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Exploring the Connection Between the Nutritional
Status of Low—Income Female Caregivers and
Their Children

presented‘by

Sikhoya L. Wabuyele

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EXPLORING THE CONNECTION BETWEEN THE NUTRITIONAL STATUS OF
LOW-INCOME FEMALE CAREGIVERS AND THEIR CHILDREN

By

Sikhoya L. Wabuyele

A THESIS
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
MASTERS OF SCIENCE

Department of Resource Development

2002

ABSTRACT

EXPLORING THE CONNECTION BETWEEN THE NUTRITIONAL STATUS OF
FEMALE CAREGIVERS AND THEIR CHILDREN

By

Sikhoya L. Wabuyele

Income is clearly one of the most important determinants of food quantity and quality in
a household. Families that live in poverty are more likely to have insufficient food, poor
quality diets and are at risk for nutrition health problems such as, iron deficiency anemia,
and obesity than high-income families. The federally funded food assistance programs
that target women and children provide food, cash assistance, and / or nutrition education
to low-income families. The goal of this study was to explore the female caregiver-child
relationship of nutrient intake, iron and weight status. Female caregivers with high fat
intake, iron deficiency or overweight, were likely to have children with high fat intake,
iron deficient or overweight. Nutrient intakes, iron deficiency and weight status of the
female caregivers and their children were significantly positively correlation (r= .12 - .40,
p<.01). The positive relationship suggests that female caregivers influence children’s
food intake and dietary behavior. The policy and program implication of this finding is
that the relationship of caregivers’ and their children’s nutrient intake is an important
factor to consider when implementing nutrition intervention that aims at improving
dietary intake and habits. The findings of this study indirectly support nutrition
intervention programs that will target the entire family’s primary prevention for

nutritional inadequacy, iron deficiency anemia and obesity.

Copyright by
Sikhoya L. Wabuyele
2001

ACKNOWLEDGMENT

I would like to thank Dr. Jim Bingen, my academic advisor, for his guidance and support.
I would also like to extend my special thanks to my committee members Dr. Won Song
and Dr. Frank Fear for their comments, suggestions and valuable criticisms towards my
study. To my lab mates: Debra Kreast, Yikyung Park, Jean Kerver, Andrea Padgatt,
Soari Obayashi, Emily Meier, and Drs. Yang and Earnsukkawat for their friendship and
encouragement. My deepest gratitude goes to my parents and family for support and

understanding throughout this process.

iv

TABLE OF CONTENTS

CHAPTER ONE

INTRODUCTION
Background .................................................................................. 1
Problem Statement. ......................................................................... 8
Research questions .......................................................................... 9

CHAPTER TWO

RELATED LITERATURE
Nutrition Intake and Disease Risks. ..................................................... 11
Dietary Habits. ............................................................................. 13
Influence on children’s nutritional quality. ............................................ 16
Nutritional Health status ................................................................... 20

CHAPTER THREE

METHODOLOGY
Description of the Third National Health And Nutrition Examination Survey
(NHANES III) ............................................................................... 25
Description of the current study subjects, research design, sampling and sampling
criteria ....................................................................................... 26
Statistical Analyses ........................................................................ 28

CHAPTER FOUR

RESULTS
Socio-demographic characteristic ........................................................ 36
Results ....................................................................................... 38

CHAPTER FIVE

CONCLUSIONS AND RESEARCH AND POLICY IMPLICATIONS
Summary .................................................................................... 53
Conclusions ................................................................................. 56
Research and policy implications ....................................................... 58

REFERENCE MATERIAL

APENDICES
Appendix A: Working definitions of terms. ........................................... 65
Appendix B: Subjects excluded from the study ........................................ 68
Appendix C: Selection criteria for female caregivers in households with more
than one women in the Sample .......................................................... 69
Appendix D: table 2 ........................................................................ 70
Appendix E: table 3 ....................................................................... 71

Appendix F: table 4 ......................................................................... 72

Appendix G: table 5 ........................................................................ 73
Appendix H: table 6 ........................................................................ 74
Appendix 1: table 7 ......................................................................... 75
Appendix J: table 13 ....................................................................... 76
Appendix K: table 14 ...................................................................... 77
Appendix L: table 15 ...................................................................... 78
Appendix M: table 16 ..................................................................... 79
Appendix N: table 17 ...................................................................... 80
Appendix 0: table 20 ..................................................................... 81
Appendix P: table 21 ..................................................................... 82
Bibiliography ........................................................................................ 84

vi

Table 1.

Table 2.

Table 3.

Table 4.

Table 5.

Table 6.

Table 7.

Table 8.

Table 9.

Table 10.

Table 11.

Table 12.

Table 13.

Table 14.

LIST OF TABLES

Socio-demographic characteristics of children and female caregivers in the
study.

Children’s dietary adequacy of total energy, percent energy from total fat
and saturated fat by heir demographic characteristics.

Children’s daily adequacy of carbohydrates, dietary fiber, and calcium by
demographic characteristics.

Children’s dietary adequacy of micro-nutrients by demographic
characteristics.

Female caregivers’ dietary adequacy of energy, total fat and saturated fat
by demographic characteristics.

Female caregivers’ dietary adequacy of carbohydrates, dietary fiber, and
calcium by demographic characteristics.

Female caregivers’ dietary adequacy of micro-nutrients by demographic
characteristics.

Relation between children’s vs female caregivers’ tertiles of nutrient
intake.

Relation between children’s vs female caregivers’ tertiles of micro-
nutrients.

Percent children who consumed breakfast and RTEC by age-group, race-
ethnicity, WIC participation, and family size.

Percent female caregivers’ who consumed breakfast and RTEC by age—
group, race-ethnicity, WIC participation, and family size.

Iron status of the children and female caregivers.
Cut-point values of iron bio-makers

Distribution of the children’s triceps (5 or > 85%tile) by age-group,
gender, race-ethnicity, and WIC participation.

vii

Table 15.

Table 16.

Table 17.

Table 18.

Table 19.

Table 20.

Distribution of the children’s weight-for-height (5 or > 85%tile) by age-
group, gender, race-ethnicity, and WIC participation and family size.

Female caregivers’ BMI and BMI classifications by their age-group, race-
ethnicity, WIC participation and family size.

Female caregivers’ triceps percentiles by their age-group, race-ethnicity,
WIC participation, and family size.

Children’s weight-for-height vs their female caregivers’ BMI score.
Children’s weight-for-height vs their female caregivers’ triceps skinfold
percentiles.

Female caregiver-child correlation for nutrients, breakfast consumption,
iron weight status.

viii

Chapter One

INTRODUCTION

Background

The third report on nutrition monitoring in the United States shows that low-
income households are at higher risk for nutrition-related health problems compared to
hi gh-income households. Poverty is one of the leading causes of poor nutrition; poor
nutrition is associated with lack of money and other resources such as food sufficiency
and nutritional knowledge (NMRRP, USDA, 1995). A recent review of dietary and
nutrition status of the US. population concluded that low-income groups are more
vulnerable to nutrition-related disease. The prevalence of nutritional heath problems in
low-income families is higher than in high-income families (Lin et al 2001).

Poverty exposes children and other family members to a wide array of health
problems that includes food insufficiency, and poor dietary intake and eating habits.
According to the Census Bureau (2000) about 11.3% of the US. population falls into the
low-income category; approximately 287,000 individuals may be exposed to poor diets
due to insufficient access to nutritious food. About four million children under age 12 do
not have enough to eat in their homes, and yet another 9.2 million are at risk for a
shortage of food. The nutrient intake of children who live in food-insufficient households
does not meet the recommended guidelines; these children are deficient in most nutrients
required for proper growth and development (Wehler, 1991).

Women and children are at highest risk for nutrition deficiencies and health risks.

Iron deficiency is the most common nutrient deficiency in women and children; it is

highest among low-income households. The prevalence of iron deficiency and anemia
raises health concerns due to the serious health risk; iron deficiency in children is
associated with developmental delays and permanent impairment to mental development
(www.healthgov/healthpeople/default.htm). A report from the third National Health and
Examination Survey (1988 — 1994) by Looker and colleagues (1997) showed the
prevalence of iron deficiency in children in the US. was 3—9%, while iron—deficiency
anemia was 1—3%. Among females aged 12—49, iron deficiency was 9—11%, and iron-
deficiency anemia was 2—5 %. The CDC report (1997) indicated that among low-income
children, 18.4% under 2 years and 16.9% ages 2-5 years had anemia. The Healthy
People Objective 2010’s target is to reduce iron deficiency in children ages 1—2 years to
5%, 3—4 years to 1% and female ages 12—49 to 7%.

Obesity has been associated with the development of heart disease, Diabetes
Mellitus, certain cancers, and stroke. There is an increase in childhood obesity, with the
highest increase among low-income children from 14% to 25—29%. Obesity has been a
prevalent problem for US. adults, and studies have shown an increase from 12% to 33%
—36% (Traino and Flegal 1995). About 280,000 deaths annually are associated with
obesity, and US. government health care costs for disease associated with overweight
and obesity have been estimated at 6.8% of the overall US. funds allocated. Studies show
that childhood obesity may persist into adulthood; therefore, an increase in childhood
obesity will result in increased heath risks for both children and adults. Deterrence of
childhood obesity can reduce and prevent health-related problems, such as heart diseases

in both children and adults, and can reduce health care costs.

In the 19605 there was a drastic increase in poverty that had severe consequences
on nutrition-related public health problems. To address this alarming health crisis, the
federal government established public food and cash assistance programs that were
intended to mitigate the effect of poverty on low-income families by providing food and
nutrition education. The federal government, through the US. Department of
Agriculture, funded the food assistance programs to improve nutritional quality and
prevent further development of nutritional health-related problems, and also promote
growth and development among low-income groups. The primary purpose of these
programs was not only to improve nutritional health status of low-income households but
also to reduce government health care costs (Better Nutrition Act for Children, 1994).

The US. Department of Agriculture coordinates many federal and state programs
that provide food and cash assistance to target low-income women and children. Some of
the programs include the Special Supplemental Food Program for Women, Children and
Infants (WIC), the Food Stamp Program (F SP), the Expanded Food and Nutrition
Education Program (EFNEP), the National School Lunch Program (NSLP), the National
School Breakfast Program (NSBP), and the Head Start Program, among others (USDA,
1997)

The Special Supplemental Food Program for Women, Infants, and Children (WIC)

WIC provides supplemental foods, nutrition and health education, and Social
Services referrals to low-income pregnant mothers, postpartum women, infants, and
young children up to five years of age. Food vouchers are provided for obtaining specific
supplemental foods high in iron, calcium, protein, vitamin A, and vitamin C. The criteria

for participation in the WIC program are based on income and nutritional status. The

income requirement stipulates that an applicant’s gross income must be at or below 185%
of the poverty level—the equivalent of a $32,600 annual income for a family of four
(effective July 1, 2001—June 30’ 2002). The nutritional status requirements refer to the
risk of anemia, low weight, poor pregnancy outcome, and an inadequate diet. The
mission of the WIC program is to safeguard the nutritional health of low-income women
and children by providing nutritious foods to supplement diets, nutrition information for
good health, and referral to health care (www.fns.usda.gov/wic).

Since the start of the program in 1974, the number of participants has increased
greatly from 344,000 participants per year in 1995 to 7.4 million people per month in
1997 (Owen and Owen, 1997). Studies have shown that the program has contributed
substantially towards the improvement of the health status of the nation’s low-income,
nutritionally at-risk families (Rose et a1, 1998).

The Food Stamp Program

The Food Stamp Program (FSP) was established in 1962 by the federal
government to end hunger by providing cash assistance to poor families for food
purchases with the goal of improving their nutrition and health status. The FSP is the
cornerstone of the federal food assistance programs, and it provides essential support to
needy families and those making the transition from welfare to work. F SP is the only
assistance program that provides cash assistance to low-income households with income
level at or less that 130% poverty level, which is equivalent to a _<_ $22,945 annual income
for a family of four (www.fns.usda.gov/fsp).

The main purpose of FSP is to increase the nutrient intake of the at-risk

population. Program evaluation reports show that FSP has increased low-income

individuals’ food supply, but has had little impact on participants’ nutrient intake. F SP
may not have achieved its goal for various reasons: 1) food stamp recipients may use the
food stamps to purchase items other than food; 2) food stamps may be used to buy foods
that do not improve the nutrient intake for the family members, such as “empty calorie”
foods, since the program does not have any restrictions on the types of foods purchased
with food stamp vouchers; 3) low-income individuals who qualify for the program and
need food assistance may not be enrolled in the program (www.fns.usda.gov/fsp).
The National School Food Programs

The National School Lunch Program (N SLP) and National School Breakfast
Program (N SBP) were enacted in 1966 to provide food for malnourished school children
from poor households. The objective of the National School Food Assistance Programs
is to reduce malnutrition by increasing the nutrient intake of program participants. NSLP
and NSBP continue to serve low-income school children, and reports show that they have
reduced rates of student absence, increased nutrient intake, and improved children’s
school performance. Both programs are required by the US. Department of Agriculture
to provide meals that meet the dietary guidelines for Americans; this means they must be
used to serve food in which 5 30% energy is from total fat and f 10% energy is from
saturated fat. The lunch meals are expected to provide one-third of the children’s
Recommended Daily Allowance (RDA) for protein, vitamin A, vitamin C, calcium, iron,
and calories. The breakfast program is required to meet one-fourth of the children’s
RDA for protein, vitamin A, vitamin C, calcium, iron, and calories (USDA, 1995).

NSLP participation has increased tremendously from 7.4 million children in

1946—1947 to 27.4 million children each day in fiscal year 2000. Approximately 7.55

million children participated in the NSBP each day in fiscal year 2000. NSLP and NSBP
programs provide free meals for children from households with income levels at or below
130% poverty (for a family of four this is equivalent to $5 22,945), meals for half-price
for children from households with income between 130—185% poverty level (for a family
of four, this is equivalent to an income between $22,946—32,653) and pay full-price for
meals for children with income over 185% poverty level. The Nutrition Initiative Team
has the responsibility of teaching and motivating children to make healthy food choices
and to provide the school food service with training and technical support. Reports show
that school food programs have successfully improved children’s nutritional quality and
school performance.

The Expanded Food and Nutrition Education Program (EFNEP) and Head Start
Program have objectives similar to other nutrition programs for low-income populations.
Unlike other nutrition programs, however, EFNEP and Head Start Programs only provide
nutrition education to enrolled participants. The programs offer nutrition education to
low-income individuals (this includes both youth and adults) on nutritional knowledge,
skills, and attitude and behavioral changes necessary for an adequate diet and for disease
prevention. The EFNEP teaches homemakers and youth new skills in healthy food
choice, preparation, storage safety, and better management of their budget related to food
resources available to them, such as food stamps. Studies indicate that EFNEP has
improved its participants’ nutritional knowledge and intake. (USDA, 1994).

There is evidence that food assistance programs can affect the type and amount of
food intake of low-income p0pulation. Reports on the effectiveness of the federally

funded programs mostly indicate that the programs have improved the nutritional quality

of the low-income program participants by improving their nutrient intake and their
eating habits. The Food Stamp program has had a very beneficial effect on the aggregate
household dietaryintake (Basiotis’ (1997). One strong positive outcome of nutrition
programs is an increase in the quantity of food consumed. However, the effect on the
quality of nutrient intake is uncertain. Increased food expenditure does not necessarily
indicate a more healthful diet. WIC, SLP, and SBP have had a positive impact on the
diets of their participants (at least while the participants were still in the program). FSP
has the largest budget and number of recipients, yet there is no convincing body of
evidence that this program improves the overall quality of participants’ nutrient intake;
there is some indication that the program has increased intake of certain nutrients. Other
studies indicate that meals provided by the school food programs are high in dietary fat

and do not meet the recommended dietary guidelines of Americans (www.fns.usda

 

/programs).

Nutrition programs for low-income households focus on increasing food
accessibility and improving their nutrient intake. The primary purpose of these programs
is to decrease the prevalence of nutrition-related diseases by reducing nutrition
deficiencies and improving eating habits of its participants. The few studies on familial
aggregation of nutrient intake and nutrition health risks between parents and their
children observe similarities in nutrient intake. The conclusion made from these studies
is that parents’ eating habits influence the children’s nutrient intake (Oliveria et al 1992).
Their influence on children’s dietary intake is considerable. A better understanding of

the impact can aid in designing nutrition programs for low-income families.

Problem Statement

Low-income individuals are at nutritional health risk due to poor and inadequate
nutrition, poor dietary habits and lifestyle. Low-income families are disadvantaged
because of inadequate income to meet their nutritional needs as well as other everyday
family needs; they also lack other resources or have inadequate resources necessary for
provision of nutritionally adequate diets for family members, such as knowledge on
nutrition and disease.

The goal of the federal food programs is to help low-income families increase
their food supplies and ultimately improve their nutritional intake and dietary habits. The
USDA coordinates federal and state programs that provide food, cash assistance, and
nutrition education to the low-income population. Some of these programs include: the
Special Supplemental Nutrition Program for Women, Infants and Children (WIC), the
Food Stamp Program (FSP); the National School Lunch Program (NSLP); the National
School Breakfast Program (NSBP); the Nutrition Education Training Program; the
Expanded Food and Nutrition Education Program (EFNEP); and the Head Start Program,
among many others.

Nutrition programs mainly target low-income women and children because of
their high vulnerability to inadequate nutrition and related health problems, such as iron
deficiency, anemia, and obesity. The WIC program targets women, infants, and children
due to the high prevalence of iron deficiency and iron-deficiency anemia, as well as the
inadequate nutrient intake among these groups. Women are also considered to be the

main meal planners in households. Therefore, they are provided with nutrition

1.

information, and they are expected to utilize the nutritional knowledge and resources
acquired from nutrition programs to make positive dietary changes and eating habits for
their children and other family members. Morton et a1 (1997) report that an increase in
parental nutrition-related knowledge through nutrition programs had led to an
improvement in the nutritional quality of children.

Despite the efforts of nutrition programs to alleviate nutrition problems in low-
income groups, nutrition inadequacy and poor diets remain a health problem in this
population. Studies have shown that there is a familial aggregation of nutrient intake and
that parents, mothers, or caregivers may influence the nutrient intake, food choices, and
dietary habits of their children. Parents’ or caregiver’s influence on children’s food intake
can hinder the effectiveness of low—income nutrition program interventions that target
children. Therefore, it is important to examine the relationship between female
caregivers’ and their children’s nutritional health status and how this relationship can
impact nutrient intake of the children and other family members.

Research is limited on the relationship of nutrient intake and health status between
parents or caregivers and their children and how this relationship may influence or
improve the dietary intake and habits of the children and other family members. Little is
known about familial nutrient aggregation and nutritional heath status of low-income
households that participate in nutrition programs. Given these limitations, this study
examines the female caregiver-children relationship in low-income households with
respect to their nutrient intake and nutrition health status.

This study is designed to answer the following four research questions:

How does the nutritional status of children relate to their female caregivers?

2. What is the relationship of the children’s breakfast consumption pattern to their female
caregivers?

3. How does the children’s iron-deficiency anemia relate to their female caregivers?

4. How does the children’s weight status relate to their female caregivers’ adiposity?

The next chapter reviews the literature related to nutrient intake and nutritional
deficiencies, and how these deficiencies affect the health status of low-income population. Iron
deficiency and obesity as indicators of poor nutrition and health risk will be discussed.
Nutritional issues on breakfast consumption, consumption of fi'uits and vegetables and high-fat
foods and their association to nutrition and health of low-income women and children will be
explored. Following Chapter Two, Chapter Three describes the data and sample used in this
study, and the statistical methods used in the data analysis. Chapter Four presents the results of
the statistical analyses. The last chapter summarizes the main conclusions and offers selected

policy and research implications that emerge from the study and other related studies.

10

Chapter Two

Nutrition Intake and Disease Risks
Nutrition Issues and Deficiencies

This chapter reviews the literature on nutritional issues in relation to low-income
households, iron deficiency, obesity, and the effect of the parent-child relationship on
nutrient intake. A review of the literature on fruit and vegetable consumption, breakfast
consumption, and high-fat food intake as indicators of low nutrient intake is also
included. This chapter also discusses the risk factors of obesity and other related disease
risks, and parental influence on children’s dietary intake and prenatal care.

It is clear that poor diet contributes substantially to the development of diseases,
and that diet modification contributes to the prevention of these diseases. Over-
consumption of certain dietary components at the expense of other nutrients has a
negative effect on health. Diseases caused by dietary excess and imbalances not only
rank among the leading causes of death in America, but they also play a prominent role in
chronic disease epidemics currently challenging many Western nations.

Low-income and Poor Nutrition

According to a study done by Kennedy and Goldberg, children's caloric
consumption has been constant, and most children met other nutritional requirements but
were deficient in iron and calcium (1 995). Data from 1960—1970 has revealed that
children from households below poverty level income were thinner and shorter than those
from high-income households. These results suggest that low-income children are

susceptible to poor nutrition (Sherry 1993).

ll

Results concerning the food consumption of low-income women from the
National Foods Consumption (NFC) data for 1988 indicated a deficiency in calcium,
zinc, and vitamins A, C, and E (Scrimshaw, 1993). The National School Advocate
Organization that examined nutritional intake of school children reported that children
consumed high amounts of cholesterol, sodium, and fewer carbohydrates. Children from
low-income families had inadequate caloric intake, iron, calcium, and vitamins (Monis
1996). There is evidence that nutritional adequacy of young children’s diet has
decreased, with calcium intake being considerably lower than the recommended
allowance (Roberts 2000).

Nutritional quality has been identified as the origin of a wide range of diseases
and disabilities. Scrimshaw illustrates that eating habits and lifestyle affect dietary
practices (1993). Diseases can be prevented by improved dietary intake and related
lifestyles (Surgeman, 1995). The Cooking and Eating Nutrition and Shopping Survey
showed that for a quarter of the low-income Hispanic women, dietary intake was less
than two-thirds of the Recommended Dietary Allowance for vitamin A, thiamin, niacin,
and riboflavin. About half the participants' diets were deficient in iron intake (J of Am
Diet Assoc 1995). Improving low-income women’s nutrition is necessary for the
implementation of dietary change to meet the recommended dietary intake.

Children are a target group for the Healthy People 2000 objectives since they are
nutritionally a high-risk group (DHHS, 1991). Childhood is a critical time for developing
a healthful attitude and behavior patterns related to food choices and physical activity.
Dietary habits and food preferences developed in childhood play an important role in

growth and development, as well as in the prevention of chronic diseases later in life

12

(Reeds, 1996). Poor nutrition among American children is on the rise, partly due to poor
eating habits that include overeating and skipping breakfast. Children of low
socioeconomic status have less diverse diets, and children with single parents are likely to
skip meals and eat fewer vegetables compared to those children with two parents (Wolfe,
1994). Nutritional intervention for specific age groups based on socio—demographic
characteristics will help improve children’s nutritional needs.
Dietary Habits
Breakfast Consumption

Breakfast, and fruit and vegetable consumption are included in this review
because they are good indicators of healthy dietary habits. In the current study, however,
data on fruit and vegetable consumption were unavailable; therefore, they were not
included in the study analyses. Consumption of breakfast and Ready-to-Eat-Cereal
(RTEC) and fruits and vegetables was also used as an indicator of nutrient adequacy
because it contributes tremendously to the daily nutrient intake and intake of vitamins
and minerals.

A study that assessed breakfast intake of 10-year-old children found that breakfast
consumption significantly contributes to the children's mean daily intake average.
Studies indicate that children who skip breakfast have significantly lower intakes in
energy and micronutrients (Nicklas, 1993), vitamin A, C, vitamin B6, and iron, compared
to those who had breakfast (Sampson, 1995). Children who eat more snacks were more
likely to skip breakfast; this is more prevalent in children with single parents (Nicklas,
1993). This is a clear indication that breakfast consumption is vital for nutrient quality

and adequacy for school children. Breakfast is referred to as the most important meal of

13

the day. Consumption of RTEC for breakfast increases the amount of minerals and
vitamins in a diet. Reduction in iron deficiency and iron-deficiency anemia in low-
income children has been attributed to the increased consumption of iron-fortified RTEC
provided by the WIC program to the children enrolled in the program (Hills, 1996).
Breakfast skipping has been shown to increase nutrition risks due to low vitamin and

mineral intake.

Fruit and Vegetable Consumption

Fruits and vegetables, a source of essential vitamins and minerals for the body,
are an important part of a healthy diet. Studies have shown that nutrient and non-nutrient
components of fruits and vegetables may reduce cancer risks. Barriers to fruit and
vegetable intake are the largest causes of variability in the actual consumption of fruits
and vegetables. Individual beliefs about the relationship between health and deficiencies
of certain nutrients may influence the readiness to improve the intake of a particular
nutrient.

Barriers to consumption of fruits and vegetables include poor eating habits, cost,
availability, lack of nutrition knowledge, and time. There is a need to balance the
benefits and barriers that influence peoples’ behavior and their readiness to consume
fruits and vegetables. Low-income women participants of the Expanded Food and
Nutrition program (EFNEP), a federally-funded nutrition education program, perceive the
consumption of fruits and vegetables as another expense that requires them to give up
other foods (Reick, 1994). One of the objectives of Health People 2000 is to increase the
consumption of complex carbohydrates and hi gh-fiber foods, as well as increase servings

of fruits to 4 per day and 3—5 servings per day of vegetables. According to CSFII 1985,

14

women from 19—50 years of age consume only 2.5 servings of fruits and vegetables,
below the Recommended Daily Allowance (RDA); and, only 24% of the population
meets the requirement for fruits and 12% for vegetables (Kreb-Smith, 1995). Given that
children have inadequate intake of dietary fiber, their fiber intake can be increased
gradually by increasing the consumption of fruits, vegetables, cereal, legumes, and other
whole grain products (Williams, 1995). Low-income children and women have a lower
intake of fruit and vegetables, and dietary fiber than the recommended levels
(Baranowsk, 1993, Wieche, 1994). Low-income women need to increase their
consumption of fruits and vegetables, and whole grains to meet the recommended dietary
guidelines (Thompson, 1992).

Though Americans have improved the quality of their diets over the last 30 years,
they still consume excessive levels of fat and inadequate amounts of fruits and vegetables
(Kimanyika, 1993). Morton and Gutherie (1994) report that progress has been made in
implementing Dietary Guidelines in the US. except for the inadequate consumption of
fruits and vegetables, and over-consumption of fats by both adults and children. A study
aimed at increasing the consumption of fruits and vegetables among low-income women
found that, though women were responsible for shopping and preparation of foods, they
did not cook extensively. The time required and effort necessary for preparation were

some of the baniers to fruit and vegetable consumption (Beto, 1997).

15

Influence on children’s nutritional quality

Parent/caregiver’s Influence

Children are part of the target group for the national health promotion for Health
People Objectives 2000 because they are at high risk for poor nutritional health.
Nutritional habits developed in childhood play an important role in growth and
development and in the prevention of chronic diseases. Parental food practices may
influence their children’s dietary choices (Kennedy et a1. 1995). In the Frarningham
children’s study, Oliveria and colleagues (1992) concluded that parents or caregivers’
dietary habits affect the nutrient quality of the children’s diet. Children tend to eat foods
that are made available by their caregivers at home. If high-fat foods are available to
children, they will develop a preference for high-fat foods.

A study by Laskaezeewski et a1 (1980) revealed that the parental intake of total
calories, saturated fat, poly-saturated fat, and carbohydrates was significantly and
positively correlated with their children’s intake of total calories, saturated fat, poly-
saturated fat, and carbohydrates. The implication of this finding is that parent—child
nutrient intake relationship is important in the nutrition intervention that intends to
improve dietary intake and food habits of the family unit; thus, nutritional interventions
that target low-income children need to focus on improving nutrient intake of the whole
family as a unit.

The development of lifelong eating behavior is shaped by a multi-factorial
process in which parents or caregivers are the key players (Nahikian-Nelms, 1997). In
the attempt to change the dietary behavior of children, the interest and cooperation of

caregivers is essential to achieve successful results. A caregiver’s acceptance of

16

nutritional knowledge and willingness to implement an adequate, nutritious diet
associated with reduced fat intake in children may lead to prevention of nutrition-related
diseases.

Certain food behavioral patterns adopted during childhood and adolescence may
result in chronic diseases in adulthood. Children’s food preferences may be altered by
parental food choices (Wagner, 1992). Caregivers in a household are expected to help
their children establish healthy food behaviors and attitudes by providing a healthy diet
and exemplifying desirable food behaviors and attitudes (Stanek, 1990).

Parent’s food behaviors and choices influence the amount of food their children eat, the
children’s eating time, as well as their food likes and dislikes (Seargant, 1990). There are
discrepancies in research findings about the female parents’ influence over the children's
food preferences and behavior. Some researchers found a significant relationship
between food preferences of preschool children and their parents, others found no
significant differences between the female parents of obese children and non-obese
children.

Parents and caregivers have the responsibility of making decisions on food
purchases and food preparation and availability to the children and other family
members. Therefore, the role of caregivers in making these decisions determines the
dietary quality of nutrient intake of the children. Children in a household might prefer
certain foods, which may in turn influence their caregivers’ decision on the type of foods
to purchase. This eventually determines the dietary pattern and, hence, the quality of the

children’s and other family members’ diet.

17

Staflan et a1. (1996) also showed a correlation between the mothers’ and
daughters’ nutritional attitudes, knowledge, and fat intake. To reduce fat intake in a
household, there is need for a family approach rather than an individual approach,
because there are similarities in family members’ attitudes and knowledge regarding
dietary fat. This approach will implement a quicker dietary change in a family as a
whole, which will eliminate disease risk factors in a family. According to Korch, U. S.
children have dietary intake that is adequate in quantity but not in quality. Parental
participation in food and nutrition programs can improve nutritional status of their
children (1989).

An increase in parental nutrition-related knowledge through nutrition education
programs for low-income groups leads to improved diets for their children (Variyan,
2001). Role modeling and continuous communication with family members, provision of
adequate nutrition, and physical exercise may not only help prevent or reduce obesity but
may also alleviate dietary inadequacy that will prevent nutrition-related diseases (USA
Today, 1994).

Koblinsky et a1 (1992) conducted a similar study with the Head Start program, a
federally-funded program for low-income families. He examined the effects of the
nutrition education program on the parents of the children enrolled in Head Start and the
dietary intake of these children. The goal of the program was to educate the mothers on
food purchasing and preparation of nutritious foods and snacks. Both groups reported
that they had made recent changes in their children’s diet, in their shopping behaviors,
meal planning, and food preparation methods. Despite the nutrition education, women in

the treatment group and the control group did not change their own diets. The only

18

change observed was the mothers’ reduced sugar and salt intake. The relationship
between program participation and dietary measures showed a weak but positive
correlation (r = 0.3, p < 0.05). There was no correlation between reading the newsletter
and post—dietary diversity in Head Start children (r =25, p < 0.09). Research has
indicated that increased parental nutrition-related knowledge leads to an improvement of
children's nutritional intake. Nutrition education programs have had a positive impact on
the Head Start parents’ nutrition-related behavior that resulted in an improvement of
children's diets that had fewer servings than the RDA. Children should gradually change
food intake and adopt an intake of not more that 30% of the calories from fat between the
ages of 2—5 years.

One of the goals of the Heart Smart Promotion Program is to improve
cardiovascular health not only for the children but also for the entire family. The
program focuses on increasing and maintaining positive dietary behavioral change, social
support, and enhancement of self-confidence (Johnson, 1995). Risk factor transformation
can begin at early ages of life at home and at school. It is easier to change health
behaviors in children than in adults. Health education is important in schools. However,
this approach may not succeed without the involvement of the parents and or mothers.
Children get most of their meals at home; it is therefore the role of the family members,
parents, or meal planner to ensure that children consume high quality diets for their good

health (Taubert, 1996).

19

Nutritional Health Status
Iron Deficiency and Iron-Deficiency Anemia

Iron deficiency is the most common known nutrition deficiency in children,
adolescents, and childbearing women the United States. There is a high prevalence
among low-income minority groups (Looker, 1997). About 20—24% of the low-income
African-Americans and Hispanics are anemic; this is an indication that, although the
prevalence has decreased, iron-deficiency anemia is still a major problem. There has been
less attention towards under-nutrition, especially among poor children, which has resulted
in increased illnesses among the poor (Pollitt, 1994).

A study that examined incidences of anemia in Head Start children found that
over 24% of 467 children had low levels of iron intake. More black children were
anemic, with the highest percentage of 27.3% versus that for white children. This implies
that anemia is a serous health problem in low-income families. This study concluded that
nutrition programs have not met the nutritional needs of low-income children in terms of
avoiding iron deficiency and iron-deficiency anemia (Francis et al, 1993). Iron
deficiency has been attributed to early introduction of cow’s milk to infants, consumption
of unfortified infant formula, low birth weights, and low economic status cereal.

Hunter reported that iron deficiency and iron-deficiency anemia among infants is
decreasing because of increased use of iron-enriched formula and other baby foods.
Despite that, there are approximately 240,000 children in America between ages 1—2
years that are anemic, and about 3.3 million American women of child-bearing age are
anemic due to a deficiency in dietary intake. Iron-deficient pregnant woman are not only

at risk for pre-term deliveries, but also for low birth weight babies. The decreased

20

prevalence of iron deficiency in high-risk infants and children may be achieved through
use of iron-fortified infant formula and other fortified children’s foods.

The third National Health and Nutrition Examination Survey (NHANES III)
1988—1994 revealed that 9% of 1—2 years old and 9-11% adolescents and women of
childbearing age were deficient in iron. Of these, 3% of the children, 2% of the
adolescents, and 5% of the women were found to have iron-deficiency anemia. A study
by Sanjur et a1. (1990) also showed that toddlers were deficient in iron. Recent studies
indicate that anemia in infancy and early childhood continues to improve, but the existing
deficiencies need to be addressed (Sherry, 1997).

A study done in the UK. by Harbottle and Duggan (1992) on preschool children
investigated whether diet affects the iron status of children. They found that a more
diverse and adequate dietary pattern was observed among children with normal iron
status. This was a cross-sectional study to determine whether dietary deficiency exists
between iron-deficient and non-deficient children. There is a high prevalence of iron
deficiency in children, adolescent girls, and women of childbearing age. One of the risks
of iron deficiency in children is its effect on brain development and increased risk of pre-
term delivery and low birth rate weight babies in women. Iron deficiency has declined in
children due to the consumption of iron-fortified foods in the United States.

A study by Bountry and Needlman ( 1999) of African American children ages 15—
60 months on the relationship between diet and microcytic anemia found that dietary
inadequacy was associated to iron microcytic anemia. Iron-deficiency anemia is a public
health problem in both developed and undeveloped countries. Approximately 30% of

children and woman of childbearing age and pregnant woman have iron-deficiency

21

anemia. It affects both hi gh-income and low-income populations. Attention needs to be
given to the inadequate of iron intake, especially at different life stages, and when the
individuals are most at risk. Studies have shown that dietary factors other than low iron
intake can contribute to IDA. Some food constituents inhibit iron absorption.
(Althaimeen et a1, 1999).

Kirchiner (1998) reported that the promotion of breastfeeding and the use
of iron-fortified formula and foods have almost eliminated iron deficiency in
infants. In his study, he concluded that the significant prevalence of iron
deficiency is in children between ages 1 to 3 years due to change of diet from
breast milk and iron-fortified formula to regular cow’s milk and adults non-iron
fortified cereals that are low in iron.

The Special Supplement Program for Women, Infants, and children (WIC) is a
federally-funded program that has positively contributed towards reducing iron
deficiency (Scholl et al 1994). WIC program provides food supplements high in iron to
low-income pregnant women, their infants and children of ages 1—5 years. Participation
in the WIC program has resulted in a reduction in iron deficiency, increased birth weight,
and improved nutritional status of low-income children (Krieger et a1 1999).

Obesity

In recent years, an increasing trend toward child obesity has become a health
concern in the United States. Kim et al. used NHANES II data to evaluate the dietary
patterns of US. children. The findings revealed that children ages 2 and over consumed
35—36% energy from total fat, and 13—18% from saturated fat, both of which were above

the recommended levels. Black children had a higher intake of cholesterol than white

22

children. Similar results have been found in other studies, such as the Bogalusa Heart
and the Lipid Research Clinical Preventive Studies; unfortunately, investigations to date
have not been successful.

Factors associated with obesity in children (as well as in adults) include total fat
intake and educational level. Kim's explanation of the role of dietary fiber in obesity is
that fiber reduces satiety, which may have a potential effect on weight reduction.
Prevention of childhood obesity may result from consumption of recommended dietary
fiber (Kim, 1995). Research confirms that obesity and high blood cholesterol levels in
United States’ children are higher than optimal levels (Ernst 1994).

A study of the weight status of children participating in the supplemental
food program for Women Infants and Children (WIC) showed that preschool
children were overweight. But the WIC program was not associated with the
increased overweight among the preschool aged children (MMWR, 1996). These
results indicated that the diets of children in their homes and outside their homes
might have contributed to the increased overweight in the WIC preschool
children. A Head Start study that screened for growth, obesity, wasting and
stature in children indicated that children enrolled in the program are at a high risk
for obesity.

A study conducted on the quality and adequacy of dietary intake of
students participating in the National School Lunch (N SLP) and School Breakfast
Program (SBP) revealed that the students’ dietary intake does not meet the
Recommended Dietary Allowance (RDA). Inadequate dietary consumption, in

school and at home, contributes to children's poor dietary intake (Osganian,

23

1995). The NSLP and SBP are associated with excess energy intake from fat,
sodium, and low-fiber intake (Brownner, 1996). School Food Programs should
meet the recommended nutrition guidelines to improve the nutritional quality of
national school meals and the children's overall dietary intake.

Fisher and Birch reported that children's fat preferences and consumption were
strongly related to parental adiposity. The reason children of heavier parents preferred
high-fat foods and consumed high percentages of energy from fats might be related to the
availability and exposure to high-fat foods (1995). An obesity prevention program for
African American women and their daughters of ages 8—12 years reported that mothers
improved their own eating patterns more than their daughters’. This finding supports the
importance of effective parent-child prevention programs in high-risk populations
(Fitzgibbon, 1995).

In summary, low-income women and children are more at risk for nutritional
health problems than those living in hi gh-income households. Low-income children and
women have: nutrient intake lower than the recommended levels, a higher prevalence of
iron deficiency and iron-deficiency anemia, and a higher intake of energy from total and
saturated fat than the recommended allowance. Increased prevalence of obesity in low-
income children and women is due to over-consumption of dietary fat and physical
inactivity. The parent—child relationship of nutrient intake and health risks indicated the
parental influence on children’s dietary intake and eating patterns eventually affects

children’s nutrition and health status.

24

Chapter Three

Methodology

The source and description of the data used in this thesis and the statistical
methods used to analyze the data are discussed in this chapter. The sample used for this
thesis was selected from the Third National Health and Nutrition Examination Survey
(NHANES 111) 1988-1994. A brief explanation of NHANES 111 subjects and sampling
design is given. The subjects, research study design and sampling, sample selection
criteria, and statistical method of data analysis are also presented.

Description of the Third National Health and Nutrition Examination Survey
(NHAN ES 111), 1988-1994

The National Health and Nutrition Examination Survey (NHANES 111)
1988—1994 was conducted and data were provided by the National Center for
Health and Statistics (NCHS) and the Center for Disease Control (CDC) on a CD-
ROM. NHANES is conducted periodically to assess the health and nutrition
status of the civilian non-institutionalized population of the United States. Goals
of the NHANES 111 include: 1) to estimate the prevalence of selected diseases and
risk factors, and 2) to investigate and document reasons for secular trend of
certain diseases and risk factors.

The survey contains data on individuals’ dietary recall and the laboratory
file includes data on the subjects’ blood analyses. Subjects who did not provide
complete dietary information as defined by the National Center for Health
Statistics (NCHS) were excluded from the study. Five data files were used to

obtain information used in the current study.

25

Description of the Study Subjects, Research Design and Sampling,
and the Sample Selection Criteria
Subjects

The subjects for the analyses in this thesis study were a subgroup of a
National Health and Nutrition Examination Survey (NHANES III) 1988—1994
with income level at or below 185% poverty level (for a family of four with
annual income at or below $32,653). A sub-sample was created of children aged
2—9 years and female caregivers of childbearing age (15-49 years) with complete
and reliable 24-hour dietary recall information. The female caregivers had at least
one live birth and also had at least one child sampled from the same household.

A female caregiver is a low-income female of childbearing age. These
females include all women ages 20—49 and girls’ ages 15—19 years with at least
one live birth living in the same household with a child aged 2—9 years. A total of
990 children aged 2—9 years were matched to 990 female caregivers with poverty
level of at or below 185%. Data collected from the subjects and used in this study
included: dietary information, biochemical, and anthropometric measurements.
Adults provided self-reported, one-day dietary recall information. A proxy
respondent provided children’s dietary recall information. A proxy respondent is a
family member, 17 years of age or over (preferably a parent or a guardian) living

in the same household.

26

Research Design and Sampling

The current study was undertaken using a cross-sectional study design for
the four study questions (see Chapter 1). This included an assessment of nutrient
intake and breakfast consumption of the children and their female caregivers, as
well as a determination of whether there was a female caregiver-child relationship
in dietary adequacy, breakfast consumption, iron, and weight status.

Two separate datasets were created from the NHANES III data: the
children’s dataset and the female caregivers’ dataset. The children’s and the
female caregivers’ datasets included information on socio-demographics, dietary
intake, anthropometrics, and blood analysis for iron biomarkers. The socio-
demographic variables were sex, age, family’s Income Poverty Ratio,
Participation in the Women Children and Infant supplement program (WIC), and
family size. The children’s data file was then merged with the female caregivers
data file to create a final data file that was used in this study.

Dataset selection. (See the appendix B for Criteria for excluded cases)

Two data sets were then created:

0 Children’s data with 2,393 children (aged 2—9 years) from households with at
least a female caregiver in the sample, and

0 Female caregivers’ data with 1,923 female caregivers (ages 15—49 years) from
households including at least one child 2—9 years of age.

Among the 2,393 children with at least a female caregiver in the
household, households with multiple children were selected. To obtain one child

per household from the 2,393 children, a random selection was performed and a

27

total of 1,704 children were selected. The family sequence number was used to
match the child to female caregivers in a household. In other words, a child and
female caregiver with the same family sequence number came from the same
household. Using a merging function in SPSS, female caregiver—child pairs were
obtained by merging the children’s dataset and female caregivers’ dataset.

The final sample was intended to consist of one child matched to one

female caregiver per household. Three hundred twenty-nine children had

more than one possible female caregiver in the household. To select only

one female caregiver from each household, certain criteria were used (see

appendix C).

Out of 1,704 female caregiver-child pairs from 1,704 households, a total
of 990 low-income female caregiver-child pairs with an income at or below 185%
poverty level were used in the current study. The final data consisted of matched
pairs of low-income children and their female caregivers living in the same
household selected from NHANES 111 1988-1994 with complete and reliable 24-
hour dietary recall information.

Statistical Analysis

The Statistical Package for the Social Science (SPSS) Version 7.5 was
used in all current study analyses because it is suitable for the study and user-
friendly. Descriptive and correlation analyses were used to answer the four
research questions in this study. Descriptive analyses included the mean, standard
deviation, and frequency distributions. For the research questions one, three, and

four mean : Standard deviation was used to determine the groups’ mean nutrient

28

intake or iron markers measurements. BMI scores were then compared to the
recommended guidelines. These comparisons enabled the generalized conclusions
on whether the group had met the dietary guidelines for each variable that was
being measured. Frequency distributions for variables in all the four research

questions were performed to determine

the nutrient adequacy level(those above and below recommended guidelines)

0 consumption of breakfast and RTEC (consumers and skippers)

iron deficiency (deficient and not deficient), and

weight status (normal, overweight, and obese).
Children’s Dietary Intake intRelationship to their Female Caregivers’

A frequency distribution of children and female caregivers was generated
by their demographic variables. The demographic variables were age, sex, and
race-ethnicity, participation in WIC Program, Income Poverty Ratio, and family
size. Dietary intake for both children and caregivers of total energy, percent
energy from fat, saturated fat, and carbohydrates, dietary fiber, calcium, iron,
vitamin A, and vitamin C intake were examined and compared to the
Recommended Dietary Allowance (RDA). Nutrient intake of < 70% of the RDA
and 3 70% RDA for each nutrient were determined.

Intake of total fat, saturated fat, carbohydrates, and fiber were compared to
Dietary Guidelines for Americans for total fat < 30%, saturated fat <10°/o,
carbohydrates <55%, and fiber 3 25g/day for ages 5 years and over. The
percentage of the sample group that had 3 30% total fat intake, 3 10% saturated

fat, > 55% carbohydrates, and < 25g/day dietary fiber was obtained. Nutrition

29

intake as a percentage of the Recommended Dietary Allowance (RDA) was
classified into tertilesl for energy, vitamin A, vitamin C, calcium, and iron. Total
fat, saturated fat, and carbohydrates as a percentage total energy intake in
kilocalories from total fat, saturated fat, and carbohydrates.

A relationship distribution was performed by children’s and female
caregivers’ nutrient tertile groups (nutrient intake were divided into three equal
parts; the lowest, middle, and top third). Children in the first, second, and third
tertiles for nutrient intake were compared to their female caregivers in the first,
second, and third tertiles. The Chi-square was calculated to determine differences
among the tertile groups. The correlation coefficiency was calculated between the
children’s nutrient intake and the female caregivers’ intake. The female nutrient
intake of total energy, energy from total fat, saturated fat, carbohydrates, dietary
fiber, calcium, iron, vitamin A and C, and children’s intake of total energy, energy
from total fat, saturated fat, carbohydrates, dietary fiber, calcium, iron, vitamin A,
and C were all included in the correlation analyses.

Children’s Breakfast Consumption Patterns Related to their Female
Caregiver

A frequency distribution of breakfast consumption, and Ready-to-Eat
Cereal (RTEC) was listed, breakfast consumption (yes = 1, N0 = 0), RTEC (yes =
1, N0 = 0) for both children and female caregivers by their age, race-ethnicity,
Poverty Income Ratio (PIR), participation in WIC, and family size. Pearson Chi-

square was computed to determine whether there is a relationship between

30

children breakfast-and-RTEC-consumers and the female caregivers breakfast-and-
RTEC-consumers.

The frequency distribution of the breakfast-consumers and breakfast-
skippers for both children and female caregivers was generated. A similar
distribution was performed for breakfast-RTEC-consumers and RTEC-
consumers. Statistical correlation was performed to determine the caregiver-child
relationship of breakfast consumption. Sensitivity, specificity, positive predictive
value, and negative predictive value were calculated to determine how well the
correlation model classified cases.

Children’s Prevalence of Iron Deficiency and Iron-Deficiency Anemia vis-a-
vis their Female Caregivers

Iron deficiency and iron-deficiency anemia was estimated by biochemical
measures of iron status used in other studies and Looker et a1 study (1999), (see
appendix). Free erythrocyte protoporphyrin, serum ferritin and transferrin
saturation were used as measures for calculating iron deficiency. Based on
laboratory tests, to be iron-deficient, a person had abnormal values of two or more
bio-makers. Hemoglobin was used to measure iron-deficiency anemia. A
combination of low hemoglobin levels and iron deficiency (two or more abnormal
values of iron indicators) was indicators of iron-deficiency anemia.

The subjects were classified by the measurement of the iron variables
using the cut-point value for each variable. The subjects were categorized into
two groups, above cut-point = 1 and below cut-point = 0. Children’s and female

caregivers’ serum ferritin, erythrocyte protoporphyrin, transferrin saturation, and

31

hemoglobin measure for ages 2—5 years were grouped as, serum ferritin met yes =
1 and N0 = 0, erythrocyte protoporphyrin met, yes = 1 and N0 = 0, transferrin
saturation met, yes = 1 and N0 = 0 and Hemoglobin met, yes = l and N0 = 0.

The subject that had two or more iron measures less than the cut-point
value was defined as iron-deficient. All three measures above the cut-point = 0,
one of iron measures below cut-point = 1, two of the iron measures above cut-
point = 2, and three of the measures below the cut-point = 3. Hemoglobin
variable was combined with the iron deficiency, if an individual had hemoglobin
less than the cut—point and was iron-deficient, then that person had iron-
deficiency anemia, iron-deficiency anemia = 2 and not iron-deficiency anemia =
1.

The objective was to assess the sample and determine individuals who
were iron-deficient and those who were anemic. The dependent variables were
children’s no iron deficiency, iron deficiency, and iron-deficiency anemia, which
were coded as 0, 1, and 2, respectively. The frequency distribution for iron
deficiency and iron-deficiency anemia were generated using the iron values as
continuous variables.

The mean values of the children’s and female caregivers’ serum ferritin
(ng/ml), free erythrocyte protoporphyrin (ug/dl), transferrin saturation (%), and
hemoglobin (g/dl) were calculated by age group. Percent frequency distribution of
those above and below recommended cut-point value was determined. Pearson
correlation was performed using continuous variables of iron makers between the

children’s serum iron, free erythrocyte protoporphyrin, transferrin saturation, and

32

hemoglobin values and female caregivers’ serum ferritin, free erythrocyte
protoporphyrin, transferrin saturation, and hemoglobin values. R value was used
to assess the strength of the relationship’s significance.

Relationship between Children’s Weight Status and their Female Caregivers’
Adiposity (the state of fatness)

The variables used to measure children’s weight status were weight-for—
height percentile and triceps skinfold measurements: 3 85th percentile for weight-
for—height and triceps skinfold measurement are both considered overweight
(NCHS, standard reference measures). The female caregivers’ weight status was
determined by the Body Mass Index (BMI) measures and triceps skinfold
measurements. BMI is calculated as weight (kg) / height (m)2‘ Children’s
weight-for-height was calculated using the weight and height measures collected
during the survey. Individuals with weight-for-height< 85th percentile = 0 and
those with weight-for-height3 85’h percentile = 1. Distributive statistics was
performed for the children’s weight-for-height and triceps skinfold measurement
by age, gender, race-ethnicity, Poverty Income ratio (PIR), participation in federal
assisted program WIC, and family size. A chi-square test was run to determine if
there were differences in the children’s weight status by their demographic
variables and the significance of the differences. The significance level of social
demographic variables was determined by the p-value (p, 0.5, significant).
Similarly, the children’s triceps skinfold measurements were grouped as < 85th
percentile = not overweight, and 3 85th percentile overweight (NCHS reference)

by their socio-demographic characteristics. Chi Square was performed to

33

determine the level of significance in the differences by the socio-demographic
variables.

BMI is often used to distinguish between the obese and the non-obese
subjects. Weight and height values were used to generate BMI scores (BMI =
weight (kg) /height2 (m)2) for each female. Descriptive statistics for female
caregivers’ BMI scores were calculated to determine those who were not
overweight, the overweight, and the obese. BMI score references used were: not
overweight 5 24.9, overweight 25 — 29.9 and obese _<_ 30 (also used in the
National Center for health services (N CHS). These were coded as not
overweight = 1, overweight = 2, and obese = 3. The female caregivers BMI was
classified by their age, race-ethnicity, PIR, participation in WIC, and family size.
Chi square analyses were performed.

Female caregivers’ triceps skinfold measurements were also used as a
measure of overweight. Female caregivers’ triceps skinfold measurements were
categorized as not overweight < 85th percentile, and overweight 3 85’h percentile
(NCHS reference standard). Chi Square was computed to determine the
significance of the difference. The female caregivers’ triceps skinfold were also
grouped by their socio-demographic variables.

Frequency distribution of children’s weight-for-height (< 85th percentile
and 3 85th percentile) by their female caregivers skinfold measures and BMI
scores was determined. Pearson correlation analysis was run to determine the
relationship between the children’s weight variables and their female caregivers.’

Female caregivers’ weight variables were independent variables and children’s

34

weight variables were dependent variables. Pearson correlation coefficients (r)
were calculated between the children’s weight-for-height and triceps skinfold
values and female caregivers’ BMI and triceps skinfold values.

The subjects in this study were a low-income sub-sample with income
level of 51 85% that participated in the NHANES III with complete and reliable
dietary information. The final sample for the study was 990 child—caregiver
pairs living in the same household. Dietary information, anthropometric, and
biochemical measures were used in the analysis for the study questions. Twenty-
four hour dietary intake included nutrient intake of energy: total fat, saturated fat,
carbohydrates, and dietary fiber; anthropometric measures used to determine
weight status were weight-for-height, BMI, and skinfold measures; and
biochemical measures used to determine iron deficiency and iron-deficiency
anemia were serum ferittin, erythrocyte protoporphyrin, transferrin saturation,
and hemoglobin. Descriptive statistics, chi-square, and correlation analyses were

used in the data analysis.

35

Chapter Four

Results

The outcome of descriptive statistics analyzes for children and female caregivers
nutrient intakes and intake adequacy when compared to the recommended guidelines are
presented first. The distributive analysis includes the mean and standard deviation of the
children’s and female caregivers’ nutrient intakes and frequency distribution of < 70%
RDA of calorie intake, calcium, iron, vitamin A and vitamin C, and 330% energy from
total fat, 310% saturated fat and 355% energy from carbohydrates. Then, correlation
analyses of the female caregiver-child relationship of nutrient intake, breakfast, iron
deficiency anemia, and weight status are presented.

Socio-Demographic Characteristics

The subjects in this study included 990 female caregiver-child pairs from the
same household with income level of 5 185% poverty level with the annual income of
$532,653 for a family of four. Table 1 shows a summary of socio-demographic variables
included in this study. The children were categorized into two age groups, ages 2 - 4
year old (n = 562) and 5 — 9 years old (n = 428). There was an even distribution of boys
and girls with the majority of the children were black (n= 410), 403 Mexican Americans
and 134 white. Of 990 children, only 199 responded that they participated in the WIC
program (468 were non-WIC participants and 322 children did not indicate whether or
not they participated in WIC). The age of female caregivers ranged from 15 —— 49 year

old.

36

Table 1. Socio-demographic characteristics of children and female caregivers in the
study

 

 

n %
Children: age (y)
2 - 4 562 56.8
5 - 9 428 43.2
Children
Gender
Boys 508 51.3
Girls 482 48.7
Female caregivers: age (y)
15 - 19 144 2.2
20 - 29 411 45.6
30 - 39 397 40.5
40 - 49 38 11.7
Children's race-ethnicity
Whites, non-Hispanic 134 13.5
Blacks, non-Hispanic 410 36.7
Mexican Americans 403 35.0
Others] 43 25.2
WIC2 Participants
yes 199 20.1
no 323 47.1
unknown 468 32.6
Family size
2 27 5.8
3 138 13.9
4 236 23.8
5+ 559 56.5

 

' All Hispanics and non Hispanics that are not white, black or Mexican Americans

2 The Special Food Supplemental Program for Women Infants and Children (WIC)

Out of 990 female caregivers, only 22% were teenage female caregivers ages 15—

l9years; 45%, 20 — 29 years; 41%, 30 — 39 years, and 12%, 40 — 49 year.

37

First Research Question:
How does the children’s nutrient intake and adequacy
relate to their female caregivers?

Nutrient intake of children and female caregivers was based on the 24-hour
dietary recall information. Most of the children’s mean caloric intake was close to 100%
RDA and greater than 70% of the Recommended Allowance (table 2, appendix D). 21%
of the children had energy intake less than 70% of the RDA. There was no difference of
energy intake by the children’s race-ethnicity, participation in WIC, or family size.
However, there was significant difference in energy intake by the children’s age-group;
19% of the 2 - 4 year old children had their total energy intake less that 70% RDA
compared to the 23% for the 5 —- 9 year old with energy intake less that 70% RDA. More
girls had less recommended energy intake (< 70% RDA, 24%) compared to boys (18 %).

Children’s average energy intake from total fat was 34% for all children ages 2 ~—
9 years. This was above the recommended guidelines of < 30%. There was no
significant difference of energy intake from total fat between white children, black or
Mexican Americans. The total fat intake of children who participated in WIC did not
differ from the fat intake of the non-participants, and the family size did not have an
effect on the child’s total fat intake. Similar results were observed with the children’s
intake of energy from saturated fat. Children’s saturated fat intake was above the
recommended guidelines of < 10%, the mean intake was 12%. There was no deference
between the children’s saturated fat intake by the children’s age group, gender, race-

ethnicity participation in WIC or household family size.

38

The children’s mean carbohydrate intake was 53.5:93 (Table 3, appendix E).
The only significant difference (p<0.01) observed among those children that consumed
more that 55% energy from intake carbohydrates was by their race-ethnicity groups; 50%
of white children, 41% blacks, 39% Mexican Americans, and 45% others had energy
intake above 55% energy form carbohydrates. Mean dietary fiber intake for the children
was about 11.1:6.6, 42% of the children had less that the recommended dietary fiber
intakes. Children ages 5 _ 9 years old had less dietary fiber intake 48% (n= 562),
compared to the 2- 4 years that had only 38% (n=428) with less intakes of dietary fiber.
The results indicated a significant difference between the children’s dietary fiber intake
by their age, gender and family size.

The average children’s intakes of calcium, iron, vitamin A and vitamin C are over
100% RDA (Table 4 & 5, appendices E & F). 23% of the children in this study had
calcium intakes less than 70% of the RDA with highest number of children from age
group 5 — 9 years (33%, n=428). A higher number of girls consumed <70% RDA of
calcium 30%, than boys (25%). Black children consumed less that 70% RDA (35%)
calcium, followed by white children, 26% then Mexican Americans, 24%. Iron intake
among all children averaged 117:67, which was above 100% RDA, and 29% of the
children consumed less that 70% RDA. Girls had less calcium intake compared to boys,
and Mexican American children had the highest deficiency of dietary iron intake with
27%, 21% and 19% in white and black children, respectively. Children from households
with high family size had lower iron intakes (24%, < 70% RDA) that those with fewer
people in the household (12%, < 70% RDA). The intakes of iron among children were

significantly different by the children’s age group, sex, and ethnicity. The only

39

difference noted in the vitamin A intake was that black children had less intake compared
to white and Mexican American children. Overall, 24% of the children consumed less
vitamin A than recommended, with the highest number of children from age group 5 - 9
years. Vitamin C was the least deficient nutrient among all children compared other
nutrients. Only 16% of the children had less that 70% RDA of vitamin C compared to
23% calcium, 29% iron, and 24% vitamin A.

The female caregivers caloric intake was also close to 100% RDA, 85.9:374
(Table 5, appendix G) but lower than the children’s mean caloric intake, 97.2:354 36%
of female caregivers had less than 70% RDA energy intake. Teenage women had slightly
higher energy intake (95.5:48), compared to other age groups. There was no difference
of caloric intake among different race-ethnicity, age groups, WIC participants and non-
WIC participants, families with different family sizes. The caregivers’ energy from total
fat intake was 34% and 12% saturated fat; both were higher than the recommended
allowance. Female caregivers differed significantly in their energy intake from total fat;
black women had the highest total fat intake of 35%, whites 34%, and Mexican American
33%. Women enrolled in WIC Program had slightly higher fat intake (36%) and
saturated fat intake (13%) compared to non-WIC participants.

The average dietary fiber intake for the caregivers was 14g/ day; this is half of the
recommended intake 25 g/day (Table 6, appendix H). White female caregivers had 14g
fiber, blacks 12g/day and Mexican Americans l7g/day. 90% of the white women, 94%
black and 78% Mexican Americans had less that 25g of dietary fiber intake. Mean
calcium (81%) iron (83%) vitamin A (57%) intakes for the caregivers were also close to

100% RDA and vitamin C (162%) over 100% RDA but slightly lower than the children’s

40

mean intakes (Table 7, appendix 1). There was significant difference of female caregiver
calcium, iron, vitamin A and C intakes by their age groups.

In general, nutrient intake was moderately positively correlated between the
female caregivers and the children. There was a statistically significant correlation (p<
.01) with correlation co-efficiency (r) ranging from .12-.40 for all the nutrients in the

study (Table 21, Appendix P).

41

Table 8. Relationship between children and their female caregivers’ tirtiles

Female caregivers' intake

 

 

Mean
Children's intakes
Energy (% RDAZ)
tertile 1 63.1
tertile 2 92.8
tertile 3 136.5
Total Fat (% Kcal)
tertile 1 24.7
tertile 2 34.1
tertile 3 41.9
Sat. Fat (% Kcal)
tertile l 8.8
tertile 2 12.4
tertile 3 16.5
ChO (0/0 Kcal)
tertile 1 43.4
tertile 2 52.9
tertile 3 63.2
Fiber (g)
tertile 1 5.7
tertile 2 10.5
tertile 3 18.8

:t 13.3
:t 7.9
3: 27.9

$4.3
:t 1.7
$4.1

:h 1.7
:l: 0.8
:l: 2.3

a: 4.9
:l: 2.1
a: 5.7

a: 1.8
:h 1.4
:58

tertilel
%

41.1
33.7
27.1

45.9
30.3
22.5

42.8
40.5
25.7

42.5
34.0
26.1

39.2
35.5
25.5

tertile2
%

33.3
35.5
30.5

32.5
34.3
33.5

32.8
40.5
29.5

32.6
32.6
33.2

34.4
35.0
32.7

tertile
%

25.
30.
42.

21.
35.
44.

24.
31.

24.
33.
40.

26.
29.
41.

P

0.00

0.00

0.00

0.00

0.00

 

lThree parts intake (tertile1-33.3%; tertile 2- 66.6%, and

tertile 3-99.9%)
2Recommended Dietary Allowance.

p value is by X2 test

42

Table 9. Relation between children's vs. female caregivers' tertiles

 

Female caregivers' intake

 

Tertile'l tertile2 tertile3

 

% % %
Children's intakes
Vitamin c (% RDAZ) _
tertile 1 72.4 :352 41.7 35.2 23.1
tertile 2 193 339.1 33.0 34.2 32.8
tertile 3 436.4 :176.1 25.8 28.8 45.3
Vitamin A (% RDA)
tertile 1 50.2 :20] 43.2 33.8 23.0
tertile 2 114.7 :19.7 34.3 37.0 28.7
tertile 3 281.3 _+_236.5 22.4 29.8 47.8
C3 (o/o RDA)
tertile 1 47.1 :158 43.3 32.9 23.8
tertile 2 91.7 :128 32.2 37.0 30.8
tertile 3 164.5 :487 29.6 27.6 42.8
Fe (% RDA)
tertile 1 90.4 :478 36.6 34.4 29.0
tertile 2 120.5 156.8 33.2 33.6 33.2
tertile 3 153.5 :835 27.2 34.9 37.9

0.00

0.03

0.00

0.01

 

' Three part intake (tertilel-33.3%; tertile 2- 66.6%, and tertile 3-99.9%)
2Recommended Dietary Allowance,

p value by X2 test

43

Second research question:

How does the children’s breakfast and Ready-To-Eat-Cereal (RTEC)

consumption relate to their female caregivers?

Most of the children in this study consumed breakfast (90%) and only 10%
skipped breakfast, 11% of the black and 12% Mexican American children did not
consume breakfast, yet only 5.6% of the white children skipped breakfast meal. The
Black and Mexican American children who skipped breakfast are twice the number of
white children. Children who participated in WIC Program consumed breakfast and
RTEC at for breakfast, 91% and 44.2%; more than non-WIC participants, 88% and 30%.
51% whites children, 37% Mexican Americans, and 26% blacks consumed RTEC for

breakfast (Table 10).

44

Table 10. Percent children who consumed breakfast and RTECl
by race-ethnicity, WIC2 participation, and family size

 

Breakfast consumption Breakfast RTEC

 

 

 

n no yes no yes
Age (y)
All 990 10 90 42.3 57.7
2 - 4 562 7 93 41.9 58.1
5 — 9 428 13.4 86.6 42.7 57.3
Race-ethnicity
White 134 5.6 94.4 49.0 51.0
Black 410 10.5 89.5 56.7 43.3
Mexican Americans 403 12.1 87.9 63.1 36.9
Others 43 12.7 87.3 70.4 29.6
WIC participation
Yes 199 9.2 90.8 55.8 44.2
No 468 12.3 87.7 69.9 30.1
Family Size
2 27 8.5 91.5 58.5 41.5
3 138 10.4 89.6 58.3 41.7
4 236 10.3 89.7 57.6 42.4
5+ 559 9.8 90.2 57.4 42.6
IReady To Eat Cereal

3 The Special Food Supplemental Program for Women Infant and Children (WIC)

Table l 1 shows that 73% female caregiver ate breakfast and only 10% ate RTEC
for breakfast. Again, more white female caregivers consumed breakfast and RTEC
compared to Black and Mexican American female caregivers; 80%, 67% and 73%
respectively. A higher percentage of Black women skipped breakfast (33%) than
Mexican Americans (27%) and whites (20%). More children consumed breakfast and

RTEC (n=990, 90% and 58%) compared to the female caregivers (n=990, 73% and

45

11%). Female caregivers skipped breakfast and did not consume RTEC often compared
to the children living in the same household. There was a and significant positive
relationship between female caregivers’ and their children’s breakfast and RTEC
consumption with a correlation coefficient of r=.2. A high specificity was calculated

(92.6%) and a low sensitivity (19.3%) was found (table 12, appendix J).

Table 11. Percent female caregivers who consumed breakfast and RTEC1 by age-group,

race-ethnicity, WIC2 participation, and family size

 

Breakfast consumer Breakfast RTECI

 

 

 

n yes no yes no
Age (y)
All 990 73.2 26.8 10.6 89.4
15-19 22 64.0 36.0 12.0 88.0
20-29 451 70.2 29.8 11.1 88.9
30-39 410 74.7 25.3 10.5 89.5
40-49 116 77.6 22.4 9.6 90.4
Race-Ethnicity
White 144 80.4 19.6 16.0 84.0
Black 411 67.5 32.5 9.6 90.4
Mexican Americans 397 73.5 26.5 8.6 91.4
Others 38 78.8 21.2 4.5 95.5
WIC2
Yes 116 35.4 64.6 10.8 89.2
No 152 66.7 33.3 12.5 87.5
lReady To Eat Cereal

2The Special Food Supplemental Program for Women Infant and Children (WIC)

46

Third Research Question:
How does the children’s iron deficiency and iron deficiency anemia
relate to their female caregivers’?

Iron deficiency biomarkers used in the study were transifenin saturation, serum
ferritin, and erythrocyte protoporphyrin. An individual with two or three of these
measures below the cut-point value was considered iron deficient (check appendix K for
cut-point values). If an iron deficient person had low hemoglobin levels, this person was
considered to have iron deficiency anemia (tablel3, and table 14, Appendix K). 3% (27)
of the children had iron deficiency and 1% had iron deficiency anemia while 8% (77) of
the female caregivers had iron deficiency and 9% (88) had iron deficiency anemia. There
is a higher prevalence of iron deficiency and iron deficiency anemia among female
caregivers than in the children. Fewer children had transfenin saturation, serum fenitin,
erythrocyte protoporphyrin and hemoglobin measures below the cut-point than female
caregivers.

Overall, 29% of female caregivers had low values for transferrin saturation, 15%
serum ferritin, 17% protoporphyrin, and 18% hemoglobin, compared to the children with
values below the cut-point; 11% transferring saturation, 5% serum ferritin, 7%
protoporphyrin and 4% hemoglobin (Table 13). Less prevalence of iron deficiency and
iron deficiency anemia among children than female caregivers may be as a result of high
consumption of breakfast and RTEC by children than by female caregivers. The highest
prevalence of iron deficiency anemia was observed among female caregivers ages 40 —

49 years old 13%, followed 7% in 20 — 29 years, and 5% 15-19 years.

47

Table 13. Iron status of children and female caregivers

 

Transferrin Serum Protoporphyrin Hemo-

Saturation ferritn

 

Iron Anemia
Erythrocyte globin Dei’

 

Female caregivers

% % % % %
below below below below
Age (y) cutoff cutoff cutoff cutoff
Children
All 3.1
2- 4 11.4 7.6 7.3 6.6 4
5— 9 19.8 2.3 6.3 1.3 2

All 28.5 14.8 17.2 18.2 15
15-19 18.2 13 13 26.1 8
20-29 29.3 16 15 16.1 14
30-39 26.8 13.6 18.4 19 14
40-49 33.3 16.1 19.5 21 17

' Iron deficiency is defined as more than one abnormal value (below the cuoff

value) of transferrin saturation, serum ferritin or erythrocyteprotoporphyrin
2 Iron deficiency and low hemoglobin value
3 Healthy People Objective 2010 for iron deficiency

48

2 Target3

2010
% Iron def

1 <1%

9 <7%
1.1
7.1

13

Fourth Research Question:
How does the children’s weight status related to their female caregivers’ adiposity?

Children’s‘weight status was measured by the triceps skinfold and weight-for-
height (wt-for-ht) percentiles (NCHS Reference). 19% of children were overweight
using triceps skinfolds of 3 85% (Table 15, appendix L). Using weight—for-height
measurements (Table 16, appendix M), 24% of children were overweight (with 3 85%
percentile as overweight). Children ages 2 — 4 years were less heavy than 16%, n=562,
than the 5 — 9 year olds, 23%, n= 428. 23% of the girls were considered overweight by
their triceps skinfold percentile, while only 15% of the boys had their triceps skinfold
measurements 3 85% tile. There was a significant difference in the weight status of the
children by their age group and gender and race-ethnicity and participation in WIC
Program. Mexican American children (30%) were more overweight than black and white
children, 20% and 24% respectively. 21% of WIC participant were overweight
compared to 10% overweight non-WIC children. The higher the family size the lower
the overweight prevalence. There were 17% overweight children in household with 5 and
over family members, and 26 — 24 % overweight children in household with two to three
family members.

The mean female caregivers’ BMI was 27.7:68, which falls with the overweight
category. 43% of female caregivers had BMI scores 5 24.9 % which is considered
normal weight, 28% overweight female caregivers with BMI 24.9 — 29.9, and 29% obese
with BMI 3 30 (Table 17, appendix N). 33% black female caregivers were obese
compared to 30% Mexican American and 20% white. Female caregivers who did not

participate in WIC Program were more overweight that the WIC participants. Female

49

BMI scores significantly differed by the female caregiver’s age group, race-ethnicity,
participation in WIC and by family size. Table 20 (appendix 0) shows the female
caregivers triceps skinfold classifications, < and >85%tile as per the reference values
from the NCHS. Triceps skinfold > 85% was considered to be overweight.

Tables 8 and 9 are children’s nutrient intake in tertiles by their female caregivers.
Children with nutrient intake in the highest tertile had most female caregivers with
intakes also in the highest tertile (third tertile). Children with intakes in the first tertile
had most of their female caregiver also with intakes in the same tertile. This implied that
the level of children’s nutrient intake is related to that of their female caregivers.
Children that were overweight were more likely to have caregivers who were overweight
or obese (Tables 18 and 19). Female caregiver-child weight status showed a positive
significant correlation with Pefa'rson’ (r) correlation coefficient of 0.12 — 0.33 (table 21,
appendix P).

In summary, 990 female caregiver-child pairs from same household with income
of 5 185% poverty level were used in these analyses. The results of the study showed a
mild to moderate significant positive correlation between the children and female
caregiver’s nutrient intakes, breakfast and RTEC consrunption, iron deficiency and
weight status. Female caregivers with high energy intake from total fat, saturated fat,
carbohydrates, low dietary fiber intake, and less consumption of breakfast and RTEC
were likely to have children with high intake of total fat, saturated fat, carbohydrates, and
low dietary fiber intakes and less breakfast and RTEC consumption. Children that had
iron deficiency, iron deficiency anemia, or over weight were likely to have female

caregivers with iron deficiency, iron deficiency anemia, overweight or obese.

50

Table 18. Children’s weight-for height and triceps skinfold percentiles by their female
Caregivers’ BMI1 scores

Female caregivers' BMI

 

 

524.9 _ 25 - 29.9 530 _ p
Weight-for-height
Percentiles
All 0.00
5 85%tile 49.1 26.5 24.4
> 85%tile 27.4 31.1 41.5
2 - 4 y 0.00
5 85%tile 51.1 22.5 26.0
> 85%tile 29.3 30.9 39.8
5-9y 000
5 85%tile 46.0 31.6 22.4
> 85%tile 25.8 31.2 43.0
Triceps
All 0.00
< 85%tile 47.0 26.8 26.2
>85%tile 30.2 30.9 38.9
2-4y 000
< 85%tile 49.4 23.2 27.4
>85%tile 33.3 29.9 36.8
5-9y 000
< 85%tile 44.0 31.3 24.6
>85%tile 27.8 31.7 40.6

 

1Body mass Index

p value by x2

51

Table 19. Children’s weight-for-height by their female caregivers’ triceps skinfold
percentiles.

 

Female caregiver's triceps

 

 

percentiles
5 85%tile . >855tile p
Weight-for-height
Percentiles
All 0.00
5 85%tile 77.3 22.7
> 85%tile 64.3 35.7
2 - 4 y 0.00
5 85%tile 76.4 23.6
> 85%tile 65.4 34.6
5 - 9 y 0.00
5 85%tile 78.5 21.5
> 85%tile 63.3 36.7
Triceps
All 0.00
< 85%tile 76.2 23.8
>85%tile 64.8 35.2
2 - 4 y 0.00
< 85%tile 75.5 24.5
>85%tile 67.4 32.6
5 - 9 y 0.00
< 85%tile 77.2 22.8
>85%tile 62.8 37.2

 

IBody mass Index

p value by x2

52

Chapter Five

Conclusion, Research and Policy Implications

Summary

This chapter consists of a summary of the background information on nutritional
adequacy among low-income families, nutrition issues, dietary habits, and related
nutrition health risks common among low-income women and children. It summarizes
the statistical methods and study findings. In addition, the overall conclusions, research,
and policy implications will be discussed.

The study of the relationship of female caregiver—child nutrient intake, iron-
deficiency anemia, and obesity provides insights into how female caregivers may
influence children’s dietary habits and, possibly, their nutritional health. Undesirable
dietary habits and lifestyles that include inadequate nutrient intake, excessive fat intake,
and low physical activity may result into nutritionally related diseases such as iron-
deficiency anemia, obesity, and cardiovascular diseases.

Low-income families have lower nutrient intake than recommended for proper
growth and development. Federal food assistance programs provide food and cash
assistance to low-income households to improve their dietary quality and reduce nutrition
deficiency diseases. Caregivers’ food choices may affect the children’s dietary quality
and habits. Studies have shown that dietary habits developed in childhood may persist
into adulthood, and healthy dietary habits developed in childhood can prevent nutritional

health risks both in childhood and adulthood.

53

Low-income children and women have a higher prevalence of iron deficiency and
iron-deficiency anemia, and higher energy intake from total and saturated fat than the
recommended allowance. Increased prevalence of obesity in low-income children and
women is due to over-consumption of dietary fat and physical inactivity. The parent-child
relationship of nutrient intake and health risks indicated the likelihood that the parental
influence on children’s dietary intake and eating patterns eventually affects the children’s
nutrition.

In this study, nutrient intake was assessed by the 24-hour dietary recall for both
children and female caregivers and was compared to the recommended allowance to
determine the adequacy intake level of each nutrient in the study. Breakfast and Ready-
To-Eat Cereal (RTEC) consumption were used as indicators of dietary habit or behavior.
Breakfast consumption and consumption of Ready-To-Eat Cereal are excellent sources of
micronutrients that contribute significantly to the total daily nutrient adequacy of
individuals. Iron deficiency and iron-deficiency anemia were determined by similar
biomarkers used in NHANES II and III and by other researchers (Looker, 1997).
Transfenin saturation, serum ferritin, and erythrocyte protoporphyrin were used to
measure iron deficiency and hemoglobin values were used to determine iron-deficiency
anemia. Children’s weight status was determined by their triceps skinfold and weight-
for-height measurements. The female caregivers BMI score (BMI score is defined as
body weight in kilograms divided by the height squared, kg/htz) and triceps skinfold
measures were the variables for female weight status.

Results on the relationship of female caregiver—child nutrient adequacy showed

that female caregivers with high nutrient inadequacy were more likely to have children

54

who consumed fewer nutrients than recommended guidelines and vise versa. Female
caregivers with diets high in calories, total fat, saturated fat, and carbohydrates had
children who were more likely to consume a similar diet. Children with low fiber,
calcium, iron, vitamin A, and vitamin C intake had female caregivers with low intake of
the same nutrients. This study revealed that there is a tendency of a variety of nutrients
intake patterns to cluster within households or families.

Findings from the study indicated that there was a positive relationship between
the children’s breakfast and RTEC consumption and that of their female caregivers.
Female caregivers who skipped breakfast and did not consume RTEC at breakfast were
more likely to have children who frequently skipped breakfast and not consume RTEC.
Children enrolled in WIC program consumed RTEC compared to their female caregivers.
This difference may be explained by the fact that WIC program provides RTEC to the
children but not to the women participating in the program. Higher consumption of
breakfast in WIC children may also be due to the free supplemental foods that are
provided by the programs, including milk, cereal, and eggs.

There was higher prevalence iron deficiency (8%) and iron-deficiency anemia
(9%) among female caregivers than in children, 3% and 1% respectively. These results
are consistent with other studies that showed a higher prevalence of iron deficiency and
iron-deficiency anemia in women than in children (NMRR, USDA, 1995). There was a
positive relationship between the iron-deficiency anemia and their female caregivers.
The correlations between female caregivers’ and children’s iron deficiency were found to
be significant and moderately correlated with R-value of .33. There was a higher

prevalence of overweight among the children and their female caregivers. Twenty-four

55

percent of the children were overweight and 28% of the female caregivers were
overweight while 29% were obese. These results are similar to other studies (Whitaker et
a1. 1997). The relationship analyses showed that overweight female caregivers were
likely to have children who were overweight, and obese female caregivers were also
likely to have children who were obese. There was a similarity in the weight status of the
children and their female caregiver. The children’s weight status was significantly and
positively correlated with that of their female caregivers.

The positive relationship between the children’s and their female caregivers’
weight status is consistent with a study done by Deutscher et a1 (1966). There is an
increase in prevalence of overweight and obesity in both children and adults. Overweight
and obesity have been associated with lack of physical activity and high-fat diets. A
study by Fisher and Birch (1995) revealed that children’s food preference of high-fat
foods was associated with their parents’ adiposity. They concluded that parents or
mothers influence their children’s high-fat food preference. Mothers determine the kinds
of food they feed their children. By making high-fat foods available to their children,

they enhance the children’s preference for foods high in fat.

Conclusions
Familial nutrient intake and health status resemblance was investigated in the
current study by Pearson correlation coefficient. There was a positive association
between the children’s caloric, total fat, saturated fat, carbohydrates, calcium, fiber, iron,
vitamin A and C intake. There was also a positive relationship between the children’s

iron-deficiency anemia and weight status with their female caregivers. The results from

56

this study reflect the stringent discipline in nutrition and lifestyle pattern that extend into
the younger generation. The homogeneity of culture within a family and similar
nutritional food patterns are likely to be the attributing factor to positive relation of
nutrient and health risk factors. These outcomes are similar to the Patterson et a1 study
(1988) that demonstrated a moderate relationship in dietary fat, sodium, and calories.
There was a positive relationship between the child-parents, sibling-sibling, and spouse-
spouse dietary intake. The correlation between the mothers and children was stronger
than between the fathers and children.

The relationship between the children’s health risk factors measured by the iron-
deficiency anemia and obesity is an indication of how aggregate dietary intake may affect
the development of health risk factors with a family. In comparison with other sources of
influence in diet, family is believed to be very important. A positive relationship of
dietary behavior within a family is expected because families eat meals together and tend
to have access to similar foods and influence each others’ eating behavior. A study by
Eastwood et al. (1982) found a positive correlation of parent-child nutrient intake of
carbohydrates, fat, and calories with the correlation ranging from 0.15—0.30. Other
studies have reported that family members’ nutrient intake contribute to coronary heart
diseases (CHD). Kleiges et al. (1990) report that parents’ interaction with children
closely correlated with the children’s physical activity, eating behavior, and perhaps
relative weight. Parents who encourage their children to eat correlated with how much
children spent to eat and the relative weight of the children. Parents who encouraged
physical activity correlated with the children’s physical activity level and the children’s

relative weight.

57

Individuals who live together share common dietary intake and habits and
possibly energy expenditure. Therefore, it is possible to expect similarities in weight
status (Garn 1988). Genetic and environmental factors are known to affect the
individual’s weight status. Environmental influence, such as consumption of foods high
in total fat and saturated fat, high caloric intake, and lack of physical activity, are
associated with development of overweight and obesity. Environmental influence on a
person’s weight is stronger than genetic influence. Because environmental factors, such
as dietary intake and the level of physical activity are modifiable, prevalence of obesity

can be reduced by positive changes in dietary intake and lifestyle.

Research and Policy Implications

Research implications

Twenty-four-hour dietary information used in NHANES III survey is not a true
representation of an individual’s usual nutrient intake. Multiple food diaries along with
food frequency and a history of food intakes may improve the accuracy of the nutrient
intakes and the outcome of the studies. Also, self reported dietary intake information
may be under or over-reported, it relies on memory and honesty of the individual
compared to observational methods, Oliveria et a1 (1992). NHANES 111 data is valid and
reliable for estimating dietary quality for the national population and for subgroups. For
a large sample size, a one- day dietary recall and mean intake of the subjects are
acceptable for making estimates of individual’s intakes for the study. A self-reported
food diaries is simple, requires less time and effort, and it is appropriated for illiterate

subjects.

58

NHAN ES III Survey does not identify the mothers or caregivers of the children
with complete and reliable dietary information. Future NHANES Surveys need to
include the variable “mother of child(ren)” to increase the accuracy on mother-child
relationship studies. Variables such as Level of education, number of food assistance
program participation, and physical activity are some of the indicators that the may reveal
more about the caregivers influence on their children’s nutritional health status that were
not included in this study.

The relationship of nutritional health status demonstrated by paired sample of
female caregiver and child was a more direct and accurate relations compared to
relationships made using group samples of children and female caregivers. Nutrient
intake, biochemical and athropometric methods are some of the commonly used methods
of accessing nutritional health of individuals; dietary pattern and food servings are
recommended for future studies on parental and children nutritional health relationships.
Studies on families’ dietary behaviors or patterns may provide more insight for nutrition
interventions that target a low-income families unit.

Policy implications

Reports from studies have shown that nutrition programs have a positive effect on
the food quantity in low-income households, but there are mixed reports on the effect of
the programs on nutrient intake of low-income families. The prevalence of nutrition
inadequacy and poor diet among low-income groups may be an indication that those
households that need to benefit from nutrition programs are not participating in the
program or low-income families are participating in fewer assistance programs. Some

reasons for non-participation in nutrition programs include poor accessibility to the

59

program site due to lack of transportation, lengthy program application process and
paperwork that discourages individuals, and lack of interest to enroll in the programs.
Nutrition programs that target low-income families need to expand the programs,
increase areas of coverage, and set up program sites closer to potential participants to
improve accessibility to the programs. The nutritional interventions need to be made
more attractive to low-income individuals in order to increase enrollment and
participation in the programs. The application process should be simple and fast to
encourage participation.

The federal government needs to increase the federal and state budget allocation
for nutrition programs targeting low-income households; this will enable the programs to
increase coverage and participation. Nutrition programs, such as WIC, have shown a
positive effect on the nutritional status of low-income women and children; a reduction in
iron-deficiency anemia among low-income women and children has been attributed to the
efforts of the WIC program. Such programs require continuous support to enable the
program to improve on its intervention strategies with the goal of eliminating nutrition-
related problems among low-income groups.

Nutrition programs need to emphasize educating the participants on the
association between nutrition and disease. Individuals’ negative attitudes toward
nutrition programs for low-income people as “a source of food and cash to low-income
families” but not as a source of assistance that aims at improving their nutrient intake and
prevention of nutrition-related diseases affects the impact of the program on the
participants. The Food Stamp Program does not provide nutrition education to’

participants along with the cash assistance offered. It is not known whether the cash

60

assistance given to program members is used to purchase nutritious food for the family
member; F SP must offer nutrition education to participants in order to improve their
nutrient intake.

WIC program provides food vouchers for specific foods high in calcium, iron,
vitamins, and minerals for women, infants, and children. The positive impact of WIC
programs on the nutrient intake of participants is mainly due to the supplemental foods
offered that are high in vitamins and minerals. F SP does not have restrictions or
specification on what the cash voucher can be used to purchase. It is likely that some of
these vouchers may be used to purchase non-food items or foods low in nutritional value,
such as high-fat foods or high-sugar beverages. Nutrition programs should have
restrictions on what foods may be purchased with the vouchers in order to make
nutritious foods available in low-income households.

Studies on the parent-child relationship on nutrient intake and disease risks have
indicated that parents/mother or caregivers may influence children’s nutritional intake
and dietary habits. Findings from my study also indicated a positive relationship between
the female caregivers and their children’s nutritional health status. There is also an
indication that the caregivers’ role has an impact on the children’s nutrition and food
habits. The positive relationship of the caregivers’ and their children’s nutritional status,
and the role of caregivers on the children’s and other family members’ nutrient intake
may have a positive effect on the nutrition program intervention. Nutrition programs
should targeting women or caregivers but yet address the nutritional needs of an entire
household, since members from same household have similar nutritional needs due to the

common dietary patterns in a household. Nutrition education targeting healthy

61

behavioral change using a household perspective may lead to higher achievements in
prevention and reduction of nutrition health problems in low-income households.

Nutrition health problems among low-income groups is a multi-factorial problem.
Social, financial, and physical factors are some of the factors contributing to nutrition
health problems. A holistic approach may be an appropriate method to address the
nutrition deficiencies and poor dietary habits in low-income groups. Collaborative efforts
with other related fields such as public health, social services, medical, nutrition,
extension, and policy maker are required to deal with nutrition problems and prevention
of nutritional deficiencies and related disease in low-income households in the United
States.

The primary goal of nutrition programs is to increase participants’ nutrient intake
to the recommended guidelines for good health and development. A change in an
individual’s nutrition practices or patterns requires elimination of barriers or forces
against positive change that may hinder the process. This process is known as forces of
continuity and change (Axinn, 1988, Lewin, 1950). Factors that may affect nutritional
behavioral change include social, cultural, physical, financial or economic, political, and
genetic. Environmental factors are modifiable; therefore, changes in these factors may
result in positive changes in nutritional quality, hence reducing related health risks. The
same factors can also become forces against positive change. For example, if nutrition
intervention incorporates the cultural food practices of a low-income Hispanic group,
there will be a positive change in their dietary intake and habits, but if cultural foods and

beliefs are overlooked, there may be no impact on Hispanic families’ food practices.

62

Social factors have a great influence on the nutritional intake of household
members. Nutrition decision-making, family organization, parenting, and lifestyle are
some of the social effects on the process of change. It is clear that household income
affects nutritional quality of a household, and program budget financial allocation also
determines the number of participants in the program and intervention strategy.
Environmental factors can also be barriers to positive change in nutritional intake and
healthy behaviors. For positive change to be achieved and sustained, the barriers to
change need to be minimized, if not eliminated.

Nutritional health inadequacy is a complex problem that cannot be solved by one
discipline in isolation; it requires a holistic, interdisciplinary approach on the part of
public health care, nutritionists, social services, researchers, and policy makers (Schensul.
1995).

Nutritional inadequacy, excess fat intake, and poor dietary habits are likely to be a
whole family’s nutritional problems; nutrition interventions that target a family as a unit
to increase nutrient intake may lead to a reduced prevalence of nutrition deficiencies and
health risks in low-income households. Caregivers are key players in nutritional changes
for children and other household members. The positive relationship between the
children’s and their female caregivers’ nutrient status is an indication that female
caregivers may influence children’s nutrient intake and dietary habits. This may have a
positive impact on the nutrition program interventions. More research is needed to

determine the parents’ or caregivers’ influence on the family members’ nutritional status.

63

 

APPENDICES

64

Appendix A

Working definitions of terms

Nutrition Assessment —A measure of indictors of dietary status and nutrition-related
health status of individuals or population to identify possible occurrence, and nature of
the deficiencies and nutrition-related diseases. The methods used in nutrition assessment
include dietary, biochemical, clinical, and anthropometric methods. NHANES HI survey
used these four methods of assessments

Dietary measurement —A measure of nutrients in a diet that is consumed by children and

 

their meal planners of income households. The foods consumed are classified into
specific food groups, and a computer software program analyzes nutrient intake of each
food.

CSFII / DHKS. Continuous Survey of Food Intake of Individuals (CSFII) and Dietary
Health and Knowledge Survey (DHKS) of non-institutionalized persons of was
established with an intention of providing dietary information of the US population, and
eating patterns of certain groups that could be at nutritional risk.

National Health And Nutrition Examination (NHANES) III- Along with dietary
assessment, NHANES III conducts biochemical, clinical, and athropometric
measurements to assess the populations nutritional status. One day’s 24-hour food recall
was used to obtain dietary information.

The Special Supplemental Food Program for Women Infant and Children (WIC). One of
the federal funded nutrition programs that were established in 1972 as result of stunted

growth and anemia occurrences among low-income families that were reflected in the

65

national nutrition survey. The task of WIC is to improve the nutritional status of women
and children of households with income level below 130% of the federal poverty
guidelines. The end-results of nutritional improvement are a reduction of low birth
weights and mortality rates in this population. Besides nutrition education, WIC offers
supplemental food package that meet certain nutritional and needs along with food
vouchers for obtaining more specific food stuff to the participants to improve food
availability in the household (Http/www.nawdconference.com, 10/09/1997).

Expanded Food and Nutrition Program (EFNEP). An education program administered by
the Cooperative State Research and Education and Extension Services. The program
intended to improve dietary adequacy by improving nutritional knowledge of the
population at risk. Homemakers and children are the target groups for EFNEP program.
Unlike other nutrition programs for low-income population, EFNEP does not give food
supplements, vouchers, or foods stamps to the participants; the program offers nutrition
education on proper utilization of food resources for optimum nutrition (USDA 1994).
Recommended Dietary Allowance (RDA)- A dietary standard that is used to evaluate the
health standards of an individual. It is the level of nutrient intake that is used to meet the
needs of known nutrient needs for a health person. RDA’s are very vital in identifying a
group of people that are at a nutrition-related health risk.

Mobile Examination Center (MEC): In NHANIES III survey, examination and interviews
were conducted in a specially equipped and designed mobile examination center (MEC)
that traveled to survey locations throughout the country. MEC consisted of a laboratory,
examination rooms for physical, and dental and x-rays a computer room and other

interview rooms.

66

A 24-hour dietary recalls. Each respondent was asked to remember and report all the food
and beverage consumed in the proceeding 24 hours or in a day. This was done through
interviews conducted by well-trained persons. The interviews were, conducted at the
mobile examination centers (MEC), or at households for the participants who could not
get to the MEC. The interviewers assisted the participants to remember the foods
consumed by asking questions on their dietary intake.

Food Frequengy Questionnaire (FFQ): The FFQ, a checklist of foods that assess the
energy and nutrient intake to determine the frequency of consumption of foods of specific
nutrient interest. FF Q was collected during the household interviews; information of
these foods can be linked to with reported health conditions.

Age of the sample group. The selected sample group for study include of women of ages

 

15-49 and children ages 2-9 years low income same household. The women in the study
include women of child-bearing age that assume the responsibility of providing care and
prepare food for children and other family members.

Income level: The federal poverty guideline is 130% below the poverty level Low this

 

level the income of the women is inadequate to provide for food and other social needs
for themselves and the family members. This group has been identified as most at
nutrition risk. Individuals who quality to enroll in the WIC program have an income
level of or below 185% poverty index. Federal government funded nutrition programs
(WIC, EFNEP NSLP, SBP, and Head Start) for low-income population improves
nutritional quality of this population by providing food vouchers or food stamps, and

nutrition knowledge.

67

Appendix B

Excluded from the study. Of 29,105 people who provided complete and

reliable 24-hour dietary recall information, the following groups were excluded

from the study:

2,755 children less that two years old

2,313 children ages 10-14 years

806 girls ages 15-19 years old that did not have at least one live birth
69 pregnant and/or lactating girls age 15-19 years old

367 pregnant and/or lactating women ages 20-49 years old

males ages 15-49, and

adults > 49 years of age.

Included in the study. The study sample included

6,167 children ages 2-9 years
126 teenage mothers ages 15-19 years, and

4,575 women ages 20-49 years old.

Each child selected had at least one female caregiver from the same

household. A total of 3,74 children were left out because there were no female

caregivers from the child’s household in the sample.

68

Appendix C

Criteria used to select female caregiver in households with more that one

women in the sample

1. Select all female age 20-49 years old and girls age 15-19 years old with at
least one live birth.

2. Select a woman who is the possible mother of the child included in the study
(using the child’s age and the mother’s age, and age at first and live birth).

3. If more than one woman (who may or may not be same age) is the possible
mother of the same child(ren) in the sample, select the younger woman.

4. In cases were two or more women are possible mothers of different children
in a household, match the child(ren) with the possible mother breaking the
household into multi-family units.

5. If none of the women in the sample is the possible mother of the child(ren) in

the sample, select the oldest woman with at least one live birth.

Appendix D

Table 2. Children’s daily adequacy of total energy, percent energy from total fat,
and saturated fat by the demographic characteristics

 

Energy (%RDA) % energy from

 

 

total fat saturated fat
<70%
RDA 33 0% fat 31 0%

 

Age (y)

69

 

All 97.2 i 35.41 21.0 33.8 37.5 29.0 12.4 :1: 3.7 24.0
2 - 4 100.3 :E 36.4 19.0 33.7 i 7.7 28.0 12.6 :1: 3.7 24.0
5 - 9 93.5 :1: 33.9 23.0 33.8 i 7.5 29.0 12.4 1: 3.6 25.0
p - 0.00 0.84 0.66
Gender

Boys 101.7 3. 36.6 18.0 33.6 i 7.5 29.0 12.5 :1: 3.6 25.0
Girls 92.5 i 33.5 24.0 34.1 :h 7.5 28.0 12.5 :t 3.6 24.0
p 0.00 0.65 0.94
Race-Ethnicity

White 99.2 a: 34.2 18.0 33.3 i 7.4 32.0 12.4 :1: 3.5 28.0
Black 97.1 :1: 35.6 21.0 34.4 2 7.5 26.0 12.3 3: 3.6 25.0
Mexican A 95.9 :t 36.3 23.0 33.8 e 7.6 28.0 12.8 i 3.7 21.0
Others5 96.1 i 32.9 21.0 31.4 :t 7.3 39.0 12.4 :1: 4.0 28.0
p 0.250 0.050 0.08
wrc‘

Yes 102.4 3; 36.4 15.0 34.6 :1: 8.3 25.0 13.1 3; 3.9 20.0
No 96.4 3: 34.8 25.0 34.3 :1: 6.7 25.0 12.3 :1: 3.2 18.0
p 0.1 0.93 0.66
Family Size

2 103.6 :1: 38.3 15.0 34.9 3 7.5 25.0 12.7 a: 3.7 22.0
3 94.0 :1: 33.0 22.0 34.1 :h 7.4 27.0 12.6 3: 3.8 25.0
4 98.4 :t 35.5 20.0 33.2 a: 7.9 31.0 12.1 a 3.7 28.0
5+ 96.8 2 35.8 21.0 34.0 :1: 7.4 28.0 12.7 :t 3.6 22.0
p 0.48 0.37 0.19
’Mean : S.D.

2Recommended Dietary Allowance

4 Special Supplemental nutrition Programs for Women Infants and Children

5 Hispanics and non Hispanics that are not white, black or Mexican Americans

p value by X2 test

70

Appendix E

Table 3. Children's daily adequacy of carbohydrates, dietary fiber, and
calcium by their demographic characteristics

 

 

 

 

 

 

 

Fiber Calcium <70%
Carbohydrates <recomm
ended

Age (y) 355%
All 53.5 :1: 9.3 43.0 11.1 :1: 6.3 42.0 101.1 d: 57.2 27.0
2 - 4 53.6 :1: 9.5 42.0 10.3 i 9.0 35.0 94.2 :1: 55.3 22.0
5 - 9 53.3 :1: 9.2 43.0 12.1 i 6.8 48.0 109.0 i 58.4 33.0
p 0.79 0.00 0.00
Gender
Boys 53.6 i 9.4 42.0 11.6 i 6.6 39.0 107.3 :t 59.9 25.0
Girls 53.3 :t 9.3 43.0 10.6 i 6.0 45.0 94.8 :1: 53.6 30.0
p 0.69 0.02 0.01
Race-Ethnicity
White 54.7 d: 9.2 50.0 10.8 i 6.0 43.0 110.8 :1: 60.7 22.0
Black 53.1 i 9.2 41.0 10.6 :l: 5.5 45.0 89.6 :1: 51.2 35.0
Mexican A 52.9 :1: 9.5 39.0 11.9 i 7.4 38.0 105.5 :1: 58.7 24.0
Others5 54.3 3: 9.0 45.0 10.7 :1: 5.6 37.0 109.1 :t 58.8 23.0
p 0.01 0.06 0.00
wrc‘
Yes 52.6 i 9.7 33.0 10.4 :1: 5.5 28.0 96.9 :E 56.1 21.0
No 52.2 i 10 42.0 10.5 :1: 5.9 34.0 79.4 i 45.1 32.0
p 0.16 0.35 0.08
Family Size
2 52.4 i 9.1 37.0 11.6 i 5.9 43.0 106.2 i 58.0 30.0
3 53.3i9.4 43.0 10.4 i 5.8 49.0 99.4 i 62.4 28.0
4 54.3de9.6 45.0 11.4 i 6.5 41.0 102.7 i 57.3 28.0
5+ 53.2 i 9.1 42.0 11.2 i 6.5 40.0 100.2 i 54.8 27.0
p 0.44 0.03 0.89
IMean I S.D.

2Recommended Dietary Allowance

4 Special Supplemental Nutrition Program for Women Infants and Children

5 Hispanics and non Hispanics that are not white, black or Mexican Americans

71

Appendix F

Table 4 Children's daily adequacy of micronutrients by their demographic

 

 

Iron Vitamin A Vitamin C

<70% <70% <70%

RDA RDA RDA
Age (3')
All 117.5 d: 67.3 22.0 151.2 i 120.5 26.0 231.7 :1: 185.5 16.0
2 - 4 109.3 i 64.1 28.0 163.1 :t 137.1 23.0 230.5 :1: 193.0 18.0
5 - 9 127.5 d: 69.6 15.0 137.6 :1: 11.4 29.0 233.2 :1: 176.6 15.0
p 0.00 0.04 0.051
Gender
Boys 126.9 i 74.7 18.0 163.9 d: 95.4 25.0 239.4 :E 198.4 16.0
Girls 108.1 d: 57.3 26.0 138.3 i124.3 27.0 224.0 i 171.2 17.0
p 0.00 0.18 0.7
Race-Ethnicity
White 122.1 i 62.9 20.0 153.7 21% 118.8 20.0 208.0 i 163.6 17.0
Black 114.6 i 74.1 19.0 140.9 i 111.8 31.0 240.7 :t 179.7 16.0
Mexican A 114.5 i 74.1 27.0 160.5 :1: 127.8 25.0 238.7 i 206.2 17.0
Otherss 10973490 23.0 149.5 3: 103.8 27.0 231.1 i 160.2 18.0
p 0.00 0.00 0.88
WIC4
All 113.0 :t 65.1 28.0 158.6 :1: 128.7 26.0 247.0 :t 229.9 19.0
Yes 119.3 i 70.5 25.0 169.3 i 135.2 23.0 252.3 :1: 114.6 15.0
No 98.9 :1: 48.6 36.0 134.7 i 110.2 32.0 235.0 :1: 219.9 27.0
p 0.08 0.18 0.02
Family Size
2 132.9 :5 78.5 12.0 161.1 i 107.7 27.0 287.8 i 195.9 15.0
3 110.5 i 57.4 25.0 142.0 i 126.1 25.0 230.4 3: 174.9 16.0
4 122.7 i 73.1 20.0 152.7 i 122.6 25.0 235.8 $189.0 17.0
5+ 115.4 i 65.4 24.0 152.3 :t 134.2 27.0 223.1 3: 185.3 16.0
p 0.01 0.92 0.96
'Mean i S.D.

2Recommended Dietary Allowance

" Special Supplemental Nutrition Program for Women Infants and Children (WIC)

5 Hispanics and non Hispanics that are not white, black or Mexican Americans

p value by X2 test

72

Appendix G

Table 5. Female caregivers' dietary adequacy of energy, total fat, and
Saturated fat, by demographic subgroups.

 

 

 

 

Energy (%) _ % Energy from
total fat saturated fat
<70% 330% 310%
RDA‘ Sat. Fat
Age 0)
All 85.9 i 37.42 36.0 34.1 i 9.3 32.0 11.3 :t 3.9 38
15 - 19 95.5 i 48.0 28.0 34.3 i 10. 28.0 11.5 i 3.8 24
20 - 29 88.7 i 36.3 33.0 34.2 :1: 9.1 32.0 11.4 :1: 3.9 36
30 - 39 84.1 :t 36.8 37.0 34.0 i 9.4 31.0 11.2 i 3.9 39
40 - 49 83.2 i 40.6 39.0 33.8 d: 9.6 32.0 11.2 :t 4.1 38
p 0.29 0.90 0.32
Race-Ethnicity
White 95.5 i 48.0 33.0 33.9 i 7.4 32.0 11.7 i 4.0 33
Black 88.7 d: 36.3 36.0 35.3 i 9.3 26.0 11.4 :t 3.8 37
Mexican American 84.1 i 36.8 38.0 33.3 :t 9.1 34.0 11.1 i 3.9 40
Others’ 83.2 4 40.6 38.0 30.4 :1: 9.4 53.0 9.8 3: 3.5 52
p 0.45 0.00 0.02
WIC"
All 91.6 3: 35.4 30.0 34.5 i: 9.0 31.0 11.8 :1: 3.3 37
Yes 96.4 i: 36.3 25.0 35.7 i 8.3 25.0 12.5 i 4.2 30
No 86.7 i 34.4 34.0 33.3 i 9.7 38.0 11.1 d: 4.3 42
p 0.19 0.11 0.17
Family Size
2 80.8 :t 33.1 39.0 34.0 :1: 9.5 31.0 11.2 i 3.8 40
3 86.2 d: 35.4 34.0 34.8 d: 8.9 29.0 11.4 at 3.8 36
4 85.1 i 39.4 39.0 34.1 i 9.7 32.0 11.1 3: 4.0 40
5+ 86.8 i 37.4 34.0 33.8 i 9.2 32.0 11.4 :1: 4.0 37.0
p 0.20 0.79 0.67

 

' Recommended Dietary Allowance

2 Standard deviation

3 Hispanics and non Hispanics that are not white, black or Mexican Americans

‘ Special Supplemental Nutrition Program for Women, Infants, and Children (WIC)

p value by X2 test

73

Appendix H

Table 6. Female caregivers' dietary adequacy carbohydrates fiber and
calcium by their demographic subgroups.

 

 

 

 

 

carbohydrates Fiber Calcium
< <70%
fl Reco

cho % RDAl RDA
Age 6)
All 50.721: 11.12 34 14.3 i 9.7 87 80.5 d: 55.1 62
15 - 19 50.7 i 9.7 28 11.4 :t 8.7 92 73.4 :1: 48.5 68
20 - 29 51.0 :1: 10.9 36 14.1 i 9.7 87 62.0 d: 62.0 62
30 - 39 50.4 :t 11.1 33 14.3 :1: 9.4 87 85.2 i 58.4 63
40 - 49 50.6 :1: 12.1 31 15.2 d: 10.3 86 86.9 i 57.9 61
p 0.52 0.79 0.83
Race-Ethnicity
White 50.8 :1: 11.8 34 13.7 i 8.4 90 92.4 :1: 58.9 54
Black 49.3 :t 11.1 30 11.9 i 8.4 94 67.5 :1: 49.7 44
Mexican American 51.8 i 10.5 37 17.3 i 11. 78 87.0 d: 55.8 55
Others’ 52.4 i 14.1 36 13.8 i 8.7 88 71.2 i 45.6 67
p 0.05 0.00 0.00
WIC"
All 51.0 :1: 10.3 65 14.7 :t 10.5 88 76.4 :t 54.5 60
Yes 50.1:t 9.4 68 15.9 i 12.4 88 85.7 i 57.4 49
No 51.8 21:11.1 63 13.7 3: 8.4 89 68.0 i 50.7 69
p 0.53 0.83 0.02
Family Size
2 50.9 :l: 12.7 64 11.6 :t 7.3 93 66.6 :E 50.9 72
3 49.0 :t 10.8 71 13.5 :t 8.3 89 76.1 i 46.5 65
4 50.5 :t 11.6 67 13.9 :t 9.3 90 80.9 i 57.5 61
5+ 51.4 :1: 10.8 65.0 15.1 :1: 10.5 84 83.8 :t 56.9 61
p 0.22 0.00 0.13

 

l1989 Recommended Dietary Allowance

2 Standard deviation

3 Hispanics and non Hispanics that are not white, black or Mexican Americans

4 Special Supplemental Food and Nutrition Program for Women, Infants,

and Children (WIC)

p value is by X2 test

74

Appendix I

Table 7. Female caregivers' dietary adequacy of micronutrients by
sociodemographic characteristics.

Iron <70% VitaminA <70% VitaminC <70%
RDA

% RDA‘ RDA % RDA RDA % RDA Vit C

 

Age (Y)

All 82.6 3 50.62 48 98.0 3 52.3 57 162.9 3 62.4 35
15 - 19 81.2 3 46.7 40 96.9 3 59.2 48 155.1 3 72.8 28
20 - 29 83.8 3 51.2 48 87.2 3 46.9 60 165.4 3 90.8 33
30 - 39 81.8 3 51.2 48 107.7 3 50.7 57 162.3 3 99.7 37
40 - 49 82.4 3 47.1 50 95.4 3 30.8 56 158.8 3 115.8 36
p 0.83 0.50 0.43

Race-Ethnicity

White 86.4 3 49.7 45 102.1 3 79.8 51 137.4 3 114.3 39
Black 77.8 3 48.6 54 89.6 3 64.2 63 154.0 3 116.7 38
Mexican Americans 84.3 3 52.3 45 102.2 3 62.0 57 185.3 3 131.1 30
Others’ 90.2 3 56.9 42 112.1 3 86.3 59 210.4 3 111.7 33
p 0.00 0.00 0.01
WIC"

All 91.2 3 58.3 42 97.2 3 40.6 62 195.3 3 147.3 27
Yes 97.4 3 58.5 32 121.6 3 97.8 54 214.9 3 101.8 26
No 85.6 3 58.0 51 75.13 57.2 71 177.7 3131.2 28
p 0.02 0.04 0.83
Family Size

2 76.6 3 52.3 59 71.2 3 83.7 67 175.0 3116.7 37
3 84.9 3 50.9 48 101.2 3 89.0 55 154.6 3 112.2 34
4 82.7 3 52.8 50 89.9 3 55.8 56 157.0 3 145.6 36
5+ 82.4 3 48.9 46.0 104.9 379.7 59.0 168.7 3138.6 35.0
p 0.07 0.15 0.94

 

I1989 Recommended Dietary Allowance
2Standard deviation
3 Hispanics and non Hispanics that are not white, black or Mexican Americans

4 Special Supplemental Nutrition Program for Women, Infants, and Children (WIC)
p value by X2 test

75

Appendix .1

Table 12. Specificity, sensitivity, negative predictive value (PV-) and positive predictive
values (PV+) of correlation model for breakfast consumption.

Correlation Model

 

 

 

Female
caregiver
Breakfast consumer
No Yes
Children
Breakfast
Consumer
No 57 5 1
Yes 237 645
Total 294 696

Sensitivity a (57/57+237) *100 = 19.3%
Specificity b (45/645+51) *100 = 92.6%
PV- ° (645/645+237) *100 = 73%
PV+ d (57/57+237) *100 = 19%

‘ Sensitivity is the fraction of children non-breakfast consumers that the correlation model predicts
correctly.

b Specificity is a fraction of children breakfast consumers that the correlation model predicts correctly
° PV- is the fraction of negative results according to the correlation model that are truly negative

d PV+ is the fraction of positive results according to the correlation model that are truly positive

76

Appendix K

Table 14. Iron status of children and female caregivers

 

 

Hemoglobin

 

 

Transferrin Serum Protoporphyrin
Saturation ferritn Erythrocyte
Age (y) cutoff cutto ff cutoff
Children
2- 4 <1 0 <1 0 >80
5 - 9 <14 <12 >70

Female caregivers

15—19 <15 <12 >70
20-29 <15 <12 >70
30-39 <15 <12 >70
40-49 <15 <12 >70

77

cutoff

 

<11
<11

<12
<12
<12
<12

Appendix L

Table 15. Distribution of children's triceps and weight for height 5 or >85%tilesl by
age, gender, race-ethnicity, WIC 2 Participation, and family size

Tricep skinfold percentiles

 

 

n _ 585%tile >85%tile p
0.000
All 990 81.0 19.0
2 - 4 y 562 84.2 15.8
5 - 9 y 428 77.3 22.7
Gender 0.000
All 990 81.0 19.0
Boys 508 84.7 15.3
Girls 482 77.2 22.8
Race-Ethnicity 0.314
All 990 81.0 19.0
White 134 82.2 17.8
Black 410 82.4 17.6
Mexican Americans 403 79.2 20.8
Others 43 76.1 23.9
WIC 0.035
All 667 82.6 17.4
Yes 199 79.1 20.9
No 468 90.4 9.6
Family Size 0.004
All 990 81.0 19.0
2 27 73.4 26.6
3 138 75.5 24.5
4 236 83.0 24.5
5+ 559 82.9 17.0

 

’ >85%tile wt-for-ht — overweight‘ Special Supplemental Nutrition
Program for Women, Infants, and Children (WIC)
p value by X2 test

78

Appendix M

Table 16. Distribution of children's weight-for-height 5 or >85%tilel by age,
Gender race-ethnicity, WIC2 Participation, and family size

Wei ght- for-height percentiles

 

 

n 585%tile >85%tile p
Children 0.00
All 990 75.6 24.4
2 - 4 y 562 78.8 21.2
5 - 9 y 428 72.0 28.0
Gender 0.37
All 990 75.6 24.4
Boys 508 76.5 23.5
Girls 482 74.6 25.4
Race-Ethnicity 0.00
White 134 77.8 22.2
Black 410 79.6 20.4
Mexican Americans 403 69.7 30.3
Others 43 76.8 23.2
WIC 0.06
Yes 199 78.9 21.1
No 468 88.9 11.1
Family Size . 0.15
All 990 75.6 24.4
2 27 68.1 31.9
3 138 71.8 28.2
4 236 78.3 21.7
5+ 559 76.3 23.7

 

' >85%tile wt-for-ht - overweight
2 Special Supplemental Nutrition Program for Women, Infants, and Children (WIC)
p value by X2 test

79

Appendix N

Table 17. Female caregivers mean 1 SD1 BMIz’ and BMI classification by their age
group, race-ethnicity, participation in WIC3 and family size

 

 

BMI
n Mean : SD 524.9 24.9 - 29.9 330 p
age
All 990 27.71268 43.2 27.6 28.6 0.000
15 - 19 y 22 24.8363 64 20 16
20 - 29 y 451 26.2i6.2 50.2 26.5 23.3
30 39 y 401 27.7:t6.9 42.1 26.5 31.4
40 - 49 y 116 29.3i7.2 29.4 35.1 35.5
Race-Ethnicity 0.000
White 144 25.3363 61.6 18.9 19.6
Black 411 28.317] 39.1 28.1 32.9
Mexican Amer 397 27.7i5.8 35.5 33.6 30.6
Other4 38 26136.0 51.1 24.2 24.2
WIC 0.012
All 368 27.0:t6.2 39.4 32.1 28.5
Yes 116 26.7:t4.3 32.3 44.6 23.1
No 152 27337.5 45.8 20.8 33.3
Family Size 0.000
2 65 26.8:t6.9 54.3 21.3 24.5
3 231 26937.1 50.6 22.1 27.3
4 239 26836.8 47.5 26.5 26.1
5+ 302 27836.6 37.5 31.3 31.2

fir: -3 ‘

 

IStandard Deviation
2 Body Mass Index

3 The Special Supplemental Food Program for women infant and children
(W1C)

4All Hispanics and non Hispanics that are not white, black or Mexican

Americans

80

Appendix 0

Table 20. Female caregivers skinfold triceps percentile by their age group, race-
ethnicity, participation in WIC3 and family size

 

 

Triceps Skinfolds
n <85tile >85%tile p
Age
All 990 74.1 25.9 0.48
15 - 19 y 22 76 24
20 - 29 y 451 73.9 26.1
30 39 y 401 72.9 27.1
40-49y 116 78.1 21.9
Race-Ethnicity 0.000
White 144 78.8 21.2
Black 41 1 68.4 31.6
Mexican Amer 397 75.5 24.5
Other4 38 84.8 15.2
wrc3 0.861
All 368 70.1 29.9
Yes 116 70.8 29.2
No 152 69.4 30.6
Family Size 0.484
2 65 70.2 29.8
3 231 73.9 26.1
4 239 76.4 23.6
5+5 302 73.1 26.9

 

lStandard Deviation

2 Body Mass Index

3 The Special Supplemental Food Program for women infant and children

(WIC)

4All Hispanics and non Hispanics that are not white, black or Mexican

Americans

81

Appendix P

Table 21. Female caregiver-child correlation for each nutrient,
Breakfast consumption, iron and weight status

 

 

Nutrients

Energy .23*
Total fat .31 *
Saturated fat .23"‘
Carbohydrates .29*
Calcium .20*
Iron .12*
Vitamin A 040*
Vitamin C .23*

Iron variables

Transiferrin saturation .13*
Serum ferritin .10*
Protoporphyrin .23*
Hemoglobin .33*

Weight status variables

 

Triceps skinfold 0.33*
BMI 0.21 *
* p<0.01

82

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