40-41.

U.S. Department of Agriculture. Extension Service. EFNEP-
Impart and accomplishments. March 1994.

U.S. Department of Agriculture and 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 health and Human Services, Public Health
Service. The Surgeon General's Report on Nutrition and
Health-Summary and Recommendations. 1988. DHHS (PHS)
Publication No. 88—50211. US Government Printing Office.

Verma S and Jones JH. Educational Participation and Dietary
Changes of EFNEP Homemakers in Louisiana. HOme Economics
Research J. 1973; 2(2):94-104.

Walker 8., Akpom K., Nierman L. Finial report: Effectively
teaching foods and nutrition to low income families.
Cooperative Extension: Michigan State University. East
Lansing, Michigan. 1983.

161

Woteki CE. Measuring dietary patterns in surveys. Vital and
Health statistics, series 4. 1991, March (27): 101-8.

Watt BK and Merrill AL. Composition of Foods-Raw, Processed,
Prepared. Rev. USDA Handbook No. 8. Washington DC. US
Government Printing Office. 1963.

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